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SDKs & Libraries

Official GPTfake SDKs for accessing AI censorship monitoring data programmatically.

Official SDKs​

Python SDK​

Installation

pip install gptfake

Quick Start

from gptfake import GPTfakeClient

client = GPTfakeClient(api_key="your-api-key")

# Get current metrics for a model
metrics = client.monitoring.get_metrics("chatgpt")
print(f"Censorship Rate: {metrics.censorship_rate}%")
print(f"Bias Score: {metrics.bias_score}")
print(f"Transparency: {metrics.transparency_score}/100")

# Compare multiple models
comparison = client.monitoring.compare_models(
    models=["chatgpt", "claude", "gemini"]
)
for model in comparison:
    print(f"{model.name}: {model.censorship_rate}% censorship")

# Get historical data
history = client.monitoring.get_history("chatgpt", days=30)
for day in history:
    print(f"{day.date}: {day.censorship_rate}%")

Features

  • Async/await support with asyncio
  • Pandas DataFrame integration
  • Type hints included
  • Comprehensive documentation
  • Jupyter notebook friendly

JavaScript SDK​

Installation

npm install gptfake

Quick Start

import { GPTfakeClient } from 'gptfake';

const client = new GPTfakeClient({
  apiKey: 'your-api-key'
});

// Get current metrics
const metrics = await client.monitoring.getMetrics('chatgpt');
console.log(`Censorship Rate: ${metrics.censorshipRate}%`);

// Compare models
const comparison = await client.monitoring.compareModels([
  'chatgpt', 'claude', 'gemini'
]);

// Get historical data
const history = await client.monitoring.getHistory('chatgpt', { days: 30 });

Features

  • Full TypeScript support
  • Promise-based API
  • Browser and Node.js compatible
  • Automatic retry logic
  • Comprehensive error handling

SDK Comparison​

FeaturePythonJavaScript
Installationpipnpm
Type SupportType hintsTypeScript
AsyncasyncioPromise
Pandas IntegrationYesNo
Browser SupportNoYes
DocumentationComprehensiveComprehensive

Common Operations​

Get Model Metrics​

# Python
metrics = client.monitoring.get_metrics("chatgpt")
// JavaScript
const metrics = await client.monitoring.getMetrics('chatgpt');

Compare Models​

# Python
comparison = client.monitoring.compare_models([
    "chatgpt", "claude", "gemini", "mistral", "qwen"
])
// JavaScript
const comparison = await client.monitoring.compareModels([
  'chatgpt', 'claude', 'gemini', 'mistral', 'qwen'
]);

Get Historical Data​

# Python
history = client.monitoring.get_history("chatgpt", days=30)
// JavaScript
const history = await client.monitoring.getHistory('chatgpt', { days: 30 });

Export Data​

# Python
data = client.research.export_data(
    models=["chatgpt", "claude"],
    format="csv",
    days=90
)
// JavaScript
const data = await client.research.exportData({
  models: ['chatgpt', 'claude'],
  format: 'csv',
  days: 90
});

Error Handling​

# Python
from gptfake.exceptions import (
    AuthenticationError,
    RateLimitError,
    ModelNotFoundError
)

try:
    metrics = client.monitoring.get_metrics("invalid-model")
except AuthenticationError:
    print("Check your API key")
except RateLimitError:
    print("Too many requests, please wait")
except ModelNotFoundError:
    print("Model not found")
// JavaScript
try {
  const metrics = await client.monitoring.getMetrics('invalid-model');
} catch (error) {
  if (error.code === 'AUTHENTICATION_ERROR') {
    console.log('Check your API key');
  } else if (error.code === 'RATE_LIMIT_ERROR') {
    console.log('Too many requests');
  }
}

CLI Tool​

In addition to SDKs, we offer a command-line interface:

pip install gptfake-cli

# Get metrics
gptfake metrics chatgpt

# Compare models
gptfake compare chatgpt claude gemini

# Export data
gptfake export --format csv --days 30 --output data.csv

Contributing​

Our SDKs are open source:

We welcome contributions, bug reports, and feature requests.

Support​

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