awesome-llm-apps/rag_tutorials/rag_chain/README.md

PharmaQuery

Overview

PharmaQuery is an advanced Pharmaceutical Insight Retrieval System designed to help users gain meaningful insights from research papers and documents in the pharmaceutical domain.

PharmaQuery Architecture

Features

• Natural Language Querying: Ask complex questions about the pharmaceutical industry and get concise, accurate answers.
• Custom Database: Upload your own research documents to enhance the retrieval system's knowledge base.
• Similarity Search: Retrieves the most relevant documents for your query using AI embeddings.
• Streamlit Interface: User-friendly interface for queries and document uploads.

Technologies Used

• Programming Language: Python 3.10+
• Framework: LangChain
• Database: ChromaDB
• Models:
  • Embeddings: Google Gemini API (embedding-001)
  • Chat: Google Gemini API (gemini-1.5-pro)
• PDF Processing: PyPDFLoader
• Document Splitter: SentenceTransformersTokenTextSplitter

Requirements

1. Install Dependencies:

   pip install -r requirements.txt
   

2. Set Up Environment Variables: Create a .env file in the project root directory with the following variables:

   GOOGLE_API_KEY="your_google_gemini_api_key"
   

   Note: Replace your_google_gemini_api_key with actual key.

3. Run the Application:

   streamlit run app.py
   

4. Use the Application:

   • Enter your query in the main interface.
   • Optionally, upload research papers in the sidebar to enhance the database.

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