pragent/pilot/ai_review.py

#!/usr/bin/env python3
"""pragent pilot — minimal AI PR reviewer.

Runs as a Gitea Actions step. Fetches a PR diff, asks glm-5.2:cloud (via the
on-network headroom proxy, Anthropic /v1/messages format) to review it, and
posts the findings back as a PR review authored by pragent-bot.

Fail-open by design: any error becomes a short "review failed" review comment,
and the process always exits 0 so it can never block CI.

Stdlib only — no pip install, fast cold start in CI.

Env:
  GITEA_API            base URL of the in-cluster Gitea, e.g. http://gitea-http.gitea.svc.cluster.local:3000
  GITEA_REPOSITORY     "owner/repo" of the PR (github.repository)
  PR_INDEX             PR number (github.event.pull_request.number)
  PR_TITLE             PR title
  PR_BODY              PR body (optional)
  PRAGENT_BOT_TOKEN    bot access token (repo secret)
  PRAGENT_SHA          head SHA to tag the review (github.event.pull_request.head.sha)
  OLLAMA_URL           headroom proxy URL, e.g. http://100.74.17.70:8789
  OLLAMA_MODEL         model id, e.g. glm-5.2:cloud
  OLLAMA_MAX_TOKENS    (optional) output cap, default 6000
  DIFF_MAX_CHARS       (optional) diff truncation cap, default 150000
"""

import json
import os
import sys
import urllib.error
import urllib.request

REVIEW_HEADER = "🤖 **AI Review** · pragent pilot · {model} · `{sha}`"

SYSTEM_PROMPT = """You are a senior, pragmatic code reviewer. Review the pull request diff below.

Report ONLY real, actionable issues: correctness bugs, security problems, risky
changes, missing tests for changed behaviour, and breaking API/contract changes.

For each issue, output exactly one line in this format:
  - [SEVERITY] path:line — concise problem. suggested fix.
where SEVERITY is one of: critical, high, medium, low.

Rules:
- Skip nitpicks, pure formatting, and praise.
- If the diff is clean, output exactly: No issues found.
- Be concise. At most ~15 findings, highest severity first.
- Do not restate the diff. Do not include a summary header. Just the findings lines."""

# ---------------------------------------------------------------------------
# Pure helpers (unit-tested, no network)
# ---------------------------------------------------------------------------


def truncate_diff(text: str, max_chars: int) -> tuple[str, bool, int]:
    """Return (text, was_truncated, original_len). Never raises on bad input."""
    if text is None:
        return "", False, 0
    orig_len = len(text)
    if orig_len <= max_chars:
        return text, False, orig_len
    return text[:max_chars] + f"\n\n[diff truncated at {max_chars} characters]\n", True, orig_len


def parse_text_blocks(content: list) -> str:
    """Join `type:"text"` blocks from an Anthropic /v1/messages response.

    Drops `thinking` blocks (glm-5.2:cloud is a reasoning model and emits them).
    Tolerates missing/malformed blocks by skipping them.
    """
    if not isinstance(content, list):
        return ""
    out = []
    for block in content:
        if not isinstance(block, dict):
            continue
        if block.get("type") == "text" and isinstance(block.get("text"), str):
            out.append(block["text"])
    return "\n".join(out).strip()


def format_review_body(findings: str, model: str, sha: str) -> str:
    """Format the posted review body. Findings empty -> "No issues found."."""
    header = REVIEW_HEADER.format(model=model, sha=sha[:8] if sha else "unknown")
    findings = (findings or "").strip()
    if not findings:
        findings = "No issues found."
    return f"{header}\n\n{findings}"


def build_user_prompt(title: str, body: str, diff: str) -> str:
    parts = [f"## PR\nTitle: {title or '(none)'}"]
    if body and body.strip():
        b = body.strip()
        if len(b) > 4000:
            b = b[:4000] + "\n…[PR body truncated]"
        parts.append(f"Description:\n{b}")
    parts.append(f"## Diff\n```diff\n{diff}\n```")
    return "\n\n".join(parts)


# ---------------------------------------------------------------------------
# Network helpers
# ---------------------------------------------------------------------------


def _http(method: str, url: str, token: str, body: dict | None = None, accept: str = "application/json") -> tuple[int, bytes]:
    headers = {"Authorization": f"token {token}", "Accept": accept}
    data = None
    if body is not None:
        data = json.dumps(body).encode()
        headers["Content-Type"] = "application/json"
    req = urllib.request.Request(url, data=data, headers=headers, method=method)
    try:
        with urllib.request.urlopen(req, timeout=180) as r:
            return r.status, r.read()
    except urllib.error.HTTPError as e:
        return e.code, e.read()
    except urllib.error.URLError as e:
        raise RuntimeError(f"network error: {e.reason}") from e


def gitea_get(api: str, repo: str, path: str, token: str, accept: str = "application/json") -> tuple[int, bytes]:
    return _http("GET", f"{api}/api/v1/repos/{repo}/{path}", token, None, accept)


def gitea_post(api: str, repo: str, path: str, token: str, body: dict) -> tuple[int, bytes]:
    return _http("POST", f"{api}/api/v1/repos/{repo}/{path}", token, body)


def fetch_pr_diff(api: str, repo: str, index: str, token: str, max_chars: int) -> tuple[str, bool, int]:
    """Get the unified diff. Try the `.diff` suffix first, fall back to the
    files endpoint (join `patch` fields) if the server does not serve .diff."""
    status, raw = gitea_get(api, repo, f"pulls/{index}.diff", token, accept="text/plain")
    if status == 200:
        return truncate_diff(raw.decode("utf-8", errors="replace"), max_chars)

    # Fallback: /pulls/{index}/files -> join patch fields.
    status, raw = gitea_get(api, repo, f"pulls/{index}/files", token)
    if status != 200:
        raise RuntimeError(f"could not fetch diff: .diff={status}, files={status}")
    files = json.loads(raw)
    joined = []
    for f in files:
        h = f.get("filename", "?")
        joined.append(f"--- {h}\n+++ {h}\n{f.get('patch', '(binary or no patch)')}")
    return truncate_diff("\n".join(joined), max_chars)


def call_model(ollama_url: str, model: str, system: str, user: str, max_tokens: int) -> str:
    payload = {
        "model": model,
        "max_tokens": max_tokens,
        "system": system,
        "messages": [{"role": "user", "content": user}],
    }
    status, raw = _http(
        "POST",
        f"{ollama_url.rstrip('/')}/v1/messages",
        "ollama",  # headroom ollama hub uses x-api-key: ollama
        payload,
    )
    if status != 200:
        raise RuntimeError(f"model call failed: HTTP {status}: {raw[:500].decode('utf-8', errors='replace')}")
    data = json.loads(raw)
    return parse_text_blocks(data.get("content", []))


def post_review(api: str, repo: str, index: str, token: str, body: str) -> None:
    status, raw = gitea_post(api, repo, f"pulls/{index}/reviews", token, {"event": "COMMENT", "body": body})
    if status not in (200, 201):
        # Fallback to a plain issue comment if reviews endpoint refuses.
        status2, raw2 = gitea_post(api, repo, f"issues/{index}/comments", token, {"body": body})
        if status2 not in (200, 201):
            raise RuntimeError(f"post review failed: reviews={status}, comments={status2}")


# ---------------------------------------------------------------------------
# Main
# ---------------------------------------------------------------------------


def _need(name: str) -> str:
    v = os.environ.get(name)
    if not v:
        raise RuntimeError(f"missing env {name}")
    return v


def run() -> int:
    api = _need("GITEA_API")
    repo = _need("GITEA_REPOSITORY")
    index = _need("PR_INDEX")
    token = _need("PRAGENT_BOT_TOKEN")
    ollama_url = _need("OLLAMA_URL")
    model = _need("OLLAMA_MODEL")
    title = os.environ.get("PR_TITLE", "")
    body = os.environ.get("PR_BODY", "")
    sha = os.environ.get("PRAGENT_SHA", "")
    max_tokens = int(os.environ.get("OLLAMA_MAX_TOKENS", "6000"))
    max_chars = int(os.environ.get("DIFF_MAX_CHARS", "150000"))

    try:
        diff, truncated, _orig = fetch_pr_diff(api, repo, index, token, max_chars)
        if not diff.strip():
            post_review(api, repo, index, token, format_review_body("No diff content to review.", model, sha))
            return 0
        user_prompt = build_user_prompt(title, body, diff)
        findings = call_model(ollama_url, model, SYSTEM_PROMPT, user_prompt, max_tokens)
        post_review(api, repo, index, token, format_review_body(findings, model, sha))
    except Exception as e:  # fail-open
        try:
            post_review(api, repo, index, token, format_review_body(f"⚠️ AI review failed: {e}", model, sha))
        except Exception as e2:
            print(f"pragent: could not post failure note: {e2}", file=sys.stderr)
        print(f"pragent: review failed: {e}", file=sys.stderr)
    return 0


if __name__ == "__main__":
    sys.exit(run())