langchain

Commit Graph

Author	SHA1	Message	Date
Bagatur	71cd6e6feb	groq[patch]: Release 0.1.7 (#24201 )	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
ccurme	74c7198906	core, anthropic[patch]: support streaming tool calls when function has no arguments (#23915 ) resolves https://github.com/langchain-ai/langchain/issues/23911 When an AIMessageChunk is instantiated, we attempt to parse tool calls off of the tool_call_chunks. Here we add a special-case to this parsing, where `""` will be parsed as `{}`. This is a reaction to how Anthropic streams tool calls in the case where a function has no arguments: ``` {'id': 'toolu_01J8CgKcuUVrMqfTQWPYh64r', 'input': {}, 'name': 'magic_function', 'type': 'tool_use', 'index': 1} {'partial_json': '', 'type': 'tool_use', 'index': 1} ``` The `partial_json` does not accumulate to a valid json string-- most other providers tend to emit `"{}"` in this case.	3 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	29aa9d6750	groq[patch]: Release 0.1.6 (#23655 )	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
ccurme	390ee8d971	standard-tests: add test for structured output (#23631 ) - add test for structured output - fix bug with structured output for Azure - better testing on Groq (break out Mixtral + Llama3 and add xfails where needed)	3 months ago
Julian Weng	6a1a0d977a	partners[minor]: Fix value error message for with_structured_output (#22877 ) Currently, calling `with_structured_output()` with an invalid method argument raises `Unrecognized method argument. Expected one of 'function_calling' or 'json_format'`, but the JSON mode option [is now referred to](https://python.langchain.com/v0.2/docs/how_to/structured_output/#the-with_structured_output-method) by `'json_mode'`. This fixes that. Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	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
Lucas Tucker	7114aed78f	docs: Standardize ChatGroq (#22751 ) Updated ChatGroq doc string as per issue https://github.com/langchain-ai/langchain/issues/22296:"langchain_groq: updated docstring for ChatGroq in langchain_groq to match that of the description (in the appendix) provided in issue https://github.com/langchain-ai/langchain/issues/22296. " Issue: This PR is in response to issue https://github.com/langchain-ai/langchain/issues/22296, and more specifically the ChatGroq model. In particular, this PR updates the docstring for langchain/libs/partners/groq/langchain_groq/chat_model.py by adding the following sections: Instantiate, Invoke, Stream, Async, Tool calling, Structured Output, and Response metadata. I used the template from the Anthropic implementation and referenced the Appendix of the original issue post. I also noted that: `usage_metadata `returns none for all ChatGroq models I tested; there is no mention of image input in the ChatGroq documentation; unlike that of ChatHuggingFace, `.stream(messages)` for ChatGroq returned blocks of output. --------- Co-authored-by: lucast2021 <lucast2021@headroyce.org> Co-authored-by: Bagatur <baskaryan@gmail.com>	3 months ago
ccurme	b626c3ca23	groq[patch]: add usage_metadata to (a)invoke and (a)stream (#22834 )	3 months ago
ccurme	b57aa89f34	multiple: implement ls_params (#22621 ) implement ls_params for ai21, fireworks, groq.	4 months ago
ccurme	3999761201	multiple: add `stop` attribute (#22573 )	4 months ago
Bagatur	222b1ba112	groq[patch]: Release 0.1.5 (#22500 )	4 months ago
ccurme	0ea1e89b2c	groq: read tool calls from .tool_calls attribute (#22096 )	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	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
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
Charlie Marsh	fd94aa8366	partner[patch]: Upgrade to Ruff v0.4.2 (#21108 ) ## Summary No new diagnostics (given that the set of enabled rules hasn't changed), but gains access to our new parser (much faster) and reduced false positives all around.	5 months ago
back2nix	a1614b88ac	groq[patch]: groq proxy support (#20758 ) # Proxy Fix for Groq Class 🐛 🚀 ## Description This PR fixes a bug related to proxy settings in the `Groq` class, allowing users to connect to LangChain services via a proxy. ## Changes Made - ✅ FIX support for specifying proxy settings in the `Groq` class. - ✅ Resolved the bug causing issues with proxy settings. - ❌ Did not include unit tests and documentation updates. - ❌ Did not run make format, make lint, and make test to ensure code quality and functionality because I couldn't get it to run, so I don't program in Python and couldn't run `ruff`. - ❔ Ensured that the changes are backwards compatible. - ✅ No additional dependencies were added to `pyproject.toml`. ### Error Before Fix ```python Traceback (most recent call last): File "/home/bg/Documents/code/github.com/back2nix/test/groq/main.py", line 9, in <module> chat = ChatGroq( ^^^^^^^^^ File "/home/bg/Documents/code/github.com/back2nix/test/groq/venv310/lib/python3.11/site-packages/langchain_core/load/serializable.py", line 120, in __init__ super().__init__(**kwargs) File "/home/bg/Documents/code/github.com/back2nix/test/groq/venv310/lib/python3.11/site-packages/pydantic/v1/main.py", line 341, in __init__ raise validation_error pydantic.v1.error_wrappers.ValidationError: 1 validation error for ChatGroq __root__ Invalid `http_client` argument; Expected an instance of `httpx.AsyncClient` but got <class 'httpx.Client'> (type=type_error) ``` ### Example usage after fix ```python3 import os import httpx from langchain_core.prompts import ChatPromptTemplate from langchain_groq import ChatGroq chat = ChatGroq( temperature=0, groq_api_key=os.environ.get("GROQ_API_KEY"), model_name="mixtral-8x7b-32768", http_client=httpx.Client( proxies="socks5://127.0.0.1:1080", transport=httpx.HTTPTransport(local_address="0.0.0.0"), ), http_async_client=httpx.AsyncClient( proxies="socks5://127.0.0.1:1080", transport=httpx.HTTPTransport(local_address="0.0.0.0"), ), ) system = "You are a helpful assistant." human = "{text}" prompt = ChatPromptTemplate.from_messages([("system", system), ("human", human)]) chain = prompt \| chat out = chain.invoke({"text": "Explain the importance of low latency LLMs"}) print(out) ``` --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Erick Friis	8c95ac3145	docs, multiple: de-beta with_structured_output (#20850 )	5 months ago
ccurme	3bcfbcc871	groq: handle null queue_time (#20839 )	5 months ago
ccurme	6debadaa70	groq: bump core (#20838 )	5 months ago
Erick Friis	7984206c95	groq: release 0.1.3 (#20836 ) Fixes #20811	5 months ago
ccurme	06b04b80b8	groq: fix warning filter for integration test (#20806 )	5 months ago
ccurme	5a3c65a756	standard tests: add xfails (#20659 )	5 months ago
ccurme	4b6b0a87b6	groq[patch]: Make stream robust to ToolMessage (#20417 ) ```python from langchain.agents import AgentExecutor, create_tool_calling_agent, tool from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder from langchain_groq import ChatGroq prompt = ChatPromptTemplate.from_messages( [ ("system", "You are a helpful assistant"), ("human", "{input}"), MessagesPlaceholder("agent_scratchpad"), ] ) model = ChatGroq(model_name="mixtral-8x7b-32768", temperature=0) @tool def magic_function(input: int) -> int: """Applies a magic function to an input.""" return input + 2 tools = [magic_function] agent = create_tool_calling_agent(model, tools, prompt) agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True) agent_executor.invoke({"input": "what is the value of magic_function(3)?"}) ``` ``` > Entering new AgentExecutor chain... Invoking: `magic_function` with `{'input': 3}` 5The value of magic\_function(3) is 5. > Finished chain. {'input': 'what is the value of magic_function(3)?', 'output': 'The value of magic\\_function(3) is 5.'} ```	5 months ago
Erick Friis	e6806a08d4	multiple: standard chat model tests (#20359 )	5 months ago
Bagatur	799714c629	release anthropic, fireworks, openai, groq, mistral (#20333 )	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>	5 months ago
Erick Friis	00552918ac	groq: xfail tool_choice tests (#20247 )	5 months ago
Bagatur	f06cb59ab9	groq[patch]: Release 0.1.1 (#20242 )	5 months ago
Erick Friis	51bdfe04e9	groq: handle streaming tool call case (#19978 )	6 months ago
Erick Friis	5acb564d6f	groq: fix core version (#19976 )	6 months ago
Erick Friis	9e60159043	groq: release 0.1.0 (#19975 )	6 months ago
Graden Rea	88cf8a2905	groq: Add tool calling support (#19971 ) Description: Add with_structured_output to groq chat models Issue: Dependencies: N/A Twitter handle: N/A	6 months ago
aditya thomas	4cd38fe89f	docs: update docstring of the ChatGroq class (#18645 ) Description: Update docstring of the ChatGroq class Issue: Not applicable Dependencies: None	6 months ago
William De Vena	5ee76fccd5	langchain_groq[patch]: Invoke callback prior to yielding token (#18272 ) ## PR title langchain_groq[patch]: Invoke callback prior to yielding ## PR message Description:Invoke callback prior to yielding token in _stream and _astream methods for groq. Issue: https://github.com/langchain-ai/langchain/issues/16913 Dependencies: None Twitter handle: None	7 months ago
Graden Rea	e5e38e89ce	partner: Add groq partner integration and chat model (#17856 ) Description: Add a Groq chat model issue: TODO Dependencies: groq Twitter handle: N/A	7 months ago

42 Commits (f4ee3c8a223ea4b3d7bd9e08fcd3769c70e3446c)