langchain

Commit Graph

Author	SHA1	Message	Date
Leonid Ganeline	3dfd055411	anthropic: docstrings (#23145 ) Added missed docstrings. Format docstrings to the consistent format (used in the API Reference)	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
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
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
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	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
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
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
Eugene Yurtsev	7a7851aa06	anthropic[patch]: Handle empty text block (#20566 ) Handle empty text block	5 months ago
Erick Friis	e7fe5f7d3f	anthropic[patch]: serialization in partner package (#18828 )	5 months ago
Bagatur	96d8769eae	anthropic[patch]: release 0.1.9, use tool calls if content is empty (#20535 )	5 months ago
Fayfox	9fd36efdb5	anthropic[patch]: env ANTHROPIC_API_URL not work (#20507 ) enviroment variable ANTHROPIC_API_URL will not work if anthropic_api_url has default value --------- Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>	5 months ago
Bagatur	f7667c614b	docs: update tool use case (#20404 )	5 months ago
Bagatur	9514bc4d67	core[minor], ...: add tool calls message (#18947 ) core[minor], langchain[patch], openai[minor], anthropic[minor], fireworks[minor], groq[minor], mistralai[minor] ```python class ToolCall(TypedDict): name: str args: Dict[str, Any] id: Optional[str] class InvalidToolCall(TypedDict): name: Optional[str] args: Optional[str] id: Optional[str] error: Optional[str] class ToolCallChunk(TypedDict): name: Optional[str] args: Optional[str] id: Optional[str] index: Optional[int] class AIMessage(BaseMessage): ... tool_calls: List[ToolCall] = [] invalid_tool_calls: List[InvalidToolCall] = [] ... class AIMessageChunk(AIMessage, BaseMessageChunk): ... tool_call_chunks: Optional[List[ToolCallChunk]] = None ... ``` Important considerations: - Parsing logic occurs within different providers; - ~Changing output type is a breaking change for anyone doing explicit type checking;~ - ~Langsmith rendering will need to be updated: https://github.com/langchain-ai/langchainplus/pull/3561~ - ~Langserve will need to be updated~ - Adding chunks: - ~AIMessage + ToolCallsMessage = ToolCallsMessage if either has non-null .tool_calls.~ - Tool call chunks are appended, merging when having equal values of `index`. - additional_kwargs accumulate the normal way. - During streaming: - ~Messages can change types (e.g., from AIMessageChunk to AIToolCallsMessageChunk)~ - Output parsers parse additional_kwargs (during .invoke they read off tool calls). Packages outside of `partners/`: - https://github.com/langchain-ai/langchain-cohere/pull/7 - https://github.com/langchain-ai/langchain-google/pull/123/files --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>	6 months ago
kaijietti	a812839f0c	community: add request_timeout and max_retries to ChatAnthropic (#19402 ) This PR make `request_timeout` and `max_retries` configurable for ChatAnthropic. --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Bagatur	a27d88f12a	anthropic[patch]: standardize init args (#20161 ) Related to #20085	6 months ago
Maxime Perrin	5ac0d1f67b	partners[anthropic]: fix anthropic chat model message type lookup keys (#19034 ) - Description: Fixing message formatting issue in ChatAnthropic model by adding dictionary keys for `AIMessageChunk `and `HumanMessageChunk` - Issue: #19025 - Twitter handle: @maximeperrin_ Co-authored-by: Maxime Perrin <mperrin@doing.fr> Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Bagatur	46f580d42d	docs: anthropic tool docstring (#20091 )	6 months ago
Bagatur	6860450e48	anthropic[patch]: use anthropic 0.23 (#20022 )	6 months ago
Bagatur	209de0a561	anthropic[minor]: tool use (#20016 )	6 months ago
aditya thomas	dc9e9a66db	docs: update docstring of the ChatAnthropic and AnthropicLLM classes (#18649 ) Description: Update docstring of the ChatAnthropic and AnthropicLLM classes Issue: Not applicable Dependencies: None	6 months ago
Bagatur	b15c7fdde6	anthropic[patch]: fix response metadata type (#19683 )	6 months ago
enfeng	b20c2640da	anthropic[patch]: update base_url of anthropic (#18634 ) A small change ~ - [ ] update base_url: "package: langchain_anthropic" --------- Co-authored-by: yangenfeng <yangenfeng@xiaoniangao.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	6 months ago
aditya thomas	8544f748f2	community[patch]: update AnthropicLLM deprecation message (#18869 ) Description: Update AnthropicLLM deprecation message import path for ChatAnthropic Issue: Incorrect import path in deprecation message Dependencies: None Lint and test: `make format`, `make lint` and `make test` were run	6 months ago
wewebber-merlin	d1f5bc4906	anthropic[patch]: add kwargs to format_output base (#18715 ) _generate() and _agenerate() both accept kwargs, then pass them on to _format_output; but _format_output doesn't accept kwargs. Attempting to pass, e.g., timeout=50 to _generate (or invoke()) results in a TypeError. 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, hwchase17. --------- Co-authored-by: Erick Friis <erick@langchain.dev>	7 months ago
Erick Friis	a5bcddc738	anthropic[patch]: streaming param (#18819 )	7 months ago
Erick Friis	8c0b215c02	anthropic[patch]: fix format output args (#18816 )	7 months ago
Erick Friis	e169ee8863	anthropic[patch]: handle lists in function calling (#18609 )	7 months ago
Erick Friis	4ac2cb4adc	anthropic[minor]: add tool calling (#18554 )	7 months ago
Erick Friis	68c1878380	anthropic[patch]: model type string (#18510 )	7 months ago
Erick Friis	25c7d52140	anthropic[patch]: multimodal (#18517 ) - anthropic[minor]: claude 3 - x - x --------- Co-authored-by: William FH <13333726+hinthornw@users.noreply.github.com>	7 months ago
aditya thomas	5c387a173f	docs: update to docstrings of ChatAnthropic class (#18493 ) Description: Update docstrings of ChatAnthropic class Issue: Change to ChatAnthropic from ChatAnthropicMessages Dependencies: None Lint and test: `make format`, `make lint` and `make test` passed	7 months ago
Erick Friis	24f9c700f2	anthropic[minor]: claude 3 (#18508 )	7 months ago
William De Vena	a37dc83a9e	langchain_anthropic[patch]: Invoke callback prior to yielding token (#18274 ) ## PR title langchain_anthropic[patch]: Invoke callback prior to yielding ## PR message - Description: Invoke callback prior to yielding token in _stream and _astream methods for anthropic. - Issue: https://github.com/langchain-ai/langchain/issues/16913 - Dependencies: None - Twitter handle: None	7 months ago
Erick Friis	3b5bdbfee8	anthropic[minor]: package move (#17974 )	7 months ago
Erick Friis	bfaa8c3048	anthropic[patch]: de-beta anthropic messages, release 0.0.2 (#17540 )	7 months ago
JongRok BAEK	3b8eba32f9	anthropic[patch]: Fix message type lookup in Anthropic Partners (#16563 ) - Description: The parameters for user and assistant in Anthropic should be 'ai -> assistant,' but they are reversed to 'assistant -> ai.' Below is error code. ```python anthropic.BadRequestError: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'messages: Unexpected role "ai". Allowed roles are "user" or "assistant"'}} ``` [anthropic](`7177f3a71f/src/anthropic/types/beta/message_param.py (L13)`) - Issue: : #16561 - Dependencies: : None - Twitter handle: : None	8 months ago

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52 Commits (9b3a025f9c806a6f8a00030c7058c689536ae5a0)