README.md

metadata

title: Chatbot for Project Guidance
emoji: 📚
colorFrom: yellow
colorTo: indigo
sdk: gradio
sdk_version: 5.14.0
app_file: app.py
pinned: false
short_description: Custom AI Chatbot for Project Guidance
license: osl-3.0
environment: conda

Custom AI Chatbot for Project Guidance

This project implements a custom AI chatbot designed to guide users through complex projects based on predefined roadmaps and rules.

Features:

• Roadmap-based Guidance: Follows a structured roadmap defined in roadmap.yaml.
• Rule Enforcement: Adheres to project rules defined in rules.yaml.
• Dynamic Response Generation: Provides context-aware and step-by-step guidance.
• Code Snippet Generation: Generates complete code snippets for project phases using templates.
• LLM Selection: Integrates with Hugging Face Hub for flexible LLM selection (DeepSeek and Gemini models).
• Model Switching: Allows users to switch between available LLMs via the UI.
• Basic LLM Responses: Generates responses using the selected LLM for general queries.
• Token Control: Limits LLM response length using max_response_tokens in configs/chatbot_config.yaml.
• Configuration Update Mode: Allows authorized users to modify chatbot configuration (rules) via chat commands in a special "update mode".
• Error Handling: Includes error handling for model loading, switching, and configuration updates, with UI warnings.
• Deployable on Hugging Face Spaces: Built using Gradio for easy deployment.

Important Notes on Safety Settings and Self-Update:

• Direct Safety Configuration Limited: For the Hugging Face models used directly via transformers (DeepSeek and Gemini Flash), there are no easily configurable, standardized "safety settings". Safety is model-dependent.
• Model-Dependent Safety: Safety behavior is primarily determined by how these models were trained.
• Configuration-Based Self-Update: The "self-update" feature is implemented as a configuration modification system. It allows authorized users to change the chatbot's rules by modifying the rules.yaml file via chat commands in "update mode." It does not modify the core Python code itself.
• Security Warning: The "self-update" feature, even in its configuration-based form, introduces security considerations. Secret commands are NOT a robust security measure. In a real deployment, stronger authentication and authorization would be essential. Use this feature with caution and only in trusted environments.

Getting Started:

1. Clone this repository.
2. Install dependencies: pip install -r requirements.txt
3. Customize roadmap.yaml and rules.yaml to define your project guidance.
4. Configure configs/chatbot_config.yaml to set up LLMs, token limits, and chatbot behavior.
5. Run the Gradio app: python app.py
6. To enter update mode: Type sagor is python/start in the chat.
7. To get help in update mode: Type sagor is python/help.
8. To exit update mode: Type sagor is python/exit.
9. Deploy to Hugging Face Spaces (refer to Hugging Face Spaces documentation).

Available Models:

• DeepSeek-R1-Distill-Llama-8B
• Gemini 2.0 Flash (Exp 01-21)

Further Development:

• Enhance LLM response generation for more context-aware and project-specific guidance.
• Implement more sophisticated state management to track user progress through the roadmap.
• Improve code generation with more dynamic templates and customization options.
• Develop a more advanced GUI or web-based interface for configuration management.
• Add more LLMs to the selection pool.
• Implement more robust error handling and logging.
• Explore and potentially integrate keyword-based output filtering for basic safety control.
• Investigate using commercial LLM APIs for more advanced safety settings and control.
• Improve security and authorization for the configuration update mode.

License: [Your License]