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91 lines
2.5 KiB
Markdown
91 lines
2.5 KiB
Markdown
# 🤔 Agentic RAG with Gemini Flash Thinking
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A RAG Agentic system built with the new Gemini 2.0 Flash Thinking model and gemini-exp-1206, Qdrant for vector storage, and Agno (phidata prev) for agent orchestration. This application features intelligent query rewriting, document processing, and web search fallback capabilities to provide comprehensive AI-powered responses.
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## Features
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- **Document Processing**
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- PDF document upload and processing
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- Web page content extraction
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- Automatic text chunking and embedding
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- Vector storage in Qdrant cloud
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- **Intelligent Querying**
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- Query rewriting for better retrieval
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- RAG-based document retrieval
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- Similarity search with threshold filtering
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- Automatic fallback to web search
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- Source attribution for answers
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- **Advanced Capabilities**
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- Exa AI web search integration
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- Custom domain filtering for web search
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- Context-aware response generation
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- Chat history management
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- Query reformulation agent
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- **Model Specific Features**
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- Gemini Thinking 2.0 Flash for chat and reasoning
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- Gemini Embedding model for vector embeddings
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- Agno Agent framework for orchestration
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- Streamlit-based interactive interface
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## Prerequisites
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### 1. Google API Key
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1. Go to [Google AI Studio](https://aistudio.google.com/apikey)
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2. Sign up or log in to your account
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3. Create a new API key
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### 2. Qdrant Cloud Setup
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1. Visit [Qdrant Cloud](https://cloud.qdrant.io/)
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2. Create an account or sign in
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3. Create a new cluster
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4. Get your credentials:
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- Qdrant API Key: Found in API Keys section
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- Qdrant URL: Your cluster URL (format: `https://xxx-xxx.cloud.qdrant.io`)
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### 3. Exa AI API Key (Optional)
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1. Visit [Exa AI](https://exa.ai)
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2. Sign up for an account
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3. Generate an API key for web search capabilities
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## How to Run
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1. Clone the repository:
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```bash
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git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
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cd rag_tutorials/gemini_agentic_rag
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```
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2. Install dependencies:
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```bash
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pip install -r requirements.txt
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```
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3. Run the application:
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```bash
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streamlit run agentic_rag_gemini.py
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```
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## Usage
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1. Configure API keys in the sidebar:
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- Enter your Google API key
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- Add Qdrant credentials
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- (Optional) Add Exa AI key for web search
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2. Upload documents:
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- Use the file uploader for PDFs
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- Enter URLs for web content
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3. Ask questions:
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- Type your query in the chat interface
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- View rewritten queries and sources
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- See web search results when relevant
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4. Manage your session:
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- Clear chat history as needed
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- Configure web search domains
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- Monitor processed documents
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