VentureScope Backend

FastAPI backend for the AI-powered career guidance platform.

Stack

Layer	Technology
Framework	FastAPI 0.115 + Uvicorn (ASGI)
Database	PostgreSQL 16 on Supabase (asyncpg + SQLAlchemy 2 async)
Migrations	Alembic (28 migrations)
Background tasks	Celery 5 + Redis
Auth	JWT (HS256) + OAuth (Google, GitHub) + TOTP MFA + Email OTP
Embeddings	HuggingFace `sentence-transformers/all-MiniLM-L6-v2` (384-dim, pgvector)
File storage	Supabase Storage (S3-compatible, CV/resume files)
Model storage	DigitalOcean Spaces (ML model staging/production)
Error tracking	Sentry (`sentry-sdk[fastapi]`)
Metrics	Prometheus (`prometheus-fastapi-instrumentator`) at `/metrics`

AI-powered career guidance platform built with FastAPI. Helps students and professionals with career discovery, resume generation, learning roadmaps, job matching, and a personalized AI chat assistant.

Tech Stack

Layer	Technology
Web Framework	FastAPI 0.115 (Python 3.12)
Database	PostgreSQL 16 + pgvector
ORM	SQLAlchemy 2.x (async)
Migrations	Alembic
Task Queue	Celery 5.x
Cache / OTP Store	Upstash Redis (HTTP)
Celery Broker	Upstash Redis (rediss://)
AI / LLM	OpenAI (gpt-4o-mini), LangChain, LangGraph
Embeddings	HuggingFace `all-MiniLM-L6-v2` (384 dims)
File Storage	Supabase Storage (S3-compatible)
Email	Mailgun
Auth	JWT + bcrypt + TOTP MFA
OAuth	Google + GitHub
Deployment	Azure Container Apps via GitHub Actions

1. Install dependencies

python -m venv .venv
source .venv/bin/activate       # Windows: .venv\Scripts\activate
---

## Features

- **Auth** — Register, login, email OTP verification, password reset, Google/GitHub OAuth, TOTP MFA, re-authentication, JWT revocation
- **User Profile** — Profile management, skills, work experience, CV upload (S3), profile picture, GitHub sync
- **AI Chat** — WebSocket streaming RAG chatbot powered by LangGraph ReAct agent + web search
- **Transcripts** — Academic transcript upload with version history, GPA validation, AI profile summary
- **Learning Roadmaps** — AI-generated week-by-week roadmaps with real resource URLs, step progress tracking, completion percentage
- **Resume Generation** — AI-generated resumes from user knowledge base (transcript, CV, GitHub, profile)
- **Jobs** — Trending careers, in-demand skills, job market stats
- **Notifications** — In-app notification system
- **Admin** — User management (list, update, soft/hard delete, reactivate)
- **Background Tasks** — Async embedding generation via Celery workers

---

## Project Structure

Backend/ ├── app/ │ ├── api/ # Route handlers (14 modules) │ ├── core/ # Config, database, security │ ├── models/ # SQLAlchemy ORM models (13 models) │ ├── repositories/ # Data access layer │ ├── schemas/ # Pydantic request/response models │ ├── services/ # Business logic │ ├── tasks/ # Celery background tasks │ ├── templates/email/ # Email templates │ └── main.py ├── alembic/ # Database migrations ├── tests/ # Unit, integration, e2e tests ├── scripts/ # Dev/ops scripts ├── Dockerfile # API image ├── Dockerfile.worker # Celery worker image ├── docker-compose.yml # Local dev stack ├── docker-compose.prod.yml └── requirements.txt


---

## API Endpoints

| Prefix | Description |
|---|---|
| `POST /api/auth/register` | Register with email/password |
| `POST /api/auth/login` | Login, returns JWT |
| `POST /api/auth/verify-email` | Verify OTP |
| `POST /api/auth/forgot-password` | Request password reset |
| `POST /api/auth/reset-password` | Reset password with OTP |
| `POST /api/auth/logout` | Revoke JWT |
| `GET  /api/auth/oauth/google/login` | Google OAuth URL |
| `GET  /api/auth/oauth/github/login` | GitHub OAuth URL |
| `POST /api/auth/mfa/enroll` | Start TOTP enrollment |
| `POST /api/auth/mfa/verify` | Verify TOTP code |
| `GET  /api/users/me` | Get own profile |
| `PATCH /api/users/me` | Update profile |
| `POST /api/users/me/cv` | Upload CV |
| `GET  /api/users/me/github/sync` | Sync GitHub profile |
| `POST /api/users/me/experiences` | Add work experience |
| `GET  /api/transcripts/` | List transcript versions |
| `POST /api/transcripts/` | Upload transcript |
| `GET  /api/chat/sessions` | List chat sessions |
| `WS   /api/chat/ws/{session_id}` | Streaming chat WebSocket |
| `POST /api/roadmaps/generate` | Generate learning roadmap |
| `GET  /api/roadmaps/` | List roadmaps with progress % |
| `PATCH /api/roadmaps/steps/{id}/progress` | Update step progress |
| `POST /api/resume/generate` | Generate AI resume |
| `GET  /api/jobs/trending` | Trending careers |
| `GET  /api/jobs/in-demand-skills` | In-demand skills |
| `GET  /api/notifications/` | List notifications |
| `GET  /api/health` | Health check |

Full interactive docs at `http://localhost:8000/docs` (Swagger UI).

---

## Local Development

### Prerequisites

- Python 3.12
- PostgreSQL 16 with pgvector extension
- Redis (local, for Celery worker)

### 1. Clone and install

```bash
git clone https://github.com/VentureScope/Backend.git
cd Backend
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

2. Configure environment

cp .env.example .env
# Fill in at minimum: DATABASE_URL, SECRET_KEY
# Generate SECRET_KEY: python -c "import secrets; print(secrets.token_hex(32))"

See Environment Variables Reference for all options.

3. Run migrations

The app connects to Supabase directly — no local Postgres needed for the default setup.

Edit .env and fill in all required values (see Environment Variables section below)


### 3. Run database migrations(local)

```bash
alembic upgrade head

4. Start the API

alembic upgrade head

4. Start the API

uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload

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

Optional: Docker Compose (local Postgres + Redis)

# API + local Postgres + Redis (DATABASE_URL is overridden to local postgres in compose)
docker compose up -d

# Also start Celery worker
docker compose --profile worker up -d

# Also start Prometheus
docker compose --profile monitoring up -d

Services:

Service	URL
API	http://localhost:8000
Postgres	localhost:5432
Redis	localhost:6379
Prometheus	http://localhost:9090

Note: docker-compose.yml overrides DATABASE_URL to point at the local Postgres container. To use Supabase, run uvicorn directly (step 4).

API overview

Auth (`/api/auth/*`)

Method	Path	Description
`POST`	`/api/auth/register`	Register with email + password
`POST`	`/api/auth/login`	Login → JWT
`POST`	`/api/auth/logout`	Invalidate token
`POST`	`/api/auth/refresh`	Refresh access token
`GET`	`/api/auth/oauth/google`	Google OAuth flow
`GET`	`/api/auth/oauth/github`	GitHub OAuth flow
`POST`	`/api/auth/mfa/enable`	Enable TOTP MFA
`POST`	`/api/auth/mfa/verify`	Verify TOTP code

Users (`/api/users/*`)

Method	Path	Description
`GET`	`/api/users/me`	Current user profile
`PATCH`	`/api/users/me`	Update profile
`POST`	`/api/users/me/cv`	Upload CV/resume

Jobs, Chat, Roadmap (`/api/*`)

Method	Path	Description
`GET`	`/api/jobs`	Search job listings
`POST`	`/api/chat`	AI career chat
`GET`	`/api/roadmap`	Learning roadmap

Super-admin dashboard (`/api/admin/*`)

All routes require is_admin=True in the JWT unless noted.

ML pipeline

Method	Path	Description
`GET`	`/api/admin/ml/runs`	List training runs (Supabase), filterable by `status`/`model_type`
`GET`	`/api/admin/ml/runs/{run_id}`	Single training run with full metrics
`POST`	`/api/admin/ml/deploy/{run_id}`	Deploy model: copies `models/staging/` → `models/production/` in DO Spaces, updates status
`POST`	`/api/admin/ml/trigger`	Trigger `monthly_training_pipeline` DAG via Airflow

Taxonomy

Method	Path	Description
`GET`	`/api/admin/taxonomy/unmatched`	List low-confidence job titles pending review
`PATCH`	`/api/admin/taxonomy/unmatched/{id}`	Accept (→ writes to `taxonomy_roles` DB) or decline
`GET`	`/api/admin/taxonomy/roles`	List accepted canonical roles

System health

Method	Path	Description
`GET`	`/api/admin/system/pipeline-status`	Last run state for both DAGs (Airflow proxy)
`GET`	`/api/admin/system/pipeline-runs`	ETL run history + task durations (Recharts data)
`GET`	`/api/admin/system/storage`	DO Spaces model file listing + total size

Sentry

Method	Path	Auth	Description
`GET`	`/api/admin/sentry/summary`	`is_admin` + 5-min cache	Error counts, trend, top issues, p95, Apdex
`POST`	`/api/admin/sentry-webhook`	HMAC-SHA256 only	Receives Sentry alert webhooks

Notifications feed

Method	Path	Description
`POST`	`/api/admin/notifications`	Receive HMAC-signed pipeline webhook from CareerCompass
`GET`	`/api/admin/notifications-feed`	List stored notifications (pipeline + Sentry), paginated
`PATCH`	`/api/admin/notifications-feed/{id}/read`	Mark one notification as read
`PATCH`	`/api/admin/notifications-feed/mark-all-read`	Bulk mark read

Users

Method	Path	Description
`GET`	`/api/admin/users`	List all users (paginated)
`GET/PATCH/DELETE`	`/api/admin/users/{id}`	Get / update / deactivate user
`POST`	`/api/admin/users/{id}/reactivate`	Reactivate deactivated user

Project structure

app/
├── api/
│   ├── deps.py                  # JWT auth dependencies
│   ├── auth.py, mfa.py          # Auth routes
│   ├── users.py, admin.py       # User management
│   ├── admin_ml.py              # ML pipeline admin + notifications feed
│   ├── admin_taxonomy.py        # Taxonomy review admin
│   ├── admin_system.py          # System health / Airflow proxy
│   ├── admin_sentry.py          # Sentry proxy + webhook receiver
│   ├── chat.py, jobs.py         # Core product routes
│   └── health.py
├── core/
│   ├── config.py                # Pydantic Settings (validates secrets at startup)
│   ├── database.py              # SQLAlchemy async engine + session
│   ├── security.py              # JWT helpers
│   └── rate_limit.py            # In-process fixed-window rate limiter
├── models/                      # SQLAlchemy ORM models (17 files)
├── repositories/                # Data access layer
├── schemas/                     # Pydantic request/response models
├── services/
│   ├── airflow_service.py       # Airflow REST API client (async, parallel calls)
│   ├── sentry_service.py        # Sentry API client (async, 5-min TTL cache, parallel calls)
│   ├── supabase_service.py      # asyncpg pool for Supabase admin queries + writes
│   ├── spaces_service.py        # Shared DO Spaces boto3 client factory
│   ├── auth_service.py, user_service.py, ...
│   └── email_service.py, embedding_service.py, ...
└── main.py                      # App factory, lifespan, router mounts
alembic/versions/                # 28 migration files

Database migrations

# Apply all pending migrations
alembic upgrade head

# Create a new migration
alembic revision --autogenerate -m "describe change"

# Check current state
alembic current

# Roll back one step
alembic downgrade -1
API: http://localhost:8000  
Docs: http://localhost:8000/docs

### 5. Start the Celery worker (local)

Upstash Redis wire-protocol is blocked by WSL2 networking. Use your local Redis for development:

```bash
CELERY_BROKER_URL=redis://localhost:6379 \
CELERY_RESULT_BACKEND=redis://localhost:6379 \
celery -A app.celery_config.celery_app worker --loglevel=info

In production (Azure) the worker uses the Upstash rediss:// URL from .env automatically.

Environment Variables

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

Variable	Description
`DATABASE_URL`	PostgreSQL async URL (`postgresql+asyncpg://...`)
`SECRET_KEY`	JWT signing key — generate with `openssl rand -hex 32`
`UPSTASH_REDIS_URL`	Upstash REST URL (`https://...upstash.io`)
`UPSTASH_REDIS_TOKEN`	Upstash REST token
`CELERY_BROKER_URL`	Upstash wire-protocol URL (`rediss://...`)
`CELERY_RESULT_BACKEND`	Same as `CELERY_BROKER_URL`
`EMBEDDING_PROVIDER`	`hf` for HuggingFace or `hosted` for OpenAI-compatible
`HF_TOKEN`	HuggingFace API token (if `EMBEDDING_PROVIDER=hf`)
`EMBEDDING_MODEL_NAME`	e.g. `sentence-transformers/all-MiniLM-L6-v2`
`EMBEDDING_DIMENSIONS`	Must match the model output (e.g. `384`)
`END_POINT`	LLM API base URL
`HOSTED_LLM_TOKEN`	LLM API token
`CHAT_MODEL_NAME`	LLM model name e.g. `gpt-4o-mini`
`AWS_ACCESS_KEY_ID`	Supabase Storage access key
`AWS_SECRET_ACCESS_KEY`	Supabase Storage secret
`S3_BUCKET_NAME`	Storage bucket name
`S3_ENDPOINT_URL`	Supabase Storage endpoint
`MAILGUN_API_KEY`	Mailgun API key
`MAILGUN_DOMAIN`	Mailgun sending domain
`GOOGLE_CLIENT_ID`	Google OAuth client ID
`GOOGLE_CLIENT_SECRET`	Google OAuth client secret
`GITHUB_CLIENT_ID`	GitHub OAuth client ID
`GITHUB_CLIENT_SECRET`	GitHub OAuth client secret
`SERPER_API_KEY`	Serper API key for web search

Background Tasks

Two Celery tasks run in the background:

Task	Triggered by	What it does
`generate_user_profile_embedding`	Register, profile update, CV upload, skills update	Builds user document text → generates vector embedding → stores in `users.embedding`
`generate_knowledge_embedding`	Transcript upload, CV upload, GitHub sync	Embeds individual knowledge chunks → stores in `user_knowledge.embedding`
`batch_generate_knowledge_embeddings`	Transcript re-upload	Re-embeds all knowledge chunks for a source type

These embeddings power semantic job matching and the RAG chatbot retrieval.

Database Models

Model	Table	Purpose
`User`	`users`	Core user identity, skills, embedding
`OAuthAccount`	`oauth_accounts`	Google/GitHub OAuth connections
`TokenBlocklist`	`token_blocklist`	JWT revocation store
`AcademicTranscript`	`academic_transcripts`	E-student transcript versions
`TranscriptConfig`	`transcript_configs`	User GPA scale config
`UserKnowledge`	`user_knowledge`	Vector-searchable RAG knowledge chunks
`Experience`	`experiences`	Work experience entries
`GitHubSyncSnapshot`	`github_sync_snapshots`	Cached GitHub profile data
`Job`	`jobs`	Job listings with embeddings
`LearningRoadmap`	`learning_roadmaps`	AI-generated learning plans
`LearningRoadmapStep`	`learning_roadmap_steps`	Weekly steps
`LearningRoadmapStepResource`	`learning_roadmap_step_resources`	Resources per step
`LearningRoadmapProgress`	`learning_roadmap_progress`	User progress per step
`Resume`	`resumes`	AI-generated resume data
`ChatSession`	`chat_sessions`	Conversation threads
`ChatMessage`	`chat_messages`	Individual messages
`Notification`	`notifications`	In-app notifications

Authentication & Security

JWT — HS256 signed tokens with jti UUID for per-token revocation via token_blocklist
AAL2 — Sensitive routes (password change, account deletion, MFA management) require re-authentication or TOTP verification
OTP — 6-digit codes stored in Upstash Redis with TTL, rate-limited (60s cooldown, max 3/hour)
OAuth CSRF — State parameter signed with HMAC-SHA256 + timestamp expiry
Timing attacks — Constant-time comparison on passwords and OTP codes throughout
bcrypt — Password hashing via passlib

Deployment

Deploys automatically to Azure Container Apps on every push to master-v2 via GitHub Actions.

What the pipeline does

Builds and pushes the API image (Dockerfile) to GitHub Container Registry
Builds and pushes the Worker image (Dockerfile.worker) to GitHub Container Registry
Updates the venturescope Container App with the new API image
Updates the backgroundworker Container App with the new worker image

Required GitHub Secrets

Secret	Value
`AZURE_CREDENTIALS`	Azure service principal JSON
`AZURE_RG`	Azure resource group name

Update environment variables on Azure

# API container
az containerapp update \
  --name venturescope \
  --resource-group <AZURE_RG> \
  --set-env-vars KEY="value" KEY2="value2"

# Worker container
az containerapp update \
  --name backgroundworker \
  --resource-group <AZURE_RG> \
  --set-env-vars KEY="value" KEY2="value2"

Testing

# All tests
./run_tests.sh

# With coverage
./run_tests.sh coverage

# In Docker
./run_tests.sh docker

# Directly
pytest tests/ -v

Environment Variables Reference

Required to start

Variable	Description
`DATABASE_URL`	PostgreSQL async URL (`postgresql+asyncpg://...`)
`SECRET_KEY`	JWT signing key — generate: `python -c "import secrets; print(secrets.token_hex(32))"`

The app refuses to start in production (ENVIRONMENT=production) if either of these is still set to their placeholder defaults.

Application

Variable	Default	Description
`ENVIRONMENT`	`development`	`development` / `staging` / `production`
`DEBUG`	`false`	Enable debug mode
`ALGORITHM`	`HS256`	JWT algorithm
`ACCESS_TOKEN_EXPIRE_MINUTES`	`1440`	24 hours

OAuth (optional)

Variable	Description
`GOOGLE_CLIENT_ID` / `GOOGLE_CLIENT_SECRET`	Google OAuth app credentials
`GITHUB_CLIENT_ID` / `GITHUB_CLIENT_SECRET`	GitHub OAuth app credentials
`OAUTH_STATE_SECRET`	CSRF protection secret (different from `SECRET_KEY`)

Embeddings / LLM

Variable	Default	Description
`EMBEDDING_PROVIDER`	`hf`	`hf` (HuggingFace local) or `hosted` (OpenAI-compatible)
`EMBEDDING_MODEL_NAME`	`sentence-transformers/all-MiniLM-L6-v2`	Model name
`EMBEDDING_DIMENSIONS`	`384`	Must match pgvector column dimension
`HF_TOKEN`		HuggingFace token (for `hf` provider)
`END_POINT` / `HOSTED_LLM_TOKEN`		Hosted LLM endpoint + token (for `hosted` provider)

Storage (Supabase S3)

Variable	Description
`AWS_ACCESS_KEY_ID` / `AWS_SECRET_ACCESS_KEY`	Supabase Storage S3 credentials
`S3_BUCKET_NAME`	Resume bucket name
`S3_ENDPOINT_URL`	Supabase Storage endpoint

Redis / Celery

Variable	Description
`REDIS_URL`	Redis connection URL (supports `rediss://` TLS)
`CELERY_BROKER_URL` / `CELERY_RESULT_BACKEND`	Usually same as `REDIS_URL`

Email / OTP

Variable	Description
`MAILGUN_API_KEY` / `MAILGUN_DOMAIN`	Mailgun credentials
`MAILGUN_FROM_EMAIL`	Sender address
`OTP_EXPIRE_MINUTES`	OTP validity window (default 10)

Super-admin dashboard

Variable	Description
`SUPABASE_URL`	Plain psycopg2 URL for Supabase (admin read/write queries)
`AIRFLOW_API_URL`	Airflow REST API base URL (`http://...:8080/api/v1`)
`AIRFLOW_SERVICE_ACCOUNT_USER` / `AIRFLOW_SERVICE_ACCOUNT_PASSWORD`	Airflow `backend-svc` account
`SENTRY_DSN`	Sentry ingest URL
`SENTRY_AUTH_TOKEN`	Internal integration token (`project:read` + `org:read`)
`SENTRY_ORG_SLUG` / `SENTRY_PROJECT_SLUG`	Sentry org/project identifiers
`SENTRY_WEBHOOK_SECRET`	HMAC secret for verifying inbound Sentry webhooks
`PIPELINE_WEBHOOK_SECRET`	HMAC secret shared with CareerCompass `notify_admin` task
`DO_SPACES_KEY` / `DO_SPACES_SECRET`	DO Spaces credentials for model deploy
`DO_SPACES_BUCKET` / `DO_SPACES_ENDPOINT` / `DO_SPACES_REGION`	DO Spaces config

Implementation status

Phase	Description	Status
Scaffold	FastAPI app, config, CORS, folder structure	✅ Done
Auth	JWT, register/login, token blocklist	✅ Done
OAuth	Google + GitHub OAuth 2.0	✅ Done
MFA	TOTP + Email OTP	✅ Done
Users	Profile update, CV upload, GitHub sync	✅ Done
Alembic	28 versioned migrations	✅ Done
Jobs	Job listings, search, pgvector similarity	✅ Done
Chat	LangGraph AI career chat	✅ Done
Roadmap	Learning roadmap generation	✅ Done
Admin users	User management endpoints	✅ Done
Phase 2	Super-admin dashboard (ML, taxonomy, system, Sentry, notifications)	✅ Done
Phase 4	Prometheus instrumentation + `/metrics` endpoint	✅ Done
pytest tests/ -v

Unit tests only

pytest tests/unit/ -v

Integration tests only

pytest tests/integration/ -v

With coverage report

pytest tests/ --cov=app --cov-report=html


Test structure:

tests/ ├── conftest.py # Fixtures: engine, db session, client, users ├── unit/ # Service and repository unit tests (9 modules) ├── integration/ # API endpoint + migration tests (6 modules) └── e2e/ # Full user journey tests (1 module)


---

## Architecture

HTTP Request → FastAPI Router → get_current_user (JWT → blocklist → user fetch) → [require_aal2 if sensitive] → Route Handler → Service Layer (business logic) → Repository Layer (SQLAlchemy async) → PostgreSQL → Celery task dispatched (embeddings) → Pydantic response serialization


WebSocket Chat flow:

WS Connect (?token=JWT) → Auth check → Receive message → Embed query → vector search UserKnowledge → Load message history → LangGraph ReAct agent (may call web search tool) → Stream tokens → WS send_json → Save assistant message → Create notification

Name		Name	Last commit message	Last commit date
Latest commit History 141 Commits
.github/workflows		.github/workflows
alembic		alembic
app		app
docs		docs
scripts		scripts
tests		tests
.env.example		.env.example
.gitattributes		.gitattributes
.gitignore		.gitignore
Dockerfile		Dockerfile
Dockerfile.test		Dockerfile.test
Dockerfile.worker		Dockerfile.worker
README.md		README.md
alembic.ini		alembic.ini
docker-compose.prod.yml		docker-compose.prod.yml
docker-compose.yml		docker-compose.yml
env.example		env.example
export_openapi.py		export_openapi.py
prometheus.yml		prometheus.yml
pytest.ini		pytest.ini
requirements.txt		requirements.txt
run_tests.sh		run_tests.sh
test_gh.py		test_gh.py

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VentureScope Backend

Stack

Tech Stack

1. Install dependencies

2. Configure environment

3. Run migrations

Edit .env and fill in all required values (see Environment Variables section below)

4. Start the API

4. Start the API

Optional: Docker Compose (local Postgres + Redis)

API overview

Auth (/api/auth/*)

Users (/api/users/*)

Jobs, Chat, Roadmap (/api/*)

Super-admin dashboard (/api/admin/*)

ML pipeline

Taxonomy

System health

Sentry

Notifications feed

Users

Project structure

Database migrations

Environment Variables

Background Tasks

Database Models

Authentication & Security

Deployment

What the pipeline does

Required GitHub Secrets

Update environment variables on Azure

Testing

Environment Variables Reference

Required to start

Application

OAuth (optional)

Embeddings / LLM

Storage (Supabase S3)

Redis / Celery

Email / OTP

Super-admin dashboard

Implementation status

Unit tests only

Integration tests only

With coverage report

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Languages

Auth (`/api/auth/*`)

Users (`/api/users/*`)

Jobs, Chat, Roadmap (`/api/*`)

Super-admin dashboard (`/api/admin/*`)

Packages