🧠 Conversation Agent (CLI) with Contextual Memory

A production-grade, CLI-based conversational AI agent that remembers important facts across conversations and responds intelligently using contextual memory.

This project is designed to be:

• Easy to clone & run
• Robust in the face of API failures
• Useful even across multiple sessions

The agent uses Gemini LLMs for response generation, FAISS for semantic memory retrieval, and SQLite for persistent chat and memory storage.

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✨ What Makes This Different?

Unlike simple chatbots, this agent:

• 🧠 Remembers important facts (e.g., user name)
• 🗂 Separates short-term and long-term memory
• 🚫 Does NOT blindly load old chats
• 🎯 Uses memory only when relevant
• 💻 Runs entirely in the terminal (CLI)

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🚀 Key Features

🧠 Contextual Memory (Cross-Session)

• Important user facts are extracted and stored
• Relevant memories are retrieved using semantic similarity
• Memory persists across runs

🔍 FAISS Semantic Search

• Uses vector embeddings for memory retrieval
• Ensures only relevant past context is injected
• Prevents prompt pollution

💾 SQLite Persistence

• Stores:
  • Full chat history
  • Structured long-term memories
• Zero external DB setup required

🤖 Gemini LLM Integration

• Uses official google-genai SDK
• Graceful handling of:
  • Quota exhaustion
  • API errors
• Clean fallback messages instead of crashes

🖥 CLI-First UX

• No UI required
• Commands:
  • /help
  • /exit
• Designed for developers & terminal users

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🛠 Technologies Used

• Python 3.10+
• Gemini LLM (via google-genai)
• FAISS (vector similarity search)
• SQLite (persistent storage)
• dotenv (environment management)

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📦 Installation

1️⃣ Clone the repository

git clone https://github.com/malikdeepak09/Conversation_Agent.git
cd Conversation_Agent

2️⃣ Create & activate a virtual environment

macOS / Linux

python3 -m venv myenv
source myenv/bin/activate

Windows

python -m venv myenv
myenv\Scripts\activate

3️⃣ Install dependencies

pip install -r requirements.txt

4️⃣ Set up environment variables

Create a .env file in the root directory:

GEMINI_API_KEY=your_gemini_api_key_here

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▶️ Usage

Run the agent:

python main.py

You’ll see:

🤖 Conversation Agent (CLI)
Type /help for commands, /exit to quit
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You >

Contributing

If you'd like to contribute to this project, feel free to fork it and submit pull requests. Please ensure that your code follows the existing style and includes proper tests.

License

This project is licensed under the MIT License - see the LICENSE file for details.