langchain

Commit Graph

Author	SHA1	Message	Date
Bagatur	259d4d2029	anthropic[patch]: Release 0.1.20 (#24204 )	2 months ago
Bagatur	cb5031f22f	integrations[patch]: require core >=0.2.17 (#24207 )	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	a0c2281540	infra: update mypy 1.10, ruff 0.5 (#23721 ) ```python """python scripts/update_mypy_ruff.py""" import glob import tomllib from pathlib import Path import toml import subprocess import re ROOT_DIR = Path(__file__).parents[1] def main(): for path in glob.glob(str(ROOT_DIR / "libs/*/pyproject.toml"), recursive=True): print(path) with open(path, "rb") as f: pyproject = tomllib.load(f) try: pyproject["tool"]["poetry"]["group"]["typing"]["dependencies"]["mypy"] = ( "^1.10" ) pyproject["tool"]["poetry"]["group"]["lint"]["dependencies"]["ruff"] = ( "^0.5" ) except KeyError: continue with open(path, "w") as f: toml.dump(pyproject, f) cwd = "/".join(path.split("/")[:-1]) completed = subprocess.run( "poetry lock --no-update; poetry install --with typing; poetry run mypy . --no-color", cwd=cwd, shell=True, capture_output=True, text=True, ) logs = completed.stdout.split("\n") to_ignore = {} for l in logs: if re.match("^(.)\:(\d+)\: error:.\[(.)\]", l): path, line_no, error_type = re.match( "^(.)\:(\d+)\: error:.\[(.*)\]", l ).groups() if (path, line_no) in to_ignore: to_ignore[(path, line_no)].append(error_type) else: to_ignore[(path, line_no)] = [error_type] print(len(to_ignore)) for (error_path, line_no), error_types in to_ignore.items(): all_errors = ", ".join(error_types) full_path = f"{cwd}/{error_path}" try: with open(full_path, "r") as f: file_lines = f.readlines() except FileNotFoundError: continue file_lines[int(line_no) - 1] = ( file_lines[int(line_no) - 1][:-1] + f" # type: ignore[{all_errors}]\n" ) with open(full_path, "w") as f: f.write("".join(file_lines)) subprocess.run( "poetry run ruff format .; poetry run ruff --select I --fix .", cwd=cwd, shell=True, capture_output=True, text=True, ) if __name__ == "__main__": main() ```	3 months ago
Bagatur	ebb404527f	anthropic[patch]: Release 0.1.19 (#23783 )	3 months ago
Bagatur	ed200bf2c4	anthropic[patch]: expose payload (#23291 ) ![Screenshot 2024-06-21 at 4 56 02 PM](https://github.com/langchain-ai/langchain/assets/22008038/a2c6224f-3741-4502-9607-1a726a0551c9)	3 months ago
ccurme	7c1cddf1b7	anthropic[patch]: release 0.1.18 (#23778 )	3 months ago
ccurme	c9dac59008	anthropic[patch]: fix model name in some integration tests (#23779 )	3 months ago
Bagatur	7a6c06cadd	anthropic[patch]: tool output parser fix (#23647 )	3 months ago
ccurme	46cbf0e4aa	anthropic[patch]: use core output parsers for structured output (#23776 ) Also add to standard tests for structured output.	3 months ago
kiarina	dc396835ed	langchain_anthropic: add stop_reason in ChatAnthropic stream result (#23689 ) `ChatAnthropic` can get `stop_reason` from the resulting `AIMessage` in `invoke` and `ainvoke`, but not in `stream` and `astream`. This is a different behavior from `ChatOpenAI`. It is possible to get `stop_reason` from `stream` as well, since it is needed to determine the next action after the LLM call. This would be easier to handle in situations where only `stop_reason` is needed. - Issue: NA - Dependencies: NA - Twitter handle: https://x.com/kiarina37	3 months ago
Bagatur	389a568f9a	standard-tests[patch]: add anthropic format integration test (#23717 )	3 months ago
Bagatur	b63c7f10bc	anthropic[patch]: Release 0.1.17 (#23650 )	3 months ago
Bagatur	fc8fd49328	openai, anthropic, ...: with_structured_output to pass in explicit tool choice (#23645 ) ...community, mistralai, groq, fireworks part of #23644	3 months ago
Bagatur	a7ab93479b	anthropic[patch]: Release 0.1.16 (#23549 )	3 months ago
Bagatur	93d0ad97fe	anthropic[patch]: test image input (#23155 )	3 months ago
Leonid Ganeline	3dfd055411	anthropic: docstrings (#23145 ) Added missed docstrings. Format docstrings to the consistent format (used in the API Reference)	3 months ago
Bagatur	90559fde70	openai[patch], standard-tests[patch]: don't pass in falsey stop vals (#23153 ) adds an image input test to standard-tests as well	3 months ago
Bagatur	d96f67b06f	standard-tests[patch]: Update chat model standard tests (#22378 ) - Refactor standard test classes to make them easier to configure - Update openai to support stop_sequences init param - Update groq to support stop_sequences init param - Update fireworks to support max_retries init param - Update ChatModel.bind_tools to type tool_choice - Update groq to handle tool_choice="any". this may be controversial --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>	3 months ago
Jacob Lee	181a61982f	anthropic[minor]: Adds streaming tool call support for Anthropic (#22687 ) Preserves string content chunks for non tool call requests for convenience. One thing - Anthropic events look like this: ``` RawContentBlockStartEvent(content_block=TextBlock(text='', type='text'), index=0, type='content_block_start') RawContentBlockDeltaEvent(delta=TextDelta(text='<thinking>\nThe', type='text_delta'), index=0, type='content_block_delta') RawContentBlockDeltaEvent(delta=TextDelta(text=' provide', type='text_delta'), index=0, type='content_block_delta') ... RawContentBlockStartEvent(content_block=ToolUseBlock(id='toolu_01GJ6x2ddcMG3psDNNe4eDqb', input={}, name='get_weather', type='tool_use'), index=1, type='content_block_start') RawContentBlockDeltaEvent(delta=InputJsonDelta(partial_json='', type='input_json_delta'), index=1, type='content_block_delta') ``` Note that `delta` has a `type` field. With this implementation, I'm dropping it because `merge_list` behavior will concatenate strings. We currently have `index` as a special field when merging lists, would it be worth adding `type` too? If so, what do we set as a context block chunk? `text` vs. `text_delta`/`tool_use` vs `input_json_delta`? CC @ccurme @efriis @baskaryan	3 months ago
ccurme	73c76b9628	anthropic[patch]: always add tool_result type to ToolMessage content (#22721 ) Anthropic tool results can contain image data, which are typically represented with content blocks having `"type": "image"`. Currently, these content blocks are passed as-is as human/user messages to Anthropic, which raises BadRequestError as it expects a tool_result block to follow a tool_use. Here we update ChatAnthropic to nest the content blocks inside a tool_result content block. Example: ```python import base64 import httpx from langchain_anthropic import ChatAnthropic from langchain_core.messages import AIMessage, HumanMessage, ToolMessage from langchain_core.pydantic_v1 import BaseModel, Field # Fetch image image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" image_data = base64.b64encode(httpx.get(image_url).content).decode("utf-8") class FetchImage(BaseModel): should_fetch: bool = Field(..., description="Whether an image is requested.") llm = ChatAnthropic(model="claude-3-sonnet-20240229").bind_tools([FetchImage]) messages = [ HumanMessage(content="Could you summon a beautiful image please?"), AIMessage( content=[ { "type": "tool_use", "id": "toolu_01Rn6Qvj5m7955x9m9Pfxbcx", "name": "FetchImage", "input": {"should_fetch": True}, }, ], tool_calls=[ { "name": "FetchImage", "args": {"should_fetch": True}, "id": "toolu_01Rn6Qvj5m7955x9m9Pfxbcx", }, ], ), ToolMessage( name="FetchImage", content=[ { "type": "image", "source": { "type": "base64", "media_type": "image/jpeg", "data": image_data, }, }, ], tool_call_id="toolu_01Rn6Qvj5m7955x9m9Pfxbcx", ), ] llm.invoke(messages) ``` Trace: https://smith.langchain.com/public/d27e4fc1-a96d-41e1-9f52-54f5004122db/r	3 months ago
ccurme	f32d57f6f0	anthropic: refactor streaming to use events api; add streaming usage metadata (#22628 ) - Refactor streaming to use raw events; - Add `stream_usage` class attribute and kwarg to stream methods that, if True, will include separate chunks in the stream containing usage metadata. There are two ways to implement streaming with anthropic's python sdk. They have slight differences in how they surface usage metadata. 1. [Use helper functions](https://github.com/anthropics/anthropic-sdk-python?tab=readme-ov-file#streaming-helpers). This is what we are doing now. ```python count = 1 with client.messages.stream(params) as stream: for text in stream.text_stream: snapshot = stream.current_message_snapshot print(f"{count}: {snapshot.usage} -- {text}") count = count + 1 final_snapshot = stream.get_final_message() print(f"{count}: {final_snapshot.usage}") ``` ``` 1: Usage(input_tokens=8, output_tokens=1) -- Hello 2: Usage(input_tokens=8, output_tokens=1) -- ! 3: Usage(input_tokens=8, output_tokens=1) -- How 4: Usage(input_tokens=8, output_tokens=1) -- can 5: Usage(input_tokens=8, output_tokens=1) -- I 6: Usage(input_tokens=8, output_tokens=1) -- assist 7: Usage(input_tokens=8, output_tokens=1) -- you 8: Usage(input_tokens=8, output_tokens=1) -- today 9: Usage(input_tokens=8, output_tokens=1) -- ? 10: Usage(input_tokens=8, output_tokens=12) ``` To do this correctly, we need to emit a new chunk at the end of the stream containing the usage metadata. 2. [Handle raw events](https://github.com/anthropics/anthropic-sdk-python?tab=readme-ov-file#streaming-responses) ```python stream = client.messages.create(params, stream=True) count = 1 for event in stream: print(f"{count}: {event}") count = count + 1 ``` ``` 1: RawMessageStartEvent(message=Message(id='msg_01Vdyov2kADZTXqSKkfNJXcS', content=[], model='claude-3-haiku-20240307', role='assistant', stop_reason=None, stop_sequence=None, type='message', usage=Usage(input_tokens=8, output_tokens=1)), type='message_start') 2: RawContentBlockStartEvent(content_block=TextBlock(text='', type='text'), index=0, type='content_block_start') 3: RawContentBlockDeltaEvent(delta=TextDelta(text='Hello', type='text_delta'), index=0, type='content_block_delta') 4: RawContentBlockDeltaEvent(delta=TextDelta(text='!', type='text_delta'), index=0, type='content_block_delta') 5: RawContentBlockDeltaEvent(delta=TextDelta(text=' How', type='text_delta'), index=0, type='content_block_delta') 6: RawContentBlockDeltaEvent(delta=TextDelta(text=' can', type='text_delta'), index=0, type='content_block_delta') 7: RawContentBlockDeltaEvent(delta=TextDelta(text=' I', type='text_delta'), index=0, type='content_block_delta') 8: RawContentBlockDeltaEvent(delta=TextDelta(text=' assist', type='text_delta'), index=0, type='content_block_delta') 9: RawContentBlockDeltaEvent(delta=TextDelta(text=' you', type='text_delta'), index=0, type='content_block_delta') 10: RawContentBlockDeltaEvent(delta=TextDelta(text=' today', type='text_delta'), index=0, type='content_block_delta') 11: RawContentBlockDeltaEvent(delta=TextDelta(text='?', type='text_delta'), index=0, type='content_block_delta') 12: RawContentBlockStopEvent(index=0, type='content_block_stop') 13: RawMessageDeltaEvent(delta=Delta(stop_reason='end_turn', stop_sequence=None), type='message_delta', usage=MessageDeltaUsage(output_tokens=12)) 14: RawMessageStopEvent(type='message_stop') ``` Here we implement the second option, in part because it should make things easier when implementing streaming tool calls in the near future. This would add two new chunks to the stream-- one at the beginning and one at the end-- with blank content and containing usage metadata. We add kwargs to the stream methods and a class attribute allowing for this behavior to be toggled. I enabled it by default. If we merge this we can add the same kwargs / attribute to OpenAI. Usage: ```python from langchain_anthropic import ChatAnthropic model = ChatAnthropic( model="claude-3-haiku-20240307", temperature=0 ) full = None for chunk in model.stream("hi"): full = chunk if full is None else full + chunk print(chunk) print(f"\nFull: {full}") ``` ``` content='' id='run-8a20843f-25c7-4025-ad72-9add395899e3' usage_metadata={'input_tokens': 8, 'output_tokens': 0, 'total_tokens': 8} content='Hello' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content='!' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' How' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' can' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' I' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' assist' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' you' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content=' today' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content='?' id='run-8a20843f-25c7-4025-ad72-9add395899e3' content='' id='run-8a20843f-25c7-4025-ad72-9add395899e3' usage_metadata={'input_tokens': 0, 'output_tokens': 12, 'total_tokens': 12} Full: content='Hello! How can I assist you today?' id='run-8a20843f-25c7-4025-ad72-9add395899e3' usage_metadata={'input_tokens': 8, 'output_tokens': 12, 'total_tokens': 20} ```	4 months ago
ccurme	c1ef731503	anthropic: update attribute name and alias (#22625 ) update name to `stop_sequences` and alias to `stop` (instead of the other way around), since `stop_sequences` is the name used by anthropic.	4 months ago
ccurme	3999761201	multiple: add `stop` attribute (#22573 )	4 months ago
ccurme	e08879147b	Revert "anthropic: stream token usage" (#22624 ) Reverts langchain-ai/langchain#20180	4 months ago
Bagatur	0d495f3f63	anthropic: stream token usage (#20180 ) open to other ideas <img width="1181" alt="Screenshot 2024-04-08 at 5 34 08 PM" src="https://github.com/langchain-ai/langchain/assets/22008038/03eb11c4-5eb5-43e3-9109-a13f76098fa4"> --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>	4 months ago
Bagatur	cb183a9bf1	docs: update anthropic chat model (#22483 ) Related to #22296 And update anthropic to accept base_url	4 months ago
Bagatur	678a19a5f7	infra: bump anthropic mypy 1 (#22373 )	4 months ago
Bagatur	a8098f5ddb	anthropic[patch]: Release 0.1.15, fix sdk tools break (#22369 )	4 months ago
Erick Friis	42ffcb2ff1	anthropic: release 0.1.14rc2, test release note gen (#22147 )	4 months ago
Bagatur	baa3c975cb	anthropic[patch]: allow tool call mutation (#22130 ) If tool_use blocks and tool_calls with overlapping IDs are present, prefer the values of the tool_calls. Allows for mutating AIMessages just via tool_calls.	4 months ago
Eugene Yurtsev	2d693c484e	docs: fix some spelling mistakes caught by newest version of code spell (#22090 ) Going to merge this even though it doesn't pass all tests, and open a separate PR for the remaining spelling mistakes.	4 months ago
ccurme	152c8cac33	anthropic, openai: cut pre-releases (#22083 )	4 months ago
ccurme	fbfed65fb1	core, partners: add token usage attribute to AIMessage (#21944 ) ```python class UsageMetadata(TypedDict): """Usage metadata for a message, such as token counts. Attributes: input_tokens: (int) count of input (or prompt) tokens output_tokens: (int) count of output (or completion) tokens total_tokens: (int) total token count """ input_tokens: int output_tokens: int total_tokens: int ``` ```python class AIMessage(BaseMessage): ... usage_metadata: Optional[UsageMetadata] = None """If provided, token usage information associated with the message.""" ... ```	4 months ago
Bagatur	50186da0a1	infra: rm unused # noqa violations (#22049 ) Updating #21137	4 months ago
ccurme	4be5537837	Revert "anthropic: set default model" (#21987 ) Reverts langchain-ai/langchain#21986	4 months ago
ccurme	35439cf3bd	anthropic: set default model (#21986 ) Various docs reference `ChatAnthropic()`, but this currently raises ValidationError.	4 months ago
ccurme	4470d3b4a0	partners: bump core in packages implementing ls_params (#21868 ) These packages all import `LangSmithParams` which was released in langchain-core==0.2.0. N.B. we will need to release `openai` and then bump `langchain-openai` in `together` and `upstage`.	4 months ago
ccurme	181dfef118	core, standard tests, partner packages: add test for model params (#21677 ) 1. Adds `.get_ls_params` to BaseChatModel which returns ```python class LangSmithParams(TypedDict, total=False): ls_provider: str ls_model_name: str ls_model_type: Literal["chat"] ls_temperature: Optional[float] ls_max_tokens: Optional[int] ls_stop: Optional[List[str]] ``` by default it will only return ```python {ls_model_type="chat", ls_stop=stop} ``` 2. Add these params to inheritable metadata in `CallbackManager.configure` 3. Implement `.get_ls_params` and populate all params for Anthropic + all subclasses of BaseChatOpenAI Sample trace: https://smith.langchain.com/public/d2962673-4c83-47c7-b51e-61d07aaffb1b/r OpenAI: <img width="984" alt="Screenshot 2024-05-17 at 10 03 35 AM" src="https://github.com/langchain-ai/langchain/assets/26529506/2ef41f74-a9df-4e0e-905d-da74fa82a910"> Anthropic: <img width="978" alt="Screenshot 2024-05-17 at 10 06 07 AM" src="https://github.com/langchain-ai/langchain/assets/26529506/39701c9f-7da5-4f1a-ab14-84e9169d63e7"> Mistral (and all others for which params are not yet populated): <img width="977" alt="Screenshot 2024-05-17 at 10 08 43 AM" src="https://github.com/langchain-ai/langchain/assets/26529506/37d7d894-fec2-4300-986f-49a5f0191b03">	4 months ago
Bagatur	6416d16d39	anthropic[patch]: Release 0.1.13, tool_choice support (#21773 )	4 months ago
Erick Friis	aca98fd150	multiple: releases with relaxed core dep (#21724 )	4 months ago
Erick Friis	c77d2f2b06	multiple: core 0.2 nonbreaking dep, check_diff community->langchain dep (#21646 ) 0.2 is not a breaking release for core (but it is for langchain and community) To keep the core+langchain+community packages in sync at 0.2, we will relax deps throughout the ecosystem to tolerate `langchain-core` 0.2	4 months ago
aditya thomas	b868c78a12	partners[anthropic]: update unit test for key passed in from the environment (#21290 ) Description: Update unit test for ChatAnthropic Issue: Test for key passed in from the environment should not have the key initialized in the constructor Dependencies: None	5 months ago
ccurme	6da3d92b42	(all): update removal in deprecation warnings from 0.2 to 0.3 (#21265 ) We are pushing out the removal of these to 0.3. `find . -type f -name "*.py" -exec sed -i '' 's/removal="0\.2/removal="0.3/g' {} +`	5 months ago
aditya thomas	8b59bddc03	anthropic[patch]: add tests for secret_str for api key (#20986 ) Description: Add tests to check API keys are masked Issue: Resolves https://github.com/langchain-ai/langchain/issues/12165 for Anthropic models Dependencies: None	5 months ago
ccurme	481d3855dc	patch: remove usage of llm, chat model __call__ (#20788 ) - `llm(prompt)` -> `llm.invoke(prompt)` - `llm(prompt=prompt` -> `llm.invoke(prompt)` (same with `messages=`) - `llm(prompt, callbacks=callbacks)` -> `llm.invoke(prompt, config={"callbacks": callbacks})` - `llm(prompt, kwargs)` -> `llm.invoke(prompt, kwargs)`	5 months ago
Erick Friis	8c95ac3145	docs, multiple: de-beta with_structured_output (#20850 )	5 months ago
Bagatur	54e9271504	anthropic[patch]: fix msg mutation (#20572 )	5 months ago
Bagatur	984e7e36c2	anthropic[patch]: Release 0.1.10 (#20568 )	5 months ago
Eugene Yurtsev	7a7851aa06	anthropic[patch]: Handle empty text block (#20566 ) Handle empty text block	5 months ago

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99 Commits (7d83189b198dea6cb228e2092f7697d380051052)