final code

ai_agent_tutorials/ai_knowledge_companion_r1_agent/README.md

@@ -0,0 +1,87 @@
+# Deepseek r1 Knowledge Agent 🤔
+
+A versatile knowledge companion built with Deepseek r1 (via Ollama), Gemini for embeddings, Qdrant for vector storage, and Agno for agent orchestration. This application features dual-mode operation - a simple chat mode using local Deepseek r1 and an advanced RAG mode with document processing and web search capabilities.
+
+## Features
+
+- **Dual Operation Modes**
+  - Simple Chat Mode: Direct interaction with Deepseek r1 locally
+  - RAG Mode: Enhanced responses with document context and web search
+
+- **Document Processing** (RAG Mode)
+  - PDF document upload and processing
+  - Web page content extraction
+  - Automatic text chunking
+  - Vector storage in Qdrant cloud
+
+- **Intelligent Querying** (RAG Mode)
+  - Query rewriting using Gemini
+  - RAG-based document retrieval
+  - Similarity search with threshold filtering
+  - Automatic fallback to web search
+  - Source attribution for answers
+
+- **Advanced Capabilities**
+  - Exa AI web search integration
+  - Custom domain filtering for web search
+  - Context-aware response generation
+  - Chat history management
+  - Thinking process visualization
+
+- **Model Specific Features**
+  - Flexible model selection:
+    - Deepseek r1 1.5b (lighter, suitable for most laptops)
+    - Deepseek r1 7b (more capable, requires better hardware)
+  - Gemini Embedding model for vector embeddings
+  - Agno Agent framework for orchestration
+  - Streamlit-based interactive interface
+
+## Prerequisites
+
+### 1. Ollama Setup
+1. Install [Ollama](https://ollama.ai)
+2. Pull the Deepseek r1 model(s):
+```bash
+# For the lighter model
+ollama pull deepseek-r1:1.5b
+
+# For the more capable model (if your hardware supports it)
+ollama pull deepseek-r1:7b
+```
+
+### 2. Google API Key (for RAG Mode)
+1. Go to [Google AI Studio](https://aistudio.google.com/apikey)
+2. Sign up or log in to your account
+3. Create a new API key
+
+### 3. Qdrant Cloud Setup (for RAG Mode)
+1. Visit [Qdrant Cloud](https://cloud.qdrant.io/)
+2. Create an account or sign in
+3. Create a new cluster
+4. Get your credentials:
+   - Qdrant API Key: Found in API Keys section
+   - Qdrant URL: Your cluster URL (format: `https://xxx-xxx.cloud.qdrant.io`)
+
+### 4. Exa AI API Key (Optional)
+1. Visit [Exa AI](https://exa.ai)
+2. Sign up for an account
+3. Generate an API key for web search capabilities
+
+## How to Run
+
+1. Clone the repository:
+```bash
+git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
+cd ai_agent_tutorials/ai_knowledge_companion_r1_agent
+```
+
+2. Install dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+3. Run the application:
+```bash
+streamlit run ai_knowledge_r1_agent.py
+```
+

ai_agent_tutorials/ai_knowledge_companion_r1_agent/ai_knowledge_r1_agent.py

@@ -49,6 +49,8 @@ if 'qdrant_api_key' not in st.session_state:
     st.session_state.qdrant_api_key = ""
 if 'qdrant_url' not in st.session_state:
     st.session_state.qdrant_url = ""
+if 'model_version' not in st.session_state:
+    st.session_state.model_version = "deepseek-r1:1.5b"  # Default to lighter model
 if 'vector_store' not in st.session_state:
     st.session_state.vector_store = None
 if 'processed_documents' not in st.session_state:
@@ -69,6 +71,24 @@ if 'rag_enabled' not in st.session_state:
 
 # Sidebar Configuration
 st.sidebar.header("🤖 Agent Configuration")
+
+# Model Selection
+st.sidebar.header("📦 Model Selection")
+model_help = """
+- 1.5b: Lighter model, suitable for most laptops
+- 7b: More capable but requires better GPU/RAM
+
+Choose based on your hardware capabilities.
+"""
+st.session_state.model_version = st.sidebar.radio(
+    "Select Model Version",
+    options=["deepseek-r1:1.5b", "deepseek-r1:7b"],
+    help=model_help
+)
+st.sidebar.info("Run ollama pull deepseek-r1:7b or deepseek-r1:1.5b respectively")
+
+# RAG Mode Toggle
+st.sidebar.header("🔍 RAG Configuration")
 st.session_state.rag_enabled = st.sidebar.toggle("Enable RAG Mode", value=st.session_state.rag_enabled)
 
 # Clear Chat Button
@@ -285,7 +305,7 @@ def get_rag_agent() -> Agent:
     """Initialize the main RAG agent."""
     return Agent(
         name="DeepSeek RAG Agent",
-        model=Ollama(id="deepseek-r1:1.5b"),
+        model=Ollama(id=st.session_state.model_version),
         instructions="""You are an Intelligent Agent specializing in providing accurate answers.
 
         When asked a question:

ai_agent_tutorials/ai_knowledge_companion_r1_agent/requirements.txt

@@ -0,0 +1,7 @@
+agno
+exa==0.5.26
+qdrant-client==1.12.1
+langchain-qdrant==0.2.0
+langchain-community==0.3.13
+streamlit==1.41.1
+ollama