Merge branch 'master' into snova-jorgep/bind_tools_sambanova_chat_models

docs/cassettes/summarize_refine_0701bb7d-fbc6-497e-a577-25d56e6e43c6.msgpack.zlib

@@ -1 +1 @@
-eNrtlglUE2cewMNiXWvdFteT1uoUsdWWCZNkcoGoyCUiBATk8GAnM1+SgclMmJkAifYQ64laR6y1Xm01EEEExQNEsbZ9nvXc5wXaw1Vr1fWoLWppa/dLgAqru+91V99rd528N5P5vv/8v//5fb9Cdx7gBZpjfSpoVgQ8QYrwRSgudPMg1w4E8c1SKxAtHOVKNCSnrLbzdMPLFlG0CSHBwYSNlnM2wBK0nOSswXmKYNJCiMHwv40BXjUuI0c5GiomB1iBIBBmIASEIOMnB5AcXIoV4UtAGk+LACEQOETSAkAEu9VK8A6EMyGiBSAmjmG4fJo1hyDhNqhVQAgeIDygAoKQAJ5jgEeHXQB8wKsT4YiVowDjGTLbRBTnUCvN0h5JFo4p4FMQeUBY4YuJYAQAB0RgtUGnRTvv0YTJsVfdFkBQMCRvuSycIEqVHZ2sIkgSQN2AJTkKmiWtMztpWxBCARNDiKAcusECbwil8hwAbCjB0HmgtOUraT0BfaBJwjMfnC1wbEVrJFDRYQP3T5d7PENh3FhR2houOFjSAC0Jjw1OdMCUsIhCrlbKsfUFqCASNAujI6AMAY0qtXnnt7WfsBFkDtSEtqZbKm35uLK9DCdIJfEEaUjuoJLgSYtUQvBWDb6x/ThvZ0XaCiR3ROL9y7VO3ltOJVdgcnxDB8Uej6R13keI905zNR2UAJF3oCQHdUkfYJVtwWIAaxYt0mqFVrmGB4INFhqYVgo/E+1CoQsmBhzY626tuFWGuLaMfi7r44qESZLqU+ww90olYiBFRIkpcXgLUepD1DgSE59SEdG6TMoDc7IhhSdYwQTzEtVWA27SYmdzAFUe8cDs13uyD73xmA9LFgUFNk4AaKtVUkU6Oral1dDYyI0tpYZyvJlgaad3WaneWwb5zoJ8irRTlCUv34rpnbiKNgI7adrU+omN5zzLQINQqyCtVuLKytaZthyUQ18xVIGhmKKuAIVVDxjaSsN4eu+t/S5ILjWGYbX3C4hcDmAFyY1j3mtHewkeWGHSPGvfU4Pr9frtDxZqU6WCInqNvq6jlADaW6NQWoXa+wVaVazChIqCNmmUpqSGQPiSRakwQkGqtRotqdZo9Zge6JVGjFSYVIRCryf0W+FOQJNQiyeZNo4XUQGQcHMTHVJDkJUo8DRdmEqhVmmgp6EIzZKMnQLJdmMk5/FBCEVsPGA4gqqKiEYjCNIC0GRv/UnuyIyE8PjYiPJkaGQEx+XQYGGjj29WFmnKMlrDmGSQEZcXkZuuHadyponAkWNPyI7NYQCuMWpshlSjis6kc51aY04SCutbr1Hq9HocVcgxuUKuQLVObb48ISPbEKk0J6lys2lNqlKdHm2OcoxUshgVYSApR/oolSrOnpEwugBLs8XGO0maHqPHk0eNtRi06vTMLHWaOtwak5QVIURa8YKMCFM49IYQLWHBoQisTRrGN6y1Q1DYIWhLf6jb+iMUobwxCJN33BpDkVHwXDCwjCMUSfYEE8AnYQXJcIMPS+BY0LAIxsCeR1Nh6sw4DRUerTWLGUmj8ewEwZzLjFampsZrSYNzpEURHu+AhR4lFOTGtguCQqVHsdY4aDBc563Ce6b/h1ZtSUfbNzxqsHlPLsnNcgJLm0ylyYCHDSSVkwxnp+Auz4NSmPOx4RnSJh2lIVWUyYhTmEJnIlXoSLh1tmn7ZXtweY4IN8HAGssjpY0WVVhACI6rAkIRKxGm08B28h6TU0s9Ncmad/nkDijqIvNevkzSp+zHmN/2i6+MG/ZSapdZJ+eVB5eFfXciIjVqd0Ng5z1XGqOz59y5vf9Jv5dr72AbVaEbP4+RjenNPDnm2Jmi3Wuopluu1G+b735ZfTX/+72XwK3x7gGm4mE1t4Oe7prJJd4pvpyQSPZ0xta5p0ddU9TONzUYlx7sU5Qbg6e837V6/x1qZOzAzWOq8WWBl4L8D751ealrxJ7FN/x9ZH/fpj1/7Im76we5vnmSPqKf9ML4lTNlSwb18tu9oviQcDVj6ILCTTGfRWX5rz7iU9Nlh3qsrSRzffobx5BRUv22nplB+fNn3nC6j3Ufvrx4cPncks2hN83bF2XWhdTsff7S+uMOZQX5TPedaScLbld1Ui1+9pxgGH/sIxt+/eop28WpQ3NXDk3zXR5/7jmTY+rKuAvyp3d36qPuPU05T750YtV2cLSmuK6Onz0/4cDmQ2TxO2PTLPPe/qnPohffi+9Dzi+mt5iOvtDsK5P9/LOv7IPb18sW/EEme4i00+gz7d/gzgQWgVciz1F20oM9JpolmDbokbfMttyjCmhBhOXwCxHZbYjIQSiiBcTGQVYLaZFrh0UQIuBJxTAODyDBPQtCFcPxHbQmgHzEa05B2/dou6tlZCRjB0bA83SrWiN8/1eyLfcYeMqxXl5j7+kPglZA94B3nONp8wNcfeQU97nM7zHH/cY4rpT0nopSw83f+KH4CI6r+xhWpdP+Oobt/X/EsCql+nfCsArdf8GwqxXWB0KsSaNQqnV6QBk1KkyhBYSKUpFak05PKZR6Umt89BD7EOCIInSU+iHCUWEHOEr4pA2O1sT7vnpmxKwe5X79us/pZ17Wt18V4KYWNl/fS1vm7N+10Jy3W3XleqcRX2dWjFgzrvry8n2V168zNTsm7qgK/n5z8xTblZjtU5rr6t+d3jBz1OrC8rSUH9fWJR7TT6vY199yIUkZffLS0KxJF4ouVH89e342nnRCd6jr/hCrfbHhZsCyAxsvGRNrXL06byi82En25bbhZML4c+70jwJ/igrpFq4ZPG7PC7Kz+yIj9/qJf6EzXAPL9iobhzVvFjr7jnprZ6j7bdz0x/45R3r39L85ZMqmRiTFVNTLWTXzUsGHOnVTbUNn/6KGdQrfHcNL8WM6Q2rfOwN3HB03c8t3g30blgzG9Ec3/tDpy5Ivdt8yhJ8dap8fV6rddPRGtnN9j3MD5p4XNQvGBB2cdbjouwE11dGLG98stnYdlFrUtGZ54EvHD33x4+G/JRpOf3VgkP/yyFNP7K48Yzn9fv6kAXfN5/YbpbVD3/l29GzqvR9lLbR084BJte5h09Ly3xYtBSH5FpppgZ5/hqBfT1IEC38tChyw0/IfY9RjjHqMUY8Ao3CF8uFilPp/CaN0+O8FoxSPAKPUuFGppYxKAtcQgNRq9ZQO1xpVFKZVU0oNpv0dYBTAMB1Fkg8Ro+a1x6h47jTWrf6HNL+Q01HGvgf3rNt54lNnhjND221GkGpL5uyegSU5iec/fKZ6hS5qcvf3b9/pP2Df7W4jvh7HhK+ZFA1WDLnW/9q+kKZ1zd9caRhef3fKmaZbocu+OFh5OmzW0CG1juheh8uf23XCf+5S2vV2jL9iqzztwldbJnCa4yPS2aOBGReNSbmE+tKqCYtSN6T3+rTJdS3jlW7Gp15Xyt64fTZeX7ZLu2F61GvRQTOQ0J6n47q/cYP5cwDVJSQyNum8qmxJwF/9fjqkn+bjipkVA0nqqy79xx/pNOdPP/R7VtjZuf5k8sTmi0jZ9OiFgfpVMfiMnz+bUPNN7fBO70aXTFP0eK3uvOaM/nD8kjtP7TjpisiavGjqENBNWtH3VHLnG/mnDp/9ZO/Hji3yE1LWgoVnr2Zv6vFtqol3vDgwhjZNmXghq/Y4Gl0WX9tYlTi26dSh/VF56saLK7My5p6jLw/bShUXd9njd/TE5PjnnRebCjbUr11rL9s/tvLZQdXJtwa0EJW5JH/Gh5Co/gGq074d
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

docs/docs/concepts/chat_models.mdx

@@ -44,7 +44,7 @@ Models that do **not** include the prefix "Chat" in their name or include "LLM"
 
 ## Interface
 
-LangChain chat models implement the [BaseChatModel](https://python.langchain.com/api_reference/core/language_models/langchain_core.language_models.chat_models.BaseChatModel.html) interface. Because [BaseChatModel] also implements the [Runnable Interface](/docs/concepts/runnables), chat models support a [standard streaming interface](/docs/concepts/streaming), [async programming](/docs/concepts/async), optimized [batching](/docs/concepts/runnables/#optimized-parallel-execution-batch), and more. Please see the [Runnable Interface](/docs/concepts/runnables) for more details.
+LangChain chat models implement the [BaseChatModel](https://python.langchain.com/api_reference/core/language_models/langchain_core.language_models.chat_models.BaseChatModel.html) interface. Because `BaseChatModel` also implements the [Runnable Interface](/docs/concepts/runnables), chat models support a [standard streaming interface](/docs/concepts/streaming), [async programming](/docs/concepts/async), optimized [batching](/docs/concepts/runnables/#optimized-parallel-execution-batch), and more. Please see the [Runnable Interface](/docs/concepts/runnables) for more details.
 
 Many of the key methods of chat models operate on [messages](/docs/concepts/messages) as input and return messages as output.
 

docs/docs/how_to/index.mdx

@@ -74,6 +74,7 @@ These are the core building blocks you can use when building applications.
 ### Chat models
 
 [Chat Models](/docs/concepts/chat_models) are newer forms of language models that take messages in and output a message.
+See [supported integrations](/docs/integrations/chat/) for details on getting started with chat models from a specific provider.
 
 - [How to: do function/tool calling](/docs/how_to/tool_calling)
 - [How to: get models to return structured output](/docs/how_to/structured_output)
@@ -153,13 +154,15 @@ What LangChain calls [LLMs](/docs/concepts/text_llms) are older forms of languag
 ### Embedding models
 
 [Embedding Models](/docs/concepts/embedding_models) take a piece of text and create a numerical representation of it.
+See [supported integrations](/docs/integrations/text_embedding/) for details on getting started with embedding models from a specific provider.
 
 - [How to: embed text data](/docs/how_to/embed_text)
 - [How to: cache embedding results](/docs/how_to/caching_embeddings)
 
 ### Vector stores
 
 [Vector stores](/docs/concepts/vectorstores) are databases that can efficiently store and retrieve embeddings.
+See [supported integrations](/docs/integrations/vectorstores/) for details on getting started with vector stores from a specific provider.
 
 - [How to: use a vector store to retrieve data](/docs/how_to/vectorstores)
 

docs/docs/introduction.mdx

@@ -29,9 +29,9 @@ import useBaseUrl from '@docusaurus/useBaseUrl';
 Concretely, the framework consists of the following open-source libraries:
 
 - **`langchain-core`**: Base abstractions and LangChain Expression Language.
-- **`langchain-community`**: Third party integrations.
-  - Partner packages (e.g. **`langchain-openai`**, **`langchain-anthropic`**, etc.): Some integrations have been further split into their own lightweight packages that only depend on **`langchain-core`**.
+- Integration packages (e.g. **`langchain-openai`**, **`langchain-anthropic`**, etc.): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers.
 - **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
+- **`langchain-community`**: Third-party integrations that are community maintained.
 - **[LangGraph](https://langchain-ai.github.io/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it.
 - **[LangServe](/docs/langserve)**: Deploy LangChain chains as REST APIs.
 - **[LangSmith](https://docs.smith.langchain.com)**: A developer platform that lets you debug, test, evaluate, and monitor LLM applications.
@@ -62,7 +62,8 @@ Explore the full list of LangChain tutorials [here](/docs/tutorials), and check
 
 [Here](/docs/how_to) you’ll find short answers to “How do I….?” types of questions.
 These how-to guides don’t cover topics in depth – you’ll find that material in the [Tutorials](/docs/tutorials) and the [API Reference](https://python.langchain.com/api_reference/).
-However, these guides will help you quickly accomplish common tasks.
+However, these guides will help you quickly accomplish common tasks using [chat models](/docs/how_to/#chat-models),
+[vector stores](/docs/how_to/#vector-stores), and other common LangChain components.
 
 Check out [LangGraph-specific how-tos here](https://langchain-ai.github.io/langgraph/how-tos/).
 
@@ -72,6 +73,13 @@ Introductions to all the key parts of LangChain you’ll need to know! [Here](/d
 
 For a deeper dive into LangGraph concepts, check out [this page](https://langchain-ai.github.io/langgraph/concepts/).
 
+## [Integrations](integrations/providers/index.mdx)
+
+LangChain is part of a rich ecosystem of tools that integrate with our framework and build on top of it.
+If you're looking to get up and running quickly with [chat models](/docs/integrations/chat/), [vector stores](/docs/integrations/vectorstores/),
+or other LangChain components from a specific provider, check out our growing list of [integrations](/docs/integrations/providers/).
+
+
 ## [API reference](https://python.langchain.com/api_reference/)
 Head to the reference section for full documentation of all classes and methods in the LangChain Python packages.
 
@@ -91,8 +99,5 @@ See what changed in v0.3, learn how to migrate legacy code, read up on our versi
 ### [Security](/docs/security)
 Read up on [security](/docs/security) best practices to make sure you're developing safely with LangChain.
 
-### [Integrations](integrations/providers/index.mdx)
-LangChain is part of a rich ecosystem of tools that integrate with our framework and build on top of it. Check out our growing list of [integrations](/docs/integrations/providers/).
-
 ### [Contributing](contributing/index.mdx)
 Check out the developer's guide for guidelines on contributing and help getting your dev environment set up.

docs/docs/tutorials/index.mdx

@@ -4,7 +4,14 @@ sidebar_class_name: hidden
 ---
 # Tutorials
 
-New to LangChain or LLM app development in general? Read this material to quickly get up and running.
+New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications.
+
+If you're looking to get up and running quickly with [chat models](/docs/integrations/chat/), [vector stores](/docs/integrations/vectorstores/),
+or other LangChain components from a specific provider, check out our supported [integrations](/docs/integrations/providers/).
+
+Refer to the [how-to guides](/docs/how_to) for more detail on using common LangChain components.
+
+See the [conceptual documentation](/docs/concepts) for high level explanations of all LangChain concepts.
 
 ## Basics
 - [LLM applications](/docs/tutorials/llm_chain): Build and deploy a simple LLM application.

docs/docs/tutorials/llm_chain.ipynb

@@ -93,7 +93,7 @@
    "source": [
     "## Using Language Models\n",
     "\n",
-    "First up, let's learn how to use a language model by itself. LangChain supports many different language models that you can use interchangeably - select the one you want to use below!\n",
+    "First up, let's learn how to use a language model by itself. LangChain supports many different language models that you can use interchangeably. For details on getting started with a specific model, refer to [supported integrations](/docs/integrations/chat/).\n",
     "\n",
     "import ChatModelTabs from \"@theme/ChatModelTabs\";\n",
     "\n",

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

@@ -632,24 +632,6 @@ def _stream(
         default_chunk_class: Type[BaseMessageChunk] = AIMessageChunk
         base_generation_info = {}
 
-        if "response_format" in payload and is_basemodel_subclass(
-            payload["response_format"]
-        ):
-            # TODO: Add support for streaming with Pydantic response_format.
-            warnings.warn("Streaming with Pydantic response_format not yet supported.")
-            chat_result = self._generate(
-                messages, stop, run_manager=run_manager, **kwargs
-            )
-            msg = chat_result.generations[0].message
-            yield ChatGenerationChunk(
-                message=AIMessageChunk(
-                    **msg.dict(exclude={"type", "additional_kwargs"}),
-                    # preserve the "parsed" Pydantic object without converting to dict
-                    additional_kwargs=msg.additional_kwargs,
-                ),
-                generation_info=chat_result.generations[0].generation_info,
-            )
-            return
         if self.include_response_headers:
             raw_response = self.client.with_raw_response.create(**payload)
             response = raw_response.parse()
@@ -783,24 +765,6 @@ async def _astream(
         payload = self._get_request_payload(messages, stop=stop, **kwargs)
         default_chunk_class: Type[BaseMessageChunk] = AIMessageChunk
         base_generation_info = {}
-        if "response_format" in payload and is_basemodel_subclass(
-            payload["response_format"]
-        ):
-            # TODO: Add support for streaming with Pydantic response_format.
-            warnings.warn("Streaming with Pydantic response_format not yet supported.")
-            chat_result = await self._agenerate(
-                messages, stop, run_manager=run_manager, **kwargs
-            )
-            msg = chat_result.generations[0].message
-            yield ChatGenerationChunk(
-                message=AIMessageChunk(
-                    **msg.dict(exclude={"type", "additional_kwargs"}),
-                    # preserve the "parsed" Pydantic object without converting to dict
-                    additional_kwargs=msg.additional_kwargs,
-                ),
-                generation_info=chat_result.generations[0].generation_info,
-            )
-            return
         if self.include_response_headers:
             raw_response = await self.async_client.with_raw_response.create(**payload)
             response = raw_response.parse()
@@ -999,6 +963,28 @@ def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
         num_tokens += 3
         return num_tokens
 
+    def _should_stream(
+        self,
+        *,
+        async_api: bool,
+        run_manager: Optional[
+            Union[CallbackManagerForLLMRun, AsyncCallbackManagerForLLMRun]
+        ] = None,
+        response_format: Optional[Union[dict, type]] = None,
+        **kwargs: Any,
+    ) -> bool:
+        if isinstance(response_format, type) and is_basemodel_subclass(response_format):
+            # TODO: Add support for streaming with Pydantic response_format.
+            warnings.warn("Streaming with Pydantic response_format not yet supported.")
+            return False
+        if self.model_name.startswith("o1"):
+            # TODO: Add support for streaming with o1 once supported.
+            return False
+
+        return super()._should_stream(
+            async_api=async_api, run_manager=run_manager, **kwargs
+        )
+
     @deprecated(
         since="0.2.1",
         alternative="langchain_openai.chat_models.base.ChatOpenAI.bind_tools",

libs/partners/openai/tests/integration_tests/chat_models/test_base.py

@@ -1061,3 +1061,27 @@ def test_prediction_tokens() -> None:
     ]
     assert output_token_details["accepted_prediction_tokens"] > 0
     assert output_token_details["rejected_prediction_tokens"] > 0
+
+
+def test_stream_o1() -> None:
+    list(ChatOpenAI(model="o1-mini").stream("how are you"))
+
+
+async def test_astream_o1() -> None:
+    async for _ in ChatOpenAI(model="o1-mini").astream("how are you"):
+        pass
+
+
+class Foo(BaseModel):
+    response: str
+
+
+def test_stream_response_format() -> None:
+    list(ChatOpenAI(model="gpt-4o-mini").stream("how are ya", response_format=Foo))
+
+
+async def test_astream_response_format() -> None:
+    async for _ in ChatOpenAI(model="gpt-4o-mini").astream(
+        "how are ya", response_format=Foo
+    ):
+        pass