🧠 Personality AI Chat

A modern Streamlit chatbot where you can choose the AI's personality type to get responses tailored to different cognitive styles and communication patterns.

✨ Features

• Personalized AI Responses - Get answers tailored to your cognitive preferences
• Modern UI Design - Clean, minimalist interface with smooth animations
• Chat History - Keep track of your conversations
• localStorage Integration - Persistent user data across browser sessions
• Memory System (Memobase) - Long-term conversation memory with cloud sync
• Powered by Mistral-7B - Using Together.ai's advanced language model

📱 localStorage System

The application uses browser localStorage for immediate data persistence:

• User Name Storage - Remembers your name across browser sessions
• Session Management - Maintains user identity locally
• Browser ID Mapping - Links browser sessions to cloud memory
• Fast Access - Instant loading without API calls
• Privacy First - Data stays on your device

// localStorage functions currently used
saveNameToLocalStorage(name)
getNameFromLocalStorage()
saveBrowserIdToLocalStorage(browserId)
getBrowserIdFromLocalStorage()
saveMemobaseMappingForBrowser(browserId, memobaseId)
getMemobaseMappingForBrowser(browserId)

🧠 Memory System - Memobase Integration

Advanced cloud-based memory system for long-term conversation storage:

Key Features:

• Long-term Memory - Conversations saved to cloud storage
• Cross-Device Sync - Access your history from any device
• Context Awareness - AI remembers previous conversations
• Manual Save Control - Choose what to save to preserve API credits
• Profile Building - System learns about user preferences over time

How It Works:

1. Browser Identity - Unique ID generated and stored in localStorage
2. Cloud Mapping - Browser ID mapped to Memobase user account
3. Conversation Storage - Chat history saved as ChatBlob format
4. Context Retrieval - Relevant past conversations inform AI responses
5. Memory Flush - Triggers profile and event extraction

Memory Architecture:

localStorage (Fast) ←→ Memobase Cloud (Persistent)
      ↓                       ↓
 User Identity          Conversation History
 Session Data           Cross-Device Sync

🏗️ System Architecture Diagram

Complete data flow architecture of the Personality AI Chat system:

graph TB
    %% User Input Layer
    subgraph UserLayer ["👤 User Input Layer"]
        User[👤 User<br/>Question + Personality]
    end
    
    %% Storage Layer - Side by side
    subgraph StorageLayer ["💾 Storage Layer"]
        direction LR
        LocalStorage[📱 Browser Storage<br/>• User Name<br/>• Browser ID<br/>• Session Data]
        CloudMemory[☁️ Cloud Memory<br/>• Chat History<br/>• User Context<br/>• Profile Data]
        LocalStorage <--> CloudMemory
    end
    
    %% AI Processing Layer - Sequential flow
    subgraph AILayer ["🤖 AI Processing Layer"]
        direction LR
        MemoryRetrieval[🧠 Memory Context<br/>Retrieval] 
        PromptBuilder[🔧 Prompt Builder<br/>+ Personality<br/>+ User History]
        TogetherAPI[🚀 Together.ai API<br/>Mistral-7B Model]
        MemoryRetrieval --> PromptBuilder --> TogetherAPI
    end
    
    %% Output Layer - Response handling
    subgraph OutputLayer ["📤 Output Layer"]
        direction TB
        AIResponse[✨ Personality Response]
        ChatUI[💬 Display in Chat]
        
        subgraph SaveOptions ["💾 Save Decision"]
            direction LR
            CloudSave[☁️ Yes → Cloud]
            SessionOnly[📱 No → Session Only]
        end
        
        AIResponse --> ChatUI
        ChatUI --> SaveOptions
    end
    
    %% Main Flow Connections
    User --> LocalStorage
    User --> MemoryRetrieval
    CloudMemory --> MemoryRetrieval
    TogetherAPI --> AIResponse
    CloudSave --> CloudMemory
    
    %% Enhanced Styling
    classDef userClass fill:#E3F2FD,stroke:#1976D2,stroke-width:3px,color:#000
    classDef storageClass fill:#F3E5F5,stroke:#7B1FA2,stroke-width:3px,color:#000
    classDef aiClass fill:#E8F5E8,stroke:#388E3C,stroke-width:3px,color:#000
    classDef outputClass fill:#FFF3E0,stroke:#F57C00,stroke-width:3px,color:#000
    classDef saveClass fill:#FFEBEE,stroke:#D32F2F,stroke-width:2px,color:#000
    
    class User userClass
    class LocalStorage,CloudMemory storageClass
    class MemoryRetrieval,PromptBuilder,TogetherAPI aiClass
    class AIResponse,ChatUI outputClass
    class CloudSave,SessionOnly saveClass
    
    %% Layer styling
    class UserLayer userClass
    class StorageLayer storageClass
    class AILayer aiClass
    class OutputLayer outputClass

Loading

⚡ Data Flow Steps:

1. 👤 User Input - User enters question & selects personality type
2. 📱 Instant Storage - localStorage saves user identity and session data
3. ☁️ Memory Retrieval - System fetches relevant conversation history from Memobase
4. 🔧 Prompt Building - Combines user input + personality + historical context
5. 🤖 AI Processing - Together.ai processes with Mistral-7B model
6. ✨ Response Generation - AI generates personality-tailored response
7. 💬 UI Display - Response appears in chat interface
8. 💾 Save Decision - User chooses: save to cloud or keep session-only

🔄 Simplified Memory Flow:

flowchart LR
    subgraph Browser ["🌐 Browser Environment"]
        LS[📱 localStorage<br/>• User Identity<br/>• Session Data<br/>• Fast Access]
    end
    
    subgraph Cloud ["☁️ Cloud Storage"]
        MB[🧠 Memobase<br/>• Conversation History<br/>• User Profiles<br/>• Cross-Device Sync]
    end
    
    LS -.->|Auto Sync| MB
    MB -.->|Context Retrieval| LS
    
    classDef browserStyle fill:#E3F2FD,stroke:#1976D2,stroke-width:3px
    classDef cloudStyle fill:#E8F5E8,stroke:#388E3C,stroke-width:3px
    
    class LS,Browser browserStyle
    class MB,Cloud cloudStyle

Loading

🛠️ Technologies Used

• Streamlit - Web application framework
• Together.ai API - AI language model (Mistral-7B)
• Memobase - Cloud memory and context management
• JavaScript localStorage - Browser-based data persistence
• Python - Backend logic
• CSS - Custom styling and animations

🔧 Installation & Setup

1. Clone the repository

   git clone https://github.com/yourusername/cognitype-chatbot.git
   cd cognitype-chatbot

2. Install dependencies

   pip install -r requirements.txt

3. Set up environment variables Create a .env.local file:

   TOGETHER_API_KEY="your-together-ai-api-key"
   MEMOBASE_API_KEY="your-memobase-api-key"
   MEMOBASE_URL="https://api.memobase.dev"

4. Run the application

   streamlit run app.py

🌐 Deployment

This application can be deployed on various platforms:

• Streamlit Community Cloud (Free)
• Railway ($5/month, no sleep mode)
• Render (Free tier with sleep mode)
• DigitalOcean App Platform ($5/month)

🤖 AI Integration

The chatbot uses Together.ai's Mistral-7B model with personality-specific prompts:

• Personalized Responses - Each personality type gets tailored communication style
• Context Awareness - Considers cognitive preferences and decision-making patterns
• Error Handling - Robust API error management
• Rate Limiting - Handles API limits gracefully

🔒 Environment Variables

TOGETHER_API_KEY=your-together-ai-api-key-here

📝 License

This project is open source and available under the MIT License.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📧 Contact

For questions or suggestions, please open an issue on GitHub.

---

Built with ❤️ using Streamlit • Powered by Together.ai & Mistral-7B