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https://github.com/Shubhamsaboo/awesome-llm-apps.git
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ShubhamSaboo
42 lines
1.5 KiB
Python
42 lines
1.5 KiB
Python
import streamlit as st
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from embedchain import App
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import tempfile
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# Define the embedchain_bot function
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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": {"model": "gpt-4-turbo", "temperature": 0.5, "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 Substack Newsletter 📝")
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st.caption("This app allows you to chat with Substack newsletter using OpenAI API")
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# Get OpenAI API key from user
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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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# Create a temporary directory to store the database
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db_path = tempfile.mkdtemp()
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# Create an instance of Embedchain App
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app = embedchain_bot(db_path, openai_access_token)
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# Get the Substack blog URL from the user
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substack_url = st.text_input("Enter Substack Newsletter URL", type="default")
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if substack_url:
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# Add the Substack blog to the knowledge base
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app.add(substack_url, data_type='substack')
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st.success(f"Added {substack_url} to knowledge base!")
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# Ask a question about the Substack blog
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query = st.text_input("Ask any question about the substack newsletter!")
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# Query the Substack blog
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if query:
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result = app.query(query)
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st.write(result)
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