Files
hermes 7dc32a50e2 Raise LLM read timeout to 300s; prefer LAN endpoint in env example
Midnight failures were read timeouts against the public URL — hairpin NAT
and/or the request queuing behind other traffic on the shared model.
LAN endpoint + longer timeout covers both.
2026-09-30 08:06:18 +00:00

134 lines
4.6 KiB
Python

"""Call an OpenAI-compatible chat completions endpoint to generate jokes."""
import json
import re
import httpx
from .config import settings
SYSTEM_PROMPT = (
"You are a comedian. You will receive the text of Wikipedia's featured article "
"of the day. Write exactly 5 short, clean, family-friendly jokes inspired by "
"facts from the article. Vary the style (one-liners, puns, observational). "
"The jokes must be understandable on their own without reading the article. "
"Respond with ONLY a JSON array of 5 strings and nothing else. "
"Example: [\"joke one\", \"joke two\", \"joke three\", \"joke four\", \"joke five\"]"
)
def _try_parse(candidate: str):
try:
return json.loads(candidate)
except json.JSONDecodeError:
return None
def _normalize_quotes(text: str) -> str:
"""Rewrite LLM quote soup into valid JSON.
Handles models that use curly quotes (“ ”) as string DELIMITERS and also
as content inside straight-quoted strings. A scanner tracks which quote
character opened the current string so content quotes are preserved
(escaped) instead of breaking the structure.
"""
out: list[str] = []
in_str: str | None = None # '"' or '“'
i = 0
n = len(text)
while i < n:
c = text[i]
if in_str is None:
if c == '"':
in_str = '"'
out.append(c)
elif c == "\u201c": # “ opens a string
in_str = "\u201c"
out.append('"')
else:
out.append(c)
else:
if c == "\\" and i + 1 < n: # keep escape pairs intact
out.append(c)
out.append(text[i + 1])
i += 2
continue
if in_str == '"':
# Straight-delimited: curly quotes are just content.
out.append(c)
if c == '"':
in_str = None
else: # curly-delimited string
if c == "\u201d": # ” closes it
in_str = None
out.append('"')
elif c == '"': # raw straight quote inside -> escape
out.append('\\"')
else:
out.append(c)
i += 1
return "".join(out)
def _repair_and_parse(text: str):
"""Parse JSON, repairing common LLM quote mistakes if strict parse fails."""
try:
return json.loads(text)
except json.JSONDecodeError:
pass
data = _try_parse(_normalize_quotes(text))
if data is not None:
return data
raise ValueError(f"Could not parse jokes JSON even after repair: {text[:200]!r}")
def _extract_json_array(text: str) -> list[str]:
"""Pull a JSON array of strings out of a possibly messy LLM response."""
text = text.strip()
# Strip markdown fences if present.
fence = re.search(r"```(?:json)?\s*(.*?)```", text, re.DOTALL)
if fence:
text = fence.group(1).strip()
# Find the outermost [...] span.
start = text.find("[")
end = text.rfind("]")
if start == -1 or end == -1 or end <= start:
raise ValueError(f"No JSON array found in LLM response: {text[:200]!r}")
data = _repair_and_parse(text[start : end + 1])
if not isinstance(data, list):
raise ValueError("Parsed JSON is not a list")
jokes = [str(j).strip() for j in data if str(j).strip()]
if len(jokes) < 5:
raise ValueError(f"Only {len(jokes)} jokes returned, expected 5")
return jokes[:5]
def generate_jokes(article_title: str, article_extract: str) -> list[str]:
url = f"{settings.openai_base_url}/chat/completions"
headers = {"Content-Type": "application/json"}
if settings.openai_api_key:
headers["Authorization"] = f"Bearer {settings.openai_api_key}"
user_prompt = (
f"Today's Wikipedia featured article: \"{article_title}\"\n\n"
f"Article text:\n{article_extract}\n\n"
"Now write exactly 5 jokes as a JSON array of 5 strings."
)
body = {
"model": settings.openai_model,
"messages": [
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": user_prompt},
],
"temperature": 0.9,
"max_tokens": 800,
}
# 300s: the model may be shared (e.g. serving this agent too), so a
# request can legitimately queue behind other traffic.
resp = httpx.post(url, headers=headers, json=body, timeout=300)
resp.raise_for_status()
payload = resp.json()
content = payload["choices"][0]["message"]["content"]
return _extract_json_array(content)