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661b502 | 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 | #!/usr/bin/env python3
"""Minimal RITS chat-completions client."""
from __future__ import annotations
import argparse
import json
import os
import sys
import urllib.error
import urllib.request
from pathlib import Path
from urllib.parse import urlsplit, urlunsplit
def load_dotenv(path: Path) -> None:
if not path.exists():
return
for raw_line in path.read_text(encoding="utf-8").splitlines():
line = raw_line.strip()
if not line or line.startswith("#") or "=" not in line:
continue
key, value = line.split("=", 1)
key = key.strip()
value = value.strip().strip('"').strip("'")
os.environ.setdefault(key, value)
def model_to_route(model: str) -> str:
model_name = model.strip("/").rsplit("/", 1)[-1]
return model_name.replace(".", "-")
def base_url_for_model(base_url: str, model: str) -> str:
"""Build the RITS base URL from .env and the requested model."""
normalized = base_url.rstrip("/")
model_route = model_to_route(model)
split = urlsplit(normalized)
parts = [part for part in split.path.split("/") if part]
if parts and parts[-1] == "v1":
parts = model_route.split("/") + ["v1"]
else:
parts = parts + model_route.split("/") + ["v1"]
return urlunsplit((split.scheme, split.netloc, "/" + "/".join(parts), "", ""))
def chat_completion(
*,
base_url: str,
api_key: str,
model: str,
prompt: str,
temperature: float,
max_tokens: int,
) -> str:
url = f"{base_url.rstrip('/')}/chat/completions"
payload = {
"model": model,
"messages": [{"role": "user", "content": prompt}],
"temperature": temperature,
"max_tokens": max_tokens,
}
request = urllib.request.Request(
url,
data=json.dumps(payload).encode("utf-8"),
headers={
"Authorization": f"Bearer {api_key}",
"RITS_API_KEY": api_key,
"Content-Type": "application/json",
"Accept": "application/json",
},
method="POST",
)
try:
with urllib.request.urlopen(request, timeout=60) as response:
data = json.loads(response.read().decode("utf-8"))
except urllib.error.HTTPError as exc:
detail = exc.read().decode("utf-8", errors="replace")
raise RuntimeError(f"RITS returned HTTP {exc.code}: {detail}") from exc
except urllib.error.URLError as exc:
raise RuntimeError(f"Could not connect to RITS: {exc.reason}") from exc
try:
return data["choices"][0]["message"]["content"]
except (KeyError, IndexError, TypeError) as exc:
raise RuntimeError(f"Unexpected RITS response: {json.dumps(data)}") from exc
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Call a RITS-hosted chat model.")
parser.add_argument("prompt", nargs="?", help="Prompt to send to the model.")
parser.add_argument(
"-m",
"--model",
help="Model name to request. Defaults to LLM_MODEL from .env.",
)
parser.add_argument(
"--base-url",
help="RITS OpenAI-compatible base URL template. Defaults to LLM_BASE_URL from .env.",
)
parser.add_argument(
"--api-key",
help="RITS API key. Defaults to LLM_API_KEY from .env.",
)
parser.add_argument(
"--input-file",
help="Path to a text file containing the prompt to send to the model.",
)
parser.add_argument(
"--gpus",
type=int,
default=1,
help="Accepted for job compatibility. Defaults to 1 and is not sent to RITS.",
)
parser.add_argument("--temperature", type=float, default=0.2)
parser.add_argument("--max-tokens", type=int, default=512)
return parser.parse_args()
def prompt_from_args(args: argparse.Namespace) -> str:
if args.input_file:
try:
return Path(args.input_file).read_text(encoding="utf-8")
except OSError as exc:
raise RuntimeError(f"Could not read input file {args.input_file}: {exc}") from exc
if args.prompt is None:
raise RuntimeError("Missing prompt. Pass a prompt argument or use --input-file.")
return args.prompt
def main() -> int:
load_dotenv(Path(".env"))
args = parse_args()
model = args.model or os.getenv("LLM_MODEL")
base_url_template = args.base_url or os.getenv("LLM_BASE_URL")
api_key = args.api_key or os.getenv("LLM_API_KEY")
missing = [
name
for name, value in {
"LLM_API_KEY": api_key,
"LLM_BASE_URL": base_url_template,
"LLM_MODEL or --model": model,
}.items()
if not value
]
if missing:
print(f"Missing required configuration: {', '.join(missing)}", file=sys.stderr)
return 2
base_url = base_url_for_model(base_url_template, model)
try:
prompt = prompt_from_args(args)
result = chat_completion(
base_url=base_url,
api_key=api_key,
model=model,
prompt=prompt,
temperature=args.temperature,
max_tokens=args.max_tokens,
)
except RuntimeError as exc:
print(exc, file=sys.stderr)
return 1
print(result)
return 0
if __name__ == "__main__":
raise SystemExit(main())
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