AICoding Connection Algorithm

Connect to AICoding.io.vn API with OpenAI and Anthropic format support

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AICoding Connection Algorithm

Dual-format connection algorithm for AICoding.io.vn API supporting both OpenAI-compatible and Anthropic-native message formats.

Overview

The AICoding Connection Algorithm provides flexible access to AICoding.io.vn's Claude AI models through both OpenAI-compatible chat completions and Anthropic's native messages endpoint.

Features

✅ Dual Format Support: OpenAI and Anthropic formats
✅ Claude Models: Sonnet 4.5, Opus 4.5, Haiku 4.5
✅ GPT Models: GPT-5.1, GPT-5.1-Codex, GPT-5.2, GPT-5.2-Codex
✅ Other Models: Gemini 3 Pro, GLM-4.6
✅ Health Monitoring: Real-time health checks (~317ms)

API Configuration

Base URL: https://aicoding.io.vn
API Key: Environment variable AICODING_API_KEY or passed as parameter

Headers:
{
    "Authorization": "Bearer {api_key}",
    "Content-Type": "application/json",
    "anthropic-version": "2023-06-01"  # For Anthropic endpoints
}

Available Models

Model	ID	Cost Multiplier
Claude Sonnet 4.5	claude-sonnet-4-5-20250929	1x
Claude Opus 4.5	claude-opus-4-5-20251001	1.5x
Claude Haiku 4.5	claude-haiku-4-5-20251001	1x
Gemini 3 Pro	gemini-3-pro-preview	1x
GPT-5.1	gpt-5.1	1x
GPT-5.1-Codex	gpt-5.1-codex	1x
GPT-5.2	gpt-5.2	1x
GPT-5.2-Codex	gpt-5.2-codex	1x
GLM-4.6	glm-4.6	1x

Supported Actions

1. Connect

Test connection and discover models.

result = aicoding.execute({"action": "connect"})

2. List Models

Get all available models.

result = aicoding.execute({"action": "list_models"})

3. Chat (OpenAI Format)

Send OpenAI-compatible chat requests.

result = aicoding.execute({
    "action": "chat",
    "model": "gpt-5.1-codex",
    "messages": [
        {"role": "system", "content": "You are a coding assistant."},
        {"role": "user", "content": "Write a quicksort in Python"}
    ],
    "temperature": 0.3,
    "max_tokens": 1500
})

4. Messages (Anthropic Format)

Send Anthropic-native message requests.

result = aicoding.execute({
    "action": "messages",
    "model": "claude-sonnet-4-5-20250929",
    "messages": [
        {"role": "user", "content": "Explain quantum computing"}
    ],
    "temperature": 0.7,
    "max_tokens": 2000
})

5. Health

Check API health.

result = aicoding.execute({"action": "health"})
# Average: 317ms response time

Usage Examples

Basic Connection

from core.algorithms.algorithm_manager import AlgorithmManager

manager = AlgorithmManager(auto_scan=True)
aicoding = manager.get_algorithm("AICodingConnection")

# Test connection
result = aicoding.execute({"action": "connect"})
print(f"Available models: {result.data['total_models']}")

OpenAI Format (Standard)

# Best for GPT models
result = aicoding.execute({
    "action": "chat",
    "model": "gpt-5.1-codex",
    "messages": [
        {"role": "user", "content": "Debug this code: ..."}
    ],
    "temperature": 0.3
})

print(result.data['response'])
print(f"Tokens used: {result.data['usage']['total_tokens']}")

Anthropic Format (Native)

# Best for Claude models (more efficient)
result = aicoding.execute({
    "action": "messages",
    "model": "claude-opus-4-5-20251001",
    "messages": [
        {"role": "user", "content": "Write a design doc for..."}
    ],
    "temperature": 0.7,
    "max_tokens": 4000
})

print(result.data['response'])

Format Comparison

Feature	OpenAI Format	Anthropic Format
Endpoint	/v1/chat/completions	/v1/messages
Best For	GPT models	Claude models
System Message	In messages array	Separate field
Response Key	choices[0].message.content	content[0].text
Token Field	usage.total_tokens	usage.input_tokens + output_tokens

Best Practices

Choose Right Format:
- Use chat for GPT models
- Use messages for Claude models (native format, more efficient)
Token Management:
- Claude Opus 4.5: multiply tokens by 1.5x
- Monitor usage with result.data['usage']
Temperature Settings:
- Code: 0.1-0.3
- Creative writing: 0.7-0.9
- General: 0.5-0.7
Error Handling:

result = aicoding.execute({...})

if result.status == "success":
    # Process response
    response = result.data['response']
elif result.status == "error":
    # Handle error
    print(f"Error: {result.error}")

Performance

Health Check: ~317ms
Model Discovery: <1s
Chat Response: 2-15s (varies by model and tokens)
Reliability: 99.9% uptime

Integration Examples

With 3-AI Orchestrator

# Use AICoding for alternative Claude access
orchestrator_config = {
    "primary": {"provider": "aicoding", "model": "claude-opus-4-5-20251001"},
    "reviewer": {"provider": "v98", "model": "gpt-5.1-codex"},
    "consultant": {"provider": "aicoding", "model": "claude-sonnet-4-5-20250929"}
}

Workflow Chain

# Document generation workflow
workflow = [
    {"algorithm": "AICodingConnection", "action": "messages", "model": "claude-sonnet..."},
    {"algorithm": "CodeReviewer"},
    {"algorithm": "DocumentationGenerator"}
]

Troubleshooting

Issue	Solution
500 Server Error	API temporarily unavailable, retry with backoff
Model not available	Check model list with `list_models`
Token limit exceeded	Reduce max_tokens or split request
Health check fails	Verify network connectivity

Cost Optimization

# Use appropriate model for task
tasks = {
    "simple_qa": "claude-haiku-4-5-20251001",      # Cheapest
    "code_review": "gpt-5.1-codex",                # Best for code
    "complex_reasoning": "claude-opus-4-5-20251001"  # Most capable (1.5x cost)
}

Related Algorithms

V98Connection: Alternative API with 475+ models
ThreeAIOrchestrator: Multi-model workflow
SmartModelRouter: Automatic model selection

File Location

D:\Antigravity\Dive AI\core\algorithms\operational\aicoding_connection.py

Version

v1.0 - Initial release with dual-format support

Repository: duclm1x1/Dive-Ai
Commit: 20ba150

Last updated: 27 days ago
Created: 27 days ago

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