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Dockerfile

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+FROM python:3.11-slim
+
+WORKDIR /app
+
+# Install dependencies
+COPY app/requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY app/ .
+
+# Create a directory for the credentials
+RUN mkdir -p /app/credentials
+
+# Expose the port
+EXPOSE 8050
+
+# Command to run the application
+# Use the default Hugging Face port 7860
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

LICENSE

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+MIT License
+
+Copyright (c) 2025 gzzhongqi
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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----
-title: Vertex Fast
-emoji: 📊
-colorFrom: blue
-colorTo: gray
-sdk: docker
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: OpenAI to Gemini Adapter
+emoji: 🔄☁️
+colorFrom: blue
+colorTo: green
+sdk: docker
+app_port: 7860
+---
+
+# OpenAI to Gemini Adapter
+
+This service provides an OpenAI-compatible API that translates requests to Google's Vertex AI Gemini models, allowing you to use Gemini models with tools expecting an OpenAI interface.
+
+## Features
+
+-   OpenAI-compatible API endpoints (`/v1/chat/completions`, `/v1/models`).
+-   Supports Google Cloud credentials via `GOOGLE_CREDENTIALS_JSON` secret (recommended for Spaces) or local file methods.
+-   Supports credential rotation when using local files.
+-   Handles streaming and non-streaming responses.
+-   Configured for easy deployment on Hugging Face Spaces using Docker (port 7860) or locally via Docker Compose (port 8050).
+
+## Hugging Face Spaces Deployment (Recommended)
+
+This application is ready for deployment on Hugging Face Spaces using Docker.
+
+1.  **Create a new Space:** Go to Hugging Face Spaces and create a new Space, choosing "Docker" as the Space SDK.
+2.  **Upload Files:** Upload the `app/` directory, `Dockerfile`, and `app/requirements.txt` to your Space repository. You can do this via the web interface or using Git.
+3.  **Configure Secrets:** In your Space settings, navigate to the **Secrets** section and add the following secrets:
+    *   `API_KEY`: Your desired API key for authenticating requests to this adapter service. If not set, it defaults to `123456`.
+    *   `GOOGLE_CREDENTIALS_JSON`: The **entire content** of your Google Cloud service account JSON key file. Copy and paste the JSON content directly into the secret value field. **This is the required method for providing credentials on Hugging Face.**
+4.  **Deployment:** Hugging Face will automatically build and deploy the Docker container. The application will run on port 7860 as defined in the `Dockerfile` and this README's metadata.
+
+Your adapter service will be available at the URL provided by your Hugging Face Space (e.g., `https://your-user-name-your-space-name.hf.space`).
+
+## Local Docker Setup (for Development/Testing)
+
+### Prerequisites
+
+-   Docker and Docker Compose
+-   Google Cloud service account credentials with Vertex AI access
+
+### Credential Setup (Local Docker)
+
+1.  Create a `credentials` directory in the project root:
+    ```bash
+    mkdir -p credentials
+    ```
+2.  Add your service account JSON files to the `credentials` directory:
+    ```bash
+    # Example with multiple credential files
+    cp /path/to/your/service-account1.json credentials/service-account1.json
+    cp /path/to/your/service-account2.json credentials/service-account2.json
+    ```
+    The service will automatically detect and rotate through all `.json` files in this directory if the `GOOGLE_CREDENTIALS_JSON` environment variable is *not* set.
+3.  Alternatively, set the `GOOGLE_APPLICATION_CREDENTIALS` environment variable *in your local environment or `docker-compose.yml`* to the *path* of a single credential file (used as a fallback if the other methods fail).
+
+### Running Locally
+
+Start the service using Docker Compose:
+
+```bash
+docker-compose up -d
+```
+
+The service will be available at `http://localhost:8050` (as defined in `docker-compose.yml`).
+
+## API Usage
+
+The service implements OpenAI-compatible endpoints:
+
+-   `GET /v1/models` - List available models
+-   `POST /v1/chat/completions` - Create a chat completion
+-   `GET /health` - Health check endpoint (includes credential status)
+
+All endpoints require authentication using an API key in the Authorization header.
+
+### Authentication
+
+The service requires an API key for authentication.
+
+To authenticate, include the API key in the `Authorization` header using the `Bearer` token format:
+
+```
+Authorization: Bearer YOUR_API_KEY
+```
+
+Replace `YOUR_API_KEY` with the key you configured (either via the `API_KEY` secret/environment variable or the default `123456`).
+
+### Example Requests
+
+*(Replace `YOUR_ADAPTER_URL` with your Hugging Face Space URL or `http://localhost:8050` if running locally)*
+
+#### Basic Request
+
+```bash
+curl -X POST YOUR_ADAPTER_URL/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer YOUR_API_KEY" \
+  -d '{
+    "model": "gemini-1.5-pro",
+    "messages": [
+      {"role": "system", "content": "You are a helpful assistant."},
+      {"role": "user", "content": "Hello, how are you?"}
+    ],
+    "temperature": 0.7
+  }'
+```
+
+#### Grounded Search Request
+
+```bash
+curl -X POST YOUR_ADAPTER_URL/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer YOUR_API_KEY" \
+  -d '{
+    "model": "gemini-2.5-pro-exp-03-25-search",
+    "messages": [
+      {"role": "system", "content": "You are a helpful assistant with access to the latest information."},
+      {"role": "user", "content": "What are the latest developments in quantum computing?"}
+    ],
+    "temperature": 0.2
+  }'
+```
+
+### Supported Models
+
+The API supports the following Vertex AI Gemini models:
+
+| Model ID                       | Description                                    |
+| ------------------------------ | ---------------------------------------------- |
+| `gemini-2.5-pro-exp-03-25`     | Gemini 2.5 Pro Experimental (March 25)         |
+| `gemini-2.5-pro-exp-03-25-search` | Gemini 2.5 Pro with Google Search grounding |
+| `gemini-2.0-flash`             | Gemini 2.0 Flash                             |
+| `gemini-2.0-flash-search`      | Gemini 2.0 Flash with Google Search grounding |
+| `gemini-2.0-flash-lite`        | Gemini 2.0 Flash Lite                          |
+| `gemini-2.0-flash-lite-search` | Gemini 2.0 Flash Lite with Google Search grounding |
+| `gemini-2.0-pro-exp-02-05`     | Gemini 2.0 Pro Experimental (February 5)      |
+| `gemini-1.5-flash`             | Gemini 1.5 Flash                             |
+| `gemini-1.5-flash-8b`          | Gemini 1.5 Flash 8B                          |
+| `gemini-1.5-pro`             | Gemini 1.5 Pro                               |
+| `gemini-1.0-pro-002`           | Gemini 1.0 Pro                               |
+| `gemini-1.0-pro-vision-001`    | Gemini 1.0 Pro Vision                        |
+| `gemini-embedding-exp`         | Gemini Embedding Experimental                |
+
+Models with the `-search` suffix enable grounding with Google Search using dynamic retrieval.
+
+### Supported Parameters
+
+The API supports common OpenAI-compatible parameters, mapping them to Vertex AI where possible:
+
+| OpenAI Parameter    | Vertex AI Parameter | Description                                       |
+| ------------------- | --------------------- | ------------------------------------------------- |
+| `temperature`       | `temperature`         | Controls randomness (0.0 to 1.0)                  |
+| `max_tokens`        | `max_output_tokens`   | Maximum number of tokens to generate              |
+| `top_p`             | `top_p`               | Nucleus sampling parameter (0.0 to 1.0)           |
+| `top_k`             | `top_k`               | Top-k sampling parameter                          |
+| `stop`              | `stop_sequences`      | List of strings that stop generation when encountered |
+| `presence_penalty`  | `presence_penalty`    | Penalizes repeated tokens                         |
+| `frequency_penalty` | `frequency_penalty`   | Penalizes frequent tokens                         |
+| `seed`              | `seed`                | Random seed for deterministic generation          |
+| `logprobs`          | `logprobs`            | Number of log probabilities to return           |
+| `n`                 | `candidate_count`     | Number of completions to generate               |
+
+## Credential Handling Priority
+
+The application loads Google Cloud credentials in the following order:
+
+1.  **`GOOGLE_CREDENTIALS_JSON` Environment Variable / Secret:** Checks for the JSON *content* directly in this variable (Required for Hugging Face).
+2.  **`credentials/` Directory (Local Only):** Looks for `.json` files in the directory specified by `CREDENTIALS_DIR` (Default: `/app/credentials` inside the container). Rotates through found files. Used if `GOOGLE_CREDENTIALS_JSON` is not set.
+3.  **`GOOGLE_APPLICATION_CREDENTIALS` Environment Variable (Local Only):** Checks for a *file path* specified by this variable. Used as a fallback if the above methods fail.
+
+## Environment Variables / Secrets
+
+-   `API_KEY`: API key for authentication (Default: `123456`). **Required as Secret on Hugging Face.**
+-   `GOOGLE_CREDENTIALS_JSON`: **(Required Secret on Hugging Face)** The full JSON content of your service account key. Takes priority over other methods.
+-   `CREDENTIALS_DIR` (Local Only): Directory containing credential files (Default: `/app/credentials` in the container). Used if `GOOGLE_CREDENTIALS_JSON` is not set.
+-   `GOOGLE_APPLICATION_CREDENTIALS` (Local Only): Path to a *specific* credential file. Used as a fallback if the above methods fail.
+-   `PORT`: Not needed for `CMD` config (uses 7860). Hugging Face provides this automatically, `docker-compose.yml` maps 8050 locally.
+
+## Health Check
+
+You can check the status of the service using the health endpoint:
+
+```bash
+curl YOUR_ADAPTER_URL/health -H "Authorization: Bearer YOUR_API_KEY"
+```
+
+This returns information about the credential status:
+
+```json
+{
+  "status": "ok",
+  "credentials": {
+    "available": 1, // Example: 1 if loaded via JSON secret, or count if loaded from files
+    "files": [], // Lists files only if using CREDENTIALS_DIR method
+    "current_index": 0
+  }
+}
+```
+
+## License
+
+This project is licensed under the MIT License.

app/config.py

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+import os
+
+# Default password if not set in environment
+DEFAULT_PASSWORD = "123456"
+
+# Get password from environment variable or use default
+API_KEY = os.environ.get("API_KEY", DEFAULT_PASSWORD)
+
+# Function to validate API key
+def validate_api_key(api_key: str) -> bool:
+    """
+    Validate the provided API key against the configured key
+    
+    Args:
+        api_key: The API key to validate
+        
+    Returns:
+        bool: True if the key is valid, False otherwise
+    """
+    if not API_KEY:
+        # If no API key is configured, authentication is disabled
+        return True
+    
+    return api_key == API_KEY

app/requirements.txt

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+fastapi==0.110.0
+uvicorn==0.27.1
+google-auth==2.38.0
+google-cloud-aiplatform==1.86.0
+pydantic==2.6.1
+google-genai==1.13.0
+openai

docker-compose.yml

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+version: '3.8'
+
+services:
+  openai-to-gemini:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    ports:
+      # Map host port 8050 to container port 7860 (for Hugging Face compatibility)
+      - "8050:7860"
+    volumes:
+      - ./credentials:/app/credentials
+    environment:
+      # This is kept for backward compatibility but our app now primarily uses the credential manager
+      - GOOGLE_APPLICATION_CREDENTIALS=/app/credentials/service-account.json
+      # Directory where credential files are stored (used by credential manager)
+      - CREDENTIALS_DIR=/app/credentials
+      # API key for authentication (default: 123456)
+      - API_KEY=123456
+      # Enable/disable fake streaming (default: false)
+      - FAKE_STREAMING=false
+      # Interval for fake streaming keep-alive messages (default: 1.0)
+      - FAKE_STREAMING_INTERVAL=1.0
+    restart: unless-stopped