langchain

Commit Graph

Author	SHA1	Message	Date
Xander Dumaine	35784d1c33	langchain[minor]: add document_variable_name to create_stuff_documents_chain (#24083 ) - Description: `StuffDocumentsChain` uses `LLMChain` which is deprecated by langchain runnables. `create_stuff_documents_chain` is the replacement, but needs support for `document_variable_name` to allow multiple uses of the chain within a longer chain. - Issue: none - Dependencies: none	2 months ago
Eugene Yurtsev	8858846607	milvus[patch]: Fix Milvus vectorstore for newer versions of langchain-core (#24152 ) Fix for: https://github.com/langchain-ai/langchain/issues/24116 This keeps the old behavior of add_documents and add_texts	2 months ago
thedavgar	ffe6ca986e	community: Fix Bug in Azure Search Vectorstore search asyncronously (#24081 ) Thank you for contributing to LangChain! Description: This PR fixes a bug described in the issue in #24064, when using the AzureSearch Vectorstore with the asyncronous methods to do search which is also the method used for the retriever. The proposed change includes just change the access of the embedding as optional because is it not used anywhere to retrieve documents. Actually, the syncronous methods of retrieval do not use the embedding neither. With this PR the code given by the user in the issue works. ```python vectorstore = AzureSearch( azure_search_endpoint=os.getenv("AI_SEARCH_ENDPOINT_SECRET"), azure_search_key=os.getenv("AI_SEARCH_API_KEY"), index_name=os.getenv("AI_SEARCH_INDEX_NAME_SECRET"), fields=fields, embedding_function=encoder, ) retriever = vectorstore.as_retriever(search_type="hybrid", k=2) await vectorstore.avector_search("what is the capital of France") await retriever.ainvoke("what is the capital of France") ``` Issue: The Azure Search Vectorstore is not working when searching for documents with asyncronous methods, as described in issue #24064 Dependencies: There are no extra dependencies required for this change. --------- Co-authored-by: isaac hershenson <ihershenson@hmc.edu>	2 months ago
Anush	7790d67f94	qdrant: New sparse embeddings provider interface - PART 1 (#24015 ) ## Description This PR introduces a new sparse embedding provider interface to work with the new Qdrant implementation that will follow this PR. Additionally, an implementation of this interface is provided with https://github.com/qdrant/fastembed. This PR will be followed by https://github.com/Anush008/langchain/pull/3.	2 months ago
Erick Friis	1132fb801b	core: release 0.2.16 (#24159 )	2 months ago
Nuno Campos	1d37aa8403	core: Remove extra newline (#24157 )	2 months ago
ccurme	cb95198398	standard-tests[patch]: add tests for runnables as tools and streaming usage metadata (#24153 )	2 months ago
Erick Friis	d002fa902f	infra: fix redundant matrix config (#24151 )	2 months ago
Bagatur	8d100c58de	core[patch]: Tool accept RunnableConfig (#24143 ) Relies on #24038 --------- Co-authored-by: Erick Friis <erick@langchain.dev>	2 months ago
Bagatur	5fd1e67808	core[minor], integrations...[patch]: Support ToolCall as Tool input and ToolMessage as Tool output (#24038 ) Changes: - ToolCall, InvalidToolCall and ToolCallChunk can all accept a "type" parameter now - LLM integration packages add "type" to all the above - Tool supports ToolCall inputs that have "type" specified - Tool outputs ToolMessage when a ToolCall is passed as input - Tools can separately specify ToolMessage.content and ToolMessage.raw_output - Tools emit events for validation errors (using on_tool_error and on_tool_end) Example: ```python @tool("structured_api", response_format="content_and_raw_output") def _mock_structured_tool_with_raw_output( arg1: int, arg2: bool, arg3: Optional[dict] = None ) -> Tuple[str, dict]: """A Structured Tool""" return f"{arg1} {arg2}", {"arg1": arg1, "arg2": arg2, "arg3": arg3} def test_tool_call_input_tool_message_with_raw_output() -> None: tool_call: Dict = { "name": "structured_api", "args": {"arg1": 1, "arg2": True, "arg3": {"img": "base64string..."}}, "id": "123", "type": "tool_call", } expected = ToolMessage("1 True", raw_output=tool_call["args"], tool_call_id="123") tool = _mock_structured_tool_with_raw_output actual = tool.invoke(tool_call) assert actual == expected tool_call.pop("type") with pytest.raises(ValidationError): tool.invoke(tool_call) actual_content = tool.invoke(tool_call["args"]) assert actual_content == expected.content ``` --------- Co-authored-by: Erick Friis <erick@langchain.dev>	2 months ago
Bagatur	eeb996034b	core[patch]: Release 0.2.15 (#24149 )	2 months ago
Nuno Campos	03fba07d15	core[patch]: Update styles for mermaid graphs (#24147 )	2 months ago
Jacob Lee	c481a2715d	docs[patch]: Add structural example to style guide (#24133 ) CC @nfcampos	2 months ago
ccurme	8ee8ca7c83	core[patch]: propagate `parse_docstring` to tool decorator (#24123 ) Disabled by default. ```python from langchain_core.tools import tool @tool(parse_docstring=True) def foo(bar: str, baz: int) -> str: """The foo. Args: bar: this is the bar baz: this is the baz """ return bar foo.args_schema.schema() ``` ```json { "title": "fooSchema", "description": "The foo.", "type": "object", "properties": { "bar": { "title": "Bar", "description": "this is the bar", "type": "string" }, "baz": { "title": "Baz", "description": "this is the baz", "type": "integer" } }, "required": [ "bar", "baz" ] } ```	2 months ago
Jacob Lee	4121d4151f	docs[patch]: Fix typo (#24132 ) CC @efriis	2 months ago
Erick Friis	bd18faa2a0	infra: add SQLAlchemy to min version testing (#23186 ) preventing issues like #22546 Notes: - this will only affect release CI. We may want to consider adding running unit tests with min versions to PR CI in some form - because this only affects release CI, it could create annoying issues releasing while I'm on vacation. Unless anyone feels strongly, I'll wait to merge this til when I'm back	2 months ago
Jacob Lee	f1f1f75782	community[patch]: Make AzureML endpoint return AI messages for type assistant (#24085 )	2 months ago
Eugene Yurtsev	4ba14adec6	core[patch]: Clean up indexing test code (#24139 ) Refactor the code to use the existing InMemroyVectorStore. This change is needed for another PR that moves some of the imports around (and messes up the mock.patch in this file)	2 months ago
Atul R	457677c1b7	community: Fixes use of ImagePromptTemplate with Ollama (#24140 ) Description: ImagePromptTemplate for Multimodal llms like llava when using Ollama Twitter handle: https://x.com/a7ulr Details: When using llava models / any ollama multimodal llms and passing images in the prompt as urls, langchain breaks with this error. ```python image_url_components = image_url.split(",") ^^^^^^^^^^^^^^^^^^^^ AttributeError: 'dict' object has no attribute 'split' ``` From the looks of it, there was bug where the condition did check for a `url` field in the variable but missed to actually assign it. This PR fixes ImagePromptTemplate for Multimodal llms like llava when using Ollama specifically. @hwchase17	2 months ago
Matt	8327925ab7	community:support additional Azure Search Options (#24134 ) - Description: Support additional kwargs options for the Azure Search client (Described here https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/core/azure-core/README.md#configurations) - Issue: N/A - Dependencies: No additional Dependencies ---------	2 months ago
ccurme	122e80e04d	core[patch]: add versionadded to `as_tool` (#24138 )	2 months ago
Erick Friis	c4417ea93c	core: release 0.2.14, remove poetry 1.7 incompatible flag from root (#24137 )	2 months ago
Isaac Francisco	7a62d3dbd6	standard-tests[patch]: test that bind_tools can accept regular python function (#24135 )	2 months ago
Nuno Campos	2428984205	core: Add metadata to graph json repr (#24131 ) Thank you for contributing to LangChain! - [ ] PR title: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" - [ ] PR message: *Delete this entire checklist* and replace with - Description: a description of the change - Issue: the issue # it fixes, if applicable - Dependencies: any dependencies required for this change - Twitter handle: if your PR gets announced, and you'd like a mention, we'll gladly shout you out! - [ ] Add tests and docs: If you're adding a new integration, please include 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. - [ ] Lint and test: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.	2 months ago
Harley Gross	ea3cd1ebba	community[minor]: added support for C in RecursiveCharacterTextSplitter (#24091 ) Description: Added support for C in RecursiveCharacterTextSplitter by reusing the separators for C++	2 months ago
Nuno Campos	3e454d7568	core: fix docstring (#24129 )	2 months ago
Eugene Yurtsev	08638ccc88	community[patch]: QianfanLLMEndpoint fix type information for the keys (#24128 ) Fix for issue: https://github.com/langchain-ai/langchain/issues/24126	2 months ago
Nuno Campos	ee3fe20af4	core: mermaid: Render metadata key-value pairs when drawing mermaid graph (#24103 ) - if node is runnable binding with metadata attached	2 months ago
Eugene Yurtsev	1e7d8ba9a6	ci[patch]: Update community linter to provide a helpful error message (#24127 ) Update community import linter to explain what's wrong	2 months ago
maang-h	16e178a8c2	docs: Add MiniMaxChat docstrings (#24026 ) - Description: Add MiniMaxChat rich docstrings. - Issue: the issue #22296	2 months ago
Christophe Bornet	5fc5ef2b52	community[minor]: Add graph store extractors (#24065 ) This adds an extractor interface and an implementation for HTML pages. Extractors are used to create GraphVectorStore Links on loaded content. Twitter handle: cbornet_	2 months ago
maang-h	9bcf8f867d	docs: Add SQLChatMessageHistory docstring (#23978 ) - Description: Add SQLChatMessageHistory docstring. - Issue: the issue #21983 Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	2 months ago
Rafael Pereira	092e9ee0e6	community[minor]: Neo4j Fixed similarity docs (#23913 ) Description: There was missing some documentation regarding the `filter` and `params` attributes in similarity search methods. --------- Co-authored-by: rpereira <rafael.pereira@criticalsoftware.com>	2 months ago
Mis	10d8c3cbfa	docs: Fix column positioning in the text splitting section for AI21SemanticTextSplitter (#24062 )	2 months ago
Jacob Lee	555c6d3c20	docs[patch]: Updates tool error handling guide, add admonition (#24102 ) @eyurtsev	2 months ago
Eugene Yurtsev	dc131ac42a	core[minor]: Add dispatching for custom events (#24080 ) This PR allows dispatching adhoc events for a given run. # Context This PR allows users to send arbitrary data to the callback system and to the astream events API from within a given runnable. This can be extremely useful to surface custom information to end users about progress etc. Integration with langsmith tracer will be done separately since the data cannot be currently visualized. It'll be accommodated using the events attribute of the Run # Examples with astream events ```python from langchain_core.callbacks import adispatch_custom_event from langchain_core.tools import tool @tool async def foo(x: int) -> int: """Foo""" await adispatch_custom_event("event1", {"x": x}) await adispatch_custom_event("event2", {"x": x}) return x + 1 async for event in foo.astream_events({'x': 1}, version='v2'): print(event) ``` ```python {'event': 'on_tool_start', 'data': {'input': {'x': 1}}, 'name': 'foo', 'tags': [], 'run_id': 'fd6fb7a7-dd37-4191-962c-e43e245909f6', 'metadata': {}, 'parent_ids': []} {'event': 'on_custom_event', 'run_id': 'fd6fb7a7-dd37-4191-962c-e43e245909f6', 'name': 'event1', 'tags': [], 'metadata': {}, 'data': {'x': 1}, 'parent_ids': []} {'event': 'on_custom_event', 'run_id': 'fd6fb7a7-dd37-4191-962c-e43e245909f6', 'name': 'event2', 'tags': [], 'metadata': {}, 'data': {'x': 1}, 'parent_ids': []} {'event': 'on_tool_end', 'data': {'output': 2}, 'run_id': 'fd6fb7a7-dd37-4191-962c-e43e245909f6', 'name': 'foo', 'tags': [], 'metadata': {}, 'parent_ids': []} ``` ```python from langchain_core.callbacks import adispatch_custom_event from langchain_core.runnables import RunnableLambda @RunnableLambda async def foo(x: int) -> int: """Foo""" await adispatch_custom_event("event1", {"x": x}) await adispatch_custom_event("event2", {"x": x}) return x + 1 async for event in foo.astream_events(1, version='v2'): print(event) ``` ```python {'event': 'on_chain_start', 'data': {'input': 1}, 'name': 'foo', 'tags': [], 'run_id': 'ce2beef2-8608-49ea-8eba-537bdaafb8ec', 'metadata': {}, 'parent_ids': []} {'event': 'on_custom_event', 'run_id': 'ce2beef2-8608-49ea-8eba-537bdaafb8ec', 'name': 'event1', 'tags': [], 'metadata': {}, 'data': {'x': 1}, 'parent_ids': []} {'event': 'on_custom_event', 'run_id': 'ce2beef2-8608-49ea-8eba-537bdaafb8ec', 'name': 'event2', 'tags': [], 'metadata': {}, 'data': {'x': 1}, 'parent_ids': []} {'event': 'on_chain_stream', 'run_id': 'ce2beef2-8608-49ea-8eba-537bdaafb8ec', 'name': 'foo', 'tags': [], 'metadata': {}, 'data': {'chunk': 2}, 'parent_ids': []} {'event': 'on_chain_end', 'data': {'output': 2}, 'run_id': 'ce2beef2-8608-49ea-8eba-537bdaafb8ec', 'name': 'foo', 'tags': [], 'metadata': {}, 'parent_ids': []} ``` # Examples with handlers This is copy pasted from unit tests ```python class CustomCallbackManager(BaseCallbackHandler): def __init__(self) -> None: self.events: List[Any] = [] def on_custom_event( self, name: str, data: Any, , run_id: UUID, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, *kwargs: Any, ) -> None: assert kwargs == {} self.events.append( ( name, data, run_id, tags, metadata, ) ) callback = CustomCallbackManager() run_id = uuid.UUID(int=7) @RunnableLambda def foo(x: int, config: RunnableConfig) -> int: dispatch_custom_event("event1", {"x": x}) dispatch_custom_event("event2", {"x": x}, config=config) return x foo.invoke(1, {"callbacks": [callback], "run_id": run_id}) assert callback.events == [ ("event1", {"x": 1}, UUID("00000000-0000-0000-0000-000000000007"), [], {}), ("event2", {"x": 1}, UUID("00000000-0000-0000-0000-000000000007"), [], {}), ] ```	2 months ago
Jacob Lee	14a8bbc21a	docs[patch]: Adds tool intermediate streaming guide (#24098 ) Can merge now and update when we add support for custom events. CC @eyurtsev @vbarda	2 months ago
Erick Friis	1de1182a9f	docs: discourage unconfirmed partner packages (#24099 )	2 months ago
Erick Friis	71c2221f8c	openai: release 0.1.15 (#24097 )	2 months ago
Erick Friis	6ea6f9f7bc	core: release 0.2.13 (#24096 )	2 months ago
ccurme	975b6129f6	core[patch]: support conversion of runnables to tools (#23992 ) Open to other thoughts on UX. string input: ```python as_tool = retriever.as_tool() as_tool.invoke("cat") # [Document(...), ...] ``` typed dict input: ```python class Args(TypedDict): key: int def f(x: Args) -> str: return str(x["key"] * 2) as_tool = RunnableLambda(f).as_tool( name="my tool", description="description", # name, description are inferred if not supplied ) as_tool.invoke({"key": 3}) # "6" ``` for untyped dict input, allow specification of parameters + types ```python def g(x: Dict[str, Any]) -> str: return str(x["key"] * 2) as_tool = RunnableLambda(g).as_tool(arg_types={"key": int}) result = as_tool.invoke({"key": 3}) # "6" ``` Passing the `arg_types` is slightly awkward but necessary to ensure tool calls populate parameters correctly: ```python from typing import Any, Dict from langchain_core.runnables import RunnableLambda from langchain_openai import ChatOpenAI def f(x: Dict[str, Any]) -> str: return str(x["key"] * 2) runnable = RunnableLambda(f) as_tool = runnable.as_tool(arg_types={"key": int}) llm = ChatOpenAI().bind_tools([as_tool]) result = llm.invoke("Use the tool on 3.") tool_call = result.tool_calls[0] args = tool_call["args"] assert args == {"key": 3} as_tool.run(args) ``` Contrived (?) example with langgraph agent as a tool: ```python from typing import List, Literal from typing_extensions import TypedDict from langchain_openai import ChatOpenAI from langgraph.prebuilt import create_react_agent llm = ChatOpenAI(temperature=0) def magic_function(input: int) -> int: """Applies a magic function to an input.""" return input + 2 agent_1 = create_react_agent(llm, [magic_function]) class Message(TypedDict): role: Literal["human"] content: str agent_tool = agent_1.as_tool( arg_types={"messages": List[Message]}, name="Jeeves", description="Ask Jeeves.", ) agent_2 = create_react_agent(llm, [agent_tool]) ``` --------- Co-authored-by: Erick Friis <erick@langchain.dev>	2 months ago
Jacob Lee	b63a48b7d3	docs[patch]: Fix typos, add prereq sections (#24095 )	2 months ago
Erick Friis	9de562f747	infra: create individual jobs in check_diff, do max milvus testing in 3.11 (#23829 ) pickup from #23721	2 months ago
Erick Friis	141943a7e1	infra: docs ignore step in script (#24090 )	2 months ago
Bagatur	6928f4c438	core[minor]: Add ToolMessage.raw_output (#23994 ) Decisions to discuss: 1. is a new attr needed or could additional_kwargs be used for this 2. is raw_output a good name for this attr 3. should raw_output default to {} or None 4. should raw_output be included in serialization 5. do we need to update repr/str to exclude raw_output	2 months ago
jongwony	14dd89a1ee	docs: add itemgetter in how_to/dynamic_chain (#23951 ) Hello! I am honored to be able to contribute to the LangChain project for the first time. - Description: Using `RunnablePassthrough` logic without providing `chat_history` key will result in nested keys in `question`, so I submit a pull request to resolve this issue. I am attaching a LangSmith screenshot below. This is the result of the current version of the document. <img width="1112" alt="image" src="https://github.com/langchain-ai/langchain/assets/12846075/f0597089-c375-472f-b2bf-793baaecd836"> without `chat_history`: <img width="1112" alt="image" src="https://github.com/langchain-ai/langchain/assets/12846075/5c0e3ae7-3afe-417c-9132-770387f0fff2"> - Lint and test: <img width="777" alt="image" src="https://github.com/langchain-ai/langchain/assets/12846075/575d2545-3aed-4338-9779-1a0b17365418">	2 months ago
Eugene Yurtsev	c4e149d4f1	community[patch]: Add linter to catch @root_validator (#24070 ) - Add linter to prevent further usage of vanilla root validator - Udpate remaining root validators	2 months ago
ccurme	9c6efadec3	community[patch]: propagate cost information to OpenAI callback (#23996 ) This is enabled following https://github.com/langchain-ai/langchain/pull/22716.	2 months ago
Dismas Banda	91b37b2d81	docs: fix spelling mistake in concepts.mdx: Fouth -> Fourth (#24067 ) Description: Corrected the spelling for fourth. Twitter handle: @dismasbanda	2 months ago
William FH	1e1fd30def	[Core] Fix fstring in logger warning (#24043 )	2 months ago

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