ATOCore/scripts/batch_llm_extract_live.py

"""Host-side LLM batch extraction — HTTP client + shared prompt module.

Fetches interactions from the AtoCore API, runs ``claude -p`` locally
for each, and POSTs candidates back. Uses stdlib + the ``claude`` CLI
on PATH, plus the stdlib-only shared prompt/parser module at
``atocore.memory._llm_prompt`` to eliminate prompt/parser drift
against the in-container extractor (R12).

This is necessary because the ``claude`` CLI is on the Dalidou HOST
but not inside the Docker container, and the host's Python doesn't
have the container's dependencies (pydantic_settings, etc.) — so we
only import the one stdlib-only module, not the full atocore package.
"""

from __future__ import annotations

import argparse
import json
import os
import shutil
import subprocess
import sys
import tempfile
import urllib.error
import urllib.parse
import urllib.request
from datetime import datetime, timezone

# R12: share the prompt + parser with the in-container extractor so
# the two paths can't drift. The imported module is stdlib-only by
# design; see src/atocore/memory/_llm_prompt.py.
_SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
_SRC_DIR = os.path.abspath(os.path.join(_SCRIPT_DIR, "..", "src"))
if _SRC_DIR not in sys.path:
    sys.path.insert(0, _SRC_DIR)

from atocore.memory._llm_prompt import (  # noqa: E402
    MEMORY_TYPES,
    SYSTEM_PROMPT,
    build_user_message,
    normalize_candidate_item,
    parse_llm_json_array,
)

DEFAULT_BASE_URL = os.environ.get("ATOCORE_BASE_URL", "http://localhost:8100")
DEFAULT_MODEL = os.environ.get("ATOCORE_LLM_EXTRACTOR_MODEL", "sonnet")
DEFAULT_TIMEOUT_S = float(os.environ.get("ATOCORE_LLM_EXTRACTOR_TIMEOUT_S", "90"))


_sandbox_cwd = None


def get_sandbox_cwd():
    global _sandbox_cwd
    if _sandbox_cwd is None:
        _sandbox_cwd = tempfile.mkdtemp(prefix="ato-llm-extract-")
    return _sandbox_cwd


def api_get(base_url, path, timeout=10):
    req = urllib.request.Request(f"{base_url}{path}")
    with urllib.request.urlopen(req, timeout=timeout) as resp:
        return json.loads(resp.read().decode("utf-8"))


def api_post(base_url, path, body, timeout=10):
    data = json.dumps(body).encode("utf-8")
    req = urllib.request.Request(
        f"{base_url}{path}", method="POST",
        headers={"Content-Type": "application/json"}, data=data,
    )
    with urllib.request.urlopen(req, timeout=timeout) as resp:
        return json.loads(resp.read().decode("utf-8"))


def get_last_run(base_url):
    try:
        state = api_get(base_url, "/project/state/atocore?category=status")
        for entry in state.get("entries", []):
            if entry.get("key") == "last_extract_batch_run":
                return entry["value"]
    except Exception:
        pass
    return None


def set_last_run(base_url, timestamp):
    try:
        api_post(base_url, "/project/state", {
            "project": "atocore", "category": "status",
            "key": "last_extract_batch_run", "value": timestamp,
            "source": "batch_llm_extract_live.py",
        })
    except Exception:
        pass


_known_projects: set[str] = set()


def _load_known_projects(base_url):
    """Fetch registered project IDs from the API for R9 validation."""
    global _known_projects
    try:
        data = api_get(base_url, "/projects")
        _known_projects = {p["id"] for p in data.get("projects", [])}
        for p in data.get("projects", []):
            for alias in p.get("aliases", []):
                _known_projects.add(alias)
    except Exception:
        pass


def extract_one(prompt, response, project, model, timeout_s):
    """Run claude -p on one interaction, return parsed candidates."""
    if not shutil.which("claude"):
        return [], "claude_cli_missing"

    user_message = build_user_message(prompt, response, project)

    args = [
        "claude", "-p",
        "--model", model,
        "--append-system-prompt", SYSTEM_PROMPT,
        "--disable-slash-commands",
        user_message,
    ]

    try:
        completed = subprocess.run(
            args, capture_output=True, text=True,
            timeout=timeout_s, cwd=get_sandbox_cwd(),
            encoding="utf-8", errors="replace",
        )
    except subprocess.TimeoutExpired:
        return [], "timeout"
    except Exception as exc:
        return [], f"subprocess_error: {exc}"

    if completed.returncode != 0:
        return [], f"exit_{completed.returncode}"

    raw = (completed.stdout or "").strip()
    return parse_candidates(raw, project), ""


def parse_candidates(raw, interaction_project):
    """Parse model JSON output into candidate dicts.

    Stripping + per-item normalization come from the shared
    ``_llm_prompt`` module. Host-side project attribution: interaction
    scope wins, otherwise keep the model's tag (the API's own R9
    registry-check will happen server-side in the container on write;
    here we preserve the signal instead of dropping it).
    """
    results = []
    for item in parse_llm_json_array(raw):
        normalized = normalize_candidate_item(item)
        if normalized is None:
            continue
        project = interaction_project or normalized["project"] or ""
        results.append({
            "memory_type": normalized["type"],
            "content": normalized["content"],
            "project": project,
            "confidence": normalized["confidence"],
        })
    return results


def main():
    parser = argparse.ArgumentParser(description="Host-side LLM batch extraction")
    parser.add_argument("--base-url", default=DEFAULT_BASE_URL)
    parser.add_argument("--limit", type=int, default=50)
    parser.add_argument("--since", default=None)
    parser.add_argument("--model", default=DEFAULT_MODEL)
    args = parser.parse_args()

    _load_known_projects(args.base_url)
    since = args.since or get_last_run(args.base_url)
    print(f"since={since or '(first run)'}  limit={args.limit}  model={args.model}  known_projects={len(_known_projects)}")

    params = [f"limit={args.limit}"]
    if since:
        params.append(f"since={urllib.parse.quote(since)}")
    listing = api_get(args.base_url, f"/interactions?{'&'.join(params)}")
    interaction_summaries = listing.get("interactions", [])
    print(f"listed {len(interaction_summaries)} interactions")

    processed = 0
    total_candidates = 0
    total_persisted = 0
    errors = 0

    for summary in interaction_summaries:
        resp_chars = summary.get("response_chars", 0) or 0
        if resp_chars < 50:
            continue
        iid = summary["id"]
        try:
            raw = api_get(
                args.base_url,
                f"/interactions/{urllib.parse.quote(iid, safe='')}",
            )
        except Exception as exc:
            print(f"  ! {iid[:8]}: fetch failed: {exc}", file=sys.stderr)
            errors += 1
            continue
        response_text = raw.get("response", "") or ""
        if not response_text.strip() or len(response_text) < 50:
            continue

        candidates, error = extract_one(
            prompt=raw.get("prompt", "") or "",
            response=response_text,
            project=raw.get("project", "") or "",
            model=args.model,
            timeout_s=DEFAULT_TIMEOUT_S,
        )

        if error:
            print(f"  ! {raw['id'][:8]}: {error}", file=sys.stderr)
            errors += 1
            continue

        processed += 1
        total_candidates += len(candidates)

        for c in candidates:
            try:
                api_post(args.base_url, "/memory", {
                    "memory_type": c["memory_type"],
                    "content": c["content"],
                    "project": c["project"],
                    "confidence": c["confidence"],
                    "status": "candidate",
                })
                total_persisted += 1
            except urllib.error.HTTPError as exc:
                if exc.code != 400:
                    errors += 1
            except Exception:
                errors += 1

    now = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
    set_last_run(args.base_url, now)

    print(f"processed={processed} candidates={total_candidates} persisted={total_persisted} errors={errors}")


if __name__ == "__main__":
    main()