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DmitryDmitriadi/multi-agent-workflow-platform

Case study: live AI consultant — typed conversation graph, source-grounded knowledge, reviewer-gated utterances, in-process cost guardian.

MIT GitHub ↗
★ 0
stars
100
AI relevance
50
solo dev
0
tool sigs

SUMMARY AI summary by gpt-5-mini

A multi-agent platform for running real-time conversational video avatars that conduct structured sales/pre-sales dialogues (greeting → diagnosis → objection handling → CTA) with sub-second per-turn latency. Intended for teams building live avatar assistants and integrations with real-time CVI APIs. Key features: - Orchestrator that runs a typed stage graph; transitions driven by structured signals (intent classifier, counts, explicit requests), not free-form LLM reasoning. - Specialized agents: knowledge (RAG retrieval + source tags), objection classifier/strategies, analytics, avatar/voice lifecycle, reviewer (policy gate on every outbound utterance), cost guardian (per-session budgets, graceful wrap-up), safety layer. - Per-turn knowledge grounding with source attribution, structured outputs at every agent boundary, OpenAI-compatible endpoint, mock mode for development, multi-language support, and session lifecycle/webhook handling.

DETECTED Detected AI stack

AI-related keywords found in this repo's description, topics, or README summary — grouped by category. Each badge links to the corresponding ranking detail page.

🧠 LLM providers (1)
OpenAI
🧩 AI frameworks (2)
LangChain LangGraph
🤝 Agent frameworks (1)
MCP

GitHub Topics

#agentic-ai #agents #ai-engineering #conversational-ai #langchain #langgraph #llm #mcp #multi-agent #openai

Owner

Account
DmitryDmitriadi
Type
User
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Dates

Created on GitHub 2026-05-16
Last push 2026-05-16
First seen here 2026-05-16
Last fetched 2026-05-16 18:19