🧠 Cerebra.aiAPI

An unofficial, feature-rich API for Cerebra.ai with OpenAI compatibility and advanced tools.

🚀 Features • 🛠️ Installation • 💻 Usage • 🖥️ Server • 🔌 OpenAI Compatibility • 🧰 Tools • 📊 Benchmarks • 🤝 Contributing • 📄 License

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🚀 Features

• 🔥 Seamless integration with Cerebra.ai models
• 🔄 OpenAI-compatible API endpoints
• 🧠 Access to state-of-the-art language models
• 🛠️ Advanced tools for enhanced capabilities
• 🖥️ Built-in server with FastAPI
• 📊 Detailed usage metrics and quotas
• 🔒 Secure cookie-based authentication
• 📡 Real-time streaming responses

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🛠️ Installation

Prerequisites

• Python 3.7+- Python 3.7+
• Cookie-Editor extension

Step-by-step Guide

1. Clone the repository:

   git clone https://github.com/OE-LUCIFER/Cerebra.aiAPI.git
   cd Cerebra.aiAPI

2. Set up a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Configure your cookies:

   • Visit the Cerebra.ai website
   • Use Cookie-Editor to export cookies
   • Save as cookies.json in the project root

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💻 Usage

Quick Start

from cerebra_ai_api import CerebrasWithCookie

client = CerebrasWithCookie(cookie_path='cookies.json')

response = client.ask("Explain the theory of relativity in simple terms.")
print(response)

Advanced Usage

Click to expand

Streaming Responses

stream = client.generate_stream(
    ChatRequest(
        messages=[{"role": "user", "content": "Write a haiku about AI."}],
        model="llama3.1-70b",
        stream=True
    )
)

for chunk in stream:
    print(chunk['data'], end='', flush=True)

Using Different Models

response_8b = client.ask("Summarize the importance of quantum computing.", model="llama3.1-8b")
response_70b = client.ask("Summarize the importance of quantum computing.", model="llama3.1-70b")

print("8B Model:", response_8b)
print("70B Model:", response_70b)

JSON Responses

json_response = client.ask(
    "List the top 5 programming languages in 2023.",
    json_response=True
)
print(json_response)

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🖥️ Server

Starting the Server

client = CerebrasWithCookie(cookie_path='cookies.json')
client.start_server(host="0.0.0.0", port=8000)

API Endpoints

Endpoint	Description
/v1/chat/completions	Chat completions API
/v1/models	List available models

Swagger Documentation

Access the interactive API documentation at http://localhost:8000/docs when the server is running.

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🔌 OpenAI Compatibility

Cerebra.aiAPI is designed as a drop-in replacement for the OpenAI Python library.

from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:8000/v1",
    api_key="dummy_key"
)

response = client.chat.completions.create(
    model="llama3.1-70b",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain the concept of machine learning."}
    ]
)

print(response.choices[0].message.content)

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🧰 Tools

Cerebra.aiAPI supports tool calling.

Example: Web Search Tool

def get_web_info(query: str, max_results: int = 5) -> str:
    results = search(query, num_results=max_results)
    return json.dumps([{"title": r.title, "link": r.url, "snippet": r.description} for r in results])

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_web_info",
            "description": "Search the web for current information",
            "parameters": {
                "type": "object",
                "properties": {
                    "query": {"type": "string", "description": "The search query"},
                    "max_results": {"type": "integer", "description": "Maximum number of results"}
                },
                "required": ["query"]
            }
        }
    }
]

response = client.chat.completions.create(
    model="llama3.1-70b",
    messages=[{"role": "user", "content": "What are the latest developments in AI?"}],
    tools=tools,
    tool_choice="auto"
)

print(response.choices[0].message.content)

More Tool Examples

Calculator Tool

def calculate(expression: str) -> str:
    try:
        return str(eval(expression))
    except Exception as e:
        return f"Error: {str(e)}"

# Usage in tools list
{
    "type": "function",
    "function": {
        "name": "calculate",
        "description": "Perform mathematical calculations",
        "parameters": {
            "type": "object",
            "properties": {
                "expression": {"type": "string", "description": "The mathematical expression to evaluate"}
            },
            "required": ["expression"]
        }
    }
}

Weather Information Tool

import requests

def get_weather(city: str) -> str:
    API_KEY = "your_openweathermap_api_key"
    url = f"http://api.openweathermap.org/data/2.5/weather?q={city}&appid={API_KEY}&units=metric"
    response = requests.get(url)
    data = response.json()
    return f"The current temperature in {city} is {data['main']['temp']}°C with {data['weather'][0]['description']}."

# Usage in tools list
{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "Get current weather information for a city",
        "parameters": {
            "type": "object",
            "properties": {
                "city": {"type": "string", "description": "The name of the city"}
            },
            "required": ["city"]
        }
    }
}

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🤝 Contributing

We welcome contributions from the community! Here's how you can help:

1. Fork the repository
2. Clone your fork: git clone https://github.com/OE-LUCIFER/Cerebra.aiAPI.git
3. Create a new branch: git checkout -b feature-name
4. Make your changes and commit them: git commit -m 'Add some feature'
5. Push to the branch: git push origin feature-name
6. Submit a pull request

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📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Made with ❤️ by Team HelpingAI

⭐️ Star us on GitHub — it motivates us a lot!

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