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langchain[patch]: init_chat_model xai support (#29849)
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@ -98,9 +98,12 @@ def init_chat_model(
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installed.
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Args:
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model: The name of the model, e.g. "gpt-4o", "claude-3-opus-20240229".
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model_provider: The model provider. Supported model_provider values and the
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corresponding integration package are:
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model: The name of the model, e.g. "o3-mini", "claude-3-5-sonnet-latest". You can
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also specify model and model provider in a single argument using
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'{model_provider}:{model}' format, e.g. "openai:o1".
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model_provider: The model provider if not specified as part of model arg (see
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above). Supported model_provider values and the corresponding integration
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package are:
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- 'openai' -> langchain-openai
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- 'anthropic' -> langchain-anthropic
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@ -118,8 +121,9 @@ def init_chat_model(
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- 'ollama' -> langchain-ollama
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- 'google_anthropic_vertex' -> langchain-google-vertexai
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- 'deepseek' -> langchain-deepseek
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- 'ibm' -> langchain-ibm
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- 'ibm' -> langchain-ibm
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- 'nvidia' -> langchain-nvidia-ai-endpoints
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- 'xai' -> langchain-xai
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Will attempt to infer model_provider from model if not specified. The
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following providers will be inferred based on these model prefixes:
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@ -131,6 +135,8 @@ def init_chat_model(
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- 'command...' -> 'cohere'
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- 'accounts/fireworks...' -> 'fireworks'
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- 'mistral...' -> 'mistralai'
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- 'deepseek...' -> 'deepseek'
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- 'grok...' -> 'xai'
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configurable_fields: Which model parameters are
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configurable:
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@ -182,13 +188,13 @@ def init_chat_model(
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# pip install langchain langchain-openai langchain-anthropic langchain-google-vertexai
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from langchain.chat_models import init_chat_model
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gpt_4o = init_chat_model("gpt-4o", model_provider="openai", temperature=0)
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claude_opus = init_chat_model("claude-3-opus-20240229", model_provider="anthropic", temperature=0)
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gemini_15 = init_chat_model("gemini-1.5-pro", model_provider="google_vertexai", temperature=0)
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o3_mini = init_chat_model("openai:o3-mini", temperature=0)
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claude_sonnet = init_chat_model("anthropic:claude-3-5-sonnet-latest", temperature=0)
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gemini_2_flash = init_chat_model("google_vertexai:gemini-2.0-flash", temperature=0)
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gpt_4o.invoke("what's your name")
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claude_opus.invoke("what's your name")
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gemini_15.invoke("what's your name")
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o3_mini.invoke("what's your name")
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claude_sonnet.invoke("what's your name")
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gemini_2_flash.invoke("what's your name")
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.. dropdown:: Partially configurable model with no default
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@ -209,7 +215,7 @@ def init_chat_model(
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configurable_model.invoke(
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"what's your name",
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config={"configurable": {"model": "claude-3-5-sonnet-20240620"}}
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config={"configurable": {"model": "claude-3-5-sonnet-latest"}}
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)
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# claude-3.5 sonnet response
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@ -221,8 +227,7 @@ def init_chat_model(
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from langchain.chat_models import init_chat_model
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configurable_model_with_default = init_chat_model(
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"gpt-4o",
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model_provider="openai",
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"openai:gpt-4o",
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configurable_fields="any", # this allows us to configure other params like temperature, max_tokens, etc at runtime.
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config_prefix="foo",
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temperature=0
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@ -235,8 +240,7 @@ def init_chat_model(
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"what's your name",
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config={
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"configurable": {
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"foo_model": "claude-3-5-sonnet-20240620",
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"foo_model_provider": "anthropic",
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"foo_model": "anthropic:claude-3-5-sonnet-20240620",
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"foo_temperature": 0.6
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}
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}
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@ -290,18 +294,22 @@ def init_chat_model(
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.. versionchanged:: 0.2.12
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Support for ChatOllama via langchain-ollama package added
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Support for Ollama via langchain-ollama package added
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(langchain_ollama.ChatOllama). Previously,
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the now-deprecated langchain-community version of Ollama was imported
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(langchain_community.chat_models.ChatOllama).
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Support for langchain_aws.ChatBedrockConverse added
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Support for AWS Bedrock models via the Converse API added
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(model_provider="bedrock_converse").
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.. versionchanged:: 0.3.5
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Out of beta.
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.. versionchanged:: 0.3.19
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Support for Deepseek, IBM, Nvidia, and xAI models added.
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""" # noqa: E501
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if not model and not configurable_fields:
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configurable_fields = ("model", "model_provider")
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@ -434,6 +442,11 @@ def _init_chat_model_helper(
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from langchain_ibm import ChatWatsonx
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return ChatWatsonx(model_id=model, **kwargs)
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elif model_provider == "xai":
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_check_pkg("langchain_xai")
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from langchain_xai import ChatXAI
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return ChatXAI(model=model, **kwargs)
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else:
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supported = ", ".join(_SUPPORTED_PROVIDERS)
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raise ValueError(
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@ -478,6 +491,10 @@ def _attempt_infer_model_provider(model_name: str) -> Optional[str]:
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return "bedrock"
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elif model_name.startswith("mistral"):
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return "mistralai"
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elif model_name.startswith("deepseek"):
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return "deepseek"
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elif model_name.startswith("grok"):
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return "xai"
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else:
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return None
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