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https://github.com/Shubhamsaboo/awesome-llm-apps.git
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38 lines
1.1 KiB
Python
38 lines
1.1 KiB
Python
import os
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import tempfile
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import streamlit as st
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from embedchain import App
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def embedchain_bot(db_path, api_key):
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return App.from_config(
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config={
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"llm": {"provider": "openai", "config": {"api_key": api_key}},
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"vectordb": {"provider": "chroma", "config": {"dir": db_path}},
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"embedder": {"provider": "openai", "config": {"api_key": api_key}},
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}
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)
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st.title("Chat with PDF")
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openai_access_token = st.text_input("OpenAI API Key", type="password")
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if openai_access_token:
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db_path = tempfile.mkdtemp()
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app = embedchain_bot(db_path, openai_access_token)
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pdf_file = st.file_uploader("Upload a PDF file", type="pdf")
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if pdf_file:
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with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as f:
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f.write(pdf_file.getvalue())
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app.add(f.name, data_type="pdf_file")
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os.remove(f.name)
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st.success(f"Added {pdf_file.name} to knowledge base!")
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prompt = st.text_input("Ask a question about the PDF")
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if prompt:
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answer = app.chat(prompt)
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st.write(answer)
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