fix

This reverts commit 48ca84dcfa.

.github/DISCUSSION_TEMPLATE/q-a.yml

@@ -96,27 +96,22 @@ body:
   - type: textarea
     id: system-info
     attributes:
-      label: System Info
       description: |
-        Please share your system info with us. 
+        Please share your system info with us. Do NOT skip this step and please don't trim
+        the output. Most users don't include enough information here and it makes it harder
+        for us to help you.
         
-        "pip freeze | grep langchain" 
-        platform (windows / linux / mac)
-        python version
-        
-        OR if you're on a recent version of langchain-core you can paste the output of:
+        Run the following command in your terminal and paste the output here:
         
         python -m langchain_core.sys_info
+        
+        or if you have an existing python interpreter running:
+        
+        from langchain_core import sys_info
+        sys_info.print_sys_info()
+        
+        alternatively, put the entire output of `pip freeze` here.
       placeholder: |
-        "pip freeze | grep langchain"
-        platform
-        python version
-        
-        Alternatively, if you're on a recent version of langchain-core you can paste the output of:
-        
         python -m langchain_core.sys_info
-        
-        These will only surface LangChain packages, don't forget to include any other relevant
-        packages you're using (if you're not sure what's relevant, you can paste the entire output of `pip freeze`).
     validations:
       required: true

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -96,25 +96,21 @@ body:
     attributes:
       label: System Info
       description: |
-        Please share your system info with us. 
+        Please share your system info with us. Do NOT skip this step and please don't trim
+        the output. Most users don't include enough information here and it makes it harder
+        for us to help you.
         
-        "pip freeze | grep langchain" 
-        platform (windows / linux / mac)
-        python version
-        
-        OR if you're on a recent version of langchain-core you can paste the output of:
+        Run the following command in your terminal and paste the output here:
         
         python -m langchain_core.sys_info
+        
+        or if you have an existing python interpreter running:
+        
+        from langchain_core import sys_info
+        sys_info.print_sys_info()
+        
+        alternatively, put the entire output of `pip freeze` here.
       placeholder: |
-        "pip freeze | grep langchain"
-        platform
-        python version
-        
-        Alternatively, if you're on a recent version of langchain-core you can paste the output of:
-        
         python -m langchain_core.sys_info
-        
-        These will only surface LangChain packages, don't forget to include any other relevant
-        packages you're using (if you're not sure what's relevant, you can paste the entire output of `pip freeze`).
     validations:
       required: true

.github/scripts/check_diff.py

@@ -68,7 +68,9 @@ def dependents_graph() -> dict:
 
         # load extended deps from extended_testing_deps.txt
         package_path = Path(path).parent
-        extended_requirement_path = package_path / "extended_testing_deps.txt"
+        extended_requirement_path = (
+            package_path / "extended_dependencies" / "extended_testing_deps.txt"
+        )
         if extended_requirement_path.exists():
             with open(extended_requirement_path, "r") as f:
                 extended_deps = f.read().splitlines()

.github/scripts/get_min_versions.py

@@ -21,7 +21,14 @@ MIN_VERSION_LIBS = [
     "SQLAlchemy",
 ]
 
-SKIP_IF_PULL_REQUEST = ["langchain-core"]
+# some libs only get checked on release because of simultaneous changes in
+# multiple libs
+SKIP_IF_PULL_REQUEST = [
+    "langchain-core",
+    "langchain-text-splitters",
+    "langchain",
+    "langchain-community",
+]
 
 
 def get_min_version(version: str) -> str:
@@ -70,7 +77,7 @@ def get_min_version_from_toml(
     for lib in set(MIN_VERSION_LIBS + (include or [])):
         if versions_for == "pull_request" and lib in SKIP_IF_PULL_REQUEST:
             # some libs only get checked on release because of simultaneous
-            # changes
+            # changes in multiple libs
             continue
         # Check if the lib is present in the dependencies
         if lib in dependencies:
@@ -88,7 +95,6 @@ def get_min_version_from_toml(
                     if check_python_version(python_version, vs["python"])
                 ][0]["version"]
 
-
             # Use parse_version to get the minimum supported version from version_string
             min_version = get_min_version(version_string)
 

.github/workflows/_extended_test.yml

@@ -0,0 +1,73 @@
+name: Extended tests
+
+on:
+  workflow_dispatch:
+    inputs:
+      working-directory:
+        required: true
+        type: string
+        default: "libs/community"
+      python-version:
+        required: true
+        type: string
+        description: "Python version to use"
+        default: "3.11"
+      extended-deps-file:
+        required: true
+        type: choice
+        description: "File to install extended dependencies from"
+        options:
+          - extended_testing_deps.txt
+          - pdf_loader_deps.txt
+          - other_deps.txt
+
+env:
+  POETRY_VERSION: "1.7.1"
+
+jobs:
+  build:
+    defaults:
+      run:
+        working-directory: ${{ inputs.working-directory }}
+    runs-on: ubuntu-latest
+    name: Python ${{ inputs.python-version }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python ${{ inputs.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
+        with:
+          python-version: ${{ inputs.python-version }}
+          poetry-version: ${{ env.POETRY_VERSION }}
+          working-directory: ${{ inputs.working-directory }}
+          cache-key: core
+
+      - name: Install extended dependencies
+        shell: bash
+        run: |
+          poetry install --with test,test_integration
+          poetry run pip install uv
+          poetry run uv pip install -r extended_dependencies/${{ inputs.extended-deps-file }}
+
+      - name: Install deps outside pyproject
+        if: ${{ startsWith(inputs.working-directory, 'libs/community/') }}
+        shell: bash
+        run: poetry run pip install "boto3<2" "google-cloud-aiplatform<2"
+
+      - name: Run extended tests
+        shell: bash
+        run: |
+          make test
+          make integration_tests
+
+      - name: Ensure the tests did not create any additional files
+        shell: bash
+        run: |
+          set -eu
+
+          STATUS="$(git status)"
+          echo "$STATUS"
+
+          # grep will exit non-zero if the target message isn't found,
+          # and `set -e` above will cause the step to fail.
+          echo "$STATUS" | grep 'nothing to commit, working tree clean'

.github/workflows/_integration_test.yml

@@ -1,3 +1,6 @@
+# Ignore changes to this file. Hijacking just to allow
+# testing of workflow dispatch on new workflow off of branch.
+
 name: Integration tests
 
 on:
@@ -6,10 +9,20 @@ on:
       working-directory:
         required: true
         type: string
+        default: "libs/community"
       python-version:
         required: true
         type: string
         description: "Python version to use"
+        default: "3.11"
+      extended-deps-file:
+        required: true
+        type: choice
+        description: "File to install extended dependencies from"
+        options:
+          - extended_testing_deps.txt
+          - pdf_loader_deps.txt
+          - other_deps.txt
 
 env:
   POETRY_VERSION: "1.7.1"
@@ -32,60 +45,22 @@ jobs:
           working-directory: ${{ inputs.working-directory }}
           cache-key: core
 
-      - name: Install dependencies
+      - name: Install extended dependencies
         shell: bash
-        run: poetry install --with test,test_integration
+        run: |
+          poetry install --with test,test_integration
+          poetry run pip install uv
+          poetry run uv pip install -r extended_dependencies/${{ inputs.extended-deps-file }}
 
       - name: Install deps outside pyproject
         if: ${{ startsWith(inputs.working-directory, 'libs/community/') }}
         shell: bash
         run: poetry run pip install "boto3<2" "google-cloud-aiplatform<2"
 
-      - name: 'Authenticate to Google Cloud'
-        id: 'auth'
-        uses: google-github-actions/auth@v2
-        with:
-          credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
-
-      - name: Run integration tests
+      - name: Run extended tests
         shell: bash
-        env:
-          AI21_API_KEY: ${{ secrets.AI21_API_KEY }}
-          FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
-          GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
-          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
-          AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
-          AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}
-          AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
-          AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_CHAT_DEPLOYMENT_NAME }}
-          AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
-          AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
-          MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }}
-          TOGETHER_API_KEY: ${{ secrets.TOGETHER_API_KEY }}
-          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-          GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
-          NVIDIA_API_KEY: ${{ secrets.NVIDIA_API_KEY }}
-          GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }}
-          GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
-          HUGGINGFACEHUB_API_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
-          EXA_API_KEY: ${{ secrets.EXA_API_KEY }}
-          NOMIC_API_KEY: ${{ secrets.NOMIC_API_KEY }}
-          WATSONX_APIKEY: ${{ secrets.WATSONX_APIKEY }}
-          WATSONX_PROJECT_ID: ${{ secrets.WATSONX_PROJECT_ID }}
-          PINECONE_API_KEY: ${{ secrets.PINECONE_API_KEY }}
-          PINECONE_ENVIRONMENT: ${{ secrets.PINECONE_ENVIRONMENT }}
-          ASTRA_DB_API_ENDPOINT: ${{ secrets.ASTRA_DB_API_ENDPOINT }}
-          ASTRA_DB_APPLICATION_TOKEN: ${{ secrets.ASTRA_DB_APPLICATION_TOKEN }}
-          ASTRA_DB_KEYSPACE: ${{ secrets.ASTRA_DB_KEYSPACE }}
-          ES_URL: ${{ secrets.ES_URL }}
-          ES_CLOUD_ID: ${{ secrets.ES_CLOUD_ID }}
-          ES_API_KEY: ${{ secrets.ES_API_KEY }}
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # for airbyte
-          MONGODB_ATLAS_URI: ${{ secrets.MONGODB_ATLAS_URI }}
-          VOYAGE_API_KEY: ${{ secrets.VOYAGE_API_KEY }}
-          COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
-          UPSTAGE_API_KEY: ${{ secrets.UPSTAGE_API_KEY }}
         run: |
+          make test
           make integration_tests
 
       - name: Ensure the tests did not create any additional files

.github/workflows/_test.yml

@@ -58,7 +58,7 @@ jobs:
         env:
           MIN_VERSIONS: ${{ steps.min-version.outputs.min-versions }}
         run: |
-          poetry run pip install --force-reinstall $MIN_VERSIONS --editable .
+          poetry run pip install $MIN_VERSIONS
           make tests
         working-directory: ${{ inputs.working-directory }}
 

.github/workflows/check_diffs.yml

@@ -139,7 +139,7 @@ jobs:
           echo "Running extended tests, installing dependencies with poetry..."
           poetry install --with test
           poetry run pip install uv
-          poetry run uv pip install -r extended_testing_deps.txt
+          poetry run uv pip install -r extended_dependencies/extended_testing_deps.txt
 
       - name: Run extended tests
         run: make extended_tests

README.md

@@ -39,7 +39,7 @@ conda install langchain -c conda-forge
 For these applications, LangChain simplifies the entire application lifecycle:
 
 - **Open-source libraries**: Build your applications using LangChain's open-source [building blocks](https://python.langchain.com/v0.2/docs/concepts#langchain-expression-language-lcel), [components](https://python.langchain.com/v0.2/docs/concepts), and [third-party integrations](https://python.langchain.com/v0.2/docs/integrations/platforms/).
-  Use [LangGraph](/docs/concepts/#langgraph) to build stateful agents with first-class streaming and human-in-the-loop support.
+  Use [LangGraph](https://langchain-ai.github.io/langgraph/) to build stateful agents with first-class streaming and human-in-the-loop support.
 - **Productionization**: Inspect, monitor, and evaluate your apps with [LangSmith](https://docs.smith.langchain.com/) so that you can constantly optimize and deploy with confidence.
 - **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/).
 

docs/api_reference/templates/runnable_pydantic.rst

@@ -15,7 +15,7 @@
     :member-order: groupwise
     :show-inheritance: True
     :special-members: __call__
-    :exclude-members: construct, copy, dict, from_orm, parse_file, parse_obj, parse_raw, schema, schema_json, update_forward_refs, validate, json, is_lc_serializable, to_json_not_implemented, lc_secrets, lc_attributes, lc_id, get_lc_namespace, astream_log, transform, atransform, get_output_schema, get_prompts, config_schema, map, pick, pipe, with_listeners, with_alisteners, with_config, with_fallbacks, with_types, with_retry, InputType, OutputType, config_specs, output_schema, get_input_schema, get_graph, get_name, input_schema, name, bind, assign, as_tool, get_config_jsonschema, get_input_jsonschema, get_output_jsonschema, model_construct, model_copy, model_dump, model_dump_json, model_parametrized_name, model_post_init, model_rebuild, model_validate, model_validate_json, model_validate_strings, to_json, model_extra, model_fields_set, model_json_schema
+    :exclude-members: construct, copy, dict, from_orm, parse_file, parse_obj, parse_raw, schema, schema_json, update_forward_refs, validate, json, is_lc_serializable, to_json_not_implemented, lc_secrets, lc_attributes, lc_id, get_lc_namespace, astream_log, transform, atransform, get_output_schema, get_prompts, config_schema, map, pick, pipe, InputType, OutputType, config_specs, output_schema, get_input_schema, get_graph, get_name, input_schema, name, assign, as_tool, get_config_jsonschema, get_input_jsonschema, get_output_jsonschema, model_construct, model_copy, model_dump, model_dump_json, model_parametrized_name, model_post_init, model_rebuild, model_validate, model_validate_json, model_validate_strings, to_json, model_extra, model_fields_set, model_json_schema, predict, apredict, predict_messages, apredict_messages, generate, generate_prompt, agenerate, agenerate_prompt, call_as_llm
 
     .. NOTE:: {{objname}} implements the standard :py:class:`Runnable Interface <langchain_core.runnables.base.Runnable>`. 🏃
 

docs/docs/concepts.mdx

@@ -595,10 +595,10 @@ tool_call = ai_msg.tool_calls[0]
 # -> ToolCall(args={...}, id=..., ...)
 tool_message = tool.invoke(tool_call)
 # -> ToolMessage(
-    content="tool result foobar...",
-    tool_call_id=...,
-    name="tool_name"
-)
+#      content="tool result foobar...",
+#      tool_call_id=...,
+#      name="tool_name"
+#    )
 ```
 
 If you are invoking the tool this way and want to include an [artifact](/docs/concepts/#toolmessage) for the ToolMessage, you will need to have the tool return two things.
@@ -717,8 +717,6 @@ During run-time LangChain configures an appropriate callback manager (e.g., [Cal
 
 The `callbacks` property is available on most objects throughout the API (Models, Tools, Agents, etc.) in two different places:
 
-The callbacks are available on most objects throughout the API (Models, Tools, Agents, etc.) in two different places:
-
 - **Request time callbacks**: Passed at the time of the request in addition to the input data.
     Available on all standard `Runnable` objects. These callbacks are INHERITED by all children
     of the object they are defined on. For example, `chain.invoke({"number": 25}, {"callbacks": [handler]})`.

docs/docs/how_to/add_scores_retriever.ipynb

@@ -206,7 +206,7 @@
     "    ) -> List[Document]:\n",
     "        \"\"\"Get docs, adding score information.\"\"\"\n",
     "        docs, scores = zip(\n",
-    "            *vectorstore.similarity_search_with_score(query, **search_kwargs)\n",
+    "            *self.vectorstore.similarity_search_with_score(query, **search_kwargs)\n",
     "        )\n",
     "        for doc, score in zip(docs, scores):\n",
     "            doc.metadata[\"score\"] = score\n",

docs/docs/how_to/chat_models_universal_init.ipynb

@@ -15,43 +15,15 @@
     "\n",
     "Make sure you have the integration packages installed for any model providers you want to support. E.g. you should have `langchain-openai` installed to init an OpenAI model.\n",
     "\n",
-    ":::\n",
-    "\n",
-    ":::info Requires ``langchain >= 0.2.8``\n",
-    "\n",
-    "This functionality was added in ``langchain-core == 0.2.8``. Please make sure your package is up to date.\n",
-    "\n",
     ":::"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "165b0de6-9ae3-4e3d-aa98-4fc8a97c4a06",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2024-09-10T20:22:32.858670Z",
-     "iopub.status.busy": "2024-09-10T20:22:32.858278Z",
-     "iopub.status.idle": "2024-09-10T20:22:33.009452Z",
-     "shell.execute_reply": "2024-09-10T20:22:33.007022Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "zsh:1: 0.2.8 not found\r\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Note: you may need to restart the kernel to use updated packages.\n"
-     ]
-    }
-   ],
+   "metadata": {},
+   "outputs": [],
    "source": [
     "%pip install -qU langchain>=0.2.8 langchain-openai langchain-anthropic langchain-google-vertexai"
    ]

docs/docs/integrations/document_loaders/firecrawl.ipynb

@@ -61,7 +61,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -qU firecrawl-py langchain_community"
+    "%pip install -qU firecrawl-py==0.0.20 langchain_community"
    ]
   },
   {

docs/docs/integrations/providers/firecrawl.mdx

@@ -10,7 +10,7 @@
 Install the python SDK:
 
 ```bash
-pip install firecrawl-py
+pip install firecrawl-py==0.0.20
 ```
 
 ## Document loader

docs/docs/integrations/tools/google_search.ipynb

@@ -21,7 +21,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install --upgrade --quiet  langchain_google_community"
+    "%pip install --upgrade --quiet  langchain-google-community"
    ]
   },
   {

docs/docs/integrations/vectorstores/chroma.ipynb

@@ -99,7 +99,7 @@
     "vector_store = Chroma(\n",
     "    collection_name=\"example_collection\",\n",
     "    embedding_function=embeddings,\n",
-    "    persist_directory=\"./chroma_langchain_db\",  # Where to save data locally, remove if not neccesary\n",
+    "    persist_directory=\"./chroma_langchain_db\",  # Where to save data locally, remove if not necessary\n",
     ")"
    ]
   },
@@ -179,7 +179,7 @@
     "from langchain_core.documents import Document\n",
     "\n",
     "document_1 = Document(\n",
-    "    page_content=\"I had chocalate chip pancakes and scrambled eggs for breakfast this morning.\",\n",
+    "    page_content=\"I had chocolate chip pancakes and scrambled eggs for breakfast this morning.\",\n",
     "    metadata={\"source\": \"tweet\"},\n",
     "    id=1,\n",
     ")\n",
@@ -273,7 +273,7 @@
    "outputs": [],
    "source": [
     "updated_document_1 = Document(\n",
-    "    page_content=\"I had chocalate chip pancakes and fried eggs for breakfast this morning.\",\n",
+    "    page_content=\"I had chocolate chip pancakes and fried eggs for breakfast this morning.\",\n",
     "    metadata={\"source\": \"tweet\"},\n",
     "    id=1,\n",
     ")\n",
@@ -287,7 +287,7 @@
     "vector_store.update_document(document_id=uuids[0], document=updated_document_1)\n",
     "# You can also update multiple documents at once\n",
     "vector_store.update_documents(\n",
-    "    ids=uuids[:2], documents=[updated_document_1, updated_document_1]\n",
+    "    ids=uuids[:2], documents=[updated_document_1, updated_document_2]\n",
     ")"
    ]
   },

docs/docs/versions/v0_3/index.mdx

@@ -1,6 +1,6 @@
 # LangChain v0.3
 
-*Last updated: 09.13.24*
+*Last updated: 09.16.24*
 
 ## What's changed
 
@@ -23,7 +23,7 @@ The following features have been added during the development of 0.2.x:
 
 ## How to update your code
 
-If you're using `langchain` / `langchain-community` / `langchain-core` 0.0 or 0.1, we recommend that you first [upgrade to 0.2](https://python.langchain.com/v0.2/docs/versions/v0_2/). The `langchain-cli` will help you to migrate many imports automatically.
+If you're using `langchain` / `langchain-community` / `langchain-core` 0.0 or 0.1, we recommend that you first [upgrade to 0.2](https://python.langchain.com/v0.2/docs/versions/v0_2/).
 
 If you're using `langgraph`, upgrade to `langgraph>=0.2.20,<0.3`. This will work with either 0.2 or 0.3 versions of all the base packages.
 
@@ -31,22 +31,27 @@ Here is a complete list of all packages that have been released and what we reco
 Any package that now requires `langchain-core` 0.3 had a minor version bump.
 Any package that is now compatible with both `langchain-core` 0.2 and 0.3 had a patch version bump.
 
+You can use the `langchain-cli` to update deprecated imports automatically.
+The CLI will handle updating deprecated imports that were introduced in LangChain 0.0.x and LangChain 0.1, as
+well as updating the `langchain_core.pydantic_v1` and `langchain.pydantic_v1` imports.
+
+
 ### Base packages
 
-| Package                                | Latest  | Recommended constraint     |
-| -------------------------------------- | ------- | -------------------------- |
-| langchain                              | 0.3.0   | >=0.3,<0.4                 |
-| langchain-community                    | 0.3.0   | >=0.3,<0.4                 |
-| langchain-text-splitters               | 0.3.0   | >=0.3,<0.4                 |
-| langchain-core                         | 0.3.0   | >=0.3,<0.4                 |
-| langchain-experimental                 | 0.3.0   | >=0.3,<0.4                 |
+| Package                  | Latest | Recommended constraint |
+|--------------------------|--------|------------------------|
+| langchain                | 0.3.0  | >=0.3,<0.4             |
+| langchain-community      | 0.3.0  | >=0.3,<0.4             |
+| langchain-text-splitters | 0.3.0  | >=0.3,<0.4             |
+| langchain-core           | 0.3.0  | >=0.3,<0.4             |
+| langchain-experimental   | 0.3.0  | >=0.3,<0.4             |
 
 ### Downstream packages
 
-| Package                                | Latest  | Recommended constraint     |
-| -------------------------------------- | ------- | -------------------------- |
-| langgraph                              | 0.2.20  | >=0.2.20,<0.3              |
-| langserve                              | 0.3.0   | >=0.3,<0.4                 |
+| Package   | Latest | Recommended constraint |
+|-----------|--------|------------------------|
+| langgraph | 0.2.20 | >=0.2.20,<0.3          |
+| langserve | 0.3.0  | >=0.3,<0.4             |
 
 ### Integration packages
 
@@ -59,7 +64,7 @@ Any package that is now compatible with both `langchain-core` 0.2 and 0.3 had a
 | langchain-azure-dynamic-sessions       | 0.2.0   | >=0.2,<0.3                 |
 | langchain-box                          | 0.2.0   | >=0.2,<0.3                 |
 | langchain-chroma                       | 0.1.4   | >=0.1.4,<0.2               |
-| langchain-cohere                       | 0.2.0   | >=0.2,<0.3                 |
+| langchain-cohere                       | 0.3.0   | >=0.3,<0.4                 |
 | langchain-elasticsearch                | 0.3.0   | >=0.3,<0.4                 |
 | langchain-exa                          | 0.2.0   | >=0.2,<0.3                 |
 | langchain-fireworks                    | 0.2.0   | >=0.2,<0.3                 |
@@ -68,6 +73,7 @@ Any package that is now compatible with both `langchain-core` 0.2 and 0.3 had a
 | langchain-google-genai                 | 2.0.0   | >=2,<3                     |
 | langchain-google-vertexai              | 2.0.0   | >=2,<3                     |
 | langchain-huggingface                  | 0.1.0   | >=0.1,<0.2                 |
+| langchain-ibm                          | 0.2.0   | >=0.2,<0.3                 |
 | langchain-milvus                       | 0.1.6   | >=0.1.6,<0.2               |
 | langchain-mistralai                    | 0.2.0   | >=0.2,<0.3                 |
 | langchain-mongodb                      | 0.2.0   | >=0.2,<0.3                 |
@@ -77,12 +83,14 @@ Any package that is now compatible with both `langchain-core` 0.2 and 0.3 had a
 | langchain-pinecone                     | 0.2.0   | >=0.2,<0.3                 |
 | langchain-postgres                     | 0.0.13  | >=0.0.13,<0.1              |
 | langchain-prompty                      | 0.1.0   | >=0.1,<0.2                 |
+| langchain-qdrant                       | 0.1.4   | >=0.1.4,<0.2               |
 | langchain-redis                        | 0.1.0   | >=0.1,<0.2                 |
-| langchain-qdrant                       | 0.2.0   | >=0.2,<0.3                 |
+| langchain-sema4                        | 0.2.0   | >=0.2,<0.3                 |
 | langchain-together                     | 0.2.0   | >=0.2,<0.3                 |
 | langchain-unstructured                 | 0.1.4   | >=0.1.4,<0.2               |
+| langchain-upstage                      | 0.3.0   | >=0.3,<0.4                 |
 | langchain-voyageai                     | 0.2.0   | >=0.2,<0.3                 |
-| langchain-weaviate                     | 0.1.0   | >=0.1,<0.2                 |
+| langchain-weaviate                     | 0.0.3   | >=0.0.3,<0.1               |
 
 Once you've updated to recent versions of the packages, you may need to address the following issues stemming from the internal switch from Pydantic v1 to Pydantic v2:
 
@@ -185,6 +193,8 @@ CustomTool(
 When sub-classing from LangChain models, users may need to add relevant imports
 to the file and rebuild the model.
 
+You can read more about `model_rebuild` [here](https://docs.pydantic.dev/latest/concepts/models/#rebuilding-model-schema).
+
 ```python
 from langchain_core.output_parsers import BaseOutputParser
 
@@ -205,3 +215,57 @@ class FooParser(BaseOutputParser):
 
 FooParser.model_rebuild()
 ```
+
+## Migrate using langchain-cli
+
+The `langchain-cli` can help update deprecated LangChain imports in your code automatically.
+
+Please note that the `langchain-cli` only handles deprecated LangChain imports and cannot
+help to upgrade your code from pydantic 1 to pydantic 2.
+
+For help with the Pydantic 1 to 2 migration itself please refer to the [Pydantic Migration Guidelines](https://docs.pydantic.dev/latest/migration/).
+
+As of 0.0.31, the `langchain-cli` relies on [gritql](https://about.grit.io/) for applying code mods.
+
+### Installation
+
+```bash
+pip install -U langchain-cli
+langchain-cli --version # <-- Make sure the version is at least 0.0.31
+```
+
+### Usage
+
+Given that the migration script is not perfect, you should make sure you have a backup of your code first (e.g., using version control like `git`).
+
+The `langchain-cli` will handle the `langchain_core.pydantic_v1` deprecation introduced in LangChain 0.3 as well
+as older deprecations (e.g.,`from langchain.chat_models import ChatOpenAI` which should be `from langchain_openai import ChatOpenAI`),
+
+You will need to run the migration script **twice** as it only applies one import replacement per run.
+
+For example, say that your code is still using the old import `from langchain.chat_models import ChatOpenAI`:
+
+After the first run, you’ll get: `from langchain_community.chat_models import ChatOpenAI`
+After the second run, you’ll get: `from langchain_openai import ChatOpenAI`
+
+```bash
+# Run a first time
+# Will replace from langchain.chat_models import ChatOpenAI
+langchain-cli migrate --help [path to code] # Help
+langchain-cli migrate [path to code] # Apply
+
+# Run a second time to apply more import replacements
+langchain-cli migrate --diff [path to code] # Preview
+langchain-cli migrate [path to code] # Apply
+```
+
+### Other options
+
+```bash
+# See help menu
+langchain-cli migrate --help
+# Preview Changes without applying
+langchain-cli migrate --diff [path to code]
+# Approve changes interactively
+langchain-cli migrate --interactive [path to code]
+```

docs/docusaurus.config.js

@@ -330,7 +330,7 @@ const config = {
         // this is linked to erick@langchain.dev currently
         apiKey: "6c01842d6a88772ed2236b9c85806441",
 
-        indexName: "python-langchain-0.2",
+        indexName: "python-langchain-latest",
 
         contextualSearch: false,
       },

docs/src/theme/NotFound.js

@@ -2538,5 +2538,389 @@ const suggestedLinks = {
     "alternative": [
       "/v0.1/docs/use_cases/web_scraping/"
     ]
+  },
+  // below are new
+  "/docs/modules/data_connection/document_transformers/text_splitters/": {"canonical": "/docs/how_to/#text-splitters", "alternative": ["/v0.1/docs/modules/data_connection/document_transformers/"]},
+  "/docs/modules/data_connection/document_transformers/text_splitters/character_text_splitter/": {"canonical": "/docs/how_to/character_text_splitter/", "alternative": ["/v0.1/docs/modules/data_connection/document_transformers/character_text_splitter/"]},
+  "/docs/modules/data_connection/document_transformers/text_splitters/code_splitter/": {"canonical": "/docs/how_to/code_splitter/", "alternative": ["/v0.1/docs/modules/data_connection/document_transformers/code_splitter/"]},
+  "/docs/modules/data_connection/document_transformers/text_splitters/HTML_header_metadata/": {"canonical": "/docs/how_to/HTML_header_metadata_splitter/", "alternative": ["/v0.1/docs/modules/data_connection/document_transformers/HTML_header_metadata/"]},
+  "/docs/modules/data_connection/document_transformers/text_splitters/HTML_section_aware_splitter/": {"canonical": "/docs/how_to/HTML_section_aware_splitter/", "alternative": ["/v0.1/docs/modules/data_connection/document_transformers/HTML_section_aware_splitter/"]},
+  "/docs/modules/data_connection/document_transformers/text_splitters/markdown_header_metadata/": {"canonical": "/docs/how_to/markdown_header_metadata_splitter/", "alternative": ["/v0.1/docs/modules/data_connection/document_transformers/markdown_header_metadata/"]},
+  "/docs/modules/data_connection/document_transformers/text_splitters/recursive_json_splitter/": {"canonical": "/docs/how_to/recursive_json_splitter/", "alternative": ["/v0.1/docs/modules/data_connection/document_transformers/recursive_json_splitter/"]},
+  "/docs/modules/data_connection/document_transformers/text_splitters/recursive_text_splitter/": {"canonical": "/docs/how_to/recursive_text_splitter/", "alternative": ["/v0.1/docs/modules/data_connection/document_transformers/recursive_text_splitter/"]},
+  "/docs/modules/data_connection/document_transformers/text_splitters/semantic-chunker/": {"canonical": "/docs/how_to/semantic-chunker/", "alternative": ["/v0.1/docs/modules/data_connection/document_transformers/semantic-chunker/"]},
+  "/docs/modules/data_connection/document_transformers/text_splitters/split_by_token/": {"canonical": "/docs/how_to/split_by_token/", "alternative": ["/v0.1/docs/modules/data_connection/document_transformers/split_by_token/"]},
+  "/docs/modules/model_io/prompts/prompt_templates/": {"canonical": "/docs/how_to/#prompt-templates", "alternative": ["/v0.1/docs/modules/model_io/prompts/"]},
+  "/docs/modules/model_io/prompts/prompt_templates/composition/": {"canonical": "/docs/how_to/prompts_composition/", "alternative": ["/v0.1/docs/modules/model_io/prompts/composition/"]},
+  "/docs/modules/model_io/prompts/prompt_templates/example_selectors/": {"canonical": "/docs/how_to/example_selectors/", "alternative": ["/v0.1/docs/modules/model_io/prompts/example_selectors/"]},
+  "/docs/modules/model_io/prompts/prompt_templates/example_selectors/length_based/": {"canonical": "/docs/how_to/example_selectors_length_based/", "alternative": ["/v0.1/docs/modules/model_io/prompts/example_selectors/length_based/"]},
+  "/docs/modules/model_io/prompts/prompt_templates/example_selectors/mmr/": {"canonical": "/docs/how_to/example_selectors_mmr/", "alternative": ["/v0.1/docs/modules/model_io/prompts/example_selectors/mmr/"]},
+  "/docs/modules/model_io/prompts/prompt_templates/example_selectors/ngram_overlap/": {"canonical": "/docs/how_to/example_selectors_ngram/", "alternative": ["/v0.1/docs/modules/model_io/prompts/example_selectors/ngram_overlap/"]},
+  "/docs/modules/model_io/prompts/prompt_templates/example_selectors/similarity/": {"canonical": "/docs/how_to/example_selectors_similarity/", "alternative": ["/v0.1/docs/modules/model_io/prompts/example_selectors/similarity/"]},
+  "/docs/modules/model_io/prompts/prompt_templates/few_shot_examples_chat/": {"canonical": "/docs/how_to/few_shot_examples_chat/", "alternative": ["/v0.1/docs/modules/model_io/prompts/few_shot_examples_chat/"]},
+  "/docs/modules/model_io/prompts/prompt_templates/few_shot_examples/": {"canonical": "/docs/how_to/few_shot_examples/", "alternative": ["/v0.1/docs/modules/model_io/prompts/few_shot_examples/"]},
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+  "/docs/modules/model_io/models/": {"canonical": "/docs/how_to/#chat-models", "alternative": ["/v0.1/docs/modules/model_io/"]},
+  "/docs/modules/model_io/models/chat/": {"canonical": "/docs/how_to/#chat-models", "alternative": ["/v0.1/docs/modules/model_io/chat/"]},
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+  "/docs/modules/model_io/models/chat/logprobs/": {"canonical": "/docs/how_to/logprobs/", "alternative": ["/v0.1/docs/modules/model_io/chat/logprobs/"]},
+  "/docs/modules/model_io/models/chat/message_types/": {"canonical": "/docs/concepts/#messages", "alternative": ["/v0.1/docs/modules/model_io/chat/message_types/"]},
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+  "/docs/modules/model_io/models/llms/custom_llm/": {"canonical": "/docs/how_to/custom_llm/", "alternative": ["/v0.1/docs/modules/model_io/llms/custom_llm/"]},
+  "/docs/modules/model_io/models/llms/llm_caching/": {"canonical": "/docs/how_to/llm_caching/", "alternative": ["/v0.1/docs/modules/model_io/llms/llm_caching/"]},
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+  "/docs/modules/model_io/models/llms/token_usage_tracking/": {"canonical": "/docs/how_to/llm_token_usage_tracking/", "alternative": ["/v0.1/docs/modules/model_io/llms/token_usage_tracking/"]},
+  "/docs/modules/model_io/models/output_parsers/": {"canonical": "/docs/how_to/#output-parsers", "alternative": ["/v0.1/docs/modules/model_io/output_parsers/"]},
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+  "/docs/contributing/packages/": {"canonical": "/docs/versions/release_policy/", "alternative": ["/v0.1/docs/packages/"]},
+  "/docs/community/": {"canonical": "/docs/contributing/"},
+  "/docs/modules/chains/(.+)/": {"canonical": "/docs/versions/migrating_chains/", "alternative": ["/v0.1/docs/modules/chains/"]},
+  "/docs/modules/agents/how_to/custom_llm_agent/": {"canonical": "/docs/how_to/migrate_agent/", "alternative": ["/v0.1/docs/modules/agents/how_to/custom_agent/"]},
+  "/docs/modules/agents/how_to/custom-functions-with-openai-functions-agent/": {"canonical": "/docs/how_to/migrate_agent/", "alternative": ["/v0.1/docs/modules/agents/how_to/custom_agent/"]},
+  "/docs/modules/agents/how_to/custom_llm_chat_agent/": {"canonical": "/docs/how_to/migrate_agent/", "alternative": ["/v0.1/docs/modules/agents/how_to/custom_agent/"]},
+  "/docs/modules/agents/how_to/custom_mrkl_agent/": {"canonical": "/docs/how_to/migrate_agent/", "alternative": ["/v0.1/docs/modules/agents/how_to/custom_agent/"]},
+  "/docs/modules/agents/how_to/streaming_stdout_final_only/": {"canonical": "/docs/how_to/migrate_agent/", "alternative": ["/v0.1/docs/modules/agents/how_to/streaming/"]},
+  "/docs/modules/model_io/prompts/prompts_pipelining/": {"canonical": "/docs/how_to/prompts_composition/", "alternative": ["/v0.1/docs/modules/model_io/prompts/composition/"]},
+  "/docs/modules/model_io/output_parsers/enum/": {"canonical": "/docs/how_to/output_parser_structured/", "alternative": ["/v0.1/docs/modules/model_io/output_parsers/types/enum/"]},
+  "/docs/modules/model_io/output_parsers/pandas_dataframe/": {"canonical": "/docs/how_to/output_parser_structured/", "alternative": ["/v0.1/docs/modules/model_io/output_parsers/types/pandas_dataframe/"]},
+  "/docs/modules/model_io/output_parsers/structured/": {"canonical": "/docs/how_to/output_parser_structured/", "alternative": ["/v0.1/docs/modules/model_io/output_parsers/types/structured/"]},
+  "/docs/modules/model_io/output_parsers/xml/": {"canonical": "/docs/how_to/output_parser_xml/", "alternative": ["/v0.1/docs/modules/model_io/output_parsers/types/xml/"]},
+  "/docs/use_cases/question_answering/code_understanding/": {"canonical": "https://langchain-ai.github.io/langgraph/tutorials/code_assistant/langgraph_code_assistant/", "alternative": ["/v0.1/docs/use_cases/code_understanding/"]},
+  "/docs/use_cases/question_answering/document-context-aware-QA/": {"canonical": "/docs/how_to/#text-splitters", "alternative": ["/v0.1/docs/modules/data_connection/document_transformers/"]},
+  "/docs/integrations/providers/alibabacloud_opensearch/": {"canonical": "/docs/integrations/providers/alibaba_cloud/"},
+  "/docs/integrations/chat/pai_eas_chat_endpoint/": {"canonical": "/docs/integrations/chat/alibaba_cloud_pai_eas/"},
+  "/docs/integrations/providers/tencentvectordb/": {"canonical": "/docs/integrations/providers/tencent/"},
+  "/docs/integrations/chat/hunyuan/": {"canonical": "/docs/integrations/chat/tencent_hunyuan/"},
+  "/docs/integrations/document_loaders/excel/": {"canonical": "/docs/integrations/document_loaders/microsoft_excel/"},
+  "/docs/integrations/document_loaders/onenote/": {"canonical": "/docs/integrations/document_loaders/microsoft_onenote/"},
+  "/docs/integrations/providers/aws_dynamodb/": {"canonical": "/docs/integrations/platforms/aws/"},
+  "/docs/integrations/providers/scann/": {"canonical": "/docs/integrations/platforms/google/"},
+  "/docs/integrations/toolkits/google_drive/": {"canonical": "/docs/integrations/tools/google_drive/"},
+  "/docs/use_cases/question_answering/chat_vector_db/": {"canonical": "/docs/tutorials/rag/", "alternative": ["/v0.1/docs/use_cases/question_answering/"]},
+  "/docs/use_cases/question_answering/in_memory_question_answering/": {"canonical": "/docs/tutorials/rag/", "alternative": ["/v0.1/docs/use_cases/question_answering/"]},
+  "/docs/use_cases/question_answering/multi_retrieval_qa_router/": {"canonical": "/docs/tutorials/rag/", "alternative": ["/v0.1/docs/use_cases/question_answering/"]},
+  "/docs/use_cases/question_answering/multiple_retrieval/": {"canonical": "/docs/tutorials/rag/", "alternative": ["/v0.1/docs/use_cases/question_answering/"]},
+  "/docs/use_cases/question_answering/vector_db_qa/": {"canonical": "/docs/tutorials/rag/", "alternative": ["/v0.1/docs/use_cases/question_answering/"]},
+  "/docs/use_cases/question_answering/vector_db_text_generation/": {"canonical": "/docs/tutorials/rag/", "alternative": ["/v0.1/docs/use_cases/question_answering/"]},
+  "/docs/guides/langsmith/": {"canonical": "https://docs.smith.langchain.com/", "alternative": ["/v0.1/docs/langsmith/"]},
+  "/docs/guides/langsmith/walkthrough/": {"canonical": "https://docs.smith.langchain.com/", "alternative": ["/v0.1/docs/langsmith/walkthrough/"]},
+  "/docs/use_cases/qa_structured/integrations/sqlite/": {"canonical": "/docs/tutorials/sql_qa/", "alternative": ["/v0.1/docs/use_cases/sql/"]},
+  "/docs/use_cases/more/data_generation/": {"canonical": "/docs/tutorials/data_generation/", "alternative": ["/v0.1/docs/use_cases/data_generation/"]},
+  "/docs/use_cases/question_answering/how_to/chat_vector_db/": {"canonical": "/docs/tutorials/rag/", "alternative": ["/v0.1/docs/use_cases/question_answering/"]},
+  "/docs/use_cases/question_answering/how_to/conversational_retrieval_agents/": {"canonical": "/docs/tutorials/qa_chat_history/", "alternative": ["/v0.1/docs/use_cases/question_answering/conversational_retrieval_agents/"]},
+  "/docs/use_cases/question_answering/question_answering/": {"canonical": "/docs/tutorials/rag/", "alternative": ["/v0.1/docs/use_cases/question_answering/"]},
+  "/docs/use_cases/question_answering/how_to/local_retrieval_qa/": {"canonical": "/docs/tutorials/rag/", "alternative": ["/v0.1/docs/use_cases/question_answering/local_retrieval_qa/"]},
+  "/docs/use_cases/question_answering/how_to/question_answering/": {"canonical": "/docs/tutorials/rag/", "alternative": ["/v0.1/docs/use_cases/question_answering/"]},
+  "/docs/modules/agents/agents/examples/mrkl_chat(.html?)/": {"canonical": "/docs/how_to/#agents", "alternative": ["/v0.1/docs/modules/agents/"]},
+  "/docs/integrations/": {"canonical": "/docs/integrations/providers/"},
+  "/docs/expression_language/cookbook/routing/": {"canonical": "/docs/how_to/routing/", "alternative": ["/v0.1/docs/expression_language/how_to/routing/"]},
+  "/docs/guides/expression_language/": {"canonical": "/docs/how_to/#langchain-expression-language-lcel", "alternative": ["/v0.1/docs/expression_language/"]},
+  "/docs/integrations/providers/amazon_api_gateway/": {"canonical": "/docs/integrations/platforms/aws/"},
+  "/docs/integrations/providers/huggingface/": {"canonical": "/docs/integrations/platforms/huggingface/"},
+  "/docs/integrations/providers/azure_blob_storage/": {"canonical": "/docs/integrations/platforms/microsoft/"},
+  "/docs/integrations/providers/google_vertexai_matchingengine/": {"canonical": "/docs/integrations/platforms/google/"},
+  "/docs/integrations/providers/aws_s3/": {"canonical": "/docs/integrations/platforms/aws/"},
+  "/docs/integrations/providers/azure_openai/": {"canonical": "/docs/integrations/platforms/microsoft/"},
+  "/docs/integrations/providers/azure_cognitive_search_/": {"canonical": "/docs/integrations/platforms/microsoft/"},
+  "/docs/integrations/providers/bedrock/": {"canonical": "/docs/integrations/platforms/aws/"},
+  "/docs/integrations/providers/google_bigquery/": {"canonical": "/docs/integrations/platforms/google/"},
+  "/docs/integrations/providers/google_cloud_storage/": {"canonical": "/docs/integrations/platforms/google/"},
+  "/docs/integrations/providers/google_drive/": {"canonical": "/docs/integrations/platforms/google/"},
+  "/docs/integrations/providers/google_search/": {"canonical": "/docs/integrations/platforms/google/"},
+  "/docs/integrations/providers/microsoft_onedrive/": {"canonical": "/docs/integrations/platforms/microsoft/"},
+  "/docs/integrations/providers/microsoft_powerpoint/": {"canonical": "/docs/integrations/platforms/microsoft/"},
+  "/docs/integrations/providers/microsoft_word/": {"canonical": "/docs/integrations/platforms/microsoft/"},
+  "/docs/integrations/providers/sagemaker_endpoint/": {"canonical": "/docs/integrations/platforms/aws/"},
+  "/docs/integrations/providers/sagemaker_tracking/": {"canonical": "/docs/integrations/callbacks/sagemaker_tracking/"},
+  "/docs/integrations/providers/openai/": {"canonical": "/docs/integrations/platforms/openai/"},
+  "/docs/integrations/cassandra/": {"canonical": "/docs/integrations/providers/cassandra/"},
+  "/docs/integrations/providers/providers/semadb/": {"canonical": "/docs/integrations/providers/semadb/"},
+  "/docs/integrations/vectorstores/vectorstores/semadb/": {"canonical": "/docs/integrations/vectorstores/semadb/"},
+  "/docs/integrations/vectorstores/async_faiss/": {"canonical": "/docs/integrations/vectorstores/faiss_async/"},
+  "/docs/integrations/vectorstores/matchingengine/": {"canonical": "/docs/integrations/vectorstores/google_vertex_ai_vector_search/"},
+  "/docs/integrations/tools/sqlite/": {"canonical": "/docs/tutorials/sql_qa/", "alternative": ["/v0.1/docs/use_cases/sql/"]},
+  "/docs/integrations/document_loaders/pdf-amazonTextractPDFLoader/": {"canonical": "/docs/integrations/document_loaders/amazon_textract/"},
+  "/docs/integrations/document_loaders/Etherscan/": {"canonical": "/docs/integrations/document_loaders/etherscan/"},
+  "/docs/integrations/document_loaders/merge_doc_loader/": {"canonical": "/docs/integrations/document_loaders/merge_doc/"},
+  "/docs/integrations/document_loaders/recursive_url_loader/": {"canonical": "/docs/integrations/document_loaders/recursive_url/"},
+  "/docs/integrations/providers/google_document_ai/": {"canonical": "/docs/integrations/platforms/google/"},
+  "/docs/integrations/memory/motorhead_memory_managed/": {"canonical": "/docs/integrations/memory/motorhead_memory/"},
+  "/docs/integrations/memory/dynamodb_chat_message_history/": {"canonical": "/docs/integrations/memory/aws_dynamodb/"},
+  "/docs/integrations/memory/entity_memory_with_sqlite/": {"canonical": "/docs/integrations/memory/sqlite/"},
+  "/docs/modules/model_io/chat/integrations/anthropic/": {"canonical": "/docs/integrations/chat/anthropic/"},
+  "/docs/modules/model_io/chat/integrations/azure_chat_openai/": {"canonical": "/docs/integrations/chat/azure_chat_openai/"},
+  "/docs/modules/model_io/chat/integrations/google_vertex_ai_palm/": {"canonical": "/docs/integrations/chat/google_vertex_ai_palm/"},
+  "/docs/modules/model_io/chat/integrations/openai/": {"canonical": "/docs/integrations/chat/openai/"},
+  "/docs/modules/model_io/chat/integrations/promptlayer_chatopenai/": {"canonical": "/docs/integrations/chat/promptlayer_chatopenai/"},
+  "/docs/modules/model_io/llms/integrations/ai21/": {"canonical": "/docs/integrations/llms/ai21/"},
+  "/docs/modules/model_io/llms/integrations/aleph_alpha/": {"canonical": "/docs/integrations/llms/aleph_alpha/"},
+  "/docs/modules/model_io/llms/integrations/anyscale/": {"canonical": "/docs/integrations/llms/anyscale/"},
+  "/docs/modules/model_io/llms/integrations/banana/": {"canonical": "/docs/integrations/llms/banana/"},
+  "/docs/modules/model_io/llms/integrations/baseten/": {"canonical": "/docs/integrations/llms/baseten/"},
+  "/docs/modules/model_io/llms/integrations/beam/": {"canonical": "/docs/integrations/llms/beam/"},
+  "/docs/modules/model_io/llms/integrations/bedrock/": {"canonical": "/docs/integrations/llms/bedrock/"},
+  "/docs/modules/model_io/llms/integrations/cohere/": {"canonical": "/docs/integrations/llms/cohere/"},
+  "/docs/modules/model_io/llms/integrations/ctransformers/": {"canonical": "/docs/integrations/llms/ctransformers/"},
+  "/docs/modules/model_io/llms/integrations/databricks/": {"canonical": "/docs/integrations/llms/databricks/"},
+  "/docs/modules/model_io/llms/integrations/google_vertex_ai_palm/": {"canonical": "/docs/integrations/llms/google_vertex_ai_palm/"},
+  "/docs/modules/model_io/llms/integrations/huggingface_pipelines/": {"canonical": "/docs/integrations/llms/huggingface_pipelines/"},
+  "/docs/modules/model_io/llms/integrations/jsonformer_experimental/": {"canonical": "/docs/integrations/llms/jsonformer_experimental/"},
+  "/docs/modules/model_io/llms/integrations/llamacpp/": {"canonical": "/docs/integrations/llms/llamacpp/"},
+  "/docs/modules/model_io/llms/integrations/manifest/": {"canonical": "/docs/integrations/llms/manifest/"},
+  "/docs/modules/model_io/llms/integrations/modal/": {"canonical": "/docs/integrations/llms/modal/"},
+  "/docs/modules/model_io/llms/integrations/mosaicml/": {"canonical": "/docs/integrations/llms/mosaicml/"},
+  "/docs/modules/model_io/llms/integrations/nlpcloud/": {"canonical": "/docs/integrations/llms/nlpcloud/"},
+  "/docs/modules/model_io/llms/integrations/openai/": {"canonical": "/docs/integrations/llms/openai/"},
+  "/docs/modules/model_io/llms/integrations/openlm/": {"canonical": "/docs/integrations/llms/openlm/"},
+  "/docs/modules/model_io/llms/integrations/predictionguard/": {"canonical": "/docs/integrations/llms/predictionguard/"},
+  "/docs/modules/model_io/llms/integrations/promptlayer_openai/": {"canonical": "/docs/integrations/llms/promptlayer_openai/"},
+  "/docs/modules/model_io/llms/integrations/rellm_experimental/": {"canonical": "/docs/integrations/llms/rellm_experimental/"},
+  "/docs/modules/model_io/llms/integrations/replicate/": {"canonical": "/docs/integrations/llms/replicate/"},
+  "/docs/modules/model_io/llms/integrations/runhouse/": {"canonical": "/docs/integrations/llms/runhouse/"},
+  "/docs/modules/model_io/llms/integrations/sagemaker/": {"canonical": "/docs/integrations/llms/sagemaker/"},
+  "/docs/modules/model_io/llms/integrations/stochasticai/": {"canonical": "/docs/integrations/llms/stochasticai/"},
+  "/docs/modules/model_io/llms/integrations/writer/": {"canonical": "/docs/integrations/llms/writer/"},
+  "/en/latest/use_cases/apis.html/": {"canonical": null, "alternative": ["/v0.1/docs/use_cases/apis/"]},
+  "/en/latest/use_cases/extraction.html/": {"canonical": "/docs/tutorials/extraction/", "alternative": ["/v0.1/docs/use_cases/extraction/"]},
+  "/en/latest/use_cases/summarization.html/": {"canonical": "/docs/tutorials/summarization/", "alternative": ["/v0.1/docs/use_cases/summarization/"]},
+  "/en/latest/use_cases/tabular.html/": {"canonical": "/docs/tutorials/sql_qa/", "alternative": ["/v0.1/docs/use_cases/sql/"]},
+  "/en/latest/youtube.html/": {"canonical": "/docs/additional_resources/youtube/"},
+  "/docs/": {"canonical": "/"},
+  "/en/latest/": {"canonical": "/"},
+  "/en/latest/index.html/": {"canonical": "/"},
+  "/en/latest/modules/models.html/": {"canonical": "/docs/how_to/#chat-models", "alternative": ["/v0.1/docs/modules/model_io/"]},
+  "/docs/integrations/retrievers/google_cloud_enterprise_search/": {"canonical": "/docs/integrations/retrievers/google_vertex_ai_search/"},
+  "/docs/integrations/tools/metaphor_search/": {"canonical": "/docs/integrations/tools/exa_search/"},
+  "/docs/expression_language/how_to/fallbacks/": {"canonical": "https://docs.smith.langchain.com/", "alternative": ["/v0.1/docs/guides/productionization/fallbacks/"]},
+  "/docs/expression_language/cookbook/retrieval/": {"canonical": "/docs/tutorials/rag/", "alternative": ["/v0.1/docs/use_cases/question_answering/"]},
+  "/docs/expression_language/cookbook/agent/": {"canonical": "/docs/how_to/migrate_agent/", "alternative": ["/v0.1/docs/modules/agents/agent_types/xml_agent/"]},
+  "/docs/modules/model_io/prompts/message_prompts/": {"canonical": "/docs/how_to/#prompt-templates", "alternative": ["/v0.1/docs/modules/model_io/prompts/quick_start/"]},
+  "/docs/modules/model_io/prompts/pipeline/": {"canonical": "/docs/how_to/prompts_composition/", "alternative": ["/v0.1/docs/modules/model_io/prompts/composition/"]},
+  "/docs/expression_language/cookbook/memory/": {"canonical": "/docs/how_to/chatbots_memory/", "alternative": ["/v0.1/docs/modules/memory/"]},
+  "/docs/expression_language/cookbook/tools/": {"canonical": "/docs/tutorials/agents/", "alternative": ["/v0.1/docs/use_cases/tool_use/quickstart/"]},
+  "/docs/expression_language/cookbook/sql_db/": {"canonical": "/docs/tutorials/sql_qa/", "alternative": ["/v0.1/docs/use_cases/sql/quickstart/"]},
+  "/docs/expression_language/cookbook/moderation/": {"canonical": "https://docs.smith.langchain.com/", "alternative": ["/v0.1/docs/guides/productionization/safety/moderation/"]},
+  "/docs/expression_language/cookbook/embedding_router/": {"canonical": "/docs/how_to/routing/", "alternative": ["/v0.1/docs/expression_language/how_to/routing/"]},
+  "/docs/guides/structured_output/": {"canonical": "/docs/how_to/structured_output/", "alternative": ["/v0.1/docs/modules/model_io/chat/structured_output/"]},
+  "/docs/modules/agents/how_to/structured_tools/": {"canonical": "/docs/how_to/#tools", "alternative": ["/v0.1/docs/modules/tools/"]},
+  "/docs/use_cases/csv/": {"canonical": "/docs/tutorials/sql_qa/", "alternative": ["/v0.1/docs/use_cases/sql/csv/"]},
+  "/docs/guides/debugging/": {"canonical": "/docs/how_to/debugging/", "alternative": ["/v0.1/docs/guides/development/debugging/"]},
+  "/docs/guides/extending_langchain/": {"canonical": "/docs/how_to/#custom", "alternative": ["/v0.1/docs/guides/development/extending_langchain/"]},
+  "/docs/guides/fallbacks/": {"canonical": "https://docs.smith.langchain.com/", "alternative": ["/v0.1/docs/guides/productionization/fallbacks/"]},
+  "/docs/guides/model_laboratory/": {"canonical": "https://docs.smith.langchain.com/", "alternative": ["/v0.1/docs/guides/productionization/evaluation/"]},
+  "/docs/guides/pydantic_compatibility/": {"canonical": "/docs/how_to/pydantic_compatibility/", "alternative": ["/v0.1/docs/guides/development/pydantic_compatibility/"]},
+  "/docs/guides/local_llms/": {"canonical": "/docs/how_to/local_llms/", "alternative": ["/v0.1/docs/guides/development/local_llms/"]},
+  "/docs/modules/model_io/quick_start/": {"canonical": "/docs/how_to/#chat-models", "alternative": ["/v0.1/docs/modules/model_io/"]},
+  "/docs/expression_language/how_to/generators/": {"canonical": "/docs/how_to/functions/", "alternative": ["/v0.1/docs/expression_language/primitives/functions/"]},
+  "/docs/expression_language/how_to/functions/": {"canonical": "/docs/how_to/functions/", "alternative": ["/v0.1/docs/expression_language/primitives/functions/"]},
+  "/docs/expression_language/how_to/passthrough/": {"canonical": "/docs/how_to/passthrough/", "alternative": ["/v0.1/docs/expression_language/primitives/passthrough/"]},
+  "/docs/expression_language/how_to/map/": {"canonical": "/docs/how_to/parallel/", "alternative": ["/v0.1/docs/expression_language/primitives/parallel/"]},
+  "/docs/expression_language/how_to/binding/": {"canonical": "/docs/how_to/binding/", "alternative": ["/v0.1/docs/expression_language/primitives/binding/"]},
+  "/docs/expression_language/how_to/configure/": {"canonical": "/docs/how_to/configure/", "alternative": ["/v0.1/docs/expression_language/primitives/configure/"]},
+  "/docs/expression_language/cookbook/prompt_llm_parser/": {"canonical": "/docs/how_to/sequence/", "alternative": ["/v0.1/docs/expression_language/get_started/"]},
+  "/docs/contributing/documentation/": {"canonical": "/docs/contributing/documentation/", "alternative": ["/v0.1/docs/contributing/documentation/technical_logistics/"]},
+  "/docs/expression_language/cookbook/": {"canonical": "/docs/how_to/#langchain-expression-language-lcel", "alternative": ["/v0.1/docs/expression_language/"]},
+  "/docs/integrations/text_embedding/solar/": {"canonical": "/docs/integrations/text_embedding/upstage/"},
+  "/docs/integrations/chat/solar/": {"canonical": "/docs/integrations/chat/upstage/"},
+  // custom ones
+
+  "/docs/modules/model_io/chat/llm_chain/": {
+    "canonical": "/docs/tutorials/llm_chain/"
+  },
+
+  "/docs/modules/agents/toolkits/": {
+    "canonical": "/docs/integrations/tools/",
+    "alternative": [
+      "/v0.1/docs/integrations/toolkits/"
+    ]
   }
 }

docs/vercel.json

@@ -26,6 +26,18 @@
     }
   ],
   "redirects": [
+    {
+      "source": "/docs/modules/agents/tools/custom_tools(/?)",
+      "destination": "/docs/how_to/custom_tools/"
+    },
+    {
+      "source": "/docs/expression_language(/?)",
+      "destination": "/docs/concepts/#langchain-expression-language-lcel"
+    },
+    {
+      "source": "/docs/expression_language/interface(/?)",
+      "destination": "/docs/concepts/#runnable-interface"
+    },
     {
       "source": "/docs/versions/overview(/?)",
       "destination": "/docs/versions/v0_2/overview/"

libs/cli/langchain_cli/integration_template/pyproject.toml

@@ -13,7 +13,7 @@ license = "MIT"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
-langchain-core = "^0.3.0.dev"
+langchain-core = "^0.3.0"
 
 [tool.poetry.group.test]
 optional = true

libs/cli/langchain_cli/namespaces/migrate/main.py

@@ -5,6 +5,7 @@ from pathlib import Path
 import rich
 import typer
 from gritql import run
+from typer import Option
 
 
 def get_gritdir_path() -> Path:
@@ -15,15 +16,28 @@ def get_gritdir_path() -> Path:
 
 def migrate(
     ctx: typer.Context,
+    # Using diff instead of dry-run for backwards compatibility with the old CLI
+    diff: bool = Option(
+        False,
+        "--diff",
+        help="Show the changes that would be made without applying them.",
+    ),
+    interactive: bool = Option(
+        False,
+        "--interactive",
+        help="Prompt for confirmation before making each change",
+    ),
 ) -> None:
     """Migrate langchain to the most recent version.
 
     Any undocumented arguments will be passed to the Grit CLI.
     """
     rich.print(
-        "✈️ This script will help you migrate to a recent version LangChain. "
+        "✈️ This script will help you migrate to a LangChain 0.3. "
         "This migration script will attempt to replace old imports in the code "
-        "with new ones.\n\n"
+        "with new ones. "
+        "If you need to migrate to LangChain 0.2, please downgrade to version 0.0.29 "
+        "of the langchain-cli.\n\n"
         "🔄 You will need to run the migration script TWICE to migrate (e.g., "
         "to update llms import from langchain, the script will first move them to "
         "corresponding imports from the community package, and on the second "
@@ -45,9 +59,15 @@ def migrate(
     rich.print("-" * 10)
     rich.print()
 
+    args = list(ctx.args)
+    if interactive:
+        args.append("--interactive")
+    if diff:
+        args.append("--dry-run")
+
     final_code = run.apply_pattern(
         "langchain_all_migrations()",
-        ctx.args,
+        args,
         grit_dir=get_gritdir_path(),
     )
 

libs/cli/langchain_cli/package_template/pyproject.toml

@@ -7,7 +7,7 @@ readme = "README.md"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
-langchain-core = "^0.3.0.dev"
+langchain-core = "^0.3.0"
 langchain-openai = ">=0.0.1"
 
 

libs/cli/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langchain-cli"
-version = "0.0.30"
+version = "0.0.31"
 description = "CLI for interacting with LangChain"
 authors = ["Erick Friis <erick@langchain.dev>"]
 readme = "README.md"

libs/community/Makefile

@@ -19,7 +19,7 @@ test tests:
 	poetry run pytest --disable-socket --allow-unix-socket $(TEST_FILE)
 
 integration_tests:
-	poetry run pytest $(TEST_FILE)
+	poetry run pytest -m runs $(TEST_FILE)
 
 test_watch:
 	poetry run ptw --disable-socket --allow-unix-socket --snapshot-update --now . -- -vv tests/unit_tests

libs/community/extended_dependencies/extended_testing_deps.txt

@@ -0,0 +1,2 @@
+-r pdf_loader_deps.txt
+-r other_deps.txt

libs/community/extended_dependencies/other_deps.txt

@@ -54,7 +54,6 @@ openapi-pydantic>=0.3.2,<0.4
 oracle-ads>=2.9.1,<3
 oracledb>=2.2.0,<3
 pandas>=2.0.1,<3
-pdfminer-six>=20221105,<20240706
 pgvector>=0.1.6,<0.2
 praw>=7.7.1,<8
 premai>=0.3.25,<0.4
@@ -62,9 +61,6 @@ psychicapi>=0.8.0,<0.9
 pydantic>=2.7.4,<3
 py-trello>=0.19.0,<0.20
 pyjwt>=2.8.0,<3
-pymupdf>=1.22.3,<2
-pypdf>=3.4.0,<5
-pypdfium2>=4.10.0,<5
 pyspark>=3.4.0,<4
 rank-bm25>=0.2.2,<0.3
 rapidfuzz>=3.1.1,<4

libs/community/extended_dependencies/pdf_loader_deps.txt

@@ -0,0 +1,4 @@
+pdfminer-six>=20221105,<20240706
+pymupdf>=1.22.3,<2
+pypdf>=3.4.0,<5
+pypdfium2>=4.10.0,<5

libs/community/langchain_community/agents/openai_assistant/base.py

@@ -301,7 +301,7 @@ class OpenAIAssistantV2Runnable(OpenAIAssistantRunnable):
             inheritable_metadata=config.get("metadata"),
         )
         run_manager = callback_manager.on_chain_start(
-            dumpd(self), input, name=config.get("run_name")
+            dumpd(self), input, name=config.get("run_name") or self.get_name()
         )
 
         files = _convert_file_ids_into_attachments(kwargs.get("file_ids", []))
@@ -437,7 +437,7 @@ class OpenAIAssistantV2Runnable(OpenAIAssistantRunnable):
             inheritable_metadata=config.get("metadata"),
         )
         run_manager = callback_manager.on_chain_start(
-            dumpd(self), input, name=config.get("run_name")
+            dumpd(self), input, name=config.get("run_name") or self.get_name()
         )
 
         files = _convert_file_ids_into_attachments(kwargs.get("file_ids", []))

libs/community/langchain_community/document_loaders/mongodb.py

@@ -20,13 +20,37 @@ class MongodbLoader(BaseLoader):
         *,
         filter_criteria: Optional[Dict] = None,
         field_names: Optional[Sequence[str]] = None,
+        metadata_names: Optional[Sequence[str]] = None,
+        include_db_collection_in_metadata: bool = True,
     ) -> None:
+        """
+        Initializes the MongoDB loader with necessary database connection
+        details and configurations.
+
+        Args:
+            connection_string (str): MongoDB connection URI.
+            db_name (str):Name of the database to connect to.
+            collection_name (str): Name of the collection to fetch documents from.
+            filter_criteria (Optional[Dict]): MongoDB filter criteria for querying
+            documents.
+            field_names (Optional[Sequence[str]]): List of field names to retrieve
+            from documents.
+            metadata_names (Optional[Sequence[str]]): Additional metadata fields to
+            extract from documents.
+            include_db_collection_in_metadata (bool): Flag to include database and
+            collection names in metadata.
+
+        Raises:
+            ImportError: If the motor library is not installed.
+            ValueError: If any necessary argument is missing.
+        """
         try:
             from motor.motor_asyncio import AsyncIOMotorClient
         except ImportError as e:
             raise ImportError(
                 "Cannot import from motor, please install with `pip install motor`."
             ) from e
+
         if not connection_string:
             raise ValueError("connection_string must be provided.")
 
@@ -39,8 +63,10 @@ class MongodbLoader(BaseLoader):
         self.client = AsyncIOMotorClient(connection_string)
         self.db_name = db_name
         self.collection_name = collection_name
-        self.field_names = field_names
+        self.field_names = field_names or []
         self.filter_criteria = filter_criteria or {}
+        self.metadata_names = metadata_names or []
+        self.include_db_collection_in_metadata = include_db_collection_in_metadata
 
         self.db = self.client.get_database(db_name)
         self.collection = self.db.get_collection(collection_name)
@@ -60,36 +86,24 @@ class MongodbLoader(BaseLoader):
         return asyncio.run(self.aload())
 
     async def aload(self) -> List[Document]:
-        """Load data into Document objects."""
+        """Asynchronously loads data into Document objects."""
         result = []
         total_docs = await self.collection.count_documents(self.filter_criteria)
 
-        # Construct the projection dictionary if field_names are specified
-        projection = (
-            {field: 1 for field in self.field_names} if self.field_names else None
-        )
+        projection = self._construct_projection()
 
         async for doc in self.collection.find(self.filter_criteria, projection):
-            metadata = {
-                "database": self.db_name,
-                "collection": self.collection_name,
-            }
+            metadata = self._extract_fields(doc, self.metadata_names, default="")
+
+            # Optionally add database and collection names to metadata
+            if self.include_db_collection_in_metadata:
+                metadata.update(
+                    {"database": self.db_name, "collection": self.collection_name}
+                )
 
             # Extract text content from filtered fields or use the entire document
             if self.field_names is not None:
-                fields = {}
-                for name in self.field_names:
-                    # Split the field names to handle nested fields
-                    keys = name.split(".")
-                    value = doc
-                    for key in keys:
-                        if key in value:
-                            value = value[key]
-                        else:
-                            value = ""
-                            break
-                    fields[name] = value
-
+                fields = self._extract_fields(doc, self.field_names, default="")
                 texts = [str(value) for value in fields.values()]
                 text = " ".join(texts)
             else:
@@ -104,3 +118,29 @@ class MongodbLoader(BaseLoader):
             )
 
         return result
+
+    def _construct_projection(self) -> Optional[Dict]:
+        """Constructs the projection dictionary for MongoDB query based
+        on the specified field names and metadata names."""
+        field_names = list(self.field_names) or []
+        metadata_names = list(self.metadata_names) or []
+        all_fields = field_names + metadata_names
+        return {field: 1 for field in all_fields} if all_fields else None
+
+    def _extract_fields(
+        self,
+        document: Dict,
+        fields: Sequence[str],
+        default: str = "",
+    ) -> Dict:
+        """Extracts and returns values for specified fields from a document."""
+        extracted = {}
+        for field in fields or []:
+            value = document
+            for key in field.split("."):
+                value = value.get(key, default)
+                if value == default:
+                    break
+            new_field_name = field.replace(".", "_")
+            extracted[new_field_name] = value
+        return extracted

libs/community/pyproject.toml

@@ -63,6 +63,7 @@ addopts = "--strict-markers --strict-config --durations=5 --snapshot-warn-unused
 markers = [
     "requires: mark tests as requiring a specific library",
     "scheduled: mark tests to run in scheduled testing",
+    "runs: mark tests to run in CI",
     "compile: mark placeholder test used to compile integration tests without running them",
 ]
 asyncio_mode = "auto"

libs/community/tests/integration_tests/conftest.py

@@ -1,6 +1,11 @@
-# Getting the absolute path of the current file's directory
+from importlib import util
 import os
+from typing import Dict, Sequence
 
+import pytest
+from pytest import Config, Function, Parser
+
+# Getting the absolute path of the current file's directory
 ABS_PATH = os.path.dirname(os.path.abspath(__file__))
 
 # Getting the absolute path of the project's root directory
@@ -17,3 +22,83 @@ def _load_env() -> None:
 
 
 _load_env()
+
+def pytest_addoption(parser: Parser) -> None:
+    """Add custom command line options to pytest."""
+    parser.addoption(
+        "--only-extended",
+        action="store_true",
+        help="Only run extended tests. Does not allow skipping any extended tests.",
+    )
+    parser.addoption(
+        "--only-core",
+        action="store_true",
+        help="Only run core tests. Never runs any extended tests.",
+    )
+
+
+def pytest_collection_modifyitems(config: Config, items: Sequence[Function]) -> None:
+    """Add implementations for handling custom markers.
+
+    At the moment, this adds support for a custom `requires` marker.
+
+    The `requires` marker is used to denote tests that require one or more packages
+    to be installed to run. If the package is not installed, the test is skipped.
+
+    The `requires` marker syntax is:
+
+    .. code-block:: python
+
+        @pytest.mark.requires("package1", "package2")
+        def test_something():
+            ...
+    """
+    # Mapping from the name of a package to whether it is installed or not.
+    # Used to avoid repeated calls to `util.find_spec`
+    required_pkgs_info: Dict[str, bool] = {}
+
+    only_extended = config.getoption("--only-extended") or False
+    only_core = config.getoption("--only-core") or False
+
+    if only_extended and only_core:
+        raise ValueError("Cannot specify both `--only-extended` and `--only-core`.")
+
+    for item in items:
+        requires_marker = item.get_closest_marker("requires")
+        if requires_marker is not None:
+            if only_core:
+                item.add_marker(pytest.mark.skip(reason="Skipping not a core test."))
+                continue
+
+            # Iterate through the list of required packages
+            required_pkgs = requires_marker.args
+            for pkg in required_pkgs:
+                # If we haven't yet checked whether the pkg is installed
+                # let's check it and store the result.
+                if pkg not in required_pkgs_info:
+                    try:
+                        installed = util.find_spec(pkg) is not None
+                    except Exception:
+                        installed = False
+                    required_pkgs_info[pkg] = installed
+
+                if not required_pkgs_info[pkg]:
+                    if only_extended:
+                        pytest.fail(
+                            f"Package `{pkg}` is not installed but is required for "
+                            f"extended tests. Please install the given package and "
+                            f"try again.",
+                        )
+
+                    else:
+                        # If the package is not installed, we immediately break
+                        # and mark the test as skipped.
+                        item.add_marker(
+                            pytest.mark.skip(reason=f"Requires pkg: `{pkg}`")
+                        )
+                        break
+        else:
+            if only_extended:
+                item.add_marker(
+                    pytest.mark.skip(reason="Skipping not an extended test.")
+                )

libs/community/tests/integration_tests/document_loaders/test_pdf.py

@@ -86,6 +86,8 @@ def test_pdfminer_pdf_as_html_loader() -> None:
     assert len(docs) == 1
 
 
+@pytest.mark.runs
+@pytest.mark.requires("pypdf")
 def test_pypdf_loader() -> None:
     """Test PyPDFLoader."""
     file_path = Path(__file__).parent.parent / "examples/hello.pdf"
@@ -101,6 +103,8 @@ def test_pypdf_loader() -> None:
     assert len(docs) == 16
 
 
+@pytest.mark.runs
+@pytest.mark.requires("pypdf")
 def test_pypdf_loader_with_layout() -> None:
     """Test PyPDFLoader with layout mode."""
     file_path = Path(__file__).parent.parent / "examples/layout-parser-paper.pdf"

libs/community/tests/unit_tests/callbacks/test_callback_manager.py

@@ -121,4 +121,4 @@ def test_callback_manager_configure_context_vars(
                     assert cb.completion_tokens == 1
                     assert cb.total_cost > 0
             wait_for_all_tracers()
-            assert LangChainTracer._persist_run_single.call_count == 1  # type: ignore
+            assert LangChainTracer._persist_run_single.call_count == 4  # type: ignore

libs/community/tests/unit_tests/document_loaders/test_mongodb.py

@@ -12,6 +12,7 @@ def raw_docs() -> List[Dict]:
     return [
         {"_id": "1", "address": {"building": "1", "room": "1"}},
         {"_id": "2", "address": {"building": "2", "room": "2"}},
+        {"_id": "3", "address": {"building": "3", "room": "2"}},
     ]
 
 
@@ -19,18 +20,23 @@ def raw_docs() -> List[Dict]:
 def expected_documents() -> List[Document]:
     return [
         Document(
-            page_content="{'_id': '1', 'address': {'building': '1', 'room': '1'}}",
+            page_content="{'_id': '2', 'address': {'building': '2', 'room': '2'}}",
             metadata={"database": "sample_restaurants", "collection": "restaurants"},
         ),
         Document(
-            page_content="{'_id': '2', 'address': {'building': '2', 'room': '2'}}",
+            page_content="{'_id': '3', 'address': {'building': '3', 'room': '2'}}",
             metadata={"database": "sample_restaurants", "collection": "restaurants"},
         ),
     ]
 
 
 @pytest.mark.requires("motor")
-async def test_load_mocked(expected_documents: List[Document]) -> None:
+async def test_load_mocked_with_filters(expected_documents: List[Document]) -> None:
+    filter_criteria = {"address.room": {"$eq": "2"}}
+    field_names = ["address.building", "address.room"]
+    metadata_names = ["_id"]
+    include_db_collection_in_metadata = True
+
     mock_async_load = AsyncMock()
     mock_async_load.return_value = expected_documents
 
@@ -51,7 +57,13 @@ async def test_load_mocked(expected_documents: List[Document]) -> None:
         new=mock_async_load,
     ):
         loader = MongodbLoader(
-            "mongodb://localhost:27017", "test_db", "test_collection"
+            "mongodb://localhost:27017",
+            "test_db",
+            "test_collection",
+            filter_criteria=filter_criteria,
+            field_names=field_names,
+            metadata_names=metadata_names,
+            include_db_collection_in_metadata=include_db_collection_in_metadata,
         )
         loader.collection = mock_collection
         documents = await loader.aload()

libs/core/langchain_core/_api/deprecation.py

@@ -333,9 +333,26 @@ def deprecated(
             old_doc = ""
 
         # Modify the docstring to include a deprecation notice.
+        if (
+            _alternative
+            and _alternative.split(".")[-1].lower() == _alternative.split(".")[-1]
+        ):
+            _alternative = f":meth:`~{_alternative}`"
+        elif _alternative:
+            _alternative = f":class:`~{_alternative}`"
+
+        if (
+            _alternative_import
+            and _alternative_import.split(".")[-1].lower()
+            == _alternative_import.split(".")[-1]
+        ):
+            _alternative_import = f":meth:`~{_alternative_import}`"
+        elif _alternative_import:
+            _alternative_import = f":class:`~{_alternative_import}`"
+
         components = [
             _message,
-            f"Use ``{_alternative}`` instead." if _alternative else "",
+            f"Use {_alternative} instead." if _alternative else "",
             f"Use ``{_alternative_import}`` instead." if _alternative_import else "",
             _addendum,
         ]

libs/core/langchain_core/messages/modifier.py

@@ -1,10 +1,8 @@
 from typing import Any, List, Literal
 
-from langchain_core._api import beta
 from langchain_core.messages.base import BaseMessage
 
 
-@beta()
 class RemoveMessage(BaseMessage):
     """Message responsible for deleting other messages."""
 

libs/core/langchain_core/tracers/schemas.py

@@ -135,11 +135,13 @@ class Run(BaseRunV2):
     @root_validator(pre=True)
     def assign_name(cls, values: dict) -> dict:
         """Assign name to the run."""
-        if values.get("name") is None:
+        if values.get("name") is None and values["serialized"] is not None:
             if "name" in values["serialized"]:
                 values["name"] = values["serialized"]["name"]
             elif "id" in values["serialized"]:
                 values["name"] = values["serialized"]["id"][-1]
+        if values.get("name") is None:
+            values["name"] = "Unnamed"
         if values.get("events") is None:
             values["events"] = []
         return values

libs/core/pyproject.toml

@@ -1,10 +1,10 @@
 [build-system]
-requires = ["poetry-core>=1.0.0"]
+requires = [ "poetry-core>=1.0.0",]
 build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "langchain-core"
-version = "0.3.0"
+version = "0.3.1"
 description = "Building applications with LLMs through composability"
 authors = []
 license = "MIT"
@@ -12,17 +12,10 @@ readme = "README.md"
 repository = "https://github.com/langchain-ai/langchain"
 
 [tool.mypy]
-exclude = [
-    "notebooks",
-    "examples",
-    "example_data",
-    "langchain_core/pydantic",
-    "tests/unit_tests/utils/test_function_calling.py",
-]
-"disallow_untyped_defs" = "True"
-
+exclude = [ "notebooks", "examples", "example_data", "langchain_core/pydantic", "tests/unit_tests/utils/test_function_calling.py",]
+disallow_untyped_defs = "True"
 [[tool.mypy.overrides]]
-module = ["numpy", "pytest"]
+module = [ "numpy", "pytest",]
 ignore_missing_imports = true
 
 [tool.poetry.urls]
@@ -37,32 +30,28 @@ jsonpatch = "^1.33"
 PyYAML = ">=5.3"
 packaging = ">=23.2,<25"
 typing-extensions = ">=4.7"
-pydantic = [
-    { version = "^2.5.2", python = "<3.12.4" },
-    { version = "^2.7.4", python = ">=3.12.4" },
-]
+[[tool.poetry.dependencies.pydantic]]
+version = "^2.5.2"
+python = "<3.12.4"
 
+[[tool.poetry.dependencies.pydantic]]
+version = "^2.7.4"
+python = ">=3.12.4"
 
 [tool.poetry.extras]
 
 [tool.ruff.lint]
-select = ["B", "E", "F", "I", "T201", "UP"]
-ignore = ["UP006", "UP007"]
+select = [ "B", "E", "F", "I", "T201", "UP",]
+ignore = [ "UP006", "UP007",]
 
 [tool.coverage.run]
-omit = ["tests/*"]
+omit = [ "tests/*",]
 
 [tool.pytest.ini_options]
 addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5"
-markers = [
-    "requires: mark tests as requiring a specific library",
-    "asyncio: mark tests as requiring asyncio",
-    "compile: mark placeholder test used to compile integration tests without running them",
-]
+markers = [ "requires: mark tests as requiring a specific library", "asyncio: mark tests as requiring asyncio", "compile: mark placeholder test used to compile integration tests without running them",]
 asyncio_mode = "auto"
-filterwarnings = [
-    "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning",
-]
+filterwarnings = [ "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning",]
 
 [tool.poetry.group.lint]
 optional = true
@@ -80,9 +69,9 @@ optional = true
 optional = true
 
 [tool.ruff.lint.per-file-ignores]
-"tests/unit_tests/prompts/test_chat.py" = ["E501"]
-"tests/unit_tests/runnables/test_runnable.py" = ["E501"]
-"tests/unit_tests/runnables/test_graph.py" = ["E501"]
+"tests/unit_tests/prompts/test_chat.py" = [ "E501",]
+"tests/unit_tests/runnables/test_runnable.py" = [ "E501",]
+"tests/unit_tests/runnables/test_graph.py" = [ "E501",]
 
 [tool.poetry.group.lint.dependencies]
 ruff = "^0.5"

libs/experimental/langchain_experimental/graph_transformers/llm.py

@@ -749,12 +749,20 @@ class LLMGraphTransformer:
             if isinstance(parsed_json, dict):
                 parsed_json = [parsed_json]
             for rel in parsed_json:
+                # Check if mandatory properties are there
+                if (
+                    not rel.get("head")
+                    or not rel.get("tail")
+                    or not rel.get("relation")
+                ):
+                    continue
                 # Nodes need to be deduplicated using a set
-                nodes_set.add((rel["head"], rel["head_type"]))
-                nodes_set.add((rel["tail"], rel["tail_type"]))
+                # Use default Node label for nodes if missing
+                nodes_set.add((rel["head"], rel.get("head_type", "Node")))
+                nodes_set.add((rel["tail"], rel.get("tail_type", "Node")))
 
-                source_node = Node(id=rel["head"], type=rel["head_type"])
-                target_node = Node(id=rel["tail"], type=rel["tail_type"])
+                source_node = Node(id=rel["head"], type=rel.get("head_type", "Node"))
+                target_node = Node(id=rel["tail"], type=rel.get("tail_type", "Node"))
                 relationships.append(
                     Relationship(
                         source=source_node, target=target_node, type=rel["relation"]

libs/langchain/langchain/agents/openai_assistant/base.py

@@ -310,7 +310,7 @@ class OpenAIAssistantRunnable(RunnableSerializable[Dict, OutputType]):
             inheritable_metadata=config.get("metadata"),
         )
         run_manager = callback_manager.on_chain_start(
-            dumpd(self), input, name=config.get("run_name")
+            dumpd(self), input, name=config.get("run_name") or self.get_name()
         )
         try:
             # Being run within AgentExecutor and there are tool outputs to submit.
@@ -429,7 +429,7 @@ class OpenAIAssistantRunnable(RunnableSerializable[Dict, OutputType]):
             inheritable_metadata=config.get("metadata"),
         )
         run_manager = callback_manager.on_chain_start(
-            dumpd(self), input, name=config.get("run_name")
+            dumpd(self), input, name=config.get("run_name") or self.get_name()
         )
         try:
             # Being run within AgentExecutor and there are tool outputs to submit.

libs/langchain/langchain/chains/llm.py

@@ -242,6 +242,7 @@ class LLMChain(Chain):
         run_manager = callback_manager.on_chain_start(
             None,
             {"input_list": input_list},
+            name=self.get_name(),
         )
         try:
             response = self.generate(input_list, run_manager=run_manager)
@@ -262,6 +263,7 @@ class LLMChain(Chain):
         run_manager = await callback_manager.on_chain_start(
             None,
             {"input_list": input_list},
+            name=self.get_name(),
         )
         try:
             response = await self.agenerate(input_list, run_manager=run_manager)

libs/langchain/langchain/chat_models/base.py

@@ -98,48 +98,42 @@ def init_chat_model(
 
     Must have the integration package corresponding to the model provider installed.
 
-    .. versionadded:: 0.2.7
-
-    .. versionchanged:: 0.2.8
-
-        Support for ``configurable_fields`` and ``config_prefix`` added.
-
-    .. versionchanged:: 0.2.12
-
-        Support for Ollama via langchain-ollama package added. Previously
-        langchain-community version of Ollama (now deprecated) was installed by default.
-
     Args:
         model: The name of the model, e.g. "gpt-4o", "claude-3-opus-20240229".
         model_provider: The model provider. Supported model_provider values and the
             corresponding integration package:
-                - openai (langchain-openai)
-                - anthropic (langchain-anthropic)
-                - azure_openai (langchain-openai)
-                - google_vertexai (langchain-google-vertexai)
-                - google_genai (langchain-google-genai)
-                - bedrock (langchain-aws)
-                - cohere (langchain-cohere)
-                - fireworks (langchain-fireworks)
-                - together (langchain-together)
-                - mistralai (langchain-mistralai)
-                - huggingface (langchain-huggingface)
-                - groq (langchain-groq)
-                - ollama (langchain-ollama)  [support added in langchain==0.2.12]
+
+            - openai (langchain-openai)
+            - anthropic (langchain-anthropic)
+            - azure_openai (langchain-openai)
+            - google_vertexai (langchain-google-vertexai)
+            - google_genai (langchain-google-genai)
+            - bedrock (langchain-aws)
+            - bedrock_converse (langchain-aws)
+            - cohere (langchain-cohere)
+            - fireworks (langchain-fireworks)
+            - together (langchain-together)
+            - mistralai (langchain-mistralai)
+            - huggingface (langchain-huggingface)
+            - groq (langchain-groq)
+            - ollama (langchain-ollama)  [support added in langchain==0.2.12]
 
             Will attempt to infer model_provider from model if not specified. The
             following providers will be inferred based on these model prefixes:
-                - gpt-3... or gpt-4... -> openai
-                - claude... -> anthropic
-                - amazon.... -> bedrock
-                - gemini... -> google_vertexai
-                - command... -> cohere
-                - accounts/fireworks... -> fireworks
+
+            - gpt-3..., gpt-4..., or o1... -> openai
+            - claude... -> anthropic
+            - amazon.... -> bedrock
+            - gemini... -> google_vertexai
+            - command... -> cohere
+            - accounts/fireworks... -> fireworks
+            - mistral... -> mistralai
         configurable_fields: Which model parameters are
             configurable:
-                - None: No configurable fields.
-                - "any": All fields are configurable. *See Security Note below.*
-                - Union[List[str], Tuple[str, ...]]: Specified fields are configurable.
+
+            - None: No configurable fields.
+            - "any": All fields are configurable. *See Security Note below.*
+            - Union[List[str], Tuple[str, ...]]: Specified fields are configurable.
 
             Fields are assumed to have config_prefix stripped if there is a
             config_prefix. If model is specified, then defaults to None. If model is
@@ -168,7 +162,9 @@ def init_chat_model(
         ValueError: If model_provider cannot be inferred or isn't supported.
         ImportError: If the model provider integration package is not installed.
 
-    Initialize non-configurable models:
+    .. dropdown:: Init non-configurable model
+        :open:
+
         .. code-block:: python
 
             # pip install langchain langchain-openai langchain-anthropic langchain-google-vertexai
@@ -183,7 +179,8 @@ def init_chat_model(
             gemini_15.invoke("what's your name")
 
 
-    Create a partially configurable model with no default model:
+    .. dropdown:: Partially configurable model with no default
+
         .. code-block:: python
 
             # pip install langchain langchain-openai langchain-anthropic
@@ -204,7 +201,8 @@ def init_chat_model(
             )
             # claude-3.5 sonnet response
 
-    Create a fully configurable model with a default model and a config prefix:
+    .. dropdown:: Fully configurable model with a default
+
         .. code-block:: python
 
             # pip install langchain langchain-openai langchain-anthropic
@@ -233,7 +231,8 @@ def init_chat_model(
             )
             # Claude-3.5 sonnet response with temperature 0.6
 
-    Bind tools to a configurable model:
+    .. dropdown:: Bind tools to a configurable model
+
         You can call any ChatModel declarative methods on a configurable model in the
         same way that you would with a normal model.
 
@@ -270,6 +269,23 @@ def init_chat_model(
                 config={"configurable": {"model": "claude-3-5-sonnet-20240620"}}
             )
             # Claude-3.5 sonnet response with tools
+
+    .. versionadded:: 0.2.7
+
+    .. versionchanged:: 0.2.8
+
+        Support for ``configurable_fields`` and ``config_prefix`` added.
+
+    .. versionchanged:: 0.2.12
+
+        Support for ChatOllama via langchain-ollama package added
+        (langchain_ollama.ChatOllama). Previously,
+        the now-deprecated langchain-community version of Ollama was imported
+        (langchain_community.chat_models.ChatOllama).
+
+        Support for langchain_aws.ChatBedrockConverse added
+        (model_provider="bedrock_converse").
+
     """  # noqa: E501
     if not model and not configurable_fields:
         configurable_fields = ("model", "model_provider")
@@ -415,7 +431,7 @@ _SUPPORTED_PROVIDERS = {
 
 
 def _attempt_infer_model_provider(model_name: str) -> Optional[str]:
-    if model_name.startswith("gpt-3") or model_name.startswith("gpt-4"):
+    if any(model_name.startswith(pre) for pre in ("gpt-3", "gpt-4", "o1")):
         return "openai"
     elif model_name.startswith("claude"):
         return "anthropic"
@@ -427,6 +443,8 @@ def _attempt_infer_model_provider(model_name: str) -> Optional[str]:
         return "google_vertexai"
     elif model_name.startswith("amazon."):
         return "bedrock"
+    elif model_name.startswith("mistral"):
+        return "mistralai"
     else:
         return None
 

libs/partners/box/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
 
 [[package]]
 name = "annotated-types"
@@ -441,7 +441,7 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.0.dev1"
+version = "0.3.0"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.9,<4.0"
@@ -450,9 +450,12 @@ develop = true
 
 [package.dependencies]
 jsonpatch = "^1.33"
-langsmith = "^0.1.75"
+langsmith = "^0.1.117"
 packaging = ">=23.2,<25"
-pydantic = "^2.7.4"
+pydantic = [
+    {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
+]
 PyYAML = ">=5.3"
 tenacity = "^8.1.0,!=8.4.0"
 typing-extensions = ">=4.7"
@@ -463,13 +466,13 @@ url = "../../core"
 
 [[package]]
 name = "langsmith"
-version = "0.1.115"
+version = "0.1.121"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.115-py3-none-any.whl", hash = "sha256:04e35cfd4c2d4ff1ea10bb577ff43957b05ebb3d9eb4e06e200701f4a2b4ac9f"},
-    {file = "langsmith-0.1.115.tar.gz", hash = "sha256:3b775377d858d32354f3ee0dd1ed637068cfe9a1f13e7b3bfa82db1615cdffc9"},
+    {file = "langsmith-0.1.121-py3-none-any.whl", hash = "sha256:fdb1ac8a671d3904201bfeea197d87bded46a10d08f1034af464211872e29893"},
+    {file = "langsmith-0.1.121.tar.gz", hash = "sha256:e9381b82a5bd484af9a51c3e96faea572746b8d617b070c1cda40cbbe48e33df"},
 ]
 
 [package.dependencies]
@@ -644,120 +647,120 @@ files = [
 
 [[package]]
 name = "pydantic"
-version = "2.9.0"
+version = "2.9.1"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pydantic-2.9.0-py3-none-any.whl", hash = "sha256:f66a7073abd93214a20c5f7b32d56843137a7a2e70d02111f3be287035c45370"},
-    {file = "pydantic-2.9.0.tar.gz", hash = "sha256:c7a8a9fdf7d100afa49647eae340e2d23efa382466a8d177efcd1381e9be5598"},
+    {file = "pydantic-2.9.1-py3-none-any.whl", hash = "sha256:7aff4db5fdf3cf573d4b3c30926a510a10e19a0774d38fc4967f78beb6deb612"},
+    {file = "pydantic-2.9.1.tar.gz", hash = "sha256:1363c7d975c7036df0db2b4a61f2e062fbc0aa5ab5f2772e0ffc7191a4f4bce2"},
 ]
 
 [package.dependencies]
-annotated-types = ">=0.4.0"
-pydantic-core = "2.23.2"
+annotated-types = ">=0.6.0"
+pydantic-core = "2.23.3"
 typing-extensions = {version = ">=4.6.1", markers = "python_version < \"3.13\""}
-tzdata = {version = "*", markers = "python_version >= \"3.9\""}
 
 [package.extras]
 email = ["email-validator (>=2.0.0)"]
+timezone = ["tzdata"]
 
 [[package]]
 name = "pydantic-core"
-version = "2.23.2"
+version = "2.23.3"
 description = "Core functionality for Pydantic validation and serialization"
 optional = false
 python-versions = ">=3.8"
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+    {file = "pydantic_core-2.23.3.tar.gz", hash = "sha256:3cb0f65d8b4121c1b015c60104a685feb929a29d7cf204387c7f2688c7974690"},
 ]
 
 [package.dependencies]
@@ -1050,17 +1053,6 @@ files = [
     {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
 ]
 
-[[package]]
-name = "tzdata"
-version = "2024.1"
-description = "Provider of IANA time zone data"
-optional = false
-python-versions = ">=2"
-files = [
-    {file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"},
-    {file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
-]
-
 [[package]]
 name = "urllib3"
 version = "2.2.2"
@@ -1081,4 +1073,4 @@ zstd = ["zstandard (>=0.18.0)"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9.0,<3.13"
-content-hash = "1f32eed9a4e19e0d1da66632d03c8026397929eab9c5c99c107d83fb120a6c05"
+content-hash = "231de5b826920531d20b71d35b92e2f79d3fb69db37848b8bdf3e9bb99a2ab03"

libs/partners/box/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langchain-box"
-version = "0.1.0"
+version = "0.2.0"
 description = "An integration package connecting Box and LangChain"
 authors = []
 readme = "README.md"
@@ -13,8 +13,9 @@ license = "MIT"
 
 [tool.poetry.dependencies]
 python = ">=3.9.0,<3.13"
-langchain-core = "^0.3.0.dev"
+langchain-core = "^0.3"
 box-sdk-gen = { extras = ["jwt"], version = "^1.1.0" }
+pydantic = "^2"
 
 [tool.poetry.group.test]
 optional = true

libs/partners/fireworks/langchain_fireworks/chat_models.py

@@ -24,6 +24,7 @@ from typing import (
 )
 
 from fireworks.client import AsyncFireworks, Fireworks  # type: ignore
+from langchain_core._api import deprecated
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
@@ -626,6 +627,11 @@ class ChatFireworks(BaseChatModel):
         """Return type of chat model."""
         return "fireworks-chat"
 
+    @deprecated(
+        since="0.2.1",
+        alternative="langchain_fireworks.chat_models.ChatFireworks.bind_tools",
+        removal="0.3.0",
+    )
     def bind_functions(
         self,
         functions: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
@@ -705,8 +711,8 @@ class ChatFireworks(BaseChatModel):
                 with the option to not call any function, "any" to enforce that some
                 function is called, or a dict of the form:
                 {"type": "function", "function": {"name": <<tool_name>>}}.
-            **kwargs: Any additional parameters to pass to the
-                :class:`~langchain.runnable.Runnable` constructor.
+            **kwargs: Any additional parameters to pass to
+                :meth:`~langchain_fireworks.chat_models.ChatFireworks.bind`
         """
 
         formatted_tools = [convert_to_openai_tool(tool) for tool in tools]

libs/partners/groq/langchain_groq/chat_models.py

@@ -23,6 +23,7 @@ from typing import (
     cast,
 )
 
+from langchain_core._api import deprecated
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
@@ -650,6 +651,11 @@ class ChatGroq(BaseChatModel):
             combined["system_fingerprint"] = system_fingerprint
         return combined
 
+    @deprecated(
+        since="0.2.1",
+        alternative="langchain_groq.chat_models.ChatGroq.bind_tools",
+        removal="0.3.0",
+    )
     def bind_functions(
         self,
         functions: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
@@ -674,8 +680,8 @@ class ChatGroq(BaseChatModel):
                 Must be the name of the single provided function or
                 "auto" to automatically determine which function to call
                 (if any).
-            **kwargs: Any additional parameters to pass to the
-                :class:`~langchain.runnable.Runnable` constructor.
+            **kwargs: Any additional parameters to pass to
+                :meth:`~langchain_groq.chat_models.ChatGroq.bind`.
         """
 
         formatted_functions = [convert_to_openai_function(fn) for fn in functions]

libs/partners/milvus/pyproject.toml

@@ -25,9 +25,17 @@ ignore_missing_imports = "True"
 "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-milvus%3D%3D0%22&expanded=true"
 
 [tool.poetry.dependencies]
-python = ">=3.9,<4.0"
-langchain-core = "^0.3.0.dev"
+python = ">=3.8.1,<4.0"
 pymilvus = "^2.4.3"
+
+[[tool.poetry.dependencies.langchain-core]]
+version = ">=0.2.38,<0.4"
+python = ">=3.9"
+
+[[tool.poetry.dependencies.langchain-core]]
+version = ">=0.2.38,<0.3"
+python = "<3.9"
+
 [[tool.poetry.dependencies.scipy]]
 version = "^1.7"
 python = "<3.12"
@@ -72,6 +80,15 @@ pytest-watcher = "^0.3.4"
 pytest-asyncio = "^0.21.1"
 milvus_model = "^0.2.0"
 
+[[tool.poetry.group.test.dependencies.langchain-core]]
+path = "../../core"
+develop = true
+python = ">=3.9"
+
+[[tool.poetry.group.test.dependencies.langchain-core]]
+version = ">=0.2.38,<0.3"
+python = "<3.9"
+
 [tool.poetry.group.codespell.dependencies]
 codespell = "^2.2.0"
 
@@ -86,14 +103,21 @@ mypy = "^0.991"
 types-requests = "^2"
 simsimd = "^5.0.0"
 
-[tool.poetry.group.test.dependencies.langchain-core]
+[[tool.poetry.group.typing.dependencies.langchain-core]]
 path = "../../core"
 develop = true
+python = ">=3.9"
 
-[tool.poetry.group.typing.dependencies.langchain-core]
-path = "../../core"
-develop = true
+[[tool.poetry.group.typing.dependencies.langchain-core]]
+version = ">=0.2.38,<0.3"
+python = "<3.9"
 
-[tool.poetry.group.dev.dependencies.langchain-core]
+[tool.poetry.group.dev.dependencies]
+[[tool.poetry.group.dev.dependencies.langchain-core]]
 path = "../../core"
 develop = true
+python = ">=3.9"
+
+[[tool.poetry.group.dev.dependencies.langchain-core]]
+version = ">=0.2.38,<0.3"
+python = "<3.9"

libs/partners/milvus/tests/integration_tests/vectorstores/test_milvus.py

@@ -1,5 +1,6 @@
 """Test Milvus functionality."""
 
+import tempfile
 from typing import Any, List, Optional
 
 import pytest
@@ -13,6 +14,7 @@ from tests.integration_tests.utils import (
     fake_texts,
 )
 
+
 #
 # To run this test properly, please start a Milvus server with the following command:
 #
@@ -24,12 +26,17 @@ from tests.integration_tests.utils import (
 # Here is the reference:
 # https://milvus.io/docs/install_standalone-docker.md
 #
+@pytest.fixture
+def temp_milvus_db() -> Any:
+    with tempfile.NamedTemporaryFile(suffix=".db") as temp_file:
+        yield temp_file.name
 
 
 def _milvus_from_texts(
     metadatas: Optional[List[dict]] = None,
     ids: Optional[List[str]] = None,
     drop: bool = True,
+    db_path: str = "./milvus_demo.db",
     **kwargs: Any,
 ) -> Milvus:
     return Milvus.from_texts(
@@ -38,7 +45,7 @@ def _milvus_from_texts(
         metadatas=metadatas,
         ids=ids,
         # connection_args={"uri": "http://127.0.0.1:19530"},
-        connection_args={"uri": "./milvus_demo.db"},
+        connection_args={"uri": db_path},
         drop_old=drop,
         consistency_level="Strong",
         **kwargs,
@@ -49,35 +56,37 @@ def _get_pks(expr: str, docsearch: Milvus) -> List[Any]:
     return docsearch.get_pks(expr)  # type: ignore[return-value]
 
 
-def test_milvus() -> None:
+def test_milvus(temp_milvus_db: Any) -> None:
     """Test end to end construction and search."""
-    docsearch = _milvus_from_texts()
+    docsearch = _milvus_from_texts(db_path=temp_milvus_db)
     output = docsearch.similarity_search("foo", k=1)
     assert_docs_equal_without_pk(output, [Document(page_content="foo")])
 
 
-def test_milvus_vector_search() -> None:
+def test_milvus_vector_search(temp_milvus_db: Any) -> None:
     """Test end to end construction and search by vector."""
-    docsearch = _milvus_from_texts()
+    docsearch = _milvus_from_texts(db_path=temp_milvus_db)
     output = docsearch.similarity_search_by_vector(
         FakeEmbeddings().embed_query("foo"), k=1
     )
     assert_docs_equal_without_pk(output, [Document(page_content="foo")])
 
 
-def test_milvus_with_metadata() -> None:
+def test_milvus_with_metadata(temp_milvus_db: Any) -> None:
     """Test with metadata"""
-    docsearch = _milvus_from_texts(metadatas=[{"label": "test"}] * len(fake_texts))
+    docsearch = _milvus_from_texts(
+        metadatas=[{"label": "test"}] * len(fake_texts), db_path=temp_milvus_db
+    )
     output = docsearch.similarity_search("foo", k=1)
     assert_docs_equal_without_pk(
         output, [Document(page_content="foo", metadata={"label": "test"})]
     )
 
 
-def test_milvus_with_id() -> None:
+def test_milvus_with_id(temp_milvus_db: Any) -> None:
     """Test with ids"""
     ids = ["id_" + str(i) for i in range(len(fake_texts))]
-    docsearch = _milvus_from_texts(ids=ids)
+    docsearch = _milvus_from_texts(ids=ids, db_path=temp_milvus_db)
     output = docsearch.similarity_search("foo", k=1)
     assert_docs_equal_without_pk(output, [Document(page_content="foo")])
 
@@ -86,16 +95,16 @@ def test_milvus_with_id() -> None:
 
     try:
         ids = ["dup_id" for _ in fake_texts]
-        _milvus_from_texts(ids=ids)
+        _milvus_from_texts(ids=ids, db_path=temp_milvus_db)
     except Exception as e:
         assert isinstance(e, AssertionError)
 
 
-def test_milvus_with_score() -> None:
+def test_milvus_with_score(temp_milvus_db: Any) -> None:
     """Test end to end construction and search with scores and IDs."""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"page": i} for i in range(len(texts))]
-    docsearch = _milvus_from_texts(metadatas=metadatas)
+    docsearch = _milvus_from_texts(metadatas=metadatas, db_path=temp_milvus_db)
     output = docsearch.similarity_search_with_score("foo", k=3)
     docs = [o[0] for o in output]
     scores = [o[1] for o in output]
@@ -110,11 +119,11 @@ def test_milvus_with_score() -> None:
     assert scores[0] < scores[1] < scores[2]
 
 
-def test_milvus_max_marginal_relevance_search() -> None:
+def test_milvus_max_marginal_relevance_search(temp_milvus_db: Any) -> None:
     """Test end to end construction and MRR search."""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"page": i} for i in range(len(texts))]
-    docsearch = _milvus_from_texts(metadatas=metadatas)
+    docsearch = _milvus_from_texts(metadatas=metadatas, db_path=temp_milvus_db)
     output = docsearch.max_marginal_relevance_search("foo", k=2, fetch_k=3)
     assert_docs_equal_without_pk(
         output,
@@ -125,11 +134,15 @@ def test_milvus_max_marginal_relevance_search() -> None:
     )
 
 
-def test_milvus_max_marginal_relevance_search_with_dynamic_field() -> None:
+def test_milvus_max_marginal_relevance_search_with_dynamic_field(
+    temp_milvus_db: Any,
+) -> None:
     """Test end to end construction and MRR search with enabling dynamic field."""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"page": i} for i in range(len(texts))]
-    docsearch = _milvus_from_texts(metadatas=metadatas, enable_dynamic_field=True)
+    docsearch = _milvus_from_texts(
+        metadatas=metadatas, enable_dynamic_field=True, db_path=temp_milvus_db
+    )
     output = docsearch.max_marginal_relevance_search("foo", k=2, fetch_k=3)
     assert_docs_equal_without_pk(
         output,
@@ -140,11 +153,11 @@ def test_milvus_max_marginal_relevance_search_with_dynamic_field() -> None:
     )
 
 
-def test_milvus_add_extra() -> None:
+def test_milvus_add_extra(temp_milvus_db: Any) -> None:
     """Test end to end construction and MRR search."""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"page": i} for i in range(len(texts))]
-    docsearch = _milvus_from_texts(metadatas=metadatas)
+    docsearch = _milvus_from_texts(metadatas=metadatas, db_path=temp_milvus_db)
 
     docsearch.add_texts(texts, metadatas)
 
@@ -152,45 +165,47 @@ def test_milvus_add_extra() -> None:
     assert len(output) == 6
 
 
-def test_milvus_no_drop() -> None:
+def test_milvus_no_drop(temp_milvus_db: Any) -> None:
     """Test construction without dropping old data."""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"page": i} for i in range(len(texts))]
-    docsearch = _milvus_from_texts(metadatas=metadatas)
+    docsearch = _milvus_from_texts(metadatas=metadatas, db_path=temp_milvus_db)
     del docsearch
 
-    docsearch = _milvus_from_texts(metadatas=metadatas, drop=False)
+    docsearch = _milvus_from_texts(
+        metadatas=metadatas, drop=False, db_path=temp_milvus_db
+    )
 
     output = docsearch.similarity_search("foo", k=10)
     assert len(output) == 6
 
 
-def test_milvus_get_pks() -> None:
+def test_milvus_get_pks(temp_milvus_db: Any) -> None:
     """Test end to end construction and get pks with expr"""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"id": i} for i in range(len(texts))]
-    docsearch = _milvus_from_texts(metadatas=metadatas)
+    docsearch = _milvus_from_texts(metadatas=metadatas, db_path=temp_milvus_db)
     expr = "id in [1,2]"
     output = _get_pks(expr, docsearch)
     assert len(output) == 2
 
 
-def test_milvus_delete_entities() -> None:
+def test_milvus_delete_entities(temp_milvus_db: Any) -> None:
     """Test end to end construction and delete entities"""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"id": i} for i in range(len(texts))]
-    docsearch = _milvus_from_texts(metadatas=metadatas)
+    docsearch = _milvus_from_texts(metadatas=metadatas, db_path=temp_milvus_db)
     expr = "id in [1,2]"
     pks = _get_pks(expr, docsearch)
     result = docsearch.delete(pks)
     assert result.delete_count == 2  # type: ignore[attr-defined]
 
 
-def test_milvus_upsert_entities() -> None:
+def test_milvus_upsert_entities(temp_milvus_db: Any) -> None:
     """Test end to end construction and upsert entities"""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"id": i} for i in range(len(texts))]
-    docsearch = _milvus_from_texts(metadatas=metadatas)
+    docsearch = _milvus_from_texts(metadatas=metadatas, db_path=temp_milvus_db)
     expr = "id in [1,2]"
     pks = _get_pks(expr, docsearch)
     documents = [
@@ -201,11 +216,13 @@ def test_milvus_upsert_entities() -> None:
     assert len(ids) == 2  # type: ignore[arg-type]
 
 
-def test_milvus_enable_dynamic_field() -> None:
+def test_milvus_enable_dynamic_field(temp_milvus_db: Any) -> None:
     """Test end to end construction and enable dynamic field"""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"id": i} for i in range(len(texts))]
-    docsearch = _milvus_from_texts(metadatas=metadatas, enable_dynamic_field=True)
+    docsearch = _milvus_from_texts(
+        metadatas=metadatas, enable_dynamic_field=True, db_path=temp_milvus_db
+    )
     output = docsearch.similarity_search("foo", k=10)
     assert len(output) == 3
 
@@ -223,11 +240,13 @@ def test_milvus_enable_dynamic_field() -> None:
     }
 
 
-def test_milvus_disable_dynamic_field() -> None:
+def test_milvus_disable_dynamic_field(temp_milvus_db: Any) -> None:
     """Test end to end construction and disable dynamic field"""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"id": i} for i in range(len(texts))]
-    docsearch = _milvus_from_texts(metadatas=metadatas, enable_dynamic_field=False)
+    docsearch = _milvus_from_texts(
+        metadatas=metadatas, enable_dynamic_field=False, db_path=temp_milvus_db
+    )
     output = docsearch.similarity_search("foo", k=10)
     assert len(output) == 3
     # ["pk", "text", "vector", "id"]
@@ -255,11 +274,13 @@ def test_milvus_disable_dynamic_field() -> None:
         docsearch.add_texts(texts, new_metadatas)
 
 
-def test_milvus_metadata_field() -> None:
+def test_milvus_metadata_field(temp_milvus_db: Any) -> None:
     """Test end to end construction and use metadata field"""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"id": i} for i in range(len(texts))]
-    docsearch = _milvus_from_texts(metadatas=metadatas, metadata_field="metadata")
+    docsearch = _milvus_from_texts(
+        metadatas=metadatas, metadata_field="metadata", db_path=temp_milvus_db
+    )
     output = docsearch.similarity_search("foo", k=10)
     assert len(output) == 3
 
@@ -277,7 +298,7 @@ def test_milvus_metadata_field() -> None:
     }
 
 
-def test_milvus_enable_dynamic_field_with_partition_key() -> None:
+def test_milvus_enable_dynamic_field_with_partition_key(temp_milvus_db: Any) -> None:
     """
     Test end to end construction and enable dynamic field
     with partition_key_field
@@ -286,7 +307,10 @@ def test_milvus_enable_dynamic_field_with_partition_key() -> None:
     metadatas = [{"id": i, "namespace": f"name_{i}"} for i in range(len(texts))]
 
     docsearch = _milvus_from_texts(
-        metadatas=metadatas, enable_dynamic_field=True, partition_key_field="namespace"
+        metadatas=metadatas,
+        enable_dynamic_field=True,
+        partition_key_field="namespace",
+        db_path=temp_milvus_db,
     )
 
     # filter on a single namespace
@@ -318,19 +342,27 @@ def test_milvus_sparse_embeddings() -> None:
         "in a surreal world of nightmares and illusions, where the boundaries between "
         "reality and fantasy blur.",
     ]
-    sparse_embedding_func = BM25SparseEmbedding(corpus=texts)
-    docsearch = Milvus.from_texts(
-        embedding=sparse_embedding_func,
-        texts=texts,
-        connection_args={"uri": "./milvus_demo.db"},
-        drop_old=True,
-    )
+    try:
+        sparse_embedding_func = BM25SparseEmbedding(corpus=texts)
+    except LookupError:
+        import nltk  # type: ignore[import]
 
-    output = docsearch.similarity_search("Pilgrim", k=1)
+        nltk.download("punkt_tab")
+        sparse_embedding_func = BM25SparseEmbedding(corpus=texts)
+
+    with tempfile.NamedTemporaryFile(suffix=".db") as temp_db:
+        docsearch = Milvus.from_texts(
+            embedding=sparse_embedding_func,
+            texts=texts,
+            connection_args={"uri": temp_db.name},
+            drop_old=True,
+        )
+
+        output = docsearch.similarity_search("Pilgrim", k=1)
     assert "Pilgrim" in output[0].page_content
 
 
-def test_milvus_array_field() -> None:
+def test_milvus_array_field(temp_milvus_db: Any) -> None:
     """Manually specify metadata schema, including an array_field.
     For more information about array data type and filtering, please refer to
     https://milvus.io/docs/array_data_type.md
@@ -353,6 +385,7 @@ def test_milvus_array_field() -> None:
             #     "dtype": DataType.INT64,
             # }
         },
+        db_path=temp_milvus_db,
     )
     output = docsearch.similarity_search("foo", k=10, expr="array_field[0] < 2")
     assert len(output) == 2
@@ -366,6 +399,7 @@ def test_milvus_array_field() -> None:
     docsearch = _milvus_from_texts(
         enable_dynamic_field=True,
         metadatas=metadatas,
+        db_path=temp_milvus_db,
     )
     output = docsearch.similarity_search("foo", k=10, expr="array_field[0] < 2")
     assert len(output) == 2

libs/partners/nomic/poetry.lock

@@ -291,15 +291,18 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "idna"
-version = "3.8"
+version = "3.10"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "idna-3.8-py3-none-any.whl", hash = "sha256:050b4e5baadcd44d760cedbd2b8e639f2ff89bbc7a5730fcc662954303377aac"},
-    {file = "idna-3.8.tar.gz", hash = "sha256:d838c2c0ed6fced7693d5e8ab8e734d5f8fda53a039c0164afb0b82e771e3603"},
+    {file = "idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"},
+    {file = "idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9"},
 ]
 
+[package.extras]
+all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2)"]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -352,7 +355,7 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.0.dev1"
+version = "0.3.0"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.9,<4.0"
@@ -361,9 +364,12 @@ develop = true
 
 [package.dependencies]
 jsonpatch = "^1.33"
-langsmith = "^0.1.75"
+langsmith = "^0.1.117"
 packaging = ">=23.2,<25"
-pydantic = "^2.7.4"
+pydantic = [
+    {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
+]
 PyYAML = ">=5.3"
 tenacity = "^8.1.0,!=8.4.0"
 typing-extensions = ">=4.7"
@@ -374,13 +380,13 @@ url = "../../core"
 
 [[package]]
 name = "langsmith"
-version = "0.1.115"
+version = "0.1.120"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.115-py3-none-any.whl", hash = "sha256:04e35cfd4c2d4ff1ea10bb577ff43957b05ebb3d9eb4e06e200701f4a2b4ac9f"},
-    {file = "langsmith-0.1.115.tar.gz", hash = "sha256:3b775377d858d32354f3ee0dd1ed637068cfe9a1f13e7b3bfa82db1615cdffc9"},
+    {file = "langsmith-0.1.120-py3-none-any.whl", hash = "sha256:54d2785e301646c0988e0a69ebe4d976488c87b41928b358cb153b6ddd8db62b"},
+    {file = "langsmith-0.1.120.tar.gz", hash = "sha256:25499ca187b41bd89d784b272b97a8d76f60e0e21bdf20336e8a2aa6a9b23ac9"},
 ]
 
 [package.dependencies]
@@ -896,123 +902,123 @@ test = ["cffi", "hypothesis", "pandas", "pytest", "pytz"]
 
 [[package]]
 name = "pydantic"
-version = "2.9.0"
+version = "2.9.1"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pydantic-2.9.0-py3-none-any.whl", hash = "sha256:f66a7073abd93214a20c5f7b32d56843137a7a2e70d02111f3be287035c45370"},
-    {file = "pydantic-2.9.0.tar.gz", hash = "sha256:c7a8a9fdf7d100afa49647eae340e2d23efa382466a8d177efcd1381e9be5598"},
+    {file = "pydantic-2.9.1-py3-none-any.whl", hash = "sha256:7aff4db5fdf3cf573d4b3c30926a510a10e19a0774d38fc4967f78beb6deb612"},
+    {file = "pydantic-2.9.1.tar.gz", hash = "sha256:1363c7d975c7036df0db2b4a61f2e062fbc0aa5ab5f2772e0ffc7191a4f4bce2"},
 ]
 
 [package.dependencies]
-annotated-types = ">=0.4.0"
-pydantic-core = "2.23.2"
+annotated-types = ">=0.6.0"
+pydantic-core = "2.23.3"
 typing-extensions = [
     {version = ">=4.6.1", markers = "python_version < \"3.13\""},
     {version = ">=4.12.2", markers = "python_version >= \"3.13\""},
 ]
-tzdata = {version = "*", markers = "python_version >= \"3.9\""}
 
 [package.extras]
 email = ["email-validator (>=2.0.0)"]
+timezone = ["tzdata"]
 
 [[package]]
 name = "pydantic-core"
-version = "2.23.2"
+version = "2.23.3"
 description = "Core functionality for Pydantic validation and serialization"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "pydantic_core-2.23.3.tar.gz", hash = "sha256:3cb0f65d8b4121c1b015c60104a685feb929a29d7cf204387c7f2688c7974690"},
 ]
 
 [package.dependencies]
@@ -1137,13 +1143,13 @@ six = ">=1.5"
 
 [[package]]
 name = "pytz"
-version = "2024.1"
+version = "2024.2"
 description = "World timezone definitions, modern and historical"
 optional = false
 python-versions = "*"
 files = [
-    {file = "pytz-2024.1-py2.py3-none-any.whl", hash = "sha256:328171f4e3623139da4983451950b28e95ac706e13f3f2630a879749e7a8b319"},
-    {file = "pytz-2024.1.tar.gz", hash = "sha256:2a29735ea9c18baf14b448846bde5a48030ed267578472d8955cd0e7443a9812"},
+    {file = "pytz-2024.2-py2.py3-none-any.whl", hash = "sha256:31c7c1817eb7fae7ca4b8c7ee50c72f93aa2dd863de768e1ef4245d426aa0725"},
+    {file = "pytz-2024.2.tar.gz", hash = "sha256:2aa355083c50a0f93fa581709deac0c9ad65cca8a9e9beac660adcbd493c798a"},
 ]
 
 [[package]]
@@ -1231,13 +1237,13 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
 [[package]]
 name = "rich"
-version = "13.8.0"
+version = "13.8.1"
 description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
 optional = false
 python-versions = ">=3.7.0"
 files = [
-    {file = "rich-13.8.0-py3-none-any.whl", hash = "sha256:2e85306a063b9492dffc86278197a60cbece75bcb766022f3436f567cae11bdc"},
-    {file = "rich-13.8.0.tar.gz", hash = "sha256:a5ac1f1cd448ade0d59cc3356f7db7a7ccda2c8cbae9c7a90c28ff463d3e91f4"},
+    {file = "rich-13.8.1-py3-none-any.whl", hash = "sha256:1760a3c0848469b97b558fc61c85233e3dafb69c7a071b4d60c38099d3cd4c06"},
+    {file = "rich-13.8.1.tar.gz", hash = "sha256:8260cda28e3db6bf04d2d1ef4dbc03ba80a824c88b0e7668a0f23126a424844a"},
 ]
 
 [package.dependencies]
@@ -1379,13 +1385,13 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "2.2.2"
+version = "2.2.3"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "urllib3-2.2.2-py3-none-any.whl", hash = "sha256:a448b2f64d686155468037e1ace9f2d2199776e17f0a46610480d311f73e3472"},
-    {file = "urllib3-2.2.2.tar.gz", hash = "sha256:dd505485549a7a552833da5e6063639d0d177c04f23bc3864e41e5dc5f612168"},
+    {file = "urllib3-2.2.3-py3-none-any.whl", hash = "sha256:ca899ca043dcb1bafa3e262d73aa25c465bfb49e0bd9dd5d59f1d0acba2f8fac"},
+    {file = "urllib3-2.2.3.tar.gz", hash = "sha256:e7d814a81dad81e6caf2ec9fdedb284ecc9c73076b62654547cc64ccdcae26e9"},
 ]
 
 [package.extras]
@@ -1453,4 +1459,4 @@ dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<4.0"
-content-hash = "24232be0600d3c0c626bf6ac18c0a9b74a19106e203d705e6fab4b5f79a90d78"
+content-hash = "fe88f226a291f6e885d0fc561a3e3023a1f7d5829f25fa767ab78dff059ac110"

libs/partners/nomic/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langchain-nomic"
-version = "0.1.2"
+version = "0.1.3"
 description = "An integration package connecting Nomic and LangChain"
 authors = []
 readme = "README.md"
@@ -13,8 +13,8 @@ license = "MIT"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
-langchain-core = "^0.3.0.dev"
-nomic = "^3.0.29"
+langchain-core = ">=0.2.40,<0.4"
+nomic = "^3.1.2"
 pillow = "^10.3.0"
 
 [tool.poetry.group.test]

libs/partners/openai/langchain_openai/chat_models/base.py

@@ -33,6 +33,7 @@ from urllib.parse import urlparse
 
 import openai
 import tiktoken
+from langchain_core._api.deprecation import deprecated
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
@@ -966,6 +967,11 @@ class BaseChatOpenAI(BaseChatModel):
         num_tokens += 3
         return num_tokens
 
+    @deprecated(
+        since="0.2.1",
+        alternative="langchain_openai.chat_models.base.ChatOpenAI.bind_tools",
+        removal="0.3.0",
+    )
     def bind_functions(
         self,
         functions: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
@@ -1033,22 +1039,18 @@ class BaseChatOpenAI(BaseChatModel):
 
         Assumes model is compatible with OpenAI tool-calling API.
 
-        .. versionchanged:: 0.1.21
-
-            Support for ``strict`` argument added.
-
         Args:
             tools: A list of tool definitions to bind to this chat model.
                 Supports any tool definition handled by
                 :meth:`langchain_core.utils.function_calling.convert_to_openai_tool`.
-            tool_choice: Which tool to require the model to call.
-                Options are:
-                    - str of the form ``"<<tool_name>>"``: calls <<tool_name>> tool.
-                    - ``"auto"``: automatically selects a tool (including no tool).
-                    - ``"none"``: does not call a tool.
-                    - ``"any"`` or ``"required"`` or ``True``: force at least one tool to be called.
-                    - dict of the form ``{"type": "function", "function": {"name": <<tool_name>>}}``: calls <<tool_name>> tool.
-                    - ``False`` or ``None``: no effect, default OpenAI behavior.
+            tool_choice: Which tool to require the model to call. Options are:
+
+                - str of the form ``"<<tool_name>>"``: calls <<tool_name>> tool.
+                - ``"auto"``: automatically selects a tool (including no tool).
+                - ``"none"``: does not call a tool.
+                - ``"any"`` or ``"required"`` or ``True``: force at least one tool to be called.
+                - dict of the form ``{"type": "function", "function": {"name": <<tool_name>>}}``: calls <<tool_name>> tool.
+                - ``False`` or ``None``: no effect, default OpenAI behavior.
             strict: If True, model output is guaranteed to exactly match the JSON Schema
                 provided in the tool definition. If True, the input schema will be
                 validated according to
@@ -1056,11 +1058,13 @@ class BaseChatOpenAI(BaseChatModel):
                 If False, input schema will not be validated and model output will not
                 be validated.
                 If None, ``strict`` argument will not be passed to the model.
-
-                .. versionadded:: 0.1.21
-
             kwargs: Any additional parameters are passed directly to
-                ``self.bind(**kwargs)``.
+                :meth:`~langchain_openai.chat_models.base.ChatOpenAI.bind`.
+
+        .. versionchanged:: 0.1.21
+
+            Support for ``strict`` argument added.
+
         """  # noqa: E501
 
         formatted_tools = [

libs/partners/qdrant/poetry.lock

@@ -11,6 +11,9 @@ files = [
     {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
 ]
 
+[package.dependencies]
+typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
+
 [[package]]
 name = "anyio"
 version = "4.4.0"
@@ -620,7 +623,27 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.0.dev5"
+version = "0.2.40"
+description = "Building applications with LLMs through composability"
+optional = false
+python-versions = "<4.0,>=3.8.1"
+files = [
+    {file = "langchain_core-0.2.40-py3-none-any.whl", hash = "sha256:71fff5cafa4b9c82a3a716e985f071383be452c35d8cc3169b3a393e6857fc99"},
+    {file = "langchain_core-0.2.40.tar.gz", hash = "sha256:c838ea0c0b73475a8e58ced3e306b6d926ef063721abd164f237c8664916f502"},
+]
+
+[package.dependencies]
+jsonpatch = ">=1.33,<2.0"
+langsmith = ">=0.1.112,<0.2.0"
+packaging = ">=23.2,<25"
+pydantic = {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}
+PyYAML = ">=5.3"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
+typing-extensions = ">=4.7"
+
+[[package]]
+name = "langchain-core"
+version = "0.3.0"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.9,<4.0"
@@ -631,7 +654,10 @@ develop = true
 jsonpatch = "^1.33"
 langsmith = "^0.1.117"
 packaging = ">=23.2,<25"
-pydantic = "^2.7.4"
+pydantic = [
+    {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
+]
 PyYAML = ">=5.3"
 tenacity = "^8.1.0,!=8.4.0"
 typing-extensions = ">=4.7"
@@ -845,6 +871,43 @@ files = [
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 [[package]]
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 version = "1.26.4"
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 ]
 
 [package.extras]
@@ -2055,5 +2123,5 @@ fastembed = ["fastembed"]
 
 [metadata]
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+content-hash = "e6e76142c4669b46c06e2a65813fbff4e6e0844953ec091eebcc8cc468943ad6"

libs/partners/qdrant/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "langchain-qdrant"
-version = "0.2.0.dev1"
+version = "0.1.4"
 description = "An integration package connecting Qdrant and LangChain"
 authors = []
 readme = "README.md"
@@ -22,10 +22,17 @@ disallow_untyped_defs = true
 "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-qdrant%3D%3D0%22&expanded=true"
 
 [tool.poetry.dependencies]
-python = ">=3.9,<4.0"
-langchain-core = { version = "^0.3.0.dev5", allow-prereleases = true }
+python = ">=3.8.1,<4"
 qdrant-client = "^1.10.1"
 fastembed = { version = "^0.3.3", python = ">=3.9,<3.13", optional = true }
+pydantic = "^2.7.4"
+[[tool.poetry.dependencies.langchain-core]]
+version = ">=0.1.52,<0.4"
+python = ">=3.9"
+
+[[tool.poetry.dependencies.langchain-core]]
+version = ">=0.1.52,<0.3"
+python = "<3.9"
 
 [tool.poetry.extras]
 fastembed = ["fastembed"]
@@ -65,6 +72,25 @@ syrupy = "^4.0.2"
 pytest-watcher = "^0.3.4"
 pytest-asyncio = "^0.21.1"
 requests = "^2.31.0"
+[[tool.poetry.group.test.dependencies.langchain-core]]
+path = "../../core"
+develop = true
+python = ">=3.9"
+
+[[tool.poetry.group.test.dependencies.langchain-core]]
+version = ">=0.1.40,<0.3"
+python = "<3.9"
+
+
+[tool.poetry.group.dev.dependencies]
+[[tool.poetry.group.dev.dependencies.langchain-core]]
+path = "../../core"
+develop = true
+python = ">=3.9"
+
+[[tool.poetry.group.dev.dependencies.langchain-core]]
+version = ">=0.1.52,<0.3"
+python = "<3.9"
 
 [tool.poetry.group.codespell.dependencies]
 codespell = "^2.2.0"
@@ -77,15 +103,11 @@ ruff = "^0.5"
 [tool.poetry.group.typing.dependencies]
 mypy = "^1.10"
 simsimd = "^5.0.0"
-
-[tool.poetry.group.test.dependencies.langchain-core]
+[[tool.poetry.group.typing.dependencies.langchain-core]]
 path = "../../core"
 develop = true
+python = ">=3.9"
 
-[tool.poetry.group.dev.dependencies.langchain-core]
-path = "../../core"
-develop = true
-
-[tool.poetry.group.typing.dependencies.langchain-core]
-path = "../../core"
-develop = true
+[[tool.poetry.group.typing.dependencies.langchain-core]]
+version = ">=0.1.52,<0.3"
+python = "<3.9"

libs/partners/unstructured/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
 
 [[package]]
 name = "annotated-types"
@@ -219,6 +219,37 @@ files = [
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+    {file = "cffi-1.17.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:0984a4925a435b1da406122d4d7968dd861c1385afe3b45ba82b750f229811e2"},
+    {file = "cffi-1.17.1-cp313-cp313-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d01b12eeeb4427d3110de311e1774046ad344f5b1a7403101878976ecd7a10f3"},
+    {file = "cffi-1.17.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:706510fe141c86a69c8ddc029c7910003a17353970cff3b904ff0686a5927683"},
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+    {file = "cffi-1.17.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cdf5ce3acdfd1661132f2a9c19cac174758dc2352bfe37d98aa7512c6b7178b3"},
+    {file = "cffi-1.17.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:9755e4345d1ec879e3849e62222a18c7174d65a6a92d5b346b1863912168b595"},
+    {file = "cffi-1.17.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:f1e22e8c4419538cb197e4dd60acc919d7696e5ef98ee4da4e01d3f8cfa4cc5a"},
+    {file = "cffi-1.17.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:c03e868a0b3bc35839ba98e74211ed2b05d2119be4e8a0f224fba9384f1fe02e"},
+    {file = "cffi-1.17.1-cp39-cp39-win32.whl", hash = "sha256:e31ae45bc2e29f6b2abd0de1cc3b9d5205aa847cafaecb8af1476a609a2f6eb7"},
+    {file = "cffi-1.17.1-cp39-cp39-win_amd64.whl", hash = "sha256:d016c76bdd850f3c626af19b0542c9677ba156e4ee4fccfdd7848803533ef662"},
+    {file = "cffi-1.17.1.tar.gz", hash = "sha256:1c39c6016c32bc48dd54561950ebd6836e1670f2ae46128f67cf49e789c52824"},
 ]
 
 [package.dependencies]
@@ -1330,7 +1361,7 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.0.dev4"
+version = "0.3.0"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.9,<4.0"
@@ -1341,7 +1372,10 @@ develop = true
 jsonpatch = "^1.33"
 langsmith = "^0.1.117"
 packaging = ">=23.2,<25"
-pydantic = "^2.7.4"
+pydantic = [
+    {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
+]
 PyYAML = ">=5.3"
 tenacity = "^8.1.0,!=8.4.0"
 typing-extensions = ">=4.7"
@@ -2189,10 +2223,10 @@ files = [
 numpy = [
     {version = ">=1.21.0", markers = "python_version == \"3.9\" and platform_system == \"Darwin\" and platform_machine == \"arm64\""},
     {version = ">=1.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"aarch64\" and python_version >= \"3.8\" and python_version < \"3.10\" or python_version > \"3.9\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_system != \"Darwin\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_machine != \"arm64\" and python_version < \"3.10\""},
-    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
-    {version = ">=1.23.5", markers = "python_version >= \"3.11\" and python_version < \"3.12\""},
     {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\" and python_version < \"3.11\""},
     {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""},
+    {version = ">=1.23.5", markers = "python_version >= \"3.11\" and python_version < \"3.12\""},
+    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
 ]
 
 [[package]]
@@ -2338,8 +2372,8 @@ files = [
 [package.dependencies]
 numpy = [
     {version = ">=1.22.4", markers = "python_version < \"3.11\""},
-    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
     {version = ">=1.23.2", markers = "python_version == \"3.11\""},
+    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -4178,11 +4212,6 @@ files = [
     {file = "triton-3.0.0-1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:34e509deb77f1c067d8640725ef00c5cbfcb2052a1a3cb6a6d343841f92624eb"},
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-    {file = "triton-3.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:39b052da883351fdf6be3d93cedae6db3b8e3988d3b09ed221bccecfa9612230"},
-    {file = "triton-3.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cd34f19a8582af96e6291d4afce25dac08cb2a5d218c599163761e8e0827208e"},
-    {file = "triton-3.0.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0d5e10de8c011adeb7c878c6ce0dd6073b14367749e34467f1cff2bde1b78253"},
-    {file = "triton-3.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e8903767951bf86ec960b4fe4e21bc970055afc65e9d57e916d79ae3c93665e3"},
-    {file = "triton-3.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:41004fb1ae9a53fcb3e970745feb87f0e3c94c6ce1ba86e95fa3b8537894bef7"},
 ]
 
 [package.dependencies]
@@ -4570,4 +4599,4 @@ local = ["unstructured"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<4.0"
-content-hash = "718b27f8d6ed513284f436b03c830e3554248577346538beb9d2272bd9b05dc0"
+content-hash = "d96509ff31d482c1144571e83f0e7cbb384581d90e4e39ee992021c080d8f8ec"

libs/partners/unstructured/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langchain-unstructured"
-version = "0.1.3"
+version = "0.1.4"
 description = "An integration package connecting Unstructured and LangChain"
 authors = []
 readme = "README.md"
@@ -13,7 +13,7 @@ license = "MIT"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
-langchain-core = "^0.3.0.dev"
+langchain-core = "^0.3"
 unstructured-client = { version = "^0.25.0" }
 unstructured = { version = "^0.15.7", optional = true, python = "<3.13", extras = [
   "all-docs",

libs/partners/voyageai/poetry.lock

@@ -522,15 +522,18 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "idna"
-version = "3.8"
+version = "3.10"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "idna-3.8-py3-none-any.whl", hash = "sha256:050b4e5baadcd44d760cedbd2b8e639f2ff89bbc7a5730fcc662954303377aac"},
-    {file = "idna-3.8.tar.gz", hash = "sha256:d838c2c0ed6fced7693d5e8ab8e734d5f8fda53a039c0164afb0b82e771e3603"},
+    {file = "idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"},
+    {file = "idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9"},
 ]
 
+[package.extras]
+all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2)"]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -569,7 +572,7 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.0.dev1"
+version = "0.3.0"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.9,<4.0"
@@ -578,9 +581,12 @@ develop = true
 
 [package.dependencies]
 jsonpatch = "^1.33"
-langsmith = "^0.1.75"
+langsmith = "^0.1.117"
 packaging = ">=23.2,<25"
-pydantic = "^2.7.4"
+pydantic = [
+    {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
+]
 PyYAML = ">=5.3"
 tenacity = "^8.1.0,!=8.4.0"
 typing-extensions = ">=4.7"
@@ -591,13 +597,13 @@ url = "../../core"
 
 [[package]]
 name = "langsmith"
-version = "0.1.115"
+version = "0.1.120"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.115-py3-none-any.whl", hash = "sha256:04e35cfd4c2d4ff1ea10bb577ff43957b05ebb3d9eb4e06e200701f4a2b4ac9f"},
-    {file = "langsmith-0.1.115.tar.gz", hash = "sha256:3b775377d858d32354f3ee0dd1ed637068cfe9a1f13e7b3bfa82db1615cdffc9"},
+    {file = "langsmith-0.1.120-py3-none-any.whl", hash = "sha256:54d2785e301646c0988e0a69ebe4d976488c87b41928b358cb153b6ddd8db62b"},
+    {file = "langsmith-0.1.120.tar.gz", hash = "sha256:25499ca187b41bd89d784b272b97a8d76f60e0e21bdf20336e8a2aa6a9b23ac9"},
 ]
 
 [package.dependencies]
@@ -611,103 +617,108 @@ requests = ">=2,<3"
 
 [[package]]
 name = "multidict"
-version = "6.0.5"
+version = "6.1.0"
 description = "multidict implementation"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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-    {file = "multidict-6.0.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:411bf8515f3be9813d06004cac41ccf7d1cd46dfe233705933dd163b60e37600"},
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-    {file = "multidict-6.0.5-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:215ed703caf15f578dca76ee6f6b21b7603791ae090fbf1ef9d865571039ade5"},
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+[package.dependencies]
+typing-extensions = {version = ">=4.1.0", markers = "python_version < \"3.11\""}
+
 [[package]]
 name = "mypy"
 version = "1.11.2"
@@ -905,123 +916,123 @@ testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
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-tzdata = {version = "*", markers = "python_version >= \"3.9\""}
 
 [package.extras]
 email = ["email-validator (>=2.0.0)"]
+timezone = ["tzdata"]
 
 [[package]]
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-version = "2.23.2"
+version = "2.23.3"
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+    {file = "yarl-1.11.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:267b24f891e74eccbdff42241c5fb4f974de2d6271dcc7d7e0c9ae1079a560d9"},
+    {file = "yarl-1.11.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:6907daa4b9d7a688063ed098c472f96e8181733c525e03e866fb5db480a424df"},
+    {file = "yarl-1.11.1-cp39-cp39-win32.whl", hash = "sha256:14438dfc5015661f75f85bc5adad0743678eefee266ff0c9a8e32969d5d69f74"},
+    {file = "yarl-1.11.1-cp39-cp39-win_amd64.whl", hash = "sha256:94d0caaa912bfcdc702a4204cd5e2bb01eb917fc4f5ea2315aa23962549561b0"},
+    {file = "yarl-1.11.1-py3-none-any.whl", hash = "sha256:72bf26f66456baa0584eff63e44545c9f0eaed9b73cb6601b647c91f14c11f38"},
+    {file = "yarl-1.11.1.tar.gz", hash = "sha256:1bb2d9e212fb7449b8fb73bc461b51eaa17cc8430b4a87d87be7b25052d92f53"},
 ]
 
 [package.dependencies]
@@ -1491,4 +1491,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<4.0"
-content-hash = "5fee5c31cad94978d4a8d8e7ee4cf538d77aebc2d353f0ebd986f439365940f2"
+content-hash = "7743429cd1357000a4fe104cf06f7e7fd8207c318af580053965257bf858ab8e"

libs/partners/voyageai/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langchain-voyageai"
-version = "0.1.1"
+version = "0.1.2"
 description = "An integration package connecting VoyageAI and LangChain"
 authors = []
 readme = "README.md"
@@ -13,7 +13,7 @@ license = "MIT"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
-langchain-core = "^0.3.0.dev"
+langchain-core = "^0.3.0"
 voyageai = ">=0.2.1,<1"
 pydantic = ">=2,<3"
 

libs/standard-tests/langchain_standard_tests/integration_tests/chat_models.py

@@ -44,6 +44,13 @@ def magic_function_no_args() -> int:
     return 5
 
 
+class Joke(BaseModel):
+    """Joke to tell user."""
+
+    setup: str = Field(description="question to set up a joke")
+    punchline: str = Field(description="answer to resolve the joke")
+
+
 def _validate_tool_call_message(message: BaseMessage) -> None:
     assert isinstance(message, AIMessage)
     assert len(message.tool_calls) == 1
@@ -240,12 +247,6 @@ class ChatModelIntegrationTests(ChatModelTests):
         if not self.has_tool_calling:
             pytest.skip("Test requires tool calling.")
 
-        class Joke(BaseModel):
-            """Joke to tell user."""
-
-            setup: str = Field(description="question to set up a joke")
-            punchline: str = Field(description="answer to resolve the joke")
-
         # Pydantic class
         # Type ignoring since the interface only officially supports pydantic 1
         # or pydantic.v1.BaseModel but not pydantic.BaseModel from pydantic 2.
@@ -268,6 +269,33 @@ class ChatModelIntegrationTests(ChatModelTests):
         assert isinstance(chunk, dict)  # for mypy
         assert set(chunk.keys()) == {"setup", "punchline"}
 
+    async def test_structured_output_async(self, model: BaseChatModel) -> None:
+        """Test to verify structured output with a Pydantic model."""
+        if not self.has_tool_calling:
+            pytest.skip("Test requires tool calling.")
+
+        # Pydantic class
+        # Type ignoring since the interface only officially supports pydantic 1
+        # or pydantic.v1.BaseModel but not pydantic.BaseModel from pydantic 2.
+        # We'll need to do a pass updating the type signatures.
+        chat = model.with_structured_output(Joke)  # type: ignore[arg-type]
+        result = await chat.ainvoke("Tell me a joke about cats.")
+        assert isinstance(result, Joke)
+
+        async for chunk in chat.astream("Tell me a joke about cats."):
+            assert isinstance(chunk, Joke)
+
+        # Schema
+        chat = model.with_structured_output(Joke.model_json_schema())
+        result = await chat.ainvoke("Tell me a joke about cats.")
+        assert isinstance(result, dict)
+        assert set(result.keys()) == {"setup", "punchline"}
+
+        async for chunk in chat.astream("Tell me a joke about cats."):
+            assert isinstance(chunk, dict)
+        assert isinstance(chunk, dict)  # for mypy
+        assert set(chunk.keys()) == {"setup", "punchline"}
+
     @pytest.mark.skipif(PYDANTIC_MAJOR_VERSION != 2, reason="Test requires pydantic 2.")
     def test_structured_output_pydantic_2_v1(self, model: BaseChatModel) -> None:
         """Test to verify compatibility with pydantic.v1.BaseModel.

libs/standard-tests/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
 [[package]]
 name = "annotated-types"
@@ -244,15 +244,18 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "idna"
-version = "3.8"
+version = "3.10"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "idna-3.8-py3-none-any.whl", hash = "sha256:050b4e5baadcd44d760cedbd2b8e639f2ff89bbc7a5730fcc662954303377aac"},
-    {file = "idna-3.8.tar.gz", hash = "sha256:d838c2c0ed6fced7693d5e8ab8e734d5f8fda53a039c0164afb0b82e771e3603"},
+    {file = "idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"},
+    {file = "idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9"},
 ]
 
+[package.extras]
+all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2)"]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -291,7 +294,7 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.0.dev4"
+version = "0.3.0"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.9,<4.0"
@@ -300,9 +303,12 @@ develop = true
 
 [package.dependencies]
 jsonpatch = "^1.33"
-langsmith = "^0.1.112"
+langsmith = "^0.1.117"
 packaging = ">=23.2,<25"
-pydantic = "^2.7.4"
+pydantic = [
+    {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
+]
 PyYAML = ">=5.3"
 tenacity = "^8.1.0,!=8.4.0"
 typing-extensions = ">=4.7"
@@ -313,21 +319,21 @@ url = "../core"
 
 [[package]]
 name = "langsmith"
-version = "0.1.117"
+version = "0.1.120"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.117-py3-none-any.whl", hash = "sha256:e936ee9bcf8293b0496df7ba462a3702179fbe51f9dc28744b0fbec0dbf206ae"},
-    {file = "langsmith-0.1.117.tar.gz", hash = "sha256:a1b532f49968b9339bcaff9118d141846d52ed3d803f342902e7448edf1d662b"},
+    {file = "langsmith-0.1.120-py3-none-any.whl", hash = "sha256:54d2785e301646c0988e0a69ebe4d976488c87b41928b358cb153b6ddd8db62b"},
+    {file = "langsmith-0.1.120.tar.gz", hash = "sha256:25499ca187b41bd89d784b272b97a8d76f60e0e21bdf20336e8a2aa6a9b23ac9"},
 ]
 
 [package.dependencies]
 httpx = ">=0.23.0,<1"
 orjson = ">=3.9.14,<4.0.0"
 pydantic = [
-    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
     {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
 ]
 requests = ">=2,<3"
 
@@ -499,8 +505,8 @@ files = [
 annotated-types = ">=0.6.0"
 pydantic-core = "2.23.3"
 typing-extensions = [
-    {version = ">=4.12.2", markers = "python_version >= \"3.13\""},
     {version = ">=4.6.1", markers = "python_version < \"3.13\""},
+    {version = ">=4.12.2", markers = "python_version >= \"3.13\""},
 ]
 
 [package.extras]
@@ -821,13 +827,13 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "2.2.2"
+version = "2.2.3"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "urllib3-2.2.2-py3-none-any.whl", hash = "sha256:a448b2f64d686155468037e1ace9f2d2199776e17f0a46610480d311f73e3472"},
-    {file = "urllib3-2.2.2.tar.gz", hash = "sha256:dd505485549a7a552833da5e6063639d0d177c04f23bc3864e41e5dc5f612168"},
+    {file = "urllib3-2.2.3-py3-none-any.whl", hash = "sha256:ca899ca043dcb1bafa3e262d73aa25c465bfb49e0bd9dd5d59f1d0acba2f8fac"},
+    {file = "urllib3-2.2.3.tar.gz", hash = "sha256:e7d814a81dad81e6caf2ec9fdedb284ecc9c73076b62654547cc64ccdcae26e9"},
 ]
 
 [package.extras]
@@ -839,4 +845,4 @@ zstd = ["zstandard (>=0.18.0)"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<4.0"
-content-hash = "22c1c9b3fe4a45afb1baf05e3757a6e5cc502388e02c4452b13cbf266a61165d"
+content-hash = "ba5e8730ffc3c7a10aded2e9625abaa51299be5b5f499d946b1ccb8f78341eb7"

libs/standard-tests/pyproject.toml

@@ -12,7 +12,7 @@ license = "MIT"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
-langchain-core = { version = ">=0.3.0.dev1", allow-prereleases = true }
+langchain-core = "^0.3.0"
 pytest = ">=7,<9"
 httpx = "^0.27.0"
 syrupy = "^4"
@@ -82,4 +82,3 @@ markers = [
   "compile: mark placeholder test used to compile integration tests without running them",
 ]
 asyncio_mode = "auto"
-

pyproject.toml

@@ -9,14 +9,13 @@ repository = "https://www.github.com/langchain-ai/langchain"
 
 
 [tool.poetry.dependencies]
-python = ">=3.8.1,<4.0"
+python = ">=3.9,<4.0"
 
 [tool.poetry.group.docs.dependencies]
-autodoc_pydantic = "^1"
-sphinx = "^7"
-myst-parser = "^3"
-sphinx-autobuild = "^2021"
-pydata-sphinx-theme = "^0.14"
+autodoc_pydantic = "^2"
+sphinx = ">=7"
+sphinx-autobuild = ">=2024"
+pydata-sphinx-theme = ">=0.15"
 toml = "^0.10.2"
 
 [tool.poetry.group.lint.dependencies]