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AI-RESEARCHER-2024
commited on
Create app.py
Browse files
app.py
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import chainlit as cl
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from langchain_openai import ChatOpenAI
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from langchain.chains import RetrievalQA
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from langchain.vectorstores import Chroma
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from langchain_community.embeddings import HuggingFaceEmbeddings
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embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
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llm = llm = ChatOpenAI(
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api_key="ollama",
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model='llama3.2',
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base_url="http://localhost:11434/v1",
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temperature=0
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)
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# Load the persisted Chroma database
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persist_directory = 'mydb'
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vectordb = Chroma(persist_directory=persist_directory, embedding_function=embeddings)
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# Create a retriever from the vector store
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retriever = vectordb.as_retriever()
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# Set up the QA chain
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qa_chain = RetrievalQA.from_chain_type(llm=llm, chain_type='stuff', retriever=retriever)
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# Define the Chainlit app
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@cl.on_message
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def main(message):
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response = qa_chain.run(message.content)
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cl.Message(content=response).send()
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