AgentHub is a Python SDK for connecting to advanced LLMs like GPT-5.2, Claude 4.5, and Gemini 3. It enables developers to build AI-powered applications with precise LLM integration. Operations teams benefit from streamlined workflows and reduced complexity in managing multiple AI models. The SDK connects to various AI services and workflows, allowing for efficient automation and enhanced productivity.
git clone https://github.com/Prism-Shadow/AgentHub.gitAgentHub is a Python SDK for connecting to advanced LLMs like GPT-5.2, Claude 4.5, and Gemini 3. It enables developers to build AI-powered applications with precise LLM integration. Operations teams benefit from streamlined workflows and reduced complexity in managing multiple AI models. The SDK connects to various AI services and workflows, allowing for efficient automation and enhanced productivity.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/Prism-Shadow/AgentHubCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Using AgentHub, create a Python script that connects to [LLM_MODEL] and automates [SPECIFIC_TASK] for [COMPANY] in the [INDUSTRY] sector. The script should handle [DATA] and integrate with [EXISTING_SYSTEM]. Provide error handling and logging for debugging purposes.
# AgentHub Automation Script for [COMPANY]
```python
import agenthub
# Initialize the AgentHub client
client = agenthub.Client(api_key='your_api_key_here')
# Define the LLM model and task
model = 'GPT-5.2'
task = 'Generate customer support responses'
# Set up the automation workflow
def automate_support_responses(data):
responses = []
for item in data:
try:
response = client.complete(
model=model,
prompt=f"Generate a support response for: {item['query']}",
max_tokens=150
)
responses.append(response['choices'][0]['text'])
except Exception as e:
print(f"Error processing {item['query']}: {str(e)})
return responses
# Example usage
data = [
{'query': 'How do I reset my password?'},
{'query': 'I can't log in to my account.'},
{'query': 'What are your business hours?'}
]
support_responses = automate_support_responses(data)
for i, response in enumerate(support_responses):
print(f"Response {i+1}: {response}")
```
## Output Example
1. **Response 1**: To reset your password, please visit our website and click on the 'Forgot Password' link. Follow the instructions to receive a reset link via email.
2. **Response 2**: If you're unable to log in, please ensure you're using the correct email address and password. If you've forgotten your password, you can reset it by clicking on the 'Forgot Password' link on our login page.
3. **Response 3**: Our business hours are Monday through Friday, 9:00 AM to 5:00 PM. We are closed on weekends and major holidays.Simulate and evaluate AI agents effectively
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