mirror of
https://github.com/hwchase17/langchain
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42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
from langchain.agents import AgentExecutor
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from langchain.chat_models import ChatAnthropic
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from langchain.prompts import ChatPromptTemplate
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from langchain.schema.output_parser import StrOutputParser
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from langchain.schema.runnable import RunnableMap, RunnablePassthrough
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from .agent_scratchpad import format_agent_scratchpad
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from .output_parser import parse_output
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from .prompts import retrieval_prompt
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from .retriever import retriever_description, search
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prompt = ChatPromptTemplate.from_messages(
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[
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("user", retrieval_prompt),
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("ai", "{agent_scratchpad}"),
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]
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)
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prompt = prompt.partial(retriever_description=retriever_description)
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model = ChatAnthropic(model="claude-2", temperature=0, max_tokens_to_sample=1000)
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chain = (
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RunnablePassthrough.assign(
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agent_scratchpad=lambda x: format_agent_scratchpad(x["intermediate_steps"])
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)
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| prompt
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| model.bind(stop_sequences=["</search_query>"])
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| StrOutputParser()
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)
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agent_chain = (
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RunnableMap(
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{
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"partial_completion": chain,
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"intermediate_steps": lambda x: x["intermediate_steps"],
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}
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)
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| parse_output
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)
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executor = AgentExecutor(agent=agent_chain, tools=[search], verbose=True)
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