remove requests

.github/CODEOWNERS

@@ -1,2 +1,2 @@
-/.github/   @baskaryan @ccurme
-/libs/packages.yml   @ccurme
+/.github/   @efriis @baskaryan @ccurme
+/libs/packages.yml   @efriis

.github/PULL_REQUEST_TEMPLATE.md

@@ -26,4 +26,4 @@ Additional guidelines:
 - Changes should be backwards compatible.
 - If you are adding something to community, do not re-import it in langchain.
 
-If no one reviews your PR within a few days, please @-mention one of baskaryan, eyurtsev, ccurme, vbarda, hwchase17.
+If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.

cookbook/elasticsearch_db_qa.ipynb

@@ -115,7 +115,7 @@
     "\n",
     "PROMPT_TEMPLATE = \"\"\"Given an input question, create a syntactically correct Elasticsearch query to run. Unless the user specifies in their question a specific number of examples they wish to obtain, always limit your query to at most {top_k} results. You can order the results by a relevant column to return the most interesting examples in the database.\n",
     "\n",
-    "Unless told to do not query for all the columns from a specific index, only ask for a few relevant columns given the question.\n",
+    "Unless told to do not query for all the columns from a specific index, only ask for a the few relevant columns given the question.\n",
     "\n",
     "Pay attention to use only the column names that you can see in the mapping description. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which index. Return the query as valid json.\n",
     "\n",

cookbook/sql_db_qa.mdx

@@ -233,7 +233,7 @@ Question: {input}"""
 
 _DEFAULT_TEMPLATE = """Given an input question, first create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer. Unless the user specifies in his question a specific number of examples he wishes to obtain, always limit your query to at most {top_k} results. You can order the results by a relevant column to return the most interesting examples in the database.
 
-Never query for all the columns from a specific table, only ask for a few relevant columns given the question.
+Never query for all the columns from a specific table, only ask for a the few relevant columns given the question.
 
 Pay attention to use only the column names that you can see in the schema description. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
 

docs/api_reference/_static/css/custom.css

@@ -328,7 +328,7 @@ html[data-theme=dark] .MathJax_SVG * {
 }
 
 .bd-sidebar-primary {
-    width: max-content;  /* Adjust this value to your preference */
+    width: 22%;  /* Adjust this value to your preference */
     line-height: 1.4;
 }
 

docs/cassettes/configure_093d1c7d-1a64-4e6a-849f-075526b9b3ca.msgpack.zlib

@@ -1 +0,0 @@
-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

docs/cassettes/configure_277e3232-9b77-4828-8082-b62f4d97127f.msgpack.zlib

@@ -1 +0,0 @@
-eNqdVXtwVNUZ3220OjKDBRGwHe12BxBr7u597TOzbZNNWJIQNskueVSZ9Oy5Z3dvcu89l/vY7C4CFTs6KOJcH6NC21ESdp1tComkKAgqdup0QFQmOhpbqrYVaXV0aJyxiiU9u9mUZOCv3j9277nf6/d9v+/7zvZiBmm6iBX7iKgYSAPQIAfd2l7U0CYT6cYvCjIy0lgYbo/G4kOmJk7+MG0Yqh50u4EqurCKFCC6IJbdGcYN08Bwk3dVQhU3wwks5CZTm50y0nWQQrozeMdmJ8QkkmI4g861SJKws9apYQmRo6kjzbllY61TxgKSyIeUalA8pmRREYmWbmgIyM5gEkg6qnUaSFYJYMPUiC3torcU0wgIJJuHhtNYN6z98/EdABAi4g8pEAuikrJ+m8qLaq1DQEkJGKhEUCmokr1VGkBIpYAkZlBhxsoaBaoqiRCU5e5+HSsj1SwoI6eiy8Wlci4USVkxrPEoAVHf7G7PkUIqDsblZVzMaJbSDSAqEqkMJQGCp6BW5C/MFagADhAnVJUkqzBjvH+uDtatfW0ARmPzXAINpq19QJO9/MG53zVTMUQZWcVw++XhqsJL4TgXw7r8Y/Mc6zkFWvsqJDw3zxgZWo6CmPiwnqb3z9ZHQkrKSFtDDM09oyFdJW2B7ikQM8PUtw8TLtBrfyxW+2NvtHWWxL/Ylg03El6sY/G0WeugvY42oDlYmvU4GG+Q44I854i0xUfC1TDxK9IwFteAoicJFU2ztBdh2lQGkFAKX5HwY2XCSTZl+KQtKZRVsY6oKiprpIfqnBkMqrnx4Ex3UVhLAUXMV8JaxyrMD+azgwI0BSGdGZTpQJ7nxAQyYXK8aqJquByGAKJk3Rpiae/+qmS29iWSK00xNEUzR7IU6XMkibJI6ln5rU6nbg17aJp+/nIFAw8gMsdFnq48L87V0JBMSCvHvuSGDwQCR6+sNOuKIyoB/3w0hFE0Fw3DyvrzlytUXeyl9ZHsrDYlCtbkCnLoYz0AIS/rpZlkgKYTwMvxnM+T8EGO9UEv7z1MJl+ExEuZTBVrBqUjSFaRkbMma2WQLc9ZiGM8nJdkWucQFSiZAoqZiUZczkGvc6gakjAQDsAkBQFMI2qm/6xiY+/6+rbmcClGQIYxHhDRw+/Zl/f1wWRfQg7lUNwTiAs+RsFrNrV0xF2NmmfA71Kjme56LHd3x2TI5tRIjO1rohgfz7A+v5/lKMZFu8iUUk39PIwMCp2eVj7CmevyeqSzKSA2RrubeiMZF611NRiDjJoRcS4Qz/Zgo9/or491d3DqYKx9TS6Xp1vCrfGe5oS/q1Py+dZJ0J/IJnztZnN8fdf6dfl6r9ri6W/pEPPJNpIiMNIhd52DNKxIih6qjg1FxoYqD40vSM8OTZ1DqBQm5Jq/Iusca8lqjypSrs4RK1cYkX8go5hooNB6rKDJR0lhzIwohMxNG3LxCNfLh1k6BnSlK94Ge/yg2aer9AbIrkl1cJGGgWRLfBDPqQzrZSi6WhwvzfsrrXkJ+v+J6lAPNXcLUFF15g4rKlhXxGSyEEMamSqrBCVsCmTba6gQXkN11vda4wEGcjwDOC7hY3mB4akGskdnvf1vZwyXr4oikEjjZaB1MM2FnEGe55x1DhmE/F4yY5Wb7u5CuVGV1B/sQ99/4Fpb5anZ2Xl81wS95OjHt9/yI9/q5pOrvtg+fk18/OSOBYsbLPjSiuTNPz6ZWXqiNL3rl+Ntpat3tC7k8Crujc9X2n/W8myIPj3l+PZvJi6Uvv7Xafma9z960K9O//uFc3vOfvj0ha+/2vh7b0f9qeuXfLg3f3t69Lv3OLmJV35w/fKNU9rjy9CGG/+0Y/navbueff1eI/KPp3a2PDDy7r7eJ8++3XvmkcXnJm95caXN5p7wneUXbxsLCXsWsE99eTR86KWFdjoSdO7cfOCuD1aNnmq4jrWfWvKfn/904nv+N6Pf+fPLtz5xtTq86FvNW78ZXRqUIm/ALNe/5dXoOyt2Bz955nzq4v3PnVj9/jsLD996w/Q/a3q9Y8WrPrjwVvbobcdHho7fG3zzht3pnlOK1Dv1ykcfo9Gf3P3JjVsXnXni7cU13e8dWPrqVctCJ5oOS48/1Hn6/rVdj/Xd99WeL++848nPtn26rOHacTuSb25ZqSxww4V/W3Rx4NMjf72Nnjr368deDq42zt+04tBdb02J9LYv7Pcd2VAIp361+/Oh35mZbqX14tY9Z8b+/ug3dptterrG9hlmzlM1Ntt/AUZXjK8=

docs/cassettes/configure_42647fb7.msgpack.zlib

@@ -1 +1 @@
-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
+eNptU39QFGUYPhQbUhmIGZv6R3ZupBqHvdtjr+OApomOEEQ6hBsGRhM/dj9ul9vbXXe/xQO0ApnUKZlZSy2omYjjzllJpSgkMSMpayAHGkeHqRwrM5pKBRRicqDvTjAZ3b++fX887/s+z/s2hmugovKSGNPJiwgqgEH4R9UbwwrcpkEVNYX8EHESGyxyl3jaNYUfTeEQktVMqxXIvAWIiFMkmWcsjOS31tisfqiqwAvVYKXE1o4eqDf7QaACST4oquZMwkal2VMJ80IQtmyqNyuSAPHLrKlQMWMvI+FORBQxeaAgEH5IAKIaQxCgUtIQUQmBopp3vhQBklgoRAIZAWgsJGmSA7xPI9NwHYqm0iNwCPplPBjSlEgVykLtDHMQsHjsS6bEICepSO+6b5RjgGGgjEgoMhLLi179Q28dL6cSLKwSAIIG7lGEUa50wwehTAKBr4GhO1n6cSDLAs+AiN9arUpi5/xMJKqV4f1uIzI6iRkRkd6TvdCHtagWMy/ilmmHhToeIFUEeFHA3JECwC2F5Kj/5L0OGTA+jEPOq6qH7iQfvTdGUvWOQsC4SxZBAoXh9A6g+B32j++1K5qIeD/Uw66i+8vNO/8vR1tsNkt61yJgtVZk9I4qIKiw6y7Jd1MMrBVNUg6SsvUsgoZIqSUZCVfQ26ijCwQKUPQiTm+32TMOK1CV8bLCXSGchjS1MYjFgkPfhOf36wN3wYLUbwRzsGz6KQ+npRK2dMLNICKyJITNnkmnZdopYl2hp9M1X8TzQJW6PAoQ1Sqs1AsLWxFmOE30QdZwPXAfjPkjInlW78PvCspGF+Ruc2nFG9VAYVFengLp9EKQzX8SIBlB0lgS4QuEZHTYANJHiUo7nWG3MU4nTdMOSDkhpKg0J2ScjN3BVjrp9hoe6IbNYiO8kuQV4DFXLukCDAfJkiglejin/MXswnxXZxlZLFVKSCU9wKsHRUmEoRKoYBV0I1oa77UCQzi9OLtc73aydqqqislgYYbdARhAPo/XZYGeu+MHI0cRvfQGLIGCTV/FbE9+Pc4U/ZZu2Fjh++G5lXNrW7ZM/NLU/XDs7eKxM3knv9/t79gFm1rdzdKzBefyD51fMXPtzLWH6pNuz64fa+xn9r63emqw9eKtyetTJ2Zvjxe03hz/Z+I7/+eXXvlyiX+M9+hGVuKjb69pfrUkvro5fsVfAyUDSUfGPgrPVF86MXx15u+JmlObyfSyrSnCwGu/TQ+ezmnvGcnal9TzFhe6fPnJ3tjTwZTDKf1E74/jzRWtMX03hp7Y8vMzhscovb717LSntzP2wrBpX9ZI/fpCNjl3uvQcvcz37k/9S8uWX+mPXftHnJLw+9Z453Dir6adVXE79geW7whIm74orTMm8xL2tx0cWt3YQO+5cv79FSNnYzYfevoGiHGzw490p3rjbnEttXvaOro+fXy7mnqhqGX51QtF617+rK7hYvIyI/+0+4rnsYI1U/WDe8etbWhoYBX4NuPrJZM335lobPhXqH/zYFlXX/mqp0ZndzuO/HkrATM8N7fURLZuWDkdYzL9Byv+bUg=

docs/cassettes/configure_48b45337.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/configure_4f83245c.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/configure_5cf53202.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/configure_61a67769-4a15-49e2-a945-1f4e7ef19d8c.msgpack.zlib

@@ -1 +0,0 @@
-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

docs/cassettes/configure_71248a9f.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/configure_7ba735f4.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/configure_927297a1.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/configure_97538c23.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/configure_9a9ea077.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/configure_9f6a7c6c.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/configure_c09fac15.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/configure_e4ee9fbc.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/configure_e75ae678.msgpack.zlib

@@ -1 +1 @@
-eNptVXtsU2UUL6AZQWVoFBON8VogGbjb3UfbtcUZt3Udc6zd1sKYaJqv3/3a3vW+dh/tHszgUOKDMa4CYkRA2FqzjDkdkzeKBsWIkaB/OCCQaGKEGaPxFcPLr10nW+D+cXPvPef7nd8553fO7c4kkarxsjRjkJd0pAKo4xfN7M6oqNVAmv5iWkR6XOb66gPB0B5D5ceWxHVd0TwlJUDhbbKCJMDboCyWJOkSGAd6CX5WBJSD6YvIXPvY2k6riDQNxJBm9azutEIZR5J0q8daz8MEAQgVSJwsEpIhRpBKgIicRARlLbaqsoCwl6Eh1dr1XLFVlDkk4A8xRSdZm4PUDTUiYz9NVxEQrZ4oEDRUbNWRqOBMsBWfpmxUVyaOAIfTvGCZ1xeXNd0cmk79fQAhwphIgjLHSzFzb6yDV4oJDkUFoKMBTFhCucKYAwmEFBIIfBKlJ06Zw0BRBB6CrL2kRZOlwXyCpN6uoFvNA9l8SFwNSTf3BTCJ8pqS+nZcY4mgbU7aRg+3kZoOeEnARSMFgPmklZz98FSDAmACg5D5/pnpicNDU31kzeyvAzAQnAYJVBg3+4EqOu0jU7+rhqTzIjIzlfW3hssbb4ZjbTRjc30wDVhrl6DZn2vD/mmHka62k1DGGOa7VBrKcoJH5tkZBeEwjIYjYll7tdrUFvX5pFqfEkzyKS/PNbhal6dcvoYVLdV8OKLKxoqwI+pQmkm61E4zpS4X4yBpG2XDOZOVcci0G8tTjnq6okaCTTybaOWblvsT/homVNXAQjcl1Cng6YDbHWryS1XLUJXidqtQSvoatUgDQI3VjY16yihvCKFgoqatRXY0NDHPlENXfaC2ASQVWuhYVWkv5RhtKYEpG0meK/MnaG9LKJJ0OJetiLN+LuCvavZXca1cReMzgSSyB1rDwfCqyEqmBk7h7KKdJJWn7aTsLip7DU0qRkBSTI+be2jG9Z6KNAXPEFqXxoXUDa27D6sTnTqZyQ/T7kDtTWHP7/NipZpHQ3GjmKCcRB1QCYZiHATt9LCsx+4kqutCg5X5MKHbCvODEB5ELYrFWTU5CBkYN6QE4gYqbzsCR7MjgPubpY+HlURtiqwhMs/KHFxFNk5sEbLGOzIxb6SsxoDEd+TCmkdzs5DqaEtx0OC4eDIlUu4OO8tHkAGj+/JHFFXOhsGESFHDxXExQ3nLpBoHcK4USVMkRR9qI/HsI4EXeVzP3D2/yjSzz4GLfeBWB11OILz0MvZcN6hjUz1UJGIZZ2PfhLG73e4jt3eahGKxi7vUeWi6l4amsqEZUTtwq0MeYjelDbZNepM8Z44txC9hdykHWQcCkYg9iqIMa3c5KQo5aQTcTpaNMgfxNuQhRsk2U5FVndQQxHtbbzfHikXQlt08ZSztYPExainBS1AwOBQ0Il45mwMWuKIiQQbc+zBKQgDjiJzQn5nxNvvL62oqP1pFThUSGVAm/hkZSdYkPhpNB5GKG2MOQEE2OLxCVZSu9JGN5c3mPjcNWTsdKYWcq9TF0TRZgZfTJNr/suvL7t8MEDD3JDRH4myZ1WO3s9alhAjKXE7cptyf5YV0NlcpdmJG96OvzbbkrlkbXg/Xfkbdf+LilcUVOw6D8eubjy0uerWQ8Xq9T289b7zF3/f66nc2dKVqzu19xP9bf+E/qW8uHfwn+uC9Ff273O+u+XpT08qeoZFfLl1fYfvwzROf9ZwtenIk3PvN/tR58a8HetZ9Wlz6ye+7HtKCzXcW9Uh06pN53Qlm58JLT3x1pnnWkgVP3dnMt+ruHRuHk7XsoWVn+MyzD395/NvtR6penPdh4thje+YP97sPvly4Zc6R2KLTV7/3zjZ8L81BF2p7ly/o6TzZ4ztd94v+5B1zV47GHts2tOXy5Ss/7ty8eC9be/F32LVo9M/xT2f84Sto6v38zPpfF1RcePuVy29s+s4TbC4+vWbt3PVf9o3uuTa3c1vy7nsYx+lTP7DRlyxc47/HK4pia+7Z3fT3OTi6KWrZffzkxyPb/5C+2Hroam9XoavgNWLO+FPLnvfIF38inhj++OzGx6WZwcJfg2pRffddsXnDkdGWQODa/ur3Xt3y3SLXOKfd+OnUlZ8LLJYbN2ZZNj9EJK7PtFj+A1XHTc0=
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

docs/cassettes/configure_f33f3cf2.msgpack.zlib

@@ -1 +1 @@
-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

docs/docs/contributing/how_to/documentation/setup.mdx

@@ -50,6 +50,11 @@ locally to ensure that it looks good and is free of errors.
 If you're unable to build it locally that's okay as well, as you will be able to
 see a preview of the documentation on the pull request page.
 
+From the **monorepo root**, run the following command to install the dependencies:
+
+```bash
+poetry install --with lint,docs --no-root
+````
 
 ### Building
 
@@ -153,6 +158,14 @@ the working directory to the `langchain-community` directory:
 cd [root]/libs/langchain-community
 ```
 
+Set up a virtual environment for the package if you haven't done so already.
+
+Install the dependencies for the package.
+
+```bash
+poetry install --with lint
+```
+
 Then you can run the following commands to lint and format the in-code documentation:
 
 ```bash

docs/docs/contributing/reference/faq.mdx

@@ -35,5 +35,5 @@ Please reference our [Review Process](review_process.mdx).
 
 ### I think my PR was closed in a way that didn't follow the review process. What should I do?
 
-Tag `@ccurme` in the PR comments referencing the portion of the review
+Tag `@efriis` in the PR comments referencing the portion of the review
 process that you believe was not followed. We'll take a look!

docs/docs/how_to/configure.ipynb

@@ -21,7 +21,7 @@
     ":::info Prerequisites\n",
     "\n",
     "This guide assumes familiarity with the following concepts:\n",
-    "- [The Runnable interface](/docs/concepts/runnables/)\n",
+    "- [LangChain Expression Language (LCEL)](/docs/concepts/lcel)\n",
     "- [Chaining runnables](/docs/how_to/sequence/)\n",
     "- [Binding runtime arguments](/docs/how_to/binding/)\n",
     "\n",
@@ -62,163 +62,6 @@
     "    os.environ[\"OPENAI_API_KEY\"] = getpass()"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "9d25f63f-a048-42f3-ac2f-e20ba99cff16",
-   "metadata": {},
-   "source": [
-    "### Configuring fields on a chat model\n",
-    "\n",
-    "If using [init_chat_model](/docs/how_to/chat_models_universal_init/) to create a chat model, you can specify configurable fields in the constructor:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "92ba5e49-b2b4-432b-b8bc-b03de46dc2bb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain.chat_models import init_chat_model\n",
-    "\n",
-    "llm = init_chat_model(\n",
-    "    \"openai:gpt-4o-mini\",\n",
-    "    # highlight-next-line\n",
-    "    configurable_fields=(\"temperature\",),\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "61ef4976-9943-492b-9554-0d10e3d3ba76",
-   "metadata": {},
-   "source": [
-    "You can then set the parameter at runtime using `.with_config`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "277e3232-9b77-4828-8082-b62f4d97127f",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Hello! How can I assist you today?\n"
-     ]
-    }
-   ],
-   "source": [
-    "response = llm.with_config({\"temperature\": 0}).invoke(\"Hello\")\n",
-    "print(response.content)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "44c5fe89-f0a6-4ff0-b419-b927e51cc9fa",
-   "metadata": {},
-   "source": [
-    ":::tip\n",
-    "\n",
-    "In addition to invocation parameters like temperature, configuring fields this way extends to clients and other attributes.\n",
-    "\n",
-    ":::"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "fed7e600-4d5e-4875-8d37-082ec926e66f",
-   "metadata": {},
-   "source": [
-    "#### Use with tools\n",
-    "\n",
-    "This method is applicable when [binding tools](/docs/concepts/tool_calling/) as well:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "61a67769-4a15-49e2-a945-1f4e7ef19d8c",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[{'name': 'get_weather',\n",
-       "  'args': {'location': 'San Francisco'},\n",
-       "  'id': 'call_B93EttzlGyYUhzbIIiMcl3bE',\n",
-       "  'type': 'tool_call'}]"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from langchain_core.tools import tool\n",
-    "\n",
-    "\n",
-    "@tool\n",
-    "def get_weather(location: str):\n",
-    "    \"\"\"Get the weather.\"\"\"\n",
-    "    return \"It's sunny.\"\n",
-    "\n",
-    "\n",
-    "llm_with_tools = llm.bind_tools([get_weather])\n",
-    "response = llm_with_tools.with_config({\"temperature\": 0}).invoke(\n",
-    "    \"What's the weather in SF?\"\n",
-    ")\n",
-    "response.tool_calls"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b71c7bf5-f351-4b90-ae86-1100d2dcdfaa",
-   "metadata": {},
-   "source": [
-    "In addition to `.with_config`, we can now include the parameter when passing a configuration directly. See example below, where we allow the underlying model temperature to be configurable inside of a [langgraph agent](/docs/tutorials/agents/):"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9bb36a46-7b67-4f11-b043-771f3005f493",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! pip install --upgrade langgraph"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "093d1c7d-1a64-4e6a-849f-075526b9b3ca",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langgraph.prebuilt import create_react_agent\n",
-    "\n",
-    "agent = create_react_agent(llm, [get_weather])\n",
-    "\n",
-    "response = agent.invoke(\n",
-    "    {\"messages\": \"What's the weather in Boston?\"},\n",
-    "    {\"configurable\": {\"temperature\": 0}},\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "9dc5be03-528f-4532-8cb0-1f149dddedc9",
-   "metadata": {},
-   "source": [
-    "### Configuring fields on arbitrary Runnables\n",
-    "\n",
-    "You can also use the `.configurable_fields` method on arbitrary [Runnables](/docs/concepts/runnables/), as shown below:"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -761,7 +604,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.4"
+   "version": "3.9.1"
   }
  },
  "nbformat": 4,

docs/docs/how_to/document_loader_custom.ipynb

@@ -551,7 +551,7 @@
     "\n",
     "While a parser encapsulates the logic needed to parse binary data into documents, *blob loaders* encapsulate the logic that's necessary to load blobs from a given storage location.\n",
     "\n",
-    "At the moment, `LangChain` only supports `FileSystemBlobLoader`.\n",
+    "A the moment, `LangChain` only supports `FileSystemBlobLoader`.\n",
     "\n",
     "You can use the `FileSystemBlobLoader` to load blobs and then use the parser to parse them."
    ]

docs/docs/how_to/migrate_agent.ipynb

@@ -329,7 +329,7 @@
    "id": "fc6059fd-0df7-4b6f-a84c-b5874e983638",
    "metadata": {},
    "source": [
-    "We can also pass in an arbitrary function or a runnable. This function/runnable should take in a graph state and output a list of messages.\n",
+    "We can also pass in an arbitrary function or a runnable. This function/runnable should take in a the graph state and output a list of messages.\n",
     "We can do all types of arbitrary formatting of messages here. In this case, let's add a SystemMessage to the start of the list of messages and append another user message at the end."
    ]
   },

docs/docs/integrations/chat/anthropic.ipynb

@@ -315,59 +315,6 @@
     "ai_msg.tool_calls"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "6e36d25c-f358-49e5-aefa-b99fbd3fec6b",
-   "metadata": {},
-   "source": [
-    "## Extended thinking\n",
-    "\n",
-    "Claude 3.7 Sonnet supports an [extended thinking](https://docs.anthropic.com/en/docs/build-with-claude/extended-thinking) feature, which will output the step-by-step reasoning process that led to its final answer.\n",
-    "\n",
-    "To use it, specify the `thinking` parameter when initializing `ChatAnthropic`. It can also be passed in as a kwarg during invocation.\n",
-    "\n",
-    "You will need to specify a token budget to use this feature. See usage example below:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "a34cf93b-8522-43a6-a3f3-8a189ddf54a7",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[\n",
-      "  {\n",
-      "    \"signature\": \"ErUBCkYIARgCIkCx7bIPj35jGPHpoVOB2y5hvPF8MN4lVK75CYGftmVNlI4axz2+bBbSexofWsN1O/prwNv8yPXnIXQmwT6zrJsKEgwJzvks0yVRZtaGBScaDOm9xcpOxbuhku1zViIw9WDgil/KZL8DsqWrhVpC6TzM0RQNCcsHcmgmyxbgG9g8PR0eJGLxCcGoEw8zMQu1Kh1hQ1/03hZ2JCOgigpByR9aNPTwwpl64fQUe6WwIw==\",\n",
-      "    \"thinking\": \"To find the cube root of 50.653, I need to find the value of $x$ such that $x^3 = 50.653$.\\n\\nI can try to estimate this first. \\n$3^3 = 27$\\n$4^3 = 64$\\n\\nSo the cube root of 50.653 will be somewhere between 3 and 4, but closer to 4.\\n\\nLet me try to compute this more precisely. I can use the cube root function:\\n\\ncube root of 50.653 = 50.653^(1/3)\\n\\nLet me calculate this:\\n50.653^(1/3) \\u2248 3.6998\\n\\nLet me verify:\\n3.6998^3 \\u2248 50.6533\\n\\nThat's very close to 50.653, so I'm confident that the cube root of 50.653 is approximately 3.6998.\\n\\nActually, let me compute this more precisely:\\n50.653^(1/3) \\u2248 3.69981\\n\\nLet me verify once more:\\n3.69981^3 \\u2248 50.652998\\n\\nThat's extremely close to 50.653, so I'll say that the cube root of 50.653 is approximately 3.69981.\",\n",
-      "    \"type\": \"thinking\"\n",
-      "  },\n",
-      "  {\n",
-      "    \"text\": \"The cube root of 50.653 is approximately 3.6998.\\n\\nTo verify: 3.6998\\u00b3 = 50.6530, which is very close to our original number.\",\n",
-      "    \"type\": \"text\"\n",
-      "  }\n",
-      "]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import json\n",
-    "\n",
-    "from langchain_anthropic import ChatAnthropic\n",
-    "\n",
-    "llm = ChatAnthropic(\n",
-    "    model=\"claude-3-7-sonnet-latest\",\n",
-    "    max_tokens=5000,\n",
-    "    thinking={\"type\": \"enabled\", \"budget_tokens\": 2000},\n",
-    ")\n",
-    "\n",
-    "response = llm.invoke(\"What is the cube root of 50.653?\")\n",
-    "print(json.dumps(response.content, indent=2))"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "301d372f-4dec-43e6-b58c-eee25633e1a6",

docs/docs/integrations/chat/tongyi.ipynb

@@ -26,9 +26,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
    "source": [
     "# Install the package\n",
     "%pip install --upgrade --quiet  dashscope"
@@ -36,12 +49,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-03-05T01:11:20.457141Z",
-     "start_time": "2025-03-05T01:11:18.810160Z"
-    },
     "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
@@ -57,12 +66,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-03-05T01:11:24.270318Z",
-     "start_time": "2025-03-05T01:11:24.268064Z"
-    },
     "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
@@ -261,52 +266,6 @@
     "ai_message"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Partial Mode\n",
-    "Enable the large model to continue generating content from the initial text you provide."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-03-05T01:31:29.155824Z",
-     "start_time": "2025-03-05T01:31:27.239667Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "AIMessage(content=' has cast off its heavy cloak of snow, donning instead a vibrant garment of fresh greens and floral hues; it is as if the world has woken from a long slumber, stretching and reveling in the warm caress of the sun. Everywhere I look, there is a symphony of life: birdsong fills the air, bees dance from flower to flower, and a gentle breeze carries the sweet fragrance of blossoms. It is in this season that my heart finds particular joy, for it whispers promises of renewal and growth, reminding me that even after the coldest winters, there will always be a spring to follow.', additional_kwargs={}, response_metadata={'model_name': 'qwen-turbo', 'finish_reason': 'stop', 'request_id': '447283e9-ee31-9d82-8734-af572921cb05', 'token_usage': {'input_tokens': 40, 'output_tokens': 127, 'prompt_tokens_details': {'cached_tokens': 0}, 'total_tokens': 167}}, id='run-6a35a91c-cc12-4afe-b56f-fd26d9035357-0')"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from langchain_community.chat_models.tongyi import ChatTongyi\n",
-    "from langchain_core.messages import AIMessage, HumanMessage\n",
-    "\n",
-    "messages = [\n",
-    "    HumanMessage(\n",
-    "        content=\"\"\"Please continue the sentence \"Spring has arrived, and the earth\" to express the beauty of spring and the author's joy.\"\"\"\n",
-    "    ),\n",
-    "    AIMessage(\n",
-    "        content=\"Spring has arrived, and the earth\", additional_kwargs={\"partial\": True}\n",
-    "    ),\n",
-    "]\n",
-    "chatLLM = ChatTongyi()\n",
-    "ai_message = chatLLM.invoke(messages)\n",
-    "ai_message"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},

docs/docs/integrations/chat/writer.ipynb

@@ -15,9 +15,9 @@
     "## Overview\n",
     "\n",
     "### Integration details\n",
-    "| Class                                                                                                                    | Package          | Local | Serializable | JS support |                                        Package downloads                                         |                                        Package latest                                         |\n",
-    "|:-------------------------------------------------------------------------------------------------------------------------|:-----------------| :---: | :---: |:----------:|:------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|\n",
-    "| [ChatWriter](https://github.com/writer/langchain-writer/blob/main/langchain_writer/chat_models.py#L308) | [langchain-writer](https://pypi.org/project/langchain-writer/) |      ❌       |                                       ❌                                       | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-writer?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-writer?style=flat-square&label=%20) |\n",
+    "| Class                                                                                                                                       | Package          | Local | Serializable | JS support |                                        Package downloads                                         |                                        Package latest                                         |\n",
+    "|:--------------------------------------------------------------------------------------------------------------------------------------------|:-----------------| :---: | :---: |:----------:|:------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|\n",
+    "| ChatWriter | [langchain-writer](https://pypi.org/project/langchain-writer/) |      ❌       |                                       ❌                                       | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-writer?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-writer?style=flat-square&label=%20) |\n",
     "### Model features\n",
     "| [Tool calling](/docs/how_to/tool_calling) | Structured output | JSON mode | Image input | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async |         [Token usage](/docs/how_to/chat_token_usage_tracking/)          | Logprobs |\n",
     "| :---: |:-----------------:| :---: | :---: |  :---: | :---: | :---: | :---: |:--------------------------------:|:--------:|\n",
@@ -36,21 +36,17 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "433e8d2b-9519-4b49-b2c4-7ab65b046c94",
-   "metadata": {
-    "jupyter": {
-     "is_executing": true
-    }
-   },
+   "metadata": {},
+   "outputs": [],
    "source": [
     "import getpass\n",
     "import os\n",
     "\n",
     "if not os.getenv(\"WRITER_API_KEY\"):\n",
     "    os.environ[\"WRITER_API_KEY\"] = getpass.getpass(\"Enter your Writer API key: \")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -62,14 +58,14 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "a15d341e-3e26-4ca3-830b-5aab30ed66de",
    "metadata": {},
+   "outputs": [],
    "source": [
     "# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
     "# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -83,13 +79,13 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "652d6238-1f87-422a-b135-f5abbb8652fc",
    "metadata": {},
+   "outputs": [],
    "source": [
     "%pip install -qU langchain-writer"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -103,8 +99,10 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
    "metadata": {},
+   "outputs": [],
    "source": [
     "from langchain_writer import ChatWriter\n",
     "\n",
@@ -115,9 +113,7 @@
     "    timeout=None,\n",
     "    max_retries=2,\n",
     ")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -131,10 +127,12 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "62e0dbc3",
    "metadata": {
     "tags": []
    },
+   "outputs": [],
    "source": [
     "messages = [\n",
     "    (\n",
@@ -145,9 +143,7 @@
     "]\n",
     "ai_msg = llm.invoke(messages)\n",
     "ai_msg"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -159,13 +155,13 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "d86145b3-bfef-46e8-b227-4dda5c9c2705",
    "metadata": {},
+   "outputs": [],
    "source": [
     "print(ai_msg.content)"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -179,8 +175,10 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "4a0f2112b3a4c79e",
    "metadata": {},
+   "outputs": [],
    "source": [
     "messages = [\n",
     "    (\n",
@@ -191,9 +189,7 @@
     "]\n",
     "ai_stream = llm.stream(messages)\n",
     "ai_stream"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -205,14 +201,14 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "8c4b7b9b9308c757",
    "metadata": {},
+   "outputs": [],
    "source": [
     "for chunk in ai_stream:\n",
     "    print(chunk.content, end=\"\")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -240,8 +236,10 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "47e2f0faceca533",
    "metadata": {},
+   "outputs": [],
    "source": [
     "from pydantic import BaseModel, Field\n",
     "\n",
@@ -253,9 +251,7 @@
     "\n",
     "\n",
     "llm.bind_tools([GetWeather])"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -267,16 +263,16 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "765527dd533ec967",
    "metadata": {},
+   "outputs": [],
    "source": [
     "ai_msg = llm.invoke(\n",
     "    \"what is the weather like in New York City\",\n",
     ")\n",
     "ai_msg"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -288,13 +284,13 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "f361c4769e772fe",
    "metadata": {},
+   "outputs": [],
    "source": [
     "print(ai_msg.tool_calls)"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -320,8 +316,10 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "c8a217f6190747fe",
    "metadata": {},
+   "outputs": [],
    "source": [
     "ai_batch = llm.batch(\n",
     "    [\n",
@@ -332,9 +330,7 @@
     "    config={\"max_concurrency\": 3},\n",
     ")\n",
     "ai_batch"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -346,15 +342,15 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "b6a228d448f3df23",
    "metadata": {},
+   "outputs": [],
    "source": [
     "for batch in ai_batch:\n",
     "    print(batch.content)\n",
     "    print(\"-\" * 100)"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -378,8 +374,10 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "e197d1d7-a070-4c96-9f8a-a0e86d046e0b",
    "metadata": {},
+   "outputs": [],
    "source": [
     "from langchain_core.prompts import ChatPromptTemplate\n",
     "\n",
@@ -401,9 +399,7 @@
     "        \"input\": \"I love programming.\",\n",
     "    }\n",
     ")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",

docs/docs/integrations/document_loaders/parsers/writer_pdf_parser.ipynb

@@ -14,9 +14,9 @@
     "## Overview\n",
     "\n",
     "### Integration details\n",
-    "| Class                                                                                                                              | Package          | Local | Serializable | JS support |                                        Package downloads                                         |                                        Package latest                                         |\n",
-    "|:-----------------------------------------------------------------------------------------------------------------------------------|:-----------------| :---: | :---: |:----------:|:------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|\n",
-    "| [PDFParser](https://github.com/writer/langchain-writer/blob/main/langchain_writer/pdf_parser.py#L55) | [langchain-writer](https://pypi.org/project/langchain-writer/) |      ❌       |                                       ❌                                       | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-writer?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-writer?style=flat-square&label=%20) |"
+    "| Class                                                                                                                                     | Package          | Local | Serializable | JS support |                                        Package downloads                                         |                                        Package latest                                         |\n",
+    "|:------------------------------------------------------------------------------------------------------------------------------------------|:-----------------| :---: | :---: |:----------:|:------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|\n",
+    "| PDFParser | [langchain-writer](https://pypi.org/project/langchain-writer/) |      ❌       |                                       ❌                                       | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-writer?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-writer?style=flat-square&label=%20) |"
    ]
   },
   {
@@ -31,13 +31,17 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "a8d653f15b7ee32d",
-   "metadata": {},
+   "metadata": {
+    "jupyter": {
+     "is_executing": true
+    }
+   },
+   "outputs": [],
    "source": [
     "%pip install --quiet -U langchain-writer"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -51,17 +55,17 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "2983e19c9d555e58",
    "metadata": {},
+   "outputs": [],
    "source": [
     "import getpass\n",
     "import os\n",
     "\n",
     "if not os.getenv(\"WRITER_API_KEY\"):\n",
     "    os.environ[\"WRITER_API_KEY\"] = getpass.getpass(\"Enter your Writer API key: \")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -73,14 +77,14 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "98d8422ecee77403",
    "metadata": {},
+   "outputs": [],
    "source": [
     "# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
     "# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -94,15 +98,15 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "787b3ba8af32533f",
    "metadata": {},
+   "outputs": [],
    "source": [
     "from langchain_writer.pdf_parser import PDFParser\n",
     "\n",
     "parser = PDFParser(format=\"markdown\")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -120,18 +124,18 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "d1a24b81a8a96f09",
    "metadata": {},
+   "outputs": [],
    "source": [
     "from langchain_core.documents.base import Blob\n",
     "\n",
-    "file = Blob.from_path(\"../example_data/layout-parser-paper.pdf\")\n",
+    "file = Blob.from_path(\"../../data/page_to_parse.pdf\")\n",
     "\n",
     "parsed_pages = parser.parse(blob=file)\n",
     "parsed_pages"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -145,14 +149,14 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "e2f7fd52b7188c6c",
    "metadata": {},
+   "outputs": [],
    "source": [
     "parsed_pages_async = await parser.aparse(blob=file)\n",
     "parsed_pages_async"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",

docs/docs/integrations/document_loaders/pymupdf4llm.ipynb

@@ -1,721 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "---\n",
-    "sidebar_label: PyMuPDF4LLM\n",
-    "---"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# PyMuPDF4LLMLoader\n",
-    "\n",
-    "This notebook provides a quick overview for getting started with PyMuPDF4LLM [document loader](https://python.langchain.com/docs/concepts/#document-loaders). For detailed documentation of all PyMuPDF4LLMLoader features and configurations head to the [GitHub repository](https://github.com/lakinduboteju/langchain-pymupdf4llm).\n",
-    "\n",
-    "## Overview\n",
-    "\n",
-    "### Integration details\n",
-    "\n",
-    "| Class | Package | Local | Serializable | JS support |\n",
-    "| :--- | :--- | :---: | :---: |  :---: |\n",
-    "| [PyMuPDF4LLMLoader](https://github.com/lakinduboteju/langchain-pymupdf4llm) | [langchain_pymupdf4llm](https://pypi.org/project/langchain-pymupdf4llm) | ✅ | ❌ | ❌ |\n",
-    "\n",
-    "### Loader features\n",
-    "\n",
-    "| Source | Document Lazy Loading | Native Async Support | Extract Images | Extract Tables |\n",
-    "| :---: | :---: | :---: | :---: | :---: |\n",
-    "| PyMuPDF4LLMLoader | ✅ | ❌ | ✅ | ✅ |\n",
-    "\n",
-    "## Setup\n",
-    "\n",
-    "To access PyMuPDF4LLM document loader you'll need to install the `langchain-pymupdf4llm` integration package.\n",
-    "\n",
-    "### Credentials\n",
-    "\n",
-    "No credentials are required to use PyMuPDF4LLMLoader."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "If you want to get automated best in-class tracing of your model calls you can also set your [LangSmith](https://docs.smith.langchain.com/) API key by uncommenting below:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")\n",
-    "# os.environ[\"LANGSMITH_TRACING\"] = \"true\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Installation\n",
-    "\n",
-    "Install **langchain_community** and **langchain-pymupdf4llm**."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Note: you may need to restart the kernel to use updated packages.\n"
-     ]
-    }
-   ],
-   "source": [
-    "%pip install -qU langchain_community langchain-pymupdf4llm"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Initialization\n",
-    "\n",
-    "Now we can instantiate our model object and load documents:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain_pymupdf4llm import PyMuPDF4LLMLoader\n",
-    "\n",
-    "file_path = \"./example_data/layout-parser-paper.pdf\"\n",
-    "loader = PyMuPDF4LLMLoader(file_path)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Load"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Document(metadata={'producer': 'pdfTeX-1.40.21', 'creator': 'LaTeX with hyperref', 'creationdate': '2021-06-22T01:27:10+00:00', 'source': './example_data/layout-parser-paper.pdf', 'file_path': './example_data/layout-parser-paper.pdf', 'total_pages': 16, 'format': 'PDF 1.5', 'title': '', 'author': '', 'subject': '', 'keywords': '', 'moddate': '2021-06-22T01:27:10+00:00', 'trapped': '', 'modDate': 'D:20210622012710Z', 'creationDate': 'D:20210622012710Z', 'page': 0}, page_content='```\\nLayoutParser: A Unified Toolkit for Deep\\n\\n## Learning Based Document Image Analysis\\n\\n```\\n\\nZejiang Shen[1] (<28>), Ruochen Zhang[2], Melissa Dell[3], Benjamin Charles Germain\\nLee[4], Jacob Carlson[3], and Weining Li[5]\\n\\n1 Allen Institute for AI\\n```\\n              shannons@allenai.org\\n\\n```\\n2 Brown University\\n```\\n             ruochen zhang@brown.edu\\n\\n```\\n3 Harvard University\\n_{melissadell,jacob carlson}@fas.harvard.edu_\\n4 University of Washington\\n```\\n              bcgl@cs.washington.edu\\n\\n```\\n5 University of Waterloo\\n```\\n              w422li@uwaterloo.ca\\n\\n```\\n\\n**Abstract. Recent advances in document image analysis (DIA) have been**\\nprimarily driven by the application of neural networks. Ideally, research\\noutcomes could be easily deployed in production and extended for further\\ninvestigation. However, various factors like loosely organized codebases\\nand sophisticated model configurations complicate the easy reuse of important innovations by a wide audience. Though there have been on-going\\nefforts to improve reusability and simplify deep learning (DL) model\\ndevelopment in disciplines like natural language processing and computer\\nvision, none of them are optimized for challenges in the domain of DIA.\\nThis represents a major gap in the existing toolkit, as DIA is central to\\nacademic research across a wide range of disciplines in the social sciences\\nand humanities. This paper introduces LayoutParser, an open-source\\nlibrary for streamlining the usage of DL in DIA research and applications. The core LayoutParser library comes with a set of simple and\\nintuitive interfaces for applying and customizing DL models for layout detection, character recognition, and many other document processing tasks.\\nTo promote extensibility, LayoutParser also incorporates a community\\nplatform for sharing both pre-trained models and full document digitization pipelines. We demonstrate that LayoutParser is helpful for both\\nlightweight and large-scale digitization pipelines in real-word use cases.\\n[The library is publicly available at https://layout-parser.github.io.](https://layout-parser.github.io)\\n\\n**Keywords: Document Image Analysis · Deep Learning · Layout Analysis**\\n\\n    - Character Recognition · Open Source library · Toolkit.\\n\\n### 1 Introduction\\n\\n\\nDeep Learning(DL)-based approaches are the state-of-the-art for a wide range of\\ndocument image analysis (DIA) tasks including document image classification [11,\\n\\n')"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "docs = loader.load()\n",
-    "docs[0]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'producer': 'pdfTeX-1.40.21',\n",
-      " 'creator': 'LaTeX with hyperref',\n",
-      " 'creationdate': '2021-06-22T01:27:10+00:00',\n",
-      " 'source': './example_data/layout-parser-paper.pdf',\n",
-      " 'file_path': './example_data/layout-parser-paper.pdf',\n",
-      " 'total_pages': 16,\n",
-      " 'format': 'PDF 1.5',\n",
-      " 'title': '',\n",
-      " 'author': '',\n",
-      " 'subject': '',\n",
-      " 'keywords': '',\n",
-      " 'moddate': '2021-06-22T01:27:10+00:00',\n",
-      " 'trapped': '',\n",
-      " 'modDate': 'D:20210622012710Z',\n",
-      " 'creationDate': 'D:20210622012710Z',\n",
-      " 'page': 0}\n"
-     ]
-    }
-   ],
-   "source": [
-    "import pprint\n",
-    "\n",
-    "pprint.pp(docs[0].metadata)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Lazy Load"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "6"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pages = []\n",
-    "for doc in loader.lazy_load():\n",
-    "    pages.append(doc)\n",
-    "    if len(pages) >= 10:\n",
-    "        # do some paged operation, e.g.\n",
-    "        # index.upsert(page)\n",
-    "\n",
-    "        pages = []\n",
-    "len(pages)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from IPython.display import Markdown, display\n",
-    "\n",
-    "part = pages[0].page_content[778:1189]\n",
-    "print(part)\n",
-    "# Markdown rendering\n",
-    "display(Markdown(part))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'producer': 'pdfTeX-1.40.21',\n",
-      " 'creator': 'LaTeX with hyperref',\n",
-      " 'creationdate': '2021-06-22T01:27:10+00:00',\n",
-      " 'source': './example_data/layout-parser-paper.pdf',\n",
-      " 'file_path': './example_data/layout-parser-paper.pdf',\n",
-      " 'total_pages': 16,\n",
-      " 'format': 'PDF 1.5',\n",
-      " 'title': '',\n",
-      " 'author': '',\n",
-      " 'subject': '',\n",
-      " 'keywords': '',\n",
-      " 'moddate': '2021-06-22T01:27:10+00:00',\n",
-      " 'trapped': '',\n",
-      " 'modDate': 'D:20210622012710Z',\n",
-      " 'creationDate': 'D:20210622012710Z',\n",
-      " 'page': 10}\n"
-     ]
-    }
-   ],
-   "source": [
-    "pprint.pp(pages[0].metadata)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The metadata attribute contains at least the following keys:\n",
-    "- source\n",
-    "- page (if in mode *page*)\n",
-    "- total_page\n",
-    "- creationdate\n",
-    "- creator\n",
-    "- producer\n",
-    "\n",
-    "Additional metadata are specific to each parser.\n",
-    "These pieces of information can be helpful (to categorize your PDFs for example)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Splitting mode & custom pages delimiter"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "When loading the PDF file you can split it in two different ways:\n",
-    "- By page\n",
-    "- As a single text flow\n",
-    "\n",
-    "By default PyMuPDF4LLMLoader will split the PDF by page."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Extract the PDF by page. Each page is extracted as a langchain Document object:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "16\n",
-      "{'producer': 'pdfTeX-1.40.21',\n",
-      " 'creator': 'LaTeX with hyperref',\n",
-      " 'creationdate': '2021-06-22T01:27:10+00:00',\n",
-      " 'source': './example_data/layout-parser-paper.pdf',\n",
-      " 'file_path': './example_data/layout-parser-paper.pdf',\n",
-      " 'total_pages': 16,\n",
-      " 'format': 'PDF 1.5',\n",
-      " 'title': '',\n",
-      " 'author': '',\n",
-      " 'subject': '',\n",
-      " 'keywords': '',\n",
-      " 'moddate': '2021-06-22T01:27:10+00:00',\n",
-      " 'trapped': '',\n",
-      " 'modDate': 'D:20210622012710Z',\n",
-      " 'creationDate': 'D:20210622012710Z',\n",
-      " 'page': 0}\n"
-     ]
-    }
-   ],
-   "source": [
-    "loader = PyMuPDF4LLMLoader(\n",
-    "    \"./example_data/layout-parser-paper.pdf\",\n",
-    "    mode=\"page\",\n",
-    ")\n",
-    "docs = loader.load()\n",
-    "\n",
-    "print(len(docs))\n",
-    "pprint.pp(docs[0].metadata)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In this mode the pdf is split by pages and the resulting Documents metadata contains the `page` (page number). But in some cases we could want to process the pdf as a single text flow (so we don't cut some paragraphs in half). In this case you can use the *single* mode :"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Extract the whole PDF as a single langchain Document object:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "1\n",
-      "{'producer': 'pdfTeX-1.40.21',\n",
-      " 'creator': 'LaTeX with hyperref',\n",
-      " 'creationdate': '2021-06-22T01:27:10+00:00',\n",
-      " 'source': './example_data/layout-parser-paper.pdf',\n",
-      " 'file_path': './example_data/layout-parser-paper.pdf',\n",
-      " 'total_pages': 16,\n",
-      " 'format': 'PDF 1.5',\n",
-      " 'title': '',\n",
-      " 'author': '',\n",
-      " 'subject': '',\n",
-      " 'keywords': '',\n",
-      " 'moddate': '2021-06-22T01:27:10+00:00',\n",
-      " 'trapped': '',\n",
-      " 'modDate': 'D:20210622012710Z',\n",
-      " 'creationDate': 'D:20210622012710Z'}\n"
-     ]
-    }
-   ],
-   "source": [
-    "loader = PyMuPDF4LLMLoader(\n",
-    "    \"./example_data/layout-parser-paper.pdf\",\n",
-    "    mode=\"single\",\n",
-    ")\n",
-    "docs = loader.load()\n",
-    "\n",
-    "print(len(docs))\n",
-    "pprint.pp(docs[0].metadata)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Logically, in this mode, the `page` (page_number) metadata disappears. Here's how to clearly identify where pages end in the text flow :"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Add a custom *pages_delimiter* to identify where are ends of pages in *single* mode:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "loader = PyMuPDF4LLMLoader(\n",
-    "    \"./example_data/layout-parser-paper.pdf\",\n",
-    "    mode=\"single\",\n",
-    "    pages_delimiter=\"\\n-------THIS IS A CUSTOM END OF PAGE-------\\n\\n\",\n",
-    ")\n",
-    "docs = loader.load()\n",
-    "\n",
-    "part = docs[0].page_content[10663:11317]\n",
-    "print(part)\n",
-    "display(Markdown(part))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The default `pages_delimiter` is \\n-----\\n\\n.\n",
-    "But this could simply be \\n, or \\f to clearly indicate a page change, or \\<!-- PAGE BREAK --> for seamless injection in a Markdown viewer without a visual effect."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Extract images from the PDF"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "You can extract images from your PDFs (in text form) with a choice of three different solutions:\n",
-    "- rapidOCR (lightweight Optical Character Recognition tool)\n",
-    "- Tesseract (OCR tool with high precision)\n",
-    "- Multimodal language model\n",
-    "\n",
-    "The result is inserted at the end of text of the page."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Extract images from the PDF with rapidOCR:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Note: you may need to restart the kernel to use updated packages.\n"
-     ]
-    }
-   ],
-   "source": [
-    "%pip install -qU rapidocr-onnxruntime pillow"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain_community.document_loaders.parsers import RapidOCRBlobParser\n",
-    "\n",
-    "loader = PyMuPDF4LLMLoader(\n",
-    "    \"./example_data/layout-parser-paper.pdf\",\n",
-    "    mode=\"page\",\n",
-    "    extract_images=True,\n",
-    "    images_parser=RapidOCRBlobParser(),\n",
-    ")\n",
-    "docs = loader.load()\n",
-    "\n",
-    "part = docs[5].page_content[1863:]\n",
-    "print(part)\n",
-    "display(Markdown(part))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Be careful, RapidOCR is designed to work with Chinese and English, not other languages."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Extract images from the PDF with Tesseract:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Note: you may need to restart the kernel to use updated packages.\n"
-     ]
-    }
-   ],
-   "source": [
-    "%pip install -qU pytesseract"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain_community.document_loaders.parsers import TesseractBlobParser\n",
-    "\n",
-    "loader = PyMuPDF4LLMLoader(\n",
-    "    \"./example_data/layout-parser-paper.pdf\",\n",
-    "    mode=\"page\",\n",
-    "    extract_images=True,\n",
-    "    images_parser=TesseractBlobParser(),\n",
-    ")\n",
-    "docs = loader.load()\n",
-    "\n",
-    "print(docs[5].page_content[1863:])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Extract images from the PDF with multimodal model:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Note: you may need to restart the kernel to use updated packages.\n"
-     ]
-    }
-   ],
-   "source": [
-    "%pip install -qU langchain_openai"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "True"
-      ]
-     },
-     "execution_count": 39,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import os\n",
-    "\n",
-    "from dotenv import load_dotenv\n",
-    "\n",
-    "load_dotenv()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from getpass import getpass\n",
-    "\n",
-    "if not os.environ.get(\"OPENAI_API_KEY\"):\n",
-    "    os.environ[\"OPENAI_API_KEY\"] = getpass(\"OpenAI API key =\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain_community.document_loaders.parsers import LLMImageBlobParser\n",
-    "from langchain_openai import ChatOpenAI\n",
-    "\n",
-    "loader = PyMuPDF4LLMLoader(\n",
-    "    \"./example_data/layout-parser-paper.pdf\",\n",
-    "    mode=\"page\",\n",
-    "    extract_images=True,\n",
-    "    images_parser=LLMImageBlobParser(\n",
-    "        model=ChatOpenAI(model=\"gpt-4o-mini\", max_tokens=1024)\n",
-    "    ),\n",
-    ")\n",
-    "docs = loader.load()\n",
-    "\n",
-    "print(docs[5].page_content[1863:])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Extract tables from the PDF\n",
-    "\n",
-    "With PyMUPDF4LLM you can extract tables from your PDFs in *markdown* format :"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "loader = PyMuPDF4LLMLoader(\n",
-    "    \"./example_data/layout-parser-paper.pdf\",\n",
-    "    mode=\"page\",\n",
-    "    # \"lines_strict\" is the default strategy and\n",
-    "    # is the most accurate for tables with column and row lines,\n",
-    "    # but may not work well with all documents.\n",
-    "    # \"lines\" is a less strict strategy that may work better with\n",
-    "    # some documents.\n",
-    "    # \"text\" is the least strict strategy and may work better\n",
-    "    # with documents that do not have tables with lines.\n",
-    "    table_strategy=\"lines\",\n",
-    ")\n",
-    "docs = loader.load()\n",
-    "\n",
-    "part = docs[4].page_content[3210:]\n",
-    "print(part)\n",
-    "display(Markdown(part))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Working with Files\n",
-    "\n",
-    "Many document loaders involve parsing files. The difference between such loaders usually stems from how the file is parsed, rather than how the file is loaded. For example, you can use `open` to read the binary content of either a PDF or a markdown file, but you need different parsing logic to convert that binary data into text.\n",
-    "\n",
-    "As a result, it can be helpful to decouple the parsing logic from the loading logic, which makes it easier to re-use a given parser regardless of how the data was loaded.\n",
-    "You can use this strategy to analyze different files, with the same parsing parameters."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain_community.document_loaders import FileSystemBlobLoader\n",
-    "from langchain_community.document_loaders.generic import GenericLoader\n",
-    "from langchain_pymupdf4llm import PyMuPDF4LLMParser\n",
-    "\n",
-    "loader = GenericLoader(\n",
-    "    blob_loader=FileSystemBlobLoader(\n",
-    "        path=\"./example_data/\",\n",
-    "        glob=\"*.pdf\",\n",
-    "    ),\n",
-    "    blob_parser=PyMuPDF4LLMParser(),\n",
-    ")\n",
-    "docs = loader.load()\n",
-    "\n",
-    "part = docs[0].page_content[:562]\n",
-    "print(part)\n",
-    "display(Markdown(part))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## API reference\n",
-    "\n",
-    "For detailed documentation of all PyMuPDF4LLMLoader features and configurations head to the GitHub repository: https://github.com/lakinduboteju/langchain-pymupdf4llm"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.21"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}

docs/docs/integrations/document_transformers/google_cloud_vertexai_rerank.ipynb

@@ -546,7 +546,7 @@
     "id": "ud_cnGszb1i9"
    },
    "source": [
-    "Let's inspect a couple of reranked documents. We observe that the retriever still returns the relevant Langchain type [documents](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) but as part of the metadata field, we also receive the `relevance_score` from the Ranking API."
+    "Let's inspect a couple of reranked documents. We observe that the retriever still returns the relevant Langchain type [documents](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) but as part of the metadata field, we also recieve the `relevance_score` from the Ranking API."
    ]
   },
   {

docs/docs/integrations/llms/lmformatenforcer_experimental.ipynb

@@ -221,7 +221,7 @@
    "source": [
     "## JSONFormer LLM Wrapper\n",
     "\n",
-    "Let's try that again, now providing the Action input's JSON Schema to the model."
+    "Let's try that again, now providing a the Action input's JSON Schema to the model."
    ]
   },
   {

docs/docs/integrations/providers/ads4gpts.mdx

@@ -1,82 +0,0 @@
-# ADS4GPTs
-
-> [ADS4GPTs](https://www.ads4gpts.com/) is building the open monetization backbone of the AI-Native internet. It helps AI applications monetize through advertising with a UX and Privacy first approach. 
-
-## Installation and Setup
-
-### Using pip
-You can install the package directly from PyPI:
-
-```bash
-pip install ads4gpts-langchain
-```
-
-### From Source
-Alternatively, install from source:
-
-```bash
-git clone https://github.com/ADS4GPTs/ads4gpts.git
-cd ads4gpts/libs/python-sdk/ads4gpts-langchain
-pip install .
-```
-
-## Prerequisites
-
-- Python 3.11+
-- ADS4GPTs API Key ([Obtain API Key](https://www.ads4gpts.com))
-
-## Environment Variables
-Set the following environment variables for API authentication:
-
-```bash
-export ADS4GPTS_API_KEY='your-ads4gpts-api-key'
-```
-
-Alternatively, API keys can be passed directly when initializing classes or stored in a `.env` file.
-
-## Tools
-
-ADS4GPTs provides two main tools for monetization:
-
-### Ads4gptsInlineSponsoredResponseTool
-This tool fetches native, sponsored responses that can be seamlessly integrated within your AI application's outputs.
-
-```python
-from ads4gpts_langchain import Ads4gptsInlineSponsoredResponseTool
-```
-
-### Ads4gptsSuggestedPromptTool
-Generates sponsored prompt suggestions to enhance user engagement and provide monetization opportunities.
-
-```python
-from ads4gpts_langchain import Ads4gptsSuggestedPromptTool
-```
-### Ads4gptsInlineConversationalTool
-Delivers conversational sponsored content that naturally fits within chat interfaces and dialogs.
-
-```python
-from ads4gpts_langchain import Ads4gptsInlineConversationalTool
-```
-
-### Ads4gptsInlineBannerTool
-Provides inline banner advertisements that can be displayed within your AI application's response.
-
-```python
-from ads4gpts_langchain import Ads4gptsInlineBannerTool
-```
-
-### Ads4gptsSuggestedBannerTool
-Generates banner advertisement suggestions that can be presented to users as recommended content.
-
-```python
-from ads4gpts_langchain import Ads4gptsSuggestedBannerTool
-```
-
-## Toolkit
-
-The `Ads4gptsToolkit` combines these tools for convenient access in LangChain applications.
-
-```python
-from ads4gpts_langchain import Ads4gptsToolkit
-```
-

docs/docs/integrations/providers/apify.mdx

@@ -29,7 +29,7 @@ You can use the `ApifyActorsTool` to use Apify Actors with agents.
 from langchain_apify import ApifyActorsTool
 ```
 
-See [this notebook](/docs/integrations/tools/apify_actors) for example usage and a full example of a tool-calling agent with LangGraph in the [Apify LangGraph agent Actor template](https://apify.com/templates/python-langgraph).
+See [this notebook](/docs/integrations/tools/apify_actors) for example usage.
 
 For more information on how to use this tool, visit [the Apify integration documentation](https://docs.apify.com/platform/integrations/langgraph).
 

docs/docs/integrations/providers/kinetica.mdx

@@ -20,7 +20,7 @@ from langchain_community.chat_models.kinetica import ChatKinetica
 The Kinetca vectorstore wrapper leverages Kinetica's native support for [vector
 similarity search](https://docs.kinetica.com/7.2/vector_search/).
 
-See [Kinetica Vectorstore API](/docs/integrations/vectorstores/kinetica) for usage.
+See [Kinetica Vectorsore API](/docs/integrations/vectorstores/kinetica) for usage.
 
 ```python
 from langchain_community.vectorstores import Kinetica
@@ -28,8 +28,8 @@ from langchain_community.vectorstores import Kinetica
 
 ## Document Loader
 
-The Kinetica Document loader can be used to load LangChain [Documents](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) from the
-[Kinetica](https://www.kinetica.com/) database.
+The Kinetica Document loader can be used to load LangChain Documents from the
+Kinetica database.
 
 See [Kinetica Document Loader](/docs/integrations/document_loaders/kinetica) for usage
 

docs/docs/integrations/providers/prolog.md

@@ -4,7 +4,7 @@ SWI-Prolog offers a comprehensive free Prolog environment.
 
 ## Installation and Setup
 
-Once SWI-Prolog has been installed, install lanchain-prolog using pip:
+Install lanchain-prolog using pip:
 ```bash
 pip install langchain-prolog
 ```

docs/docs/integrations/providers/pymupdf4llm.ipynb

@@ -1,59 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# PyMuPDF4LLM\n",
-    "\n",
-    "[PyMuPDF4LLM](https://pymupdf.readthedocs.io/en/latest/pymupdf4llm) is aimed to make it easier to extract PDF content in Markdown format, needed for LLM & RAG applications.\n",
-    "\n",
-    "[langchain-pymupdf4llm](https://github.com/lakinduboteju/langchain-pymupdf4llm) integrates PyMuPDF4LLM to LangChain as a Document Loader."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%pip install -qU langchain-pymupdf4llm"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "y8ku6X96sebl"
-   },
-   "outputs": [],
-   "source": [
-    "from langchain_pymupdf4llm import PyMuPDF4LLMLoader, PyMuPDF4LLMParser"
-   ]
-  }
- ],
- "metadata": {
-  "colab": {
-   "provenance": []
-  },
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.11"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 1
-}

docs/docs/integrations/providers/tableau.mdx

@@ -1,15 +0,0 @@
-# Tableau
-
-[Tableau](https://www.tableau.com/) is an analytics platform that enables anyone to
-see and understand data. 
-
-
-## Installation and Setup
-
-```bash
-pip install langchain-tableau
-```
-
-## Tools
-
-See detail on available tools [here](/docs/integrations/tools/tableau).

docs/docs/integrations/providers/taiga.mdx

@@ -1,49 +0,0 @@
-# Taiga
-
-> [Taiga](https://docs.taiga.io/) is an open-source project management platform designed for agile teams, offering features like Kanban, Scrum, and issue tracking.
-
-## Installation and Setup
-
-Install the `langchain-taiga` package:
-
-```bash
-pip install langchain-taiga
-```
-
-You must provide a logins via environment variable so the tools can authenticate.
-
-```bash
-export TAIGA_URL="https://taiga.xyz.org/"
-export TAIGA_API_URL="https://taiga.xyz.org/"
-export TAIGA_USERNAME="username"
-export TAIGA_PASSWORD="pw"
-export OPENAI_API_KEY="OPENAI_API_KEY"
-```
-
-
----
-
-## Tools
-
-See a [usage example](/docs/integrations/tools/taiga)
-
----
-
-## Toolkit
-
-`TaigaToolkit` groups multiple Taiga-related tools into a single interface.
-
-```python
-from langchain_taiga.toolkits import TaigaToolkit
-
-toolkit = TaigaToolkit()
-tools = toolkit.get_tools()
-
-```
-
----
-
-## Future Integrations
-
-
-Check the [Taiga Developer Docs](https://docs.taiga.io/) for more information, and watch for updates or advanced usage examples in the [langchain_taiga GitHub repo](https://github.com/Shikenso-Analytics/langchain-taiga).

docs/docs/integrations/providers/writer.mdx

@@ -51,5 +51,3 @@ Support of basic function calls defined via dicts, Pydantic, python functions et
 ```python
 from langchain_writer.tools import GraphTool
 ```
-
-Writer-specific remotely invoking tool

docs/docs/integrations/splitters/writer_text_splitter.ipynb

@@ -14,9 +14,9 @@
     "## Overview\n",
     "\n",
     "### Integration details\n",
-    "| Class                                                                                                                                    | Package          | Local | Serializable | JS support |                                        Package downloads                                         |                                        Package latest                                         |\n",
-    "|:-----------------------------------------------------------------------------------------------------------------------------------------|:-----------------| :---: | :---: |:----------:|:------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|\n",
-    "| [WriterTextSplitter](https://github.com/writer/langchain-writer/blob/main/langchain_writer/text_splitter.py#L11) | [langchain-writer](https://pypi.org/project/langchain-writer/) |      ❌       |                                       ❌                                       | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-writer?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-writer?style=flat-square&label=%20) |"
+    "| Class                                                                                                                                                      | Package          | Local | Serializable | JS support |                                        Package downloads                                         |                                        Package latest                                         |\n",
+    "|:-----------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------| :---: | :---: |:----------:|:------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|\n",
+    "| WriterTextSplitter | [langchain-writer](https://pypi.org/project/langchain-writer/) |      ❌       |                                       ❌                                       | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-writer?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-writer?style=flat-square&label=%20) |"
    ]
   },
   {
@@ -31,11 +31,11 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "a8d653f15b7ee32d",
    "metadata": {},
-   "source": "%pip install --quiet -U langchain-writer",
    "outputs": [],
-   "execution_count": null
+   "source": "%pip install --quiet -U langchain-writer"
   },
   {
    "cell_type": "markdown",
@@ -49,17 +49,17 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "2983e19c9d555e58",
    "metadata": {},
+   "outputs": [],
    "source": [
     "import getpass\n",
     "import os\n",
     "\n",
     "if not os.getenv(\"WRITER_API_KEY\"):\n",
     "    os.environ[\"WRITER_API_KEY\"] = getpass.getpass(\"Enter your Writer API key: \")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -71,14 +71,14 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "98d8422ecee77403",
    "metadata": {},
+   "outputs": [],
    "source": [
     "# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
     "# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -96,15 +96,15 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "787b3ba8af32533f",
    "metadata": {},
+   "outputs": [],
    "source": [
     "from langchain_writer.text_splitter import WriterTextSplitter\n",
     "\n",
     "splitter = WriterTextSplitter(strategy=\"fast_split\")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -120,8 +120,10 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "d1a24b81a8a96f09",
    "metadata": {},
+   "outputs": [],
    "source": [
     "text = \"\"\"Reeeeeeeeeeeeeeeeeeeeeaally long text you want to divide into smaller chunks. For example you can add a poem multiple times:\n",
     "Two roads diverged in a yellow wood,\n",
@@ -199,9 +201,7 @@
     "\n",
     "chunks = splitter.split_text(text)\n",
     "chunks"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -213,13 +213,13 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "a470daa875d99006",
    "metadata": {},
+   "outputs": [],
    "source": [
     "print(len(chunks))"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -232,14 +232,14 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "e2f7fd52b7188c6c",
    "metadata": {},
+   "outputs": [],
    "source": [
     "async_chunks = await splitter.asplit_text(text)\n",
     "async_chunks"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -251,13 +251,13 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "a1439db14e687fa4",
    "metadata": {},
+   "outputs": [],
    "source": [
     "print(len(async_chunks))"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",

docs/docs/integrations/tools/ads4gpts.ipynb

@@ -1,365 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# ADS4GPTs\n",
-    "\n",
-    "Integrate AI native advertising into your Agentic application.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Overview"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "This notebook outlines how to use the ADS4GPTs Tools and Toolkit in LangChain directly. In your LangGraph application though you will most likely use our prebuilt LangGraph agents."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Setup"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Install ADS4GPTs Package\n",
-    "Install the ADS4GPTs package using pip."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Install ADS4GPTs Package\n",
-    "# Install the ADS4GPTs package using pip\n",
-    "!pip install ads4gpts-langchain"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Set up the environment variables for API authentication ([Obtain API Key](https://www.ads4gpts.com))."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Setup Environment Variables\n",
-    "# Prompt the user to enter their ADS4GPTs API key securely\n",
-    "if not os.environ.get(\"ADS4GPTS_API_KEY\"):\n",
-    "    os.environ[\"ADS4GPTS_API_KEY\"] = getpass(\"Enter your ADS4GPTS API key: \")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Instantiation"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Import the necessary libraries, including ADS4GPTs tools and toolkit.\n",
-    "\n",
-    "Initialize the ADS4GPTs tools such as Ads4gptsInlineSponsoredResponseTool. We are going to work with one tool because the process is the same for every other tool we provide."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Import Required Libraries\n",
-    "\n",
-    "import os\n",
-    "from getpass import getpass\n",
-    "\n",
-    "from ads4gpts_langchain import Ads4gptsInlineSponsoredResponseTool, Ads4gptsToolkit"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Initialize ADS4GPTs Tools\n",
-    "# Initialize the Ads4gptsInlineSponsoredResponseTool\n",
-    "inline_sponsored_response_tool = Ads4gptsInlineSponsoredResponseTool(\n",
-    "    ads4gpts_api_key=os.environ[\"ADS4GPTS_API_KEY\"],\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Toolkit Instantiation\n",
-    "Initialize the Ads4gptsToolkit with the required parameters."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Initialized tool: Ads4gptsInlineSponsoredResponseTool\n",
-      "Initialized tool: Ads4gptsSuggestedPromptTool\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Toolkit Initialization\n",
-    "# Initialize the Ads4gptsToolkit with the required parameters\n",
-    "toolkit = Ads4gptsToolkit(\n",
-    "    ads4gpts_api_key=os.environ[\"ADS4GPTS_API_KEY\"],\n",
-    ")\n",
-    "\n",
-    "# Retrieve tools from the toolkit\n",
-    "tools = toolkit.get_tools()\n",
-    "\n",
-    "# Print the initialized tools\n",
-    "for tool in tools:\n",
-    "    print(f\"Initialized tool: {tool.__class__.__name__}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Invocation"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Run the ADS4GPTs tools with sample inputs and display the results."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Inline Sponsored Response Result: {'ad_text': '<- Promoted Content ->\\n\\nLearn the sartorial ways and get your handmade tailored suit by the masters themselves with Bespoke Tailors. [Subscribe now](https://youtube.com/@bespoketailorsdubai?si=9iH587ujoWKkueFa)\\n\\n<->'}\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Run ADS4GPTs Tools\n",
-    "# Sample input data for the tools\n",
-    "sample_input = {\n",
-    "    \"id\": \"test_id\",\n",
-    "    \"user_gender\": \"female\",\n",
-    "    \"user_age\": \"25-34\",\n",
-    "    \"user_persona\": \"test_persona\",\n",
-    "    \"ad_recommendation\": \"test_recommendation\",\n",
-    "    \"undesired_ads\": \"test_undesired_ads\",\n",
-    "    \"context\": \"test_context\",\n",
-    "    \"num_ads\": 1,\n",
-    "    \"style\": \"neutral\",\n",
-    "}\n",
-    "\n",
-    "# Run Ads4gptsInlineSponsoredResponseTool\n",
-    "inline_sponsored_response_result = inline_sponsored_response_tool._run(\n",
-    "    **sample_input, ad_format=\"INLINE_SPONSORED_RESPONSE\"\n",
-    ")\n",
-    "print(\"Inline Sponsored Response Result:\", inline_sponsored_response_result)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Async Run ADS4GPTs Tools\n",
-    "Run the ADS4GPTs tools asynchronously with sample inputs and display the results."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Async Inline Sponsored Response Result: {'ad_text': '<- Promoted Content ->\\n\\nGet the best tailoring content from Jonathan Farley. Learn to tie 100 knots and more! [Subscribe now](https://www.youtube.com/channel/UCx5hk4LN3p02jcUt3j_cexQ)\\n\\n<->'}\n"
-     ]
-    }
-   ],
-   "source": [
-    "import asyncio\n",
-    "\n",
-    "\n",
-    "# Define an async function to run the tools asynchronously\n",
-    "async def run_ads4gpts_tools_async():\n",
-    "    # Run Ads4gptsInlineSponsoredResponseTool asynchronously\n",
-    "    inline_sponsored_response_result = await inline_sponsored_response_tool._arun(\n",
-    "        **sample_input, ad_format=\"INLINE_SPONSORED_RESPONSE\"\n",
-    "    )\n",
-    "    print(\"Async Inline Sponsored Response Result:\", inline_sponsored_response_result)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Toolkit Invocation\n",
-    "Use the Ads4gptsToolkit to get and run tools."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Result from Ads4gptsInlineSponsoredResponseTool: {'ad_text': '<- Promoted Content ->\\n\\nLearn the sartorial ways and get your handmade tailored suit by the masters themselves with Bespoke Tailors. [Subscribe now](https://youtube.com/@bespoketailorsdubai?si=9iH587ujoWKkueFa)\\n\\n<->'}\n",
-      "Async result from Ads4gptsInlineSponsoredResponseTool: {'ad_text': '<- Promoted Content ->\\n\\nGet the best tailoring content from Jonathan Farley. Learn to tie 100 knots and more! [Subscribe now](https://www.youtube.com/channel/UCx5hk4LN3p02jcUt3j_cexQ)\\n\\n<->'}\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Sample input data for the tools\n",
-    "sample_input = {\n",
-    "    \"id\": \"test_id\",\n",
-    "    \"user_gender\": \"female\",\n",
-    "    \"user_age\": \"25-34\",\n",
-    "    \"user_persona\": \"test_persona\",\n",
-    "    \"ad_recommendation\": \"test_recommendation\",\n",
-    "    \"undesired_ads\": \"test_undesired_ads\",\n",
-    "    \"context\": \"test_context\",\n",
-    "    \"num_ads\": 1,\n",
-    "    \"style\": \"neutral\",\n",
-    "}\n",
-    "\n",
-    "# Run one tool and print the result\n",
-    "tool = tools[0]\n",
-    "result = tool._run(**sample_input)\n",
-    "print(f\"Result from {tool.__class__.__name__}:\", result)\n",
-    "\n",
-    "\n",
-    "# Define an async function to run the tools asynchronously\n",
-    "async def run_toolkit_tools_async():\n",
-    "    result = await tool._arun(**sample_input)\n",
-    "    print(f\"Async result from {tool.__class__.__name__}:\", result)\n",
-    "\n",
-    "\n",
-    "# Execute the async function\n",
-    "await run_toolkit_tools_async()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Chaining\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "if not os.environ.get(\"OPENAI_API_KEY\"):\n",
-    "    os.environ[\"OPENAI_API_KEY\"] = getpass(\"Enter your OPENAI_API_KEY API key: \")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Tool call: content='' additional_kwargs={'tool_calls': [{'id': 'call_XLR5UjF8JhylVHvrk9mTjhj8', 'function': {'arguments': '{\"id\":\"unique_user_id_001\",\"user_gender\":\"male\",\"user_age\":\"18-24\",\"ad_recommendation\":\"Stylish and trendy clothing suitable for young men going out with friends.\",\"undesired_ads\":\"formal wear, women\\'s clothing, children\\'s clothing\",\"context\":\"A young man looking for clothing to go out with friends\",\"num_ads\":1,\"style\":\"youthful and trendy\",\"ad_format\":\"INLINE_SPONSORED_RESPONSE\"}', 'name': 'ads4gpts_inline_sponsored_response'}, 'type': 'function'}], 'refusal': None} response_metadata={'token_usage': {'completion_tokens': 106, 'prompt_tokens': 1070, 'total_tokens': 1176, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 1024}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_eb9dce56a8', 'finish_reason': 'tool_calls', 'logprobs': None} id='run-e3e64b4b-4505-4a71-bf02-a8d77bb68eee-0' tool_calls=[{'name': 'ads4gpts_inline_sponsored_response', 'args': {'id': 'unique_user_id_001', 'user_gender': 'male', 'user_age': '18-24', 'ad_recommendation': 'Stylish and trendy clothing suitable for young men going out with friends.', 'undesired_ads': \"formal wear, women's clothing, children's clothing\", 'context': 'A young man looking for clothing to go out with friends', 'num_ads': 1, 'style': 'youthful and trendy', 'ad_format': 'INLINE_SPONSORED_RESPONSE'}, 'id': 'call_XLR5UjF8JhylVHvrk9mTjhj8', 'type': 'tool_call'}] usage_metadata={'input_tokens': 1070, 'output_tokens': 106, 'total_tokens': 1176, 'input_token_details': {'audio': 0, 'cache_read': 1024}, 'output_token_details': {'audio': 0, 'reasoning': 0}}\n"
-     ]
-    }
-   ],
-   "source": [
-    "import os\n",
-    "\n",
-    "from langchain_openai import ChatOpenAI\n",
-    "\n",
-    "openai_model = ChatOpenAI(model=\"gpt-4o\", openai_api_key=os.environ[\"OPENAI_API_KEY\"])\n",
-    "model = openai_model.bind_tools(tools)\n",
-    "model_response = model.invoke(\n",
-    "    \"Get me an ad for clothing. I am a young man looking to go out with friends.\"\n",
-    ")\n",
-    "print(\"Tool call:\", model_response)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## API reference"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "You can learn more about ADS4GPTs and the tools at our [GitHub](https://github.com/ADS4GPTs/ads4gpts/tree/main)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "ads4gpts-langraph-agent",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.9"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}

docs/docs/integrations/tools/apify_actors.ipynb

@@ -1,258 +1,256 @@
 {
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_9MNj58sIkGN"
-      },
-      "source": [
-        "# Apify Actor\n",
-        "\n",
-        ">[Apify Actors](https://docs.apify.com/platform/actors) are cloud programs designed for a wide range of web scraping, crawling, and data extraction tasks. These actors facilitate automated data gathering from the web, enabling users to extract, process, and store information efficiently. Actors can be used to perform tasks like scraping e-commerce sites for product details, monitoring price changes, or gathering search engine results. They integrate seamlessly with [Apify Datasets](https://docs.apify.com/platform/storage/dataset), allowing the structured data collected by actors to be stored, managed, and exported in formats like JSON, CSV, or Excel for further analysis or use.\n",
-        "\n",
-        "## Overview\n",
-        "\n",
-        "This notebook walks you through using [Apify Actors](https://docs.apify.com/platform/actors) with LangChain to automate web scraping and data extraction. The `langchain-apify` package integrates Apify's cloud-based tools with LangChain agents, enabling efficient data collection and processing for AI applications.\n",
-        "\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "OHLF9t9v9HCb"
-      },
-      "source": [
-        "## Setup\n",
-        "\n",
-        "This integration lives in the [langchain-apify](https://pypi.org/project/langchain-apify/) package. The package can be installed using pip.\n"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "4DdGmBn5IbXz"
-      },
-      "outputs": [],
-      "source": [
-        "%pip install langchain-apify"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "rEAwonXqwggR"
-      },
-      "source": [
-        "### Prerequisites\n",
-        "\n",
-        "- **Apify account**: Register your free Apify account [here](https://console.apify.com/sign-up).\n",
-        "- **Apify API token**: Learn how to get your API token in the [Apify documentation](https://docs.apify.com/platform/integrations/api)."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "9nJOl4MBMkcR"
-      },
-      "outputs": [],
-      "source": [
-        "import os\n",
-        "\n",
-        "os.environ[\"APIFY_API_TOKEN\"] = \"your-apify-api-token\"\n",
-        "os.environ[\"OPENAI_API_KEY\"] = \"your-openai-api-key\""
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "UfoQxAlCxR9q"
-      },
-      "source": [
-        "## Instantiation"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "qG9KtXtLM8i7"
-      },
-      "source": [
-        "Here we instantiate the `ApifyActorsTool` to be able to call [RAG Web Browser](https://apify.com/apify/rag-web-browser) Apify Actor. This Actor provides web browsing functionality for AI and LLM applications, similar to the web browsing feature in ChatGPT. Any Actor from the [Apify Store](https://apify.com/store) can be used in this way."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "cyxeTlPnM4Ya"
-      },
-      "outputs": [],
-      "source": [
-        "from langchain_apify import ApifyActorsTool\n",
-        "\n",
-        "tool = ApifyActorsTool(\"apify/rag-web-browser\")"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "fGDLvDCqyKWO"
-      },
-      "source": [
-        "## Invocation\n",
-        "\n",
-        "The `ApifyActorsTool` takes a single argument, which is `run_input` - a dictionary that is passed as a run input to the Actor. Run input schema documentation can be found in the input section of the Actor details page. See [RAG Web Browser input schema](https://apify.com/apify/rag-web-browser/input-schema).\n",
-        "\n"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "nTWy6Hx1yk04"
-      },
-      "outputs": [],
-      "source": [
-        "tool.invoke({\"run_input\": {\"query\": \"what is apify?\", \"maxResults\": 2}})"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "kQsa27hoO58S"
-      },
-      "source": [
-        "## Chaining\n",
-        "\n",
-        "We can provide the created tool to an [agent](https://python.langchain.com/docs/tutorials/agents/). When asked to search for information, the agent will call the Apify Actor, which will search the web, and then retrieve the search results.\n",
-        "\n"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "YySvLskW72Y8"
-      },
-      "outputs": [],
-      "source": [
-        "%pip install langgraph langchain-openai"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "QEDz07btO5Gi"
-      },
-      "outputs": [],
-      "source": [
-        "from langchain_core.messages import ToolMessage\n",
-        "from langchain_openai import ChatOpenAI\n",
-        "from langgraph.prebuilt import create_react_agent\n",
-        "\n",
-        "model = ChatOpenAI(model=\"gpt-4o\")\n",
-        "tools = [tool]\n",
-        "graph = create_react_agent(model, tools=tools)"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "XS1GEyNkQxGu",
-        "outputId": "195273d7-034c-425b-f3f9-95c0a9fb0c9e"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "================================\u001b[1m Human Message \u001b[0m=================================\n",
-            "\n",
-            "search for what is Apify\n",
-            "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
-            "Tool Calls:\n",
-            "  apify_actor_apify_rag-web-browser (call_27mjHLzDzwa5ZaHWCMH510lm)\n",
-            " Call ID: call_27mjHLzDzwa5ZaHWCMH510lm\n",
-            "  Args:\n",
-            "    run_input: {\"run_input\":{\"query\":\"Apify\",\"maxResults\":3,\"outputFormats\":[\"markdown\"]}}\n",
-            "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
-            "\n",
-            "Apify is a comprehensive platform for web scraping, browser automation, and data extraction. It offers a wide array of tools and services that cater to developers and businesses looking to extract data from websites efficiently and effectively. Here's an overview of Apify:\n",
-            "\n",
-            "1. **Ecosystem and Tools**:\n",
-            "   - Apify provides an ecosystem where developers can build, deploy, and publish data extraction and web automation tools called Actors.\n",
-            "   - The platform supports various use cases such as extracting data from social media platforms, conducting automated browser-based tasks, and more.\n",
-            "\n",
-            "2. **Offerings**:\n",
-            "   - Apify offers over 3,000 ready-made scraping tools and code templates.\n",
-            "   - Users can also build custom solutions or hire Apify's professional services for more tailored data extraction needs.\n",
-            "\n",
-            "3. **Technology and Integration**:\n",
-            "   - The platform supports integration with popular tools and services like Zapier, GitHub, Google Sheets, Pinecone, and more.\n",
-            "   - Apify supports open-source tools and technologies such as JavaScript, Python, Puppeteer, Playwright, Selenium, and its own Crawlee library for web crawling and browser automation.\n",
-            "\n",
-            "4. **Community and Learning**:\n",
-            "   - Apify hosts a community on Discord where developers can get help and share expertise.\n",
-            "   - It offers educational resources through the Web Scraping Academy to help users become proficient in data scraping and automation.\n",
-            "\n",
-            "5. **Enterprise Solutions**:\n",
-            "   - Apify provides enterprise-grade web data extraction solutions with high reliability, 99.95% uptime, and compliance with SOC2, GDPR, and CCPA standards.\n",
-            "\n",
-            "For more information, you can visit [Apify's official website](https://apify.com/) or their [GitHub page](https://github.com/apify) which contains their code repositories and further details about their projects.\n"
-          ]
-        }
-      ],
-      "source": [
-        "inputs = {\"messages\": [(\"user\", \"search for what is Apify\")]}\n",
-        "for s in graph.stream(inputs, stream_mode=\"values\"):\n",
-        "    message = s[\"messages\"][-1]\n",
-        "    # skip tool messages\n",
-        "    if isinstance(message, ToolMessage):\n",
-        "        continue\n",
-        "    message.pretty_print()"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "WYXuQIQx8AvG"
-      },
-      "source": [
-        "## API reference\n",
-        "\n",
-        "For more information on how to use this integration, see the [git repository](https://github.com/apify/langchain-apify) or the [Apify integration documentation](https://docs.apify.com/platform/integrations/langgraph)."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "f1NnMik78oib"
-      },
-      "outputs": [],
-      "source": []
-    }
-  ],
-  "metadata": {
-    "colab": {
-      "provenance": [],
-      "toc_visible": true
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    }
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_9MNj58sIkGN"
+   },
+   "source": [
+    "# Apify Actor\n",
+    "\n",
+    "## Overview\n",
+    "\n",
+    ">[Apify Actors](https://docs.apify.com/platform/actors) are cloud programs designed for a wide range of web scraping, crawling, and data extraction tasks. These actors facilitate automated data gathering from the web, enabling users to extract, process, and store information efficiently. Actors can be used to perform tasks like scraping e-commerce sites for product details, monitoring price changes, or gathering search engine results. They integrate seamlessly with [Apify Datasets](https://docs.apify.com/platform/storage/dataset), allowing the structured data collected by actors to be stored, managed, and exported in formats like JSON, CSV, or Excel for further analysis or use.\n",
+    "\n"
+   ]
   },
-  "nbformat": 4,
-  "nbformat_minor": 0
-}
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "OHLF9t9v9HCb"
+   },
+   "source": [
+    "## Setup\n",
+    "\n",
+    "This integration lives in the [langchain-apify](https://pypi.org/project/langchain-apify/) package. The package can be installed using pip.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "4DdGmBn5IbXz"
+   },
+   "outputs": [],
+   "source": [
+    "%pip install langchain-apify"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "rEAwonXqwggR"
+   },
+   "source": [
+    "### Prerequisites\n",
+    "\n",
+    "- **Apify account**: Register your free Apify account [here](https://console.apify.com/sign-up).\n",
+    "- **Apify API token**: Learn how to get your API token in the [Apify documentation](https://docs.apify.com/platform/integrations/api)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "9nJOl4MBMkcR"
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "os.environ[\"APIFY_API_TOKEN\"] = \"your-apify-api-token\"\n",
+    "os.environ[\"OPENAI_API_KEY\"] = \"your-openai-api-key\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "UfoQxAlCxR9q"
+   },
+   "source": [
+    "## Instantiation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "qG9KtXtLM8i7"
+   },
+   "source": [
+    "Here we instantiate the `ApifyActorsTool` to be able to call [RAG Web Browser](https://apify.com/apify/rag-web-browser) Apify Actor. This Actor provides web browsing functionality for AI and LLM applications, similar to the web browsing feature in ChatGPT. Any Actor from the [Apify Store](https://apify.com/store) can be used in this way."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "id": "cyxeTlPnM4Ya"
+   },
+   "outputs": [],
+   "source": [
+    "from langchain_apify import ApifyActorsTool\n",
+    "\n",
+    "tool = ApifyActorsTool(\"apify/rag-web-browser\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "fGDLvDCqyKWO"
+   },
+   "source": [
+    "## Invocation\n",
+    "\n",
+    "The `ApifyActorsTool` takes a single argument, which is `run_input` - a dictionary that is passed as a run input to the Actor. Run input schema documentation can be found in the input section of the Actor details page. See [RAG Web Browser input schema](https://apify.com/apify/rag-web-browser/input-schema).\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "nTWy6Hx1yk04"
+   },
+   "outputs": [],
+   "source": [
+    "tool.invoke({\"run_input\": {\"query\": \"what is apify?\", \"maxResults\": 2}})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "kQsa27hoO58S"
+   },
+   "source": [
+    "## Chaining\n",
+    "\n",
+    "We can provide the created tool to an [agent](https://python.langchain.com/docs/tutorials/agents/). When asked to search for information, the agent will call the Apify Actor, which will search the web, and then retrieve the search results.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YySvLskW72Y8"
+   },
+   "outputs": [],
+   "source": [
+    "%pip install langgraph langchain-openai"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "id": "QEDz07btO5Gi"
+   },
+   "outputs": [],
+   "source": [
+    "from langchain_core.messages import ToolMessage\n",
+    "from langchain_openai import ChatOpenAI\n",
+    "from langgraph.prebuilt import create_react_agent\n",
+    "\n",
+    "model = ChatOpenAI(model=\"gpt-4o\")\n",
+    "tools = [tool]\n",
+    "graph = create_react_agent(model, tools=tools)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "XS1GEyNkQxGu",
+    "outputId": "195273d7-034c-425b-f3f9-95c0a9fb0c9e"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "================================\u001b[1m Human Message \u001b[0m=================================\n",
+      "\n",
+      "search for what is Apify\n",
+      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
+      "Tool Calls:\n",
+      "  apify_actor_apify_rag-web-browser (call_27mjHLzDzwa5ZaHWCMH510lm)\n",
+      " Call ID: call_27mjHLzDzwa5ZaHWCMH510lm\n",
+      "  Args:\n",
+      "    run_input: {\"run_input\":{\"query\":\"Apify\",\"maxResults\":3,\"outputFormats\":[\"markdown\"]}}\n",
+      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
+      "\n",
+      "Apify is a comprehensive platform for web scraping, browser automation, and data extraction. It offers a wide array of tools and services that cater to developers and businesses looking to extract data from websites efficiently and effectively. Here's an overview of Apify:\n",
+      "\n",
+      "1. **Ecosystem and Tools**:\n",
+      "   - Apify provides an ecosystem where developers can build, deploy, and publish data extraction and web automation tools called Actors.\n",
+      "   - The platform supports various use cases such as extracting data from social media platforms, conducting automated browser-based tasks, and more.\n",
+      "\n",
+      "2. **Offerings**:\n",
+      "   - Apify offers over 3,000 ready-made scraping tools and code templates.\n",
+      "   - Users can also build custom solutions or hire Apify's professional services for more tailored data extraction needs.\n",
+      "\n",
+      "3. **Technology and Integration**:\n",
+      "   - The platform supports integration with popular tools and services like Zapier, GitHub, Google Sheets, Pinecone, and more.\n",
+      "   - Apify supports open-source tools and technologies such as JavaScript, Python, Puppeteer, Playwright, Selenium, and its own Crawlee library for web crawling and browser automation.\n",
+      "\n",
+      "4. **Community and Learning**:\n",
+      "   - Apify hosts a community on Discord where developers can get help and share expertise.\n",
+      "   - It offers educational resources through the Web Scraping Academy to help users become proficient in data scraping and automation.\n",
+      "\n",
+      "5. **Enterprise Solutions**:\n",
+      "   - Apify provides enterprise-grade web data extraction solutions with high reliability, 99.95% uptime, and compliance with SOC2, GDPR, and CCPA standards.\n",
+      "\n",
+      "For more information, you can visit [Apify's official website](https://apify.com/) or their [GitHub page](https://github.com/apify) which contains their code repositories and further details about their projects.\n"
+     ]
+    }
+   ],
+   "source": [
+    "inputs = {\"messages\": [(\"user\", \"search for what is Apify\")]}\n",
+    "for s in graph.stream(inputs, stream_mode=\"values\"):\n",
+    "    message = s[\"messages\"][-1]\n",
+    "    # skip tool messages\n",
+    "    if isinstance(message, ToolMessage):\n",
+    "        continue\n",
+    "    message.pretty_print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "WYXuQIQx8AvG"
+   },
+   "source": [
+    "## API reference\n",
+    "\n",
+    "For more information on how to use this integration, see the [git repository](https://github.com/apify/langchain-apify) or the [Apify integration documentation](https://docs.apify.com/platform/integrations/langgraph)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "f1NnMik78oib"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "provenance": [],
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}

docs/docs/integrations/tools/tableau.ipynb

@@ -1,315 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "1f302499-eb05-4296-8716-950babc0f10e",
-   "metadata": {},
-   "source": [
-    "# Tableau\n",
-    "\n",
-    "This notebook provides a quick overview for getting started with [Tableau](https://help.tableau.com/current/api/vizql-data-service/en-us/index.html). "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4d57b913-819e-4676-9f6e-3afe0a80030e",
-   "metadata": {},
-   "source": [
-    "### Overview\n",
-    "\n",
-    "Tableau's VizQL Data Service (aka VDS) provides developers with programmatic access to their Tableau Published Data Sources, allowing them to extend their business semantics for any custom workload or application, including AI Agents. The simple_datasource_qa tool adds VDS to the Langchain framework. This notebook shows you how you can use it to build agents that answer analytical questions grounded on your enterprise semantic models. \n",
-    "\n",
-    "Follow the [tableau-langchain](https://github.com/Tab-SE/tableau_langchain) project for more tools coming soon!"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "311bce64",
-   "metadata": {},
-   "source": [
-    "#### Setup\n",
-    "Make sure you are running and have access to:\n",
-    "1. python version 3.12.2 or higher\n",
-    "2. A Tableau Cloud or Server environment with at least 1 published data source\n",
-    "\n",
-    "Get started by installing and/or importing the required packages"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9b178e95-ffae-4f04-ad77-1fdc2ab05edf",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# %pip install langchain-openai"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8605e87a-2253-4c89-992a-ecdbec955ef6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# %pip install langgraph"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c13dca76",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Requirement already satisfied: regex>=2022.1.18 in /Users/joe.constantino/.pyenv/versions/3.12.2/lib/python3.12/site-packages (from tiktoken<1,>=0.7->langchain-openai->langchain-tableau) (2024.11.6)\r\n",
-      "Requirement already satisfied: httpcore==1.* in /Users/joe.constantino/.pyenv/versions/3.12.2/lib/python3.12/site-packages (from httpx>=0.25.2->langgraph-sdk<0.2.0,>=0.1.42->langgraph->langchain-tableau) (1.0.7)\r\n",
-      "Requirement already satisfied: h11<0.15,>=0.13 in /Users/joe.constantino/.pyenv/versions/3.12.2/lib/python3.12/site-packages (from httpcore==1.*->httpx>=0.25.2->langgraph-sdk<0.2.0,>=0.1.42->langgraph->langchain-tableau) (0.14.0)\r\n"
-     ]
-    }
-   ],
-   "source": [
-    "# %pip install langchain-tableau --upgrade"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "bbaa05f4",
-   "metadata": {},
-   "source": [
-    "Note you may need to restart your kernal to use updated packages"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "80473fcc",
-   "metadata": {},
-   "source": [
-    "### Credentials\n",
-    "\n",
-    "You can declare your environment variables explicitly, as shown in several cases in this doc. However, if these parameters are not provided, the simple_datasource_qa tool will attempt to automatically read them from environment variables.\n",
-    "\n",
-    "For the Data Source that you choose to query, make sure you've updated the VizqlDataApiAccess permission in Tableau to allow the VDS API to access that Data Source via REST. More info [here](https://help.tableau.com/current/server/en-us/permissions_capabilities.htm#data-sources\n",
-    "). "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "310d21b3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# langchain package imports\n",
-    "from langchain_openai import ChatOpenAI\n",
-    "\n",
-    "# langchain_tableau and langgraph imports\n",
-    "from langchain_tableau.tools.simple_datasource_qa import initialize_simple_datasource_qa\n",
-    "from langgraph.prebuilt import create_react_agent"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "596d6718-f2e1-44bb-b614-65447862661c",
-   "metadata": {},
-   "source": [
-    "## Authentication Variables\n",
-    "You can declare your environment variables explicitly, as shown in several cases in this cookbook. However, if these parameters are not provided, the simple_datasource_qa tool will attempt to automatically read them from environment variables.\n",
-    "\n",
-    "For the Data Source that you choose, make sure you've updated the VizqlDataApiAccess permission in Tableau to allow the VDS API to access that Data Source via REST. More info [here](https://help.tableau.com/current/server/en-us/permissions_capabilities.htm#data-sources\n",
-    "). "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "ccfb4159-34ac-4816-a8f0-795c5442c0b2",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "\n",
-    "from dotenv import load_dotenv\n",
-    "\n",
-    "load_dotenv()\n",
-    "\n",
-    "tableau_server = \"https://stage-dataplane2.tableau.sfdc-shbmgi.svc.sfdcfc.net/\"  # replace with your Tableau server name\n",
-    "tableau_site = \"vizqldataservicestage02\"  # replace with your Tableau site\n",
-    "tableau_jwt_client_id = os.getenv(\n",
-    "    \"TABLEAU_JWT_CLIENT_ID\"\n",
-    ")  # a JWT client ID (obtained through Tableau's admin UI)\n",
-    "tableau_jwt_secret_id = os.getenv(\n",
-    "    \"TABLEAU_JWT_SECRET_ID\"\n",
-    ")  # a JWT secret ID (obtained through Tableau's admin UI)\n",
-    "tableau_jwt_secret = os.getenv(\n",
-    "    \"TABLEAU_JWT_SECRET\"\n",
-    ")  # a JWT secret ID (obtained through Tableau's admin UI)\n",
-    "tableau_api_version = \"3.21\"  # the current Tableau REST API Version\n",
-    "tableau_user = \"joe.constantino@salesforce.com\"  # replace with the username querying the target Tableau Data Source\n",
-    "\n",
-    "# For this cookbook we are connecting to the Superstore dataset that comes by default with every Tableau server\n",
-    "datasource_luid = (\n",
-    "    \"0965e61b-a072-43cf-994c-8c6cf526940d\"  # the target data source for this Tool\n",
-    ")\n",
-    "\n",
-    "# Add variables to control LLM models for the Agent and Tools\n",
-    "os.environ[\"OPENAI_API_KEY\"]  # set an your model API key as an environment variable\n",
-    "tooling_llm_model = \"gpt-4o\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "64d08107",
-   "metadata": {},
-   "source": [
-    "## Instantiation\n",
-    "The initialize_simple_datasource_qa initializes the Langgraph tool called [simple_datasource_qa](https://github.com/Tab-SE/tableau_langchain/blob/3ff9047414479cd55d797c18a78f834d57860761/pip_package/langchain_tableau/tools/simple_datasource_qa.py#L101), which can be used for analytical questions and answers on a Tableau Data Source.\n",
-    "\n",
-    "This initializer function:\n",
-    "1. Authenticates to Tableau using Tableau's connected-app framework for JWT-based authentication. All the required variables must be defined at runtime or as environment variables.\n",
-    "2. Asynchronously queries for the field metadata of the target datasource specified in the datasource_luid variable.\n",
-    "3. Grounds on the metadata of the target datasource to transform natural language questions into the json-formatted query payload required to make VDS query-datasource requests.\n",
-    "4. Executes a POST request to VDS.\n",
-    "5. Formats and returns the results in a structured response."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "72ee3eca",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Initalize simple_datasource_qa for querying Tableau Datasources through VDS\n",
-    "analyze_datasource = initialize_simple_datasource_qa(\n",
-    "    domain=tableau_server,\n",
-    "    site=tableau_site,\n",
-    "    jwt_client_id=tableau_jwt_client_id,\n",
-    "    jwt_secret_id=tableau_jwt_secret_id,\n",
-    "    jwt_secret=tableau_jwt_secret,\n",
-    "    tableau_api_version=tableau_api_version,\n",
-    "    tableau_user=tableau_user,\n",
-    "    datasource_luid=datasource_luid,\n",
-    "    tooling_llm_model=tooling_llm_model,\n",
-    ")\n",
-    "\n",
-    "# load the List of Tools to be used by the Agent. In this case we will just load our data source Q&A tool.\n",
-    "tools = [analyze_datasource]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0ac5daa0-4336-48d0-9c26-20bf2c252bad",
-   "metadata": {},
-   "source": [
-    "## Invocation - Langgraph Example\n",
-    "First, we'll initlialize the LLM of our choice. Then, we define an agent using a langgraph agent constructor class and invoke it with a query related to the target data source. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "06a1d3f7-79a8-452e-b37e-9070d15445b0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "Here are the results for the states with the highest sales and profits based on the data queried:\n",
-       "\n",
-       "### States with the Most Sales\n",
-       "1. **California**: $457,687.63\n",
-       "2. **New York**: $310,876.27\n",
-       "3. **Texas**: $170,188.05\n",
-       "4. **Washington**: $138,641.27\n",
-       "5. **Pennsylvania**: $116,511.91\n",
-       "\n",
-       "### States with the Most Profit\n",
-       "1. **California**: $76,381.39\n",
-       "2. **New York**: $74,038.55\n",
-       "3. **Washington**: $33,402.65\n",
-       "4. **Michigan**: $24,463.19\n",
-       "5. **Virginia**: $18,597.95\n",
-       "\n",
-       "### Comparison\n",
-       "- **California** and **New York** are the only states that appear in both lists, indicating they are the top sellers and also generate the most profit.\n",
-       "- **Texas**, while having the third highest sales, does not rank in the top five for profit, showing a potential issue with profitability despite high sales.\n",
-       "\n",
-       "This analysis suggests that high sales do not always correlate with high profits, as seen with Texas."
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from IPython.display import Markdown, display\n",
-    "\n",
-    "model = ChatOpenAI(model=\"gpt-4o-mini\", temperature=0)\n",
-    "\n",
-    "tableauAgent = create_react_agent(model, tools)\n",
-    "\n",
-    "# Run the agent\n",
-    "messages = tableauAgent.invoke(\n",
-    "    {\n",
-    "        \"messages\": [\n",
-    "            (\n",
-    "                \"human\",\n",
-    "                \"which states sell the most? Are those the same states with the most profits?\",\n",
-    "            )\n",
-    "        ]\n",
-    "    }\n",
-    ")\n",
-    "messages\n",
-    "# display(Markdown(messages['messages'][4].content)) #display a nicely formatted answer for successful generations"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e6b20093",
-   "metadata": {},
-   "source": [
-    "## Chaining\n",
-    "\n",
-    "TODO."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "12ab3d7b",
-   "metadata": {},
-   "source": [
-    "## API reference\n",
-    "\n",
-    "TODO."
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python (package_test_env)",
-   "language": "python",
-   "name": "package_test_env"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

docs/docs/integrations/tools/taiga.ipynb

@@ -1,306 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "raw",
-   "id": "10238e62-3465-4973-9279-606cbb7ccf16",
-   "metadata": {},
-   "source": [
-    "---\n",
-    "sidebar_label: Taiga\n",
-    "---"
-   ]
-  },
-  {
-   "metadata": {},
-   "cell_type": "markdown",
-   "source": [
-    "# Taiga\n",
-    "\n",
-    "This notebook provides a quick overview for getting started with Taiga tooling in [langchain_taiga](https://github.com/Shikenso-Analytics/langchain-taiga/blob/main/docs/tools.ipynb). For more details on each tool and configuration, see the docstrings in your repository or relevant doc pages.\n",
-    "\n",
-    "\n",
-    "\n",
-    "## Overview\n",
-    "\n",
-    "### Integration details\n",
-    "\n",
-    "| Class                                                                                                | Package                                                                    | Serializable | JS support |                                        Package latest                                        |\n",
-    "|:-----------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------| :---:        |:------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------:|\n",
-    "| `create_entity_tool`, `search_entities_tool`, `get_entity_by_ref_tool`, `update_entity_by_ref_tool` , `add_comment_by_ref_tool`, `add_attachment_by_ref_tool` | [langchain-taiga](https://github.com/Shikenso-Analytics/langchain-taiga)   | N/A          |                                      TBD                                       | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-taiga?style=flat-square&label=%20) |\n",
-    "\n",
-    "### Tool features\n",
-    "\n",
-    "- **`create_entity_tool`**: Creates user stories, tasks and issues in Taiga.\n",
-    "- **`search_entities_tool`**: Searches for user stories, tasks and issues in Taiga.\n",
-    "- **`get_entity_by_ref_tool`**: Gets a user story, task or issue by reference.\n",
-    "- **`update_entity_by_ref_tool`**: Updates a user story, task or issue by reference.\n",
-    "- **`add_comment_by_ref_tool`**: Adds a comment to a user story, task or issue.\n",
-    "- **`add_attachment_by_ref_tool`**: Adds an attachment to a user story, task or issue.\n",
-    "\n",
-    "## Setup\n",
-    "\n",
-    "The integration lives in the `langchain-taiga` package."
-   ],
-   "id": "41616bfd02d989a6"
-  },
-  {
-   "cell_type": "code",
-   "id": "f85b4089",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-02-28T12:43:23.290414Z",
-     "start_time": "2025-02-28T12:43:23.162563Z"
-    }
-   },
-   "source": "%pip install --quiet -U langchain-taiga",
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "/home/henlein/Workspace/PyCharm/langchain/.venv/bin/python: No module named pip\r\n",
-      "Note: you may need to restart the kernel to use updated packages.\n"
-     ]
-    }
-   ],
-   "execution_count": 3
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b15e9266",
-   "metadata": {},
-   "source": [
-    "### Credentials\n",
-    "\n",
-    "This integration requires you to set `TAIGA_URL`, `TAIGA_API_URL`, `TAIGA_USERNAME`, `TAIGA_PASSWORD` and `OPENAI_API_KEY` as environment variables to authenticate with Taiga.\n",
-    "\n",
-    "```bash\n",
-    "export TAIGA_URL=\"https://taiga.xyz.org/\"\n",
-    "export TAIGA_API_URL=\"https://taiga.xyz.org/\"\n",
-    "export TAIGA_USERNAME=\"username\"\n",
-    "export TAIGA_PASSWORD=\"pw\"\n",
-    "export OPENAI_API_KEY=\"OPENAI_API_KEY\"\n",
-    "```"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "bc5ab717-fd27-4c59-b912-bdd099541478",
-   "metadata": {},
-   "source": [
-    "It's also helpful (but not needed) to set up [LangSmith](https://smith.langchain.com/) for best-in-class observability:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "id": "a6c2f136-6367-4f1f-825d-ae741e1bf281",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-02-28T12:43:23.295879Z",
-     "start_time": "2025-02-28T12:43:23.293809Z"
-    }
-   },
-   "source": [
-    "# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
-    "# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()"
-   ],
-   "outputs": [],
-   "execution_count": 4
-  },
-  {
-   "metadata": {},
-   "cell_type": "markdown",
-   "source": [
-    "## Instantiation\n",
-    "\n",
-    "Below is an example showing how to instantiate the Taiga tools in `langchain_taiga`. Adjust as needed for your specific usage."
-   ],
-   "id": "d6eab61edeeb40a5"
-  },
-  {
-   "metadata": {},
-   "cell_type": "code",
-   "outputs": [],
-   "execution_count": null,
-   "source": [
-    "from langchain_taiga.tools.discord_read_messages import create_entity_tool\n",
-    "from langchain_taiga.tools.discord_send_messages import search_entities_tool\n",
-    "\n",
-    "create_tool = create_entity_tool\n",
-    "search_tool = search_entities_tool"
-   ],
-   "id": "8ae97a3413cd040e"
-  },
-  {
-   "cell_type": "markdown",
-   "id": "74147a1a",
-   "metadata": {},
-   "source": [
-    "## Invocation\n",
-    "\n",
-    "### Direct invocation with args\n",
-    "\n",
-    "Below is a simple example of calling the tool with keyword arguments in a dictionary."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "id": "65310a8b-eb0c-4d9e-a618-4f4abe2414fc",
-   "metadata": {},
-   "source": [
-    "from langchain_taiga.tools.taiga_tools import (\n",
-    "    add_attachment_by_ref_tool,\n",
-    "    add_comment_by_ref_tool,\n",
-    "    create_entity_tool,\n",
-    "    get_entity_by_ref_tool,\n",
-    "    search_entities_tool,\n",
-    "    update_entity_by_ref_tool,\n",
-    ")\n",
-    "\n",
-    "response = create_entity_tool.invoke(\n",
-    "    {\n",
-    "        \"project_slug\": \"slug\",\n",
-    "        \"entity_type\": \"us\",\n",
-    "        \"subject\": \"subject\",\n",
-    "        \"status\": \"new\",\n",
-    "        \"description\": \"desc\",\n",
-    "        \"parent_ref\": 5,\n",
-    "        \"assign_to\": \"user\",\n",
-    "        \"due_date\": \"2022-01-01\",\n",
-    "        \"tags\": [\"tag1\", \"tag2\"],\n",
-    "    }\n",
-    ")\n",
-    "\n",
-    "response = search_entities_tool.invoke(\n",
-    "    {\"project_slug\": \"slug\", \"query\": \"query\", \"entity_type\": \"task\"}\n",
-    ")\n",
-    "\n",
-    "response = get_entity_by_ref_tool.invoke(\n",
-    "    {\"entity_type\": \"user_story\", \"project_id\": 1, \"ref\": \"1\"}\n",
-    ")\n",
-    "\n",
-    "response = update_entity_by_ref_tool.invoke(\n",
-    "    {\"project_slug\": \"slug\", \"entity_ref\": 555, \"entity_type\": \"us\"}\n",
-    ")\n",
-    "\n",
-    "\n",
-    "response = add_comment_by_ref_tool.invoke(\n",
-    "    {\"project_slug\": \"slug\", \"entity_ref\": 3, \"entity_type\": \"us\", \"comment\": \"new\"}\n",
-    ")\n",
-    "\n",
-    "response = add_attachment_by_ref_tool.invoke(\n",
-    "    {\n",
-    "        \"project_slug\": \"slug\",\n",
-    "        \"entity_ref\": 3,\n",
-    "        \"entity_type\": \"us\",\n",
-    "        \"attachment_url\": \"url\",\n",
-    "        \"content_type\": \"png\",\n",
-    "        \"description\": \"desc\",\n",
-    "    }\n",
-    ")"
-   ],
-   "outputs": [],
-   "execution_count": null
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d6e73897",
-   "metadata": {},
-   "source": [
-    "### Invocation with ToolCall\n",
-    "\n",
-    "If you have a model-generated `ToolCall`, pass it to `tool.invoke()` in the format shown below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f90e33a7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# This is usually generated by a model, but we'll create a tool call directly for demo purposes.\n",
-    "model_generated_tool_call = {\n",
-    "    \"args\": {\"project_slug\": \"slug\", \"query\": \"query\", \"entity_type\": \"task\"},\n",
-    "    \"id\": \"1\",\n",
-    "    \"name\": search_entities_tool.name,\n",
-    "    \"type\": \"tool_call\",\n",
-    "}\n",
-    "tool.invoke(model_generated_tool_call)"
-   ]
-  },
-  {
-   "metadata": {},
-   "cell_type": "markdown",
-   "source": [
-    "## Chaining\n",
-    "\n",
-    "Below is a more complete example showing how you might integrate the `create_entity_tool` and `search_entities_tool` tools in a chain or agent with an LLM. This example assumes you have a function (like `create_react_agent`) that sets up a LangChain-style agent capable of calling tools when appropriate.\n",
-    "\n",
-    "\n",
-    "```python\n",
-    "# Example: Using Taiga Tools in an Agent\n",
-    "\n",
-    "from langgraph.prebuilt import create_react_agent\n",
-    "from langchain_taiga.tools.taiga_tools import create_entity_tool, search_entities_tool\n",
-    "\n",
-    "# 1. Instantiate or configure your language model\n",
-    "# (Replace with your actual LLM, e.g., ChatOpenAI(temperature=0))\n",
-    "llm = ...\n",
-    "\n",
-    "# 2. Build an agent that has access to these tools\n",
-    "agent_executor = create_react_agent(llm, [create_entity_tool, search_entities_tool])\n",
-    "\n",
-    "# 4. Formulate a user query that may invoke one or both tools\n",
-    "example_query = \"Please create a new user story with the subject 'subject' in slug project: 'slug'\"\n",
-    "\n",
-    "# 5. Execute the agent in streaming mode (or however your code is structured)\n",
-    "events = agent_executor.stream(\n",
-    "    {\"messages\": [(\"user\", example_query)]},\n",
-    "    stream_mode=\"values\",\n",
-    ")\n",
-    "\n",
-    "# 6. Print out the model's responses (and any tool outputs) as they arrive\n",
-    "for event in events:\n",
-    "    event[\"messages\"][-1].pretty_print()\n",
-    "```\n"
-   ],
-   "id": "8cafefef7c8bd43e"
-  },
-  {
-   "metadata": {},
-   "cell_type": "markdown",
-   "source": [
-    "## API reference\n",
-    "\n",
-    "See the docstrings in:\n",
-    "- [taiga_tools.py](https://github.com/Shikenso-Analytics/langchain-taiga/blob/main/langchain_taiga/tools/taiga_tools.py)\n",
-    "- [toolkits.py](https://github.com/Shikenso-Analytics/langchain-taiga/blob/main/langchain_taiga/toolkits.py)\n",
-    "\n",
-    "for usage details, parameters, and advanced configurations."
-   ],
-   "id": "4ac8146c"
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.9"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

docs/docs/integrations/tools/writer.ipynb

@@ -14,9 +14,9 @@
     "\n",
     "### Integration details\n",
     "\n",
-    "| Class                                                                                                      | Package          | Local | Serializable | JS support |                                        Package downloads                                         |                                        Package latest                                         |\n",
-    "|:-----------------------------------------------------------------------------------------------------------|:-----------------| :---: | :---: |:----------:|:------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|\n",
-    "| [GraphTool](https://github.com/writer/langchain-writer/blob/main/langchain_writer/tools.py#L9) | [langchain-writer](https://pypi.org/project/langchain-writer/) |      ❌       |                                       ❌                                       | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-writer?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-writer?style=flat-square&label=%20) |\n",
+    "| Class                                                                                                                                      | Package          | Local | Serializable | JS support |                                        Package downloads                                         |                                        Package latest                                         |\n",
+    "|:-------------------------------------------------------------------------------------------------------------------------------------------|:-----------------| :---: | :---: |:----------:|:------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|\n",
+    "| GraphTool                                                                                                                                  | [langchain-writer](https://pypi.org/project/langchain-writer/) |      ❌       |                                       ❌                                       | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-writer?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-writer?style=flat-square&label=%20) |\n",
     "\n",
     "### Features\n",
     "\n",
@@ -43,17 +43,17 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "80d4e1a791aaa8",
    "metadata": {},
+   "outputs": [],
    "source": [
     "import getpass\n",
     "import os\n",
     "\n",
     "if not os.getenv(\"WRITER_API_KEY\"):\n",
     "    os.environ[\"WRITER_API_KEY\"] = getpass.getpass(\"Enter your Writer API key: \")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -77,8 +77,10 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "6faaae25509f0f28",
    "metadata": {},
+   "outputs": [],
    "source": [
     "from langchain_writer.chat_models import ChatWriter\n",
     "from langchain_writer.tools import GraphTool\n",
@@ -87,9 +89,7 @@
     "\n",
     "graph_id = getpass.getpass(\"Enter Writer Knowledge Graph ID: \")\n",
     "graph_tool = GraphTool(graph_ids=[graph_id])"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -99,8 +99,10 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "e98d7deedb0e5c6f",
    "metadata": {},
+   "outputs": [],
    "source": [
     "from typing import Optional\n",
     "\n",
@@ -152,9 +154,7 @@
     "        },\n",
     "    },\n",
     "}"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -167,15 +167,15 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "a4833f2597a87777",
    "metadata": {},
+   "outputs": [],
    "source": [
     "chat.bind_tools(\n",
     "    [graph_tool, get_supercopa_trophies_count, GetWeather, get_product_info]\n",
     ")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -187,13 +187,13 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "ccb61b945a56672b",
    "metadata": {},
+   "outputs": [],
    "source": [
     "chat.tools"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -205,13 +205,13 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "381f0d4b9a8357a4",
    "metadata": {},
+   "outputs": [],
    "source": [
     "chat.tool_choice"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -225,8 +225,10 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "74df06b58b5dc2e9",
    "metadata": {},
+   "outputs": [],
    "source": [
     "from langchain_core.messages import HumanMessage\n",
     "\n",
@@ -238,9 +240,7 @@
     "\n",
     "response = chat.invoke(messages)\n",
     "messages.append(response)"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -252,13 +252,13 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "e271e0fc677446b2",
    "metadata": {},
+   "outputs": [],
    "source": [
     "print(response.tool_calls)"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -270,8 +270,10 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "156b58108aa9b367",
    "metadata": {},
+   "outputs": [],
    "source": [
     "for tool_call in response.tool_calls:\n",
     "    selected_tool = {\n",
@@ -282,9 +284,7 @@
     "\n",
     "response = chat.invoke(messages)\n",
     "print(response.content)"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -296,13 +296,13 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "4b3c6f05096fc9e3",
    "metadata": {},
+   "outputs": [],
    "source": [
     "print(response.additional_kwargs[\"graph_data\"])"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -314,13 +314,13 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "id": "eb6e0da74b10b8fc",
    "metadata": {},
+   "outputs": [],
    "source": [
     "print(response.content)"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -329,7 +329,7 @@
    "source": [
     "## Chaining\n",
     "\n",
-    "Due to specificity of Writer Graph tool (you don't need to call it manually, Writer server will call it by himself and return RAG based generation) it's impossible to invoke it separately, so GraphTool can't be used as part of chain"
+    "#TODO: fill chaining section"
    ]
   },
   {

docs/docs/tutorials/qa_chat_history.ipynb

@@ -19,7 +19,7 @@
     "\n",
     "In many Q&A applications we want to allow the user to have a back-and-forth conversation, meaning the application needs some sort of \"memory\" of past questions and answers, and some logic for incorporating those into its current thinking.\n",
     "\n",
-    "This is the second part of a multi-part tutorial:\n",
+    "This is a the second part of a multi-part tutorial:\n",
     "\n",
     "- [Part 1](/docs/tutorials/rag) introduces RAG and walks through a minimal implementation.\n",
     "- [Part 2](/docs/tutorials/qa_chat_history) (this guide) extends the implementation to accommodate conversation-style interactions and multi-step retrieval processes.\n",

docs/src/theme/ChatModelTabs.js

@@ -211,13 +211,6 @@ ${llmVarName} = ChatWatsonx(
       apiKeyName: "DATABRICKS_TOKEN",
       packageName: "databricks-langchain",
     },
-    {
-      value: "xai",
-      label: "xAI",
-      model: "grok-2",
-      apiKeyName: "XAI_API_KEY",
-      packageName: "langchain-xai",
-    },
   ].map((item) => ({
     ...item,
     ...overrideParams?.[item.value],

docs/src/theme/FeatureTables.js

@@ -888,13 +888,6 @@ const FEATURE_TABLES = {
                 api: "Package",
                 apiLink: "https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PyMuPDFLoader.html"
             },
-            {
-                name: "PyMuPDF4LLM",
-                link: "pymupdf4llm",
-                source: "Load PDF content to Markdown using PyMuPDF4LLM",
-                api: "Package",
-                apiLink: "https://github.com/lakinduboteju/langchain-pymupdf4llm"
-            },
             {
                 name: "PDFMiner",
                 link: "pdfminer",

docs/vercel_overrides.txt

@@ -1,2 +1 @@
-httpx
-grpcio
+httpx

libs/cli/Makefile

@@ -48,5 +48,4 @@ _e2e_test:
 			poetry run pip install -e ../../../standard-tests && \
 			make format lint tests && \
 			poetry install --with test_integration && \
-			poetry run pip install -e ../../../core && \
 			make integration_test 

libs/cli/pyproject.toml

@@ -15,7 +15,7 @@ dependencies = [
     "gritql<1.0.0,>=0.2.0",
 ]
 name = "langchain-cli"
-version = "0.0.36"
+version = "0.0.35"
 description = "CLI for interacting with LangChain"
 readme = "README.md"
 
@@ -31,12 +31,11 @@ langchain-cli = "langchain_cli.cli:app"
 [dependency-groups]
 dev = ["pytest<8.0.0,>=7.4.2", "pytest-watch<5.0.0,>=4.2.0"]
 lint = ["ruff<1.0,>=0.5", "mypy<2.0.0,>=1.13.0"]
-test = ["langchain-core", "langchain"]
+test = ["langchain"]
 typing = ["langchain"]
 test_integration = []
 
 [tool.uv.sources]
-langchain-core = { path = "../core", editable = true }
 langchain = { path = "../langchain", editable = true }
 
 [tool.ruff.lint]

libs/cli/uv.lock

@@ -6,6 +6,120 @@ resolution-markers = [
     "python_full_version < '3.12'",
 ]
 
+[[package]]
+name = "aiohappyeyeballs"
+version = "2.4.4"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/7f/55/e4373e888fdacb15563ef6fa9fa8c8252476ea071e96fb46defac9f18bf2/aiohappyeyeballs-2.4.4.tar.gz", hash = "sha256:5fdd7d87889c63183afc18ce9271f9b0a7d32c2303e394468dd45d514a757745", size = 21977 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/b9/74/fbb6559de3607b3300b9be3cc64e97548d55678e44623db17820dbd20002/aiohappyeyeballs-2.4.4-py3-none-any.whl", hash = "sha256:a980909d50efcd44795c4afeca523296716d50cd756ddca6af8c65b996e27de8", size = 14756 },
+]
+
+[[package]]
+name = "aiohttp"
+version = "3.11.11"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "aiohappyeyeballs" },
+    { name = "aiosignal" },
+    { name = "async-timeout", marker = "python_full_version < '3.11'" },
+    { name = "attrs" },
+    { name = "frozenlist" },
+    { name = "multidict" },
+    { name = "propcache" },
+    { name = "yarl" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/fe/ed/f26db39d29cd3cb2f5a3374304c713fe5ab5a0e4c8ee25a0c45cc6adf844/aiohttp-3.11.11.tar.gz", hash = "sha256:bb49c7f1e6ebf3821a42d81d494f538107610c3a705987f53068546b0e90303e", size = 7669618 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/75/7d/ff2e314b8f9e0b1df833e2d4778eaf23eae6b8cc8f922495d110ddcbf9e1/aiohttp-3.11.11-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a60804bff28662cbcf340a4d61598891f12eea3a66af48ecfdc975ceec21e3c8", size = 708550 },
+    { url = "https://files.pythonhosted.org/packages/09/b8/aeb4975d5bba233d6f246941f5957a5ad4e3def8b0855a72742e391925f2/aiohttp-3.11.11-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:4b4fa1cb5f270fb3eab079536b764ad740bb749ce69a94d4ec30ceee1b5940d5", size = 468430 },
+    { url = "https://files.pythonhosted.org/packages/9c/5b/5b620279b3df46e597008b09fa1e10027a39467387c2332657288e25811a/aiohttp-3.11.11-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:731468f555656767cda219ab42e033355fe48c85fbe3ba83a349631541715ba2", size = 455593 },
+    { url = "https://files.pythonhosted.org/packages/d8/75/0cdf014b816867d86c0bc26f3d3e3f194198dbf33037890beed629cd4f8f/aiohttp-3.11.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cb23d8bb86282b342481cad4370ea0853a39e4a32a0042bb52ca6bdde132df43", size = 1584635 },
+    { url = "https://files.pythonhosted.org/packages/df/2f/95b8f4e4dfeb57c1d9ad9fa911ede35a0249d75aa339edd2c2270dc539da/aiohttp-3.11.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f047569d655f81cb70ea5be942ee5d4421b6219c3f05d131f64088c73bb0917f", size = 1632363 },
+    { url = "https://files.pythonhosted.org/packages/39/cb/70cf69ea7c50f5b0021a84f4c59c3622b2b3b81695f48a2f0e42ef7eba6e/aiohttp-3.11.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dd7659baae9ccf94ae5fe8bfaa2c7bc2e94d24611528395ce88d009107e00c6d", size = 1668315 },
+    { url = "https://files.pythonhosted.org/packages/2f/cc/3a3fc7a290eabc59839a7e15289cd48f33dd9337d06e301064e1e7fb26c5/aiohttp-3.11.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:af01e42ad87ae24932138f154105e88da13ce7d202a6de93fafdafb2883a00ef", size = 1589546 },
+    { url = "https://files.pythonhosted.org/packages/15/b4/0f7b0ed41ac6000e283e7332f0f608d734b675a8509763ca78e93714cfb0/aiohttp-3.11.11-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5854be2f3e5a729800bac57a8d76af464e160f19676ab6aea74bde18ad19d438", size = 1544581 },
+    { url = "https://files.pythonhosted.org/packages/58/b9/4d06470fd85c687b6b0e31935ef73dde6e31767c9576d617309a2206556f/aiohttp-3.11.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:6526e5fb4e14f4bbf30411216780c9967c20c5a55f2f51d3abd6de68320cc2f3", size = 1529256 },
+    { url = "https://files.pythonhosted.org/packages/61/a2/6958b1b880fc017fd35f5dfb2c26a9a50c755b75fd9ae001dc2236a4fb79/aiohttp-3.11.11-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:85992ee30a31835fc482468637b3e5bd085fa8fe9392ba0bdcbdc1ef5e9e3c55", size = 1536592 },
+    { url = "https://files.pythonhosted.org/packages/0f/dd/b974012a9551fd654f5bb95a6dd3f03d6e6472a17e1a8216dd42e9638d6c/aiohttp-3.11.11-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:88a12ad8ccf325a8a5ed80e6d7c3bdc247d66175afedbe104ee2aaca72960d8e", size = 1607446 },
+    { url = "https://files.pythonhosted.org/packages/e0/d3/6c98fd87e638e51f074a3f2061e81fcb92123bcaf1439ac1b4a896446e40/aiohttp-3.11.11-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:0a6d3fbf2232e3a08c41eca81ae4f1dff3d8f1a30bae415ebe0af2d2458b8a33", size = 1628809 },
+    { url = "https://files.pythonhosted.org/packages/a8/2e/86e6f85cbca02be042c268c3d93e7f35977a0e127de56e319bdd1569eaa8/aiohttp-3.11.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:84a585799c58b795573c7fa9b84c455adf3e1d72f19a2bf498b54a95ae0d194c", size = 1564291 },
+    { url = "https://files.pythonhosted.org/packages/0b/8d/1f4ef3503b767717f65e1f5178b0173ab03cba1a19997ebf7b052161189f/aiohttp-3.11.11-cp310-cp310-win32.whl", hash = "sha256:bfde76a8f430cf5c5584553adf9926534352251d379dcb266ad2b93c54a29745", size = 416601 },
+    { url = "https://files.pythonhosted.org/packages/ad/86/81cb83691b5ace3d9aa148dc42bacc3450d749fc88c5ec1973573c1c1779/aiohttp-3.11.11-cp310-cp310-win_amd64.whl", hash = "sha256:0fd82b8e9c383af11d2b26f27a478640b6b83d669440c0a71481f7c865a51da9", size = 442007 },
+    { url = "https://files.pythonhosted.org/packages/34/ae/e8806a9f054e15f1d18b04db75c23ec38ec954a10c0a68d3bd275d7e8be3/aiohttp-3.11.11-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:ba74ec819177af1ef7f59063c6d35a214a8fde6f987f7661f4f0eecc468a8f76", size = 708624 },
+    { url = "https://files.pythonhosted.org/packages/c7/e0/313ef1a333fb4d58d0c55a6acb3cd772f5d7756604b455181049e222c020/aiohttp-3.11.11-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4af57160800b7a815f3fe0eba9b46bf28aafc195555f1824555fa2cfab6c1538", size = 468507 },
+    { url = "https://files.pythonhosted.org/packages/a9/60/03455476bf1f467e5b4a32a465c450548b2ce724eec39d69f737191f936a/aiohttp-3.11.11-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ffa336210cf9cd8ed117011085817d00abe4c08f99968deef0013ea283547204", size = 455571 },
+    { url = "https://files.pythonhosted.org/packages/be/f9/469588603bd75bf02c8ffb8c8a0d4b217eed446b49d4a767684685aa33fd/aiohttp-3.11.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:81b8fe282183e4a3c7a1b72f5ade1094ed1c6345a8f153506d114af5bf8accd9", size = 1685694 },
+    { url = "https://files.pythonhosted.org/packages/88/b9/1b7fa43faf6c8616fa94c568dc1309ffee2b6b68b04ac268e5d64b738688/aiohttp-3.11.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3af41686ccec6a0f2bdc66686dc0f403c41ac2089f80e2214a0f82d001052c03", size = 1743660 },
+    { url = "https://files.pythonhosted.org/packages/2a/8b/0248d19dbb16b67222e75f6aecedd014656225733157e5afaf6a6a07e2e8/aiohttp-3.11.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:70d1f9dde0e5dd9e292a6d4d00058737052b01f3532f69c0c65818dac26dc287", size = 1785421 },
+    { url = "https://files.pythonhosted.org/packages/c4/11/f478e071815a46ca0a5ae974651ff0c7a35898c55063305a896e58aa1247/aiohttp-3.11.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:249cc6912405917344192b9f9ea5cd5b139d49e0d2f5c7f70bdfaf6b4dbf3a2e", size = 1675145 },
+    { url = "https://files.pythonhosted.org/packages/26/5d/284d182fecbb5075ae10153ff7374f57314c93a8681666600e3a9e09c505/aiohttp-3.11.11-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0eb98d90b6690827dcc84c246811feeb4e1eea683c0eac6caed7549be9c84665", size = 1619804 },
+    { url = "https://files.pythonhosted.org/packages/1b/78/980064c2ad685c64ce0e8aeeb7ef1e53f43c5b005edcd7d32e60809c4992/aiohttp-3.11.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:ec82bf1fda6cecce7f7b915f9196601a1bd1a3079796b76d16ae4cce6d0ef89b", size = 1654007 },
+    { url = "https://files.pythonhosted.org/packages/21/8d/9e658d63b1438ad42b96f94da227f2e2c1d5c6001c9e8ffcc0bfb22e9105/aiohttp-3.11.11-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:9fd46ce0845cfe28f108888b3ab17abff84ff695e01e73657eec3f96d72eef34", size = 1650022 },
+    { url = "https://files.pythonhosted.org/packages/85/fd/a032bf7f2755c2df4f87f9effa34ccc1ef5cea465377dbaeef93bb56bbd6/aiohttp-3.11.11-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:bd176afcf8f5d2aed50c3647d4925d0db0579d96f75a31e77cbaf67d8a87742d", size = 1732899 },
+    { url = "https://files.pythonhosted.org/packages/c5/0c/c2b85fde167dd440c7ba50af2aac20b5a5666392b174df54c00f888c5a75/aiohttp-3.11.11-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:ec2aa89305006fba9ffb98970db6c8221541be7bee4c1d027421d6f6df7d1ce2", size = 1755142 },
+    { url = "https://files.pythonhosted.org/packages/bc/78/91ae1a3b3b3bed8b893c5d69c07023e151b1c95d79544ad04cf68f596c2f/aiohttp-3.11.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:92cde43018a2e17d48bb09c79e4d4cb0e236de5063ce897a5e40ac7cb4878773", size = 1692736 },
+    { url = "https://files.pythonhosted.org/packages/77/89/a7ef9c4b4cdb546fcc650ca7f7395aaffbd267f0e1f648a436bec33c9b95/aiohttp-3.11.11-cp311-cp311-win32.whl", hash = "sha256:aba807f9569455cba566882c8938f1a549f205ee43c27b126e5450dc9f83cc62", size = 416418 },
+    { url = "https://files.pythonhosted.org/packages/fc/db/2192489a8a51b52e06627506f8ac8df69ee221de88ab9bdea77aa793aa6a/aiohttp-3.11.11-cp311-cp311-win_amd64.whl", hash = "sha256:ae545f31489548c87b0cced5755cfe5a5308d00407000e72c4fa30b19c3220ac", size = 442509 },
+    { url = "https://files.pythonhosted.org/packages/69/cf/4bda538c502f9738d6b95ada11603c05ec260807246e15e869fc3ec5de97/aiohttp-3.11.11-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:e595c591a48bbc295ebf47cb91aebf9bd32f3ff76749ecf282ea7f9f6bb73886", size = 704666 },
+    { url = "https://files.pythonhosted.org/packages/46/7b/87fcef2cad2fad420ca77bef981e815df6904047d0a1bd6aeded1b0d1d66/aiohttp-3.11.11-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:3ea1b59dc06396b0b424740a10a0a63974c725b1c64736ff788a3689d36c02d2", size = 464057 },
+    { url = "https://files.pythonhosted.org/packages/5a/a6/789e1f17a1b6f4a38939fbc39d29e1d960d5f89f73d0629a939410171bc0/aiohttp-3.11.11-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8811f3f098a78ffa16e0ea36dffd577eb031aea797cbdba81be039a4169e242c", size = 455996 },
+    { url = "https://files.pythonhosted.org/packages/b7/dd/485061fbfef33165ce7320db36e530cd7116ee1098e9c3774d15a732b3fd/aiohttp-3.11.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bd7227b87a355ce1f4bf83bfae4399b1f5bb42e0259cb9405824bd03d2f4336a", size = 1682367 },
+    { url = "https://files.pythonhosted.org/packages/e9/d7/9ec5b3ea9ae215c311d88b2093e8da17e67b8856673e4166c994e117ee3e/aiohttp-3.11.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d40f9da8cabbf295d3a9dae1295c69975b86d941bc20f0a087f0477fa0a66231", size = 1736989 },
+    { url = "https://files.pythonhosted.org/packages/d6/fb/ea94927f7bfe1d86178c9d3e0a8c54f651a0a655214cce930b3c679b8f64/aiohttp-3.11.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ffb3dc385f6bb1568aa974fe65da84723210e5d9707e360e9ecb51f59406cd2e", size = 1793265 },
+    { url = "https://files.pythonhosted.org/packages/40/7f/6de218084f9b653026bd7063cd8045123a7ba90c25176465f266976d8c82/aiohttp-3.11.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a8f5f7515f3552d899c61202d99dcb17d6e3b0de777900405611cd747cecd1b8", size = 1691841 },
+    { url = "https://files.pythonhosted.org/packages/77/e2/992f43d87831cbddb6b09c57ab55499332f60ad6fdbf438ff4419c2925fc/aiohttp-3.11.11-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3499c7ffbfd9c6a3d8d6a2b01c26639da7e43d47c7b4f788016226b1e711caa8", size = 1619317 },
+    { url = "https://files.pythonhosted.org/packages/96/74/879b23cdd816db4133325a201287c95bef4ce669acde37f8f1b8669e1755/aiohttp-3.11.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8e2bf8029dbf0810c7bfbc3e594b51c4cc9101fbffb583a3923aea184724203c", size = 1641416 },
+    { url = "https://files.pythonhosted.org/packages/30/98/b123f6b15d87c54e58fd7ae3558ff594f898d7f30a90899718f3215ad328/aiohttp-3.11.11-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:b6212a60e5c482ef90f2d788835387070a88d52cf6241d3916733c9176d39eab", size = 1646514 },
+    { url = "https://files.pythonhosted.org/packages/d7/38/257fda3dc99d6978ab943141d5165ec74fd4b4164baa15e9c66fa21da86b/aiohttp-3.11.11-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:d119fafe7b634dbfa25a8c597718e69a930e4847f0b88e172744be24515140da", size = 1702095 },
+    { url = "https://files.pythonhosted.org/packages/0c/f4/ddab089053f9fb96654df5505c0a69bde093214b3c3454f6bfdb1845f558/aiohttp-3.11.11-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:6fba278063559acc730abf49845d0e9a9e1ba74f85f0ee6efd5803f08b285853", size = 1734611 },
+    { url = "https://files.pythonhosted.org/packages/c3/d6/f30b2bc520c38c8aa4657ed953186e535ae84abe55c08d0f70acd72ff577/aiohttp-3.11.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:92fc484e34b733704ad77210c7957679c5c3877bd1e6b6d74b185e9320cc716e", size = 1694576 },
+    { url = "https://files.pythonhosted.org/packages/bc/97/b0a88c3f4c6d0020b34045ee6d954058abc870814f6e310c4c9b74254116/aiohttp-3.11.11-cp312-cp312-win32.whl", hash = "sha256:9f5b3c1ed63c8fa937a920b6c1bec78b74ee09593b3f5b979ab2ae5ef60d7600", size = 411363 },
+    { url = "https://files.pythonhosted.org/packages/7f/23/cc36d9c398980acaeeb443100f0216f50a7cfe20c67a9fd0a2f1a5a846de/aiohttp-3.11.11-cp312-cp312-win_amd64.whl", hash = "sha256:1e69966ea6ef0c14ee53ef7a3d68b564cc408121ea56c0caa2dc918c1b2f553d", size = 437666 },
+    { url = "https://files.pythonhosted.org/packages/49/d1/d8af164f400bad432b63e1ac857d74a09311a8334b0481f2f64b158b50eb/aiohttp-3.11.11-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:541d823548ab69d13d23730a06f97460f4238ad2e5ed966aaf850d7c369782d9", size = 697982 },
+    { url = "https://files.pythonhosted.org/packages/92/d1/faad3bf9fa4bfd26b95c69fc2e98937d52b1ff44f7e28131855a98d23a17/aiohttp-3.11.11-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:929f3ed33743a49ab127c58c3e0a827de0664bfcda566108989a14068f820194", size = 460662 },
+    { url = "https://files.pythonhosted.org/packages/db/61/0d71cc66d63909dabc4590f74eba71f91873a77ea52424401c2498d47536/aiohttp-3.11.11-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:0882c2820fd0132240edbb4a51eb8ceb6eef8181db9ad5291ab3332e0d71df5f", size = 452950 },
+    { url = "https://files.pythonhosted.org/packages/07/db/6d04bc7fd92784900704e16b745484ef45b77bd04e25f58f6febaadf7983/aiohttp-3.11.11-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b63de12e44935d5aca7ed7ed98a255a11e5cb47f83a9fded7a5e41c40277d104", size = 1665178 },
+    { url = "https://files.pythonhosted.org/packages/54/5c/e95ade9ae29f375411884d9fd98e50535bf9fe316c9feb0f30cd2ac8f508/aiohttp-3.11.11-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:aa54f8ef31d23c506910c21163f22b124facb573bff73930735cf9fe38bf7dff", size = 1717939 },
+    { url = "https://files.pythonhosted.org/packages/6f/1c/1e7d5c5daea9e409ed70f7986001b8c9e3a49a50b28404498d30860edab6/aiohttp-3.11.11-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a344d5dc18074e3872777b62f5f7d584ae4344cd6006c17ba12103759d407af3", size = 1775125 },
+    { url = "https://files.pythonhosted.org/packages/5d/66/890987e44f7d2f33a130e37e01a164168e6aff06fce15217b6eaf14df4f6/aiohttp-3.11.11-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0b7fb429ab1aafa1f48578eb315ca45bd46e9c37de11fe45c7f5f4138091e2f1", size = 1677176 },
+    { url = "https://files.pythonhosted.org/packages/8f/dc/e2ba57d7a52df6cdf1072fd5fa9c6301a68e1cd67415f189805d3eeb031d/aiohttp-3.11.11-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c341c7d868750e31961d6d8e60ff040fb9d3d3a46d77fd85e1ab8e76c3e9a5c4", size = 1603192 },
+    { url = "https://files.pythonhosted.org/packages/6c/9e/8d08a57de79ca3a358da449405555e668f2c8871a7777ecd2f0e3912c272/aiohttp-3.11.11-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ed9ee95614a71e87f1a70bc81603f6c6760128b140bc4030abe6abaa988f1c3d", size = 1618296 },
+    { url = "https://files.pythonhosted.org/packages/56/51/89822e3ec72db352c32e7fc1c690370e24e231837d9abd056490f3a49886/aiohttp-3.11.11-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:de8d38f1c2810fa2a4f1d995a2e9c70bb8737b18da04ac2afbf3971f65781d87", size = 1616524 },
+    { url = "https://files.pythonhosted.org/packages/2c/fa/e2e6d9398f462ffaa095e84717c1732916a57f1814502929ed67dd7568ef/aiohttp-3.11.11-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:a9b7371665d4f00deb8f32208c7c5e652059b0fda41cf6dbcac6114a041f1cc2", size = 1685471 },
+    { url = "https://files.pythonhosted.org/packages/ae/5f/6bb976e619ca28a052e2c0ca7b0251ccd893f93d7c24a96abea38e332bf6/aiohttp-3.11.11-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:620598717fce1b3bd14dd09947ea53e1ad510317c85dda2c9c65b622edc96b12", size = 1715312 },
+    { url = "https://files.pythonhosted.org/packages/79/c1/756a7e65aa087c7fac724d6c4c038f2faaa2a42fe56dbc1dd62a33ca7213/aiohttp-3.11.11-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:bf8d9bfee991d8acc72d060d53860f356e07a50f0e0d09a8dfedea1c554dd0d5", size = 1672783 },
+    { url = "https://files.pythonhosted.org/packages/73/ba/a6190ebb02176c7f75e6308da31f5d49f6477b651a3dcfaaaca865a298e2/aiohttp-3.11.11-cp313-cp313-win32.whl", hash = "sha256:9d73ee3725b7a737ad86c2eac5c57a4a97793d9f442599bea5ec67ac9f4bdc3d", size = 410229 },
+    { url = "https://files.pythonhosted.org/packages/b8/62/c9fa5bafe03186a0e4699150a7fed9b1e73240996d0d2f0e5f70f3fdf471/aiohttp-3.11.11-cp313-cp313-win_amd64.whl", hash = "sha256:c7a06301c2fb096bdb0bd25fe2011531c1453b9f2c163c8031600ec73af1cc99", size = 436081 },
+    { url = "https://files.pythonhosted.org/packages/9f/37/326ee86b7640be6ca4493c8121cb9a4386e07cf1e5757ce6b7fa854d0a5f/aiohttp-3.11.11-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:3e23419d832d969f659c208557de4a123e30a10d26e1e14b73431d3c13444c2e", size = 709424 },
+    { url = "https://files.pythonhosted.org/packages/9c/c5/a88ec2160b06c22e57e483a1f78f99f005fcd4e7d6855a2d3d6510881b65/aiohttp-3.11.11-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:21fef42317cf02e05d3b09c028712e1d73a9606f02467fd803f7c1f39cc59add", size = 468907 },
+    { url = "https://files.pythonhosted.org/packages/b2/f0/02f03f818e91996161cce200241b631bb2b4a87e61acddb5b974e254a288/aiohttp-3.11.11-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:1f21bb8d0235fc10c09ce1d11ffbd40fc50d3f08a89e4cf3a0c503dc2562247a", size = 455981 },
+    { url = "https://files.pythonhosted.org/packages/0e/17/c8be12436ec19915f67b1ab8240d4105aba0f7e0894a1f0d8939c3e79c70/aiohttp-3.11.11-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1642eceeaa5ab6c9b6dfeaaa626ae314d808188ab23ae196a34c9d97efb68350", size = 1587395 },
+    { url = "https://files.pythonhosted.org/packages/43/c0/f4db1ac30ebe855b2fefd6fa98767862d88ac54ab08a6ad07d619146270c/aiohttp-3.11.11-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2170816e34e10f2fd120f603e951630f8a112e1be3b60963a1f159f5699059a6", size = 1636243 },
+    { url = "https://files.pythonhosted.org/packages/ea/a7/9acf20e9a09b0d38b5b55691410500d051a9f4194692cac22b0d0fc92ad9/aiohttp-3.11.11-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8be8508d110d93061197fd2d6a74f7401f73b6d12f8822bbcd6d74f2b55d71b1", size = 1672323 },
+    { url = "https://files.pythonhosted.org/packages/f7/5b/a27e8fe1a3b0e245ca80863eefd83fc00136752d27d2cf1afa0130a76f34/aiohttp-3.11.11-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4eed954b161e6b9b65f6be446ed448ed3921763cc432053ceb606f89d793927e", size = 1589521 },
+    { url = "https://files.pythonhosted.org/packages/25/50/8bccd08004e15906791b46f0a908a8e7f5e0c5882b17da96d1933bd34ac0/aiohttp-3.11.11-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d6c9af134da4bc9b3bd3e6a70072509f295d10ee60c697826225b60b9959acdd", size = 1544059 },
+    { url = "https://files.pythonhosted.org/packages/84/5a/42250b37b06ee0cb7a03dd1630243b1d739ca3edb5abd8b18f479a539900/aiohttp-3.11.11-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:44167fc6a763d534a6908bdb2592269b4bf30a03239bcb1654781adf5e49caf1", size = 1530217 },
+    { url = "https://files.pythonhosted.org/packages/18/08/eb334da86cd2cdbd0621bb7039255b19ca74ce8b05e8fb61850e2589938c/aiohttp-3.11.11-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:479b8c6ebd12aedfe64563b85920525d05d394b85f166b7873c8bde6da612f9c", size = 1536081 },
+    { url = "https://files.pythonhosted.org/packages/1a/a9/9d59958084d5bad7e77a44841013bd59768cda94f9f744769461b66038fc/aiohttp-3.11.11-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:10b4ff0ad793d98605958089fabfa350e8e62bd5d40aa65cdc69d6785859f94e", size = 1606918 },
+    { url = "https://files.pythonhosted.org/packages/4f/e7/27feb1cff17dcddb7a5b703199106196718d622a3aa70f80a386d15361d7/aiohttp-3.11.11-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:b540bd67cfb54e6f0865ceccd9979687210d7ed1a1cc8c01f8e67e2f1e883d28", size = 1629101 },
+    { url = "https://files.pythonhosted.org/packages/e8/29/49debcd858b997c655fca274c5247fcfe29bf31a4ddb1ce3f088539b14e4/aiohttp-3.11.11-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1dac54e8ce2ed83b1f6b1a54005c87dfed139cf3f777fdc8afc76e7841101226", size = 1567338 },
+    { url = "https://files.pythonhosted.org/packages/3b/34/33af1e97aba1862e1812e2e2b96a1e050c5a6e9cecd5a5370591122fb07b/aiohttp-3.11.11-cp39-cp39-win32.whl", hash = "sha256:568c1236b2fde93b7720f95a890741854c1200fba4a3471ff48b2934d2d93fd3", size = 416914 },
+    { url = "https://files.pythonhosted.org/packages/2d/47/28b3fbd97026963af2774423c64341e0d4ec180ea3b79a2762a3c18d5d94/aiohttp-3.11.11-cp39-cp39-win_amd64.whl", hash = "sha256:943a8b052e54dfd6439fd7989f67fc6a7f2138d0a2cf0a7de5f18aa4fe7eb3b1", size = 442225 },
+]
+
+[[package]]
+name = "aiosignal"
+version = "1.3.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "frozenlist" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ba/b5/6d55e80f6d8a08ce22b982eafa278d823b541c925f11ee774b0b9c43473d/aiosignal-1.3.2.tar.gz", hash = "sha256:a8c255c66fafb1e499c9351d0bf32ff2d8a0321595ebac3b93713656d2436f54", size = 19424 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/ec/6a/bc7e17a3e87a2985d3e8f4da4cd0f481060eb78fb08596c42be62c90a4d9/aiosignal-1.3.2-py2.py3-none-any.whl", hash = "sha256:45cde58e409a301715980c2b01d0c28bdde3770d8290b5eb2173759d9acb31a5", size = 7597 },
+]
+
 [[package]]
 name = "annotated-types"
 version = "0.7.0"
@@ -39,6 +153,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a7/fa/e01228c2938de91d47b307831c62ab9e4001e747789d0b05baf779a6488c/async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028", size = 5721 },
 ]
 
+[[package]]
+name = "attrs"
+version = "25.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/49/7c/fdf464bcc51d23881d110abd74b512a42b3d5d376a55a831b44c603ae17f/attrs-25.1.0.tar.gz", hash = "sha256:1c97078a80c814273a76b2a298a932eb681c87415c11dee0a6921de7f1b02c3e", size = 810562 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/fc/30/d4986a882011f9df997a55e6becd864812ccfcd821d64aac8570ee39f719/attrs-25.1.0-py3-none-any.whl", hash = "sha256:c75a69e28a550a7e93789579c22aa26b0f5b83b75dc4e08fe092980051e1090a", size = 63152 },
+]
+
 [[package]]
 name = "certifi"
 version = "2025.1.31"
@@ -241,6 +364,90 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/8f/7d/2d6ce181d7a5f51dedb8c06206cbf0ec026a99bf145edd309f9e17c3282f/fastapi-0.115.8-py3-none-any.whl", hash = "sha256:753a96dd7e036b34eeef8babdfcfe3f28ff79648f86551eb36bfc1b0bf4a8cbf", size = 94814 },
 ]
 
+[[package]]
+name = "frozenlist"
+version = "1.5.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/8f/ed/0f4cec13a93c02c47ec32d81d11c0c1efbadf4a471e3f3ce7cad366cbbd3/frozenlist-1.5.0.tar.gz", hash = "sha256:81d5af29e61b9c8348e876d442253723928dce6433e0e76cd925cd83f1b4b817", size = 39930 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/54/79/29d44c4af36b2b240725dce566b20f63f9b36ef267aaaa64ee7466f4f2f8/frozenlist-1.5.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5b6a66c18b5b9dd261ca98dffcb826a525334b2f29e7caa54e182255c5f6a65a", size = 94451 },
+    { url = "https://files.pythonhosted.org/packages/47/47/0c999aeace6ead8a44441b4f4173e2261b18219e4ad1fe9a479871ca02fc/frozenlist-1.5.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d1b3eb7b05ea246510b43a7e53ed1653e55c2121019a97e60cad7efb881a97bb", size = 54301 },
+    { url = "https://files.pythonhosted.org/packages/8d/60/107a38c1e54176d12e06e9d4b5d755b677d71d1219217cee063911b1384f/frozenlist-1.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:15538c0cbf0e4fa11d1e3a71f823524b0c46299aed6e10ebb4c2089abd8c3bec", size = 52213 },
+    { url = "https://files.pythonhosted.org/packages/17/62/594a6829ac5679c25755362a9dc93486a8a45241394564309641425d3ff6/frozenlist-1.5.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e79225373c317ff1e35f210dd5f1344ff31066ba8067c307ab60254cd3a78ad5", size = 240946 },
+    { url = "https://files.pythonhosted.org/packages/7e/75/6c8419d8f92c80dd0ee3f63bdde2702ce6398b0ac8410ff459f9b6f2f9cb/frozenlist-1.5.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9272fa73ca71266702c4c3e2d4a28553ea03418e591e377a03b8e3659d94fa76", size = 264608 },
+    { url = "https://files.pythonhosted.org/packages/88/3e/82a6f0b84bc6fb7e0be240e52863c6d4ab6098cd62e4f5b972cd31e002e8/frozenlist-1.5.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:498524025a5b8ba81695761d78c8dd7382ac0b052f34e66939c42df860b8ff17", size = 261361 },
+    { url = "https://files.pythonhosted.org/packages/fd/85/14e5f9ccac1b64ff2f10c927b3ffdf88772aea875882406f9ba0cec8ad84/frozenlist-1.5.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:92b5278ed9d50fe610185ecd23c55d8b307d75ca18e94c0e7de328089ac5dcba", size = 231649 },
+    { url = "https://files.pythonhosted.org/packages/ee/59/928322800306f6529d1852323014ee9008551e9bb027cc38d276cbc0b0e7/frozenlist-1.5.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f3c8c1dacd037df16e85227bac13cca58c30da836c6f936ba1df0c05d046d8d", size = 241853 },
+    { url = "https://files.pythonhosted.org/packages/7d/bd/e01fa4f146a6f6c18c5d34cab8abdc4013774a26c4ff851128cd1bd3008e/frozenlist-1.5.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:f2ac49a9bedb996086057b75bf93538240538c6d9b38e57c82d51f75a73409d2", size = 243652 },
+    { url = "https://files.pythonhosted.org/packages/a5/bd/e4771fd18a8ec6757033f0fa903e447aecc3fbba54e3630397b61596acf0/frozenlist-1.5.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:e66cc454f97053b79c2ab09c17fbe3c825ea6b4de20baf1be28919460dd7877f", size = 241734 },
+    { url = "https://files.pythonhosted.org/packages/21/13/c83821fa5544af4f60c5d3a65d054af3213c26b14d3f5f48e43e5fb48556/frozenlist-1.5.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:5a3ba5f9a0dfed20337d3e966dc359784c9f96503674c2faf015f7fe8e96798c", size = 260959 },
+    { url = "https://files.pythonhosted.org/packages/71/f3/1f91c9a9bf7ed0e8edcf52698d23f3c211d8d00291a53c9f115ceb977ab1/frozenlist-1.5.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:6321899477db90bdeb9299ac3627a6a53c7399c8cd58d25da094007402b039ab", size = 262706 },
+    { url = "https://files.pythonhosted.org/packages/4c/22/4a256fdf5d9bcb3ae32622c796ee5ff9451b3a13a68cfe3f68e2c95588ce/frozenlist-1.5.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:76e4753701248476e6286f2ef492af900ea67d9706a0155335a40ea21bf3b2f5", size = 250401 },
+    { url = "https://files.pythonhosted.org/packages/af/89/c48ebe1f7991bd2be6d5f4ed202d94960c01b3017a03d6954dd5fa9ea1e8/frozenlist-1.5.0-cp310-cp310-win32.whl", hash = "sha256:977701c081c0241d0955c9586ffdd9ce44f7a7795df39b9151cd9a6fd0ce4cfb", size = 45498 },
+    { url = "https://files.pythonhosted.org/packages/28/2f/cc27d5f43e023d21fe5c19538e08894db3d7e081cbf582ad5ed366c24446/frozenlist-1.5.0-cp310-cp310-win_amd64.whl", hash = "sha256:189f03b53e64144f90990d29a27ec4f7997d91ed3d01b51fa39d2dbe77540fd4", size = 51622 },
+    { url = "https://files.pythonhosted.org/packages/79/43/0bed28bf5eb1c9e4301003b74453b8e7aa85fb293b31dde352aac528dafc/frozenlist-1.5.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:fd74520371c3c4175142d02a976aee0b4cb4a7cc912a60586ffd8d5929979b30", size = 94987 },
+    { url = "https://files.pythonhosted.org/packages/bb/bf/b74e38f09a246e8abbe1e90eb65787ed745ccab6eaa58b9c9308e052323d/frozenlist-1.5.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2f3f7a0fbc219fb4455264cae4d9f01ad41ae6ee8524500f381de64ffaa077d5", size = 54584 },
+    { url = "https://files.pythonhosted.org/packages/2c/31/ab01375682f14f7613a1ade30149f684c84f9b8823a4391ed950c8285656/frozenlist-1.5.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f47c9c9028f55a04ac254346e92977bf0f166c483c74b4232bee19a6697e4778", size = 52499 },
+    { url = "https://files.pythonhosted.org/packages/98/a8/d0ac0b9276e1404f58fec3ab6e90a4f76b778a49373ccaf6a563f100dfbc/frozenlist-1.5.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0996c66760924da6e88922756d99b47512a71cfd45215f3570bf1e0b694c206a", size = 276357 },
+    { url = "https://files.pythonhosted.org/packages/ad/c9/c7761084fa822f07dac38ac29f841d4587570dd211e2262544aa0b791d21/frozenlist-1.5.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a2fe128eb4edeabe11896cb6af88fca5346059f6c8d807e3b910069f39157869", size = 287516 },
+    { url = "https://files.pythonhosted.org/packages/a1/ff/cd7479e703c39df7bdab431798cef89dc75010d8aa0ca2514c5b9321db27/frozenlist-1.5.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1a8ea951bbb6cacd492e3948b8da8c502a3f814f5d20935aae74b5df2b19cf3d", size = 283131 },
+    { url = "https://files.pythonhosted.org/packages/59/a0/370941beb47d237eca4fbf27e4e91389fd68699e6f4b0ebcc95da463835b/frozenlist-1.5.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:de537c11e4aa01d37db0d403b57bd6f0546e71a82347a97c6a9f0dcc532b3a45", size = 261320 },
+    { url = "https://files.pythonhosted.org/packages/b8/5f/c10123e8d64867bc9b4f2f510a32042a306ff5fcd7e2e09e5ae5100ee333/frozenlist-1.5.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9c2623347b933fcb9095841f1cc5d4ff0b278addd743e0e966cb3d460278840d", size = 274877 },
+    { url = "https://files.pythonhosted.org/packages/fa/79/38c505601ae29d4348f21706c5d89755ceded02a745016ba2f58bd5f1ea6/frozenlist-1.5.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:cee6798eaf8b1416ef6909b06f7dc04b60755206bddc599f52232606e18179d3", size = 269592 },
+    { url = "https://files.pythonhosted.org/packages/19/e2/39f3a53191b8204ba9f0bb574b926b73dd2efba2a2b9d2d730517e8f7622/frozenlist-1.5.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:f5f9da7f5dbc00a604fe74aa02ae7c98bcede8a3b8b9666f9f86fc13993bc71a", size = 265934 },
+    { url = "https://files.pythonhosted.org/packages/d5/c9/3075eb7f7f3a91f1a6b00284af4de0a65a9ae47084930916f5528144c9dd/frozenlist-1.5.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:90646abbc7a5d5c7c19461d2e3eeb76eb0b204919e6ece342feb6032c9325ae9", size = 283859 },
+    { url = "https://files.pythonhosted.org/packages/05/f5/549f44d314c29408b962fa2b0e69a1a67c59379fb143b92a0a065ffd1f0f/frozenlist-1.5.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:bdac3c7d9b705d253b2ce370fde941836a5f8b3c5c2b8fd70940a3ea3af7f4f2", size = 287560 },
+    { url = "https://files.pythonhosted.org/packages/9d/f8/cb09b3c24a3eac02c4c07a9558e11e9e244fb02bf62c85ac2106d1eb0c0b/frozenlist-1.5.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:03d33c2ddbc1816237a67f66336616416e2bbb6beb306e5f890f2eb22b959cdf", size = 277150 },
+    { url = "https://files.pythonhosted.org/packages/37/48/38c2db3f54d1501e692d6fe058f45b6ad1b358d82cd19436efab80cfc965/frozenlist-1.5.0-cp311-cp311-win32.whl", hash = "sha256:237f6b23ee0f44066219dae14c70ae38a63f0440ce6750f868ee08775073f942", size = 45244 },
+    { url = "https://files.pythonhosted.org/packages/ca/8c/2ddffeb8b60a4bce3b196c32fcc30d8830d4615e7b492ec2071da801b8ad/frozenlist-1.5.0-cp311-cp311-win_amd64.whl", hash = "sha256:0cc974cc93d32c42e7b0f6cf242a6bd941c57c61b618e78b6c0a96cb72788c1d", size = 51634 },
+    { url = "https://files.pythonhosted.org/packages/79/73/fa6d1a96ab7fd6e6d1c3500700963eab46813847f01ef0ccbaa726181dd5/frozenlist-1.5.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:31115ba75889723431aa9a4e77d5f398f5cf976eea3bdf61749731f62d4a4a21", size = 94026 },
+    { url = "https://files.pythonhosted.org/packages/ab/04/ea8bf62c8868b8eada363f20ff1b647cf2e93377a7b284d36062d21d81d1/frozenlist-1.5.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7437601c4d89d070eac8323f121fcf25f88674627505334654fd027b091db09d", size = 54150 },
+    { url = "https://files.pythonhosted.org/packages/d0/9a/8e479b482a6f2070b26bda572c5e6889bb3ba48977e81beea35b5ae13ece/frozenlist-1.5.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:7948140d9f8ece1745be806f2bfdf390127cf1a763b925c4a805c603df5e697e", size = 51927 },
+    { url = "https://files.pythonhosted.org/packages/e3/12/2aad87deb08a4e7ccfb33600871bbe8f0e08cb6d8224371387f3303654d7/frozenlist-1.5.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:feeb64bc9bcc6b45c6311c9e9b99406660a9c05ca8a5b30d14a78555088b0b3a", size = 282647 },
+    { url = "https://files.pythonhosted.org/packages/77/f2/07f06b05d8a427ea0060a9cef6e63405ea9e0d761846b95ef3fb3be57111/frozenlist-1.5.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:683173d371daad49cffb8309779e886e59c2f369430ad28fe715f66d08d4ab1a", size = 289052 },
+    { url = "https://files.pythonhosted.org/packages/bd/9f/8bf45a2f1cd4aa401acd271b077989c9267ae8463e7c8b1eb0d3f561b65e/frozenlist-1.5.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7d57d8f702221405a9d9b40f9da8ac2e4a1a8b5285aac6100f3393675f0a85ee", size = 291719 },
+    { url = "https://files.pythonhosted.org/packages/41/d1/1f20fd05a6c42d3868709b7604c9f15538a29e4f734c694c6bcfc3d3b935/frozenlist-1.5.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:30c72000fbcc35b129cb09956836c7d7abf78ab5416595e4857d1cae8d6251a6", size = 267433 },
+    { url = "https://files.pythonhosted.org/packages/af/f2/64b73a9bb86f5a89fb55450e97cd5c1f84a862d4ff90d9fd1a73ab0f64a5/frozenlist-1.5.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:000a77d6034fbad9b6bb880f7ec073027908f1b40254b5d6f26210d2dab1240e", size = 283591 },
+    { url = "https://files.pythonhosted.org/packages/29/e2/ffbb1fae55a791fd6c2938dd9ea779509c977435ba3940b9f2e8dc9d5316/frozenlist-1.5.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5d7f5a50342475962eb18b740f3beecc685a15b52c91f7d975257e13e029eca9", size = 273249 },
+    { url = "https://files.pythonhosted.org/packages/2e/6e/008136a30798bb63618a114b9321b5971172a5abddff44a100c7edc5ad4f/frozenlist-1.5.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:87f724d055eb4785d9be84e9ebf0f24e392ddfad00b3fe036e43f489fafc9039", size = 271075 },
+    { url = "https://files.pythonhosted.org/packages/ae/f0/4e71e54a026b06724cec9b6c54f0b13a4e9e298cc8db0f82ec70e151f5ce/frozenlist-1.5.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:6e9080bb2fb195a046e5177f10d9d82b8a204c0736a97a153c2466127de87784", size = 285398 },
+    { url = "https://files.pythonhosted.org/packages/4d/36/70ec246851478b1c0b59f11ef8ade9c482ff447c1363c2bd5fad45098b12/frozenlist-1.5.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:9b93d7aaa36c966fa42efcaf716e6b3900438632a626fb09c049f6a2f09fc631", size = 294445 },
+    { url = "https://files.pythonhosted.org/packages/37/e0/47f87544055b3349b633a03c4d94b405956cf2437f4ab46d0928b74b7526/frozenlist-1.5.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:52ef692a4bc60a6dd57f507429636c2af8b6046db8b31b18dac02cbc8f507f7f", size = 280569 },
+    { url = "https://files.pythonhosted.org/packages/f9/7c/490133c160fb6b84ed374c266f42800e33b50c3bbab1652764e6e1fc498a/frozenlist-1.5.0-cp312-cp312-win32.whl", hash = "sha256:29d94c256679247b33a3dc96cce0f93cbc69c23bf75ff715919332fdbb6a32b8", size = 44721 },
+    { url = "https://files.pythonhosted.org/packages/b1/56/4e45136ffc6bdbfa68c29ca56ef53783ef4c2fd395f7cbf99a2624aa9aaa/frozenlist-1.5.0-cp312-cp312-win_amd64.whl", hash = "sha256:8969190d709e7c48ea386db202d708eb94bdb29207a1f269bab1196ce0dcca1f", size = 51329 },
+    { url = "https://files.pythonhosted.org/packages/da/3b/915f0bca8a7ea04483622e84a9bd90033bab54bdf485479556c74fd5eaf5/frozenlist-1.5.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:7a1a048f9215c90973402e26c01d1cff8a209e1f1b53f72b95c13db61b00f953", size = 91538 },
+    { url = "https://files.pythonhosted.org/packages/c7/d1/a7c98aad7e44afe5306a2b068434a5830f1470675f0e715abb86eb15f15b/frozenlist-1.5.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:dd47a5181ce5fcb463b5d9e17ecfdb02b678cca31280639255ce9d0e5aa67af0", size = 52849 },
+    { url = "https://files.pythonhosted.org/packages/3a/c8/76f23bf9ab15d5f760eb48701909645f686f9c64fbb8982674c241fbef14/frozenlist-1.5.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:1431d60b36d15cda188ea222033eec8e0eab488f39a272461f2e6d9e1a8e63c2", size = 50583 },
+    { url = "https://files.pythonhosted.org/packages/1f/22/462a3dd093d11df623179d7754a3b3269de3b42de2808cddef50ee0f4f48/frozenlist-1.5.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6482a5851f5d72767fbd0e507e80737f9c8646ae7fd303def99bfe813f76cf7f", size = 265636 },
+    { url = "https://files.pythonhosted.org/packages/80/cf/e075e407fc2ae7328155a1cd7e22f932773c8073c1fc78016607d19cc3e5/frozenlist-1.5.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:44c49271a937625619e862baacbd037a7ef86dd1ee215afc298a417ff3270608", size = 270214 },
+    { url = "https://files.pythonhosted.org/packages/a1/58/0642d061d5de779f39c50cbb00df49682832923f3d2ebfb0fedf02d05f7f/frozenlist-1.5.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:12f78f98c2f1c2429d42e6a485f433722b0061d5c0b0139efa64f396efb5886b", size = 273905 },
+    { url = "https://files.pythonhosted.org/packages/ab/66/3fe0f5f8f2add5b4ab7aa4e199f767fd3b55da26e3ca4ce2cc36698e50c4/frozenlist-1.5.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ce3aa154c452d2467487765e3adc730a8c153af77ad84096bc19ce19a2400840", size = 250542 },
+    { url = "https://files.pythonhosted.org/packages/f6/b8/260791bde9198c87a465224e0e2bb62c4e716f5d198fc3a1dacc4895dbd1/frozenlist-1.5.0-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9b7dc0c4338e6b8b091e8faf0db3168a37101943e687f373dce00959583f7439", size = 267026 },
+    { url = "https://files.pythonhosted.org/packages/2e/a4/3d24f88c527f08f8d44ade24eaee83b2627793fa62fa07cbb7ff7a2f7d42/frozenlist-1.5.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:45e0896250900b5aa25180f9aec243e84e92ac84bd4a74d9ad4138ef3f5c97de", size = 257690 },
+    { url = "https://files.pythonhosted.org/packages/de/9a/d311d660420b2beeff3459b6626f2ab4fb236d07afbdac034a4371fe696e/frozenlist-1.5.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:561eb1c9579d495fddb6da8959fd2a1fca2c6d060d4113f5844b433fc02f2641", size = 253893 },
+    { url = "https://files.pythonhosted.org/packages/c6/23/e491aadc25b56eabd0f18c53bb19f3cdc6de30b2129ee0bc39cd387cd560/frozenlist-1.5.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:df6e2f325bfee1f49f81aaac97d2aa757c7646534a06f8f577ce184afe2f0a9e", size = 267006 },
+    { url = "https://files.pythonhosted.org/packages/08/c4/ab918ce636a35fb974d13d666dcbe03969592aeca6c3ab3835acff01f79c/frozenlist-1.5.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:140228863501b44b809fb39ec56b5d4071f4d0aa6d216c19cbb08b8c5a7eadb9", size = 276157 },
+    { url = "https://files.pythonhosted.org/packages/c0/29/3b7a0bbbbe5a34833ba26f686aabfe982924adbdcafdc294a7a129c31688/frozenlist-1.5.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:7707a25d6a77f5d27ea7dc7d1fc608aa0a478193823f88511ef5e6b8a48f9d03", size = 264642 },
+    { url = "https://files.pythonhosted.org/packages/ab/42/0595b3dbffc2e82d7fe658c12d5a5bafcd7516c6bf2d1d1feb5387caa9c1/frozenlist-1.5.0-cp313-cp313-win32.whl", hash = "sha256:31a9ac2b38ab9b5a8933b693db4939764ad3f299fcaa931a3e605bc3460e693c", size = 44914 },
+    { url = "https://files.pythonhosted.org/packages/17/c4/b7db1206a3fea44bf3b838ca61deb6f74424a8a5db1dd53ecb21da669be6/frozenlist-1.5.0-cp313-cp313-win_amd64.whl", hash = "sha256:11aabdd62b8b9c4b84081a3c246506d1cddd2dd93ff0ad53ede5defec7886b28", size = 51167 },
+    { url = "https://files.pythonhosted.org/packages/da/4d/d94ff0fb0f5313902c132817c62d19cdc5bdcd0c195d392006ef4b779fc6/frozenlist-1.5.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:9bbcdfaf4af7ce002694a4e10a0159d5a8d20056a12b05b45cea944a4953f972", size = 95319 },
+    { url = "https://files.pythonhosted.org/packages/8c/1b/d90e554ca2b483d31cb2296e393f72c25bdc38d64526579e95576bfda587/frozenlist-1.5.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:1893f948bf6681733aaccf36c5232c231e3b5166d607c5fa77773611df6dc336", size = 54749 },
+    { url = "https://files.pythonhosted.org/packages/f8/66/7fdecc9ef49f8db2aa4d9da916e4ecf357d867d87aea292efc11e1b2e932/frozenlist-1.5.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:2b5e23253bb709ef57a8e95e6ae48daa9ac5f265637529e4ce6b003a37b2621f", size = 52718 },
+    { url = "https://files.pythonhosted.org/packages/08/04/e2fddc92135276e07addbc1cf413acffa0c2d848b3e54cacf684e146df49/frozenlist-1.5.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0f253985bb515ecd89629db13cb58d702035ecd8cfbca7d7a7e29a0e6d39af5f", size = 241756 },
+    { url = "https://files.pythonhosted.org/packages/c6/52/be5ff200815d8a341aee5b16b6b707355e0ca3652953852238eb92b120c2/frozenlist-1.5.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:04a5c6babd5e8fb7d3c871dc8b321166b80e41b637c31a995ed844a6139942b6", size = 267718 },
+    { url = "https://files.pythonhosted.org/packages/88/be/4bd93a58be57a3722fc544c36debdf9dcc6758f761092e894d78f18b8f20/frozenlist-1.5.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9fe0f1c29ba24ba6ff6abf688cb0b7cf1efab6b6aa6adc55441773c252f7411", size = 263494 },
+    { url = "https://files.pythonhosted.org/packages/32/ba/58348b90193caa096ce9e9befea6ae67f38dabfd3aacb47e46137a6250a8/frozenlist-1.5.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:226d72559fa19babe2ccd920273e767c96a49b9d3d38badd7c91a0fdeda8ea08", size = 232838 },
+    { url = "https://files.pythonhosted.org/packages/f6/33/9f152105227630246135188901373c4f322cc026565ca6215b063f4c82f4/frozenlist-1.5.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:15b731db116ab3aedec558573c1a5eec78822b32292fe4f2f0345b7f697745c2", size = 242912 },
+    { url = "https://files.pythonhosted.org/packages/a0/10/3db38fb3ccbafadd80a1b0d6800c987b0e3fe3ef2d117c6ced0246eea17a/frozenlist-1.5.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:366d8f93e3edfe5a918c874702f78faac300209a4d5bf38352b2c1bdc07a766d", size = 244763 },
+    { url = "https://files.pythonhosted.org/packages/e2/cd/1df468fdce2f66a4608dffe44c40cdc35eeaa67ef7fd1d813f99a9a37842/frozenlist-1.5.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:1b96af8c582b94d381a1c1f51ffaedeb77c821c690ea5f01da3d70a487dd0a9b", size = 242841 },
+    { url = "https://files.pythonhosted.org/packages/ee/5f/16097a5ca0bb6b6779c02cc9379c72fe98d56115d4c54d059fb233168fb6/frozenlist-1.5.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:c03eff4a41bd4e38415cbed054bbaff4a075b093e2394b6915dca34a40d1e38b", size = 263407 },
+    { url = "https://files.pythonhosted.org/packages/0f/f7/58cd220ee1c2248ee65a32f5b4b93689e3fe1764d85537eee9fc392543bc/frozenlist-1.5.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:50cf5e7ee9b98f22bdecbabf3800ae78ddcc26e4a435515fc72d97903e8488e0", size = 265083 },
+    { url = "https://files.pythonhosted.org/packages/62/b8/49768980caabf81ac4a2d156008f7cbd0107e6b36d08a313bb31035d9201/frozenlist-1.5.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1e76bfbc72353269c44e0bc2cfe171900fbf7f722ad74c9a7b638052afe6a00c", size = 251564 },
+    { url = "https://files.pythonhosted.org/packages/cb/83/619327da3b86ef957ee7a0cbf3c166a09ed1e87a3f7f1ff487d7d0284683/frozenlist-1.5.0-cp39-cp39-win32.whl", hash = "sha256:666534d15ba8f0fda3f53969117383d5dc021266b3c1a42c9ec4855e4b58b9d3", size = 45691 },
+    { url = "https://files.pythonhosted.org/packages/8b/28/407bc34a745151ed2322c690b6e7d83d7101472e81ed76e1ebdac0b70a78/frozenlist-1.5.0-cp39-cp39-win_amd64.whl", hash = "sha256:5c28f4b5dbef8a0d8aad0d4de24d1e9e981728628afaf4ea0792f5d0939372f0", size = 51767 },
+    { url = "https://files.pythonhosted.org/packages/c6/c8/a5be5b7550c10858fcf9b0ea054baccab474da77d37f1e828ce043a3a5d4/frozenlist-1.5.0-py3-none-any.whl", hash = "sha256:d994863bba198a4a518b467bb971c56e1db3f180a25c6cf7bb1949c267f748c3", size = 11901 },
+]
+
 [[package]]
 name = "gitdb"
 version = "4.0.12"
@@ -413,21 +620,26 @@ wheels = [
 
 [[package]]
 name = "langchain"
-version = "0.3.20"
+version = "0.3.18"
 source = { editable = "../langchain" }
 dependencies = [
+    { name = "aiohttp" },
     { name = "async-timeout", marker = "python_full_version < '3.11'" },
     { name = "langchain-core" },
     { name = "langchain-text-splitters" },
     { name = "langsmith" },
+    { name = "numpy", version = "1.26.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
+    { name = "numpy", version = "2.2.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "pydantic" },
     { name = "pyyaml" },
     { name = "requests" },
     { name = "sqlalchemy" },
+    { name = "tenacity" },
 ]
 
 [package.metadata]
 requires-dist = [
+    { name = "aiohttp", specifier = ">=3.8.3,<4.0.0" },
     { name = "async-timeout", marker = "python_full_version < '3.11'", specifier = ">=4.0.0,<5.0.0" },
     { name = "langchain-anthropic", marker = "extra == 'anthropic'" },
     { name = "langchain-aws", marker = "extra == 'aws'" },
@@ -445,12 +657,14 @@ requires-dist = [
     { name = "langchain-openai", marker = "extra == 'openai'", editable = "../partners/openai" },
     { name = "langchain-text-splitters", editable = "../text-splitters" },
     { name = "langchain-together", marker = "extra == 'together'" },
-    { name = "langchain-xai", marker = "extra == 'xai'" },
     { name = "langsmith", specifier = ">=0.1.17,<0.4" },
+    { name = "numpy", marker = "python_full_version < '3.12'", specifier = ">=1.26.4,<2" },
+    { name = "numpy", marker = "python_full_version >= '3.12'", specifier = ">=1.26.2,<3" },
     { name = "pydantic", specifier = ">=2.7.4,<3.0.0" },
     { name = "pyyaml", specifier = ">=5.3" },
     { name = "requests", specifier = ">=2,<3" },
     { name = "sqlalchemy", specifier = ">=1.4,<3" },
+    { name = "tenacity", specifier = ">=8.1.0,!=8.4.0,<10" },
 ]
 
 [package.metadata.requires-dev]
@@ -468,7 +682,7 @@ lint = [
     { name = "ruff", specifier = ">=0.9.2,<1.0.0" },
 ]
 test = [
-    { name = "blockbuster", specifier = ">=1.5.18,<1.6" },
+    { name = "blockbuster", specifier = ">=1.5.14,<1.6" },
     { name = "cffi", marker = "python_full_version < '3.10'", specifier = "<1.17.1" },
     { name = "cffi", marker = "python_full_version >= '3.10'" },
     { name = "duckdb-engine", specifier = ">=0.9.2,<1.0.0" },
@@ -478,7 +692,6 @@ test = [
     { name = "langchain-tests", editable = "../standard-tests" },
     { name = "langchain-text-splitters", editable = "../text-splitters" },
     { name = "lark", specifier = ">=1.1.5,<2.0.0" },
-    { name = "numpy", specifier = ">=1.26.4,<3" },
     { name = "packaging", specifier = ">=24.2" },
     { name = "pandas", specifier = ">=2.0.0,<3.0.0" },
     { name = "pytest", specifier = ">=8,<9" },
@@ -509,7 +722,6 @@ typing = [
     { name = "langchain-text-splitters", editable = "../text-splitters" },
     { name = "mypy", specifier = ">=1.10,<2.0" },
     { name = "mypy-protobuf", specifier = ">=3.0.0,<4.0.0" },
-    { name = "numpy", specifier = ">=1.26.4,<3" },
     { name = "types-chardet", specifier = ">=5.0.4.6,<6.0.0.0" },
     { name = "types-pytz", specifier = ">=2023.3.0.0,<2024.0.0.0" },
     { name = "types-pyyaml", specifier = ">=6.0.12.2,<7.0.0.0" },
@@ -542,7 +754,6 @@ lint = [
 ]
 test = [
     { name = "langchain" },
-    { name = "langchain-core" },
 ]
 typing = [
     { name = "langchain" },
@@ -567,16 +778,13 @@ lint = [
     { name = "mypy", specifier = ">=1.13.0,<2.0.0" },
     { name = "ruff", specifier = ">=0.5,<1.0" },
 ]
-test = [
-    { name = "langchain", editable = "../langchain" },
-    { name = "langchain-core", editable = "../core" },
-]
+test = [{ name = "langchain", editable = "../langchain" }]
 test-integration = []
 typing = [{ name = "langchain", editable = "../langchain" }]
 
 [[package]]
 name = "langchain-core"
-version = "0.3.41"
+version = "0.3.35"
 source = { editable = "../core" }
 dependencies = [
     { name = "jsonpatch" },
@@ -608,7 +816,7 @@ dev = [
 ]
 lint = [{ name = "ruff", specifier = ">=0.9.2,<1.0.0" }]
 test = [
-    { name = "blockbuster", specifier = "~=1.5.18" },
+    { name = "blockbuster", specifier = "~=1.5.11" },
     { name = "freezegun", specifier = ">=1.2.2,<2.0.0" },
     { name = "grandalf", specifier = ">=0.8,<1.0" },
     { name = "langchain-tests", directory = "../standard-tests" },
@@ -735,6 +943,93 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b3/38/89ba8ad64ae25be8de66a6d463314cf1eb366222074cfda9ee839c56a4b4/mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8", size = 9979 },
 ]
 
+[[package]]
+name = "multidict"
+version = "6.1.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "typing-extensions", marker = "python_full_version < '3.11'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/d6/be/504b89a5e9ca731cd47487e91c469064f8ae5af93b7259758dcfc2b9c848/multidict-6.1.0.tar.gz", hash = "sha256:22ae2ebf9b0c69d206c003e2f6a914ea33f0a932d4aa16f236afc049d9958f4a", size = 64002 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/29/68/259dee7fd14cf56a17c554125e534f6274c2860159692a414d0b402b9a6d/multidict-6.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:3380252550e372e8511d49481bd836264c009adb826b23fefcc5dd3c69692f60", size = 48628 },
+    { url = "https://files.pythonhosted.org/packages/50/79/53ba256069fe5386a4a9e80d4e12857ced9de295baf3e20c68cdda746e04/multidict-6.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:99f826cbf970077383d7de805c0681799491cb939c25450b9b5b3ced03ca99f1", size = 29327 },
+    { url = "https://files.pythonhosted.org/packages/ff/10/71f1379b05b196dae749b5ac062e87273e3f11634f447ebac12a571d90ae/multidict-6.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a114d03b938376557927ab23f1e950827c3b893ccb94b62fd95d430fd0e5cf53", size = 29689 },
+    { url = "https://files.pythonhosted.org/packages/71/45/70bac4f87438ded36ad4793793c0095de6572d433d98575a5752629ef549/multidict-6.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b1c416351ee6271b2f49b56ad7f308072f6f44b37118d69c2cad94f3fa8a40d5", size = 126639 },
+    { url = "https://files.pythonhosted.org/packages/80/cf/17f35b3b9509b4959303c05379c4bfb0d7dd05c3306039fc79cf035bbac0/multidict-6.1.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6b5d83030255983181005e6cfbac1617ce9746b219bc2aad52201ad121226581", size = 134315 },
+    { url = "https://files.pythonhosted.org/packages/ef/1f/652d70ab5effb33c031510a3503d4d6efc5ec93153562f1ee0acdc895a57/multidict-6.1.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3e97b5e938051226dc025ec80980c285b053ffb1e25a3db2a3aa3bc046bf7f56", size = 129471 },
+    { url = "https://files.pythonhosted.org/packages/a6/64/2dd6c4c681688c0165dea3975a6a4eab4944ea30f35000f8b8af1df3148c/multidict-6.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d618649d4e70ac6efcbba75be98b26ef5078faad23592f9b51ca492953012429", size = 124585 },
+    { url = "https://files.pythonhosted.org/packages/87/56/e6ee5459894c7e554b57ba88f7257dc3c3d2d379cb15baaa1e265b8c6165/multidict-6.1.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:10524ebd769727ac77ef2278390fb0068d83f3acb7773792a5080f2b0abf7748", size = 116957 },
+    { url = "https://files.pythonhosted.org/packages/36/9e/616ce5e8d375c24b84f14fc263c7ef1d8d5e8ef529dbc0f1df8ce71bb5b8/multidict-6.1.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:ff3827aef427c89a25cc96ded1759271a93603aba9fb977a6d264648ebf989db", size = 128609 },
+    { url = "https://files.pythonhosted.org/packages/8c/4f/4783e48a38495d000f2124020dc96bacc806a4340345211b1ab6175a6cb4/multidict-6.1.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:06809f4f0f7ab7ea2cabf9caca7d79c22c0758b58a71f9d32943ae13c7ace056", size = 123016 },
+    { url = "https://files.pythonhosted.org/packages/3e/b3/4950551ab8fc39862ba5e9907dc821f896aa829b4524b4deefd3e12945ab/multidict-6.1.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:f179dee3b863ab1c59580ff60f9d99f632f34ccb38bf67a33ec6b3ecadd0fd76", size = 133542 },
+    { url = "https://files.pythonhosted.org/packages/96/4d/f0ce6ac9914168a2a71df117935bb1f1781916acdecbb43285e225b484b8/multidict-6.1.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:aaed8b0562be4a0876ee3b6946f6869b7bcdb571a5d1496683505944e268b160", size = 130163 },
+    { url = "https://files.pythonhosted.org/packages/be/72/17c9f67e7542a49dd252c5ae50248607dfb780bcc03035907dafefb067e3/multidict-6.1.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:3c8b88a2ccf5493b6c8da9076fb151ba106960a2df90c2633f342f120751a9e7", size = 126832 },
+    { url = "https://files.pythonhosted.org/packages/71/9f/72d719e248cbd755c8736c6d14780533a1606ffb3fbb0fbd77da9f0372da/multidict-6.1.0-cp310-cp310-win32.whl", hash = "sha256:4a9cb68166a34117d6646c0023c7b759bf197bee5ad4272f420a0141d7eb03a0", size = 26402 },
+    { url = "https://files.pythonhosted.org/packages/04/5a/d88cd5d00a184e1ddffc82aa2e6e915164a6d2641ed3606e766b5d2f275a/multidict-6.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:20b9b5fbe0b88d0bdef2012ef7dee867f874b72528cf1d08f1d59b0e3850129d", size = 28800 },
+    { url = "https://files.pythonhosted.org/packages/93/13/df3505a46d0cd08428e4c8169a196131d1b0c4b515c3649829258843dde6/multidict-6.1.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:3efe2c2cb5763f2f1b275ad2bf7a287d3f7ebbef35648a9726e3b69284a4f3d6", size = 48570 },
+    { url = "https://files.pythonhosted.org/packages/f0/e1/a215908bfae1343cdb72f805366592bdd60487b4232d039c437fe8f5013d/multidict-6.1.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c7053d3b0353a8b9de430a4f4b4268ac9a4fb3481af37dfe49825bf45ca24156", size = 29316 },
+    { url = "https://files.pythonhosted.org/packages/70/0f/6dc70ddf5d442702ed74f298d69977f904960b82368532c88e854b79f72b/multidict-6.1.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:27e5fc84ccef8dfaabb09d82b7d179c7cf1a3fbc8a966f8274fcb4ab2eb4cadb", size = 29640 },
+    { url = "https://files.pythonhosted.org/packages/d8/6d/9c87b73a13d1cdea30b321ef4b3824449866bd7f7127eceed066ccb9b9ff/multidict-6.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0e2b90b43e696f25c62656389d32236e049568b39320e2735d51f08fd362761b", size = 131067 },
+    { url = "https://files.pythonhosted.org/packages/cc/1e/1b34154fef373371fd6c65125b3d42ff5f56c7ccc6bfff91b9b3c60ae9e0/multidict-6.1.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d83a047959d38a7ff552ff94be767b7fd79b831ad1cd9920662db05fec24fe72", size = 138507 },
+    { url = "https://files.pythonhosted.org/packages/fb/e0/0bc6b2bac6e461822b5f575eae85da6aae76d0e2a79b6665d6206b8e2e48/multidict-6.1.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d1a9dd711d0877a1ece3d2e4fea11a8e75741ca21954c919406b44e7cf971304", size = 133905 },
+    { url = "https://files.pythonhosted.org/packages/ba/af/73d13b918071ff9b2205fcf773d316e0f8fefb4ec65354bbcf0b10908cc6/multidict-6.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ec2abea24d98246b94913b76a125e855eb5c434f7c46546046372fe60f666351", size = 129004 },
+    { url = "https://files.pythonhosted.org/packages/74/21/23960627b00ed39643302d81bcda44c9444ebcdc04ee5bedd0757513f259/multidict-6.1.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4867cafcbc6585e4b678876c489b9273b13e9fff9f6d6d66add5e15d11d926cb", size = 121308 },
+    { url = "https://files.pythonhosted.org/packages/8b/5c/cf282263ffce4a596ed0bb2aa1a1dddfe1996d6a62d08842a8d4b33dca13/multidict-6.1.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:5b48204e8d955c47c55b72779802b219a39acc3ee3d0116d5080c388970b76e3", size = 132608 },
+    { url = "https://files.pythonhosted.org/packages/d7/3e/97e778c041c72063f42b290888daff008d3ab1427f5b09b714f5a8eff294/multidict-6.1.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:d8fff389528cad1618fb4b26b95550327495462cd745d879a8c7c2115248e399", size = 127029 },
+    { url = "https://files.pythonhosted.org/packages/47/ac/3efb7bfe2f3aefcf8d103e9a7162572f01936155ab2f7ebcc7c255a23212/multidict-6.1.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:a7a9541cd308eed5e30318430a9c74d2132e9a8cb46b901326272d780bf2d423", size = 137594 },
+    { url = "https://files.pythonhosted.org/packages/42/9b/6c6e9e8dc4f915fc90a9b7798c44a30773dea2995fdcb619870e705afe2b/multidict-6.1.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:da1758c76f50c39a2efd5e9859ce7d776317eb1dd34317c8152ac9251fc574a3", size = 134556 },
+    { url = "https://files.pythonhosted.org/packages/1d/10/8e881743b26aaf718379a14ac58572a240e8293a1c9d68e1418fb11c0f90/multidict-6.1.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:c943a53e9186688b45b323602298ab727d8865d8c9ee0b17f8d62d14b56f0753", size = 130993 },
+    { url = "https://files.pythonhosted.org/packages/45/84/3eb91b4b557442802d058a7579e864b329968c8d0ea57d907e7023c677f2/multidict-6.1.0-cp311-cp311-win32.whl", hash = "sha256:90f8717cb649eea3504091e640a1b8568faad18bd4b9fcd692853a04475a4b80", size = 26405 },
+    { url = "https://files.pythonhosted.org/packages/9f/0b/ad879847ecbf6d27e90a6eabb7eff6b62c129eefe617ea45eae7c1f0aead/multidict-6.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:82176036e65644a6cc5bd619f65f6f19781e8ec2e5330f51aa9ada7504cc1926", size = 28795 },
+    { url = "https://files.pythonhosted.org/packages/fd/16/92057c74ba3b96d5e211b553895cd6dc7cc4d1e43d9ab8fafc727681ef71/multidict-6.1.0-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:b04772ed465fa3cc947db808fa306d79b43e896beb677a56fb2347ca1a49c1fa", size = 48713 },
+    { url = "https://files.pythonhosted.org/packages/94/3d/37d1b8893ae79716179540b89fc6a0ee56b4a65fcc0d63535c6f5d96f217/multidict-6.1.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:6180c0ae073bddeb5a97a38c03f30c233e0a4d39cd86166251617d1bbd0af436", size = 29516 },
+    { url = "https://files.pythonhosted.org/packages/a2/12/adb6b3200c363062f805275b4c1e656be2b3681aada66c80129932ff0bae/multidict-6.1.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:071120490b47aa997cca00666923a83f02c7fbb44f71cf7f136df753f7fa8761", size = 29557 },
+    { url = "https://files.pythonhosted.org/packages/47/e9/604bb05e6e5bce1e6a5cf80a474e0f072e80d8ac105f1b994a53e0b28c42/multidict-6.1.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:50b3a2710631848991d0bf7de077502e8994c804bb805aeb2925a981de58ec2e", size = 130170 },
+    { url = "https://files.pythonhosted.org/packages/7e/13/9efa50801785eccbf7086b3c83b71a4fb501a4d43549c2f2f80b8787d69f/multidict-6.1.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b58c621844d55e71c1b7f7c498ce5aa6985d743a1a59034c57a905b3f153c1ef", size = 134836 },
+    { url = "https://files.pythonhosted.org/packages/bf/0f/93808b765192780d117814a6dfcc2e75de6dcc610009ad408b8814dca3ba/multidict-6.1.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:55b6d90641869892caa9ca42ff913f7ff1c5ece06474fbd32fb2cf6834726c95", size = 133475 },
+    { url = "https://files.pythonhosted.org/packages/d3/c8/529101d7176fe7dfe1d99604e48d69c5dfdcadb4f06561f465c8ef12b4df/multidict-6.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4b820514bfc0b98a30e3d85462084779900347e4d49267f747ff54060cc33925", size = 131049 },
+    { url = "https://files.pythonhosted.org/packages/ca/0c/fc85b439014d5a58063e19c3a158a889deec399d47b5269a0f3b6a2e28bc/multidict-6.1.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:10a9b09aba0c5b48c53761b7c720aaaf7cf236d5fe394cd399c7ba662d5f9966", size = 120370 },
+    { url = "https://files.pythonhosted.org/packages/db/46/d4416eb20176492d2258fbd47b4abe729ff3b6e9c829ea4236f93c865089/multidict-6.1.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:1e16bf3e5fc9f44632affb159d30a437bfe286ce9e02754759be5536b169b305", size = 125178 },
+    { url = "https://files.pythonhosted.org/packages/5b/46/73697ad7ec521df7de5531a32780bbfd908ded0643cbe457f981a701457c/multidict-6.1.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:76f364861c3bfc98cbbcbd402d83454ed9e01a5224bb3a28bf70002a230f73e2", size = 119567 },
+    { url = "https://files.pythonhosted.org/packages/cd/ed/51f060e2cb0e7635329fa6ff930aa5cffa17f4c7f5c6c3ddc3500708e2f2/multidict-6.1.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:820c661588bd01a0aa62a1283f20d2be4281b086f80dad9e955e690c75fb54a2", size = 129822 },
+    { url = "https://files.pythonhosted.org/packages/df/9e/ee7d1954b1331da3eddea0c4e08d9142da5f14b1321c7301f5014f49d492/multidict-6.1.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:0e5f362e895bc5b9e67fe6e4ded2492d8124bdf817827f33c5b46c2fe3ffaca6", size = 128656 },
+    { url = "https://files.pythonhosted.org/packages/77/00/8538f11e3356b5d95fa4b024aa566cde7a38aa7a5f08f4912b32a037c5dc/multidict-6.1.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:3ec660d19bbc671e3a6443325f07263be452c453ac9e512f5eb935e7d4ac28b3", size = 125360 },
+    { url = "https://files.pythonhosted.org/packages/be/05/5d334c1f2462d43fec2363cd00b1c44c93a78c3925d952e9a71caf662e96/multidict-6.1.0-cp312-cp312-win32.whl", hash = "sha256:58130ecf8f7b8112cdb841486404f1282b9c86ccb30d3519faf301b2e5659133", size = 26382 },
+    { url = "https://files.pythonhosted.org/packages/a3/bf/f332a13486b1ed0496d624bcc7e8357bb8053823e8cd4b9a18edc1d97e73/multidict-6.1.0-cp312-cp312-win_amd64.whl", hash = "sha256:188215fc0aafb8e03341995e7c4797860181562380f81ed0a87ff455b70bf1f1", size = 28529 },
+    { url = "https://files.pythonhosted.org/packages/22/67/1c7c0f39fe069aa4e5d794f323be24bf4d33d62d2a348acdb7991f8f30db/multidict-6.1.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:d569388c381b24671589335a3be6e1d45546c2988c2ebe30fdcada8457a31008", size = 48771 },
+    { url = "https://files.pythonhosted.org/packages/3c/25/c186ee7b212bdf0df2519eacfb1981a017bda34392c67542c274651daf23/multidict-6.1.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:052e10d2d37810b99cc170b785945421141bf7bb7d2f8799d431e7db229c385f", size = 29533 },
+    { url = "https://files.pythonhosted.org/packages/67/5e/04575fd837e0958e324ca035b339cea174554f6f641d3fb2b4f2e7ff44a2/multidict-6.1.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f90c822a402cb865e396a504f9fc8173ef34212a342d92e362ca498cad308e28", size = 29595 },
+    { url = "https://files.pythonhosted.org/packages/d3/b2/e56388f86663810c07cfe4a3c3d87227f3811eeb2d08450b9e5d19d78876/multidict-6.1.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b225d95519a5bf73860323e633a664b0d85ad3d5bede6d30d95b35d4dfe8805b", size = 130094 },
+    { url = "https://files.pythonhosted.org/packages/6c/ee/30ae9b4186a644d284543d55d491fbd4239b015d36b23fea43b4c94f7052/multidict-6.1.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:23bfd518810af7de1116313ebd9092cb9aa629beb12f6ed631ad53356ed6b86c", size = 134876 },
+    { url = "https://files.pythonhosted.org/packages/84/c7/70461c13ba8ce3c779503c70ec9d0345ae84de04521c1f45a04d5f48943d/multidict-6.1.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5c09fcfdccdd0b57867577b719c69e347a436b86cd83747f179dbf0cc0d4c1f3", size = 133500 },
+    { url = "https://files.pythonhosted.org/packages/4a/9f/002af221253f10f99959561123fae676148dd730e2daa2cd053846a58507/multidict-6.1.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf6bea52ec97e95560af5ae576bdac3aa3aae0b6758c6efa115236d9e07dae44", size = 131099 },
+    { url = "https://files.pythonhosted.org/packages/82/42/d1c7a7301d52af79d88548a97e297f9d99c961ad76bbe6f67442bb77f097/multidict-6.1.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:57feec87371dbb3520da6192213c7d6fc892d5589a93db548331954de8248fd2", size = 120403 },
+    { url = "https://files.pythonhosted.org/packages/68/f3/471985c2c7ac707547553e8f37cff5158030d36bdec4414cb825fbaa5327/multidict-6.1.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:0c3f390dc53279cbc8ba976e5f8035eab997829066756d811616b652b00a23a3", size = 125348 },
+    { url = "https://files.pythonhosted.org/packages/67/2c/e6df05c77e0e433c214ec1d21ddd203d9a4770a1f2866a8ca40a545869a0/multidict-6.1.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:59bfeae4b25ec05b34f1956eaa1cb38032282cd4dfabc5056d0a1ec4d696d3aa", size = 119673 },
+    { url = "https://files.pythonhosted.org/packages/c5/cd/bc8608fff06239c9fb333f9db7743a1b2eafe98c2666c9a196e867a3a0a4/multidict-6.1.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:b2f59caeaf7632cc633b5cf6fc449372b83bbdf0da4ae04d5be36118e46cc0aa", size = 129927 },
+    { url = "https://files.pythonhosted.org/packages/44/8e/281b69b7bc84fc963a44dc6e0bbcc7150e517b91df368a27834299a526ac/multidict-6.1.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:37bb93b2178e02b7b618893990941900fd25b6b9ac0fa49931a40aecdf083fe4", size = 128711 },
+    { url = "https://files.pythonhosted.org/packages/12/a4/63e7cd38ed29dd9f1881d5119f272c898ca92536cdb53ffe0843197f6c85/multidict-6.1.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:4e9f48f58c2c523d5a06faea47866cd35b32655c46b443f163d08c6d0ddb17d6", size = 125519 },
+    { url = "https://files.pythonhosted.org/packages/38/e0/4f5855037a72cd8a7a2f60a3952d9aa45feedb37ae7831642102604e8a37/multidict-6.1.0-cp313-cp313-win32.whl", hash = "sha256:3a37ffb35399029b45c6cc33640a92bef403c9fd388acce75cdc88f58bd19a81", size = 26426 },
+    { url = "https://files.pythonhosted.org/packages/7e/a5/17ee3a4db1e310b7405f5d25834460073a8ccd86198ce044dfaf69eac073/multidict-6.1.0-cp313-cp313-win_amd64.whl", hash = "sha256:e9aa71e15d9d9beaad2c6b9319edcdc0a49a43ef5c0a4c8265ca9ee7d6c67774", size = 28531 },
+    { url = "https://files.pythonhosted.org/packages/e7/c9/9e153a6572b38ac5ff4434113af38acf8d5e9957897cdb1f513b3d6614ed/multidict-6.1.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:4e18b656c5e844539d506a0a06432274d7bd52a7487e6828c63a63d69185626c", size = 48550 },
+    { url = "https://files.pythonhosted.org/packages/76/f5/79565ddb629eba6c7f704f09a09df085c8dc04643b12506f10f718cee37a/multidict-6.1.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:a185f876e69897a6f3325c3f19f26a297fa058c5e456bfcff8015e9a27e83ae1", size = 29298 },
+    { url = "https://files.pythonhosted.org/packages/60/1b/9851878b704bc98e641a3e0bce49382ae9e05743dac6d97748feb5b7baba/multidict-6.1.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:ab7c4ceb38d91570a650dba194e1ca87c2b543488fe9309b4212694174fd539c", size = 29641 },
+    { url = "https://files.pythonhosted.org/packages/89/87/d451d45aab9e422cb0fb2f7720c31a4c1d3012c740483c37f642eba568fb/multidict-6.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e617fb6b0b6953fffd762669610c1c4ffd05632c138d61ac7e14ad187870669c", size = 126202 },
+    { url = "https://files.pythonhosted.org/packages/fa/b4/27cbe9f3e2e469359887653f2e45470272eef7295139916cc21107c6b48c/multidict-6.1.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:16e5f4bf4e603eb1fdd5d8180f1a25f30056f22e55ce51fb3d6ad4ab29f7d96f", size = 133925 },
+    { url = "https://files.pythonhosted.org/packages/4d/a3/afc841899face8adfd004235ce759a37619f6ec99eafd959650c5ce4df57/multidict-6.1.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f4c035da3f544b1882bac24115f3e2e8760f10a0107614fc9839fd232200b875", size = 129039 },
+    { url = "https://files.pythonhosted.org/packages/5e/41/0d0fb18c1ad574f807196f5f3d99164edf9de3e169a58c6dc2d6ed5742b9/multidict-6.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:957cf8e4b6e123a9eea554fa7ebc85674674b713551de587eb318a2df3e00255", size = 124072 },
+    { url = "https://files.pythonhosted.org/packages/00/22/defd7a2e71a44e6e5b9a5428f972e5b572e7fe28e404dfa6519bbf057c93/multidict-6.1.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:483a6aea59cb89904e1ceabd2b47368b5600fb7de78a6e4a2c2987b2d256cf30", size = 116532 },
+    { url = "https://files.pythonhosted.org/packages/91/25/f7545102def0b1d456ab6449388eed2dfd822debba1d65af60194904a23a/multidict-6.1.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:87701f25a2352e5bf7454caa64757642734da9f6b11384c1f9d1a8e699758057", size = 128173 },
+    { url = "https://files.pythonhosted.org/packages/45/79/3dbe8d35fc99f5ea610813a72ab55f426cb9cf482f860fa8496e5409be11/multidict-6.1.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:682b987361e5fd7a139ed565e30d81fd81e9629acc7d925a205366877d8c8657", size = 122654 },
+    { url = "https://files.pythonhosted.org/packages/97/cb/209e735eeab96e1b160825b5d0b36c56d3862abff828fc43999bb957dcad/multidict-6.1.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:ce2186a7df133a9c895dea3331ddc5ddad42cdd0d1ea2f0a51e5d161e4762f28", size = 133197 },
+    { url = "https://files.pythonhosted.org/packages/e4/3a/a13808a7ada62808afccea67837a79d00ad6581440015ef00f726d064c2d/multidict-6.1.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:9f636b730f7e8cb19feb87094949ba54ee5357440b9658b2a32a5ce4bce53972", size = 129754 },
+    { url = "https://files.pythonhosted.org/packages/77/dd/8540e139eafb240079242da8f8ffdf9d3f4b4ad1aac5a786cd4050923783/multidict-6.1.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:73eae06aa53af2ea5270cc066dcaf02cc60d2994bbb2c4ef5764949257d10f43", size = 126402 },
+    { url = "https://files.pythonhosted.org/packages/86/99/e82e1a275d8b1ea16d3a251474262258dbbe41c05cce0c01bceda1fc8ea5/multidict-6.1.0-cp39-cp39-win32.whl", hash = "sha256:1ca0083e80e791cffc6efce7660ad24af66c8d4079d2a750b29001b53ff59ada", size = 26421 },
+    { url = "https://files.pythonhosted.org/packages/86/1c/9fa630272355af7e4446a2c7550c259f11ee422ab2d30ff90a0a71cf3d9e/multidict-6.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:aa466da5b15ccea564bdab9c89175c762bc12825f4659c11227f515cee76fa4a", size = 28791 },
+    { url = "https://files.pythonhosted.org/packages/99/b7/b9e70fde2c0f0c9af4cc5277782a89b66d35948ea3369ec9f598358c3ac5/multidict-6.1.0-py3-none-any.whl", hash = "sha256:48e171e52d1c4d33888e529b999e5900356b9ae588c2f09a52dcefb158b27506", size = 10051 },
+]
+
 [[package]]
 name = "mypy"
 version = "1.14.1"
@@ -788,6 +1083,118 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/2a/e2/5d3f6ada4297caebe1a2add3b126fe800c96f56dbe5d1988a2cbe0b267aa/mypy_extensions-1.0.0-py3-none-any.whl", hash = "sha256:4392f6c0eb8a5668a69e23d168ffa70f0be9ccfd32b5cc2d26a34ae5b844552d", size = 4695 },
 ]
 
+[[package]]
+name = "numpy"
+version = "1.26.4"
+source = { registry = "https://pypi.org/simple" }
+resolution-markers = [
+    "python_full_version < '3.12'",
+]
+sdist = { url = "https://files.pythonhosted.org/packages/65/6e/09db70a523a96d25e115e71cc56a6f9031e7b8cd166c1ac8438307c14058/numpy-1.26.4.tar.gz", hash = "sha256:2a02aba9ed12e4ac4eb3ea9421c420301a0c6460d9830d74a9df87efa4912010", size = 15786129 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a7/94/ace0fdea5241a27d13543ee117cbc65868e82213fb31a8eb7fe9ff23f313/numpy-1.26.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:9ff0f4f29c51e2803569d7a51c2304de5554655a60c5d776e35b4a41413830d0", size = 20631468 },
+    { url = "https://files.pythonhosted.org/packages/20/f7/b24208eba89f9d1b58c1668bc6c8c4fd472b20c45573cb767f59d49fb0f6/numpy-1.26.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2e4ee3380d6de9c9ec04745830fd9e2eccb3e6cf790d39d7b98ffd19b0dd754a", size = 13966411 },
+    { url = "https://files.pythonhosted.org/packages/fc/a5/4beee6488160798683eed5bdb7eead455892c3b4e1f78d79d8d3f3b084ac/numpy-1.26.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d209d8969599b27ad20994c8e41936ee0964e6da07478d6c35016bc386b66ad4", size = 14219016 },
+    { url = "https://files.pythonhosted.org/packages/4b/d7/ecf66c1cd12dc28b4040b15ab4d17b773b87fa9d29ca16125de01adb36cd/numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ffa75af20b44f8dba823498024771d5ac50620e6915abac414251bd971b4529f", size = 18240889 },
+    { url = "https://files.pythonhosted.org/packages/24/03/6f229fe3187546435c4f6f89f6d26c129d4f5bed40552899fcf1f0bf9e50/numpy-1.26.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:62b8e4b1e28009ef2846b4c7852046736bab361f7aeadeb6a5b89ebec3c7055a", size = 13876746 },
+    { url = "https://files.pythonhosted.org/packages/39/fe/39ada9b094f01f5a35486577c848fe274e374bbf8d8f472e1423a0bbd26d/numpy-1.26.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:a4abb4f9001ad2858e7ac189089c42178fcce737e4169dc61321660f1a96c7d2", size = 18078620 },
+    { url = "https://files.pythonhosted.org/packages/d5/ef/6ad11d51197aad206a9ad2286dc1aac6a378059e06e8cf22cd08ed4f20dc/numpy-1.26.4-cp310-cp310-win32.whl", hash = "sha256:bfe25acf8b437eb2a8b2d49d443800a5f18508cd811fea3181723922a8a82b07", size = 5972659 },
+    { url = "https://files.pythonhosted.org/packages/19/77/538f202862b9183f54108557bfda67e17603fc560c384559e769321c9d92/numpy-1.26.4-cp310-cp310-win_amd64.whl", hash = "sha256:b97fe8060236edf3662adfc2c633f56a08ae30560c56310562cb4f95500022d5", size = 15808905 },
+    { url = "https://files.pythonhosted.org/packages/11/57/baae43d14fe163fa0e4c47f307b6b2511ab8d7d30177c491960504252053/numpy-1.26.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4c66707fabe114439db9068ee468c26bbdf909cac0fb58686a42a24de1760c71", size = 20630554 },
+    { url = "https://files.pythonhosted.org/packages/1a/2e/151484f49fd03944c4a3ad9c418ed193cfd02724e138ac8a9505d056c582/numpy-1.26.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:edd8b5fe47dab091176d21bb6de568acdd906d1887a4584a15a9a96a1dca06ef", size = 13997127 },
+    { url = "https://files.pythonhosted.org/packages/79/ae/7e5b85136806f9dadf4878bf73cf223fe5c2636818ba3ab1c585d0403164/numpy-1.26.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ab55401287bfec946ced39700c053796e7cc0e3acbef09993a9ad2adba6ca6e", size = 14222994 },
+    { url = "https://files.pythonhosted.org/packages/3a/d0/edc009c27b406c4f9cbc79274d6e46d634d139075492ad055e3d68445925/numpy-1.26.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:666dbfb6ec68962c033a450943ded891bed2d54e6755e35e5835d63f4f6931d5", size = 18252005 },
+    { url = "https://files.pythonhosted.org/packages/09/bf/2b1aaf8f525f2923ff6cfcf134ae5e750e279ac65ebf386c75a0cf6da06a/numpy-1.26.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:96ff0b2ad353d8f990b63294c8986f1ec3cb19d749234014f4e7eb0112ceba5a", size = 13885297 },
+    { url = "https://files.pythonhosted.org/packages/df/a0/4e0f14d847cfc2a633a1c8621d00724f3206cfeddeb66d35698c4e2cf3d2/numpy-1.26.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:60dedbb91afcbfdc9bc0b1f3f402804070deed7392c23eb7a7f07fa857868e8a", size = 18093567 },
+    { url = "https://files.pythonhosted.org/packages/d2/b7/a734c733286e10a7f1a8ad1ae8c90f2d33bf604a96548e0a4a3a6739b468/numpy-1.26.4-cp311-cp311-win32.whl", hash = "sha256:1af303d6b2210eb850fcf03064d364652b7120803a0b872f5211f5234b399f20", size = 5968812 },
+    { url = "https://files.pythonhosted.org/packages/3f/6b/5610004206cf7f8e7ad91c5a85a8c71b2f2f8051a0c0c4d5916b76d6cbb2/numpy-1.26.4-cp311-cp311-win_amd64.whl", hash = "sha256:cd25bcecc4974d09257ffcd1f098ee778f7834c3ad767fe5db785be9a4aa9cb2", size = 15811913 },
+    { url = "https://files.pythonhosted.org/packages/95/12/8f2020a8e8b8383ac0177dc9570aad031a3beb12e38847f7129bacd96228/numpy-1.26.4-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:b3ce300f3644fb06443ee2222c2201dd3a89ea6040541412b8fa189341847218", size = 20335901 },
+    { url = "https://files.pythonhosted.org/packages/75/5b/ca6c8bd14007e5ca171c7c03102d17b4f4e0ceb53957e8c44343a9546dcc/numpy-1.26.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b", size = 13685868 },
+    { url = "https://files.pythonhosted.org/packages/79/f8/97f10e6755e2a7d027ca783f63044d5b1bc1ae7acb12afe6a9b4286eac17/numpy-1.26.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9fad7dcb1aac3c7f0584a5a8133e3a43eeb2fe127f47e3632d43d677c66c102b", size = 13925109 },
+    { url = "https://files.pythonhosted.org/packages/0f/50/de23fde84e45f5c4fda2488c759b69990fd4512387a8632860f3ac9cd225/numpy-1.26.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:675d61ffbfa78604709862923189bad94014bef562cc35cf61d3a07bba02a7ed", size = 17950613 },
+    { url = "https://files.pythonhosted.org/packages/4c/0c/9c603826b6465e82591e05ca230dfc13376da512b25ccd0894709b054ed0/numpy-1.26.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:ab47dbe5cc8210f55aa58e4805fe224dac469cde56b9f731a4c098b91917159a", size = 13572172 },
+    { url = "https://files.pythonhosted.org/packages/76/8c/2ba3902e1a0fc1c74962ea9bb33a534bb05984ad7ff9515bf8d07527cadd/numpy-1.26.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:1dda2e7b4ec9dd512f84935c5f126c8bd8b9f2fc001e9f54af255e8c5f16b0e0", size = 17786643 },
+    { url = "https://files.pythonhosted.org/packages/28/4a/46d9e65106879492374999e76eb85f87b15328e06bd1550668f79f7b18c6/numpy-1.26.4-cp312-cp312-win32.whl", hash = "sha256:50193e430acfc1346175fcbdaa28ffec49947a06918b7b92130744e81e640110", size = 5677803 },
+    { url = "https://files.pythonhosted.org/packages/16/2e/86f24451c2d530c88daf997cb8d6ac622c1d40d19f5a031ed68a4b73a374/numpy-1.26.4-cp312-cp312-win_amd64.whl", hash = "sha256:08beddf13648eb95f8d867350f6a018a4be2e5ad54c8d8caed89ebca558b2818", size = 15517754 },
+    { url = "https://files.pythonhosted.org/packages/7d/24/ce71dc08f06534269f66e73c04f5709ee024a1afe92a7b6e1d73f158e1f8/numpy-1.26.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:7349ab0fa0c429c82442a27a9673fc802ffdb7c7775fad780226cb234965e53c", size = 20636301 },
+    { url = "https://files.pythonhosted.org/packages/ae/8c/ab03a7c25741f9ebc92684a20125fbc9fc1b8e1e700beb9197d750fdff88/numpy-1.26.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:52b8b60467cd7dd1e9ed082188b4e6bb35aa5cdd01777621a1658910745b90be", size = 13971216 },
+    { url = "https://files.pythonhosted.org/packages/6d/64/c3bcdf822269421d85fe0d64ba972003f9bb4aa9a419da64b86856c9961f/numpy-1.26.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d5241e0a80d808d70546c697135da2c613f30e28251ff8307eb72ba696945764", size = 14226281 },
+    { url = "https://files.pythonhosted.org/packages/54/30/c2a907b9443cf42b90c17ad10c1e8fa801975f01cb9764f3f8eb8aea638b/numpy-1.26.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f870204a840a60da0b12273ef34f7051e98c3b5961b61b0c2c1be6dfd64fbcd3", size = 18249516 },
+    { url = "https://files.pythonhosted.org/packages/43/12/01a563fc44c07095996d0129b8899daf89e4742146f7044cdbdb3101c57f/numpy-1.26.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:679b0076f67ecc0138fd2ede3a8fd196dddc2ad3254069bcb9faf9a79b1cebcd", size = 13882132 },
+    { url = "https://files.pythonhosted.org/packages/16/ee/9df80b06680aaa23fc6c31211387e0db349e0e36d6a63ba3bd78c5acdf11/numpy-1.26.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:47711010ad8555514b434df65f7d7b076bb8261df1ca9bb78f53d3b2db02e95c", size = 18084181 },
+    { url = "https://files.pythonhosted.org/packages/28/7d/4b92e2fe20b214ffca36107f1a3e75ef4c488430e64de2d9af5db3a4637d/numpy-1.26.4-cp39-cp39-win32.whl", hash = "sha256:a354325ee03388678242a4d7ebcd08b5c727033fcff3b2f536aea978e15ee9e6", size = 5976360 },
+    { url = "https://files.pythonhosted.org/packages/b5/42/054082bd8220bbf6f297f982f0a8f5479fcbc55c8b511d928df07b965869/numpy-1.26.4-cp39-cp39-win_amd64.whl", hash = "sha256:3373d5d70a5fe74a2c1bb6d2cfd9609ecf686d47a2d7b1d37a8f3b6bf6003aea", size = 15814633 },
+    { url = "https://files.pythonhosted.org/packages/3f/72/3df6c1c06fc83d9cfe381cccb4be2532bbd38bf93fbc9fad087b6687f1c0/numpy-1.26.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:afedb719a9dcfc7eaf2287b839d8198e06dcd4cb5d276a3df279231138e83d30", size = 20455961 },
+    { url = "https://files.pythonhosted.org/packages/8e/02/570545bac308b58ffb21adda0f4e220ba716fb658a63c151daecc3293350/numpy-1.26.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:95a7476c59002f2f6c590b9b7b998306fba6a5aa646b1e22ddfeaf8f78c3a29c", size = 18061071 },
+    { url = "https://files.pythonhosted.org/packages/f4/5f/fafd8c51235f60d49f7a88e2275e13971e90555b67da52dd6416caec32fe/numpy-1.26.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:7e50d0a0cc3189f9cb0aeb3a6a6af18c16f59f004b866cd2be1c14b36134a4a0", size = 15709730 },
+]
+
+[[package]]
+name = "numpy"
+version = "2.2.2"
+source = { registry = "https://pypi.org/simple" }
+resolution-markers = [
+    "python_full_version >= '3.12.4'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4'",
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ec/d0/c12ddfd3a02274be06ffc71f3efc6d0e457b0409c4481596881e748cb264/numpy-2.2.2.tar.gz", hash = "sha256:ed6906f61834d687738d25988ae117683705636936cc605be0bb208b23df4d8f", size = 20233295 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/70/2a/69033dc22d981ad21325314f8357438078f5c28310a6d89fb3833030ec8a/numpy-2.2.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7079129b64cb78bdc8d611d1fd7e8002c0a2565da6a47c4df8062349fee90e3e", size = 21215825 },
+    { url = "https://files.pythonhosted.org/packages/31/2c/39f91e00bbd3d5639b027ac48c55dc5f2992bd2b305412d26be4c830862a/numpy-2.2.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2ec6c689c61df613b783aeb21f945c4cbe6c51c28cb70aae8430577ab39f163e", size = 14354996 },
+    { url = "https://files.pythonhosted.org/packages/0a/2c/d468ebd253851af10de5b3e8f3418ebabfaab5f0337a75299fbeb8b8c17a/numpy-2.2.2-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:40c7ff5da22cd391944a28c6a9c638a5eef77fcf71d6e3a79e1d9d9e82752715", size = 5393621 },
+    { url = "https://files.pythonhosted.org/packages/7f/f4/3d8a5a0da297034106c5de92be881aca7079cde6058934215a1de91334f6/numpy-2.2.2-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:995f9e8181723852ca458e22de5d9b7d3ba4da3f11cc1cb113f093b271d7965a", size = 6928931 },
+    { url = "https://files.pythonhosted.org/packages/47/a7/029354ab56edd43dd3f5efbfad292b8844f98b93174f322f82353fa46efa/numpy-2.2.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b78ea78450fd96a498f50ee096f69c75379af5138f7881a51355ab0e11286c97", size = 14333157 },
+    { url = "https://files.pythonhosted.org/packages/e3/d7/11fc594838d35c43519763310c316d4fd56f8600d3fc80a8e13e325b5c5c/numpy-2.2.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3fbe72d347fbc59f94124125e73fc4976a06927ebc503ec5afbfb35f193cd957", size = 16381794 },
+    { url = "https://files.pythonhosted.org/packages/af/d4/dd9b19cd4aff9c79d3f54d17f8be815407520d3116004bc574948336981b/numpy-2.2.2-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:8e6da5cffbbe571f93588f562ed130ea63ee206d12851b60819512dd3e1ba50d", size = 15543990 },
+    { url = "https://files.pythonhosted.org/packages/30/97/ab96b7650f27f684a9b1e46757a7294ecc50cab27701d05f146e9f779627/numpy-2.2.2-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:09d6a2032faf25e8d0cadde7fd6145118ac55d2740132c1d845f98721b5ebcfd", size = 18170896 },
+    { url = "https://files.pythonhosted.org/packages/81/9b/bae9618cab20db67a2ca9d711795cad29b2ca4b73034dd3b5d05b962070a/numpy-2.2.2-cp310-cp310-win32.whl", hash = "sha256:159ff6ee4c4a36a23fe01b7c3d07bd8c14cc433d9720f977fcd52c13c0098160", size = 6573458 },
+    { url = "https://files.pythonhosted.org/packages/92/9b/95678092febd14070cfb7906ea7932e71e9dd5a6ab3ee948f9ed975e905d/numpy-2.2.2-cp310-cp310-win_amd64.whl", hash = "sha256:64bd6e1762cd7f0986a740fee4dff927b9ec2c5e4d9a28d056eb17d332158014", size = 12915812 },
+    { url = "https://files.pythonhosted.org/packages/21/67/32c68756eed84df181c06528ff57e09138f893c4653448c4967311e0f992/numpy-2.2.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:642199e98af1bd2b6aeb8ecf726972d238c9877b0f6e8221ee5ab945ec8a2189", size = 21220002 },
+    { url = "https://files.pythonhosted.org/packages/3b/89/f43bcad18f2b2e5814457b1c7f7b0e671d0db12c8c0e43397ab8cb1831ed/numpy-2.2.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:6d9fc9d812c81e6168b6d405bf00b8d6739a7f72ef22a9214c4241e0dc70b323", size = 14391215 },
+    { url = "https://files.pythonhosted.org/packages/9c/e6/efb8cd6122bf25e86e3dd89d9dbfec9e6861c50e8810eed77d4be59b51c6/numpy-2.2.2-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:c7d1fd447e33ee20c1f33f2c8e6634211124a9aabde3c617687d8b739aa69eac", size = 5391918 },
+    { url = "https://files.pythonhosted.org/packages/47/e2/fccf89d64d9b47ffb242823d4e851fc9d36fa751908c9aac2807924d9b4e/numpy-2.2.2-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:451e854cfae0febe723077bd0cf0a4302a5d84ff25f0bfece8f29206c7bed02e", size = 6933133 },
+    { url = "https://files.pythonhosted.org/packages/34/22/5ece749c0e5420a9380eef6fbf83d16a50010bd18fef77b9193d80a6760e/numpy-2.2.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bd249bc894af67cbd8bad2c22e7cbcd46cf87ddfca1f1289d1e7e54868cc785c", size = 14338187 },
+    { url = "https://files.pythonhosted.org/packages/5b/86/caec78829311f62afa6fa334c8dfcd79cffb4d24bcf96ee02ae4840d462b/numpy-2.2.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02935e2c3c0c6cbe9c7955a8efa8908dd4221d7755644c59d1bba28b94fd334f", size = 16393429 },
+    { url = "https://files.pythonhosted.org/packages/c8/4e/0c25f74c88239a37924577d6ad780f3212a50f4b4b5f54f5e8c918d726bd/numpy-2.2.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:a972cec723e0563aa0823ee2ab1df0cb196ed0778f173b381c871a03719d4826", size = 15559103 },
+    { url = "https://files.pythonhosted.org/packages/d4/bd/d557f10fa50dc4d5871fb9606af563249b66af2fc6f99041a10e8757c6f1/numpy-2.2.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:d6d6a0910c3b4368d89dde073e630882cdb266755565155bc33520283b2d9df8", size = 18182967 },
+    { url = "https://files.pythonhosted.org/packages/30/e9/66cc0f66386d78ed89e45a56e2a1d051e177b6e04477c4a41cd590ef4017/numpy-2.2.2-cp311-cp311-win32.whl", hash = "sha256:860fd59990c37c3ef913c3ae390b3929d005243acca1a86facb0773e2d8d9e50", size = 6571499 },
+    { url = "https://files.pythonhosted.org/packages/66/a3/4139296b481ae7304a43581046b8f0a20da6a0dfe0ee47a044cade796603/numpy-2.2.2-cp311-cp311-win_amd64.whl", hash = "sha256:da1eeb460ecce8d5b8608826595c777728cdf28ce7b5a5a8c8ac8d949beadcf2", size = 12919805 },
+    { url = "https://files.pythonhosted.org/packages/0c/e6/847d15770ab7a01e807bdfcd4ead5bdae57c0092b7dc83878171b6af97bb/numpy-2.2.2-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:ac9bea18d6d58a995fac1b2cb4488e17eceeac413af014b1dd26170b766d8467", size = 20912636 },
+    { url = "https://files.pythonhosted.org/packages/d1/af/f83580891577b13bd7e261416120e036d0d8fb508c8a43a73e38928b794b/numpy-2.2.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:23ae9f0c2d889b7b2d88a3791f6c09e2ef827c2446f1c4a3e3e76328ee4afd9a", size = 14098403 },
+    { url = "https://files.pythonhosted.org/packages/2b/86/d019fb60a9d0f1d4cf04b014fe88a9135090adfadcc31c1fadbb071d7fa7/numpy-2.2.2-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:3074634ea4d6df66be04f6728ee1d173cfded75d002c75fac79503a880bf3825", size = 5128938 },
+    { url = "https://files.pythonhosted.org/packages/7a/1b/50985edb6f1ec495a1c36452e860476f5b7ecdc3fc59ea89ccad3c4926c5/numpy-2.2.2-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:8ec0636d3f7d68520afc6ac2dc4b8341ddb725039de042faf0e311599f54eb37", size = 6661937 },
+    { url = "https://files.pythonhosted.org/packages/f4/1b/17efd94cad1b9d605c3f8907fb06bcffc4ce4d1d14d46b95316cccccf2b9/numpy-2.2.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2ffbb1acd69fdf8e89dd60ef6182ca90a743620957afb7066385a7bbe88dc748", size = 14049518 },
+    { url = "https://files.pythonhosted.org/packages/5b/73/65d2f0b698df1731e851e3295eb29a5ab8aa06f763f7e4188647a809578d/numpy-2.2.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0349b025e15ea9d05c3d63f9657707a4e1d471128a3b1d876c095f328f8ff7f0", size = 16099146 },
+    { url = "https://files.pythonhosted.org/packages/d5/69/308f55c0e19d4b5057b5df286c5433822e3c8039ede06d4051d96f1c2c4e/numpy-2.2.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:463247edcee4a5537841d5350bc87fe8e92d7dd0e8c71c995d2c6eecb8208278", size = 15246336 },
+    { url = "https://files.pythonhosted.org/packages/f0/d8/d8d333ad0d8518d077a21aeea7b7c826eff766a2b1ce1194dea95ca0bacf/numpy-2.2.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:9dd47ff0cb2a656ad69c38da850df3454da88ee9a6fde0ba79acceee0e79daba", size = 17863507 },
+    { url = "https://files.pythonhosted.org/packages/82/6e/0b84ad3103ffc16d6673e63b5acbe7901b2af96c2837174c6318c98e27ab/numpy-2.2.2-cp312-cp312-win32.whl", hash = "sha256:4525b88c11906d5ab1b0ec1f290996c0020dd318af8b49acaa46f198b1ffc283", size = 6276491 },
+    { url = "https://files.pythonhosted.org/packages/fc/84/7f801a42a67b9772a883223a0a1e12069a14626c81a732bd70aac57aebc1/numpy-2.2.2-cp312-cp312-win_amd64.whl", hash = "sha256:5acea83b801e98541619af398cc0109ff48016955cc0818f478ee9ef1c5c3dcb", size = 12616372 },
+    { url = "https://files.pythonhosted.org/packages/e1/fe/df5624001f4f5c3e0b78e9017bfab7fdc18a8d3b3d3161da3d64924dd659/numpy-2.2.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:b208cfd4f5fe34e1535c08983a1a6803fdbc7a1e86cf13dd0c61de0b51a0aadc", size = 20899188 },
+    { url = "https://files.pythonhosted.org/packages/a9/80/d349c3b5ed66bd3cb0214be60c27e32b90a506946857b866838adbe84040/numpy-2.2.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:d0bbe7dd86dca64854f4b6ce2ea5c60b51e36dfd597300057cf473d3615f2369", size = 14113972 },
+    { url = "https://files.pythonhosted.org/packages/9d/50/949ec9cbb28c4b751edfa64503f0913cbfa8d795b4a251e7980f13a8a655/numpy-2.2.2-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:22ea3bb552ade325530e72a0c557cdf2dea8914d3a5e1fecf58fa5dbcc6f43cd", size = 5114294 },
+    { url = "https://files.pythonhosted.org/packages/8d/f3/399c15629d5a0c68ef2aa7621d430b2be22034f01dd7f3c65a9c9666c445/numpy-2.2.2-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:128c41c085cab8a85dc29e66ed88c05613dccf6bc28b3866cd16050a2f5448be", size = 6648426 },
+    { url = "https://files.pythonhosted.org/packages/2c/03/c72474c13772e30e1bc2e558cdffd9123c7872b731263d5648b5c49dd459/numpy-2.2.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:250c16b277e3b809ac20d1f590716597481061b514223c7badb7a0f9993c7f84", size = 14045990 },
+    { url = "https://files.pythonhosted.org/packages/83/9c/96a9ab62274ffafb023f8ee08c88d3d31ee74ca58869f859db6845494fa6/numpy-2.2.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e0c8854b09bc4de7b041148d8550d3bd712b5c21ff6a8ed308085f190235d7ff", size = 16096614 },
+    { url = "https://files.pythonhosted.org/packages/d5/34/cd0a735534c29bec7093544b3a509febc9b0df77718a9b41ffb0809c9f46/numpy-2.2.2-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:b6fb9c32a91ec32a689ec6410def76443e3c750e7cfc3fb2206b985ffb2b85f0", size = 15242123 },
+    { url = "https://files.pythonhosted.org/packages/5e/6d/541717a554a8f56fa75e91886d9b79ade2e595918690eb5d0d3dbd3accb9/numpy-2.2.2-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:57b4012e04cc12b78590a334907e01b3a85efb2107df2b8733ff1ed05fce71de", size = 17859160 },
+    { url = "https://files.pythonhosted.org/packages/b9/a5/fbf1f2b54adab31510728edd06a05c1b30839f37cf8c9747cb85831aaf1b/numpy-2.2.2-cp313-cp313-win32.whl", hash = "sha256:4dbd80e453bd34bd003b16bd802fac70ad76bd463f81f0c518d1245b1c55e3d9", size = 6273337 },
+    { url = "https://files.pythonhosted.org/packages/56/e5/01106b9291ef1d680f82bc47d0c5b5e26dfed15b0754928e8f856c82c881/numpy-2.2.2-cp313-cp313-win_amd64.whl", hash = "sha256:5a8c863ceacae696aff37d1fd636121f1a512117652e5dfb86031c8d84836369", size = 12609010 },
+    { url = "https://files.pythonhosted.org/packages/9f/30/f23d9876de0f08dceb707c4dcf7f8dd7588266745029debb12a3cdd40be6/numpy-2.2.2-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:b3482cb7b3325faa5f6bc179649406058253d91ceda359c104dac0ad320e1391", size = 20924451 },
+    { url = "https://files.pythonhosted.org/packages/6a/ec/6ea85b2da9d5dfa1dbb4cb3c76587fc8ddcae580cb1262303ab21c0926c4/numpy-2.2.2-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:9491100aba630910489c1d0158034e1c9a6546f0b1340f716d522dc103788e39", size = 14122390 },
+    { url = "https://files.pythonhosted.org/packages/68/05/bfbdf490414a7dbaf65b10c78bc243f312c4553234b6d91c94eb7c4b53c2/numpy-2.2.2-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:41184c416143defa34cc8eb9d070b0a5ba4f13a0fa96a709e20584638254b317", size = 5156590 },
+    { url = "https://files.pythonhosted.org/packages/f7/ec/fe2e91b2642b9d6544518388a441bcd65c904cea38d9ff998e2e8ebf808e/numpy-2.2.2-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:7dca87ca328f5ea7dafc907c5ec100d187911f94825f8700caac0b3f4c384b49", size = 6671958 },
+    { url = "https://files.pythonhosted.org/packages/b1/6f/6531a78e182f194d33ee17e59d67d03d0d5a1ce7f6be7343787828d1bd4a/numpy-2.2.2-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0bc61b307655d1a7f9f4b043628b9f2b721e80839914ede634e3d485913e1fb2", size = 14019950 },
+    { url = "https://files.pythonhosted.org/packages/e1/fb/13c58591d0b6294a08cc40fcc6b9552d239d773d520858ae27f39997f2ae/numpy-2.2.2-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fad446ad0bc886855ddf5909cbf8cb5d0faa637aaa6277fb4b19ade134ab3c7", size = 16079759 },
+    { url = "https://files.pythonhosted.org/packages/2c/f2/f2f8edd62abb4b289f65a7f6d1f3650273af00b91b7267a2431be7f1aec6/numpy-2.2.2-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:149d1113ac15005652e8d0d3f6fd599360e1a708a4f98e43c9c77834a28238cb", size = 15226139 },
+    { url = "https://files.pythonhosted.org/packages/aa/29/14a177f1a90b8ad8a592ca32124ac06af5eff32889874e53a308f850290f/numpy-2.2.2-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:106397dbbb1896f99e044efc90360d098b3335060375c26aa89c0d8a97c5f648", size = 17856316 },
+    { url = "https://files.pythonhosted.org/packages/95/03/242ae8d7b97f4e0e4ab8dd51231465fb23ed5e802680d629149722e3faf1/numpy-2.2.2-cp313-cp313t-win32.whl", hash = "sha256:0eec19f8af947a61e968d5429f0bd92fec46d92b0008d0a6685b40d6adf8a4f4", size = 6329134 },
+    { url = "https://files.pythonhosted.org/packages/80/94/cd9e9b04012c015cb6320ab3bf43bc615e248dddfeb163728e800a5d96f0/numpy-2.2.2-cp313-cp313t-win_amd64.whl", hash = "sha256:97b974d3ba0fb4612b77ed35d7627490e8e3dff56ab41454d9e8b23448940576", size = 12696208 },
+    { url = "https://files.pythonhosted.org/packages/96/7e/1dd770ee68916ed358991ab62c2cc353ffd98d0b75b901d52183ca28e8bb/numpy-2.2.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:b0531f0b0e07643eb089df4c509d30d72c9ef40defa53e41363eca8a8cc61495", size = 21047291 },
+    { url = "https://files.pythonhosted.org/packages/d1/3c/ccd08578dc532a8e6927952339d4a02682b776d5e85be49ed0760308433e/numpy-2.2.2-pp310-pypy310_pp73-macosx_14_0_x86_64.whl", hash = "sha256:e9e82dcb3f2ebbc8cb5ce1102d5f1c5ed236bf8a11730fb45ba82e2841ec21df", size = 6792494 },
+    { url = "https://files.pythonhosted.org/packages/7c/28/8754b9aee4f97199f9a047f73bb644b5a2014994a6d7b061ba67134a42de/numpy-2.2.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e0d4142eb40ca6f94539e4db929410f2a46052a0fe7a2c1c59f6179c39938d2a", size = 16197312 },
+    { url = "https://files.pythonhosted.org/packages/26/96/deb93f871f401045a684ca08a009382b247d14996d7a94fea6aa43c67b94/numpy-2.2.2-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:356ca982c188acbfa6af0d694284d8cf20e95b1c3d0aefa8929376fea9146f60", size = 12822674 },
+]
+
 [[package]]
 name = "orjson"
 version = "3.10.15"
@@ -879,6 +1286,95 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/88/5f/e351af9a41f866ac3f1fac4ca0613908d9a41741cfcf2228f4ad853b697d/pluggy-1.5.0-py3-none-any.whl", hash = "sha256:44e1ad92c8ca002de6377e165f3e0f1be63266ab4d554740532335b9d75ea669", size = 20556 },
 ]
 
+[[package]]
+name = "propcache"
+version = "0.2.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/20/c8/2a13f78d82211490855b2fb303b6721348d0787fdd9a12ac46d99d3acde1/propcache-0.2.1.tar.gz", hash = "sha256:3f77ce728b19cb537714499928fe800c3dda29e8d9428778fc7c186da4c09a64", size = 41735 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a7/a5/0ea64c9426959ef145a938e38c832fc551843481d356713ececa9a8a64e8/propcache-0.2.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:6b3f39a85d671436ee3d12c017f8fdea38509e4f25b28eb25877293c98c243f6", size = 79296 },
+    { url = "https://files.pythonhosted.org/packages/76/5a/916db1aba735f55e5eca4733eea4d1973845cf77dfe67c2381a2ca3ce52d/propcache-0.2.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:39d51fbe4285d5db5d92a929e3e21536ea3dd43732c5b177c7ef03f918dff9f2", size = 45622 },
+    { url = "https://files.pythonhosted.org/packages/2d/62/685d3cf268b8401ec12b250b925b21d152b9d193b7bffa5fdc4815c392c2/propcache-0.2.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:6445804cf4ec763dc70de65a3b0d9954e868609e83850a47ca4f0cb64bd79fea", size = 45133 },
+    { url = "https://files.pythonhosted.org/packages/4d/3d/31c9c29ee7192defc05aa4d01624fd85a41cf98e5922aaed206017329944/propcache-0.2.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f9479aa06a793c5aeba49ce5c5692ffb51fcd9a7016e017d555d5e2b0045d212", size = 204809 },
+    { url = "https://files.pythonhosted.org/packages/10/a1/e4050776f4797fc86140ac9a480d5dc069fbfa9d499fe5c5d2fa1ae71f07/propcache-0.2.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d9631c5e8b5b3a0fda99cb0d29c18133bca1e18aea9effe55adb3da1adef80d3", size = 219109 },
+    { url = "https://files.pythonhosted.org/packages/c9/c0/e7ae0df76343d5e107d81e59acc085cea5fd36a48aa53ef09add7503e888/propcache-0.2.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3156628250f46a0895f1f36e1d4fbe062a1af8718ec3ebeb746f1d23f0c5dc4d", size = 217368 },
+    { url = "https://files.pythonhosted.org/packages/fc/e1/e0a2ed6394b5772508868a977d3238f4afb2eebaf9976f0b44a8d347ad63/propcache-0.2.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6b6fb63ae352e13748289f04f37868099e69dba4c2b3e271c46061e82c745634", size = 205124 },
+    { url = "https://files.pythonhosted.org/packages/50/c1/e388c232d15ca10f233c778bbdc1034ba53ede14c207a72008de45b2db2e/propcache-0.2.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:887d9b0a65404929641a9fabb6452b07fe4572b269d901d622d8a34a4e9043b2", size = 195463 },
+    { url = "https://files.pythonhosted.org/packages/0a/fd/71b349b9def426cc73813dbd0f33e266de77305e337c8c12bfb0a2a82bfb/propcache-0.2.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:a96dc1fa45bd8c407a0af03b2d5218392729e1822b0c32e62c5bf7eeb5fb3958", size = 198358 },
+    { url = "https://files.pythonhosted.org/packages/02/f2/d7c497cd148ebfc5b0ae32808e6c1af5922215fe38c7a06e4e722fe937c8/propcache-0.2.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:a7e65eb5c003a303b94aa2c3852ef130230ec79e349632d030e9571b87c4698c", size = 195560 },
+    { url = "https://files.pythonhosted.org/packages/bb/57/f37041bbe5e0dfed80a3f6be2612a3a75b9cfe2652abf2c99bef3455bbad/propcache-0.2.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:999779addc413181912e984b942fbcc951be1f5b3663cd80b2687758f434c583", size = 196895 },
+    { url = "https://files.pythonhosted.org/packages/83/36/ae3cc3e4f310bff2f064e3d2ed5558935cc7778d6f827dce74dcfa125304/propcache-0.2.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:19a0f89a7bb9d8048d9c4370c9c543c396e894c76be5525f5e1ad287f1750ddf", size = 207124 },
+    { url = "https://files.pythonhosted.org/packages/8c/c4/811b9f311f10ce9d31a32ff14ce58500458443627e4df4ae9c264defba7f/propcache-0.2.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:1ac2f5fe02fa75f56e1ad473f1175e11f475606ec9bd0be2e78e4734ad575034", size = 210442 },
+    { url = "https://files.pythonhosted.org/packages/18/dd/a1670d483a61ecac0d7fc4305d91caaac7a8fc1b200ea3965a01cf03bced/propcache-0.2.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:574faa3b79e8ebac7cb1d7930f51184ba1ccf69adfdec53a12f319a06030a68b", size = 203219 },
+    { url = "https://files.pythonhosted.org/packages/f9/2d/30ced5afde41b099b2dc0c6573b66b45d16d73090e85655f1a30c5a24e07/propcache-0.2.1-cp310-cp310-win32.whl", hash = "sha256:03ff9d3f665769b2a85e6157ac8b439644f2d7fd17615a82fa55739bc97863f4", size = 40313 },
+    { url = "https://files.pythonhosted.org/packages/23/84/bd9b207ac80da237af77aa6e153b08ffa83264b1c7882495984fcbfcf85c/propcache-0.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:2d3af2e79991102678f53e0dbf4c35de99b6b8b58f29a27ca0325816364caaba", size = 44428 },
+    { url = "https://files.pythonhosted.org/packages/bc/0f/2913b6791ebefb2b25b4efd4bb2299c985e09786b9f5b19184a88e5778dd/propcache-0.2.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:1ffc3cca89bb438fb9c95c13fc874012f7b9466b89328c3c8b1aa93cdcfadd16", size = 79297 },
+    { url = "https://files.pythonhosted.org/packages/cf/73/af2053aeccd40b05d6e19058419ac77674daecdd32478088b79375b9ab54/propcache-0.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f174bbd484294ed9fdf09437f889f95807e5f229d5d93588d34e92106fbf6717", size = 45611 },
+    { url = "https://files.pythonhosted.org/packages/3c/09/8386115ba7775ea3b9537730e8cf718d83bbf95bffe30757ccf37ec4e5da/propcache-0.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:70693319e0b8fd35dd863e3e29513875eb15c51945bf32519ef52927ca883bc3", size = 45146 },
+    { url = "https://files.pythonhosted.org/packages/03/7a/793aa12f0537b2e520bf09f4c6833706b63170a211ad042ca71cbf79d9cb/propcache-0.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b480c6a4e1138e1aa137c0079b9b6305ec6dcc1098a8ca5196283e8a49df95a9", size = 232136 },
+    { url = "https://files.pythonhosted.org/packages/f1/38/b921b3168d72111769f648314100558c2ea1d52eb3d1ba7ea5c4aa6f9848/propcache-0.2.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d27b84d5880f6d8aa9ae3edb253c59d9f6642ffbb2c889b78b60361eed449787", size = 239706 },
+    { url = "https://files.pythonhosted.org/packages/14/29/4636f500c69b5edea7786db3c34eb6166f3384b905665ce312a6e42c720c/propcache-0.2.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:857112b22acd417c40fa4595db2fe28ab900c8c5fe4670c7989b1c0230955465", size = 238531 },
+    { url = "https://files.pythonhosted.org/packages/85/14/01fe53580a8e1734ebb704a3482b7829a0ef4ea68d356141cf0994d9659b/propcache-0.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cf6c4150f8c0e32d241436526f3c3f9cbd34429492abddbada2ffcff506c51af", size = 231063 },
+    { url = "https://files.pythonhosted.org/packages/33/5c/1d961299f3c3b8438301ccfbff0143b69afcc30c05fa28673cface692305/propcache-0.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:66d4cfda1d8ed687daa4bc0274fcfd5267873db9a5bc0418c2da19273040eeb7", size = 220134 },
+    { url = "https://files.pythonhosted.org/packages/00/d0/ed735e76db279ba67a7d3b45ba4c654e7b02bc2f8050671ec365d8665e21/propcache-0.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c2f992c07c0fca81655066705beae35fc95a2fa7366467366db627d9f2ee097f", size = 220009 },
+    { url = "https://files.pythonhosted.org/packages/75/90/ee8fab7304ad6533872fee982cfff5a53b63d095d78140827d93de22e2d4/propcache-0.2.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:4a571d97dbe66ef38e472703067021b1467025ec85707d57e78711c085984e54", size = 212199 },
+    { url = "https://files.pythonhosted.org/packages/eb/ec/977ffaf1664f82e90737275873461695d4c9407d52abc2f3c3e24716da13/propcache-0.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:bb6178c241278d5fe853b3de743087be7f5f4c6f7d6d22a3b524d323eecec505", size = 214827 },
+    { url = "https://files.pythonhosted.org/packages/57/48/031fb87ab6081764054821a71b71942161619549396224cbb242922525e8/propcache-0.2.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:ad1af54a62ffe39cf34db1aa6ed1a1873bd548f6401db39d8e7cd060b9211f82", size = 228009 },
+    { url = "https://files.pythonhosted.org/packages/1a/06/ef1390f2524850838f2390421b23a8b298f6ce3396a7cc6d39dedd4047b0/propcache-0.2.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:e7048abd75fe40712005bcfc06bb44b9dfcd8e101dda2ecf2f5aa46115ad07ca", size = 231638 },
+    { url = "https://files.pythonhosted.org/packages/38/2a/101e6386d5a93358395da1d41642b79c1ee0f3b12e31727932b069282b1d/propcache-0.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:160291c60081f23ee43d44b08a7e5fb76681221a8e10b3139618c5a9a291b84e", size = 222788 },
+    { url = "https://files.pythonhosted.org/packages/db/81/786f687951d0979007e05ad9346cd357e50e3d0b0f1a1d6074df334b1bbb/propcache-0.2.1-cp311-cp311-win32.whl", hash = "sha256:819ce3b883b7576ca28da3861c7e1a88afd08cc8c96908e08a3f4dd64a228034", size = 40170 },
+    { url = "https://files.pythonhosted.org/packages/cf/59/7cc7037b295d5772eceb426358bb1b86e6cab4616d971bd74275395d100d/propcache-0.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:edc9fc7051e3350643ad929df55c451899bb9ae6d24998a949d2e4c87fb596d3", size = 44404 },
+    { url = "https://files.pythonhosted.org/packages/4c/28/1d205fe49be8b1b4df4c50024e62480a442b1a7b818e734308bb0d17e7fb/propcache-0.2.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:081a430aa8d5e8876c6909b67bd2d937bfd531b0382d3fdedb82612c618bc41a", size = 79588 },
+    { url = "https://files.pythonhosted.org/packages/21/ee/fc4d893f8d81cd4971affef2a6cb542b36617cd1d8ce56b406112cb80bf7/propcache-0.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:d2ccec9ac47cf4e04897619c0e0c1a48c54a71bdf045117d3a26f80d38ab1fb0", size = 45825 },
+    { url = "https://files.pythonhosted.org/packages/4a/de/bbe712f94d088da1d237c35d735f675e494a816fd6f54e9db2f61ef4d03f/propcache-0.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:14d86fe14b7e04fa306e0c43cdbeebe6b2c2156a0c9ce56b815faacc193e320d", size = 45357 },
+    { url = "https://files.pythonhosted.org/packages/7f/14/7ae06a6cf2a2f1cb382586d5a99efe66b0b3d0c6f9ac2f759e6f7af9d7cf/propcache-0.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:049324ee97bb67285b49632132db351b41e77833678432be52bdd0289c0e05e4", size = 241869 },
+    { url = "https://files.pythonhosted.org/packages/cc/59/227a78be960b54a41124e639e2c39e8807ac0c751c735a900e21315f8c2b/propcache-0.2.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1cd9a1d071158de1cc1c71a26014dcdfa7dd3d5f4f88c298c7f90ad6f27bb46d", size = 247884 },
+    { url = "https://files.pythonhosted.org/packages/84/58/f62b4ffaedf88dc1b17f04d57d8536601e4e030feb26617228ef930c3279/propcache-0.2.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:98110aa363f1bb4c073e8dcfaefd3a5cea0f0834c2aab23dda657e4dab2f53b5", size = 248486 },
+    { url = "https://files.pythonhosted.org/packages/1c/07/ebe102777a830bca91bbb93e3479cd34c2ca5d0361b83be9dbd93104865e/propcache-0.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:647894f5ae99c4cf6bb82a1bb3a796f6e06af3caa3d32e26d2350d0e3e3faf24", size = 243649 },
+    { url = "https://files.pythonhosted.org/packages/ed/bc/4f7aba7f08f520376c4bb6a20b9a981a581b7f2e385fa0ec9f789bb2d362/propcache-0.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bfd3223c15bebe26518d58ccf9a39b93948d3dcb3e57a20480dfdd315356baff", size = 229103 },
+    { url = "https://files.pythonhosted.org/packages/fe/d5/04ac9cd4e51a57a96f78795e03c5a0ddb8f23ec098b86f92de028d7f2a6b/propcache-0.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d71264a80f3fcf512eb4f18f59423fe82d6e346ee97b90625f283df56aee103f", size = 226607 },
+    { url = "https://files.pythonhosted.org/packages/e3/f0/24060d959ea41d7a7cc7fdbf68b31852331aabda914a0c63bdb0e22e96d6/propcache-0.2.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:e73091191e4280403bde6c9a52a6999d69cdfde498f1fdf629105247599b57ec", size = 221153 },
+    { url = "https://files.pythonhosted.org/packages/77/a7/3ac76045a077b3e4de4859a0753010765e45749bdf53bd02bc4d372da1a0/propcache-0.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:3935bfa5fede35fb202c4b569bb9c042f337ca4ff7bd540a0aa5e37131659348", size = 222151 },
+    { url = "https://files.pythonhosted.org/packages/e7/af/5e29da6f80cebab3f5a4dcd2a3240e7f56f2c4abf51cbfcc99be34e17f0b/propcache-0.2.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f508b0491767bb1f2b87fdfacaba5f7eddc2f867740ec69ece6d1946d29029a6", size = 233812 },
+    { url = "https://files.pythonhosted.org/packages/8c/89/ebe3ad52642cc5509eaa453e9f4b94b374d81bae3265c59d5c2d98efa1b4/propcache-0.2.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:1672137af7c46662a1c2be1e8dc78cb6d224319aaa40271c9257d886be4363a6", size = 238829 },
+    { url = "https://files.pythonhosted.org/packages/e9/2f/6b32f273fa02e978b7577159eae7471b3cfb88b48563b1c2578b2d7ca0bb/propcache-0.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b74c261802d3d2b85c9df2dfb2fa81b6f90deeef63c2db9f0e029a3cac50b518", size = 230704 },
+    { url = "https://files.pythonhosted.org/packages/5c/2e/f40ae6ff5624a5f77edd7b8359b208b5455ea113f68309e2b00a2e1426b6/propcache-0.2.1-cp312-cp312-win32.whl", hash = "sha256:d09c333d36c1409d56a9d29b3a1b800a42c76a57a5a8907eacdbce3f18768246", size = 40050 },
+    { url = "https://files.pythonhosted.org/packages/3b/77/a92c3ef994e47180862b9d7d11e37624fb1c00a16d61faf55115d970628b/propcache-0.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:c214999039d4f2a5b2073ac506bba279945233da8c786e490d411dfc30f855c1", size = 44117 },
+    { url = "https://files.pythonhosted.org/packages/0f/2a/329e0547cf2def8857157f9477669043e75524cc3e6251cef332b3ff256f/propcache-0.2.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:aca405706e0b0a44cc6bfd41fbe89919a6a56999157f6de7e182a990c36e37bc", size = 77002 },
+    { url = "https://files.pythonhosted.org/packages/12/2d/c4df5415e2382f840dc2ecbca0eeb2293024bc28e57a80392f2012b4708c/propcache-0.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:12d1083f001ace206fe34b6bdc2cb94be66d57a850866f0b908972f90996b3e9", size = 44639 },
+    { url = "https://files.pythonhosted.org/packages/d0/5a/21aaa4ea2f326edaa4e240959ac8b8386ea31dedfdaa636a3544d9e7a408/propcache-0.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:d93f3307ad32a27bda2e88ec81134b823c240aa3abb55821a8da553eed8d9439", size = 44049 },
+    { url = "https://files.pythonhosted.org/packages/4e/3e/021b6cd86c0acc90d74784ccbb66808b0bd36067a1bf3e2deb0f3845f618/propcache-0.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ba278acf14471d36316159c94a802933d10b6a1e117b8554fe0d0d9b75c9d536", size = 224819 },
+    { url = "https://files.pythonhosted.org/packages/3c/57/c2fdeed1b3b8918b1770a133ba5c43ad3d78e18285b0c06364861ef5cc38/propcache-0.2.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4e6281aedfca15301c41f74d7005e6e3f4ca143584ba696ac69df4f02f40d629", size = 229625 },
+    { url = "https://files.pythonhosted.org/packages/9d/81/70d4ff57bf2877b5780b466471bebf5892f851a7e2ca0ae7ffd728220281/propcache-0.2.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5b750a8e5a1262434fb1517ddf64b5de58327f1adc3524a5e44c2ca43305eb0b", size = 232934 },
+    { url = "https://files.pythonhosted.org/packages/3c/b9/bb51ea95d73b3fb4100cb95adbd4e1acaf2cbb1fd1083f5468eeb4a099a8/propcache-0.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf72af5e0fb40e9babf594308911436c8efde3cb5e75b6f206c34ad18be5c052", size = 227361 },
+    { url = "https://files.pythonhosted.org/packages/f1/20/3c6d696cd6fd70b29445960cc803b1851a1131e7a2e4ee261ee48e002bcd/propcache-0.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b2d0a12018b04f4cb820781ec0dffb5f7c7c1d2a5cd22bff7fb055a2cb19ebce", size = 213904 },
+    { url = "https://files.pythonhosted.org/packages/a1/cb/1593bfc5ac6d40c010fa823f128056d6bc25b667f5393781e37d62f12005/propcache-0.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e800776a79a5aabdb17dcc2346a7d66d0777e942e4cd251defeb084762ecd17d", size = 212632 },
+    { url = "https://files.pythonhosted.org/packages/6d/5c/e95617e222be14a34c709442a0ec179f3207f8a2b900273720501a70ec5e/propcache-0.2.1-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:4160d9283bd382fa6c0c2b5e017acc95bc183570cd70968b9202ad6d8fc48dce", size = 207897 },
+    { url = "https://files.pythonhosted.org/packages/8e/3b/56c5ab3dc00f6375fbcdeefdede5adf9bee94f1fab04adc8db118f0f9e25/propcache-0.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:30b43e74f1359353341a7adb783c8f1b1c676367b011709f466f42fda2045e95", size = 208118 },
+    { url = "https://files.pythonhosted.org/packages/86/25/d7ef738323fbc6ebcbce33eb2a19c5e07a89a3df2fded206065bd5e868a9/propcache-0.2.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:58791550b27d5488b1bb52bc96328456095d96206a250d28d874fafe11b3dfaf", size = 217851 },
+    { url = "https://files.pythonhosted.org/packages/b3/77/763e6cef1852cf1ba740590364ec50309b89d1c818e3256d3929eb92fabf/propcache-0.2.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:0f022d381747f0dfe27e99d928e31bc51a18b65bb9e481ae0af1380a6725dd1f", size = 222630 },
+    { url = "https://files.pythonhosted.org/packages/4f/e9/0f86be33602089c701696fbed8d8c4c07b6ee9605c5b7536fd27ed540c5b/propcache-0.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:297878dc9d0a334358f9b608b56d02e72899f3b8499fc6044133f0d319e2ec30", size = 216269 },
+    { url = "https://files.pythonhosted.org/packages/cc/02/5ac83217d522394b6a2e81a2e888167e7ca629ef6569a3f09852d6dcb01a/propcache-0.2.1-cp313-cp313-win32.whl", hash = "sha256:ddfab44e4489bd79bda09d84c430677fc7f0a4939a73d2bba3073036f487a0a6", size = 39472 },
+    { url = "https://files.pythonhosted.org/packages/f4/33/d6f5420252a36034bc8a3a01171bc55b4bff5df50d1c63d9caa50693662f/propcache-0.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:556fc6c10989f19a179e4321e5d678db8eb2924131e64652a51fe83e4c3db0e1", size = 43363 },
+    { url = "https://files.pythonhosted.org/packages/0a/08/6ab7f65240a16fa01023125e65258acf7e4884f483f267cdd6fcc48f37db/propcache-0.2.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:6a9a8c34fb7bb609419a211e59da8887eeca40d300b5ea8e56af98f6fbbb1541", size = 80403 },
+    { url = "https://files.pythonhosted.org/packages/34/fe/e7180285e21b4e6dff7d311fdf22490c9146a09a02834b5232d6248c6004/propcache-0.2.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:ae1aa1cd222c6d205853b3013c69cd04515f9d6ab6de4b0603e2e1c33221303e", size = 46152 },
+    { url = "https://files.pythonhosted.org/packages/9c/36/aa74d884af826030ba9cee2ac109b0664beb7e9449c315c9c44db99efbb3/propcache-0.2.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:accb6150ce61c9c4b7738d45550806aa2b71c7668c6942f17b0ac182b6142fd4", size = 45674 },
+    { url = "https://files.pythonhosted.org/packages/22/59/6fe80a3fe7720f715f2c0f6df250dacbd7cad42832410dbd84c719c52f78/propcache-0.2.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5eee736daafa7af6d0a2dc15cc75e05c64f37fc37bafef2e00d77c14171c2097", size = 207792 },
+    { url = "https://files.pythonhosted.org/packages/4a/68/584cd51dd8f4d0f5fff5b128ce0cdb257cde903898eecfb92156bbc2c780/propcache-0.2.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f7a31fc1e1bd362874863fdeed71aed92d348f5336fd84f2197ba40c59f061bd", size = 223280 },
+    { url = "https://files.pythonhosted.org/packages/85/cb/4c3528460c41e61b06ec3f970c0f89f87fa21f63acac8642ed81a886c164/propcache-0.2.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cba4cfa1052819d16699e1d55d18c92b6e094d4517c41dd231a8b9f87b6fa681", size = 221293 },
+    { url = "https://files.pythonhosted.org/packages/69/c0/560e050aa6d31eeece3490d1174da508f05ab27536dfc8474af88b97160a/propcache-0.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f089118d584e859c62b3da0892b88a83d611c2033ac410e929cb6754eec0ed16", size = 208259 },
+    { url = "https://files.pythonhosted.org/packages/0c/87/d6c86a77632eb1ba86a328e3313159f246e7564cb5951e05ed77555826a0/propcache-0.2.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:781e65134efaf88feb447e8c97a51772aa75e48b794352f94cb7ea717dedda0d", size = 198632 },
+    { url = "https://files.pythonhosted.org/packages/3a/2b/3690ea7b662dc762ab7af5f3ef0e2d7513c823d193d7b2a1b4cda472c2be/propcache-0.2.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:31f5af773530fd3c658b32b6bdc2d0838543de70eb9a2156c03e410f7b0d3aae", size = 203516 },
+    { url = "https://files.pythonhosted.org/packages/4d/b5/afe716c16c23c77657185c257a41918b83e03993b6ccdfa748e5e7d328e9/propcache-0.2.1-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:a7a078f5d37bee6690959c813977da5291b24286e7b962e62a94cec31aa5188b", size = 199402 },
+    { url = "https://files.pythonhosted.org/packages/a4/c0/2d2df3aa7f8660d0d4cc4f1e00490c48d5958da57082e70dea7af366f876/propcache-0.2.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:cea7daf9fc7ae6687cf1e2c049752f19f146fdc37c2cc376e7d0032cf4f25347", size = 200528 },
+    { url = "https://files.pythonhosted.org/packages/21/c8/65ac9142f5e40c8497f7176e71d18826b09e06dd4eb401c9a4ee41aa9c74/propcache-0.2.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:8b3489ff1ed1e8315674d0775dc7d2195fb13ca17b3808721b54dbe9fd020faf", size = 211254 },
+    { url = "https://files.pythonhosted.org/packages/09/e4/edb70b447a1d8142df51ec7511e84aa64d7f6ce0a0fdf5eb55363cdd0935/propcache-0.2.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:9403db39be1393618dd80c746cb22ccda168efce239c73af13c3763ef56ffc04", size = 214589 },
+    { url = "https://files.pythonhosted.org/packages/cb/02/817f309ec8d8883287781d6d9390f80b14db6e6de08bc659dfe798a825c2/propcache-0.2.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:5d97151bc92d2b2578ff7ce779cdb9174337390a535953cbb9452fb65164c587", size = 207283 },
+    { url = "https://files.pythonhosted.org/packages/d7/fe/2d18612096ed2212cfef821b6fccdba5d52efc1d64511c206c5c16be28fd/propcache-0.2.1-cp39-cp39-win32.whl", hash = "sha256:9caac6b54914bdf41bcc91e7eb9147d331d29235a7c967c150ef5df6464fd1bb", size = 40866 },
+    { url = "https://files.pythonhosted.org/packages/24/2e/b5134802e7b57c403c7b73c7a39374e7a6b7f128d1968b4a4b4c0b700250/propcache-0.2.1-cp39-cp39-win_amd64.whl", hash = "sha256:92fc4500fcb33899b05ba73276dfb684a20d31caa567b7cb5252d48f896a91b1", size = 44975 },
+    { url = "https://files.pythonhosted.org/packages/41/b6/c5319caea262f4821995dca2107483b94a3345d4607ad797c76cb9c36bcc/propcache-0.2.1-py3-none-any.whl", hash = "sha256:52277518d6aae65536e9cea52d4e7fd2f7a66f4aa2d30ed3f2fcea620ace3c54", size = 11818 },
+]
+
 [[package]]
 name = "pycparser"
 version = "2.22"
@@ -1405,6 +1901,100 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/33/e8/e40370e6d74ddba47f002a32919d91310d6074130fe4e17dabcafc15cbf1/watchdog-6.0.0-py3-none-win_ia64.whl", hash = "sha256:a1914259fa9e1454315171103c6a30961236f508b9b623eae470268bbcc6a22f", size = 79067 },
 ]
 
+[[package]]
+name = "yarl"
+version = "1.18.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "idna" },
+    { name = "multidict" },
+    { name = "propcache" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/b7/9d/4b94a8e6d2b51b599516a5cb88e5bc99b4d8d4583e468057eaa29d5f0918/yarl-1.18.3.tar.gz", hash = "sha256:ac1801c45cbf77b6c99242eeff4fffb5e4e73a800b5c4ad4fc0be5def634d2e1", size = 181062 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d2/98/e005bc608765a8a5569f58e650961314873c8469c333616eb40bff19ae97/yarl-1.18.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7df647e8edd71f000a5208fe6ff8c382a1de8edfbccdbbfe649d263de07d8c34", size = 141458 },
+    { url = "https://files.pythonhosted.org/packages/df/5d/f8106b263b8ae8a866b46d9be869ac01f9b3fb7f2325f3ecb3df8003f796/yarl-1.18.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c69697d3adff5aa4f874b19c0e4ed65180ceed6318ec856ebc423aa5850d84f7", size = 94365 },
+    { url = "https://files.pythonhosted.org/packages/56/3e/d8637ddb9ba69bf851f765a3ee288676f7cf64fb3be13760c18cbc9d10bd/yarl-1.18.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:602d98f2c2d929f8e697ed274fbadc09902c4025c5a9963bf4e9edfc3ab6f7ed", size = 92181 },
+    { url = "https://files.pythonhosted.org/packages/76/f9/d616a5c2daae281171de10fba41e1c0e2d8207166fc3547252f7d469b4e1/yarl-1.18.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c654d5207c78e0bd6d749f6dae1dcbbfde3403ad3a4b11f3c5544d9906969dde", size = 315349 },
+    { url = "https://files.pythonhosted.org/packages/bb/b4/3ea5e7b6f08f698b3769a06054783e434f6d59857181b5c4e145de83f59b/yarl-1.18.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5094d9206c64181d0f6e76ebd8fb2f8fe274950a63890ee9e0ebfd58bf9d787b", size = 330494 },
+    { url = "https://files.pythonhosted.org/packages/55/f1/e0fc810554877b1b67420568afff51b967baed5b53bcc983ab164eebf9c9/yarl-1.18.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:35098b24e0327fc4ebdc8ffe336cee0a87a700c24ffed13161af80124b7dc8e5", size = 326927 },
+    { url = "https://files.pythonhosted.org/packages/a9/42/b1753949b327b36f210899f2dd0a0947c0c74e42a32de3f8eb5c7d93edca/yarl-1.18.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3236da9272872443f81fedc389bace88408f64f89f75d1bdb2256069a8730ccc", size = 319703 },
+    { url = "https://files.pythonhosted.org/packages/f0/6d/e87c62dc9635daefb064b56f5c97df55a2e9cc947a2b3afd4fd2f3b841c7/yarl-1.18.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e2c08cc9b16f4f4bc522771d96734c7901e7ebef70c6c5c35dd0f10845270bcd", size = 310246 },
+    { url = "https://files.pythonhosted.org/packages/e3/ef/e2e8d1785cdcbd986f7622d7f0098205f3644546da7919c24b95790ec65a/yarl-1.18.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:80316a8bd5109320d38eef8833ccf5f89608c9107d02d2a7f985f98ed6876990", size = 319730 },
+    { url = "https://files.pythonhosted.org/packages/fc/15/8723e22345bc160dfde68c4b3ae8b236e868f9963c74015f1bc8a614101c/yarl-1.18.3-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:c1e1cc06da1491e6734f0ea1e6294ce00792193c463350626571c287c9a704db", size = 321681 },
+    { url = "https://files.pythonhosted.org/packages/86/09/bf764e974f1516efa0ae2801494a5951e959f1610dd41edbfc07e5e0f978/yarl-1.18.3-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fea09ca13323376a2fdfb353a5fa2e59f90cd18d7ca4eaa1fd31f0a8b4f91e62", size = 324812 },
+    { url = "https://files.pythonhosted.org/packages/f6/4c/20a0187e3b903c97d857cf0272d687c1b08b03438968ae8ffc50fe78b0d6/yarl-1.18.3-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e3b9fd71836999aad54084906f8663dffcd2a7fb5cdafd6c37713b2e72be1760", size = 337011 },
+    { url = "https://files.pythonhosted.org/packages/c9/71/6244599a6e1cc4c9f73254a627234e0dad3883ece40cc33dce6265977461/yarl-1.18.3-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:757e81cae69244257d125ff31663249b3013b5dc0a8520d73694aed497fb195b", size = 338132 },
+    { url = "https://files.pythonhosted.org/packages/af/f5/e0c3efaf74566c4b4a41cb76d27097df424052a064216beccae8d303c90f/yarl-1.18.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:b1771de9944d875f1b98a745bc547e684b863abf8f8287da8466cf470ef52690", size = 331849 },
+    { url = "https://files.pythonhosted.org/packages/8a/b8/3d16209c2014c2f98a8f658850a57b716efb97930aebf1ca0d9325933731/yarl-1.18.3-cp310-cp310-win32.whl", hash = "sha256:8874027a53e3aea659a6d62751800cf6e63314c160fd607489ba5c2edd753cf6", size = 84309 },
+    { url = "https://files.pythonhosted.org/packages/fd/b7/2e9a5b18eb0fe24c3a0e8bae994e812ed9852ab4fd067c0107fadde0d5f0/yarl-1.18.3-cp310-cp310-win_amd64.whl", hash = "sha256:93b2e109287f93db79210f86deb6b9bbb81ac32fc97236b16f7433db7fc437d8", size = 90484 },
+    { url = "https://files.pythonhosted.org/packages/40/93/282b5f4898d8e8efaf0790ba6d10e2245d2c9f30e199d1a85cae9356098c/yarl-1.18.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8503ad47387b8ebd39cbbbdf0bf113e17330ffd339ba1144074da24c545f0069", size = 141555 },
+    { url = "https://files.pythonhosted.org/packages/6d/9c/0a49af78df099c283ca3444560f10718fadb8a18dc8b3edf8c7bd9fd7d89/yarl-1.18.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:02ddb6756f8f4517a2d5e99d8b2f272488e18dd0bfbc802f31c16c6c20f22193", size = 94351 },
+    { url = "https://files.pythonhosted.org/packages/5a/a1/205ab51e148fdcedad189ca8dd587794c6f119882437d04c33c01a75dece/yarl-1.18.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:67a283dd2882ac98cc6318384f565bffc751ab564605959df4752d42483ad889", size = 92286 },
+    { url = "https://files.pythonhosted.org/packages/ed/fe/88b690b30f3f59275fb674f5f93ddd4a3ae796c2b62e5bb9ece8a4914b83/yarl-1.18.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d980e0325b6eddc81331d3f4551e2a333999fb176fd153e075c6d1c2530aa8a8", size = 340649 },
+    { url = "https://files.pythonhosted.org/packages/07/eb/3b65499b568e01f36e847cebdc8d7ccb51fff716dbda1ae83c3cbb8ca1c9/yarl-1.18.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b643562c12680b01e17239be267bc306bbc6aac1f34f6444d1bded0c5ce438ca", size = 356623 },
+    { url = "https://files.pythonhosted.org/packages/33/46/f559dc184280b745fc76ec6b1954de2c55595f0ec0a7614238b9ebf69618/yarl-1.18.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c017a3b6df3a1bd45b9fa49a0f54005e53fbcad16633870104b66fa1a30a29d8", size = 354007 },
+    { url = "https://files.pythonhosted.org/packages/af/ba/1865d85212351ad160f19fb99808acf23aab9a0f8ff31c8c9f1b4d671fc9/yarl-1.18.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75674776d96d7b851b6498f17824ba17849d790a44d282929c42dbb77d4f17ae", size = 344145 },
+    { url = "https://files.pythonhosted.org/packages/94/cb/5c3e975d77755d7b3d5193e92056b19d83752ea2da7ab394e22260a7b824/yarl-1.18.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ccaa3a4b521b780a7e771cc336a2dba389a0861592bbce09a476190bb0c8b4b3", size = 336133 },
+    { url = "https://files.pythonhosted.org/packages/19/89/b77d3fd249ab52a5c40859815765d35c91425b6bb82e7427ab2f78f5ff55/yarl-1.18.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2d06d3005e668744e11ed80812e61efd77d70bb7f03e33c1598c301eea20efbb", size = 347967 },
+    { url = "https://files.pythonhosted.org/packages/35/bd/f6b7630ba2cc06c319c3235634c582a6ab014d52311e7d7c22f9518189b5/yarl-1.18.3-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:9d41beda9dc97ca9ab0b9888cb71f7539124bc05df02c0cff6e5acc5a19dcc6e", size = 346397 },
+    { url = "https://files.pythonhosted.org/packages/18/1a/0b4e367d5a72d1f095318344848e93ea70da728118221f84f1bf6c1e39e7/yarl-1.18.3-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:ba23302c0c61a9999784e73809427c9dbedd79f66a13d84ad1b1943802eaaf59", size = 350206 },
+    { url = "https://files.pythonhosted.org/packages/b5/cf/320fff4367341fb77809a2d8d7fe75b5d323a8e1b35710aafe41fdbf327b/yarl-1.18.3-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:6748dbf9bfa5ba1afcc7556b71cda0d7ce5f24768043a02a58846e4a443d808d", size = 362089 },
+    { url = "https://files.pythonhosted.org/packages/57/cf/aadba261d8b920253204085268bad5e8cdd86b50162fcb1b10c10834885a/yarl-1.18.3-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:0b0cad37311123211dc91eadcb322ef4d4a66008d3e1bdc404808992260e1a0e", size = 366267 },
+    { url = "https://files.pythonhosted.org/packages/54/58/fb4cadd81acdee6dafe14abeb258f876e4dd410518099ae9a35c88d8097c/yarl-1.18.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:0fb2171a4486bb075316ee754c6d8382ea6eb8b399d4ec62fde2b591f879778a", size = 359141 },
+    { url = "https://files.pythonhosted.org/packages/9a/7a/4c571597589da4cd5c14ed2a0b17ac56ec9ee7ee615013f74653169e702d/yarl-1.18.3-cp311-cp311-win32.whl", hash = "sha256:61b1a825a13bef4a5f10b1885245377d3cd0bf87cba068e1d9a88c2ae36880e1", size = 84402 },
+    { url = "https://files.pythonhosted.org/packages/ae/7b/8600250b3d89b625f1121d897062f629883c2f45339623b69b1747ec65fa/yarl-1.18.3-cp311-cp311-win_amd64.whl", hash = "sha256:b9d60031cf568c627d028239693fd718025719c02c9f55df0a53e587aab951b5", size = 91030 },
+    { url = "https://files.pythonhosted.org/packages/33/85/bd2e2729752ff4c77338e0102914897512e92496375e079ce0150a6dc306/yarl-1.18.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:1dd4bdd05407ced96fed3d7f25dbbf88d2ffb045a0db60dbc247f5b3c5c25d50", size = 142644 },
+    { url = "https://files.pythonhosted.org/packages/ff/74/1178322cc0f10288d7eefa6e4a85d8d2e28187ccab13d5b844e8b5d7c88d/yarl-1.18.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7c33dd1931a95e5d9a772d0ac5e44cac8957eaf58e3c8da8c1414de7dd27c576", size = 94962 },
+    { url = "https://files.pythonhosted.org/packages/be/75/79c6acc0261e2c2ae8a1c41cf12265e91628c8c58ae91f5ff59e29c0787f/yarl-1.18.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:25b411eddcfd56a2f0cd6a384e9f4f7aa3efee14b188de13048c25b5e91f1640", size = 92795 },
+    { url = "https://files.pythonhosted.org/packages/6b/32/927b2d67a412c31199e83fefdce6e645247b4fb164aa1ecb35a0f9eb2058/yarl-1.18.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:436c4fc0a4d66b2badc6c5fc5ef4e47bb10e4fd9bf0c79524ac719a01f3607c2", size = 332368 },
+    { url = "https://files.pythonhosted.org/packages/19/e5/859fca07169d6eceeaa4fde1997c91d8abde4e9a7c018e371640c2da2b71/yarl-1.18.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e35ef8683211db69ffe129a25d5634319a677570ab6b2eba4afa860f54eeaf75", size = 342314 },
+    { url = "https://files.pythonhosted.org/packages/08/75/76b63ccd91c9e03ab213ef27ae6add2e3400e77e5cdddf8ed2dbc36e3f21/yarl-1.18.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84b2deecba4a3f1a398df819151eb72d29bfeb3b69abb145a00ddc8d30094512", size = 341987 },
+    { url = "https://files.pythonhosted.org/packages/1a/e1/a097d5755d3ea8479a42856f51d97eeff7a3a7160593332d98f2709b3580/yarl-1.18.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:00e5a1fea0fd4f5bfa7440a47eff01d9822a65b4488f7cff83155a0f31a2ecba", size = 336914 },
+    { url = "https://files.pythonhosted.org/packages/0b/42/e1b4d0e396b7987feceebe565286c27bc085bf07d61a59508cdaf2d45e63/yarl-1.18.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d0e883008013c0e4aef84dcfe2a0b172c4d23c2669412cf5b3371003941f72bb", size = 325765 },
+    { url = "https://files.pythonhosted.org/packages/7e/18/03a5834ccc9177f97ca1bbb245b93c13e58e8225276f01eedc4cc98ab820/yarl-1.18.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5a3f356548e34a70b0172d8890006c37be92995f62d95a07b4a42e90fba54272", size = 344444 },
+    { url = "https://files.pythonhosted.org/packages/c8/03/a713633bdde0640b0472aa197b5b86e90fbc4c5bc05b727b714cd8a40e6d/yarl-1.18.3-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ccd17349166b1bee6e529b4add61727d3f55edb7babbe4069b5764c9587a8cc6", size = 340760 },
+    { url = "https://files.pythonhosted.org/packages/eb/99/f6567e3f3bbad8fd101886ea0276c68ecb86a2b58be0f64077396cd4b95e/yarl-1.18.3-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:b958ddd075ddba5b09bb0be8a6d9906d2ce933aee81100db289badbeb966f54e", size = 346484 },
+    { url = "https://files.pythonhosted.org/packages/8e/a9/84717c896b2fc6cb15bd4eecd64e34a2f0a9fd6669e69170c73a8b46795a/yarl-1.18.3-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:c7d79f7d9aabd6011004e33b22bc13056a3e3fb54794d138af57f5ee9d9032cb", size = 359864 },
+    { url = "https://files.pythonhosted.org/packages/1e/2e/d0f5f1bef7ee93ed17e739ec8dbcb47794af891f7d165fa6014517b48169/yarl-1.18.3-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:4891ed92157e5430874dad17b15eb1fda57627710756c27422200c52d8a4e393", size = 364537 },
+    { url = "https://files.pythonhosted.org/packages/97/8a/568d07c5d4964da5b02621a517532adb8ec5ba181ad1687191fffeda0ab6/yarl-1.18.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:ce1af883b94304f493698b00d0f006d56aea98aeb49d75ec7d98cd4a777e9285", size = 357861 },
+    { url = "https://files.pythonhosted.org/packages/7d/e3/924c3f64b6b3077889df9a1ece1ed8947e7b61b0a933f2ec93041990a677/yarl-1.18.3-cp312-cp312-win32.whl", hash = "sha256:f91c4803173928a25e1a55b943c81f55b8872f0018be83e3ad4938adffb77dd2", size = 84097 },
+    { url = "https://files.pythonhosted.org/packages/34/45/0e055320daaabfc169b21ff6174567b2c910c45617b0d79c68d7ab349b02/yarl-1.18.3-cp312-cp312-win_amd64.whl", hash = "sha256:7e2ee16578af3b52ac2f334c3b1f92262f47e02cc6193c598502bd46f5cd1477", size = 90399 },
+    { url = "https://files.pythonhosted.org/packages/30/c7/c790513d5328a8390be8f47be5d52e141f78b66c6c48f48d241ca6bd5265/yarl-1.18.3-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:90adb47ad432332d4f0bc28f83a5963f426ce9a1a8809f5e584e704b82685dcb", size = 140789 },
+    { url = "https://files.pythonhosted.org/packages/30/aa/a2f84e93554a578463e2edaaf2300faa61c8701f0898725842c704ba5444/yarl-1.18.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:913829534200eb0f789d45349e55203a091f45c37a2674678744ae52fae23efa", size = 94144 },
+    { url = "https://files.pythonhosted.org/packages/c6/fc/d68d8f83714b221a85ce7866832cba36d7c04a68fa6a960b908c2c84f325/yarl-1.18.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:ef9f7768395923c3039055c14334ba4d926f3baf7b776c923c93d80195624782", size = 91974 },
+    { url = "https://files.pythonhosted.org/packages/56/4e/d2563d8323a7e9a414b5b25341b3942af5902a2263d36d20fb17c40411e2/yarl-1.18.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:88a19f62ff30117e706ebc9090b8ecc79aeb77d0b1f5ec10d2d27a12bc9f66d0", size = 333587 },
+    { url = "https://files.pythonhosted.org/packages/25/c9/cfec0bc0cac8d054be223e9f2c7909d3e8442a856af9dbce7e3442a8ec8d/yarl-1.18.3-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e17c9361d46a4d5addf777c6dd5eab0715a7684c2f11b88c67ac37edfba6c482", size = 344386 },
+    { url = "https://files.pythonhosted.org/packages/ab/5d/4c532190113b25f1364d25f4c319322e86232d69175b91f27e3ebc2caf9a/yarl-1.18.3-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1a74a13a4c857a84a845505fd2d68e54826a2cd01935a96efb1e9d86c728e186", size = 345421 },
+    { url = "https://files.pythonhosted.org/packages/23/d1/6cdd1632da013aa6ba18cee4d750d953104a5e7aac44e249d9410a972bf5/yarl-1.18.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:41f7ce59d6ee7741af71d82020346af364949314ed3d87553763a2df1829cc58", size = 339384 },
+    { url = "https://files.pythonhosted.org/packages/9a/c4/6b3c39bec352e441bd30f432cda6ba51681ab19bb8abe023f0d19777aad1/yarl-1.18.3-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f52a265001d830bc425f82ca9eabda94a64a4d753b07d623a9f2863fde532b53", size = 326689 },
+    { url = "https://files.pythonhosted.org/packages/23/30/07fb088f2eefdc0aa4fc1af4e3ca4eb1a3aadd1ce7d866d74c0f124e6a85/yarl-1.18.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:82123d0c954dc58db301f5021a01854a85bf1f3bb7d12ae0c01afc414a882ca2", size = 345453 },
+    { url = "https://files.pythonhosted.org/packages/63/09/d54befb48f9cd8eec43797f624ec37783a0266855f4930a91e3d5c7717f8/yarl-1.18.3-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:2ec9bbba33b2d00999af4631a3397d1fd78290c48e2a3e52d8dd72db3a067ac8", size = 341872 },
+    { url = "https://files.pythonhosted.org/packages/91/26/fd0ef9bf29dd906a84b59f0cd1281e65b0c3e08c6aa94b57f7d11f593518/yarl-1.18.3-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:fbd6748e8ab9b41171bb95c6142faf068f5ef1511935a0aa07025438dd9a9bc1", size = 347497 },
+    { url = "https://files.pythonhosted.org/packages/d9/b5/14ac7a256d0511b2ac168d50d4b7d744aea1c1aa20c79f620d1059aab8b2/yarl-1.18.3-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:877d209b6aebeb5b16c42cbb377f5f94d9e556626b1bfff66d7b0d115be88d0a", size = 359981 },
+    { url = "https://files.pythonhosted.org/packages/ca/b3/d493221ad5cbd18bc07e642894030437e405e1413c4236dd5db6e46bcec9/yarl-1.18.3-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:b464c4ab4bfcb41e3bfd3f1c26600d038376c2de3297760dfe064d2cb7ea8e10", size = 366229 },
+    { url = "https://files.pythonhosted.org/packages/04/56/6a3e2a5d9152c56c346df9b8fb8edd2c8888b1e03f96324d457e5cf06d34/yarl-1.18.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:8d39d351e7faf01483cc7ff7c0213c412e38e5a340238826be7e0e4da450fdc8", size = 360383 },
+    { url = "https://files.pythonhosted.org/packages/fd/b7/4b3c7c7913a278d445cc6284e59b2e62fa25e72758f888b7a7a39eb8423f/yarl-1.18.3-cp313-cp313-win32.whl", hash = "sha256:61ee62ead9b68b9123ec24bc866cbef297dd266175d53296e2db5e7f797f902d", size = 310152 },
+    { url = "https://files.pythonhosted.org/packages/f5/d5/688db678e987c3e0fb17867970700b92603cadf36c56e5fb08f23e822a0c/yarl-1.18.3-cp313-cp313-win_amd64.whl", hash = "sha256:578e281c393af575879990861823ef19d66e2b1d0098414855dd367e234f5b3c", size = 315723 },
+    { url = "https://files.pythonhosted.org/packages/6a/3b/fec4b08f5e88f68e56ee698a59284a73704df2e0e0b5bdf6536c86e76c76/yarl-1.18.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:61e5e68cb65ac8f547f6b5ef933f510134a6bf31bb178be428994b0cb46c2a04", size = 142780 },
+    { url = "https://files.pythonhosted.org/packages/ed/85/796b0d6a22d536ec8e14bdbb86519250bad980cec450b6e299b1c2a9079e/yarl-1.18.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:fe57328fbc1bfd0bd0514470ac692630f3901c0ee39052ae47acd1d90a436719", size = 94981 },
+    { url = "https://files.pythonhosted.org/packages/ee/0e/a830fd2238f7a29050f6dd0de748b3d6f33a7dbb67dbbc081a970b2bbbeb/yarl-1.18.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a440a2a624683108a1b454705ecd7afc1c3438a08e890a1513d468671d90a04e", size = 92789 },
+    { url = "https://files.pythonhosted.org/packages/0f/4f/438c9fd668954779e48f08c0688ee25e0673380a21bb1e8ccc56de5b55d7/yarl-1.18.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:09c7907c8548bcd6ab860e5f513e727c53b4a714f459b084f6580b49fa1b9cee", size = 317327 },
+    { url = "https://files.pythonhosted.org/packages/bd/79/a78066f06179b4ed4581186c136c12fcfb928c475cbeb23743e71a991935/yarl-1.18.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b4f6450109834af88cb4cc5ecddfc5380ebb9c228695afc11915a0bf82116789", size = 336999 },
+    { url = "https://files.pythonhosted.org/packages/55/02/527963cf65f34a06aed1e766ff9a3b3e7d0eaa1c90736b2948a62e528e1d/yarl-1.18.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a9ca04806f3be0ac6d558fffc2fdf8fcef767e0489d2684a21912cc4ed0cd1b8", size = 331693 },
+    { url = "https://files.pythonhosted.org/packages/a2/2a/167447ae39252ba624b98b8c13c0ba35994d40d9110e8a724c83dbbb5822/yarl-1.18.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:77a6e85b90a7641d2e07184df5557132a337f136250caafc9ccaa4a2a998ca2c", size = 321473 },
+    { url = "https://files.pythonhosted.org/packages/55/03/07955fabb20082373be311c91fd78abe458bc7ff9069d34385e8bddad20e/yarl-1.18.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6333c5a377c8e2f5fae35e7b8f145c617b02c939d04110c76f29ee3676b5f9a5", size = 313571 },
+    { url = "https://files.pythonhosted.org/packages/95/e2/67c8d3ec58a8cd8ddb1d63bd06eb7e7b91c9f148707a3eeb5a7ed87df0ef/yarl-1.18.3-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:0b3c92fa08759dbf12b3a59579a4096ba9af8dd344d9a813fc7f5070d86bbab1", size = 325004 },
+    { url = "https://files.pythonhosted.org/packages/06/43/51ceb3e427368fe6ccd9eccd162be227fd082523e02bad1fd3063daf68da/yarl-1.18.3-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:4ac515b860c36becb81bb84b667466885096b5fc85596948548b667da3bf9f24", size = 322677 },
+    { url = "https://files.pythonhosted.org/packages/e4/0e/7ef286bfb23267739a703f7b967a858e2128c10bea898de8fa027e962521/yarl-1.18.3-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:045b8482ce9483ada4f3f23b3774f4e1bf4f23a2d5c912ed5170f68efb053318", size = 332806 },
+    { url = "https://files.pythonhosted.org/packages/c8/94/2d1f060f4bfa47c8bd0bcb652bfe71fba881564bcac06ebb6d8ced9ac3bc/yarl-1.18.3-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:a4bb030cf46a434ec0225bddbebd4b89e6471814ca851abb8696170adb163985", size = 339919 },
+    { url = "https://files.pythonhosted.org/packages/8e/8d/73b5f9a6ab69acddf1ca1d5e7bc92f50b69124512e6c26b36844531d7f23/yarl-1.18.3-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:54d6921f07555713b9300bee9c50fb46e57e2e639027089b1d795ecd9f7fa910", size = 340960 },
+    { url = "https://files.pythonhosted.org/packages/41/13/ce6bc32be4476b60f4f8694831f49590884b2c975afcffc8d533bf2be7ec/yarl-1.18.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1d407181cfa6e70077df3377938c08012d18893f9f20e92f7d2f314a437c30b1", size = 336592 },
+    { url = "https://files.pythonhosted.org/packages/81/d5/6e0460292d6299ac3919945f912b16b104f4e81ab20bf53e0872a1296daf/yarl-1.18.3-cp39-cp39-win32.whl", hash = "sha256:ac36703a585e0929b032fbaab0707b75dc12703766d0b53486eabd5139ebadd5", size = 84833 },
+    { url = "https://files.pythonhosted.org/packages/b2/fc/a8aef69156ad5508165d8ae956736d55c3a68890610834bd985540966008/yarl-1.18.3-cp39-cp39-win_amd64.whl", hash = "sha256:ba87babd629f8af77f557b61e49e7c7cac36f22f871156b91e10a6e9d4f829e9", size = 90968 },
+    { url = "https://files.pythonhosted.org/packages/f5/4b/a06e0ec3d155924f77835ed2d167ebd3b211a7b0853da1cf8d8414d784ef/yarl-1.18.3-py3-none-any.whl", hash = "sha256:b57f4f58099328dfb26c6a771d09fb20dbbae81d20cfb66141251ea063bd101b", size = 45109 },
+]
+
 [[package]]
 name = "zstandard"
 version = "0.23.0"

libs/community/langchain_community/callbacks/bedrock_anthropic_callback.py

@@ -11,7 +11,6 @@ MODEL_COST_PER_1K_INPUT_TOKENS = {
     "anthropic.claude-3-sonnet-20240229-v1:0": 0.003,
     "anthropic.claude-3-5-sonnet-20240620-v1:0": 0.003,
     "anthropic.claude-3-5-sonnet-20241022-v2:0": 0.003,
-    "anthropic.claude-3-7-sonnet-20250219-v1:0": 0.003,
     "anthropic.claude-3-haiku-20240307-v1:0": 0.00025,
     "anthropic.claude-3-opus-20240229-v1:0": 0.015,
     "anthropic.claude-3-5-haiku-20241022-v1:0": 0.0008,
@@ -24,7 +23,6 @@ MODEL_COST_PER_1K_OUTPUT_TOKENS = {
     "anthropic.claude-3-sonnet-20240229-v1:0": 0.015,
     "anthropic.claude-3-5-sonnet-20240620-v1:0": 0.015,
     "anthropic.claude-3-5-sonnet-20241022-v2:0": 0.015,
-    "anthropic.claude-3-7-sonnet-20250219-v1:0": 0.015,
     "anthropic.claude-3-haiku-20240307-v1:0": 0.00125,
     "anthropic.claude-3-opus-20240229-v1:0": 0.075,
     "anthropic.claude-3-5-haiku-20241022-v1:0": 0.004,

libs/community/langchain_community/chat_models/tongyi.py

@@ -123,8 +123,6 @@ def convert_dict_to_message(
                             tool_calls.append(parsed_tool)
                     except Exception as e:
                         invalid_tool_calls.append(make_invalid_tool_call(value, str(e)))
-        elif "partial" in _dict and isinstance(_dict["partial"], bool):
-            additional_kwargs = {"partial": _dict["partial"]}
         else:
             additional_kwargs = {}
 
@@ -206,9 +204,6 @@ def convert_message_to_dict(message: BaseMessage) -> dict:
         message_dict = {"role": "assistant", "content": message.content}
         if "tool_calls" in message.additional_kwargs:
             message_dict["tool_calls"] = message.additional_kwargs["tool_calls"]
-        # support Partial Mode for text continuation
-        if "partial" in message.additional_kwargs:
-            message_dict["partial"] = message.additional_kwargs["partial"]
     elif isinstance(message, SystemMessage):
         message_dict = {"role": "system", "content": message.content}
     elif isinstance(message, ToolMessage):

libs/community/langchain_community/document_loaders/url_playwright.py

@@ -177,8 +177,6 @@ class PlaywrightURLLoader(BaseLoader):
                     if response is None:
                         raise ValueError(f"page.goto() returned None for url {url}")
 
-                    page.wait_for_load_state("load")
-
                     text = self.evaluator.evaluate(page, browser, response)
                     metadata = {"source": url}
                     yield Document(page_content=text, metadata=metadata)
@@ -218,8 +216,6 @@ class PlaywrightURLLoader(BaseLoader):
                     if response is None:
                         raise ValueError(f"page.goto() returned None for url {url}")
 
-                    await page.wait_for_load_state("load")
-
                     text = await self.evaluator.evaluate_async(page, browser, response)
                     metadata = {"source": url}
                     yield Document(page_content=text, metadata=metadata)

libs/community/langchain_community/embeddings/ascend.py

@@ -30,7 +30,6 @@ class AscendEmbeddings(Embeddings, BaseModel):
     document_instruction: str = ""
     use_fp16: bool = True
     pooling_method: Optional[str] = "cls"
-    batch_size: int = 32
     model: Any
     tokenizer: Any
 
@@ -120,18 +119,7 @@ class AscendEmbeddings(Embeddings, BaseModel):
             )
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
-        try:
-            import numpy as np
-        except ImportError as e:
-            raise ImportError(
-                "Unable to import numpy, please install with `pip install -U numpy`."
-            ) from e
-        embedding_list = []
-        for i in range(0, len(texts), self.batch_size):
-            texts_ = texts[i : i + self.batch_size]
-            emb = self.encode([self.document_instruction + text for text in texts_])
-            embedding_list.append(emb)
-        return np.concatenate(embedding_list)
+        return self.encode([self.document_instruction + text for text in texts])
 
     def embed_query(self, text: str) -> List[float]:
         return self.encode([self.query_instruction + text])[0]

libs/community/langchain_community/graph_vectorstores/__init__.py

@@ -34,7 +34,6 @@ Example::
     - :class:`How to link Documents on hyperlinks in HTML <langchain_community.graph_vectorstores.extractors.html_link_extractor.HtmlLinkExtractor>`
     - :class:`How to link Documents on common keywords (using KeyBERT) <langchain_community.graph_vectorstores.extractors.keybert_link_extractor.KeybertLinkExtractor>`
     - :class:`How to link Documents on common named entities (using GliNER) <langchain_community.graph_vectorstores.extractors.gliner_link_extractor.GLiNERLinkExtractor>`
-    - `langchain-jieba: link extraction tailored for Chinese language <https://github.com/cqzyys/langchain-jieba>`_
 
 Get started
 -----------

libs/community/langchain_community/graph_vectorstores/visualize.py

@@ -20,7 +20,7 @@ _EDGE_DIRECTION = {
     "bidir": "both",
 }
 
-_WORD_RE = re.compile(r"\s*\S+")
+_WORD_RE = re.compile("\s*\S+")
 
 
 def _split_prefix(s: str, max_chars: int = 50) -> str:

libs/community/langchain_community/llms/openai.py

@@ -724,7 +724,7 @@ class BaseOpenAI(BaseLLM):
         Example:
             .. code-block:: python
 
-                max_tokens = openai.max_tokens_for_prompt("Tell me a joke.")
+                max_tokens = openai.max_token_for_prompt("Tell me a joke.")
         """
         num_tokens = self.get_num_tokens(prompt)
         return self.max_context_size - num_tokens

libs/community/langchain_community/llms/outlines.py

@@ -59,7 +59,7 @@ class Outlines(LLM):
     """Whether to stream the results, token by token."""
 
     regex: Optional[str] = None
-    r"""Regular expression for structured generation.
+    """Regular expression for structured generation.
     
     If provided, Outlines will guarantee that the generated text matches this regex.
     This can be useful for generating structured outputs like IP addresses, dates, etc.

libs/community/langchain_community/llms/tongyi.py

@@ -59,7 +59,6 @@ def check_response(resp: Any) -> Any:
         return resp
     elif resp["status_code"] in [400, 401]:
         raise ValueError(
-            f"request_id: {resp['request_id']} \n "
             f"status_code: {resp['status_code']} \n "
             f"code: {resp['code']} \n message: {resp['message']}"
         )

libs/community/langchain_community/llms/xinference.py

@@ -1,10 +1,8 @@
 from __future__ import annotations
 
-import json
 from typing import (
     TYPE_CHECKING,
     Any,
-    AsyncIterator,
     Dict,
     Generator,
     Iterator,
@@ -14,12 +12,7 @@ from typing import (
     Union,
 )
 
-import aiohttp
-import requests
-from langchain_core.callbacks import (
-    AsyncCallbackManagerForLLMRun,
-    CallbackManagerForLLMRun,
-)
+from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
 
@@ -133,7 +126,6 @@ class Xinference(LLM):
         self,
         server_url: Optional[str] = None,
         model_uid: Optional[str] = None,
-        api_key: Optional[str] = None,
         **model_kwargs: Any,
     ):
         try:
@@ -163,13 +155,7 @@ class Xinference(LLM):
         if self.model_uid is None:
             raise ValueError("Please provide the model UID")
 
-        self._headers: Dict[str, str] = {}
-        self._cluster_authed = False
-        self._check_cluster_authenticated()
-        if api_key is not None and self._cluster_authed:
-            self._headers["Authorization"] = f"Bearer {api_key}"
-
-        self.client = RESTfulClient(server_url, api_key)
+        self.client = RESTfulClient(server_url)
 
     @property
     def _llm_type(self) -> str:
@@ -185,20 +171,6 @@ class Xinference(LLM):
             **{"model_kwargs": self.model_kwargs},
         }
 
-    def _check_cluster_authenticated(self) -> None:
-        url = f"{self.server_url}/v1/cluster/auth"
-        response = requests.get(url)
-        if response.status_code == 404:
-            self._cluster_authed = False
-        else:
-            if response.status_code != 200:
-                raise RuntimeError(
-                    f"Failed to get cluster information, "
-                    f"detail: {response.json()['detail']}"
-                )
-            response_data = response.json()
-            self._cluster_authed = bool(response_data["auth"])
-
     def _call(
         self,
         prompt: str,
@@ -333,61 +305,3 @@ class Xinference(LLM):
                 return GenerationChunk(text=token)
         else:
             raise TypeError("stream_response type error!")
-
-    async def _astream(
-        self,
-        prompt: str,
-        stop: Optional[List[str]] = None,
-        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
-        **kwargs: Any,
-    ) -> AsyncIterator[GenerationChunk]:
-        generate_config = kwargs.get("generate_config", {})
-        generate_config = {**self.model_kwargs, **generate_config}
-        if stop:
-            generate_config["stop"] = stop
-        async for stream_resp in self._acreate_generate_stream(prompt, generate_config):
-            if stream_resp:
-                chunk = self._stream_response_to_generation_chunk(stream_resp)
-                if run_manager:
-                    await run_manager.on_llm_new_token(
-                        chunk.text,
-                        verbose=self.verbose,
-                    )
-                yield chunk
-
-    async def _acreate_generate_stream(
-        self, prompt: str, generate_config: Optional[Dict[str, List[str]]] = None
-    ) -> AsyncIterator[str]:
-        request_body: Dict[str, Any] = {"model": self.model_uid, "prompt": prompt}
-        if generate_config is not None:
-            for key, value in generate_config.items():
-                request_body[key] = value
-
-        stream = bool(generate_config and generate_config.get("stream"))
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                url=f"{self.server_url}/v1/completions",
-                json=request_body,
-            ) as response:
-                if response.status != 200:
-                    if response.status == 404:
-                        raise FileNotFoundError(
-                            "astream call failed with status code 404."
-                        )
-                    else:
-                        optional_detail = response.text
-                        raise ValueError(
-                            f"astream call failed with status code {response.status}."
-                            f" Details: {optional_detail}"
-                        )
-
-                async for line in response.content:
-                    if not stream:
-                        yield json.loads(line)
-                    else:
-                        json_str = line.decode("utf-8")
-                        if line.startswith(b"data:"):
-                            json_str = json_str[len(b"data:") :].strip()
-                            if not json_str:
-                                continue
-                            yield json.loads(json_str)

libs/community/langchain_community/retrievers/tavily_search_api.py

@@ -123,7 +123,7 @@ class TavilySearchAPIRetriever(BaseRetriever):
             Document(
                 page_content=result.get("content", "")
                 if not self.include_raw_content
-                else (result.get("raw_content") or ""),
+                else result.get("raw_content", ""),
                 metadata={
                     "title": result.get("title", ""),
                     "source": result.get("url", ""),

libs/community/langchain_community/tools/tavily_search/tool.py

@@ -51,12 +51,9 @@ class TavilySearchResults(BaseTool):  # type: ignore[override, override]
 
             tool.invoke({'query': 'who won the last french open'})
 
-        .. code-block:: json
+        .. code-block:: python
 
-            {
-                "url": "https://www.nytimes.com...",
-                "content": "Novak Djokovic won the last French Open by beating Casper Ruud ..."
-            }
+            '{\n  "url": "https://www.nytimes.com...", "content": "Novak Djokovic won the last French Open by beating Casper Ruud ...'
 
     Invoke with tool call:
 
@@ -67,7 +64,7 @@ class TavilySearchResults(BaseTool):  # type: ignore[override, override]
         .. code-block:: python
 
             ToolMessage(
-                content='{ "url": "https://www.nytimes.com...", "content": "Novak Djokovic won the last French Open by beating Casper Ruud ..." }',
+                content='{\n  "url": "https://www.nytimes.com...", "content": "Novak Djokovic won the last French Open by beating Casper Ruud ...',
                 artifact={
                     'query': 'who won the last french open',
                     'follow_up_questions': None,

libs/community/langchain_community/utilities/jira.py

@@ -40,9 +40,6 @@ class JiraAPIWrapper(BaseModel):
         )
         values["jira_instance_url"] = jira_instance_url
 
-        if "jira_cloud" in values and values["jira_cloud"] is not None:
-            values["jira_cloud"] = str(values["jira_cloud"])
-
         jira_cloud_str = get_from_dict_or_env(values, "jira_cloud", "JIRA_CLOUD")
         jira_cloud = jira_cloud_str.lower() == "true"
         values["jira_cloud"] = jira_cloud

libs/community/langchain_community/utilities/tavily_search.py

@@ -176,13 +176,10 @@ class TavilySearchAPIWrapper(BaseModel):
         """Clean results from Tavily Search API."""
         clean_results = []
         for result in results:
-            clean_result = {
-                "title": result["title"],
-                "url": result["url"],
-                "content": result["content"],
-                "score": result["score"],
-            }
-            if raw_content := result.get("raw_content"):
-                clean_result["raw_content"] = raw_content
-            clean_results.append(clean_result)
+            clean_results.append(
+                {
+                    "url": result["url"],
+                    "content": result["content"],
+                }
+            )
         return clean_results

libs/community/langchain_community/vectorstores/apache_doris.py

@@ -4,30 +4,16 @@ import json
 import logging
 from hashlib import sha1
 from threading import Thread
-from typing import Any, Dict, Iterable, List, Mapping, Optional, Tuple, Union
+from typing import Any, Dict, Iterable, List, Optional, Tuple
 
-import numpy as np
 from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
 from langchain_core.vectorstores import VectorStore
 from pydantic_settings import BaseSettings, SettingsConfigDict
-from typing_extensions import TypedDict
-
-from langchain_community.vectorstores.utils import maximal_marginal_relevance
 
 logger = logging.getLogger()
 DEBUG = False
 
-Metadata = Mapping[str, Union[str, int, float, bool]]
-
-
-class QueryResult(TypedDict):
-    ids: List[List[str]]
-    embeddings: List[Any]
-    documents: List[Document]
-    metadatas: Optional[List[Metadata]]
-    distances: Optional[List[float]]
-
 
 class ApacheDorisSettings(BaseSettings):
     """Apache Doris client configuration.
@@ -324,13 +310,10 @@ CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(
             where_str = ""
 
         q_str = f"""
-            SELECT 
-                id as id,
-                {self.config.column_map["document"]} as document, 
-                {self.config.column_map["metadata"]} as metadata, 
+            SELECT {self.config.column_map["document"]}, 
+                {self.config.column_map["metadata"]}, 
                 cosine_distance(array<float>[{q_emb_str}],
-                {self.config.column_map["embedding"]}) as dist,
-                {self.config.column_map["embedding"]} as embedding
+                  {self.config.column_map["embedding"]}) as dist
             FROM {self.config.database}.{self.config.table}
             {where_str}
             ORDER BY dist {self.dist_order}
@@ -388,13 +371,12 @@ CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(
         """
         q_str = self._build_query_sql(embedding, k, where_str)
         try:
-            q_r = _get_named_result(self.connection, q_str)
             return [
                 Document(
                     page_content=r[self.config.column_map["document"]],
                     metadata=json.loads(r[self.config.column_map["metadata"]]),
                 )
-                for r in q_r
+                for r in _get_named_result(self.connection, q_str)
             ]
         except Exception as e:
             logger.error(f"\033[91m\033[1m{type(e)}\033[0m \033[95m{str(e)}\033[0m")
@@ -448,63 +430,6 @@ CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(
     def metadata_column(self) -> str:
         return self.config.column_map["metadata"]
 
-    def max_marginal_relevance_search_by_vector(
-        self,
-        embedding: list[float],
-        k: int = 4,
-        fetch_k: int = 20,
-        lambda_mult: float = 0.5,
-        **kwargs: Any,
-    ) -> list[Document]:
-        q_str = self._build_query_sql(embedding, fetch_k, None)
-        q_r = _get_named_result(self.connection, q_str)
-        results = QueryResult(
-            ids=[r["id"] for r in q_r],
-            embeddings=[
-                json.loads(r[self.config.column_map["embedding"]]) for r in q_r
-            ],
-            documents=[r[self.config.column_map["document"]] for r in q_r],
-            metadatas=[json.loads(r[self.config.column_map["metadata"]]) for r in q_r],
-            distances=[r["dist"] for r in q_r],
-        )
-
-        mmr_selected = maximal_marginal_relevance(
-            np.array(embedding, dtype=np.float32),
-            results["embeddings"],
-            k=k,
-            lambda_mult=lambda_mult,
-        )
-
-        candidates = _results_to_docs(results)
-
-        selected_results = [r for i, r in enumerate(candidates) if i in mmr_selected]
-        return selected_results
-
-    def max_marginal_relevance_search(
-        self,
-        query: str,
-        k: int = 5,
-        fetch_k: int = 20,
-        lambda_mult: float = 0.5,
-        filter: Optional[Dict[str, str]] = None,
-        where_document: Optional[Dict[str, str]] = None,
-        **kwargs: Any,
-    ) -> List[Document]:
-        if self.embeddings is None:
-            raise ValueError(
-                "For MMR search, you must specify an embedding function oncreation."
-            )
-
-        embedding = self.embeddings.embed_query(query)
-        return self.max_marginal_relevance_search_by_vector(
-            embedding,
-            k,
-            fetch_k,
-            lambda_mult=lambda_mult,
-            filter=filter,
-            where_document=where_document,
-        )
-
 
 def _has_mul_sub_str(s: str, *args: Any) -> bool:
     """Check if a string has multiple substrings.
@@ -555,18 +480,3 @@ def _get_named_result(connection: Any, query: str) -> List[dict[str, Any]]:
     _debug_output(result)
     cursor.close()
     return result
-
-
-def _results_to_docs(results: Any) -> List[Document]:
-    return [doc for doc, _ in _results_to_docs_and_scores(results)]
-
-
-def _results_to_docs_and_scores(results: Any) -> List[Tuple[Document, float]]:
-    return [
-        (Document(page_content=result[0], metadata=result[1] or {}), result[2])
-        for result in zip(
-            results["documents"],
-            results["metadatas"],
-            results["distances"],
-        )
-    ]

libs/community/langchain_community/vectorstores/lancedb.py

@@ -75,7 +75,6 @@ class LanceDB(VectorStore):
     ):
         """Initialize with Lance DB vectorstore"""
         lancedb = guard_import("lancedb")
-        lancedb.remote.table = guard_import("lancedb.remote.table")
         self._embedding = embedding
         self._vector_key = vector_key
         self._id_key = id_key

libs/community/langchain_community/vectorstores/sqlitevec.py

@@ -95,7 +95,7 @@ class SQLiteVec(VectorStore):
         )
         self._connection.execute(
             f"""
-                CREATE TRIGGER IF NOT EXISTS {self._table}_embed_text 
+                CREATE TRIGGER IF NOT EXISTS embed_text 
                 AFTER INSERT ON {self._table}
                 BEGIN
                     INSERT INTO {self._table}_vec(rowid, text_embedding)

libs/community/langchain_community/vectorstores/starrocks.py

@@ -4,16 +4,12 @@ import json
 import logging
 from hashlib import sha1
 from threading import Thread
-from typing import Any, Dict, Iterable, List, Mapping, Optional, Tuple, Union
+from typing import Any, Dict, Iterable, List, Optional, Tuple
 
-import numpy as np
 from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
 from langchain_core.vectorstores import VectorStore
 from pydantic_settings import BaseSettings, SettingsConfigDict
-from typing_extensions import TypedDict
-
-from langchain_community.vectorstores.utils import maximal_marginal_relevance
 
 logger = logging.getLogger()
 DEBUG = False
@@ -70,17 +66,6 @@ def get_named_result(connection: Any, query: str) -> List[dict[str, Any]]:
     return result
 
 
-Metadata = Mapping[str, Union[str, int, float, bool]]
-
-
-class QueryResult(TypedDict):
-    ids: List[List[str]]
-    embeddings: List[Any]
-    documents: List[Document]
-    metadatas: Optional[List[Metadata]]
-    distances: Optional[List[float]]
-
-
 class StarRocksSettings(BaseSettings):
     """StarRocks client configuration.
 
@@ -378,13 +363,10 @@ CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(
             where_str = ""
 
         q_str = f"""
-            SELECT 
-                id as id,
-                {self.config.column_map["document"]} as document, 
-                {self.config.column_map["metadata"]} as metadata, 
+            SELECT {self.config.column_map["document"]}, 
+                {self.config.column_map["metadata"]}, 
                 cosine_similarity_norm(array<float>[{q_emb_str}],
-                {self.config.column_map["embedding"]}) as dist,
-                {self.config.column_map["embedding"]} as embedding
+                  {self.config.column_map["embedding"]}) as dist
             FROM {self.config.database}.{self.config.table}
             {where_str}
             ORDER BY dist {self.dist_order}
@@ -442,13 +424,12 @@ CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(
         """
         q_str = self._build_query_sql(embedding, k, where_str)
         try:
-            q_r = get_named_result(self.connection, q_str)
             return [
                 Document(
                     page_content=r[self.config.column_map["document"]],
                     metadata=json.loads(r[self.config.column_map["metadata"]]),
                 )
-                for r in q_r
+                for r in get_named_result(self.connection, q_str)
             ]
         except Exception as e:
             logger.error(f"\033[91m\033[1m{type(e)}\033[0m \033[95m{str(e)}\033[0m")
@@ -503,75 +484,3 @@ CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(
     @property
     def metadata_column(self) -> str:
         return self.config.column_map["metadata"]
-
-    def max_marginal_relevance_search_by_vector(
-        self,
-        embedding: list[float],
-        k: int = 4,
-        fetch_k: int = 20,
-        lambda_mult: float = 0.5,
-        **kwargs: Any,
-    ) -> list[Document]:
-        q_str = self._build_query_sql(embedding, fetch_k, None)
-        q_r = get_named_result(self.connection, q_str)
-        results = QueryResult(
-            ids=[r["id"] for r in q_r],
-            embeddings=[
-                json.loads(r[self.config.column_map["embedding"]]) for r in q_r
-            ],
-            documents=[r[self.config.column_map["document"]] for r in q_r],
-            metadatas=[json.loads(r[self.config.column_map["metadata"]]) for r in q_r],
-            distances=[r["dist"] for r in q_r],
-        )
-
-        mmr_selected = maximal_marginal_relevance(
-            np.array(embedding, dtype=np.float32),
-            results["embeddings"],
-            k=k,
-            lambda_mult=lambda_mult,
-        )
-
-        candidates = _results_to_docs(results)
-
-        selected_results = [r for i, r in enumerate(candidates) if i in mmr_selected]
-        return selected_results
-
-    def max_marginal_relevance_search(
-        self,
-        query: str,
-        k: int = 5,
-        fetch_k: int = 20,
-        lambda_mult: float = 0.5,
-        filter: Optional[Dict[str, str]] = None,
-        where_document: Optional[Dict[str, str]] = None,
-        **kwargs: Any,
-    ) -> List[Document]:
-        if self.embeddings is None:
-            raise ValueError(
-                "For MMR search, you must specify an embedding function oncreation."
-            )
-
-        embedding = self.embeddings.embed_query(query)
-        return self.max_marginal_relevance_search_by_vector(
-            embedding,
-            k,
-            fetch_k,
-            lambda_mult=lambda_mult,
-            filter=filter,
-            where_document=where_document,
-        )
-
-
-def _results_to_docs(results: Any) -> List[Document]:
-    return [doc for doc, _ in _results_to_docs_and_scores(results)]
-
-
-def _results_to_docs_and_scores(results: Any) -> List[Tuple[Document, float]]:
-    return [
-        (Document(page_content=result[0], metadata=result[1] or {}), result[2])
-        for result in zip(
-            results["documents"],
-            results["metadatas"],
-            results["distances"],
-        )
-    ]

libs/community/pyproject.toml

@@ -7,8 +7,8 @@ authors = []
 license = { text = "MIT" }
 requires-python = "<4.0,>=3.9"
 dependencies = [
-    "langchain-core<1.0.0,>=0.3.41",
-    "langchain<1.0.0,>=0.3.20",
+    "langchain-core<1.0.0,>=0.3.37",
+    "langchain<1.0.0,>=0.3.19",
     "SQLAlchemy<3,>=1.4",
     "requests<3,>=2",
     "PyYAML>=5.3",
@@ -18,10 +18,11 @@ dependencies = [
     "pydantic-settings<3.0.0,>=2.4.0",
     "langsmith<0.4,>=0.1.125",
     "httpx-sse<1.0.0,>=0.4.0",
-    "numpy<3,>=1.26.2",
+    "numpy<2,>=1.26.4; python_version < \"3.12\"",
+    "numpy<3,>=1.26.2; python_version >= \"3.12\"",
 ]
 name = "langchain-community"
-version = "0.3.19"
+version = "0.3.18"
 description = "Community contributed LangChain integrations."
 readme = "README.md"
 

libs/community/tests/integration_tests/vectorstores/test_sqlitevec.py

@@ -56,27 +56,3 @@ def test_sqlitevec_add_extra() -> None:
     docsearch.add_texts(texts, metadatas)
     output = docsearch.similarity_search("foo", k=10)
     assert len(output) == 6
-
-
-@pytest.mark.requires("sqlite-vec")
-def test_sqlitevec_search_multiple_tables() -> None:
-    """Test end to end construction and search with multiple tables."""
-    docsearch_1 = SQLiteVec.from_texts(
-        fake_texts,
-        FakeEmbeddings(),
-        table="table_1",
-        db_file=":memory:",  ## change to local storage for testing
-    )
-
-    docsearch_2 = SQLiteVec.from_texts(
-        fake_texts,
-        FakeEmbeddings(),
-        table="table_2",
-        db_file=":memory:",
-    )
-
-    output_1 = docsearch_1.similarity_search("foo", k=1)
-    output_2 = docsearch_2.similarity_search("foo", k=1)
-
-    assert output_1 == [Document(page_content="foo", metadata={})]
-    assert output_2 == [Document(page_content="foo", metadata={})]

libs/community/tests/unit_tests/chat_models/test_tongyi.py

@@ -65,13 +65,6 @@ def test__convert_dict_to_message_function_call() -> None:
     assert result == expected_output
 
 
-def test__convert_dict_to_message_partial_mode() -> None:
-    message_dict = {"role": "assistant", "content": "foo", "partial": True}
-    result = convert_dict_to_message(message_dict)
-    expected_output = AIMessage(content="foo", additional_kwargs={"partial": True})
-    assert result == expected_output
-
-
 def test__convert_message_to_dict_human() -> None:
     message = HumanMessage(content="foo")
     result = convert_message_to_dict(message)
@@ -86,13 +79,6 @@ def test__convert_message_to_dict_ai() -> None:
     assert result == expected_output
 
 
-def test__convert_message_to_dict_ai_partial_mode() -> None:
-    message = AIMessage(content="foo", additional_kwargs={"partial": True})
-    result = convert_message_to_dict(message)
-    expected_output = {"role": "assistant", "content": "foo", "partial": True}
-    assert result == expected_output
-
-
 def test__convert_message_to_dict_system() -> None:
     message = SystemMessage(content="foo")
     result = convert_message_to_dict(message)

libs/community/tests/unit_tests/jira/test_jira_api_wrapper.py

@@ -1,62 +0,0 @@
-from unittest.mock import MagicMock, patch
-
-import pytest
-
-from langchain_community.utilities.jira import JiraAPIWrapper
-
-
-@pytest.fixture
-def mock_jira():  # type: ignore
-    with patch("atlassian.Jira") as mock_jira:
-        yield mock_jira
-
-
-@pytest.mark.requires("atlassian")
-class TestJiraAPIWrapper:
-    def test_jira_api_wrapper(self, mock_jira: MagicMock) -> None:
-        """Test for Jira API Wrapper using mocks"""
-        # Configure the mock instance
-        mock_jira_instance = mock_jira.return_value
-
-        # Mock projects method to return mock projects
-        mock_project1 = MagicMock(key="PROJ1")
-        mock_project2 = MagicMock(key="PROJ2")
-
-        # Set up the mock to return our mock projects
-        mock_jira_instance.projects.return_value = [mock_project1, mock_project2]
-
-        # Initialize wrapper with mocks in place
-        jira_wrapper = JiraAPIWrapper(
-            jira_username="test_user",
-            jira_api_token="test_token",
-            jira_instance_url="https://test.atlassian.net",
-            jira_cloud=True,
-        )
-
-        mock_jira.assert_called_once_with(
-            url="https://test.atlassian.net",
-            username="test_user",
-            password="test_token",
-            cloud=True,
-        )
-
-        # Test get_projects function
-        result = jira_wrapper.run("get_projects", "")
-
-        # Verify the mock was called and the result contains expected info
-        mock_jira_instance.projects.assert_called_once()
-        assert result.startswith("Found 2 projects")
-
-    def test_jira_api_wrapper_with_cloud_false(self, mock_jira: MagicMock) -> None:
-        JiraAPIWrapper(
-            jira_username="test_user",
-            jira_api_token="test_token",
-            jira_instance_url="https://test.atlassian.net",
-            jira_cloud=False,
-        )
-        mock_jira.assert_called_once_with(
-            url="https://test.atlassian.net",
-            username="test_user",
-            password="test_token",
-            cloud=False,
-        )

libs/community/uv.lock

@@ -1491,21 +1491,26 @@ wheels = [
 
 [[package]]
 name = "langchain"
-version = "0.3.20"
+version = "0.3.19"
 source = { editable = "../langchain" }
 dependencies = [
+    { name = "aiohttp" },
     { name = "async-timeout", marker = "python_full_version < '3.11'" },
     { name = "langchain-core" },
     { name = "langchain-text-splitters" },
     { name = "langsmith" },
+    { name = "numpy", version = "1.26.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
+    { name = "numpy", version = "2.2.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "pydantic" },
     { name = "pyyaml" },
     { name = "requests" },
     { name = "sqlalchemy" },
+    { name = "tenacity" },
 ]
 
 [package.metadata]
 requires-dist = [
+    { name = "aiohttp", specifier = ">=3.8.3,<4.0.0" },
     { name = "async-timeout", marker = "python_full_version < '3.11'", specifier = ">=4.0.0,<5.0.0" },
     { name = "langchain-anthropic", marker = "extra == 'anthropic'" },
     { name = "langchain-aws", marker = "extra == 'aws'" },
@@ -1525,10 +1530,13 @@ requires-dist = [
     { name = "langchain-together", marker = "extra == 'together'" },
     { name = "langchain-xai", marker = "extra == 'xai'" },
     { name = "langsmith", specifier = ">=0.1.17,<0.4" },
+    { name = "numpy", marker = "python_full_version < '3.12'", specifier = ">=1.26.4,<2" },
+    { name = "numpy", marker = "python_full_version >= '3.12'", specifier = ">=1.26.2,<3" },
     { name = "pydantic", specifier = ">=2.7.4,<3.0.0" },
     { name = "pyyaml", specifier = ">=5.3" },
     { name = "requests", specifier = ">=2,<3" },
     { name = "sqlalchemy", specifier = ">=1.4,<3" },
+    { name = "tenacity", specifier = ">=8.1.0,!=8.4.0,<10" },
 ]
 
 [package.metadata.requires-dev]
@@ -1556,7 +1564,6 @@ test = [
     { name = "langchain-tests", editable = "../standard-tests" },
     { name = "langchain-text-splitters", editable = "../text-splitters" },
     { name = "lark", specifier = ">=1.1.5,<2.0.0" },
-    { name = "numpy", specifier = ">=1.26.4,<3" },
     { name = "packaging", specifier = ">=24.2" },
     { name = "pandas", specifier = ">=2.0.0,<3.0.0" },
     { name = "pytest", specifier = ">=8,<9" },
@@ -1587,7 +1594,6 @@ typing = [
     { name = "langchain-text-splitters", editable = "../text-splitters" },
     { name = "mypy", specifier = ">=1.10,<2.0" },
     { name = "mypy-protobuf", specifier = ">=3.0.0,<4.0.0" },
-    { name = "numpy", specifier = ">=1.26.4,<3" },
     { name = "types-chardet", specifier = ">=5.0.4.6,<6.0.0.0" },
     { name = "types-pytz", specifier = ">=2023.3.0.0,<2024.0.0.0" },
     { name = "types-pyyaml", specifier = ">=6.0.12.2,<7.0.0.0" },
@@ -1598,7 +1604,7 @@ typing = [
 
 [[package]]
 name = "langchain-community"
-version = "0.3.19"
+version = "0.3.18"
 source = { editable = "." }
 dependencies = [
     { name = "aiohttp" },
@@ -1607,8 +1613,8 @@ dependencies = [
     { name = "langchain" },
     { name = "langchain-core" },
     { name = "langsmith" },
-    { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" },
-    { name = "numpy", version = "2.2.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" },
+    { name = "numpy", version = "1.26.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
+    { name = "numpy", version = "2.2.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "pydantic-settings" },
     { name = "pyyaml" },
     { name = "requests" },
@@ -1680,7 +1686,8 @@ requires-dist = [
     { name = "langchain", editable = "../langchain" },
     { name = "langchain-core", editable = "../core" },
     { name = "langsmith", specifier = ">=0.1.125,<0.4" },
-    { name = "numpy", specifier = ">=1.26.2,<3" },
+    { name = "numpy", marker = "python_full_version < '3.12'", specifier = ">=1.26.4,<2" },
+    { name = "numpy", marker = "python_full_version >= '3.12'", specifier = ">=1.26.2,<3" },
     { name = "pydantic-settings", specifier = ">=2.4.0,<3.0.0" },
     { name = "pyyaml", specifier = ">=5.3" },
     { name = "requests", specifier = ">=2,<3" },
@@ -1744,7 +1751,7 @@ typing = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.41"
+version = "0.3.36"
 source = { editable = "../core" }
 dependencies = [
     { name = "jsonpatch" },
@@ -1802,13 +1809,13 @@ typing = [
 
 [[package]]
 name = "langchain-tests"
-version = "0.3.13"
+version = "0.3.12"
 source = { editable = "../standard-tests" }
 dependencies = [
     { name = "httpx" },
     { name = "langchain-core" },
-    { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" },
-    { name = "numpy", version = "2.2.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" },
+    { name = "numpy", version = "1.26.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
+    { name = "numpy", version = "2.2.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "pytest" },
     { name = "pytest-asyncio" },
     { name = "pytest-socket" },
@@ -1819,7 +1826,8 @@ dependencies = [
 requires-dist = [
     { name = "httpx", specifier = ">=0.25.0,<1" },
     { name = "langchain-core", editable = "../core" },
-    { name = "numpy", specifier = ">=1.26.2,<3" },
+    { name = "numpy", marker = "python_full_version < '3.12'", specifier = ">=1.24.0,<2.0.0" },
+    { name = "numpy", marker = "python_full_version >= '3.12'", specifier = ">=1.26.2,<3" },
     { name = "pytest", specifier = ">=7,<9" },
     { name = "pytest-asyncio", specifier = ">=0.20,<1" },
     { name = "pytest-socket", specifier = ">=0.6.0,<1" },
@@ -2258,130 +2266,121 @@ wheels = [
 
 [[package]]
 name = "numpy"
-version = "2.0.2"
+version = "1.26.4"
 source = { registry = "https://pypi.org/simple" }
 resolution-markers = [
+    "python_full_version == '3.11.*' and platform_python_implementation == 'PyPy'",
+    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy'",
+    "python_full_version == '3.10.*' and platform_python_implementation == 'PyPy'",
+    "python_full_version == '3.10.*' and platform_python_implementation != 'PyPy'",
     "python_full_version < '3.10' and platform_python_implementation == 'PyPy'",
     "python_full_version < '3.10' and platform_python_implementation != 'PyPy'",
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/a9/75/10dd1f8116a8b796cb2c737b674e02d02e80454bda953fa7e65d8c12b016/numpy-2.0.2.tar.gz", hash = "sha256:883c987dee1880e2a864ab0dc9892292582510604156762362d9326444636e78", size = 18902015 }
+sdist = { url = "https://files.pythonhosted.org/packages/65/6e/09db70a523a96d25e115e71cc56a6f9031e7b8cd166c1ac8438307c14058/numpy-1.26.4.tar.gz", hash = "sha256:2a02aba9ed12e4ac4eb3ea9421c420301a0c6460d9830d74a9df87efa4912010", size = 15786129 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/21/91/3495b3237510f79f5d81f2508f9f13fea78ebfdf07538fc7444badda173d/numpy-2.0.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:51129a29dbe56f9ca83438b706e2e69a39892b5eda6cedcb6b0c9fdc9b0d3ece", size = 21165245 },
-    { url = "https://files.pythonhosted.org/packages/05/33/26178c7d437a87082d11019292dce6d3fe6f0e9026b7b2309cbf3e489b1d/numpy-2.0.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f15975dfec0cf2239224d80e32c3170b1d168335eaedee69da84fbe9f1f9cd04", size = 13738540 },
-    { url = "https://files.pythonhosted.org/packages/ec/31/cc46e13bf07644efc7a4bf68df2df5fb2a1a88d0cd0da9ddc84dc0033e51/numpy-2.0.2-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:8c5713284ce4e282544c68d1c3b2c7161d38c256d2eefc93c1d683cf47683e66", size = 5300623 },
-    { url = "https://files.pythonhosted.org/packages/6e/16/7bfcebf27bb4f9d7ec67332ffebee4d1bf085c84246552d52dbb548600e7/numpy-2.0.2-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:becfae3ddd30736fe1889a37f1f580e245ba79a5855bff5f2a29cb3ccc22dd7b", size = 6901774 },
-    { url = "https://files.pythonhosted.org/packages/f9/a3/561c531c0e8bf082c5bef509d00d56f82e0ea7e1e3e3a7fc8fa78742a6e5/numpy-2.0.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2da5960c3cf0df7eafefd806d4e612c5e19358de82cb3c343631188991566ccd", size = 13907081 },
-    { url = "https://files.pythonhosted.org/packages/fa/66/f7177ab331876200ac7563a580140643d1179c8b4b6a6b0fc9838de2a9b8/numpy-2.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:496f71341824ed9f3d2fd36cf3ac57ae2e0165c143b55c3a035ee219413f3318", size = 19523451 },
-    { url = "https://files.pythonhosted.org/packages/25/7f/0b209498009ad6453e4efc2c65bcdf0ae08a182b2b7877d7ab38a92dc542/numpy-2.0.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:a61ec659f68ae254e4d237816e33171497e978140353c0c2038d46e63282d0c8", size = 19927572 },
-    { url = "https://files.pythonhosted.org/packages/3e/df/2619393b1e1b565cd2d4c4403bdd979621e2c4dea1f8532754b2598ed63b/numpy-2.0.2-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d731a1c6116ba289c1e9ee714b08a8ff882944d4ad631fd411106a30f083c326", size = 14400722 },
-    { url = "https://files.pythonhosted.org/packages/22/ad/77e921b9f256d5da36424ffb711ae79ca3f451ff8489eeca544d0701d74a/numpy-2.0.2-cp310-cp310-win32.whl", hash = "sha256:984d96121c9f9616cd33fbd0618b7f08e0cfc9600a7ee1d6fd9b239186d19d97", size = 6472170 },
-    { url = "https://files.pythonhosted.org/packages/10/05/3442317535028bc29cf0c0dd4c191a4481e8376e9f0db6bcf29703cadae6/numpy-2.0.2-cp310-cp310-win_amd64.whl", hash = "sha256:c7b0be4ef08607dd04da4092faee0b86607f111d5ae68036f16cc787e250a131", size = 15905558 },
-    { url = "https://files.pythonhosted.org/packages/8b/cf/034500fb83041aa0286e0fb16e7c76e5c8b67c0711bb6e9e9737a717d5fe/numpy-2.0.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:49ca4decb342d66018b01932139c0961a8f9ddc7589611158cb3c27cbcf76448", size = 21169137 },
-    { url = "https://files.pythonhosted.org/packages/4a/d9/32de45561811a4b87fbdee23b5797394e3d1504b4a7cf40c10199848893e/numpy-2.0.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:11a76c372d1d37437857280aa142086476136a8c0f373b2e648ab2c8f18fb195", size = 13703552 },
-    { url = "https://files.pythonhosted.org/packages/c1/ca/2f384720020c7b244d22508cb7ab23d95f179fcfff33c31a6eeba8d6c512/numpy-2.0.2-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:807ec44583fd708a21d4a11d94aedf2f4f3c3719035c76a2bbe1fe8e217bdc57", size = 5298957 },
-    { url = "https://files.pythonhosted.org/packages/0e/78/a3e4f9fb6aa4e6fdca0c5428e8ba039408514388cf62d89651aade838269/numpy-2.0.2-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:8cafab480740e22f8d833acefed5cc87ce276f4ece12fdaa2e8903db2f82897a", size = 6905573 },
-    { url = "https://files.pythonhosted.org/packages/a0/72/cfc3a1beb2caf4efc9d0b38a15fe34025230da27e1c08cc2eb9bfb1c7231/numpy-2.0.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a15f476a45e6e5a3a79d8a14e62161d27ad897381fecfa4a09ed5322f2085669", size = 13914330 },
-    { url = "https://files.pythonhosted.org/packages/ba/a8/c17acf65a931ce551fee11b72e8de63bf7e8a6f0e21add4c937c83563538/numpy-2.0.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:13e689d772146140a252c3a28501da66dfecd77490b498b168b501835041f951", size = 19534895 },
-    { url = "https://files.pythonhosted.org/packages/ba/86/8767f3d54f6ae0165749f84648da9dcc8cd78ab65d415494962c86fac80f/numpy-2.0.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:9ea91dfb7c3d1c56a0e55657c0afb38cf1eeae4544c208dc465c3c9f3a7c09f9", size = 19937253 },
-    { url = "https://files.pythonhosted.org/packages/df/87/f76450e6e1c14e5bb1eae6836478b1028e096fd02e85c1c37674606ab752/numpy-2.0.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c1c9307701fec8f3f7a1e6711f9089c06e6284b3afbbcd259f7791282d660a15", size = 14414074 },
-    { url = "https://files.pythonhosted.org/packages/5c/ca/0f0f328e1e59f73754f06e1adfb909de43726d4f24c6a3f8805f34f2b0fa/numpy-2.0.2-cp311-cp311-win32.whl", hash = "sha256:a392a68bd329eafac5817e5aefeb39038c48b671afd242710b451e76090e81f4", size = 6470640 },
-    { url = "https://files.pythonhosted.org/packages/eb/57/3a3f14d3a759dcf9bf6e9eda905794726b758819df4663f217d658a58695/numpy-2.0.2-cp311-cp311-win_amd64.whl", hash = "sha256:286cd40ce2b7d652a6f22efdfc6d1edf879440e53e76a75955bc0c826c7e64dc", size = 15910230 },
-    { url = "https://files.pythonhosted.org/packages/45/40/2e117be60ec50d98fa08c2f8c48e09b3edea93cfcabd5a9ff6925d54b1c2/numpy-2.0.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:df55d490dea7934f330006d0f81e8551ba6010a5bf035a249ef61a94f21c500b", size = 20895803 },
-    { url = "https://files.pythonhosted.org/packages/46/92/1b8b8dee833f53cef3e0a3f69b2374467789e0bb7399689582314df02651/numpy-2.0.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8df823f570d9adf0978347d1f926b2a867d5608f434a7cff7f7908c6570dcf5e", size = 13471835 },
-    { url = "https://files.pythonhosted.org/packages/7f/19/e2793bde475f1edaea6945be141aef6c8b4c669b90c90a300a8954d08f0a/numpy-2.0.2-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:9a92ae5c14811e390f3767053ff54eaee3bf84576d99a2456391401323f4ec2c", size = 5038499 },
-    { url = "https://files.pythonhosted.org/packages/e3/ff/ddf6dac2ff0dd50a7327bcdba45cb0264d0e96bb44d33324853f781a8f3c/numpy-2.0.2-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:a842d573724391493a97a62ebbb8e731f8a5dcc5d285dfc99141ca15a3302d0c", size = 6633497 },
-    { url = "https://files.pythonhosted.org/packages/72/21/67f36eac8e2d2cd652a2e69595a54128297cdcb1ff3931cfc87838874bd4/numpy-2.0.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c05e238064fc0610c840d1cf6a13bf63d7e391717d247f1bf0318172e759e692", size = 13621158 },
-    { url = "https://files.pythonhosted.org/packages/39/68/e9f1126d757653496dbc096cb429014347a36b228f5a991dae2c6b6cfd40/numpy-2.0.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0123ffdaa88fa4ab64835dcbde75dcdf89c453c922f18dced6e27c90d1d0ec5a", size = 19236173 },
-    { url = "https://files.pythonhosted.org/packages/d1/e9/1f5333281e4ebf483ba1c888b1d61ba7e78d7e910fdd8e6499667041cc35/numpy-2.0.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:96a55f64139912d61de9137f11bf39a55ec8faec288c75a54f93dfd39f7eb40c", size = 19634174 },
-    { url = "https://files.pythonhosted.org/packages/71/af/a469674070c8d8408384e3012e064299f7a2de540738a8e414dcfd639996/numpy-2.0.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:ec9852fb39354b5a45a80bdab5ac02dd02b15f44b3804e9f00c556bf24b4bded", size = 14099701 },
-    { url = "https://files.pythonhosted.org/packages/d0/3d/08ea9f239d0e0e939b6ca52ad403c84a2bce1bde301a8eb4888c1c1543f1/numpy-2.0.2-cp312-cp312-win32.whl", hash = "sha256:671bec6496f83202ed2d3c8fdc486a8fc86942f2e69ff0e986140339a63bcbe5", size = 6174313 },
-    { url = "https://files.pythonhosted.org/packages/b2/b5/4ac39baebf1fdb2e72585c8352c56d063b6126be9fc95bd2bb5ef5770c20/numpy-2.0.2-cp312-cp312-win_amd64.whl", hash = "sha256:cfd41e13fdc257aa5778496b8caa5e856dc4896d4ccf01841daee1d96465467a", size = 15606179 },
-    { url = "https://files.pythonhosted.org/packages/43/c1/41c8f6df3162b0c6ffd4437d729115704bd43363de0090c7f913cfbc2d89/numpy-2.0.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9059e10581ce4093f735ed23f3b9d283b9d517ff46009ddd485f1747eb22653c", size = 21169942 },
-    { url = "https://files.pythonhosted.org/packages/39/bc/fd298f308dcd232b56a4031fd6ddf11c43f9917fbc937e53762f7b5a3bb1/numpy-2.0.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:423e89b23490805d2a5a96fe40ec507407b8ee786d66f7328be214f9679df6dd", size = 13711512 },
-    { url = "https://files.pythonhosted.org/packages/96/ff/06d1aa3eeb1c614eda245c1ba4fb88c483bee6520d361641331872ac4b82/numpy-2.0.2-cp39-cp39-macosx_14_0_arm64.whl", hash = "sha256:2b2955fa6f11907cf7a70dab0d0755159bca87755e831e47932367fc8f2f2d0b", size = 5306976 },
-    { url = "https://files.pythonhosted.org/packages/2d/98/121996dcfb10a6087a05e54453e28e58694a7db62c5a5a29cee14c6e047b/numpy-2.0.2-cp39-cp39-macosx_14_0_x86_64.whl", hash = "sha256:97032a27bd9d8988b9a97a8c4d2c9f2c15a81f61e2f21404d7e8ef00cb5be729", size = 6906494 },
-    { url = "https://files.pythonhosted.org/packages/15/31/9dffc70da6b9bbf7968f6551967fc21156207366272c2a40b4ed6008dc9b/numpy-2.0.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1e795a8be3ddbac43274f18588329c72939870a16cae810c2b73461c40718ab1", size = 13912596 },
-    { url = "https://files.pythonhosted.org/packages/b9/14/78635daab4b07c0930c919d451b8bf8c164774e6a3413aed04a6d95758ce/numpy-2.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f26b258c385842546006213344c50655ff1555a9338e2e5e02a0756dc3e803dd", size = 19526099 },
-    { url = "https://files.pythonhosted.org/packages/26/4c/0eeca4614003077f68bfe7aac8b7496f04221865b3a5e7cb230c9d055afd/numpy-2.0.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:5fec9451a7789926bcf7c2b8d187292c9f93ea30284802a0ab3f5be8ab36865d", size = 19932823 },
-    { url = "https://files.pythonhosted.org/packages/f1/46/ea25b98b13dccaebddf1a803f8c748680d972e00507cd9bc6dcdb5aa2ac1/numpy-2.0.2-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:9189427407d88ff25ecf8f12469d4d39d35bee1db5d39fc5c168c6f088a6956d", size = 14404424 },
-    { url = "https://files.pythonhosted.org/packages/c8/a6/177dd88d95ecf07e722d21008b1b40e681a929eb9e329684d449c36586b2/numpy-2.0.2-cp39-cp39-win32.whl", hash = "sha256:905d16e0c60200656500c95b6b8dca5d109e23cb24abc701d41c02d74c6b3afa", size = 6476809 },
-    { url = "https://files.pythonhosted.org/packages/ea/2b/7fc9f4e7ae5b507c1a3a21f0f15ed03e794c1242ea8a242ac158beb56034/numpy-2.0.2-cp39-cp39-win_amd64.whl", hash = "sha256:a3f4ab0caa7f053f6797fcd4e1e25caee367db3112ef2b6ef82d749530768c73", size = 15911314 },
-    { url = "https://files.pythonhosted.org/packages/8f/3b/df5a870ac6a3be3a86856ce195ef42eec7ae50d2a202be1f5a4b3b340e14/numpy-2.0.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:7f0a0c6f12e07fa94133c8a67404322845220c06a9e80e85999afe727f7438b8", size = 21025288 },
-    { url = "https://files.pythonhosted.org/packages/2c/97/51af92f18d6f6f2d9ad8b482a99fb74e142d71372da5d834b3a2747a446e/numpy-2.0.2-pp39-pypy39_pp73-macosx_14_0_x86_64.whl", hash = "sha256:312950fdd060354350ed123c0e25a71327d3711584beaef30cdaa93320c392d4", size = 6762793 },
-    { url = "https://files.pythonhosted.org/packages/12/46/de1fbd0c1b5ccaa7f9a005b66761533e2f6a3e560096682683a223631fe9/numpy-2.0.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:26df23238872200f63518dd2aa984cfca675d82469535dc7162dc2ee52d9dd5c", size = 19334885 },
-    { url = "https://files.pythonhosted.org/packages/cc/dc/d330a6faefd92b446ec0f0dfea4c3207bb1fef3c4771d19cf4543efd2c78/numpy-2.0.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:a46288ec55ebbd58947d31d72be2c63cbf839f0a63b49cb755022310792a3385", size = 15828784 },
+    { url = "https://files.pythonhosted.org/packages/a7/94/ace0fdea5241a27d13543ee117cbc65868e82213fb31a8eb7fe9ff23f313/numpy-1.26.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:9ff0f4f29c51e2803569d7a51c2304de5554655a60c5d776e35b4a41413830d0", size = 20631468 },
+    { url = "https://files.pythonhosted.org/packages/20/f7/b24208eba89f9d1b58c1668bc6c8c4fd472b20c45573cb767f59d49fb0f6/numpy-1.26.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2e4ee3380d6de9c9ec04745830fd9e2eccb3e6cf790d39d7b98ffd19b0dd754a", size = 13966411 },
+    { url = "https://files.pythonhosted.org/packages/fc/a5/4beee6488160798683eed5bdb7eead455892c3b4e1f78d79d8d3f3b084ac/numpy-1.26.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d209d8969599b27ad20994c8e41936ee0964e6da07478d6c35016bc386b66ad4", size = 14219016 },
+    { url = "https://files.pythonhosted.org/packages/4b/d7/ecf66c1cd12dc28b4040b15ab4d17b773b87fa9d29ca16125de01adb36cd/numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ffa75af20b44f8dba823498024771d5ac50620e6915abac414251bd971b4529f", size = 18240889 },
+    { url = "https://files.pythonhosted.org/packages/24/03/6f229fe3187546435c4f6f89f6d26c129d4f5bed40552899fcf1f0bf9e50/numpy-1.26.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:62b8e4b1e28009ef2846b4c7852046736bab361f7aeadeb6a5b89ebec3c7055a", size = 13876746 },
+    { url = "https://files.pythonhosted.org/packages/39/fe/39ada9b094f01f5a35486577c848fe274e374bbf8d8f472e1423a0bbd26d/numpy-1.26.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:a4abb4f9001ad2858e7ac189089c42178fcce737e4169dc61321660f1a96c7d2", size = 18078620 },
+    { url = "https://files.pythonhosted.org/packages/d5/ef/6ad11d51197aad206a9ad2286dc1aac6a378059e06e8cf22cd08ed4f20dc/numpy-1.26.4-cp310-cp310-win32.whl", hash = "sha256:bfe25acf8b437eb2a8b2d49d443800a5f18508cd811fea3181723922a8a82b07", size = 5972659 },
+    { url = "https://files.pythonhosted.org/packages/19/77/538f202862b9183f54108557bfda67e17603fc560c384559e769321c9d92/numpy-1.26.4-cp310-cp310-win_amd64.whl", hash = "sha256:b97fe8060236edf3662adfc2c633f56a08ae30560c56310562cb4f95500022d5", size = 15808905 },
+    { url = "https://files.pythonhosted.org/packages/11/57/baae43d14fe163fa0e4c47f307b6b2511ab8d7d30177c491960504252053/numpy-1.26.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4c66707fabe114439db9068ee468c26bbdf909cac0fb58686a42a24de1760c71", size = 20630554 },
+    { url = "https://files.pythonhosted.org/packages/1a/2e/151484f49fd03944c4a3ad9c418ed193cfd02724e138ac8a9505d056c582/numpy-1.26.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:edd8b5fe47dab091176d21bb6de568acdd906d1887a4584a15a9a96a1dca06ef", size = 13997127 },
+    { url = "https://files.pythonhosted.org/packages/79/ae/7e5b85136806f9dadf4878bf73cf223fe5c2636818ba3ab1c585d0403164/numpy-1.26.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7ab55401287bfec946ced39700c053796e7cc0e3acbef09993a9ad2adba6ca6e", size = 14222994 },
+    { url = "https://files.pythonhosted.org/packages/3a/d0/edc009c27b406c4f9cbc79274d6e46d634d139075492ad055e3d68445925/numpy-1.26.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:666dbfb6ec68962c033a450943ded891bed2d54e6755e35e5835d63f4f6931d5", size = 18252005 },
+    { url = "https://files.pythonhosted.org/packages/09/bf/2b1aaf8f525f2923ff6cfcf134ae5e750e279ac65ebf386c75a0cf6da06a/numpy-1.26.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:96ff0b2ad353d8f990b63294c8986f1ec3cb19d749234014f4e7eb0112ceba5a", size = 13885297 },
+    { url = "https://files.pythonhosted.org/packages/df/a0/4e0f14d847cfc2a633a1c8621d00724f3206cfeddeb66d35698c4e2cf3d2/numpy-1.26.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:60dedbb91afcbfdc9bc0b1f3f402804070deed7392c23eb7a7f07fa857868e8a", size = 18093567 },
+    { url = "https://files.pythonhosted.org/packages/d2/b7/a734c733286e10a7f1a8ad1ae8c90f2d33bf604a96548e0a4a3a6739b468/numpy-1.26.4-cp311-cp311-win32.whl", hash = "sha256:1af303d6b2210eb850fcf03064d364652b7120803a0b872f5211f5234b399f20", size = 5968812 },
+    { url = "https://files.pythonhosted.org/packages/3f/6b/5610004206cf7f8e7ad91c5a85a8c71b2f2f8051a0c0c4d5916b76d6cbb2/numpy-1.26.4-cp311-cp311-win_amd64.whl", hash = "sha256:cd25bcecc4974d09257ffcd1f098ee778f7834c3ad767fe5db785be9a4aa9cb2", size = 15811913 },
+    { url = "https://files.pythonhosted.org/packages/95/12/8f2020a8e8b8383ac0177dc9570aad031a3beb12e38847f7129bacd96228/numpy-1.26.4-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:b3ce300f3644fb06443ee2222c2201dd3a89ea6040541412b8fa189341847218", size = 20335901 },
+    { url = "https://files.pythonhosted.org/packages/75/5b/ca6c8bd14007e5ca171c7c03102d17b4f4e0ceb53957e8c44343a9546dcc/numpy-1.26.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b", size = 13685868 },
+    { url = "https://files.pythonhosted.org/packages/79/f8/97f10e6755e2a7d027ca783f63044d5b1bc1ae7acb12afe6a9b4286eac17/numpy-1.26.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9fad7dcb1aac3c7f0584a5a8133e3a43eeb2fe127f47e3632d43d677c66c102b", size = 13925109 },
+    { url = "https://files.pythonhosted.org/packages/0f/50/de23fde84e45f5c4fda2488c759b69990fd4512387a8632860f3ac9cd225/numpy-1.26.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:675d61ffbfa78604709862923189bad94014bef562cc35cf61d3a07bba02a7ed", size = 17950613 },
+    { url = "https://files.pythonhosted.org/packages/4c/0c/9c603826b6465e82591e05ca230dfc13376da512b25ccd0894709b054ed0/numpy-1.26.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:ab47dbe5cc8210f55aa58e4805fe224dac469cde56b9f731a4c098b91917159a", size = 13572172 },
+    { url = "https://files.pythonhosted.org/packages/76/8c/2ba3902e1a0fc1c74962ea9bb33a534bb05984ad7ff9515bf8d07527cadd/numpy-1.26.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:1dda2e7b4ec9dd512f84935c5f126c8bd8b9f2fc001e9f54af255e8c5f16b0e0", size = 17786643 },
+    { url = "https://files.pythonhosted.org/packages/28/4a/46d9e65106879492374999e76eb85f87b15328e06bd1550668f79f7b18c6/numpy-1.26.4-cp312-cp312-win32.whl", hash = "sha256:50193e430acfc1346175fcbdaa28ffec49947a06918b7b92130744e81e640110", size = 5677803 },
+    { url = "https://files.pythonhosted.org/packages/16/2e/86f24451c2d530c88daf997cb8d6ac622c1d40d19f5a031ed68a4b73a374/numpy-1.26.4-cp312-cp312-win_amd64.whl", hash = "sha256:08beddf13648eb95f8d867350f6a018a4be2e5ad54c8d8caed89ebca558b2818", size = 15517754 },
+    { url = "https://files.pythonhosted.org/packages/7d/24/ce71dc08f06534269f66e73c04f5709ee024a1afe92a7b6e1d73f158e1f8/numpy-1.26.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:7349ab0fa0c429c82442a27a9673fc802ffdb7c7775fad780226cb234965e53c", size = 20636301 },
+    { url = "https://files.pythonhosted.org/packages/ae/8c/ab03a7c25741f9ebc92684a20125fbc9fc1b8e1e700beb9197d750fdff88/numpy-1.26.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:52b8b60467cd7dd1e9ed082188b4e6bb35aa5cdd01777621a1658910745b90be", size = 13971216 },
+    { url = "https://files.pythonhosted.org/packages/6d/64/c3bcdf822269421d85fe0d64ba972003f9bb4aa9a419da64b86856c9961f/numpy-1.26.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d5241e0a80d808d70546c697135da2c613f30e28251ff8307eb72ba696945764", size = 14226281 },
+    { url = "https://files.pythonhosted.org/packages/54/30/c2a907b9443cf42b90c17ad10c1e8fa801975f01cb9764f3f8eb8aea638b/numpy-1.26.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f870204a840a60da0b12273ef34f7051e98c3b5961b61b0c2c1be6dfd64fbcd3", size = 18249516 },
+    { url = "https://files.pythonhosted.org/packages/43/12/01a563fc44c07095996d0129b8899daf89e4742146f7044cdbdb3101c57f/numpy-1.26.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:679b0076f67ecc0138fd2ede3a8fd196dddc2ad3254069bcb9faf9a79b1cebcd", size = 13882132 },
+    { url = "https://files.pythonhosted.org/packages/16/ee/9df80b06680aaa23fc6c31211387e0db349e0e36d6a63ba3bd78c5acdf11/numpy-1.26.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:47711010ad8555514b434df65f7d7b076bb8261df1ca9bb78f53d3b2db02e95c", size = 18084181 },
+    { url = "https://files.pythonhosted.org/packages/28/7d/4b92e2fe20b214ffca36107f1a3e75ef4c488430e64de2d9af5db3a4637d/numpy-1.26.4-cp39-cp39-win32.whl", hash = "sha256:a354325ee03388678242a4d7ebcd08b5c727033fcff3b2f536aea978e15ee9e6", size = 5976360 },
+    { url = "https://files.pythonhosted.org/packages/b5/42/054082bd8220bbf6f297f982f0a8f5479fcbc55c8b511d928df07b965869/numpy-1.26.4-cp39-cp39-win_amd64.whl", hash = "sha256:3373d5d70a5fe74a2c1bb6d2cfd9609ecf686d47a2d7b1d37a8f3b6bf6003aea", size = 15814633 },
+    { url = "https://files.pythonhosted.org/packages/3f/72/3df6c1c06fc83d9cfe381cccb4be2532bbd38bf93fbc9fad087b6687f1c0/numpy-1.26.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:afedb719a9dcfc7eaf2287b839d8198e06dcd4cb5d276a3df279231138e83d30", size = 20455961 },
+    { url = "https://files.pythonhosted.org/packages/8e/02/570545bac308b58ffb21adda0f4e220ba716fb658a63c151daecc3293350/numpy-1.26.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:95a7476c59002f2f6c590b9b7b998306fba6a5aa646b1e22ddfeaf8f78c3a29c", size = 18061071 },
+    { url = "https://files.pythonhosted.org/packages/f4/5f/fafd8c51235f60d49f7a88e2275e13971e90555b67da52dd6416caec32fe/numpy-1.26.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:7e50d0a0cc3189f9cb0aeb3a6a6af18c16f59f004b866cd2be1c14b36134a4a0", size = 15709730 },
 ]
 
 [[package]]
 name = "numpy"
-version = "2.2.3"
+version = "2.2.2"
 source = { registry = "https://pypi.org/simple" }
 resolution-markers = [
     "python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy'",
     "python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy'",
     "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy'",
     "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy'",
-    "python_full_version == '3.11.*' and platform_python_implementation == 'PyPy'",
-    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy'",
-    "python_full_version == '3.10.*' and platform_python_implementation == 'PyPy'",
-    "python_full_version == '3.10.*' and platform_python_implementation != 'PyPy'",
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/fb/90/8956572f5c4ae52201fdec7ba2044b2c882832dcec7d5d0922c9e9acf2de/numpy-2.2.3.tar.gz", hash = "sha256:dbdc15f0c81611925f382dfa97b3bd0bc2c1ce19d4fe50482cb0ddc12ba30020", size = 20262700 }
+sdist = { url = "https://files.pythonhosted.org/packages/ec/d0/c12ddfd3a02274be06ffc71f3efc6d0e457b0409c4481596881e748cb264/numpy-2.2.2.tar.gz", hash = "sha256:ed6906f61834d687738d25988ae117683705636936cc605be0bb208b23df4d8f", size = 20233295 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/5e/e1/1816d5d527fa870b260a1c2c5904d060caad7515637bd54f495a5ce13ccd/numpy-2.2.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:cbc6472e01952d3d1b2772b720428f8b90e2deea8344e854df22b0618e9cce71", size = 21232911 },
-    { url = "https://files.pythonhosted.org/packages/29/46/9f25dc19b359f10c0e52b6bac25d3181eb1f4b4d04c9846a32cf5ea52762/numpy-2.2.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:cdfe0c22692a30cd830c0755746473ae66c4a8f2e7bd508b35fb3b6a0813d787", size = 14371955 },
-    { url = "https://files.pythonhosted.org/packages/72/d7/de941296e6b09a5c81d3664ad912f1496a0ecdd2f403318e5e35604ff70f/numpy-2.2.3-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:e37242f5324ffd9f7ba5acf96d774f9276aa62a966c0bad8dae692deebec7716", size = 5410476 },
-    { url = "https://files.pythonhosted.org/packages/36/ce/55f685995110f8a268fdca0f198c9a84fa87b39512830965cc1087af6391/numpy-2.2.3-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:95172a21038c9b423e68be78fd0be6e1b97674cde269b76fe269a5dfa6fadf0b", size = 6945730 },
-    { url = "https://files.pythonhosted.org/packages/4f/84/abdb9f6e22576d89c259401c3234d4755b322539491bbcffadc8bcb120d3/numpy-2.2.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d5b47c440210c5d1d67e1cf434124e0b5c395eee1f5806fdd89b553ed1acd0a3", size = 14350752 },
-    { url = "https://files.pythonhosted.org/packages/e9/88/3870cfa9bef4dffb3a326507f430e6007eeac258ebeef6b76fc542aef66d/numpy-2.2.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0391ea3622f5c51a2e29708877d56e3d276827ac5447d7f45e9bc4ade8923c52", size = 16399386 },
-    { url = "https://files.pythonhosted.org/packages/02/10/3f629682dd0b457525c131945329c4e81e2dadeb11256e6ce4c9a1a6fb41/numpy-2.2.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:f6b3dfc7661f8842babd8ea07e9897fe3d9b69a1d7e5fbb743e4160f9387833b", size = 15561826 },
-    { url = "https://files.pythonhosted.org/packages/da/18/fd35673ba9751eba449d4ce5d24d94e3b612cdbfba79348da71488c0b7ac/numpy-2.2.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:1ad78ce7f18ce4e7df1b2ea4019b5817a2f6a8a16e34ff2775f646adce0a5027", size = 18188593 },
-    { url = "https://files.pythonhosted.org/packages/ce/4c/c0f897b580ea59484b4cc96a441fea50333b26675a60a1421bc912268b5f/numpy-2.2.3-cp310-cp310-win32.whl", hash = "sha256:5ebeb7ef54a7be11044c33a17b2624abe4307a75893c001a4800857956b41094", size = 6590421 },
-    { url = "https://files.pythonhosted.org/packages/e5/5b/aaabbfc7060c5c8f0124c5deb5e114a3b413a548bbc64e372c5b5db36165/numpy-2.2.3-cp310-cp310-win_amd64.whl", hash = "sha256:596140185c7fa113563c67c2e894eabe0daea18cf8e33851738c19f70ce86aeb", size = 12925667 },
-    { url = "https://files.pythonhosted.org/packages/96/86/453aa3949eab6ff54e2405f9cb0c01f756f031c3dc2a6d60a1d40cba5488/numpy-2.2.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:16372619ee728ed67a2a606a614f56d3eabc5b86f8b615c79d01957062826ca8", size = 21237256 },
-    { url = "https://files.pythonhosted.org/packages/20/c3/93ecceadf3e155d6a9e4464dd2392d8d80cf436084c714dc8535121c83e8/numpy-2.2.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:5521a06a3148686d9269c53b09f7d399a5725c47bbb5b35747e1cb76326b714b", size = 14408049 },
-    { url = "https://files.pythonhosted.org/packages/8d/29/076999b69bd9264b8df5e56f2be18da2de6b2a2d0e10737e5307592e01de/numpy-2.2.3-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:7c8dde0ca2f77828815fd1aedfdf52e59071a5bae30dac3b4da2a335c672149a", size = 5408655 },
-    { url = "https://files.pythonhosted.org/packages/e2/a7/b14f0a73eb0fe77cb9bd5b44534c183b23d4229c099e339c522724b02678/numpy-2.2.3-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:77974aba6c1bc26e3c205c2214f0d5b4305bdc719268b93e768ddb17e3fdd636", size = 6949996 },
-    { url = "https://files.pythonhosted.org/packages/72/2f/8063da0616bb0f414b66dccead503bd96e33e43685c820e78a61a214c098/numpy-2.2.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d42f9c36d06440e34226e8bd65ff065ca0963aeecada587b937011efa02cdc9d", size = 14355789 },
-    { url = "https://files.pythonhosted.org/packages/e6/d7/3cd47b00b8ea95ab358c376cf5602ad21871410950bc754cf3284771f8b6/numpy-2.2.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f2712c5179f40af9ddc8f6727f2bd910ea0eb50206daea75f58ddd9fa3f715bb", size = 16411356 },
-    { url = "https://files.pythonhosted.org/packages/27/c0/a2379e202acbb70b85b41483a422c1e697ff7eee74db642ca478de4ba89f/numpy-2.2.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c8b0451d2ec95010d1db8ca733afc41f659f425b7f608af569711097fd6014e2", size = 15576770 },
-    { url = "https://files.pythonhosted.org/packages/bc/63/a13ee650f27b7999e5b9e1964ae942af50bb25606d088df4229283eda779/numpy-2.2.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:d9b4a8148c57ecac25a16b0e11798cbe88edf5237b0df99973687dd866f05e1b", size = 18200483 },
-    { url = "https://files.pythonhosted.org/packages/4c/87/e71f89935e09e8161ac9c590c82f66d2321eb163893a94af749dfa8a3cf8/numpy-2.2.3-cp311-cp311-win32.whl", hash = "sha256:1f45315b2dc58d8a3e7754fe4e38b6fce132dab284a92851e41b2b344f6441c5", size = 6588415 },
-    { url = "https://files.pythonhosted.org/packages/b9/c6/cd4298729826af9979c5f9ab02fcaa344b82621e7c49322cd2d210483d3f/numpy-2.2.3-cp311-cp311-win_amd64.whl", hash = "sha256:9f48ba6f6c13e5e49f3d3efb1b51c8193215c42ac82610a04624906a9270be6f", size = 12929604 },
-    { url = "https://files.pythonhosted.org/packages/43/ec/43628dcf98466e087812142eec6d1c1a6c6bdfdad30a0aa07b872dc01f6f/numpy-2.2.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:12c045f43b1d2915eca6b880a7f4a256f59d62df4f044788c8ba67709412128d", size = 20929458 },
-    { url = "https://files.pythonhosted.org/packages/9b/c0/2f4225073e99a5c12350954949ed19b5d4a738f541d33e6f7439e33e98e4/numpy-2.2.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:87eed225fd415bbae787f93a457af7f5990b92a334e346f72070bf569b9c9c95", size = 14115299 },
-    { url = "https://files.pythonhosted.org/packages/ca/fa/d2c5575d9c734a7376cc1592fae50257ec95d061b27ee3dbdb0b3b551eb2/numpy-2.2.3-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:712a64103d97c404e87d4d7c47fb0c7ff9acccc625ca2002848e0d53288b90ea", size = 5145723 },
-    { url = "https://files.pythonhosted.org/packages/eb/dc/023dad5b268a7895e58e791f28dc1c60eb7b6c06fcbc2af8538ad069d5f3/numpy-2.2.3-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:a5ae282abe60a2db0fd407072aff4599c279bcd6e9a2475500fc35b00a57c532", size = 6678797 },
-    { url = "https://files.pythonhosted.org/packages/3f/19/bcd641ccf19ac25abb6fb1dcd7744840c11f9d62519d7057b6ab2096eb60/numpy-2.2.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5266de33d4c3420973cf9ae3b98b54a2a6d53a559310e3236c4b2b06b9c07d4e", size = 14067362 },
-    { url = "https://files.pythonhosted.org/packages/39/04/78d2e7402fb479d893953fb78fa7045f7deb635ec095b6b4f0260223091a/numpy-2.2.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3b787adbf04b0db1967798dba8da1af07e387908ed1553a0d6e74c084d1ceafe", size = 16116679 },
-    { url = "https://files.pythonhosted.org/packages/d0/a1/e90f7aa66512be3150cb9d27f3d9995db330ad1b2046474a13b7040dfd92/numpy-2.2.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:34c1b7e83f94f3b564b35f480f5652a47007dd91f7c839f404d03279cc8dd021", size = 15264272 },
-    { url = "https://files.pythonhosted.org/packages/dc/b6/50bd027cca494de4fa1fc7bf1662983d0ba5f256fa0ece2c376b5eb9b3f0/numpy-2.2.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:4d8335b5f1b6e2bce120d55fb17064b0262ff29b459e8493d1785c18ae2553b8", size = 17880549 },
-    { url = "https://files.pythonhosted.org/packages/96/30/f7bf4acb5f8db10a96f73896bdeed7a63373137b131ca18bd3dab889db3b/numpy-2.2.3-cp312-cp312-win32.whl", hash = "sha256:4d9828d25fb246bedd31e04c9e75714a4087211ac348cb39c8c5f99dbb6683fe", size = 6293394 },
-    { url = "https://files.pythonhosted.org/packages/42/6e/55580a538116d16ae7c9aa17d4edd56e83f42126cb1dfe7a684da7925d2c/numpy-2.2.3-cp312-cp312-win_amd64.whl", hash = "sha256:83807d445817326b4bcdaaaf8e8e9f1753da04341eceec705c001ff342002e5d", size = 12626357 },
-    { url = "https://files.pythonhosted.org/packages/0e/8b/88b98ed534d6a03ba8cddb316950fe80842885709b58501233c29dfa24a9/numpy-2.2.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:7bfdb06b395385ea9b91bf55c1adf1b297c9fdb531552845ff1d3ea6e40d5aba", size = 20916001 },
-    { url = "https://files.pythonhosted.org/packages/d9/b4/def6ec32c725cc5fbd8bdf8af80f616acf075fe752d8a23e895da8c67b70/numpy-2.2.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:23c9f4edbf4c065fddb10a4f6e8b6a244342d95966a48820c614891e5059bb50", size = 14130721 },
-    { url = "https://files.pythonhosted.org/packages/20/60/70af0acc86495b25b672d403e12cb25448d79a2b9658f4fc45e845c397a8/numpy-2.2.3-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:a0c03b6be48aaf92525cccf393265e02773be8fd9551a2f9adbe7db1fa2b60f1", size = 5130999 },
-    { url = "https://files.pythonhosted.org/packages/2e/69/d96c006fb73c9a47bcb3611417cf178049aae159afae47c48bd66df9c536/numpy-2.2.3-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:2376e317111daa0a6739e50f7ee2a6353f768489102308b0d98fcf4a04f7f3b5", size = 6665299 },
-    { url = "https://files.pythonhosted.org/packages/5a/3f/d8a877b6e48103733ac224ffa26b30887dc9944ff95dffdfa6c4ce3d7df3/numpy-2.2.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8fb62fe3d206d72fe1cfe31c4a1106ad2b136fcc1606093aeab314f02930fdf2", size = 14064096 },
-    { url = "https://files.pythonhosted.org/packages/e4/43/619c2c7a0665aafc80efca465ddb1f260287266bdbdce517396f2f145d49/numpy-2.2.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:52659ad2534427dffcc36aac76bebdd02b67e3b7a619ac67543bc9bfe6b7cdb1", size = 16114758 },
-    { url = "https://files.pythonhosted.org/packages/d9/79/ee4fe4f60967ccd3897aa71ae14cdee9e3c097e3256975cc9575d393cb42/numpy-2.2.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:1b416af7d0ed3271cad0f0a0d0bee0911ed7eba23e66f8424d9f3dfcdcae1304", size = 15259880 },
-    { url = "https://files.pythonhosted.org/packages/fb/c8/8b55cf05db6d85b7a7d414b3d1bd5a740706df00bfa0824a08bf041e52ee/numpy-2.2.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:1402da8e0f435991983d0a9708b779f95a8c98c6b18a171b9f1be09005e64d9d", size = 17876721 },
-    { url = "https://files.pythonhosted.org/packages/21/d6/b4c2f0564b7dcc413117b0ffbb818d837e4b29996b9234e38b2025ed24e7/numpy-2.2.3-cp313-cp313-win32.whl", hash = "sha256:136553f123ee2951bfcfbc264acd34a2fc2f29d7cdf610ce7daf672b6fbaa693", size = 6290195 },
-    { url = "https://files.pythonhosted.org/packages/97/e7/7d55a86719d0de7a6a597949f3febefb1009435b79ba510ff32f05a8c1d7/numpy-2.2.3-cp313-cp313-win_amd64.whl", hash = "sha256:5b732c8beef1d7bc2d9e476dbba20aaff6167bf205ad9aa8d30913859e82884b", size = 12619013 },
-    { url = "https://files.pythonhosted.org/packages/a6/1f/0b863d5528b9048fd486a56e0b97c18bf705e88736c8cea7239012119a54/numpy-2.2.3-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:435e7a933b9fda8126130b046975a968cc2d833b505475e588339e09f7672890", size = 20944621 },
-    { url = "https://files.pythonhosted.org/packages/aa/99/b478c384f7a0a2e0736177aafc97dc9152fc036a3fdb13f5a3ab225f1494/numpy-2.2.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:7678556eeb0152cbd1522b684dcd215250885993dd00adb93679ec3c0e6e091c", size = 14142502 },
-    { url = "https://files.pythonhosted.org/packages/fb/61/2d9a694a0f9cd0a839501d362de2a18de75e3004576a3008e56bdd60fcdb/numpy-2.2.3-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:2e8da03bd561504d9b20e7a12340870dfc206c64ea59b4cfee9fceb95070ee94", size = 5176293 },
-    { url = "https://files.pythonhosted.org/packages/33/35/51e94011b23e753fa33f891f601e5c1c9a3d515448659b06df9d40c0aa6e/numpy-2.2.3-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:c9aa4496fd0e17e3843399f533d62857cef5900facf93e735ef65aa4bbc90ef0", size = 6691874 },
-    { url = "https://files.pythonhosted.org/packages/ff/cf/06e37619aad98a9d03bd8d65b8e3041c3a639be0f5f6b0a0e2da544538d4/numpy-2.2.3-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f4ca91d61a4bf61b0f2228f24bbfa6a9facd5f8af03759fe2a655c50ae2c6610", size = 14036826 },
-    { url = "https://files.pythonhosted.org/packages/0c/93/5d7d19955abd4d6099ef4a8ee006f9ce258166c38af259f9e5558a172e3e/numpy-2.2.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:deaa09cd492e24fd9b15296844c0ad1b3c976da7907e1c1ed3a0ad21dded6f76", size = 16096567 },
-    { url = "https://files.pythonhosted.org/packages/af/53/d1c599acf7732d81f46a93621dab6aa8daad914b502a7a115b3f17288ab2/numpy-2.2.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:246535e2f7496b7ac85deffe932896a3577be7af8fb7eebe7146444680297e9a", size = 15242514 },
-    { url = "https://files.pythonhosted.org/packages/53/43/c0f5411c7b3ea90adf341d05ace762dad8cb9819ef26093e27b15dd121ac/numpy-2.2.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:daf43a3d1ea699402c5a850e5313680ac355b4adc9770cd5cfc2940e7861f1bf", size = 17872920 },
-    { url = "https://files.pythonhosted.org/packages/5b/57/6dbdd45ab277aff62021cafa1e15f9644a52f5b5fc840bc7591b4079fb58/numpy-2.2.3-cp313-cp313t-win32.whl", hash = "sha256:cf802eef1f0134afb81fef94020351be4fe1d6681aadf9c5e862af6602af64ef", size = 6346584 },
-    { url = "https://files.pythonhosted.org/packages/97/9b/484f7d04b537d0a1202a5ba81c6f53f1846ae6c63c2127f8df869ed31342/numpy-2.2.3-cp313-cp313t-win_amd64.whl", hash = "sha256:aee2512827ceb6d7f517c8b85aa5d3923afe8fc7a57d028cffcd522f1c6fd082", size = 12706784 },
-    { url = "https://files.pythonhosted.org/packages/0a/b5/a7839f5478be8f859cb880f13d90fcfe4b0ec7a9ebaff2bcc30d96760596/numpy-2.2.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:3c2ec8a0f51d60f1e9c0c5ab116b7fc104b165ada3f6c58abf881cb2eb16044d", size = 21064244 },
-    { url = "https://files.pythonhosted.org/packages/29/e8/5da32ffcaa7a72f7ecd82f90c062140a061eb823cb88e90279424e515cf4/numpy-2.2.3-pp310-pypy310_pp73-macosx_14_0_x86_64.whl", hash = "sha256:ed2cf9ed4e8ebc3b754d398cba12f24359f018b416c380f577bbae112ca52fc9", size = 6809418 },
-    { url = "https://files.pythonhosted.org/packages/a8/a9/68aa7076c7656a7308a0f73d0a2ced8c03f282c9fd98fa7ce21c12634087/numpy-2.2.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:39261798d208c3095ae4f7bc8eaeb3481ea8c6e03dc48028057d3cbdbdb8937e", size = 16215461 },
-    { url = "https://files.pythonhosted.org/packages/17/7f/d322a4125405920401450118dbdc52e0384026bd669939484670ce8b2ab9/numpy-2.2.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:783145835458e60fa97afac25d511d00a1eca94d4a8f3ace9fe2043003c678e4", size = 12839607 },
+    { url = "https://files.pythonhosted.org/packages/70/2a/69033dc22d981ad21325314f8357438078f5c28310a6d89fb3833030ec8a/numpy-2.2.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7079129b64cb78bdc8d611d1fd7e8002c0a2565da6a47c4df8062349fee90e3e", size = 21215825 },
+    { url = "https://files.pythonhosted.org/packages/31/2c/39f91e00bbd3d5639b027ac48c55dc5f2992bd2b305412d26be4c830862a/numpy-2.2.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2ec6c689c61df613b783aeb21f945c4cbe6c51c28cb70aae8430577ab39f163e", size = 14354996 },
+    { url = "https://files.pythonhosted.org/packages/0a/2c/d468ebd253851af10de5b3e8f3418ebabfaab5f0337a75299fbeb8b8c17a/numpy-2.2.2-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:40c7ff5da22cd391944a28c6a9c638a5eef77fcf71d6e3a79e1d9d9e82752715", size = 5393621 },
+    { url = "https://files.pythonhosted.org/packages/7f/f4/3d8a5a0da297034106c5de92be881aca7079cde6058934215a1de91334f6/numpy-2.2.2-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:995f9e8181723852ca458e22de5d9b7d3ba4da3f11cc1cb113f093b271d7965a", size = 6928931 },
+    { url = "https://files.pythonhosted.org/packages/47/a7/029354ab56edd43dd3f5efbfad292b8844f98b93174f322f82353fa46efa/numpy-2.2.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b78ea78450fd96a498f50ee096f69c75379af5138f7881a51355ab0e11286c97", size = 14333157 },
+    { url = "https://files.pythonhosted.org/packages/e3/d7/11fc594838d35c43519763310c316d4fd56f8600d3fc80a8e13e325b5c5c/numpy-2.2.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3fbe72d347fbc59f94124125e73fc4976a06927ebc503ec5afbfb35f193cd957", size = 16381794 },
+    { url = "https://files.pythonhosted.org/packages/af/d4/dd9b19cd4aff9c79d3f54d17f8be815407520d3116004bc574948336981b/numpy-2.2.2-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:8e6da5cffbbe571f93588f562ed130ea63ee206d12851b60819512dd3e1ba50d", size = 15543990 },
+    { url = "https://files.pythonhosted.org/packages/30/97/ab96b7650f27f684a9b1e46757a7294ecc50cab27701d05f146e9f779627/numpy-2.2.2-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:09d6a2032faf25e8d0cadde7fd6145118ac55d2740132c1d845f98721b5ebcfd", size = 18170896 },
+    { url = "https://files.pythonhosted.org/packages/81/9b/bae9618cab20db67a2ca9d711795cad29b2ca4b73034dd3b5d05b962070a/numpy-2.2.2-cp310-cp310-win32.whl", hash = "sha256:159ff6ee4c4a36a23fe01b7c3d07bd8c14cc433d9720f977fcd52c13c0098160", size = 6573458 },
+    { url = "https://files.pythonhosted.org/packages/92/9b/95678092febd14070cfb7906ea7932e71e9dd5a6ab3ee948f9ed975e905d/numpy-2.2.2-cp310-cp310-win_amd64.whl", hash = "sha256:64bd6e1762cd7f0986a740fee4dff927b9ec2c5e4d9a28d056eb17d332158014", size = 12915812 },
+    { url = "https://files.pythonhosted.org/packages/21/67/32c68756eed84df181c06528ff57e09138f893c4653448c4967311e0f992/numpy-2.2.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:642199e98af1bd2b6aeb8ecf726972d238c9877b0f6e8221ee5ab945ec8a2189", size = 21220002 },
+    { url = "https://files.pythonhosted.org/packages/3b/89/f43bcad18f2b2e5814457b1c7f7b0e671d0db12c8c0e43397ab8cb1831ed/numpy-2.2.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:6d9fc9d812c81e6168b6d405bf00b8d6739a7f72ef22a9214c4241e0dc70b323", size = 14391215 },
+    { url = "https://files.pythonhosted.org/packages/9c/e6/efb8cd6122bf25e86e3dd89d9dbfec9e6861c50e8810eed77d4be59b51c6/numpy-2.2.2-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:c7d1fd447e33ee20c1f33f2c8e6634211124a9aabde3c617687d8b739aa69eac", size = 5391918 },
+    { url = "https://files.pythonhosted.org/packages/47/e2/fccf89d64d9b47ffb242823d4e851fc9d36fa751908c9aac2807924d9b4e/numpy-2.2.2-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:451e854cfae0febe723077bd0cf0a4302a5d84ff25f0bfece8f29206c7bed02e", size = 6933133 },
+    { url = "https://files.pythonhosted.org/packages/34/22/5ece749c0e5420a9380eef6fbf83d16a50010bd18fef77b9193d80a6760e/numpy-2.2.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bd249bc894af67cbd8bad2c22e7cbcd46cf87ddfca1f1289d1e7e54868cc785c", size = 14338187 },
+    { url = "https://files.pythonhosted.org/packages/5b/86/caec78829311f62afa6fa334c8dfcd79cffb4d24bcf96ee02ae4840d462b/numpy-2.2.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:02935e2c3c0c6cbe9c7955a8efa8908dd4221d7755644c59d1bba28b94fd334f", size = 16393429 },
+    { url = "https://files.pythonhosted.org/packages/c8/4e/0c25f74c88239a37924577d6ad780f3212a50f4b4b5f54f5e8c918d726bd/numpy-2.2.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:a972cec723e0563aa0823ee2ab1df0cb196ed0778f173b381c871a03719d4826", size = 15559103 },
+    { url = "https://files.pythonhosted.org/packages/d4/bd/d557f10fa50dc4d5871fb9606af563249b66af2fc6f99041a10e8757c6f1/numpy-2.2.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:d6d6a0910c3b4368d89dde073e630882cdb266755565155bc33520283b2d9df8", size = 18182967 },
+    { url = "https://files.pythonhosted.org/packages/30/e9/66cc0f66386d78ed89e45a56e2a1d051e177b6e04477c4a41cd590ef4017/numpy-2.2.2-cp311-cp311-win32.whl", hash = "sha256:860fd59990c37c3ef913c3ae390b3929d005243acca1a86facb0773e2d8d9e50", size = 6571499 },
+    { url = "https://files.pythonhosted.org/packages/66/a3/4139296b481ae7304a43581046b8f0a20da6a0dfe0ee47a044cade796603/numpy-2.2.2-cp311-cp311-win_amd64.whl", hash = "sha256:da1eeb460ecce8d5b8608826595c777728cdf28ce7b5a5a8c8ac8d949beadcf2", size = 12919805 },
+    { url = "https://files.pythonhosted.org/packages/0c/e6/847d15770ab7a01e807bdfcd4ead5bdae57c0092b7dc83878171b6af97bb/numpy-2.2.2-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:ac9bea18d6d58a995fac1b2cb4488e17eceeac413af014b1dd26170b766d8467", size = 20912636 },
+    { url = "https://files.pythonhosted.org/packages/d1/af/f83580891577b13bd7e261416120e036d0d8fb508c8a43a73e38928b794b/numpy-2.2.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:23ae9f0c2d889b7b2d88a3791f6c09e2ef827c2446f1c4a3e3e76328ee4afd9a", size = 14098403 },
+    { url = "https://files.pythonhosted.org/packages/2b/86/d019fb60a9d0f1d4cf04b014fe88a9135090adfadcc31c1fadbb071d7fa7/numpy-2.2.2-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:3074634ea4d6df66be04f6728ee1d173cfded75d002c75fac79503a880bf3825", size = 5128938 },
+    { url = "https://files.pythonhosted.org/packages/7a/1b/50985edb6f1ec495a1c36452e860476f5b7ecdc3fc59ea89ccad3c4926c5/numpy-2.2.2-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:8ec0636d3f7d68520afc6ac2dc4b8341ddb725039de042faf0e311599f54eb37", size = 6661937 },
+    { url = "https://files.pythonhosted.org/packages/f4/1b/17efd94cad1b9d605c3f8907fb06bcffc4ce4d1d14d46b95316cccccf2b9/numpy-2.2.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2ffbb1acd69fdf8e89dd60ef6182ca90a743620957afb7066385a7bbe88dc748", size = 14049518 },
+    { url = "https://files.pythonhosted.org/packages/5b/73/65d2f0b698df1731e851e3295eb29a5ab8aa06f763f7e4188647a809578d/numpy-2.2.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0349b025e15ea9d05c3d63f9657707a4e1d471128a3b1d876c095f328f8ff7f0", size = 16099146 },
+    { url = "https://files.pythonhosted.org/packages/d5/69/308f55c0e19d4b5057b5df286c5433822e3c8039ede06d4051d96f1c2c4e/numpy-2.2.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:463247edcee4a5537841d5350bc87fe8e92d7dd0e8c71c995d2c6eecb8208278", size = 15246336 },
+    { url = "https://files.pythonhosted.org/packages/f0/d8/d8d333ad0d8518d077a21aeea7b7c826eff766a2b1ce1194dea95ca0bacf/numpy-2.2.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:9dd47ff0cb2a656ad69c38da850df3454da88ee9a6fde0ba79acceee0e79daba", size = 17863507 },
+    { url = "https://files.pythonhosted.org/packages/82/6e/0b84ad3103ffc16d6673e63b5acbe7901b2af96c2837174c6318c98e27ab/numpy-2.2.2-cp312-cp312-win32.whl", hash = "sha256:4525b88c11906d5ab1b0ec1f290996c0020dd318af8b49acaa46f198b1ffc283", size = 6276491 },
+    { url = "https://files.pythonhosted.org/packages/fc/84/7f801a42a67b9772a883223a0a1e12069a14626c81a732bd70aac57aebc1/numpy-2.2.2-cp312-cp312-win_amd64.whl", hash = "sha256:5acea83b801e98541619af398cc0109ff48016955cc0818f478ee9ef1c5c3dcb", size = 12616372 },
+    { url = "https://files.pythonhosted.org/packages/e1/fe/df5624001f4f5c3e0b78e9017bfab7fdc18a8d3b3d3161da3d64924dd659/numpy-2.2.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:b208cfd4f5fe34e1535c08983a1a6803fdbc7a1e86cf13dd0c61de0b51a0aadc", size = 20899188 },
+    { url = "https://files.pythonhosted.org/packages/a9/80/d349c3b5ed66bd3cb0214be60c27e32b90a506946857b866838adbe84040/numpy-2.2.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:d0bbe7dd86dca64854f4b6ce2ea5c60b51e36dfd597300057cf473d3615f2369", size = 14113972 },
+    { url = "https://files.pythonhosted.org/packages/9d/50/949ec9cbb28c4b751edfa64503f0913cbfa8d795b4a251e7980f13a8a655/numpy-2.2.2-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:22ea3bb552ade325530e72a0c557cdf2dea8914d3a5e1fecf58fa5dbcc6f43cd", size = 5114294 },
+    { url = "https://files.pythonhosted.org/packages/8d/f3/399c15629d5a0c68ef2aa7621d430b2be22034f01dd7f3c65a9c9666c445/numpy-2.2.2-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:128c41c085cab8a85dc29e66ed88c05613dccf6bc28b3866cd16050a2f5448be", size = 6648426 },
+    { url = "https://files.pythonhosted.org/packages/2c/03/c72474c13772e30e1bc2e558cdffd9123c7872b731263d5648b5c49dd459/numpy-2.2.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:250c16b277e3b809ac20d1f590716597481061b514223c7badb7a0f9993c7f84", size = 14045990 },
+    { url = "https://files.pythonhosted.org/packages/83/9c/96a9ab62274ffafb023f8ee08c88d3d31ee74ca58869f859db6845494fa6/numpy-2.2.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e0c8854b09bc4de7b041148d8550d3bd712b5c21ff6a8ed308085f190235d7ff", size = 16096614 },
+    { url = "https://files.pythonhosted.org/packages/d5/34/cd0a735534c29bec7093544b3a509febc9b0df77718a9b41ffb0809c9f46/numpy-2.2.2-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:b6fb9c32a91ec32a689ec6410def76443e3c750e7cfc3fb2206b985ffb2b85f0", size = 15242123 },
+    { url = "https://files.pythonhosted.org/packages/5e/6d/541717a554a8f56fa75e91886d9b79ade2e595918690eb5d0d3dbd3accb9/numpy-2.2.2-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:57b4012e04cc12b78590a334907e01b3a85efb2107df2b8733ff1ed05fce71de", size = 17859160 },
+    { url = "https://files.pythonhosted.org/packages/b9/a5/fbf1f2b54adab31510728edd06a05c1b30839f37cf8c9747cb85831aaf1b/numpy-2.2.2-cp313-cp313-win32.whl", hash = "sha256:4dbd80e453bd34bd003b16bd802fac70ad76bd463f81f0c518d1245b1c55e3d9", size = 6273337 },
+    { url = "https://files.pythonhosted.org/packages/56/e5/01106b9291ef1d680f82bc47d0c5b5e26dfed15b0754928e8f856c82c881/numpy-2.2.2-cp313-cp313-win_amd64.whl", hash = "sha256:5a8c863ceacae696aff37d1fd636121f1a512117652e5dfb86031c8d84836369", size = 12609010 },
+    { url = "https://files.pythonhosted.org/packages/9f/30/f23d9876de0f08dceb707c4dcf7f8dd7588266745029debb12a3cdd40be6/numpy-2.2.2-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:b3482cb7b3325faa5f6bc179649406058253d91ceda359c104dac0ad320e1391", size = 20924451 },
+    { url = "https://files.pythonhosted.org/packages/6a/ec/6ea85b2da9d5dfa1dbb4cb3c76587fc8ddcae580cb1262303ab21c0926c4/numpy-2.2.2-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:9491100aba630910489c1d0158034e1c9a6546f0b1340f716d522dc103788e39", size = 14122390 },
+    { url = "https://files.pythonhosted.org/packages/68/05/bfbdf490414a7dbaf65b10c78bc243f312c4553234b6d91c94eb7c4b53c2/numpy-2.2.2-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:41184c416143defa34cc8eb9d070b0a5ba4f13a0fa96a709e20584638254b317", size = 5156590 },
+    { url = "https://files.pythonhosted.org/packages/f7/ec/fe2e91b2642b9d6544518388a441bcd65c904cea38d9ff998e2e8ebf808e/numpy-2.2.2-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:7dca87ca328f5ea7dafc907c5ec100d187911f94825f8700caac0b3f4c384b49", size = 6671958 },
+    { url = "https://files.pythonhosted.org/packages/b1/6f/6531a78e182f194d33ee17e59d67d03d0d5a1ce7f6be7343787828d1bd4a/numpy-2.2.2-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0bc61b307655d1a7f9f4b043628b9f2b721e80839914ede634e3d485913e1fb2", size = 14019950 },
+    { url = "https://files.pythonhosted.org/packages/e1/fb/13c58591d0b6294a08cc40fcc6b9552d239d773d520858ae27f39997f2ae/numpy-2.2.2-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fad446ad0bc886855ddf5909cbf8cb5d0faa637aaa6277fb4b19ade134ab3c7", size = 16079759 },
+    { url = "https://files.pythonhosted.org/packages/2c/f2/f2f8edd62abb4b289f65a7f6d1f3650273af00b91b7267a2431be7f1aec6/numpy-2.2.2-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:149d1113ac15005652e8d0d3f6fd599360e1a708a4f98e43c9c77834a28238cb", size = 15226139 },
+    { url = "https://files.pythonhosted.org/packages/aa/29/14a177f1a90b8ad8a592ca32124ac06af5eff32889874e53a308f850290f/numpy-2.2.2-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:106397dbbb1896f99e044efc90360d098b3335060375c26aa89c0d8a97c5f648", size = 17856316 },
+    { url = "https://files.pythonhosted.org/packages/95/03/242ae8d7b97f4e0e4ab8dd51231465fb23ed5e802680d629149722e3faf1/numpy-2.2.2-cp313-cp313t-win32.whl", hash = "sha256:0eec19f8af947a61e968d5429f0bd92fec46d92b0008d0a6685b40d6adf8a4f4", size = 6329134 },
+    { url = "https://files.pythonhosted.org/packages/80/94/cd9e9b04012c015cb6320ab3bf43bc615e248dddfeb163728e800a5d96f0/numpy-2.2.2-cp313-cp313t-win_amd64.whl", hash = "sha256:97b974d3ba0fb4612b77ed35d7627490e8e3dff56ab41454d9e8b23448940576", size = 12696208 },
+    { url = "https://files.pythonhosted.org/packages/96/7e/1dd770ee68916ed358991ab62c2cc353ffd98d0b75b901d52183ca28e8bb/numpy-2.2.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:b0531f0b0e07643eb089df4c509d30d72c9ef40defa53e41363eca8a8cc61495", size = 21047291 },
+    { url = "https://files.pythonhosted.org/packages/d1/3c/ccd08578dc532a8e6927952339d4a02682b776d5e85be49ed0760308433e/numpy-2.2.2-pp310-pypy310_pp73-macosx_14_0_x86_64.whl", hash = "sha256:e9e82dcb3f2ebbc8cb5ce1102d5f1c5ed236bf8a11730fb45ba82e2841ec21df", size = 6792494 },
+    { url = "https://files.pythonhosted.org/packages/7c/28/8754b9aee4f97199f9a047f73bb644b5a2014994a6d7b061ba67134a42de/numpy-2.2.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e0d4142eb40ca6f94539e4db929410f2a46052a0fe7a2c1c59f6179c39938d2a", size = 16197312 },
+    { url = "https://files.pythonhosted.org/packages/26/96/deb93f871f401045a684ca08a009382b247d14996d7a94fea6aa43c67b94/numpy-2.2.2-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:356ca982c188acbfa6af0d694284d8cf20e95b1c3d0aefa8929376fea9146f60", size = 12822674 },
 ]
 
 [[package]]
@@ -2480,8 +2479,8 @@ name = "pandas"
 version = "2.2.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" },
-    { name = "numpy", version = "2.2.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" },
+    { name = "numpy", version = "1.26.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
+    { name = "numpy", version = "2.2.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "python-dateutil" },
     { name = "pytz" },
     { name = "tzdata" },

libs/core/langchain_core/callbacks/base.py

@@ -3,14 +3,13 @@
 from __future__ import annotations
 
 import logging
+from collections.abc import Sequence
 from typing import TYPE_CHECKING, Any, Optional, TypeVar, Union
+from uuid import UUID
+
+from tenacity import RetryCallState
 
 if TYPE_CHECKING:
-    from collections.abc import Sequence
-    from uuid import UUID
-
-    from tenacity import RetryCallState
-
     from langchain_core.agents import AgentAction, AgentFinish
     from langchain_core.documents import Document
     from langchain_core.messages import BaseMessage

libs/core/langchain_core/callbacks/file.py

@@ -2,15 +2,12 @@
 
 from __future__ import annotations
 
-from pathlib import Path
-from typing import TYPE_CHECKING, Any, Optional, TextIO, cast
+from typing import Any, Optional, TextIO, cast
 
+from langchain_core.agents import AgentAction, AgentFinish
 from langchain_core.callbacks import BaseCallbackHandler
 from langchain_core.utils.input import print_text
 
-if TYPE_CHECKING:
-    from langchain_core.agents import AgentAction, AgentFinish
-
 
 class FileCallbackHandler(BaseCallbackHandler):
     """Callback Handler that writes to a file.
@@ -31,7 +28,7 @@ class FileCallbackHandler(BaseCallbackHandler):
             mode: The mode to open the file in. Defaults to "a".
             color: The color to use for the text. Defaults to None.
         """
-        self.file = cast(TextIO, Path(filename).open(mode, encoding="utf-8"))  # noqa: SIM115
+        self.file = cast(TextIO, open(filename, mode, encoding="utf-8"))  # noqa: SIM115
         self.color = color
 
     def __del__(self) -> None:
@@ -48,15 +45,9 @@ class FileCallbackHandler(BaseCallbackHandler):
             inputs (Dict[str, Any]): The inputs to the chain.
             **kwargs (Any): Additional keyword arguments.
         """
-        if "name" in kwargs:
-            name = kwargs["name"]
-        else:
-            if serialized:
-                name = serialized.get("name", serialized.get("id", ["<unknown>"])[-1])
-            else:
-                name = "<unknown>"
+        class_name = serialized.get("name", serialized.get("id", ["<unknown>"])[-1])
         print_text(
-            f"\n\n\033[1m> Entering new {name} chain...\033[0m",
+            f"\n\n\033[1m> Entering new {class_name} chain...\033[0m",
             end="\n",
             file=self.file,
         )

libs/core/langchain_core/callbacks/manager.py

@@ -5,6 +5,7 @@ import functools
 import logging
 import uuid
 from abc import ABC, abstractmethod
+from collections.abc import AsyncGenerator, Coroutine, Generator, Sequence
 from concurrent.futures import ThreadPoolExecutor
 from contextlib import asynccontextmanager, contextmanager
 from contextvars import copy_context
@@ -20,6 +21,7 @@ from typing import (
 from uuid import UUID
 
 from langsmith.run_helpers import get_tracing_context
+from tenacity import RetryCallState
 
 from langchain_core.callbacks.base import (
     BaseCallbackHandler,
@@ -37,10 +39,6 @@ from langchain_core.tracers.schemas import Run
 from langchain_core.utils.env import env_var_is_set
 
 if TYPE_CHECKING:
-    from collections.abc import AsyncGenerator, Coroutine, Generator, Sequence
-
-    from tenacity import RetryCallState
-
     from langchain_core.agents import AgentAction, AgentFinish
     from langchain_core.documents import Document
     from langchain_core.outputs import ChatGenerationChunk, GenerationChunk, LLMResult

libs/core/langchain_core/chat_history.py

@@ -17,7 +17,8 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING, Union
+from collections.abc import Sequence
+from typing import Union
 
 from pydantic import BaseModel, Field
 
@@ -28,9 +29,6 @@ from langchain_core.messages import (
     get_buffer_string,
 )
 
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
 
 class BaseChatMessageHistory(ABC):
     """Abstract base class for storing chat message history.

libs/core/langchain_core/document_loaders/base.py

@@ -3,17 +3,16 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
+from collections.abc import AsyncIterator, Iterator
 from typing import TYPE_CHECKING, Optional
 
+from langchain_core.documents import Document
 from langchain_core.runnables import run_in_executor
 
 if TYPE_CHECKING:
-    from collections.abc import AsyncIterator, Iterator
-
     from langchain_text_splitters import TextSplitter
 
-    from langchain_core.documents import Document
-    from langchain_core.documents.base import Blob
+from langchain_core.documents.base import Blob
 
 
 class BaseLoader(ABC):  # noqa: B024

libs/core/langchain_core/document_loaders/blob_loaders.py

@@ -8,15 +8,12 @@ In addition, content loading code should provide a lazy loading interface by def
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING
+from collections.abc import Iterable
 
 # Re-export Blob and PathLike for backwards compatibility
 from langchain_core.documents.base import Blob as Blob
 from langchain_core.documents.base import PathLike as PathLike
 
-if TYPE_CHECKING:
-    from collections.abc import Iterable
-
 
 class BlobLoader(ABC):
     """Abstract interface for blob loaders implementation.

libs/core/langchain_core/documents/base.py

@@ -2,17 +2,15 @@ from __future__ import annotations
 
 import contextlib
 import mimetypes
+from collections.abc import Generator
 from io import BufferedReader, BytesIO
-from pathlib import Path, PurePath
-from typing import TYPE_CHECKING, Any, Literal, Optional, Union, cast
+from pathlib import PurePath
+from typing import Any, Literal, Optional, Union, cast
 
 from pydantic import ConfigDict, Field, field_validator, model_validator
 
 from langchain_core.load.serializable import Serializable
 
-if TYPE_CHECKING:
-    from collections.abc import Generator
-
 PathLike = Union[str, PurePath]
 
 
@@ -151,7 +149,8 @@ class Blob(BaseMedia):
     def as_string(self) -> str:
         """Read data as a string."""
         if self.data is None and self.path:
-            return Path(self.path).read_text(encoding=self.encoding)
+            with open(str(self.path), encoding=self.encoding) as f:
+                return f.read()
         elif isinstance(self.data, bytes):
             return self.data.decode(self.encoding)
         elif isinstance(self.data, str):
@@ -167,7 +166,8 @@ class Blob(BaseMedia):
         elif isinstance(self.data, str):
             return self.data.encode(self.encoding)
         elif self.data is None and self.path:
-            return Path(self.path).read_bytes()
+            with open(str(self.path), "rb") as f:
+                return f.read()
         else:
             msg = f"Unable to get bytes for blob {self}"
             raise ValueError(msg)
@@ -178,7 +178,7 @@ class Blob(BaseMedia):
         if isinstance(self.data, bytes):
             yield BytesIO(self.data)
         elif self.data is None and self.path:
-            with Path(self.path).open("rb") as f:
+            with open(str(self.path), "rb") as f:
                 yield f
         else:
             msg = f"Unable to convert blob {self}"

libs/core/langchain_core/documents/compressor.py

@@ -1,18 +1,15 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING, Optional
+from collections.abc import Sequence
+from typing import Optional
 
 from pydantic import BaseModel
 
+from langchain_core.callbacks import Callbacks
+from langchain_core.documents import Document
 from langchain_core.runnables import run_in_executor
 
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-    from langchain_core.callbacks import Callbacks
-    from langchain_core.documents import Document
-
 
 class BaseDocumentCompressor(BaseModel, ABC):
     """Base class for document compressors.

libs/core/langchain_core/documents/transformers.py

@@ -1,13 +1,12 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
+from collections.abc import Sequence
 from typing import TYPE_CHECKING, Any
 
 from langchain_core.runnables.config import run_in_executor
 
 if TYPE_CHECKING:
-    from collections.abc import Sequence
-
     from langchain_core.documents import Document
 
 

libs/core/langchain_core/example_selectors/semantic_similarity.py

@@ -7,11 +7,11 @@ from typing import TYPE_CHECKING, Any, Optional
 
 from pydantic import BaseModel, ConfigDict
 
+from langchain_core.documents import Document
 from langchain_core.example_selectors.base import BaseExampleSelector
 from langchain_core.vectorstores import VectorStore
 
 if TYPE_CHECKING:
-    from langchain_core.documents import Document
     from langchain_core.embeddings import Embeddings
 
 

libs/core/langchain_core/indexing/base.py

@@ -3,17 +3,14 @@ from __future__ import annotations
 import abc
 import time
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING, Any, Optional, TypedDict
+from collections.abc import Sequence
+from typing import Any, Optional, TypedDict
 
 from langchain_core._api import beta
+from langchain_core.documents import Document
 from langchain_core.retrievers import BaseRetriever
 from langchain_core.runnables import run_in_executor
 
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-    from langchain_core.documents import Document
-
 
 class RecordManager(ABC):
     """Abstract base class representing the interface for a record manager.

libs/core/langchain_core/language_models/chat_models.py

@@ -4,6 +4,7 @@ import asyncio
 import inspect
 import json
 import typing
+import uuid
 import warnings
 from abc import ABC, abstractmethod
 from collections.abc import AsyncIterator, Iterator, Sequence
@@ -65,15 +66,10 @@ from langchain_core.rate_limiters import BaseRateLimiter
 from langchain_core.runnables import RunnableMap, RunnablePassthrough
 from langchain_core.runnables.config import ensure_config, run_in_executor
 from langchain_core.tracers._streaming import _StreamingCallbackHandler
-from langchain_core.utils.function_calling import (
-    convert_to_json_schema,
-    convert_to_openai_tool,
-)
+from langchain_core.utils.function_calling import convert_to_openai_tool
 from langchain_core.utils.pydantic import TypeBaseModel, is_basemodel_subclass
 
 if TYPE_CHECKING:
-    import uuid
-
     from langchain_core.output_parsers.base import OutputParserLike
     from langchain_core.runnables import Runnable, RunnableConfig
     from langchain_core.tools import BaseTool
@@ -119,25 +115,6 @@ async def agenerate_from_stream(
     return await run_in_executor(None, generate_from_stream, iter(chunks))
 
 
-def _format_ls_structured_output(ls_structured_output_format: Optional[dict]) -> dict:
-    if ls_structured_output_format:
-        try:
-            ls_structured_output_format_dict = {
-                "ls_structured_output_format": {
-                    "kwargs": ls_structured_output_format.get("kwargs", {}),
-                    "schema": convert_to_json_schema(
-                        ls_structured_output_format["schema"]
-                    ),
-                }
-            }
-        except ValueError:
-            ls_structured_output_format_dict = {}
-    else:
-        ls_structured_output_format_dict = {}
-
-    return ls_structured_output_format_dict
-
-
 class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
     """Base class for chat models.
 
@@ -388,18 +365,28 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
         else:
             config = ensure_config(config)
             messages = self._convert_input(input).to_messages()
-            ls_structured_output_format = kwargs.pop(
-                "ls_structured_output_format", None
-            )
-            ls_structured_output_format_dict = _format_ls_structured_output(
-                ls_structured_output_format
-            )
+            structured_output_format = kwargs.pop("structured_output_format", None)
+            if structured_output_format:
+                try:
+                    structured_output_format_dict = {
+                        "structured_output_format": {
+                            "kwargs": structured_output_format.get("kwargs", {}),
+                            "schema": convert_to_openai_tool(
+                                structured_output_format["schema"]
+                            ),
+                        }
+                    }
+                except ValueError:
+                    structured_output_format_dict = {}
+            else:
+                structured_output_format_dict = {}
 
             params = self._get_invocation_params(stop=stop, **kwargs)
-            options = {"stop": stop, **kwargs, **ls_structured_output_format_dict}
+            options = {"stop": stop, **kwargs}
             inheritable_metadata = {
                 **(config.get("metadata") or {}),
                 **self._get_ls_params(stop=stop, **kwargs),
+                **structured_output_format_dict,
             }
             callback_manager = CallbackManager.configure(
                 config.get("callbacks"),
@@ -472,16 +459,28 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
         config = ensure_config(config)
         messages = self._convert_input(input).to_messages()
 
-        ls_structured_output_format = kwargs.pop("ls_structured_output_format", None)
-        ls_structured_output_format_dict = _format_ls_structured_output(
-            ls_structured_output_format
-        )
+        structured_output_format = kwargs.pop("structured_output_format", None)
+        if structured_output_format:
+            try:
+                structured_output_format_dict = {
+                    "structured_output_format": {
+                        "kwargs": structured_output_format.get("kwargs", {}),
+                        "schema": convert_to_openai_tool(
+                            structured_output_format["schema"]
+                        ),
+                    }
+                }
+            except ValueError:
+                structured_output_format_dict = {}
+        else:
+            structured_output_format_dict = {}
 
         params = self._get_invocation_params(stop=stop, **kwargs)
-        options = {"stop": stop, **kwargs, **ls_structured_output_format_dict}
+        options = {"stop": stop, **kwargs}
         inheritable_metadata = {
             **(config.get("metadata") or {}),
             **self._get_ls_params(stop=stop, **kwargs),
+            **structured_output_format_dict,
         }
         callback_manager = AsyncCallbackManager.configure(
             config.get("callbacks"),
@@ -642,16 +641,28 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             An LLMResult, which contains a list of candidate Generations for each input
                 prompt and additional model provider-specific output.
         """
-        ls_structured_output_format = kwargs.pop("ls_structured_output_format", None)
-        ls_structured_output_format_dict = _format_ls_structured_output(
-            ls_structured_output_format
-        )
+        structured_output_format = kwargs.pop("structured_output_format", None)
+        if structured_output_format:
+            try:
+                structured_output_format_dict = {
+                    "structured_output_format": {
+                        "kwargs": structured_output_format.get("kwargs", {}),
+                        "schema": convert_to_openai_tool(
+                            structured_output_format["schema"]
+                        ),
+                    }
+                }
+            except ValueError:
+                structured_output_format_dict = {}
+        else:
+            structured_output_format_dict = {}
 
         params = self._get_invocation_params(stop=stop, **kwargs)
-        options = {"stop": stop, **ls_structured_output_format_dict}
+        options = {"stop": stop}
         inheritable_metadata = {
             **(metadata or {}),
             **self._get_ls_params(stop=stop, **kwargs),
+            **structured_output_format_dict,
         }
 
         callback_manager = CallbackManager.configure(
@@ -738,16 +749,28 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             An LLMResult, which contains a list of candidate Generations for each input
                 prompt and additional model provider-specific output.
         """
-        ls_structured_output_format = kwargs.pop("ls_structured_output_format", None)
-        ls_structured_output_format_dict = _format_ls_structured_output(
-            ls_structured_output_format
-        )
+        structured_output_format = kwargs.pop("structured_output_format", None)
+        if structured_output_format:
+            try:
+                structured_output_format_dict = {
+                    "structured_output_format": {
+                        "kwargs": structured_output_format.get("kwargs", {}),
+                        "schema": convert_to_openai_tool(
+                            structured_output_format["schema"]
+                        ),
+                    }
+                }
+            except ValueError:
+                structured_output_format_dict = {}
+        else:
+            structured_output_format_dict = {}
 
         params = self._get_invocation_params(stop=stop, **kwargs)
-        options = {"stop": stop, **ls_structured_output_format_dict}
+        options = {"stop": stop}
         inheritable_metadata = {
             **(metadata or {}),
             **self._get_ls_params(stop=stop, **kwargs),
+            **structured_output_format_dict,
         }
 
         callback_manager = AsyncCallbackManager.configure(
@@ -1290,10 +1313,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
         llm = self.bind_tools(
             [schema],
             tool_choice="any",
-            ls_structured_output_format={
-                "kwargs": {"method": "function_calling"},
-                "schema": schema,
-            },
+            structured_output_format={"kwargs": {}, "schema": schema},
         )
         if isinstance(schema, type) and is_basemodel_subclass(schema):
             output_parser: OutputParserLike = PydanticToolsParser(

libs/core/langchain_core/language_models/llms.py

@@ -7,12 +7,12 @@ import functools
 import inspect
 import json
 import logging
+import uuid
 import warnings
 from abc import ABC, abstractmethod
 from collections.abc import AsyncIterator, Iterator, Sequence
 from pathlib import Path
 from typing import (
-    TYPE_CHECKING,
     Any,
     Callable,
     Optional,
@@ -61,9 +61,6 @@ from langchain_core.prompt_values import ChatPromptValue, PromptValue, StringPro
 from langchain_core.runnables import RunnableConfig, ensure_config, get_config_list
 from langchain_core.runnables.config import run_in_executor
 
-if TYPE_CHECKING:
-    import uuid
-
 logger = logging.getLogger(__name__)
 
 
@@ -1402,7 +1399,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
             llm.save(file_path="path/llm.yaml")
         """
         # Convert file to Path object.
-        save_path = Path(file_path)
+        save_path = Path(file_path) if isinstance(file_path, str) else file_path
 
         directory_path = save_path.parent
         directory_path.mkdir(parents=True, exist_ok=True)
@@ -1411,10 +1408,10 @@ class BaseLLM(BaseLanguageModel[str], ABC):
         prompt_dict = self.dict()
 
         if save_path.suffix == ".json":
-            with save_path.open("w") as f:
+            with open(file_path, "w") as f:
                 json.dump(prompt_dict, f, indent=4)
         elif save_path.suffix.endswith((".yaml", ".yml")):
-            with save_path.open("w") as f:
+            with open(file_path, "w") as f:
                 yaml.dump(prompt_dict, f, default_flow_style=False)
         else:
             msg = f"{save_path} must be json or yaml"

libs/core/langchain_core/messages/base.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from collections.abc import Sequence
 from typing import TYPE_CHECKING, Any, Optional, Union, cast
 
 from pydantic import ConfigDict, Field, field_validator
@@ -10,8 +11,6 @@ from langchain_core.utils._merge import merge_dicts, merge_lists
 from langchain_core.utils.interactive_env import is_interactive_env
 
 if TYPE_CHECKING:
-    from collections.abc import Sequence
-
     from langchain_core.prompts.chat import ChatPromptTemplate
 
 
@@ -145,11 +144,11 @@ def merge_content(
     first_content: Union[str, list[Union[str, dict]]],
     *contents: Union[str, list[Union[str, dict]]],
 ) -> Union[str, list[Union[str, dict]]]:
-    """Merge multiple message contents.
+    """Merge two message contents.
 
     Args:
         first_content: The first content. Can be a string or a list.
-        contents: The other contents. Can be a string or a list.
+        second_content: The second content. Can be a string or a list.
 
     Returns:
         The merged content.

libs/core/langchain_core/messages/utils.py

@@ -1191,8 +1191,6 @@ def convert_to_openai_messages(
                                 },
                             }
                         )
-                    elif block.get("type") == "thinking":
-                        content.append(block)
                     else:
                         err = (
                             f"Unrecognized content block at "

libs/core/langchain_core/output_parsers/list.py

@@ -4,16 +4,14 @@ import csv
 import re
 from abc import abstractmethod
 from collections import deque
+from collections.abc import AsyncIterator, Iterator
 from io import StringIO
-from typing import TYPE_CHECKING, TypeVar, Union
 from typing import Optional as Optional
+from typing import TypeVar, Union
 
 from langchain_core.messages import BaseMessage
 from langchain_core.output_parsers.transform import BaseTransformOutputParser
 
-if TYPE_CHECKING:
-    from collections.abc import AsyncIterator, Iterator
-
 T = TypeVar("T")
 
 

libs/core/langchain_core/output_parsers/transform.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from collections.abc import AsyncIterator, Iterator
 from typing import (
     TYPE_CHECKING,
     Any,
@@ -18,8 +19,6 @@ from langchain_core.outputs import (
 from langchain_core.runnables.config import run_in_executor
 
 if TYPE_CHECKING:
-    from collections.abc import AsyncIterator, Iterator
-
     from langchain_core.runnables import RunnableConfig
 
 

libs/core/langchain_core/outputs/chat_generation.py

@@ -1,16 +1,14 @@
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Literal, Union
+from typing import Literal, Union
 
 from pydantic import model_validator
+from typing_extensions import Self
 
 from langchain_core.messages import BaseMessage, BaseMessageChunk
 from langchain_core.outputs.generation import Generation
 from langchain_core.utils._merge import merge_dicts
 
-if TYPE_CHECKING:
-    from typing_extensions import Self
-
 
 class ChatGeneration(Generation):
     """A single chat generation output.

libs/core/langchain_core/prompts/base.py

@@ -368,16 +368,16 @@ class BasePromptTemplate(
             raise NotImplementedError(msg)
 
         # Convert file to Path object.
-        save_path = Path(file_path)
+        save_path = Path(file_path) if isinstance(file_path, str) else file_path
 
         directory_path = save_path.parent
         directory_path.mkdir(parents=True, exist_ok=True)
 
         if save_path.suffix == ".json":
-            with save_path.open("w") as f:
+            with open(file_path, "w") as f:
                 json.dump(prompt_dict, f, indent=4)
         elif save_path.suffix.endswith((".yaml", ".yml")):
-            with save_path.open("w") as f:
+            with open(file_path, "w") as f:
                 yaml.dump(prompt_dict, f, default_flow_style=False)
         else:
             msg = f"{save_path} must be json or yaml"

libs/core/langchain_core/prompts/chat.py

@@ -3,9 +3,9 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
+from collections.abc import Sequence
 from pathlib import Path
 from typing import (
-    TYPE_CHECKING,
     Annotated,
     Any,
     Optional,
@@ -47,9 +47,6 @@ from langchain_core.prompts.string import (
 from langchain_core.utils import get_colored_text
 from langchain_core.utils.interactive_env import is_interactive_env
 
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
 
 class BaseMessagePromptTemplate(Serializable, ABC):
     """Base class for message prompt templates."""
@@ -599,7 +596,8 @@ class _StringImageMessagePromptTemplate(BaseMessagePromptTemplate):
         Returns:
             A new instance of this class.
         """
-        template = Path(template_file).read_text()
+        with open(str(template_file)) as f:
+            template = f.read()
         return cls.from_template(template, input_variables=input_variables, **kwargs)
 
     def format_messages(self, **kwargs: Any) -> list[BaseMessage]: