Spaces:
Running
Running
File size: 8,503 Bytes
2129c29 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 | #!/usr/bin/env python3
"""
ASGI server startup command for NLProxy.
Provides a production-ready FastAPI/uvicorn launcher with environment-aware
configuration, graceful shutdown, structured logging, and dev/prod mode handling.
Usage
-----
# Production startup (auto-detects CPU cores, disables reload)
$ python -m nlproxy runserver
# Development with auto-reload & debug logging
$ python -m nlproxy runserver --reload --log-level debug
# Bind to specific interface with explicit workers
$ python -m nlproxy runserver --host 0.0.0.0 --port 8080 --workers 4
Configuration
-------------
Environment variables:
NLPROXY_HOST Server bind host (default: 0.0.0.0)
NLPROXY_PORT Server bind port (default: 8000)
NLPROXY_LOG_LEVEL Logging level: debug, info, warning, error, critical
NLPROXY_RELOAD Set to "true" to enable dev auto-reload
Author: IntelliDeep Labs Team
License: BSL 1.1
"""
from __future__ import annotations
import argparse
import logging
import multiprocessing
import os
import sys
from typing import Dict, Optional
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# .env file loader (no external dependency required)
# ---------------------------------------------------------------------------
def _load_dotenv(path: Optional[str] = None) -> Dict[str, str]:
"""
Parse a .env file and return environment variables as a dict.
Looks for ``.env`` in the current working directory by default.
Supports ``KEY=VALUE`` syntax with optional quoting, and ``#`` comments.
Skips empty lines.
"""
dotenv_path = path or os.path.join(os.getcwd(), ".env")
result: Dict[str, str] = {}
if not os.path.isfile(dotenv_path):
return result
try:
with open(dotenv_path, "r") as f:
for line in f:
line = line.strip()
if not line or line.startswith("#") or "=" not in line:
continue
key, _, value = line.partition("=")
key = key.strip()
value = value.strip().strip("\"'")
if key:
result[key] = value
except OSError:
pass
return result
# Attempt to load .env variables into the environment so they are available
# for :func:`os.getenv` calls that follow.
_dotenv_vars = _load_dotenv()
for _k, _v in _dotenv_vars.items():
os.environ.setdefault(_k, _v)
del _dotenv_vars
def setup_logging(level: str = "INFO") -> None:
"""Configure structured console logging for CLI/server processes."""
numeric_level = getattr(logging, level.upper(), logging.INFO)
logging.basicConfig(
level=numeric_level,
format="%(asctime)s [%(levelname)-8s] %(message)s",
datefmt="%H:%M:%S",
stream=sys.stderr,
)
DEFAULT_MODEL_PER_PROVIDER = {
"gemini": "gemini-2.0-flash",
"claude": "claude-3-sonnet-20240229",
"openai": "gpt-4",
"deepseek": "deepseek-chat",
"qwen": "qwen-max",
"kimi": "kimi",
"openrouter": "openai/gpt-4",
}
def cmd_runserver(args: argparse.Namespace) -> None:
setup_logging(args.log_level)
try:
import uvicorn
except ImportError:
logger.error("uvicorn is required for server mode...")
sys.exit(1)
workers = args.workers or multiprocessing.cpu_count()
if args.reload and workers > 1:
logger.warning(
"--reload requested but multiple workers configured (%d). "
"Auto-reload requires a single worker process; forcing workers=1 to enable reload.",
workers,
)
workers = 1
provider = args.llm_client or os.getenv("NLPROXY_DEFAULT_LLM_PROVIDER") or "openai"
provider = provider.lower()
if provider not in DEFAULT_MODEL_PER_PROVIDER:
logger.error(f"Unsupported provider: {provider}. Valid: {list(DEFAULT_MODEL_PER_PROVIDER.keys())}")
sys.exit(1)
if args.model:
model = args.model
else:
model = os.getenv("NLPROXY_DEFAULT_LLM_MODEL") or DEFAULT_MODEL_PER_PROVIDER.get(provider)
api_key = args.api_key_client
if not api_key:
env_key_name = {
"gemini": "GEMINI_API_KEY",
"claude": "ANTHROPIC_API_KEY",
"openai": "OPENAI_API_KEY",
"deepseek": "DEEPSEEK_API_KEY",
"qwen": "QWEN_API_KEY",
"kimi": "KIMI_API_KEY",
"openrouter": "OPENROUTER_API_KEY",
}.get(provider)
if env_key_name:
api_key = os.getenv(env_key_name)
if not api_key:
logger.error(f"No API key found for provider '{provider}'. Provide via --api-key-client or set {env_key_name}")
sys.exit(1)
env_map = {
"gemini": "GEMINI_API_KEY",
"claude": "ANTHROPIC_API_KEY",
"openai": "OPENAI_API_KEY",
"deepseek": "DEEPSEEK_API_KEY",
"qwen": "QWEN_API_KEY",
"kimi": "KIMI_API_KEY",
"openrouter": "OPENROUTER_API_KEY",
}
env_var = env_map.get(provider)
if env_var:
os.environ[env_var] = api_key
os.environ[env_var.lower()] = api_key
os.environ["NLPROXY_DEFAULT_LLM_PROVIDER"] = provider
os.environ["nlproxy_default_llm_provider"] = provider
os.environ["NLPROXY_DEFAULT_LLM_MODEL"] = model
os.environ["nlproxy_default_llm_model"] = model
os.environ["LLM_CLIENT"] = provider
os.environ["LLM_API_CLIENT"] = api_key
logger.info(f"Configured LLM: provider={provider}, model={model}")
if args.list_models:
logger.info("Available models per provider:")
for prov, mdl in DEFAULT_MODEL_PER_PROVIDER.items():
logger.info(f" {prov}: {mdl}")
return
server_config = {
"app": "nlproxy.server:app",
"host": args.host,
"port": args.port,
"workers": workers,
"log_level": args.log_level.lower(),
"access_log": args.access_log,
"reload": args.reload,
"reload_dirs": ["nlproxy"],
"loop": "auto",
"http": "httptools",
"ws": "websockets",
"timeout_graceful_shutdown": 30,
"use_colors": True,
}
logger.info(f"Setting env: NLPROXY_DEFAULT_LLM_PROVIDER={os.environ.get('NLPROXY_DEFAULT_LLM_PROVIDER')}")
logger.info(f"Setting env: {env_var}={api_key[:10]}...")
uvicorn.run(**server_config)
def main(argv: Optional[list[str]] = None) -> int:
parser = argparse.ArgumentParser(
prog="nlproxy runserver",
description="Start the NLProxy Enterprise FastAPI server with production-ready configuration.",
)
parser.add_argument("--host", type=str, default=os.getenv("NLPROXY_HOST", "0.0.0.0"))
parser.add_argument("--port", type=int, default=int(os.getenv("NLPROXY_PORT", "8000")))
parser.add_argument("--workers", type=int, default=1)
parser.add_argument("--llm-client", type=str, default=os.getenv("NLPROXY_DEFAULT_LLM_PROVIDER", None),
help="LLM provider to use (gemini|claude|openai|deepseek|qwen|kimi|openrouter).")
parser.add_argument("--model", type=str, default=None,
help="Model name (e.g., gpt-4, gemini-2.0-flash). Overrides env NLPROXY_DEFAULT_LLM_MODEL.")
parser.add_argument("--api-key-client", type=str, default=None,
help="API key for the selected LLM provider (overrides provider-specific env var).")
parser.add_argument("--list-models", action="store_true",
help="List available models for each provider and exit.")
parser.add_argument("--reload", action="store_true", help="Enable auto-reload for development")
parser.add_argument("--log-level", type=str, default=os.getenv("NLPROXY_LOG_LEVEL", "info"),
choices=["debug", "info", "warning", "error", "critical"])
parser.add_argument("--access-log", action="store_true", default=True, help="Enable HTTP access logging")
parser.add_argument("-q", "--quiet", action="store_true", help="Suppress non-essential output")
args = parser.parse_args(argv)
if args.quiet:
logging.getLogger("nlproxy").setLevel(logging.WARNING)
logging.getLogger("uvicorn").setLevel(logging.WARNING)
try:
cmd_runserver(args)
return 0
except KeyboardInterrupt:
return 0
except Exception as e:
logger.error(str(e))
return 1
if __name__ == "__main__":
sys.exit(main())
|