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* Update model configurations, provider implementations, and documentation - Updated model names and aliases for Qwen QVQ 72B and Qwen 2 72B (@TheFirstNoob) - Revised HuggingSpace class configuration, added default_image_model - Added llama-3.2-70b alias for Llama 3.2 70B model in AutonomousAI - Removed BlackboxCreateAgent class - Added gpt-4o alias for Copilot model - Moved api_key to Mhystical class attribute - Added models property with default_model value for Free2GPT - Simplified Jmuz class implementation - Improved image generation and model handling in DeepInfra - Standardized default models and removed aliases in Gemini - Replaced model aliases with direct model list in GlhfChat (@TheFirstNoob) - Removed trailing slash from image generation URL in PollinationsAI (https://github.com/xtekky/gpt4free/issues/2571) - Updated llama and qwen model configurations - Enhanced provider documentation and model details * Removed from (g4f/models.py) 'Yqcloud' provider from Default due to error 'ResponseStatusError: Response 429: 文字过长,请删减后重试。' * Update docs/providers-and-models.md * refactor(g4f/Provider/DDG.py): Add error handling and rate limiting to DDG provider - Add custom exception classes for rate limits, timeouts, and conversation limits - Implement rate limiting with sleep between requests (0.75s minimum delay) - Add model validation method to check supported models - Add proper error handling for API responses with custom exceptions - Improve session cookie handling for conversation persistence - Clean up User-Agent string and remove redundant code - Add proper error propagation through async generator Breaking changes: - New custom exceptions may require updates to error handling code - Rate limiting affects request timing and throughput - Model validation is now stricter Related: - Adds error handling similar to standard API clients - Improves reliability and robustness of chat interactions * Update g4f/models.py g4f/Provider/PollinationsAI.py * Update g4f/models.py * Restored provider which was not working and was disabled (g4f/Provider/DeepInfraChat.py) * Fixing a bug with Streaming Completions * Update g4f/Provider/PollinationsAI.py * Update g4f/Provider/Blackbox.py g4f/Provider/DDG.py * Added another model for generating images 'ImageGeneration2' to the 'Blackbox' provider * Update docs/providers-and-models.md * Update g4f/models.py g4f/Provider/Blackbox.py * Added a new OIVSCode provider from the Text Models and Vision (Image Upload) model * Update docs/providers-and-models.md * docs: add Conversation Memory class with context handling requested by @TheFirstNoob * Simplified README.md documentation added new docs/configuration.md documentation * Update add README.md docs/configuration.md * Update README.md * Update docs/providers-and-models.md g4f/models.py g4f/Provider/PollinationsAI.py * Added new model deepseek-r1 to Blackbox provider. @TheFirstNoob * Fixed bugs and updated docs/providers-and-models.md etc/unittest/client.py g4f/models.py g4f/Provider/. --------- Co-authored-by: kqlio67 <> Co-authored-by: H Lohaus <hlohaus@users.noreply.github.com>
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# G4F - Authentication Guide
This documentation explains how to authenticate with G4F providers and configure GUI security. It covers API key management, cookie-based authentication, rate limiting, and GUI access controls.
Table of Contents
Provider Authentication
Prerequisites
- Python 3.7+
- Installed
g4fpackage:pip install g4f - API keys or cookies from providers (if required).
API Key Setup
Step 1: Set Environment Variables
For Linux/macOS (Terminal):
# Example for Anthropic
export ANTHROPIC_API_KEY="your_key_here"
# Example for HuggingFace
export HUGGINGFACE_API_KEY="another_key_here"
For Windows (Command Prompt):
:: Example for Anthropic
set ANTHROPIC_API_KEY=your_key_here
:: Example for HuggingFace
set HUGGINGFACE_API_KEY=another_key_here
For Windows (PowerShell):
# Example for Anthropic
$env:ANTHROPIC_API_KEY = "your_key_here"
# Example for HuggingFace
$env:HUGGINGFACE_API_KEY = "another_key_here"
Step 2: Initialize Client
from g4f.client import Client
# Example for Anthropic
client = Client(
provider="g4f.Provider.Anthropic",
api_key="your_key_here" # Or use os.getenv("ANTHROPIC_API_KEY")
)
Synchronous Usage
from g4f.client import Client
# Initialize with Anthropic
client = Client(provider="g4f.Provider.Anthropic", api_key="your_key_here")
# Simple request
response = client.chat.completions.create(
model="claude-3.5-sonnet",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
Asynchronous Usage
import asyncio
from g4f.client import AsyncClient
async def main():
# Initialize with Groq
client = AsyncClient(provider="g4f.Provider.Groq", api_key="your_key_here")
response = await client.chat.completions.create(
model="mixtral-8x7b",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
asyncio.run(main())
Multiple Providers with API Keys
import os
from g4f.client import Client
# Using environment variables
providers = {
"Anthropic": os.getenv("ANTHROPIC_API_KEY"),
"Groq": os.getenv("GROQ_API_KEY")
}
for provider_name, api_key in providers.items():
client = Client(provider=f"g4f.Provider.{provider_name}", api_key=api_key)
response = client.chat.completions.create(
model="claude-3.5-sonnet",
messages=[{"role": "user", "content": f"Hello from {provider_name}!"}]
)
print(f"{provider_name}: {response.choices[0].message.content}")
Cookie-Based Authentication
For Providers Like Gemini/Bing:
- Open your browser and log in to the provider's website.
- Use developer tools (F12) to copy cookies:
- Chrome/Edge: Application → Cookies
- Firefox: Storage → Cookies
from g4f.Provider import Gemini
# Initialize with cookies
client = Client(
provider=Gemini,
cookies={
"__Secure-1PSID": "your_cookie_value_here",
"__Secure-1PSIDTS": "timestamp_value_here"
}
)
Rate Limiting
from aiolimiter import AsyncLimiter
# Limit to 5 requests per second
rate_limiter = AsyncLimiter(max_rate=5, time_period=1)
async def make_request():
async with rate_limiter:
return await client.chat.completions.create(...)
Error Handling
from tenacity import retry, stop_after_attempt, wait_exponential
@retry(stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=4, max=10))
def safe_request():
try:
return client.chat.completions.create(...)
except Exception as e:
print(f"Attempt failed: {str(e)}")
raise
Supported Providers
| Provider | Auth Type | Example Models |
|---|---|---|
| Anthropic | API Key | claude-3.5-sonnet |
| Gemini | Cookies | gemini-1.5-pro |
| Groq | API Key | mixtral-8x7b |
| HuggingFace | API Key | llama-3.1-70b |
Full list: Providers and Models
GUI Authentication
Server Setup
- Create a password:
# Linux/macOS export G4F_API_KEY="your_password_here" # Windows (Command Prompt) set G4F_API_KEY=your_password_here # Windows (PowerShell) $env:G4F_API_KEY = "your_password_here" - Start the server:
python -m g4f --debug --port 8080 --g4f-api-key $G4F_API_KEY
Browser Access
- Navigate to
http://localhost:8080/chat/. - Use credentials:
- Username: Any value (e.g.,
admin). - Password: Your
G4F_API_KEY.
- Username: Any value (e.g.,
Programmatic Access
import requests
response = requests.get(
"http://localhost:8080/chat/",
auth=("admin", "your_password_here")
)
print("Success!" if response.status_code == 200 else f"Failed: {response.status_code}")
Best Practices
- 🔒 Never hardcode keys
- Use
.envfiles or secret managers like AWS Secrets Manager.
- Use
- 🔄 Rotate keys every 90 days
- Especially critical for production environments.
- 📊 Monitor API usage
- Use tools like Prometheus/Grafana for tracking.
- ♻️ Retry transient errors
- Use the
tenacitylibrary for robust retry logic.
- Use the
Troubleshooting
| Issue | Solution |
|---|---|
| "Invalid API Key" | 1. Verify key spelling 2. Regenerate key in provider dashboard |
| "Cookie Expired" | 1. Re-login to provider website 2. Update cookie values |
| "Rate Limit Exceeded" | 1. Implement rate limiting 2. Upgrade provider plan |
| "Provider Not Found" | 1. Check provider name spelling 2. Verify provider compatibility |