Synapse — AI Knowledge Base

A full-stack RAG platform that lets you chat with your documents, search the web, and collaborate on shared knowledge bases — all through a sleek glassmorphism UI.

Features · Quick Start · Architecture · RBAC · API Reference · Configuration

Overview

Synapse is a self-correcting RAG (Retrieval-Augmented Generation) system that transforms your documents into a searchable intelligence layer. It combines hybrid FAISS + BM25 retrieval, an Advanced RAG brain with query optimization, live web search, async document indexing via Celery, and a full role-based access control system for team collaboration — all streaming in real time through a polished glassmorphism interface.

┌──────────────────────────────────────────────────────────────┐
│                    Synapse — at a glance                      │
│                                                              │
│  Upload docs (PDF / DOCX / TXT / MD / XLSX)                  │
│    → Async-indexed via Celery + Redis (or BackgroundTasks)   │
│  Simple RAG       → FAISS + BM25 hybrid search               │
│  Advanced RAG     → Query optimization + precision pull       │
│  Web Search       → Serper (Google) + DuckDuckGo fallback    │
│  Summarizer       → Chunked AI summarization                 │
│  RBAC             → Owner / Editor / Viewer per KB + Admin   │
└──────────────────────────────────────────────────────────────┘

Features

Chat & RAG

Knowledge Base Chat — Ask questions across one or more knowledge bases using hybrid retrieval
Advanced RAG — Multi-step pipeline: query optimization → precision FAISS retrieval → reranking
Web Search — Live Serper (Google) / DuckDuckGo search woven into answers
Streaming Responses — Real-time NDJSON token-by-token output
RAG Pipeline Visualizer — Live numbered step-by-step progress card during retrieval
Citation Chips — Source pills with document name + color-coded relevance score
- 🟢 ≥ 85 % · 🟡 70–84 % · 🔴 < 70 %
Skeleton Loaders — Shimmer placeholders while the model is retrieving
Session Memory — Persistent conversation history across browser sessions

Knowledge Management

Multiple Knowledge Bases — Create, switch, and query multiple KBs at once
Async Document Indexing — Celery workers process uploads in the background with automatic retry; falls back to FastAPI BackgroundTasks when Redis is not available
Document Upload — Ingest PDF, DOCX, DOC, TXT, Markdown, XLSX (chunked + embedded in background)
Document Preview — Read source files inline without leaving the chat
Summarizer — Paste text or upload a file to get a summary + key takeaways
FAISS Quantization — Optional 8-bit scalar quantization (4× memory reduction, ~1 % recall loss)

Collaboration & Access Control

Role-Based Access Control (RBAC) — Two-layer permission system
- Global roles: admin / user
- Per-KB roles: owner / editor / viewer
KB Sharing — Owners invite teammates by username with a specific role
Admin Panel — User management, role promotion/demotion, system-wide stats
First-user Admin — The first registered account automatically gets admin role
Permission guards — Every API route enforces the minimum required role

LLM Providers

Provider	Notes
Groq	Default — fast Llama 3.1 inference (free tier available)
OpenAI	GPT-4o Mini and above
Google Gemini	Gemini 2.0 Flash (free tier + 1 M context)
NVIDIA NIM	Meta Llama via NVIDIA cloud API
AWS Bedrock	Claude 3 Haiku and other foundation models
Ollama	Fully local — no API key required

UI / UX

Glassmorphism dark-first design with aurora blue-violet gradient
Light / Dark theme toggle (persisted)
Settings page with tabbed navigation — LLM Providers · Web Search · Account
Collapsible sidebar with session management and Admin nav item (visible to admins only)
Role pills on KB cards; Share modal for member management; role-gated upload/delete controls

Tech Stack

Backend

Layer	Technology
API Framework	FastAPI 0.110+
Server	Uvicorn (async)
Database	SQLite via SQLAlchemy async (PostgreSQL-ready)
Auth	JWT (PyJWT) + bcrypt
Task Queue	Celery 5.3+ with Redis broker
Vector Store	FAISS-CPU (flat + optional SQ8/SQ4 quantization)
Keyword Search	BM25 (rank-bm25)
Embeddings	Sentence Transformers (`all-MiniLM-L6-v2`)
LLM Orchestration	LangChain + LangGraph
Web Search	DuckDuckGo Search / Serper API
File Parsing	pdfplumber, python-docx, pandas
Encryption	AES-256-GCM (API keys at rest)

Frontend

Layer	Technology
Framework	React 18
Build Tool	Vite 5
HTTP Client	Axios
Styling	Pure CSS with design tokens (no CSS framework)

Project Structure

KnowledgeBase/
├── src/                              # FastAPI backend
│   ├── main.py                       # App factory, lifespan, schema migrations
│   ├── api/
│   │   ├── auth.py                   # Register / login / JWT (first-user admin)
│   │   ├── chat.py                   # Streaming chat endpoint (NDJSON)
│   │   ├── knowledge_base.py         # KB CRUD + member management endpoints
│   │   ├── documents.py              # Upload, list, delete, summarize
│   │   └── admin.py                  # Admin-only: users, roles, stats
│   ├── worker/
│   │   ├── celery_app.py             # Celery app factory (reads settings)
│   │   └── tasks/indexing.py         # index_document Celery task (retry logic)
│   ├── application/
│   │   ├── rag_service.py            # SelfCorrectingRAG orchestrator
│   │   └── hybrid_retriever.py       # FAISS + BM25 + RRF fusion
│   ├── core/
│   │   ├── settings.py               # Pydantic settings (reads .env)
│   │   ├── search/                   # Query processor, reranker, web search
│   │   └── services/summarizer.py    # Chunked AI summarizer
│   ├── infrastructure/
│   │   ├── adapters/                 # LLM, FAISS, BM25, DB adapters
│   │   └── database/
│   │       ├── models.py             # ORM: User, KnowledgeBase, Document,
│   │       │                         #      ChatSession, Message, KBMember
│   │       └── repositories.py       # Typed repos incl. KBMemberRepository
│   └── shared/
│       ├── rbac.py                   # ROLE_ORDER, require_admin, require_kb_role
│       ├── encryption.py             # AES-256-GCM for API keys
│       └── security.py              # JWT helpers
│
├── web/                              # React frontend
│   └── src/
│       ├── pages/
│       │   ├── Chat.jsx              # Main chat interface + RAG controls
│       │   ├── KnowledgeBase.jsx     # KB management + Share modal
│       │   ├── Settings.jsx          # Tabbed settings (LLM / Web Search / Account)
│       │   └── AdminPage.jsx         # Admin panel: user table + stats
│       ├── components/
│       │   ├── Sidebar.jsx           # Nav with Admin item for admins
│       │   ├── AuthPage.jsx
│       │   ├── SummarizerPage.jsx
│       │   └── ErrorBoundary.jsx
│       ├── hooks/
│       │   ├── useDocuments.js       # Module-level cache (instant re-nav)
│       │   └── useRAGQuery.js        # Streaming fetch + NDJSON parser
│       └── api/
│           ├── documentApi.js        # KB, document, member API calls
│           └── adminApi.js           # Admin API calls
│
├── data_storage/                     # Auto-created at runtime
│   ├── knowledge_base.db             # SQLite database
│   ├── uploads/                      # Uploaded source files
│   └── indices/                      # FAISS + BM25 index files
│
├── docker-compose.yml                # Redis + backend + Celery worker + frontend
├── Dockerfile.backend
├── requirements.txt
└── .env                              # API keys & config (see setup)

Quick Start

Prerequisites

Python 3.11+
Node.js 18+
At least one LLM API key or Ollama running locally
Redis (optional — only needed for Celery; omit for BackgroundTasks mode)

1 — Clone & install backend

git clone <repo-url>
cd KnowledgeBase

python -m venv .venv

# Windows
.venv\Scripts\activate
# macOS / Linux
source .venv/bin/activate

pip install -r requirements.txt

2 — Configure environment

Copy .env.example to .env and fill in your values:

# ── Security (required) ────────────────────────────────────
JWT_SECRET=your-secure-256-bit-secret-here
ENCRYPTION_KEY=your-64-char-hex-key-here   # python -c "import secrets; print(secrets.token_hex(32))"

# ── LLM Provider (pick at least one) ──────────────────────
GROQ_API_KEY=gsk_...          # https://console.groq.com  (free tier)
OPENAI_API_KEY=sk-...
GEMINI_API_KEY=AIza...        # https://aistudio.google.com  (free tier)

# ── Web Search (optional) ──────────────────────────────────
SERPER_API_KEY=...            # Leave blank → DuckDuckGo fallback

# ── Celery (optional — leave blank for BackgroundTasks) ────
CELERY_BROKER_URL=redis://localhost:6379/0
CELERY_RESULT_BACKEND=redis://localhost:6379/0

# ── CORS ───────────────────────────────────────────────────
CORS_ORIGINS=http://localhost:5173,http://localhost:3000

3 — Start the backend

uvicorn src.main:app --reload --port 8000

Interactive API docs: http://localhost:8000/docs

4 — (Optional) Start Celery worker

Only needed if CELERY_BROKER_URL is set. Without it, document indexing runs as FastAPI BackgroundTasks.

# Requires Redis to be running
celery -A src.worker.celery_app.celery_app worker --loglevel=info --concurrency=2

5 — Start the frontend

cd web
npm install
npm run dev

Open http://localhost:5173

6 — First run

Register — the first account automatically becomes admin
Go to Settings → LLM Providers → enter your API key → Save & Activate
Go to Knowledge Base → create a KB → upload documents
Go to Chat → select your KB → ask questions

Docker Compose

Starts Redis + FastAPI backend + Celery worker + React frontend in one command:

cp .env.example .env   # fill in JWT_SECRET and at least one API key
docker compose up --build

Service	Port	Description
`redis`	6379	Celery broker + result backend
`backend`	8000	FastAPI + Uvicorn
`celery_worker`	—	Async document indexing
`frontend`	3000	React (Vite production build)

Architecture

┌─────────────────────────────────────────────────────────────────┐
│                     React Frontend :5173                         │
│                                                                  │
│  AuthPage → App.jsx → Sidebar + Chat / KB / Settings / Admin    │
│                                                                  │
│  Chat.jsx                                                        │
│  ├─ RAG controls (KB selector, Advanced RAG, Web Search)         │
│  ├─ PipelineProgress (live step visualizer)                      │
│  └─ Citation chips (source + relevance %)                        │
│                                                                  │
│  KnowledgeBase.jsx                                               │
│  ├─ Role pills (owner / editor / viewer)                         │
│  ├─ Share modal → member invite + role management                │
│  └─ Upload / delete gated by role                                │
│                                                                  │
│  AdminPage.jsx                                                   │
│  └─ Stats cards + user table (promote / demote)                  │
└───────────────────────────┬─────────────────────────────────────┘
                            │  REST + NDJSON streaming (Axios + JWT)
┌───────────────────────────▼─────────────────────────────────────┐
│                    FastAPI Backend :8000                          │
│                                                                  │
│  RBAC middleware                                                  │
│  ├─ require_admin()       → global admin guard                   │
│  └─ require_kb_role()     → per-KB role guard (admins bypass)    │
│                                                                  │
│  POST /api/chat  (streaming NDJSON)                              │
│  ├─ JWT auth + KB viewer check                                   │
│  ├─ Resolve LLM adapter (per-user provider + key)                │
│  ├─ Optional: WebSearch → inject results into context            │
│  ├─ SelfCorrectingRAG.answer(query, context)                     │
│  │   ├─ HybridRetriever → FAISS + BM25 + RRF fusion              │
│  │   ├─ LLM.chat(system + context + query)                       │
│  │   └─ confidence_score < threshold → retry                     │
│  └─ Stream: status → content → meta (sources, confidence)        │
│                                                                  │
│  POST /api/kb/{id}/documents  (upload)                           │
│  └─ editor+ check → save file → dispatch to Celery / BG task    │
└──────────────────┬──────────────────────────────────────────────┘
                   │
      ┌────────────┴──────────────────────────────┐
      │                                           │
┌─────▼──────┐  ┌───────────────────────────────────────────────┐
│  SQLite DB │  │            Celery Worker                       │
│  users     │  │  index_document task                           │
│  kb_members│  │  ├─ extract text (PDF/DOCX/TXT/XLSX)           │
│  knowledge │  │  ├─ chunk + embed (SentenceTransformer)        │
│  _bases    │  │  ├─ build FAISS + BM25 index                   │
│  documents │  │  └─ update DB status (indexed / failed)        │
│  sessions  │  │  max_retries=2, retry_delay=30s                │
│  messages  │  └───────────────────────────────────────────────┘
└────────────┘

Role-Based Access Control

Permission Matrix

Action	Viewer	Editor	Owner	Admin
Chat with KB / view documents	✅	✅	✅	✅
Upload / delete documents	❌	✅	✅	✅
Delete KB	❌	❌	✅	✅
Manage members (invite / remove / change role)	❌	❌	✅	✅
View all users	❌	❌	❌	✅
Change global user roles	❌	❌	❌	✅
Access any KB regardless of membership	❌	❌	❌	✅

How it works

Global role (user / admin) is stored on User.role. The first registered user automatically becomes admin.
Per-KB role (viewer / editor / owner) is stored in the KBMember join table. Creating a KB auto-enrolls the creator as owner.
Admin users bypass all per-KB membership checks — they can access everything.
Existing knowledge bases are auto-migrated on startup: every KB gets an owner KBMember record for its creator.

Sharing a Knowledge Base

Open Knowledge Base → select a KB you own
Click the 👥 icon beside the KB name
In the Share modal: type a username, pick a role, click Invite
Members can be re-roled or removed at any time

Async Document Indexing

Documents are indexed asynchronously so uploads return instantly.

With Celery + Redis (recommended for production)

Set CELERY_BROKER_URL and CELERY_RESULT_BACKEND in .env:

CELERY_BROKER_URL=redis://localhost:6379/0
CELERY_RESULT_BACKEND=redis://localhost:6379/0

Start the worker:

celery -A src.worker.celery_app.celery_app worker --loglevel=info --concurrency=2

Features: persistent queue, survives server restarts, automatic retry (up to 2× with 30 s delay), per-task status tracking.

Without Redis (BackgroundTasks fallback)

Leave both CELERY_* vars empty. Indexing runs inside FastAPI's BackgroundTasks — zero extra infrastructure, fine for local development.

FAISS Quantization

Reduce memory footprint of large FAISS indices:

FAISS_QUANTIZE=true
FAISS_QUANTIZE_TYPE=sq8   # sq8 = 8-bit (4× reduction, ~1% recall loss)
                           # sq4 = 4-bit (8× reduction, ~3% recall loss)

Set FAISS_QUANTIZE=false to use raw float32 IndexFlatL2.

Chat Modes

Mode	What happens
No KB selected	General LLM chat (no retrieval)
KB selected	Simple RAG — FAISS + BM25 hybrid search
KB + Advanced RAG	Query optimization → precision retrieval → reranking
+ Web Search	Augments any mode with live search results

NDJSON stream format

Each line from POST /api/chat is a JSON object:

{ "type": "session", "session_id": 42 }
{ "type": "status",  "content": "🔍 Searching knowledge base..." }
{ "type": "content", "delta": "According to " }
{ "type": "meta",    "session_id": 42, "sources": [...] }
{ "type": "error",   "content": "..." }

API Reference

Authentication

Method	Endpoint	Description
`POST`	`/auth/register`	Create account, returns JWT + role
`POST`	`/auth/login`	Login, returns JWT + role
`GET`	`/auth/me`	Current user profile (includes `role`)
`GET/POST`	`/auth/settings`	Read / update user settings

Chat

Method	Endpoint	Description
`POST`	`/api/chat`	Streaming chat (NDJSON)
`GET`	`/api/sessions`	List chat sessions
`POST`	`/api/sessions`	Create session
`DELETE`	`/api/sessions/{id}`	Delete session
`GET`	`/api/models`	List models for active provider

Knowledge Bases & Documents

Method	Endpoint	Min Role	Description
`GET`	`/api/kb`	—	List KBs the caller is a member of
`POST`	`/api/kb`	—	Create KB (caller becomes owner)
`GET`	`/api/kb/{id}`	viewer	Get KB detail
`DELETE`	`/api/kb/{id}`	owner	Delete KB + all documents
`GET`	`/api/kb/{id}/documents`	viewer	List documents
`POST`	`/api/kb/{id}/documents`	editor	Upload file
`DELETE`	`/api/documents/{id}`	editor	Delete document
`GET`	`/api/documents/{id}/file`	viewer	Download source file
`POST`	`/api/summarize`	—	Summarize text
`POST`	`/api/summarize/file`	—	Upload + summarize file

KB Members

Method	Endpoint	Min Role	Description
`GET`	`/api/kb/{id}/members`	viewer	List members + roles
`POST`	`/api/kb/{id}/members`	owner	Invite user by username
`PUT`	`/api/kb/{id}/members/{uid}`	owner	Change member role
`DELETE`	`/api/kb/{id}/members/{uid}`	owner	Remove member

Admin (admin role required)

Method	Endpoint	Description
`GET`	`/api/admin/users`	Paginated user list
`PUT`	`/api/admin/users/{id}/role`	Promote / demote user
`GET`	`/api/admin/stats`	Total users / KBs / documents

System

Method	Endpoint	Description
`GET`	`/health`	Health check
`GET`	`/docs`	Swagger UI

Configuration

Variable	Default	Description
`JWT_SECRET`	dev default	Change in production
`ENCRYPTION_KEY`	—	64-char hex key for API key encryption at rest
`DATABASE_URL`	`sqlite:///data_storage/knowledge_base.db`	SQLite or PostgreSQL URL
`CORS_ORIGINS`	`http://localhost:3000`	Comma-separated allowed origins
`CELERY_BROKER_URL`	`""`	Redis URL — leave empty for BackgroundTasks
`CELERY_RESULT_BACKEND`	`""`	Redis URL for task results
`FAISS_QUANTIZE`	`true`	Enable SQ8 quantization
`FAISS_QUANTIZE_TYPE`	`sq8`	`sq8` or `sq4`
`GROQ_API_KEY`	—	Groq API key
`GROQ_MODEL`	`llama-3.1-8b-instant`	Groq model
`OPENAI_API_KEY`	—	OpenAI API key
`OPENAI_MODEL`	`gpt-4o-mini`	OpenAI model
`GEMINI_API_KEY`	—	Google Gemini key
`GEMINI_MODEL`	`gemini-2.0-flash`	Gemini model
`NVIDIA_API_KEY`	—	NVIDIA NIM key
`AWS_ACCESS_KEY_ID`	—	AWS credentials
`SERPER_API_KEY`	—	Google Search via Serper (optional)
`EMBEDDER_MODEL`	`all-MiniLM-L6-v2`	Sentence Transformer model
`CONFIDENCE_THRESHOLD`	`0.5`	Min RAG score before retry
`OLLAMA_BASE_URL`	`http://localhost:11434`	Ollama server URL
`LOG_LEVEL`	`INFO`	Logging verbosity
`DEBUG`	`false`	FastAPI debug mode

Supported File Types

Format	Parser
`.pdf`	pdfplumber (fallback: PyPDF2)
`.docx` / `.doc`	python-docx
`.xlsx` / `.xls`	pandas + openpyxl
`.txt` / `.md`	Built-in

Files are indexed asynchronously — the upload endpoint returns immediately while chunking, embedding, and FAISS/BM25 indexing happen in the background.

Development

# Backend with hot reload
uvicorn src.main:app --reload --port 8000

# Celery worker (separate terminal, needs Redis)
celery -A src.worker.celery_app.celery_app worker --loglevel=info

# Frontend with HMR
cd web && npm run dev

# Run tests
pytest tests/ -v

# Production frontend build
cd web && npm run build   # outputs to web/dist/

Adding a new LLM provider

Create src/infrastructure/adapters/myprovider_llm_adapter.py implementing LLMPort
Add a branch in src/infrastructure/adapters/llm_provider_factory.py
Add static fallback models in src/api/chat.py
Add the provider tab to web/src/pages/Settings.jsx

Roadmap

License

MIT License — see LICENSE for details.

Built with FastAPI · React · LangChain · FAISS · Sentence Transformers · Celery

Name		Name	Last commit message	Last commit date
Latest commit History 32 Commits
.claude		.claude
.github/workflows		.github/workflows
.kilo		.kilo
graphs		graphs
improvements		improvements
src		src
tests		tests
web		web
.dockerignore		.dockerignore
.env.example		.env.example
.gitignore		.gitignore
.python-version		.python-version
CHANGELOG.md		CHANGELOG.md
Dockerfile.backend		Dockerfile.backend
README.md		README.md
SETUP.md		SETUP.md
architecture.md		architecture.md
architecture_graph.png		architecture_graph.png
clean_hashes.py		clean_hashes.py
data_flow_graph.png		data_flow_graph.png
docker-compose.yml		docker-compose.yml
dummy.txt		dummy.txt
pyproject.toml		pyproject.toml
requirements.txt		requirements.txt
settings.json		settings.json
test_full_system.py		test_full_system.py
test_upload.py		test_upload.py
test_upload_with_token.py		test_upload_with_token.py
uv.lock		uv.lock

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Synapse — AI Knowledge Base

Overview

Features

Chat & RAG

Knowledge Management

Collaboration & Access Control

LLM Providers

UI / UX

Tech Stack

Backend

Frontend

Project Structure

Quick Start

Prerequisites

1 — Clone & install backend

2 — Configure environment

3 — Start the backend

4 — (Optional) Start Celery worker

5 — Start the frontend

6 — First run

Docker Compose

Architecture

Role-Based Access Control

Permission Matrix

How it works

Sharing a Knowledge Base

Async Document Indexing

With Celery + Redis (recommended for production)

Without Redis (BackgroundTasks fallback)

FAISS Quantization

Chat Modes

NDJSON stream format

API Reference

Authentication

Chat

Knowledge Bases & Documents

KB Members

Admin (admin role required)

System

Configuration

Supported File Types

Development

Adding a new LLM provider

Roadmap

License

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