8 Commits (73da8f863cff5ef6af358ec173572a1a8495baef)

Author	SHA1	Message	Date
Nuno Campos	9cbf14dec2	Fetch runnable config from context var inside runnable lambda and runnable generator (#15334) ... - easier to write custom logic/loops with automatic tracing - if you don't want to streaming support write a regular function and pass to RunnableLambda - if you do want streaming write a generator and pass it to RunnableGenerator ```py import json from typing import AsyncIterator from langchain_core.messages import BaseMessage, FunctionMessage, HumanMessage from langchain_core.agents import AgentAction, AgentFinish from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder from langchain_core.runnables import Runnable, RunnableGenerator, RunnablePassthrough from langchain_core.tools import BaseTool from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser from langchain.chat_models import ChatOpenAI from langchain.tools.render import format_tool_to_openai_function def _get_tavily(): from langchain.tools.tavily_search import TavilySearchResults from langchain.utilities.tavily_search import TavilySearchAPIWrapper tavily_search = TavilySearchAPIWrapper() return TavilySearchResults(api_wrapper=tavily_search) async def _agent_executor_generator( input: AsyncIterator[list[BaseMessage]], *, max_iterations: int = 10, tools: dict[str, BaseTool], agent: Runnable[list[BaseMessage], BaseMessage], parser: Runnable[BaseMessage, AgentAction | AgentFinish], ) -> AsyncIterator[BaseMessage]: messages = [m async for mm in input for m in mm] for _ in range(max_iterations): next_message = await agent.ainvoke(messages) yield next_message messages.append(next_message) parsed = await parser.ainvoke(next_message) if isinstance(parsed, AgentAction): result = await tools[parsed.tool].ainvoke(parsed.tool_input) next_message = FunctionMessage(name=parsed.tool, content=json.dumps(result)) yield next_message messages.append(next_message) elif isinstance(parsed, AgentFinish): return def get_agent_executor(tools: list[BaseTool], system_message: str): llm = ChatOpenAI(model="gpt-4-1106-preview", temperature=0, streaming=True) prompt = ChatPromptTemplate.from_messages( [ ("system", system_message), MessagesPlaceholder(variable_name="messages"), ] ) llm_with_tools = llm.bind( functions=[format_tool_to_openai_function(t) for t in tools] ) agent = {"messages": RunnablePassthrough()} | prompt | llm_with_tools parser = OpenAIFunctionsAgentOutputParser() executor = RunnableGenerator(_agent_executor_generator) return executor.bind( tools={tool.name for tool in tools}, agent=agent, parser=parser ) agent = get_agent_executor([_get_tavily()], "You are a very nice agent!") async def main(): async for message in agent.astream( [HumanMessage(content="whats the weather in sf tomorrow?")] ): print(message) if __name__ == "__main__": import asyncio asyncio.run(main()) ``` results in this trace https://smith.langchain.com/public/fa17f05d-9724-4d08-8fa1-750f8fcd051b/r	8 months ago
Nuno Campos	eb5e250188	Propagate context vars in all classes/methods ... - Any direct usage of ThreadPoolExecutor or asyncio.run_in_executor needs manual handling of context vars	9 months ago
Nuno Campos	6a5a2fb9c8	Add .pick and .assign methods to Runnable (#15229) ... <!-- Thank you for contributing to LangChain! Please title your PR "<package>: <description>", where <package> is whichever of langchain, community, core, experimental, etc. is being modified. Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes if applicable, - **Dependencies:** any dependencies required for this change, - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` from the root of the package you've modified to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://python.langchain.com/docs/contributing/ 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. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->	9 months ago
Nuno Campos	3b5b0f16c6	Move runnable context to beta (#14507) ... <!-- Thank you for contributing to LangChain! Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes (if applicable), - **Dependencies:** any dependencies required for this change, - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md 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/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->	9 months ago
Nuno Campos	77c38df36c	[core/minor] Runnables: Implement a context api (#14046) ... <!-- Thank you for contributing to LangChain! Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes (if applicable), - **Dependencies:** any dependencies required for this change, - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md 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/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> --------- Co-authored-by: Brace Sproul <braceasproul@gmail.com>	9 months ago
Nuno Campos	0f255bb6c4	In Runnable.stream_log build up final_output from adding output chunks (#12781) ... Add arg to omit streamed_output list, in cases where final_output is enough this saves bandwidth <!-- Thank you for contributing to LangChain! Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes (if applicable), - **Dependencies:** any dependencies required for this change, - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md 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/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->	10 months ago
Bagatur	d32e511826	REFACTOR: Refactor langchain_core (#13627) ... Changes: - remove langchain_core/schema since no clear distinction b/n schema and non-schema modules - make every module that doesn't end in -y plural - where easy have 1-2 classes per file - no more than one level of nesting in directories - only import from top level core modules in langchain	10 months ago
Harrison Chase	d82cbf5e76	Separate out langchain_core package (#13577) ... Co-authored-by: Nuno Campos <nuno@boringbits.io> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev>	10 months ago