BLACKBOX AI is a coding-focused AI platform that delivers precise, context-aware support to streamline software development and tackle complex programming challenges efficiently.
The BlackboxAI agent can help you solve any code-related task.
- Framework: LangChain
- Tools used: Coral Server Tools
- AI model: OpenAI GPT-4.1-mini
- Date added: 06/07/25
- Reference: BlackboxAI
- License: MIT
# In a new terminal clone the repository:
git clone https://github.com/Coral-Protocol/Coral-BlackboxAI-Agent.git
# Navigate to the project directory:
cd Coral-BlackboxAI-Agent
# Run the build script (Linux/Mac):
./build.sh
# Or on Windows:
# build.bat# In a new terminal clone the repository:
git clone https://github.com/Coral-Protocol/Coral-BlackboxAI-Agent.git
# Navigate to the project directory:
cd Coral-BlackboxAI-Agent
# Download and run the UV installer, setting the installation directory to the current one
curl -LsSf https://astral.sh/uv/install.sh | env UV_INSTALL_DIR=$(pwd) sh
# Create a virtual environment named `.venv` using UV
uv venv .venv
# Activate the virtual environment
source .venv/bin/activate
# install uv
pip install uv
# Install dependencies from `pyproject.toml` using `uv`:
uv syncGet the API Keys:
# Create .env file in project root
cp -r .env.example .envYou can run in either of the below modes to get your system running.
- The Executable Model is part of the Coral Protocol Orchestrator which works with Coral Studio UI.
- The Dev Mode allows the Coral Server and all agents to be seaprately running on each terminal without UI support.
Checkout: How to Build a Multi-Agent System with Awesome Open Source Agents using Coral Protocol and update the file: coral-server/src/main/resources/application.yaml with the details below, then run the Coral Server and Coral Studio UI. You do not need to set up the .env in the project directory for running in this mode; it will be captured through the variables below.
For Linux or MAC:
# PROJECT_DIR="/PATH/TO/YOUR/PROJECT"
applications:
- id: "app"
name: "Default Application"
description: "Default application for testing"
privacyKeys:
- "default-key"
- "public"
- "priv"
registry:
blackboxai_agent:
options:
- name: "BLACKBOXAI_API_KEY"
type: "string"
description: "API key for the service"
runtime:
type: "executable"
command: ["bash", "-c", "${PROJECT_DIR}/run_agent.sh main.py"]
environment:
- name: "BLACKBOXAI_API_KEY"
from: "BLACKBOXAI_API_KEY"
- name: "BLACKBOXAI_URL"
value: "https://api.blackbox.ai"
- name: "MODEL_NAME"
value: "blackboxai/openai/gpt-4.1-mini"
For Windows, create a powershell command (run_agent.ps1) and run:
command: ["powershell","-ExecutionPolicy", "Bypass", "-File", "${PROJECT_DIR}/run_agent.ps1","main.py"]Ensure that the Coral Server is running on your system and run below command in a separate terminal.
# Run the agent using `uv`:
uv run python main.py# Input:
help me design a simple front end
# Output:
Here is a simple front end example provided by BlackboxAI agent:
---
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Simple Front End</title>
<style>
body {
font-family: Arial, sans-serif;
margin: 20px;
background-color: #f4f4f4;
}
h1 {
color: #333;
}
button {
padding: 10px 15px;
background-color: #007BFF;
color: white;
border: none;
border-radius: 5px;
cursor: pointer;
}
button:hover {
background-color: #0056b3;
}
</style>
</head>
<body>
<h1>Welcome to Simple Front End!</h1>
<button onclick="showMessage()">Click Me</button>
<p id="message"></p>
<script>
function showMessage() {
document.getElementById('message').innerText = 'Hello! You clicked the button.';
}
</script>
</body>
</html>
---
This creates a basic web page with a heading, a button, and a message that appears when you click the button. Would you like to customize this further or need help with something more specific?- Name: Xinxing
- Affiliation: Coral Protocol
- Contact: Discord