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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-ID header
  • 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-ID header 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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