Commit Graph

7 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 7e26559256
Fix runnable vistitor for funcs without pos args (#15182) 9 months ago
Nuno Campos 0d0901ea18
Nc/dec22/runnable graph lambda (#15078)
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9 months ago
Nuno Campos 7d5800ee51
Add Runnable.get_graph() to get a graph representation of a Runnable (#15040)
It can be drawn in ascii with Runnable.get_graph().draw()
9 months ago
Nuno Campos 77c38df36c
[core/minor] Runnables: Implement a context api (#14046)
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gets announced, and you'd like a mention, we'll gladly shout you out!

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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:

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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`
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---------

Co-authored-by: Brace Sproul <braceasproul@gmail.com>
9 months ago
Nuno Campos 8a3e0c9afa
Add option to prefix config keys in configurable_alts (#13714) 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