update

Dockerfile

@@ -17,6 +17,9 @@ RUN useradd -m -u 1000 user
 # Install uv instead of poetry
 RUN pip install uv
 
+# Install uvicorn explicitly
+RUN pip install uvicorn
+
 # Create and configure cache directory
 RUN mkdir -p /app/.cache && \
     chown -R user:user /app
@@ -59,4 +62,4 @@ USER user
 EXPOSE 7860
 
 # Start both servers with wait-for
-CMD ["sh", "-c", "uvicorn app.asgi:app --host 0.0.0.0 --port 7861 & while ! nc -z localhost 7861; do sleep 1; done && cd frontend && npm run serve"]
+CMD ["sh", "-c", "uvicorn main:app --host 0.0.0.0 --port 7861 & while ! nc -z localhost 7861; do sleep 1; done && cd frontend && npm run serve"]

backend/README.md

@@ -1,352 +0,0 @@
-# Backend - Open LLM Leaderboard 🏆
-
-FastAPI backend for the Open LLM Leaderboard. This service is part of a larger architecture that includes a React frontend. For complete project installation, see the [main README](../README.md).
-
-## ✨ Features
-
-- 📊 REST API for LLM models leaderboard management
-- 🗳️ Voting and ranking system
-- 🔄 HuggingFace Hub integration
-- 🚀 Caching and performance optimizations
-
-## 🏗 Architecture
-
-```mermaid
-flowchart TD
-    Client(["**Frontend**<br><br>React Application"]) --> API["**API Server**<br><br>FastAPI REST Endpoints"]
-
-    subgraph Backend
-        API --> Core["**Core Layer**<br><br>• Middleware<br>• Cache<br>• Rate Limiting"]
-        Core --> Services["**Services Layer**<br><br>• Business Logic<br>• Data Processing"]
-
-        subgraph Services Layer
-            Services --> Models["**Model Service**<br><br>• Model Submission<br>• Evaluation Pipeline"]
-            Services --> Votes["**Vote Service**<br><br>• Vote Management<br>• Data Synchronization"]
-            Services --> Board["**Leaderboard Service**<br><br>• Rankings<br>• Performance Metrics"]
-        end
-
-        Models --> Cache["**Cache Layer**<br><br>• In-Memory Store<br>• Auto Invalidation"]
-        Votes --> Cache
-        Board --> Cache
-
-        Models --> HF["**HuggingFace Hub**<br><br>• Models Repository<br>• Datasets Access"]
-        Votes --> HF
-        Board --> HF
-    end
-
-    style Client fill:#f9f,stroke:#333,stroke-width:2px
-    style Models fill:#bbf,stroke:#333,stroke-width:2px
-    style Votes fill:#bbf,stroke:#333,stroke-width:2px
-    style Board fill:#bbf,stroke:#333,stroke-width:2px
-    style HF fill:#bfb,stroke:#333,stroke-width:2px
-```
-
-## 🛠️ HuggingFace Datasets
-
-The application uses several datasets on the HuggingFace Hub:
-
-### 1. Requests Dataset (`{HF_ORGANIZATION}/requests`)
-
-- **Operations**:
-  - 📤 `POST /api/models/submit`: Adds a JSON file for each new model submission
-  - 📥 `GET /api/models/status`: Reads files to get models status
-- **Format**: One JSON file per model with submission details
-- **Updates**: On each new model submission
-
-### 2. Votes Dataset (`{HF_ORGANIZATION}/votes`)
-
-- **Operations**:
-  - 📤 `POST /api/votes/{model_id}`: Adds a new vote
-  - 📥 `GET /api/votes/model/{provider}/{model}`: Reads model votes
-  - 📥 `GET /api/votes/user/{user_id}`: Reads user votes
-- **Format**: JSONL with one vote per line
-- **Sync**: Bidirectional between local cache and Hub
-
-### 3. Contents Dataset (`{HF_ORGANIZATION}/contents`)
-
-- **Operations**:
-  - 📥 `GET /api/leaderboard`: Reads raw data
-  - 📥 `GET /api/leaderboard/formatted`: Reads and formats data
-- **Format**: Main dataset containing all scores and metrics
-- **Updates**: Automatic after model evaluations
-
-### 4. Official Providers Dataset (`{HF_ORGANIZATION}/official-providers`)
-
-- **Operations**:
-  - 📥 Read-only access for highlighted models
-- **Format**: List of models selected by maintainers
-- **Updates**: Manual by maintainers
-
-## 🛠 Local Development
-
-### Prerequisites
-
-- Python 3.9+
-- [Poetry](https://python-poetry.org/docs/#installation)
-
-### Standalone Installation (without Docker)
-
-```bash
-# Install dependencies
-poetry install
-
-# Setup configuration
-cp .env.example .env
-
-# Start development server
-poetry run uvicorn app.asgi:app --host 0.0.0.0 --port 7860 --reload
-```
-
-Server will be available at http://localhost:7860
-
-## ⚙️ Configuration
-
-| Variable     | Description                          | Default     |
-| ------------ | ------------------------------------ | ----------- |
-| ENVIRONMENT  | Environment (development/production) | development |
-| HF_TOKEN     | HuggingFace authentication token     | -           |
-| PORT         | Server port                          | 7860        |
-| LOG_LEVEL    | Logging level (INFO/DEBUG/WARNING)   | INFO        |
-| CORS_ORIGINS | Allowed CORS origins                 | ["*"]       |
-| CACHE_TTL    | Cache Time To Live in seconds        | 300         |
-
-## 🔧 Middleware
-
-The backend uses several middleware layers for optimal performance and security:
-
-- **CORS Middleware**: Handles Cross-Origin Resource Sharing
-- **GZIP Middleware**: Compresses responses > 500 bytes
-- **Rate Limiting**: Prevents API abuse
-- **Caching**: In-memory caching with automatic invalidation
-
-## 📝 Logging
-
-The application uses a structured logging system with:
-
-- Formatted console output
-- Different log levels per component
-- Request/Response logging
-- Performance metrics
-- Error tracking
-
-## 📁 File Structure
-
-```
-backend/
-├── app/                  # Source code
-│   ├── api/             # Routes and endpoints
-│   │   └── endpoints/   # Endpoint handlers
-│   ├── core/           # Configurations
-│   ├── services/       # Business logic
-│   └── utils/          # Utilities
-└── tests/              # Tests
-```
-
-## 📚 API
-
-Swagger documentation available at http://localhost:7860/docs
-
-### Main Endpoints & Data Structures
-
-#### Leaderboard
-
-- `GET /api/leaderboard/formatted` - Formatted data with computed fields and metadata
-
-  ```typescript
-  Response {
-    models: [{
-      id: string,  // eval_name
-      model: {
-        name: string,  // fullname
-        sha: string,  // Model sha
-        precision: string,  // e.g. "fp16", "int8"
-        type: string,  // e.g. "fined-tuned-on-domain-specific-dataset"
-        weight_type: string,
-        architecture: string,
-        average_score: number,
-        has_chat_template: boolean
-      },
-      evaluations: {
-        ifeval: {
-          name: "IFEval",
-          value: number,  // Raw score
-          normalized_score: number
-        },
-        bbh: {
-          name: "BBH",
-          value: number,
-          normalized_score: number
-        },
-        math: {
-          name: "MATH Level 5",
-          value: number,
-          normalized_score: number
-        },
-        gpqa: {
-          name: "GPQA",
-          value: number,
-          normalized_score: number
-        },
-        musr: {
-          name: "MUSR",
-          value: number,
-          normalized_score: number
-        },
-        mmlu_pro: {
-          name: "MMLU-PRO",
-          value: number,
-          normalized_score: number
-        }
-      },
-      features: {
-        is_not_available_on_hub: boolean,
-        is_merged: boolean,
-        is_moe: boolean,
-        is_flagged: boolean,
-        is_official_provider: boolean
-      },
-      metadata: {
-        upload_date: string,
-        submission_date: string,
-        generation: string,
-        base_model: string,
-        hub_license: string,
-        hub_hearts: number,
-        params_billions: number,
-        co2_cost: number  // CO₂ cost in kg
-      }
-    }]
-  }
-  ```
-
-- `GET /api/leaderboard` - Raw data from the HuggingFace dataset
-  ```typescript
-  Response {
-    models: [{
-      eval_name: string,
-      Precision: string,
-      Type: string,
-      "Weight type": string,
-      Architecture: string,
-      Model: string,
-      fullname: string,
-      "Model sha": string,
-      "Average ⬆️": number,
-      "Hub License": string,
-      "Hub ❤️": number,
-      "#Params (B)": number,
-      "Available on the hub": boolean,
-      Merged: boolean,
-      MoE: boolean,
-      Flagged: boolean,
-      "Chat Template": boolean,
-      "CO₂ cost (kg)": number,
-      "IFEval Raw": number,
-      IFEval: number,
-      "BBH Raw": number,
-      BBH: number,
-      "MATH Lvl 5 Raw": number,
-      "MATH Lvl 5": number,
-      "GPQA Raw": number,
-      GPQA: number,
-      "MUSR Raw": number,
-      MUSR: number,
-      "MMLU-PRO Raw": number,
-      "MMLU-PRO": number,
-      "Maintainer's Highlight": boolean,
-      "Upload To Hub Date": string,
-      "Submission Date": string,
-      Generation: string,
-      "Base Model": string
-    }]
-  }
-  ```
-
-#### Models
-
-- `GET /api/models/status` - Get all models grouped by status
-  ```typescript
-  Response {
-    pending: [{
-      name: string,
-      submitter: string,
-      revision: string,
-      wait_time: string,
-      submission_time: string,
-      status: "PENDING" | "EVALUATING" | "FINISHED",
-      precision: string
-    }],
-    evaluating: Array<Model>,
-    finished: Array<Model>
-  }
-  ```
-- `GET /api/models/pending` - Get pending models only
-- `POST /api/models/submit` - Submit model
-
-  ```typescript
-  Request {
-    user_id: string,
-    model_id: string,
-    base_model?: string,
-    precision?: string,
-    model_type: string
-  }
-
-  Response {
-    status: string,
-    message: string
-  }
-  ```
-
-- `GET /api/models/{model_id}/status` - Get model status
-
-#### Votes
-
-- `POST /api/votes/{model_id}` - Vote
-
-  ```typescript
-  Request {
-    vote_type: "up" | "down",
-    user_id: string  // HuggingFace username
-  }
-
-  Response {
-    success: boolean,
-    message: string
-  }
-  ```
-
-- `GET /api/votes/model/{provider}/{model}` - Get model votes
-  ```typescript
-  Response {
-    total_votes: number,
-    up_votes: number,
-    down_votes: number
-  }
-  ```
-- `GET /api/votes/user/{user_id}` - Get user votes
-  ```typescript
-  Response Array<{
-    model_id: string,
-    vote_type: string,
-    timestamp: string
-  }>
-  ```
-
-## 🔒 Authentication
-
-The backend uses HuggingFace token-based authentication for secure API access. Make sure to:
-
-1. Set your HF_TOKEN in the .env file
-2. Include the token in API requests via Bearer authentication
-3. Keep your token secure and never commit it to version control
-
-## 🚀 Performance
-
-The backend implements several optimizations:
-
-- In-memory caching with configurable TTL (Time To Live)
-- Batch processing for model evaluations
-- Rate limiting for API endpoints
-- Efficient database queries with proper indexing
-- Automatic cache invalidation for votes