🧠
Autogen Multi Agent Chat model by Ei Ayw
⭐ 36.2
🧠
Model

Autogen Multi Agent Chat

by Ei Ayw ei-ayw/autogen-multi-agent-chat
Free2AITools Nexus Index
36.2
S: Semantic 50

Query-time baseline · scored live at search

A: Authority —

Not yet linked · authority accrues from citations / mesh

P: Popularity 0
R: Recency 67
Q: Quality 70
Tech Context
Vital Performance —
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 36.2 FNI Score
Tiny - Params
- Context
0 Downloads
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID ei-ayw/autogen-multi-agent-chat
License MIT
Provider github
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{ei_ayw_autogen_multi_agent_chat,
  author = {Ei Ayw},
  title = {Autogen Multi Agent Chat Model},
  year = {2026},
  howpublished = {\url{https://github.com/Ei-Ayw/autogen-multi-agent-chat}},
  note = {Accessed via Free2AITools.}
}
APA Style
Ei Ayw. (2026). Autogen Multi Agent Chat [Model]. Free2AITools. https://github.com/Ei-Ayw/autogen-multi-agent-chat

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ™ Git Clone
git clone https://github.com/Ei-Ayw/autogen-multi-agent-chat

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) —

Not yet linked · authority accrues from citations / mesh

Popularity (P) 0
Recency (R) 67
Quality (Q) 70

πŸ’¬ Index Insight

FNI V2.0 for Autogen Multi Agent Chat: Authority (A:not yet linked), Popularity (P:0), Recency (R:67), Quality (Q:70). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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πŸš€ What's Next?

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Deployment reference

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Technical Deep Dive

AutoGen Multi-Agent Chat

An industrial-grade, multi-agent AI coding platform built on Microsoft AutoGen. Three specialized AI agents collaborate autonomously to analyze requirements, write code, review it, and execute β€” featuring a full-stack React + FastAPI web interface.

Features

  • Three-Agent Architecture β€” Admin (executor), Architect (coder), Reviewer (auditor)
  • Local Safe Sandbox β€” Regex-based guardrails block dangerous commands; subprocess timeout prevents infinite loops
  • Agent Toolchain β€” File read/write, web search (DuckDuckGo), log grep β€” with project-directory isolation
  • ChromaDB Memory β€” Long-context compression via vector store; recalls relevant past context across sessions
  • Full-Stack Web UI β€” React + TypeScript + Xterm.js frontend with FastAPI WebSocket backend
  • CLI Interface β€” python main.py -t "your task" for terminal-based usage
  • Cost-Effective Mode β€” Use high-tier models for coding, low-tier for review/routing

Architecture

text 
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚                        FastAPI Server                           β”‚
β”‚  REST: /api/files, /api/models    WebSocket: /ws (streaming)   β”‚
β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€
β”‚                 AutoGen GroupChat                      β”‚ Memory β”‚
β”‚  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”           β”‚ Chrome β”‚
β”‚  β”‚  Admin   β”‚  β”‚  Architect β”‚  β”‚ Reviewer β”‚           β”‚   DB   β”‚
β”‚  β”‚ executor β”‚  β”‚   coder    β”‚  β”‚  auditor β”‚           β”‚        β”‚
β”‚  β””β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”˜  β””β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”˜  β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜           β”‚        β”‚
β”‚       β”‚              β”‚                                 β”‚        β”‚
β”‚  β”Œβ”€β”€β”€β”€β–Όβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β–Όβ”€β”€β”€β”€β”€β”   β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”   β”‚        β”‚
β”‚  β”‚   LocalSafeWorkspace    β”‚   β”‚    Toolchain      β”‚   β”‚        β”‚
β”‚  β”‚  β€’ danger regex guard   β”‚   β”‚  β€’ read/write     β”‚   β”‚        β”‚
β”‚  β”‚  β€’ 30s timeout          β”‚   β”‚  β€’ web search     β”‚   β”‚        β”‚
β”‚  β”‚  β€’ coding/ sandbox      β”‚   β”‚  β€’ grep logs      β”‚   β”‚

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.
0
πŸ™ Data Source: GitHub β†—
πŸ”„ Updated daily

Source summary: Based on GitHub metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
gh-model--ei-ayw--autogen-multi-agent-chat
slug
ei-ayw--autogen-multi-agent-chat
source
github
author
Ei Ayw
license
MIT
tags
ai-agents, anthropic, autogen, claude, code-generation, group-chat, llm, multi-agent, python

βš™οΈ Technical Specs

pipeline tag
text-generation

πŸ“Š Engagement & Metrics

downloads
0
stars
0
forks
0

Data indexed from public sources. Updated daily.