AI-powered analytics SDK for backend applications with automatic LLM tracking
Project description
Scope Analytics - Backend SDK
AI-powered analytics for backend applications with zero-code LLM conversation tracking.
Features
- Automatic LLM Tracking: Captures OpenAI, Anthropic, and Gemini calls automatically
- Session Correlation: Links backend events to frontend user sessions via
X-Scope-Session-IDheader - Conversation Intelligence: Classifies LLM calls as user-facing vs background jobs
- Zero Code Changes: Drop-in integration with automatic monkey-patching
- Async & Non-Blocking: Events shipped in background without affecting performance
Installation
pip install scope-analytics
Quick Start
Choose your installation method:
Option A: No-Code Installation (Recommended)
Zero code changes required - just change how you run your app.
Step 1: Set your API key
export SCOPE_API_KEY="sk_live_..."
Step 2: Run with scope-run
# Instead of: python app.py
# Run: scope-run python app.py
# Instead of: uvicorn main:app --reload
# Run: scope-run uvicorn main:app --reload
# Instead of: gunicorn app:app -w 4
# Run: scope-run gunicorn app:app -w 4
# Instead of: flask run --port 5000
# Run: scope-run flask run --port 5000
That's it! Your LLM calls are now automatically tracked AND correlated with frontend sessions (for FastAPI, Flask, Django).
Option B: Code-Based Installation
Add 2 lines to your app for more control.
from scope_analytics import ScopeAnalytics
scope = ScopeAnalytics(api_key="sk_live_...")
For session correlation with frontend, add middleware:
FastAPI:
from fastapi import FastAPI
from scope_analytics import ScopeAnalytics, ScopeSessionMiddleware
app = FastAPI()
app.add_middleware(ScopeSessionMiddleware)
scope = ScopeAnalytics(api_key="sk_live_...")
Flask:
from flask import Flask
from scope_analytics import ScopeAnalytics, init_flask_session_tracking
app = Flask(__name__)
init_flask_session_tracking(app)
scope = ScopeAnalytics(api_key="sk_live_...")
Django:
# settings.py
MIDDLEWARE = [
'scope_analytics.middleware.DjangoScopeMiddleware',
# ... other middleware
]
Installation Comparison
| Feature | No-Code (scope-run) |
Code-Based |
|---|---|---|
| Code changes required | None | 2 lines minimum |
| LLM tracking | ✅ Automatic | ✅ Automatic |
| Session correlation | ✅ Automatic (FastAPI/Flask/Django) | Manual middleware |
| Custom configuration | Via env vars | Full Python API |
| Best for | Quick start, CI/CD, ops teams | Developers wanting control |
CLI Usage
# Show version
scope-run --version
# Show help
scope-run --help
# Run with debug logging
scope-run --debug python app.py
# Dry run (show what would be executed)
scope-run --dry-run uvicorn main:app
Environment Variables
| Variable | Required | Description |
|---|---|---|
SCOPE_API_KEY |
Yes | Your Scope Analytics API key |
SCOPE_ENDPOINT |
No | Custom API endpoint |
SCOPE_DEBUG |
No | Set to 'true' for debug logging |
SCOPE_ENVIRONMENT |
No | Environment name (default: production) |
Configuration (Code-Based)
scope = ScopeAnalytics(
api_key="sk_live_...", # Required: Your secret API key
endpoint="https://api.scopeai.dev", # Optional: API endpoint
auto_patch=True, # Optional: Auto-patch LLM libraries (default: True)
batch_size=10, # Optional: Events per batch (default: 10)
batch_timeout_seconds=5, # Optional: Max wait time (default: 5)
debug=False, # Optional: Enable debug logging
environment="production", # Optional: Environment name
)
Framework Support Matrix
| Framework | Auto-Injection | Session Correlation | How |
|---|---|---|---|
| FastAPI | ✅ Automatic | ✅ Full | Patches FastAPI.__init__ |
| Starlette | ✅ Automatic | ✅ Full | Patches Starlette.__init__ |
| Flask | ✅ Automatic | ✅ Full | Patches Flask.__init__ |
| Django | ✅ Automatic | ✅ Full | Modifies settings.MIDDLEWARE |
| Other ASGI | ⚠️ Manual | ✅ With 1 line | Add ScopeSessionMiddleware |
| Other WSGI | ⚠️ Manual | ✅ With 1 line | Call ScopeContext.set_session_id() |
| No framework | ⚠️ Manual | ✅ With 1 line | Call ScopeContext.set_session_id() |
Manual Session Correlation (For Other Frameworks)
# Option A: ASGI middleware (for ASGI frameworks)
from scope_analytics import ScopeSessionMiddleware
app = ScopeSessionMiddleware(app)
# Option B: Manual context (for any framework)
from scope_analytics import ScopeContext
def my_request_handler(request):
# Extract session from header and set context
ScopeContext.set_session_id(request.headers.get('X-Scope-Session-ID'))
# Your code - LLM calls will now have session_id attached
response = openai.chat.completions.create(...)
Key Point: Even without middleware, LLM tracking STILL WORKS. The middleware is only needed for correlating backend events with frontend sessions via X-Scope-Session-ID.
Frontend SDK
Add the frontend SDK to link user interactions with backend LLM calls:
<script src="https://cdn.scopeai.dev/v1/sdk.js"
data-api-key="pk_live_your_public_key"></script>
The frontend SDK automatically:
- Tracks clicks, page views, form submissions
- Generates session IDs (stored in localStorage)
- Sends
X-Scope-Session-IDheader with API requests
Comparison with Industry Tools
| Feature | Scope (scope-run) |
DataDog (ddtrace-run) |
New Relic |
|---|---|---|---|
| No code changes | ✅ | ✅ | ✅ |
| Env var config | ✅ SCOPE_API_KEY |
✅ DD_API_KEY |
✅ NEW_RELIC_LICENSE_KEY |
| Works with uvicorn | ✅ | ✅ | ✅ |
| Works with gunicorn | ✅ | ✅ | ✅ |
| LLM call capture | ✅ | ❌ | ❌ |
| Session correlation | ✅ | ❌ | ❌ |
| Debug mode | ✅ --debug |
✅ --info |
✅ |
Full Documentation
See SDK Installation Guide for complete documentation including:
- Detailed configuration options
- Troubleshooting guide
- Complete example applications
- Verification steps
License
MIT
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