langchain/templates/anthropic-iterative-search/anthropic_iterative_search/retriever_agent.py
donbr de496062b3
templates: migrate to langchain_anthropic package to support Claude 3 models (#19393)
- **Description:** update langchain anthropic templates to support
Claude 3 (iterative search, chain of note, summarization, and XML
response)
- **Issue:** issue # N/A. Stability issues and errors encountered when
trying to use older langchain and anthropic libraries.
- **Dependencies:**
  - langchain_anthropic version 0.1.4\
- anthropic package version in the range ">=0.17.0,<1" to support
langchain_anthropic.
- **Twitter handle:** @d_w_b7


- [ x]**Add tests and docs**: If you're adding a new integration, please
include
  1. used instructions in the README for testing

- [ x] **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: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
2024-04-06 00:33:59 +00:00

44 lines
1.2 KiB
Python

from langchain.agents import AgentExecutor
from langchain_anthropic import ChatAnthropic
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnableParallel, RunnablePassthrough
from .agent_scratchpad import format_agent_scratchpad
from .output_parser import parse_output
from .prompts import retrieval_prompt
from .retriever import retriever_description, search
prompt = ChatPromptTemplate.from_messages(
[
("user", retrieval_prompt),
("ai", "{agent_scratchpad}"),
]
)
prompt = prompt.partial(retriever_description=retriever_description)
model = ChatAnthropic(
model="claude-3-sonnet-20240229", temperature=0, max_tokens_to_sample=1000
)
chain = (
RunnablePassthrough.assign(
agent_scratchpad=lambda x: format_agent_scratchpad(x["intermediate_steps"])
)
| prompt
| model.bind(stop_sequences=["</search_query>"])
| StrOutputParser()
)
agent_chain = (
RunnableParallel(
{
"partial_completion": chain,
"intermediate_steps": lambda x: x["intermediate_steps"],
}
)
| parse_output
)
executor = AgentExecutor(agent=agent_chain, tools=[search], verbose=True)