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"""
CASCADE Proxy - Protocol-level AI observation.
Works with ANY language, ANY framework, ANY client.
Just set environment variables and CASCADE sees everything.
Usage:
# Start the proxy
python -m cascade.proxy
# In another terminal, point your app at it
export OPENAI_BASE_URL=http://localhost:7777/v1
export ANTHROPIC_BASE_URL=http://localhost:7777/anthropic
# Run your app normally - CASCADE observes all calls
python your_agent.py
The proxy forwards requests to the real API and emits receipts for every call.
"""
import asyncio
import hashlib
import json
import os
import time
import uuid
from datetime import datetime, timezone
from typing import Dict, Any, Optional
from pathlib import Path
try:
from aiohttp import web, ClientSession
AIOHTTP_AVAILABLE = True
except ImportError:
AIOHTTP_AVAILABLE = False
# Import CASCADE SDK for emission
from cascade.sdk import CascadeSDK
class CascadeProxy:
"""
HTTP proxy that intercepts LLM API calls and emits CASCADE receipts.
Supported providers:
- OpenAI (and OpenAI-compatible APIs)
- Anthropic
- Cohere
- Mistral
- Any OpenAI-compatible endpoint
"""
# Real API endpoints
ENDPOINTS = {
"openai": "https://api.openai.com",
"anthropic": "https://api.anthropic.com",
"cohere": "https://api.cohere.ai",
"mistral": "https://api.mistral.ai",
}
def __init__(
self,
host: str = "0.0.0.0",
port: int = 7777,
verbose: bool = True,
):
self.host = host
self.port = port
self.verbose = verbose
self.sdk = CascadeSDK()
self.sdk.init(emit_async=True, verbose=verbose)
self.session: Optional[ClientSession] = None
# Stats
self.stats = {
"requests": 0,
"receipts_emitted": 0,
"bytes_proxied": 0,
"start_time": None,
}
async def start(self):
"""Start the proxy server."""
if not AIOHTTP_AVAILABLE:
print("ERROR: aiohttp required for proxy mode")
print("Install with: pip install aiohttp")
return
self.session = ClientSession()
self.stats["start_time"] = time.time()
app = web.Application()
# Route all requests
app.router.add_route("*", "/{path:.*}", self.handle_request)
runner = web.AppRunner(app)
await runner.setup()
site = web.TCPSite(runner, self.host, self.port)
print(f"""
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β CASCADE PROXY - Protocol-Level AI Observation β
β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ£
β Listening: http://{self.host}:{self.port} β
β β
β Set these environment variables in your app: β
β β
β export OPENAI_BASE_URL=http://localhost:{self.port}/v1 β
β export ANTHROPIC_BASE_URL=http://localhost:{self.port}/anthropicβ
β β
β Then run your app normally. CASCADE sees everything. β
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
""")
await site.start()
# Keep running
while True:
await asyncio.sleep(3600)
async def handle_request(self, request: web.Request) -> web.Response:
"""Handle incoming request, proxy to real API, emit receipt."""
path = request.path
# Determine provider from path
provider, real_url = self._resolve_provider(path, request)
if not real_url:
return web.json_response(
{"error": "Unknown provider. Use /v1/* for OpenAI or /anthropic/* for Anthropic"},
status=400
)
# Read request body
body = await request.read()
request_data = {}
try:
if body:
request_data = json.loads(body)
except:
pass
# Forward headers (strip host, add auth if needed)
headers = dict(request.headers)
headers.pop("Host", None)
headers.pop("host", None)
# Make request to real API
try:
async with self.session.request(
method=request.method,
url=real_url,
headers=headers,
data=body,
) as response:
response_body = await response.read()
response_data = {}
try:
response_data = json.loads(response_body)
except:
pass
# Emit receipt
self._emit_receipt(provider, request_data, response_data, path)
# Update stats
self.stats["requests"] += 1
self.stats["bytes_proxied"] += len(body) + len(response_body)
# Return response to client
return web.Response(
body=response_body,
status=response.status,
headers={
k: v for k, v in response.headers.items()
if k.lower() not in ("transfer-encoding", "content-encoding")
},
)
except Exception as e:
if self.verbose:
print(f"[CASCADE PROXY] Error: {e}")
return web.json_response(
{"error": f"Proxy error: {str(e)}"},
status=502
)
def _resolve_provider(self, path: str, request: web.Request) -> tuple:
"""Resolve which provider to forward to based on path."""
# OpenAI: /v1/* -> api.openai.com/v1/*
if path.startswith("/v1"):
return "openai", f"https://api.openai.com{path}"
# Anthropic: /anthropic/* -> api.anthropic.com/*
if path.startswith("/anthropic"):
real_path = path[len("/anthropic"):]
return "anthropic", f"https://api.anthropic.com{real_path}"
# Cohere: /cohere/* -> api.cohere.ai/*
if path.startswith("/cohere"):
real_path = path[len("/cohere"):]
return "cohere", f"https://api.cohere.ai{real_path}"
# Mistral: /mistral/* -> api.mistral.ai/*
if path.startswith("/mistral"):
real_path = path[len("/mistral"):]
return "mistral", f"https://api.mistral.ai{real_path}"
# Custom endpoint via header
custom_base = request.headers.get("X-Cascade-Forward-To")
if custom_base:
return "custom", f"{custom_base}{path}"
return None, None
def _emit_receipt(
self,
provider: str,
request_data: Dict[str, Any],
response_data: Dict[str, Any],
path: str,
):
"""Emit CASCADE receipt for this request/response."""
try:
# Extract model ID
model_id = self._extract_model_id(provider, request_data, response_data)
# Extract input
input_text = self._extract_input(provider, request_data)
# Extract output
output_text = self._extract_output(provider, response_data)
# Extract metrics
metrics = self._extract_metrics(provider, response_data, request_data)
# Emit via SDK
self.sdk.observe(
model_id=model_id,
input_data=input_text,
output_data=output_text,
metrics=metrics,
context={
"provider": provider,
"endpoint": path,
"via": "proxy",
}
)
self.stats["receipts_emitted"] += 1
if self.verbose:
print(f"[CASCADE] Receipt: {model_id} via proxy")
except Exception as e:
if self.verbose:
print(f"[CASCADE] Failed to emit receipt: {e}")
def _extract_model_id(
self,
provider: str,
request_data: Dict[str, Any],
response_data: Dict[str, Any],
) -> str:
"""Extract canonical model ID."""
model = request_data.get("model") or response_data.get("model", "unknown")
return f"{provider}/{model}"
def _extract_input(self, provider: str, request_data: Dict[str, Any]) -> str:
"""Extract input text from request."""
# Chat completion style
messages = request_data.get("messages", [])
if messages:
user_msgs = [m for m in messages if m.get("role") == "user"]
if user_msgs:
content = user_msgs[-1].get("content", "")
if isinstance(content, list):
texts = [c.get("text", "") for c in content if isinstance(c, dict)]
return " ".join(texts)
return str(content)
# Completion style
return request_data.get("prompt", "")
def _extract_output(self, provider: str, response_data: Dict[str, Any]) -> str:
"""Extract output text from response."""
# OpenAI style
choices = response_data.get("choices", [])
if choices:
choice = choices[0]
if "message" in choice:
return choice["message"].get("content", "")
if "text" in choice:
return choice["text"]
# Anthropic style
content = response_data.get("content", [])
if content and isinstance(content, list):
texts = [c.get("text", "") for c in content if isinstance(c, dict)]
return " ".join(texts)
return ""
def _extract_metrics(
self,
provider: str,
response_data: Dict[str, Any],
request_data: Dict[str, Any],
) -> Dict[str, Any]:
"""Extract metrics from response."""
metrics = {}
# Usage stats
usage = response_data.get("usage", {})
if usage:
metrics["prompt_tokens"] = usage.get("prompt_tokens") or usage.get("input_tokens")
metrics["completion_tokens"] = usage.get("completion_tokens") or usage.get("output_tokens")
metrics["total_tokens"] = usage.get("total_tokens")
# Request params
metrics["temperature"] = request_data.get("temperature")
metrics["max_tokens"] = request_data.get("max_tokens")
return {k: v for k, v in metrics.items() if v is not None}
async def shutdown(self):
"""Shutdown proxy."""
if self.session:
await self.session.close()
self.sdk.shutdown()
# Print stats
runtime = time.time() - self.stats["start_time"] if self.stats["start_time"] else 0
print(f"""
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β CASCADE PROXY - Shutdown β
β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ£
β Runtime: {runtime:.1f}s β
β Requests: {self.stats['requests']} β
β Receipts: {self.stats['receipts_emitted']} β
β Bytes: {self.stats['bytes_proxied']} β
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
""")
def run_proxy(host: str = "0.0.0.0", port: int = 7777, verbose: bool = True):
"""Run the CASCADE proxy server."""
proxy = CascadeProxy(host=host, port=port, verbose=verbose)
try:
asyncio.run(proxy.start())
except KeyboardInterrupt:
print("\nShutting down...")
asyncio.run(proxy.shutdown())
# =============================================================================
# CLI
# =============================================================================
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser(
description="CASCADE Proxy - Protocol-level AI observation"
)
parser.add_argument("--host", default="0.0.0.0", help="Host to bind to")
parser.add_argument("--port", "-p", type=int, default=7777, help="Port to listen on")
parser.add_argument("--quiet", "-q", action="store_true", help="Suppress output")
args = parser.parse_args()
run_proxy(host=args.host, port=args.port, verbose=not args.quiet)
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