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chore: update references to use the latest version of Claude-3.5 Sonnet (#32594)

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Mason Daugherty 2025-08-18 14:11:15 -04:00 committed by GitHub
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11 changed files with 34 additions and 34 deletions
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16
docs/docs/how_to/chat_models_universal_init.ipynb
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@ -159,7 +159,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 8, "execution_count": null,
"id": "321e3036-abd2-4e1f-bcc6-606efd036954", "id": "321e3036-abd2-4e1f-bcc6-606efd036954",
"metadata": { "metadata": {
"execution": { "execution": {
@ -183,7 +183,7 @@
], ],
"source": [ "source": [
"configurable_model.invoke(\n", "configurable_model.invoke(\n",
" \"what's your name\", config={\"configurable\": {\"model\": \"claude-3-5-sonnet-20240620\"}}\n", " \"what's your name\", config={\"configurable\": {\"model\": \"claude-3-5-sonnet-latest\"}}\n",
")" ")"
] ]
}, },
@ -234,7 +234,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": null,
"id": "6c8755ba-c001-4f5a-a497-be3f1db83244", "id": "6c8755ba-c001-4f5a-a497-be3f1db83244",
"metadata": { "metadata": {
"execution": { "execution": {
@ -261,7 +261,7 @@
" \"what's your name\",\n", " \"what's your name\",\n",
" config={\n", " config={\n",
" \"configurable\": {\n", " \"configurable\": {\n",
" \"first_model\": \"claude-3-5-sonnet-20240620\",\n", " \"first_model\": \"claude-3-5-sonnet-latest\",\n",
" \"first_temperature\": 0.5,\n", " \"first_temperature\": 0.5,\n",
" \"first_max_tokens\": 100,\n", " \"first_max_tokens\": 100,\n",
" }\n", " }\n",
@ -336,7 +336,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 9, "execution_count": null,
"id": "e57dfe9f-cd24-4e37-9ce9-ccf8daf78f89", "id": "e57dfe9f-cd24-4e37-9ce9-ccf8daf78f89",
"metadata": { "metadata": {
"execution": { "execution": {
@ -368,14 +368,14 @@
"source": [ "source": [
"llm_with_tools.invoke(\n", "llm_with_tools.invoke(\n",
" \"what's bigger in 2024 LA or NYC\",\n", " \"what's bigger in 2024 LA or NYC\",\n",
" config={\"configurable\": {\"model\": \"claude-3-5-sonnet-20240620\"}},\n", " config={\"configurable\": {\"model\": \"claude-3-5-sonnet-latest\"}},\n",
").tool_calls" ").tool_calls"
] ]
} }
], ],
"metadata": { "metadata": {
"kernelspec": { "kernelspec": {
"display_name": "langchain", "display_name": "langchain-monorepo",
"language": "python", "language": "python",
"name": "python3" "name": "python3"
}, },
@ -389,7 +389,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.10.16" "version": "3.12.11"
} }
}, },
"nbformat": 4, "nbformat": 4,

4
docs/docs/how_to/tool_artifacts.ipynb
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@ -147,7 +147,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": null,
"id": "74de0286-b003-4b48-9cdd-ecab435515ca", "id": "74de0286-b003-4b48-9cdd-ecab435515ca",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -157,7 +157,7 @@
"\n", "\n",
"from langchain_anthropic import ChatAnthropic\n", "from langchain_anthropic import ChatAnthropic\n",
"\n", "\n",
"llm = ChatAnthropic(model=\"claude-3-5-sonnet-20240620\", temperature=0)" "llm = ChatAnthropic(model=\"claude-3-5-sonnet-latest\", temperature=0)"
] ]
}, },
{ {

4
docs/docs/how_to/tool_stream_events.ipynb
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@ -38,7 +38,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
@ -53,7 +53,7 @@
"if \"ANTHROPIC_API_KEY\" not in os.environ:\n", "if \"ANTHROPIC_API_KEY\" not in os.environ:\n",
" os.environ[\"ANTHROPIC_API_KEY\"] = getpass()\n", " os.environ[\"ANTHROPIC_API_KEY\"] = getpass()\n",
"\n", "\n",
"model = ChatAnthropic(model=\"claude-3-5-sonnet-20240620\", temperature=0)" "model = ChatAnthropic(model=\"claude-3-5-sonnet-latest\", temperature=0)"
] ]
}, },
{ {

4
docs/docs/integrations/chat/anthropic.ipynb
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@ -124,7 +124,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": null,
"id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae", "id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -132,7 +132,7 @@
"from langchain_anthropic import ChatAnthropic\n", "from langchain_anthropic import ChatAnthropic\n",
"\n", "\n",
"llm = ChatAnthropic(\n", "llm = ChatAnthropic(\n",
" model=\"claude-3-5-sonnet-20240620\",\n", " model=\"claude-3-5-sonnet-latest\",\n",
" temperature=0,\n", " temperature=0,\n",
" max_tokens=1024,\n", " max_tokens=1024,\n",
" timeout=None,\n", " timeout=None,\n",

4
docs/docs/integrations/chat/bedrock.ipynb
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@ -129,7 +129,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": null,
"id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae", "id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -137,7 +137,7 @@
"from langchain_aws import ChatBedrockConverse\n", "from langchain_aws import ChatBedrockConverse\n",
"\n", "\n",
"llm = ChatBedrockConverse(\n", "llm = ChatBedrockConverse(\n",
" model_id=\"anthropic.claude-3-5-sonnet-20240620-v1:0\",\n", " model_id=\"anthropic.claude-3-5-sonnet-latest-v1:0\",\n",
" # region_name=...,\n", " # region_name=...,\n",
" # aws_access_key_id=...,\n", " # aws_access_key_id=...,\n",
" # aws_secret_access_key=...,\n", " # aws_secret_access_key=...,\n",

2
docs/docs/integrations/tools/stripe.ipynb
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@ -153,7 +153,7 @@
"from langgraph.prebuilt import create_react_agent\n", "from langgraph.prebuilt import create_react_agent\n",
"\n", "\n",
"llm = ChatAnthropic(\n", "llm = ChatAnthropic(\n",
" model=\"claude-3-5-sonnet-20240620\",\n", " model=\"claude-3-5-sonnet-latest\",\n",
")\n", ")\n",
"\n", "\n",
"langgraph_agent_executor = create_react_agent(llm, stripe_agent_toolkit.get_tools())\n", "langgraph_agent_executor = create_react_agent(llm, stripe_agent_toolkit.get_tools())\n",

4
docs/docs/troubleshooting/errors/MESSAGE_COERCION_FAILURE.ipynb
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@ -45,7 +45,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -74,7 +74,7 @@
"\n", "\n",
"uncoercible_message = {\"role\": \"HumanMessage\", \"random_field\": \"random value\"}\n", "uncoercible_message = {\"role\": \"HumanMessage\", \"random_field\": \"random value\"}\n",
"\n", "\n",
"model = ChatAnthropic(model=\"claude-3-5-sonnet-20240620\")\n", "model = ChatAnthropic(model=\"claude-3-5-sonnet-latest\")\n",
"\n", "\n",
"model.invoke([uncoercible_message])" "model.invoke([uncoercible_message])"
] ]

2
docs/docs/tutorials/summarization.ipynb
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@ -236,7 +236,7 @@
"We can use [create_stuff_documents_chain](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.combine_documents.stuff.create_stuff_documents_chain.html), especially if using larger context window models such as:\n", "We can use [create_stuff_documents_chain](https://python.langchain.com/api_reference/langchain/chains/langchain.chains.combine_documents.stuff.create_stuff_documents_chain.html), especially if using larger context window models such as:\n",
"\n", "\n",
"* 128k token OpenAI `gpt-4o` \n", "* 128k token OpenAI `gpt-4o` \n",
"* 200k token Anthropic `claude-3-5-sonnet-20240620`\n", "* 200k token Anthropic `claude-3-5-sonnet-latest`\n",
"\n", "\n",
"The chain will take a list of documents, insert them all into a prompt, and pass that prompt to an LLM:" "The chain will take a list of documents, insert them all into a prompt, and pass that prompt to an LLM:"
] ]

4
libs/langchain/langchain/chat_models/base.py
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@ -230,7 +230,7 @@ def init_chat_model(
"what's your name", "what's your name",
config={ config={
"configurable": { "configurable": {
"foo_model": "anthropic:claude-3-5-sonnet-20240620", "foo_model": "anthropic:claude-3-5-sonnet-latest",
"foo_temperature": 0.6 "foo_temperature": 0.6
} }
} }
@ -272,7 +272,7 @@ def init_chat_model(
configurable_model_with_tools.invoke( configurable_model_with_tools.invoke(
"Which city is hotter today and which is bigger: LA or NY?", "Which city is hotter today and which is bigger: LA or NY?",
config={"configurable": {"model": "claude-3-5-sonnet-20240620"}} config={"configurable": {"model": "claude-3-5-sonnet-latest"}}
) )
# Claude-3.5 sonnet response with tools # Claude-3.5 sonnet response with tools

4
libs/langchain_v1/langchain/chat_models/base.py
View File

@ -224,7 +224,7 @@ def init_chat_model(
"what's your name", "what's your name",
config={ config={
"configurable": { "configurable": {
"foo_model": "anthropic:claude-3-5-sonnet-20240620", "foo_model": "anthropic:claude-3-5-sonnet-latest",
"foo_temperature": 0.6 "foo_temperature": 0.6
} }
} }
@ -266,7 +266,7 @@ def init_chat_model(
configurable_model_with_tools.invoke( configurable_model_with_tools.invoke(
"Which city is hotter today and which is bigger: LA or NY?", "Which city is hotter today and which is bigger: LA or NY?",
config={"configurable": {"model": "claude-3-5-sonnet-20240620"}} config={"configurable": {"model": "claude-3-5-sonnet-latest"}}
) )
# Claude-3.5 sonnet response with tools # Claude-3.5 sonnet response with tools

20
libs/partners/anthropic/langchain_anthropic/chat_models.py
View File

@ -1731,7 +1731,7 @@ class ChatAnthropic(BaseChatModel):
product: str = Field(..., description="The product to look up.") product: str = Field(..., description="The product to look up.")
llm = ChatAnthropic(model="claude-3-5-sonnet-20240620", temperature=0) llm = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
llm_with_tools = llm.bind_tools([GetWeather, GetPrice]) llm_with_tools = llm.bind_tools([GetWeather, GetPrice])
llm_with_tools.invoke("what is the weather like in San Francisco",) llm_with_tools.invoke("what is the weather like in San Francisco",)
# -> AIMessage( # -> AIMessage(
@ -1739,7 +1739,7 @@ class ChatAnthropic(BaseChatModel):
# {'text': '<thinking>\nBased on the user\'s question, the relevant function to call is GetWeather, which requires the "location" parameter.\n\nThe user has directly specified the location as "San Francisco". Since San Francisco is a well known city, I can reasonably infer they mean San Francisco, CA without needing the state specified.\n\nAll the required parameters are provided, so I can proceed with the API call.\n</thinking>', 'type': 'text'}, # {'text': '<thinking>\nBased on the user\'s question, the relevant function to call is GetWeather, which requires the "location" parameter.\n\nThe user has directly specified the location as "San Francisco". Since San Francisco is a well known city, I can reasonably infer they mean San Francisco, CA without needing the state specified.\n\nAll the required parameters are provided, so I can proceed with the API call.\n</thinking>', 'type': 'text'},
# {'text': None, 'type': 'tool_use', 'id': 'toolu_01SCgExKzQ7eqSkMHfygvYuu', 'name': 'GetWeather', 'input': {'location': 'San Francisco, CA'}} # {'text': None, 'type': 'tool_use', 'id': 'toolu_01SCgExKzQ7eqSkMHfygvYuu', 'name': 'GetWeather', 'input': {'location': 'San Francisco, CA'}}
# ], # ],
# response_metadata={'id': 'msg_01GM3zQtoFv8jGQMW7abLnhi', 'model': 'claude-3-5-sonnet-20240620', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 487, 'output_tokens': 145}}, # response_metadata={'id': 'msg_01GM3zQtoFv8jGQMW7abLnhi', 'model': 'claude-3-5-sonnet-latest', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 487, 'output_tokens': 145}},
# id='run-87b1331e-9251-4a68-acef-f0a018b639cc-0' # id='run-87b1331e-9251-4a68-acef-f0a018b639cc-0'
# ) # )
@ -1761,7 +1761,7 @@ class ChatAnthropic(BaseChatModel):
product: str = Field(..., description="The product to look up.") product: str = Field(..., description="The product to look up.")
llm = ChatAnthropic(model="claude-3-5-sonnet-20240620", temperature=0) llm = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
llm_with_tools = llm.bind_tools([GetWeather, GetPrice], tool_choice="any") llm_with_tools = llm.bind_tools([GetWeather, GetPrice], tool_choice="any")
llm_with_tools.invoke("what is the weather like in San Francisco",) llm_with_tools.invoke("what is the weather like in San Francisco",)
@ -1784,7 +1784,7 @@ class ChatAnthropic(BaseChatModel):
product: str = Field(..., description="The product to look up.") product: str = Field(..., description="The product to look up.")
llm = ChatAnthropic(model="claude-3-5-sonnet-20240620", temperature=0) llm = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
llm_with_tools = llm.bind_tools([GetWeather, GetPrice], tool_choice="GetWeather") llm_with_tools = llm.bind_tools([GetWeather, GetPrice], tool_choice="GetWeather")
llm_with_tools.invoke("what is the weather like in San Francisco",) llm_with_tools.invoke("what is the weather like in San Francisco",)
@ -1816,7 +1816,7 @@ class ChatAnthropic(BaseChatModel):
# We need to pass in extra headers to enable use of the beta cache # We need to pass in extra headers to enable use of the beta cache
# control API. # control API.
llm = ChatAnthropic( llm = ChatAnthropic(
model="claude-3-5-sonnet-20240620", model="claude-3-5-sonnet-latest",
temperature=0, temperature=0,
) )
llm_with_tools = llm.bind_tools([GetWeather, cached_price_tool]) llm_with_tools = llm.bind_tools([GetWeather, cached_price_tool])
@ -1826,13 +1826,13 @@ class ChatAnthropic(BaseChatModel):
.. code-block:: python .. code-block:: python
AIMessage(content=[{'text': "Certainly! I can help you find out the current weather in San Francisco. To get this information, I'll use the GetWeather function. Let me fetch that data for you right away.", 'type': 'text'}, {'id': 'toolu_01TS5h8LNo7p5imcG7yRiaUM', 'input': {'location': 'San Francisco, CA'}, 'name': 'GetWeather', 'type': 'tool_use'}], response_metadata={'id': 'msg_01Xg7Wr5inFWgBxE5jH9rpRo', 'model': 'claude-3-5-sonnet-20240620', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 171, 'output_tokens': 96, 'cache_creation_input_tokens': 1470, 'cache_read_input_tokens': 0}}, id='run-b36a5b54-5d69-470e-a1b0-b932d00b089e-0', tool_calls=[{'name': 'GetWeather', 'args': {'location': 'San Francisco, CA'}, 'id': 'toolu_01TS5h8LNo7p5imcG7yRiaUM', 'type': 'tool_call'}], usage_metadata={'input_tokens': 171, 'output_tokens': 96, 'total_tokens': 267}) AIMessage(content=[{'text': "Certainly! I can help you find out the current weather in San Francisco. To get this information, I'll use the GetWeather function. Let me fetch that data for you right away.", 'type': 'text'}, {'id': 'toolu_01TS5h8LNo7p5imcG7yRiaUM', 'input': {'location': 'San Francisco, CA'}, 'name': 'GetWeather', 'type': 'tool_use'}], response_metadata={'id': 'msg_01Xg7Wr5inFWgBxE5jH9rpRo', 'model': 'claude-3-5-sonnet-latest', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 171, 'output_tokens': 96, 'cache_creation_input_tokens': 1470, 'cache_read_input_tokens': 0}}, id='run-b36a5b54-5d69-470e-a1b0-b932d00b089e-0', tool_calls=[{'name': 'GetWeather', 'args': {'location': 'San Francisco, CA'}, 'id': 'toolu_01TS5h8LNo7p5imcG7yRiaUM', 'type': 'tool_call'}], usage_metadata={'input_tokens': 171, 'output_tokens': 96, 'total_tokens': 267})
If we invoke the tool again, we can see that the "usage" information in the AIMessage.response_metadata shows that we had a cache hit: If we invoke the tool again, we can see that the "usage" information in the AIMessage.response_metadata shows that we had a cache hit:
.. code-block:: python .. code-block:: python
AIMessage(content=[{'text': 'To get the current weather in San Francisco, I can use the GetWeather function. Let me check that for you.', 'type': 'text'}, {'id': 'toolu_01HtVtY1qhMFdPprx42qU2eA', 'input': {'location': 'San Francisco, CA'}, 'name': 'GetWeather', 'type': 'tool_use'}], response_metadata={'id': 'msg_016RfWHrRvW6DAGCdwB6Ac64', 'model': 'claude-3-5-sonnet-20240620', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 171, 'output_tokens': 82, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 1470}}, id='run-88b1f825-dcb7-4277-ac27-53df55d22001-0', tool_calls=[{'name': 'GetWeather', 'args': {'location': 'San Francisco, CA'}, 'id': 'toolu_01HtVtY1qhMFdPprx42qU2eA', 'type': 'tool_call'}], usage_metadata={'input_tokens': 171, 'output_tokens': 82, 'total_tokens': 253}) AIMessage(content=[{'text': 'To get the current weather in San Francisco, I can use the GetWeather function. Let me check that for you.', 'type': 'text'}, {'id': 'toolu_01HtVtY1qhMFdPprx42qU2eA', 'input': {'location': 'San Francisco, CA'}, 'name': 'GetWeather', 'type': 'tool_use'}], response_metadata={'id': 'msg_016RfWHrRvW6DAGCdwB6Ac64', 'model': 'claude-3-5-sonnet-latest', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 171, 'output_tokens': 82, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 1470}}, id='run-88b1f825-dcb7-4277-ac27-53df55d22001-0', tool_calls=[{'name': 'GetWeather', 'args': {'location': 'San Francisco, CA'}, 'id': 'toolu_01HtVtY1qhMFdPprx42qU2eA', 'type': 'tool_call'}], usage_metadata={'input_tokens': 171, 'output_tokens': 82, 'total_tokens': 253})
""" # noqa: E501 """ # noqa: E501
formatted_tools = [ formatted_tools = [
@ -1929,7 +1929,7 @@ class ChatAnthropic(BaseChatModel):
answer: str answer: str
justification: str justification: str
llm = ChatAnthropic(model="claude-3-5-sonnet-20240620", temperature=0) llm = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
structured_llm = llm.with_structured_output(AnswerWithJustification) structured_llm = llm.with_structured_output(AnswerWithJustification)
structured_llm.invoke("What weighs more a pound of bricks or a pound of feathers") structured_llm.invoke("What weighs more a pound of bricks or a pound of feathers")
@ -1951,7 +1951,7 @@ class ChatAnthropic(BaseChatModel):
answer: str answer: str
justification: str justification: str
llm = ChatAnthropic(model="claude-3-5-sonnet-20240620", temperature=0) llm = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
structured_llm = llm.with_structured_output(AnswerWithJustification, include_raw=True) structured_llm = llm.with_structured_output(AnswerWithJustification, include_raw=True)
structured_llm.invoke("What weighs more a pound of bricks or a pound of feathers") structured_llm.invoke("What weighs more a pound of bricks or a pound of feathers")
@ -1979,7 +1979,7 @@ class ChatAnthropic(BaseChatModel):
"required": ["answer", "justification"] "required": ["answer", "justification"]
} }
} }
llm = ChatAnthropic(model="claude-3-5-sonnet-20240620", temperature=0) llm = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
structured_llm = llm.with_structured_output(schema) structured_llm = llm.with_structured_output(schema)
structured_llm.invoke("What weighs more a pound of bricks or a pound of feathers") structured_llm.invoke("What weighs more a pound of bricks or a pound of feathers")