OverseeX AutoGen Integration
Auto-instrumentation for Microsoft AutoGen multi-agent conversations.
Installation
pip install overseex-autogen
Quick Start
from autogen import AssistantAgent, UserProxyAgent
from overseex_autogen import monitor_autogen
# Create your AutoGen agents
assistant = AssistantAgent("assistant", llm_config=llm_config)
user_proxy = UserProxyAgent("user_proxy")
# Monitor the conversation
with monitor_autogen(api_key="ag_live_...", agents=[assistant, user_proxy]) as monitor:
user_proxy.initiate_chat(assistant, message="What is the capital of France?")
# All interactions are automatically traced to OverseeX!
Features
- Zero-config Auto-instrumentation: Just wrap your code and traces are captured
- Multi-turn Conversation Tracking: Every message between agents is recorded
- Function Call Monitoring: Track all function/tool executions
- Agent Role Analysis: Monitor agent behaviors and coordination
- Coordination Intelligence: Detect handoff patterns and issues
Usage
Context Manager
from overseex_autogen import AutoGenMonitor
with AutoGenMonitor(api_key="your-api-key") as monitor:
# Start tracking
monitor.start_chat([assistant, user_proxy])
# Your AutoGen code
result = user_proxy.initiate_chat(assistant, message="Hello!")
# End tracking
monitor.end_chat()
Manual Callback
from overseex_autogen import OverseeXAutoGenCallback
callback = OverseeXAutoGenCallback(
api_key="your-api-key",
capture_functions=True,
capture_messages=True,
verbose=True
)
# Register agents
callback.register_agent(assistant)
callback.register_agent(user_proxy)
# Start conversation tracking
callback.start_conversation([assistant, user_proxy])
# ... run your AutoGen code ...
# End and send traces
callback.end_conversation()
What Gets Captured
- Messages: All inter-agent communication
- Function Calls: Tool usage with inputs/outputs
- Agent Roles: AssistantAgent, UserProxyAgent, GroupChat, etc.
- Conversation Flow: Turn-by-turn execution
- Token Usage: LLM token consumption
- Coordination Events: Handoffs between agents
Configuration
OverseeXAutoGenCallback(
api_key="your-api-key", # Required
base_url="https://api.overseex.com", # Optional
capture_functions=True, # Capture function calls
capture_messages=True, # Capture message content
capture_system_prompts=False, # Capture system prompts (may contain sensitive data)
auto_register_agents=True, # Auto-register agents in OverseeX
max_message_length=2000, # Truncate long messages
verbose=False, # Enable debug logging
)
License
MIT
Metadata
Release files for overseex-autogen 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| overseex_autogen-0.1.0.tar.gz | 9.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| overseex_autogen-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 17.6 kB
Release files / overseex_autogen-0.1.0.tar.gz
| Download URL | overseex_autogen-0.1.0.tar.gz |
|---|---|
| Size | 9.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.2
|
Release files / overseex_autogen-0.1.0-py3-none-any.whl
| Download URL | overseex_autogen-0.1.0-py3-none-any.whl |
|---|---|
| Size | 8.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.2
|