Mira is an advanced AI chatbot designed to interact with users in a meaningful and context-aware manner. Mira incorporates various AI technologies, including tone analysis, context management, and memory integration, to provide a personalized and empathetic user experience.

• Project Overview
• Current Features
• Planned Features
• Installation
• Usage
• Project Structure
• Contributing
• License

Mira aims to create a next-generation conversational AI that can understand and respond to users' emotional states, maintain context over long-term interactions, and provide personalized responses based on user profiles. The project is structured in iterative phases, each building on the previous to enhance Mira's capabilities.

• Infrastructure Setup:
  • GitHub repository initialized.
  • GPU setup for model training and inference.
• Basic Chatting Pipeline:
  • Initial message handling pipeline.
  • Capability to handle full message exchanges.
  • Basic finetuning of models to assess initial performance.

• Tone Determination:
  • Small language model to analyze the tone of user messages and determine the AI's response tone.
• Context Filling:
  • Integration of a context-filling module.
  • Incorporation of Mira's profile for character traits and roles using prompt engineering.
• Memory Space:
  • Development of a memory pipeline for user profiles.
  • DynamoDB setup for long-term memory management.
• Front-End Development:
  • Basic online testing playground.
  • API and front-end integration for seamless user interaction.

• Short-Term Memory:
  • Implementation using text embeddings to maintain session context.
• Emotional Computing:
  • Exploration and integration of emotional computing for empathetic responses.
• Advanced Context Processing:
  • Regular inferences and deeper analysis of conversation context.
• User Onboarding:
  • Onboarding process to understand and store user information.

• Future Iterations:
  • Advanced emotional computing.
  • Complex memory synthesis.
  • Nuanced conversational capabilities based on user feedback.

To set up Mira locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/thejackluo/mira.git
   cd mira

2. Install dependencies:

   pip install -r requirements.txt

3. Set up environment variables: Create a .env file and add your configuration details.

4. Run the application:

   python main.py

Mira can be interacted with through a terminal interface initially. As development progresses, a web-based interface will be available for a more user-friendly experience.