Thought on multi-agent key management

[asterworks]

PraisonAI is great — we built AsterWorks for exactly this use case. Running multi-agent workflows across different LLMs means managing a bunch of API keys. We made a unified gateway that works with OpenAI, Anthropic, and Gemini SDKs without changing code. Might be useful as a recommended integration.

[praisonai-triage-agent]

👋 Thanks for opening this issue, @asterworks!

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Analysis of AsterWorks Key Management Integration

• Read AGENTS.md to understand architecture rules
• Research existing key management in PraisonAI
• Analyze where AsterWorks integration would fit
• Provide guidance on integration approach

Integration Analysis

Current State

PraisonAI currently manages API keys through:

• Environment variables (standard approach)
• Individual SDK client initialization per model provider
• Gateway protocols for multi-agent coordination

AsterWorks Integration Approach

Based on PraisonAI's architecture guidelines, the AsterWorks unified gateway would fit best as:

🎯 Plugin Category - Framework lifecycle extension under PraisonAI-Plugins

Architecture Routing Decision

According to AGENTS.md Section 2 architecture validation:

• Not Core SDK: This is heavy implementation with external dependencies
• Not Wrapper: This isn't a PraisonAI-specific CLI tool
• ✅ Plugin: This is a framework lifecycle extension that replaces API key management behavior

Recommended Integration Pattern

# Plugin implementation approach
from praisonaiagents.plugins import Plugin
from praisonaiagents.llm import LLMProtocol

class AsterWorksKeyManagementPlugin(Plugin):
    """Plugin to route LLM calls through AsterWorks unified gateway"""
    
    def __init__(self, asterworks_endpoint: str, api_key: str):
        self.endpoint = asterworks_endpoint
        self.api_key = api_key
    
    def on_llm_request(self, event):
        # Route through AsterWorks instead of direct provider calls
        pass

Benefits for PraisonAI Users

1. Simplified Key Management: One API key instead of managing OpenAI, Anthropic, Gemini separately
2. Unified Billing/Monitoring: Single point for cost tracking across providers
3. Provider Abstraction: Switch models without SDK changes

Next Steps

1. Create a plugin in the PraisonAI-Plugins repository
2. Hook into PraisonAI's LLM client layer via the plugin system
3. Provide documentation for users on the unified gateway benefits

This integration preserves PraisonAI's protocol-driven architecture while offering users a cleaner key management experience.