ai.py

"""
ai.py — Groq-powered reasoning for the B24 Browser AI backend.
Uses llama-3.3-70b-versatile, same model as Joy on B24 Messenger.
"""

import os
from groq import Groq

GROQ_KEY = os.environ.get("groq_key")
_client = Groq(api_key=GROQ_KEY) if GROQ_KEY else None

MODEL = "llama-3.3-70b-versatile"


def _chat(system: str, user: str, max_tokens: int = 700) -> str:
    if not _client:
        return "AI is not configured (missing groq_key secret)."
    completion = _client.chat.completions.create(
        model=MODEL,
        messages=[
            {"role": "system", "content": system},
            {"role": "user", "content": user},
        ],
        max_tokens=max_tokens,
        temperature=0.4,
    )
    return completion.choices[0].message.content.strip()


def summarize_page(url: str, text: str) -> str:
    text = (text or "")[:12000]
    system = (
        "You summarize web pages clearly and concisely for someone browsing "
        "on a phone. Use short paragraphs or bullet points. No fluff."
    )
    user = f"URL: {url}\n\nPage content:\n{text}\n\nSummarize this page."
    return _chat(system, user, max_tokens=500)


def synthesize_search(query: str, results: list) -> str:
    listing = "\n".join(
        f"- {r['title']}: {r['snippet']} ({r['url']})" for r in results[:8]
    )
    system = (
        "You are a smart search assistant. Given raw search results, write "
        "a short, direct answer to the user's query, citing which result(s) "
        "back it up by title. Keep it tight — a few sentences."
    )
    user = f"Query: {query}\n\nSearch results:\n{listing}\n\nAnswer the query."
    return _chat(system, user, max_tokens=400)


def suggest_related(url: str, text: str) -> list:
    text = (text or "")[:6000]
    system = (
        "Given a web page's content, suggest 5 short, specific search "
        "queries a curious reader might want to explore next. "
        "Return ONLY a JSON array of strings, nothing else."
    )
    user = f"URL: {url}\n\nPage content:\n{text}"
    raw = _chat(system, user, max_tokens=200)

    import json

    try:
        cleaned = raw.strip().strip("`").replace("json", "", 1) if raw.strip().startswith("```") else raw
        parsed = json.loads(cleaned)
        if isinstance(parsed, list):
            return [str(x) for x in parsed[:5]]
    except (json.JSONDecodeError, ValueError):
        pass

    lines = [l.strip("-• ").strip() for l in raw.splitlines() if l.strip()]
    return lines[:5]