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import os
import time
from contextlib import asynccontextmanager
from fastapi import FastAPI, Request, HTTPException
from fastapi.responses import StreamingResponse, JSONResponse
from config import (
UPSTREAM_URL, SUPPORTED_MODELS, DEFAULT_MODEL,
UPSTREAM_TIMEOUT_SECS, UPSTREAM_CONNECT_TIMEOUT_SECS,
UPSTREAM_MAX_CONNECTIONS, UPSTREAM_MAX_KEEPALIVE_CONNECTIONS,
UPSTREAM_KEEPALIVE_EXPIRY_SECS, UPSTREAM_PROXY_URL,
)
from response_cache import get_cache_service
from translate import (
pick_model, build_payload,
build_upstream_messages_anthropic, build_upstream_messages_openai,
)
from upstream import create_upstream_client, close_upstream_client, fetch_completion_artifact
from render import (
render_anthropic_json_from_artifact, render_openai_json_from_artifact,
anthropic_stream_from_artifact, openai_stream_from_artifact,
anthropic_aggregate, openai_aggregate,
)
from stream import (
anthropic_stream_plain, anthropic_stream_with_tools,
openai_stream_plain, openai_stream_with_tools,
build_cache_headers, build_stream_headers,
wait_for_inflight_artifact, finalize_stream_cache,
)
from upstream import LiveArtifactCapture
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s %(levelname)s [%(name)s] %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
)
logger = logging.getLogger(__name__)
@asynccontextmanager
async def lifespan(_: FastAPI):
client = create_upstream_client()
logger.info("upstream client created (proxy=%s)", bool(UPSTREAM_PROXY_URL))
try:
yield
finally:
await close_upstream_client()
logger.info("upstream client closed")
app = FastAPI(title="p5js.ai 2 API (Anthropic + OpenAI)", lifespan=lifespan)
@app.get("/")
@app.get("/health")
async def health():
cache_service = get_cache_service()
return {
"status": "ok",
"service": "p5js.ai-2api",
"endpoints": ["/v1/messages", "/v1/chat/completions", "/v1/models"],
"models": sorted(SUPPORTED_MODELS),
"tool_use": "pseudo (XML-based, upstream does not support native tool_use)",
"cache": cache_service.describe(),
"upstream": {
"url": UPSTREAM_URL,
"proxy_configured": bool(UPSTREAM_PROXY_URL or os.getenv("HTTPS_PROXY") or os.getenv("HTTP_PROXY")),
"timeout_secs": UPSTREAM_TIMEOUT_SECS,
"connect_timeout_secs": UPSTREAM_CONNECT_TIMEOUT_SECS,
"max_connections": UPSTREAM_MAX_CONNECTIONS,
"max_keepalive_connections": UPSTREAM_MAX_KEEPALIVE_CONNECTIONS,
"keepalive_expiry_secs": UPSTREAM_KEEPALIVE_EXPIRY_SECS,
},
}
@app.get("/v1/models")
async def list_models():
now = int(time.time())
return {
"data": [
{"id": m, "object": "model", "created": now, "owned_by": "anthropic"}
for m in sorted(SUPPORTED_MODELS)
],
"object": "list",
}
@app.post("/v1/messages")
async def anthropic_messages(request: Request):
try:
body = await request.json()
except Exception:
raise HTTPException(status_code=400, detail="invalid json body")
model = pick_model(body.get("model"))
stream = bool(body.get("stream", False))
tools = body.get("tools") or None
has_tools = bool(tools)
upstream_messages = build_upstream_messages_anthropic(body.get("system"), body.get("messages", []), tools)
payload = build_payload(model, upstream_messages)
cache_service = get_cache_service()
bypass_cache = cache_service.should_bypass(request.headers)
if bypass_cache:
await cache_service.record_bypass()
live_status = "MISS" if cache_service.config.enabled and not bypass_cache else ("BYPASS" if bypass_cache else "DISABLED")
cache_key = cache_service.build_key(
protocol_family="anthropic",
resolved_model=model,
upstream_messages=upstream_messages,
auth_scope=cache_service.auth_scope_from_headers(request.headers),
has_tools=has_tools,
)
ttl_secs = cache_service.config.ttl_for(has_tools)
if cache_service.config.enabled and not bypass_cache:
lookup = await cache_service.get(cache_key)
if lookup.artifact is not None:
logger.debug("anthropic cache HIT key=%s source=%s", cache_key[:24], lookup.source)
if stream:
return StreamingResponse(
anthropic_stream_from_artifact(lookup.artifact, has_tools),
media_type="text/event-stream",
headers=build_stream_headers("HIT", lookup.source),
)
return JSONResponse(
render_anthropic_json_from_artifact(lookup.artifact, has_tools),
headers=build_cache_headers("HIT", lookup.source),
)
is_leader, future = await cache_service.inflight.start(cache_key)
if not is_leader:
await cache_service.record_inflight_wait()
artifact = await wait_for_inflight_artifact(future)
if artifact is not None:
if stream:
return StreamingResponse(
anthropic_stream_from_artifact(artifact, has_tools),
media_type="text/event-stream",
headers=build_stream_headers("HIT", "inflight"),
)
return JSONResponse(
render_anthropic_json_from_artifact(artifact, has_tools),
headers=build_cache_headers("HIT", "inflight"),
)
else:
if stream:
capture = LiveArtifactCapture(model)
live_stream = anthropic_stream_with_tools(payload, capture) if has_tools else anthropic_stream_plain(payload, capture)
return StreamingResponse(
finalize_stream_cache(live_stream, capture, cache_key, ttl_secs),
media_type="text/event-stream",
headers=build_stream_headers("MISS", "live"),
)
try:
artifact = await fetch_completion_artifact(payload)
await cache_service.set(cache_key, artifact, ttl_secs)
await cache_service.inflight.resolve(cache_key, artifact)
except Exception as exc:
await cache_service.inflight.reject(cache_key, exc)
raise
return JSONResponse(
render_anthropic_json_from_artifact(artifact, has_tools),
headers=build_cache_headers("MISS", "live"),
)
if stream:
gen = anthropic_stream_with_tools(payload) if has_tools else anthropic_stream_plain(payload)
return StreamingResponse(
gen,
media_type="text/event-stream",
headers=build_stream_headers(live_status, "live"),
)
return JSONResponse(
await anthropic_aggregate(payload, has_tools),
headers=build_cache_headers(live_status, "live"),
)
@app.post("/v1/chat/completions")
async def openai_chat_completions(request: Request):
try:
body = await request.json()
except Exception:
raise HTTPException(status_code=400, detail="invalid json body")
requested_model = body.get("model") or DEFAULT_MODEL
model = pick_model(requested_model)
stream = bool(body.get("stream", False))
tools = body.get("tools") or None
has_tools = bool(tools)
upstream_messages = build_upstream_messages_openai(body.get("messages", []), tools)
payload = build_payload(model, upstream_messages)
cache_service = get_cache_service()
bypass_cache = cache_service.should_bypass(request.headers)
if bypass_cache:
await cache_service.record_bypass()
live_status = "MISS" if cache_service.config.enabled and not bypass_cache else ("BYPASS" if bypass_cache else "DISABLED")
cache_key = cache_service.build_key(
protocol_family="openai",
resolved_model=model,
upstream_messages=upstream_messages,
auth_scope=cache_service.auth_scope_from_headers(request.headers),
has_tools=has_tools,
)
ttl_secs = cache_service.config.ttl_for(has_tools)
if cache_service.config.enabled and not bypass_cache:
lookup = await cache_service.get(cache_key)
if lookup.artifact is not None:
logger.debug("openai cache HIT key=%s source=%s", cache_key[:24], lookup.source)
if stream:
return StreamingResponse(
openai_stream_from_artifact(lookup.artifact, has_tools),
media_type="text/event-stream",
headers=build_stream_headers("HIT", lookup.source),
)
return JSONResponse(
render_openai_json_from_artifact(lookup.artifact, has_tools),
headers=build_cache_headers("HIT", lookup.source),
)
is_leader, future = await cache_service.inflight.start(cache_key)
if not is_leader:
await cache_service.record_inflight_wait()
artifact = await wait_for_inflight_artifact(future)
if artifact is not None:
if stream:
return StreamingResponse(
openai_stream_from_artifact(artifact, has_tools),
media_type="text/event-stream",
headers=build_stream_headers("HIT", "inflight"),
)
return JSONResponse(
render_openai_json_from_artifact(artifact, has_tools),
headers=build_cache_headers("HIT", "inflight"),
)
else:
if stream:
capture = LiveArtifactCapture(model)
live_stream = openai_stream_with_tools(payload, requested_model, capture) if has_tools else openai_stream_plain(payload, requested_model, capture)
return StreamingResponse(
finalize_stream_cache(live_stream, capture, cache_key, ttl_secs),
media_type="text/event-stream",
headers=build_stream_headers("MISS", "live"),
)
try:
artifact = await fetch_completion_artifact(payload)
await cache_service.set(cache_key, artifact, ttl_secs)
await cache_service.inflight.resolve(cache_key, artifact)
except Exception as exc:
await cache_service.inflight.reject(cache_key, exc)
raise
return JSONResponse(
render_openai_json_from_artifact(artifact, has_tools),
headers=build_cache_headers("MISS", "live"),
)
if stream:
gen = openai_stream_with_tools(payload, requested_model) if has_tools else openai_stream_plain(payload, requested_model)
return StreamingResponse(
gen,
media_type="text/event-stream",
headers=build_stream_headers(live_status, "live"),
)
return JSONResponse(
await openai_aggregate(payload, requested_model, has_tools),
headers=build_cache_headers(live_status, "live"),
)
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=18185)
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