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simulacra-forge
by janaador0827-commits
Async multi-agent dialogue simulator for studying emergent AI character behavior
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Updated Aug 25, 2026
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Summary
Implements autonomous multi-agent system dialogue simulations to study AI character emergence and interaction patterns. Runs agents as async participants over websockets/HTTP (FastAPI) and connects to LLM backends like OpenAI and Ollama to drive conversations and behaviors (tool-use pattern). Exposes configuration for agent personas, messaging rules, and scenario scripts to reproduce emergent dynamics and failure modes.
Why It Matters
As agents become more autonomous, their interactions produce emergent behaviors that affect trust and reliability. Simulacra Forge makes those interactions observable and reproducible, letting teams surface failure modes, delegation breakdowns, and reputation-relevant signals. Until now many multi-agent demos were ad hoc; this repo gives a repeatable playground for collecting agent-to-agent evaluation data and building agent track records.
Ideal For
Researchers and engineers exploring multi-agent interactions, emergent failure modes, or building reproducible agent-to-agent evaluation scenarios (e.g., Mutual Verification Pattern).
Applications
- Reproduce and analyze emergent behaviors in multi-agent conversations
- Collect interaction logs and metrics for agent-to-agent evaluation and reputation building
- Stress-test delegation and failure modes across LLM backends and networked agents
Works With
openaiollamafastapipydanticwebsocketspythonasyncio
Topics
ai-simulationasynciofastapillmmulti-agent-systemollamaopenaipydanticpythonwebsockets
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autogencrewai
Keywords
multi-agent trustagent-to-agent evaluationagent track recordmulti-agent orchestration