API_DOCUMENTATION.md

Loomyloo Personal Coder AI - API Reference

This document details all available endpoints and parameters for your custom AI API hosted on Hugging Face Spaces.

🌍 Base URL

https://loomisgitarrist-personal-coder-ai.hf.space

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📡 Endpoints

1. Chat Completion (/ask)

Generates a response from the Qwen 2.5 Coder 1.5B model.

• Type: Coding Assistant

• Status: Active (Stable)

• Context: 20 Message Memory

• Method: GET

• URL: /ask

Parameters

Parameter	Type	Required	Description
prompt	string	Yes	The user's input message, question, or code task.

Example Request

curl "https://loomisgitarrist-personal-coder-ai.hf.space/ask?prompt=Write%20a%20Python%20Hello%20World"

Example Response (JSON)

{
  "generated_text": "Here is the Python code:\n\n```python\nprint('Hello, World!')\n```"
}

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2. Reset Memory (/reset)

Clears the conversation history stored on the server. Use this when starting a completely new task or topic to prevent the AI from getting confused by previous context.

• Method: GET
• URL: /reset

Parameters

None

Example Request

curl "https://loomisgitarrist-personal-coder-ai.hf.space/reset"

Example Response (JSON)

{
  "status": "Memory reset",
  "message": "Conversation history cleared."
}

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3. Visual Chat UI (/)

A graphical web interface to chat with the model in your browser.

• Method: GET
• URL: /
• Access: Open https://loomisgitarrist-personal-coder-ai.hf.space in your browser.

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💻 Code Integration Examples

Python Client

import requests

API_URL = "https://loomisgitarrist-personal-coder-ai.hf.space"

def ask_ai(prompt):
    # 1. Send request
    response = requests.get(f"{API_URL}/ask", params={"prompt": prompt})
    
    # 2. Parse JSON
    if response.status_code == 200:
        return response.json()['generated_text']
    else:
        return f"Error: {response.status_code}"

# Usage
print(ask_ai("Write a binary search function in Go"))

JavaScript / Node.js Client

const API_URL = "https://loomisgitarrist-personal-coder-ai.hf.space";

async function askAI(prompt) {
  try {
    const response = await fetch(`${API_URL}/ask?prompt=${encodeURIComponent(prompt)}`);
    const data = await response.json();
    console.log("AI Response:", data.generated_text);
  } catch (error) {
    console.error("Error:", error);
  }
}

// Usage
askAI("Explain how to use Docker with FastAPI");

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⚙️ Model Configuration (Server-Side)

These settings are hardcoded on the server for stability on the free tier.

• Model: Qwen2.5-Coder-1.5B-Instruct
• Max Response Length: 512 tokens
• Temperature: 0.7 (Creativity balance)
• Top P: 0.9
• Memory Limit: Last 20 messages