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title: Demo Agentic Service Data Eyond
emoji: 🏆
colorFrom: yellow
colorTo: pink
sdk: docker
pinned: false
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
How to run:
`uv run --no-sync uvicorn main:app --host 0.0.0.0 --port 7860`
Agent
Orchestrator : intent recognition, orchestrate, and plannings
Chatbot : have tools (retriever, and search), called by orchestrator
APIs
/api/v1/login -> login by email and password
/api/v1/documents/{user_id} -> list all documents
/api/v1/document/upload -> upload document
/api/v1/document/delete -> delete document
/api/v1/document/process -> extract document and ingest to vector index
/api/v1/chat/stream -> talk with agent chatbot, in streaming response
/api/v1/rooms/{user_id} -> list all room based on user id
/api/v1/room/{room_id} -> get room based on room id
Config
- Agent: system prompt, guardrails
- others config needed
DB
- using postgres as db
- we can use pg vector from this db also
- use redis for caching response, same question will not re-processed for 24 hour
Document
- service to manage document, upload, delete, log to db
Knowledge
- service to process document into vector, until ingestion to pg vector
Middleware
CORS:
- allow all
Rate limiting:
- upload document: 10 document per menit
Logging:
- create clear and strutured logging for better debuging
Models
- Data models
Observability
- Langfuse traceability
RAG
- retriever service to get relevant context from pg vector
storage
- storage functionality to communicate with storage provider
tools
- tools that can be use by agent
Users
- Users management, to get user indentity based on login information.
Utils
- Other functionality |