Find all the awesome LLM Apps demo with RAG in the following Github Repo. P.S: Don't forget to star the repo to show your support
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Streamlit PDF Chat Application Demo with Llama3
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Working Application demo using Streamlit
— Shubham Saboo (@Saboo_Shubham_) 23 mai 2024
Paste the above code in vscode or pycharm and run the following command: 'streamlit run chat_pdf_llama3.py' pic.twitter.com/cnyYCaFIfSWorking Application demo using Streamlit Paste the above code in vscode or pycharm and run the following command: 'streamlit run chat_pdf_llama3.py'
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Full RAG Application Code to Chat with PDF using Llama-3
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Full RAG Application Code to Chat with PDF using Llama-3
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Build PDF Q&A App Using Embedchain and Streamlit
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6. Ask question about the PDF and display the answer • Create a text input for the user to enter their question using 'st.text_input()'
• If a question is asked, get the answer from the Embedchain app and display it using 'st.write()' -
Upload PDF to Knowledge Base Using Streamlit File Uploader
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5. Upload a PDF file from UI and add it to the knowledge base • Use 'st.file_uploader()' to create a file uploader for PDF files.
• If a PDF file is uploaded, create a temporary file and write the contents of the uploaded file to it. -
Initializing Embedchain App with Vector Database Setup
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4. Initialize the Embedchain App • Create a temporary directory for the vector database using 'tempfile.mkdtemp()'
• Create an instance of embedchain bot. -
Setting Up Streamlit App User Interface with Python
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3. Set up the Streamlit App Streamlit lets you create user interface with just python code, for this app we will: • Add a title to the app using 'st.title()'
• Add a description for the app using 'st.caption()' -
Configure Embedchain App with Llama-3 and Chroma DB
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2. Configure the Embedchain App For this application we will use Llama-3, you can choose from OpenAI, cohere, anthropic or any other LLM of your choice. Select the vector database as the opensource chroma db (you are free to choose any other vector database of your choice).
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Building RAG Web Apps with Streamlit and Embedchain
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1. Import necessary libraries • Streamlit for building the web app
• Embedchain for the RAG functionality
• tempfile for creating temporary files and directories -
Build Local LLM RAG App Chat PDF Llama-3
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Build a LLM app with RAG to chat with PDF using Llama-3 running locally on your computer (100% free and without internet):