feat: Add extract_topic and voice_chat tools to MCP service, enhancing functionality for topic extraction and chatbot responses. Update models and routes to support new features.

feat: Add analysis endpoints and service for processing arguments, extracting topics, and predicting stance

feat: Implement user management service with Supabase integration, including user registration, retrieval, and name update endpoints.

Merge branch 'main' of https://huggingface.co/spaces/NLP-Debater-Project/FastAPI-Backend-Models

feat: Add topic-related schemas and API routes for topic management, along with LangChain dependencies in requirements.

feat: Enhance ToolCallRequest and ToolCallResponse models with detailed examples and descriptions for improved clarity and usability in MCP tool calls.

refactor: Remove GenerateArgumentRequest and GenerateArgumentResponse models; update generate_argument endpoint to accept topic and position parameters.

feat: Introduce FastAPI endpoints for single and batch text generation with Pydantic models and Hugging Face model management.

feat: Add text generation endpoint with corresponding request and response models.

feat: add Pydantic models for text generation requests and responses.

Add response models for new MCP tools: DetectStance, MatchKeypoint, TranscribeAudio, GenerateSpeech, and GenerateArgument

Update expose

add mcp part

Update chat voice part

Correct version

Add groq apis

Refactor audio processing and chatbot services; enhance STT and TTS functionalities with base64 support and session management

Update files

Refactor audio processing to utilize free models and enhance logging; update TTS and STT services for improved functionality

Enhance configuration validation and audio processing limits

add files

Correct files

Refactor audio models and services for improved error handling and response streaming

Fix errors

Add tts/stt services

Update label.py

Update label.py

Update label.py

Update label files

Update label.py

update name

update name

Add label/KPA-related schemas to models and update documentation in label routes

Add Kpa classification model

test

add label schema (#1)

Add model_config to HealthResponse in health.py for enhanced configuration options

first test