mirror of
https://github.com/hwchase17/langchain
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60 lines
1.3 KiB
Python
60 lines
1.3 KiB
Python
from langchain.chat_models import ChatOpenAI
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from langchain.prompts import ChatPromptTemplate
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from langchain.pydantic_v1 import BaseModel
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from langchain.schema.output_parser import StrOutputParser
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from langchain.schema.runnable import RunnablePassthrough
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from langchain.utilities import DuckDuckGoSearchAPIWrapper
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template = """Answer the users question based only on the following context:
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<context>
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{context}
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</context>
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Question: {question}
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"""
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prompt = ChatPromptTemplate.from_template(template)
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model = ChatOpenAI(temperature=0)
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search = DuckDuckGoSearchAPIWrapper()
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def retriever(query):
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return search.run(query)
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template = """Provide a better search query for \
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web search engine to answer the given question, end \
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the queries with ’**’. Question: \
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{x} Answer:"""
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rewrite_prompt = ChatPromptTemplate.from_template(template)
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# Parser to remove the `**`
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def _parse(text):
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return text.strip("**")
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rewriter = rewrite_prompt | ChatOpenAI(temperature=0) | StrOutputParser() | _parse
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chain = (
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{
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"context": {"x": RunnablePassthrough()} | rewriter | retriever,
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"question": RunnablePassthrough(),
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}
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| prompt
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| model
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| StrOutputParser()
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)
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# Add input type for playground
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class Question(BaseModel):
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__root__: str
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chain = chain.with_types(input_type=Question)
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