AI Chatbot Stack
AI / MLLLM-powered chatbot with RAG vector retrieval, streaming, and provider failover
9 nodes8 connections
Use Case
AI assistants, RAG chatbots, conversational interfaces
Stack Breakdown
ReactWebSocketFastAPIPineconeOpenAIAnthropic
Architecture Layers
1Frontend
2Real-time Gateway
3AI Orchestration
4Vector DB (RAG)
5LLM Providers
6Persistence
Components by Category
frontend
React
backend
WebSocket GatewayFastAPI
database
PineconeRedisPostgreSQL
external
OpenAIAnthropicSentry
Why This Topology Works
WebSocket gateway provides streaming responses. FastAPI orchestrates RAG retrieval from Pinecone before calling LLM providers. Fallback chain (OpenAI → Anthropic) ensures availability.
Scaling Notes
FastAPI workers scale per-request. Pinecone handles vector similarity search at scale. Token budget controls cost per conversation.
Observability
Token usage tracked per conversation. Latency percentiles on LLM calls. Sentry captures embedding and generation failures.