Merge agent-A: move feedback*.py from WIP into tree
This commit is contained in:
Marcos
@@ -0,0 +1,356 @@
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"""pragent pilot — feedback storage.
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A thin SQLite layer that records every bot review comment + the reactions /
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thread-state / replies it accumulates over time. Powers the daily analysis
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that produces suggested addenda for `.pr-review.json:instructions` and
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`PRAGENT_ADDITIONAL_CONTEXT_URL` (see `feedback_analyze.py`).
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Why SQLite: stdlib, no extra deps in the container, single writer (the
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webhook server is one process per pod). Mount at `/data/feedback.db`
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via the `feedback-data` PVC.
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Schema (idempotent — safe to call `init` at every boot):
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review(repo, pr, head_sha, body_comment_id, posted_at, review_id_gitea)
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inline_finding(review_id → review.id, repo, pr, path, line,
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severity, problem, fix, suggestion,
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comment_id, posthash UNIQUE, posted_at)
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reaction(comment_id, user, content, created_at,
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PRIMARY KEY (comment_id, user, content))
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thread_state(finding_id → inline_finding.id, resolved, checked_at,
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PRIMARY KEY (finding_id))
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reply(finding_id → inline_finding.id, author, body, created_at,
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PRIMARY KEY (finding_id, created_at))
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`posthash` is a short hash of (path|line|severity|first 80 chars of problem).
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It survives across reviews of the same finding on the same line — same
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finding on PR #5 and PR #12 of the same file de-duplicate, so the daily
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analyzer can count votes across reviews instead of one-at-a-time.
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Everything is best-effort. The webhook server never aborts a review
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because the feedback DB had a hiccup — `record_*` functions log and
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swallow.
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"""
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from __future__ import annotations
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import hashlib
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import logging
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import sqlite3
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import time
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from typing import Iterable, Optional
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log = logging.getLogger("pragent.feedback")
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# ---------------------------------------------------------------------------
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# Schema
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# ---------------------------------------------------------------------------
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_SCHEMA = """
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CREATE TABLE IF NOT EXISTS review (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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repo TEXT NOT NULL,
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pr INTEGER NOT NULL,
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head_sha TEXT NOT NULL,
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review_id_gitea INTEGER,
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body_comment_id INTEGER,
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posted_at INTEGER NOT NULL
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);
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CREATE INDEX IF NOT EXISTS review_repo_pr ON review(repo, pr);
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CREATE TABLE IF NOT EXISTS inline_finding (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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review_id INTEGER REFERENCES review(id),
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repo TEXT NOT NULL,
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pr INTEGER NOT NULL,
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path TEXT NOT NULL,
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line INTEGER NOT NULL,
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severity TEXT NOT NULL,
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problem TEXT NOT NULL,
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fix TEXT,
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suggestion TEXT,
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comment_id INTEGER,
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posthash TEXT NOT NULL,
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posted_at INTEGER NOT NULL
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);
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CREATE INDEX IF NOT EXISTS inline_finding_posthash_idx ON inline_finding(posthash);
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CREATE INDEX IF NOT EXISTS inline_finding_repo_pr ON inline_finding(repo, pr);
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CREATE INDEX IF NOT EXISTS inline_finding_posthash ON inline_finding(posthash);
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CREATE TABLE IF NOT EXISTS reaction (
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comment_id INTEGER NOT NULL,
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user TEXT NOT NULL,
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content TEXT NOT NULL,
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created_at INTEGER NOT NULL,
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PRIMARY KEY (comment_id, user, content)
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);
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CREATE INDEX IF NOT EXISTS reaction_comment ON reaction(comment_id);
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CREATE TABLE IF NOT EXISTS thread_state (
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finding_id INTEGER NOT NULL REFERENCES inline_finding(id),
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resolved INTEGER NOT NULL,
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checked_at INTEGER NOT NULL,
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PRIMARY KEY (finding_id)
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);
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CREATE TABLE IF NOT EXISTS reply (
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finding_id INTEGER NOT NULL REFERENCES inline_finding(id),
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author TEXT NOT NULL,
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body TEXT NOT NULL,
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created_at INTEGER NOT NULL,
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PRIMARY KEY (finding_id, created_at)
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);
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"""
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def init(db_path: str) -> sqlite3.Connection:
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"""Open (or create) the DB, ensure schema. Returns a Connection."""
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conn = sqlite3.connect(db_path)
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conn.row_factory = sqlite3.Row # so callers can use row["name"]
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conn.executescript(_SCHEMA)
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conn.commit()
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return conn
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# ---------------------------------------------------------------------------
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# Posthash — cross-review finding dedup
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# ---------------------------------------------------------------------------
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def posthash(path: str, line: int, severity: str, problem: str) -> str:
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"""Short stable hash of the finding's identifying triple + a problem
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fingerprint. Designed so two reviews of the SAME finding (same file,
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same line, same severity, same core complaint) collapse to one row —
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reactions across PRs aggregate.
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`line` is the post-change (RIGHT-side) line — the agent anchors on it
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and so does this hash. Different lines = different finding, by design.
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`severity` participates because "this is a CRITICAL bug" and "this is a
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LOW nitpick" at the same line on the same problem text are different
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signals to learn from.
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"""
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h = hashlib.sha256()
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h.update(f"{path}\n".encode())
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h.update(f"{line}\n".encode())
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h.update(f"{severity.upper()}\n".encode())
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h.update(problem[:80].strip().lower().encode())
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return h.hexdigest()[:16]
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# ---------------------------------------------------------------------------
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# Write helpers — all best-effort. Log + swallow.
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# ---------------------------------------------------------------------------
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def record_review(
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conn: sqlite3.Connection,
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*,
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repo: str,
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pr: int,
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head_sha: str,
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review_id_gitea: Optional[int] = None,
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body_comment_id: Optional[int] = None,
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posted_at: Optional[int] = None,
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) -> Optional[int]:
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"""Insert a review row. Returns the new row id, or None on failure."""
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try:
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cur = conn.execute(
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"INSERT INTO review(repo, pr, head_sha, review_id_gitea, body_comment_id, posted_at) "
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"VALUES(?,?,?,?,?,?)",
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(repo, pr, head_sha, review_id_gitea, body_comment_id, posted_at or int(time.time())),
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)
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conn.commit()
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return cur.lastrowid
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except Exception as e:
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log.warning("record_review failed: %s", e)
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return None
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def record_inline_finding(
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conn: sqlite3.Connection,
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*,
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review_id: Optional[int],
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repo: str,
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pr: int,
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path: str,
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line: int,
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severity: str,
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problem: str,
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fix: str = "",
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suggestion: str = "",
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comment_id: Optional[int] = None,
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posted_at: Optional[int] = None,
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) -> Optional[int]:
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"""Insert an inline-finding row, deduped on posthash.
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`comment_id` is filled in by the harvester when it discovers the
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Gitea-assigned comment id for this finding. The post path returns the
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`review_id` only; the inline ids come from a follow-up fetch.
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"""
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ph = posthash(path, line, severity, problem)
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ts = posted_at or int(time.time())
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# Every call inserts a fresh row. Aggregation by posthash is the
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# caller's job — see `findings_with_votes` which GROUP BYs posthash.
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# Letting each finding be its own row means reactions on different
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# comment_ids across multiple PR reviews are not lost when one of
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# those comment_ids becomes stale.
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try:
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cur = conn.execute(
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"INSERT INTO inline_finding(review_id, repo, pr, path, line, severity, "
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"problem, fix, suggestion, comment_id, posthash, posted_at) "
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"VALUES(?,?,?,?,?,?,?,?,?,?,?,?)",
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(review_id, repo, pr, path, line, severity, problem, fix, suggestion,
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comment_id, ph, ts),
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)
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conn.commit()
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return cur.lastrowid
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except Exception as e:
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log.warning("record_inline_finding failed: %s", e)
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return None
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def record_reaction(
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conn: sqlite3.Connection,
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*,
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comment_id: int,
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user: str,
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content: str,
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created_at: Optional[int] = None,
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) -> bool:
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"""Upsert one reaction. PK = (comment_id, user, content)."""
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try:
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conn.execute(
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"INSERT OR IGNORE INTO reaction(comment_id, user, content, created_at) "
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"VALUES(?,?,?,?)",
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(comment_id, user, content, created_at or int(time.time())),
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)
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conn.commit()
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return True
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except Exception as e:
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log.warning("record_reaction failed: %s", e)
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return False
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def record_thread_state(
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conn: sqlite3.Connection,
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*,
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finding_id: int,
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resolved: bool,
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checked_at: Optional[int] = None,
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) -> bool:
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"""Upsert the latest thread-state check."""
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try:
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conn.execute(
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"INSERT INTO thread_state(finding_id, resolved, checked_at) "
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"VALUES(?,?,?) "
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"ON CONFLICT(finding_id) DO UPDATE SET "
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" resolved = excluded.resolved, checked_at = excluded.checked_at",
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(finding_id, 1 if resolved else 0, checked_at or int(time.time())),
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)
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conn.commit()
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return True
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except Exception as e:
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log.warning("record_thread_state failed: %s", e)
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return False
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def record_reply(
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conn: sqlite3.Connection,
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*,
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finding_id: int,
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author: str,
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body: str,
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created_at: int,
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) -> bool:
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"""Insert one reply. PK includes created_at → re-imports are idempotent."""
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try:
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conn.execute(
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"INSERT OR IGNORE INTO reply(finding_id, author, body, created_at) "
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"VALUES(?,?,?,?)",
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(finding_id, author, body, created_at),
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)
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conn.commit()
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return True
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except Exception as e:
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log.warning("record_reply failed: %s", e)
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return False
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# ---------------------------------------------------------------------------
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# Read helpers — for the analyzer
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# ---------------------------------------------------------------------------
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def findings_with_votes(
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conn: sqlite3.Connection,
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*,
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repo: Optional[str] = None,
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since_ts: Optional[int] = None,
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) -> Iterable[sqlite3.Row]:
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"""Stream every inline finding with rolled-up votes attached.
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Joins:
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inline_finding ◀ reaction (count by content)
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inline_finding ◀ thread_state (latest resolved flag)
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inline_finding ◀ reply (count + concatenation of bodies for negation
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pattern matching)
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Yielded rows expose:
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id, repo, pr, path, line, severity, problem, fix, suggestion,
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comment_id, posthash, posted_at,
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upvotes INT, downvotes INT,
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resolved INT (0/1/NULL),
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reply_count INT,
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reply_bodies TEXT ('\\n\\n'-joined for substring match),
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review_posted_at INT
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"""
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where = []
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params: list = []
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if repo:
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where.append("f.repo = ?")
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params.append(repo)
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if since_ts is not None:
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where.append("COALESCE(r.posted_at, f.posted_at) >= ?")
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params.append(since_ts)
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where_sql = ("WHERE " + " AND ".join(where)) if where else ""
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sql = f"""
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SELECT
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f.posthash AS id, -- alias for compat — every row IS an aggregated posthash
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f.repo, MAX(f.pr) AS pr, f.path, f.line, MAX(f.severity) AS severity,
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MAX(f.problem) AS problem, MAX(f.fix) AS fix, MAX(f.suggestion) AS suggestion,
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MAX(f.comment_id) AS comment_id, f.posthash, MAX(f.posted_at) AS posted_at,
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COUNT(*) AS occurrences,
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r.posted_at AS review_posted_at,
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COALESCE(SUM(CASE WHEN rct.content = '+1' THEN 1 ELSE 0 END), 0) AS upvotes,
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COALESCE(SUM(CASE WHEN rct.content = '-1' THEN 1 ELSE 0 END), 0) AS downvotes,
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MAX(ts.resolved) AS resolved,
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COALESCE((SELECT COUNT(*) FROM reply WHERE finding_id IN (SELECT id FROM inline_finding WHERE posthash = f.posthash AND repo = f.repo AND path = f.path AND line = f.line)), 0) AS reply_count,
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COALESCE((SELECT GROUP_CONCAT(body, char(10)||char(10)) FROM reply WHERE finding_id IN (SELECT id FROM inline_finding WHERE posthash = f.posthash AND repo = f.repo AND path = f.path AND line = f.line)), '') AS reply_bodies
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FROM inline_finding f
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LEFT JOIN review r ON r.id = f.review_id
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LEFT JOIN reaction rct ON rct.comment_id = f.comment_id
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LEFT JOIN thread_state ts ON ts.finding_id = f.id
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{where_sql}
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GROUP BY f.posthash, f.repo, f.path, f.line
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ORDER BY posted_at DESC
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"""
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return conn.execute(sql, params)
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def known_posthashes_for_repo(conn: sqlite3.Connection, repo: str) -> set[str]:
|
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"""For the harvester: which findings on this repo have already been
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recorded? Used to skip re-fetching reactions we already harvested this
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round."""
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return {
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row[0]
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for row in conn.execute(
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"SELECT DISTINCT posthash FROM inline_finding WHERE repo = ?", (repo,)
|
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).fetchall()
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}
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def comment_ids_for_finding(conn: sqlite3.Connection, posthash: str) -> Optional[int]:
|
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"""Return the current Gitea comment_id for an existing finding (used to
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harvest votes for findings the harvester discovers on a brand-new PR that
|
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ALSO has older bot comments on prior PRs)."""
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row = conn.execute(
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"SELECT comment_id FROM inline_finding WHERE posthash = ?", (posthash,)
|
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).fetchone()
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return row[0] if row else None
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@@ -0,0 +1,419 @@
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"""pragent pilot — daily feedback analyzer.
|
||||
|
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Reads `feedback.db` (written by `feedback_harvest.py`) and produces a
|
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markdown report that:
|
||||
|
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1. Ranks inline findings by **net false-positive score** (downvotes +
|
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unresolved + negation-phrase replies − upvotes − resolved). Top of
|
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this list = "the bot has been wrong about this repeatedly". These
|
||||
are the candidates that *might* belong in the per-repo
|
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`.pr-review.json:instructions` addendum.
|
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2. Ranks findings by **net acceptance** — repeated 👍 / resolution =
|
||||
"the bot's framing here is genuinely useful". These can be promoted
|
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to the shared `architecture.md` so they don't have to be re-derived
|
||||
every PR.
|
||||
3. Reports a **restraint metric** — for every PR where the bot posted
|
||||
zero findings, count how often a human reviewer also posted zero
|
||||
substantive review comments. When the bot is loud on clean code,
|
||||
that's a false-positive rate we can act on (DoorDash lesson:
|
||||
"excessive noise on clean code is its own failure mode").
|
||||
4. Reports a **case-review queue** — every disagreement case (a
|
||||
downvote, unresolved, or a reply matching `FALSE_POSITIVE_PHRASES`)
|
||||
is listed in full so a human can re-read the original PR and decide
|
||||
if the finding was right or wrong.
|
||||
|
||||
Output is plain markdown so it can be posted as a Gitea issue / comment
|
||||
without rendering work. Designed to be reviewed by a human, not auto-
|
||||
applied — per the DoorDash pattern, every material change to model /
|
||||
prompt / context goes through a benchmark gate first; this report IS
|
||||
that gate (or, more precisely, the queue feeding the gate).
|
||||
|
||||
Never raises. A bad DB / no data → returns a friendly empty-state report.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import sqlite3
|
||||
from collections import defaultdict
|
||||
from datetime import datetime, timezone
|
||||
from typing import Optional
|
||||
|
||||
import feedback
|
||||
from feedback_harvest import (
|
||||
FALSE_POSITIVE_PHRASES,
|
||||
classify_reaction,
|
||||
_is_negation_reply, # noqa: F401 (re-exported for the test suite)
|
||||
)
|
||||
|
||||
log = logging.getLogger("pragent.feedback.analyze")
|
||||
|
||||
# How many findings to surface in each top-list. Capped because the
|
||||
# reports are read by humans; more than 20 per list and they skim.
|
||||
TOP_N = 20
|
||||
|
||||
# Restraint threshold — fraction of "clean" PRs (zero findings) where
|
||||
# the bot produced ANY findings. Above this we recommend `.pr-review.json:
|
||||
# exclude_patterns` or a stricter `severity_threshold`.
|
||||
RESTRAINT_NOISE_THRESHOLD = 0.25
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Helpers
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _net_score(row) -> tuple[int, int]:
|
||||
"""Return (false_positive_score, acceptance_score) for one finding row.
|
||||
|
||||
FP signals: downvotes (+1), unresolved (+1), negation-phrase replies (+2).
|
||||
Acceptance signals: upvotes (+1), resolved (+1).
|
||||
"""
|
||||
fp = 0
|
||||
ac = 0
|
||||
fp += int(row["downvotes"] or 0)
|
||||
fp += 1 if row["resolved"] == 0 else 0 # 0/1/NULL; 0 = unresolved
|
||||
ac += 1 if row["resolved"] == 1 else 0
|
||||
ac += int(row["upvotes"] or 0)
|
||||
if row["reply_bodies"] and _is_negation_reply(row["reply_bodies"]):
|
||||
fp += 2
|
||||
return fp, ac
|
||||
|
||||
|
||||
def _short_problem(problem: str, n: int = 100) -> str:
|
||||
s = (problem or "").strip().replace("\n", " ")
|
||||
return s if len(s) <= n else s[: n - 1] + "…"
|
||||
|
||||
|
||||
def _restraint_stats(conn: sqlite3.Connection) -> dict:
|
||||
"""How often does the bot post findings on PRs that received zero
|
||||
bot findings (= presumably clean)? Looks at `review.findings_total`
|
||||
if present, otherwise counts `inline_finding` per PR.
|
||||
|
||||
NOTE: until `post_inline_review` records `findings_total`, this falls
|
||||
back to "PRs with at least one finding row" which is an underestimate
|
||||
(a bot review with zero findings leaves no row).
|
||||
"""
|
||||
total_prs_with_review = conn.execute(
|
||||
"SELECT COUNT(DISTINCT repo || '#' || pr) FROM review"
|
||||
).fetchone()[0]
|
||||
prs_with_findings = conn.execute(
|
||||
"SELECT COUNT(DISTINCT repo || '#' || pr) FROM inline_finding"
|
||||
).fetchone()[0]
|
||||
if total_prs_with_review == 0:
|
||||
return {"total": 0, "noisy": 0, "ratio": 0.0}
|
||||
# This is currently "PRs where the bot left at least one inline
|
||||
# comment". A precise "findings_total per review" needs
|
||||
# post_inline_review to record it (TODO in the wiring step). Until
|
||||
# then, treat this as a floor: real noise is >= this.
|
||||
return {
|
||||
"total": total_prs_with_review,
|
||||
"noisy": prs_with_findings,
|
||||
"ratio": prs_with_findings / total_prs_with_review,
|
||||
}
|
||||
|
||||
|
||||
def _case_review_queue(conn: sqlite3.Connection, limit: int = 30) -> list[dict]:
|
||||
"""Findings that humans pushed back on — for manual re-review."""
|
||||
rows = feedback.findings_with_votes(conn)
|
||||
cases = []
|
||||
for r in rows:
|
||||
fp_score, _ = _net_score(r)
|
||||
if fp_score <= 0:
|
||||
continue
|
||||
cases.append({
|
||||
"posthash": r["posthash"],
|
||||
"repo": r["repo"],
|
||||
"pr": r["pr"],
|
||||
"path": r["path"],
|
||||
"line": r["line"],
|
||||
"severity": r["severity"],
|
||||
"problem": _short_problem(r["problem"], 200),
|
||||
"fp_score": fp_score,
|
||||
"upvotes": r["upvotes"] or 0,
|
||||
"downvotes": r["downvotes"] or 0,
|
||||
"resolved": r["resolved"],
|
||||
"reply_count": r["reply_count"] or 0,
|
||||
"reply_excerpt": _short_problem(r["reply_bodies"] or "", 200),
|
||||
})
|
||||
cases.sort(key=lambda c: c["fp_score"], reverse=True)
|
||||
return cases[:limit]
|
||||
|
||||
|
||||
def _format_table(headers: list[str], rows: list[list[str]]) -> str:
|
||||
if not rows:
|
||||
return "_none yet_\n"
|
||||
out = ["| " + " | ".join(headers) + " |",
|
||||
"|" + "|".join(["---"] * len(headers)) + "|"]
|
||||
for row in rows:
|
||||
out.append("| " + " | ".join(row) + " |")
|
||||
return "\n".join(out) + "\n"
|
||||
|
||||
|
||||
def _md_escape(s: str) -> str:
|
||||
"""Escape pipes + newlines so the value stays in one table cell."""
|
||||
return (s or "").replace("|", "\\|").replace("\n", " ").strip()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Main report builder
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def analyze(db_path: str, *, since_ts: Optional[int] = None,
|
||||
as_json: bool = False) -> str:
|
||||
"""Build the daily report. Returns a markdown string by default;
|
||||
`as_json=True` returns a structured dict (for tests + dashboards)."""
|
||||
conn = feedback.init(db_path)
|
||||
try:
|
||||
findings = list(feedback.findings_with_votes(conn, since_ts=since_ts))
|
||||
total_findings = len(findings)
|
||||
repo_set = {f["repo"] for f in findings}
|
||||
case_queue = _case_review_queue(conn)
|
||||
restraint = _restraint_stats(conn)
|
||||
|
||||
# Compute scores
|
||||
scored: list[tuple[int, int, sqlite3.Row]] = []
|
||||
for f in findings:
|
||||
fp, ac = _net_score(f)
|
||||
scored.append((fp, ac, f))
|
||||
|
||||
# Top false-positive patterns (sorted by fp score, deduped by posthash).
|
||||
# `occurrences` comes from the inline_finding row — posthash UNIQUE
|
||||
# means a single row can carry a count > 1 (set by record_inline_finding's
|
||||
# ON CONFLICT DO UPDATE).
|
||||
fp_by_hash: dict[str, dict] = {}
|
||||
for fp, ac, f in scored:
|
||||
if fp <= 0:
|
||||
continue
|
||||
ph = f["posthash"]
|
||||
entry = fp_by_hash.setdefault(ph, {
|
||||
"posthash": ph, "fp_score": 0, "ac_score": 0,
|
||||
"repo": f["repo"], "path": f["path"], "line": f["line"],
|
||||
"severity": f["severity"], "problem": f["problem"],
|
||||
"occurrences": f["occurrences"], "upvs": 0, "downs": 0,
|
||||
"resolved_true": 0, "resolved_false": 0,
|
||||
})
|
||||
entry["fp_score"] += fp
|
||||
entry["ac_score"] += ac
|
||||
entry["upvs"] += f["upvotes"] or 0
|
||||
entry["downs"] += f["downvotes"] or 0
|
||||
if f["resolved"] == 1:
|
||||
entry["resolved_true"] += 1
|
||||
elif f["resolved"] == 0:
|
||||
entry["resolved_false"] += 1
|
||||
fp_sorted = sorted(
|
||||
fp_by_hash.values(), key=lambda e: e["fp_score"], reverse=True,
|
||||
)[:TOP_N]
|
||||
|
||||
# Top accepted patterns
|
||||
ac_by_hash: dict[str, dict] = {}
|
||||
for fp, ac, f in scored:
|
||||
if ac <= 0:
|
||||
continue
|
||||
ph = f["posthash"]
|
||||
entry = ac_by_hash.setdefault(ph, {
|
||||
"posthash": ph, "ac_score": 0, "fp_score": 0,
|
||||
"repo": f["repo"], "path": f["path"], "line": f["line"],
|
||||
"severity": f["severity"], "problem": f["problem"],
|
||||
"occurrences": f["occurrences"], "upvs": 0, "downs": 0,
|
||||
"resolved_true": 0,
|
||||
})
|
||||
entry["ac_score"] += ac
|
||||
entry["fp_score"] += fp
|
||||
entry["upvs"] += f["upvotes"] or 0
|
||||
entry["downs"] += f["downvotes"] or 0
|
||||
if f["resolved"] == 1:
|
||||
entry["resolved_true"] += 1
|
||||
ac_sorted = sorted(
|
||||
ac_by_hash.values(), key=lambda e: e["ac_score"], reverse=True,
|
||||
)[:TOP_N]
|
||||
|
||||
# Restraint recommendation
|
||||
if restraint["ratio"] > RESTRAINT_NOISE_THRESHOLD:
|
||||
restraint_msg = (
|
||||
f"⚠️ Bot posted findings on **{restraint['ratio']:.0%}** of "
|
||||
f"reviewed PRs ({restraint['noisy']} / {restraint['total']}). "
|
||||
f"Above the {RESTRAINT_NOISE_THRESHOLD:.0%} threshold — "
|
||||
"consider raising `.pr-review.json:severity_threshold` to "
|
||||
"`medium` or `high` for noisy repos, or adding "
|
||||
"`patterns.deny` to skip stylistic-only findings."
|
||||
)
|
||||
else:
|
||||
restraint_msg = (
|
||||
f"✅ Bot stayed quiet on **{1 - restraint['ratio']:.0%}** of "
|
||||
f"reviewed PRs ({restraint['total'] - restraint['noisy']} / "
|
||||
f"{restraint['total']}). Restraint OK."
|
||||
)
|
||||
|
||||
if as_json:
|
||||
return json.dumps({
|
||||
"total_findings": total_findings,
|
||||
"repos_seen": sorted(repo_set),
|
||||
"restraint": restraint,
|
||||
"top_false_positive": fp_sorted,
|
||||
"top_accepted": ac_sorted,
|
||||
"case_review_queue": case_queue,
|
||||
"restraint_msg": restraint_msg,
|
||||
}, indent=2)
|
||||
|
||||
# Markdown
|
||||
ts_str = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M UTC")
|
||||
out = [f"# pragent feedback report — {ts_str}", ""]
|
||||
out.append(f"- **findings analyzed**: {total_findings}")
|
||||
out.append(f"- **repos with feedback**: {len(repo_set)} "
|
||||
f"({', '.join(sorted(repo_set))})")
|
||||
out.append(f"- **case-review queue**: {len(case_queue)} disagreement(s)")
|
||||
out.append("")
|
||||
out.append("## Restraint")
|
||||
out.append("")
|
||||
out.append(restraint_msg)
|
||||
out.append("")
|
||||
out.append("> DoorDash rule (2026-07-06): *excessive noise on clean "
|
||||
"code is its own failure mode*. `severity_threshold` + "
|
||||
"`patterns.deny` are the knobs that dial restraint.")
|
||||
out.append("")
|
||||
|
||||
out.append(f"## Top {len(fp_sorted)} false-positive candidates")
|
||||
out.append("")
|
||||
out.append("Aggregated by `posthash` (path:line:severity:problem). "
|
||||
"Sort key = downvotes + unresolved + negation-phrase replies "
|
||||
"− upvotes − resolved.")
|
||||
out.append("")
|
||||
rows = []
|
||||
for e in fp_sorted:
|
||||
rows.append([
|
||||
str(e["fp_score"]),
|
||||
f"`{_md_escape(e['repo'])}`",
|
||||
f"`{_md_escape(e['path'])}:{e['line']}`",
|
||||
e["severity"],
|
||||
_md_escape(_short_problem(e["problem"])),
|
||||
f"👍{e['upvs']} 👎{e['downs']}",
|
||||
f"✅{e['resolved_true']} ❌{e['resolved_false']}",
|
||||
str(e["occurrences"]),
|
||||
])
|
||||
out.append(_format_table(
|
||||
["FP", "repo", "path:line", "sev", "problem",
|
||||
"votes", "resolved", "seen"],
|
||||
rows,
|
||||
))
|
||||
out.append("")
|
||||
out.append("_Review each row before adding it to "
|
||||
"`.pr-review.json:instructions`. Human reactions are NOT "
|
||||
"ground truth (DoorDash, 2026-07-06: authors accept/reject "
|
||||
"for workflow reasons) — re-read the PR before acting._")
|
||||
out.append("")
|
||||
|
||||
out.append(f"## Top {len(ac_sorted)} accepted patterns")
|
||||
out.append("")
|
||||
out.append("Aggregated by posthash. Sort key = upvotes + resolved − "
|
||||
"downvotes − unresolved − negation-phrase replies.")
|
||||
out.append("")
|
||||
rows = []
|
||||
for e in ac_sorted:
|
||||
rows.append([
|
||||
str(e["ac_score"]),
|
||||
f"`{_md_escape(e['repo'])}`",
|
||||
f"`{_md_escape(e['path'])}:{e['line']}`",
|
||||
e["severity"],
|
||||
_md_escape(_short_problem(e["problem"])),
|
||||
f"👍{e['upvs']} 👎{e['downs']}",
|
||||
f"✅{e['resolved_true']}",
|
||||
str(e["occurrences"]),
|
||||
])
|
||||
out.append(_format_table(
|
||||
["AC", "repo", "path:line", "sev", "problem",
|
||||
"votes", "resolved", "seen"],
|
||||
rows,
|
||||
))
|
||||
out.append("")
|
||||
out.append("_Promote widely-accepted patterns into the shared "
|
||||
"`architecture.md` on Nexus raw-hosted (or the per-repo "
|
||||
"`additional_context_urls`). These become part of the "
|
||||
"prompt-cached prefix → ~0 marginal cost on step 2+._")
|
||||
out.append("")
|
||||
|
||||
out.append(f"## Case-review queue ({len(case_queue)})")
|
||||
out.append("")
|
||||
if not case_queue:
|
||||
out.append("_No disagreements recorded yet. Once humans start "
|
||||
"reacting 👎 / leaving replies / not resolving bot "
|
||||
"comments, cases will appear here._")
|
||||
else:
|
||||
out.append("Each row needs a human to re-read the original PR and "
|
||||
"decide: was the bot right? If not, draft an "
|
||||
"`instructions` addendum or a `patterns.deny` rule.")
|
||||
out.append("")
|
||||
for c in case_queue:
|
||||
url = (
|
||||
f"https://gitea.marcospaulo.dev.br/{c['repo']}/pulls/"
|
||||
f"{c['pr']}/files#r{c['posthash']}"
|
||||
)
|
||||
out.append(f"### FP={c['fp_score']} · {c['repo']}#{c['pr']}")
|
||||
out.append(
|
||||
f"- file: `{_md_escape(c['path'])}:{c['line']}` · "
|
||||
f"severity: `{c['severity']}`",
|
||||
)
|
||||
out.append(f"- problem: {_md_escape(c['problem'])}")
|
||||
out.append(
|
||||
f"- signals: 👍{c['upvotes']} 👎{c['downvotes']} · "
|
||||
f"resolved={c['resolved']} · replies={c['reply_count']}",
|
||||
)
|
||||
if c["reply_excerpt"]:
|
||||
out.append(
|
||||
f"- last reply: {_md_escape(c['reply_excerpt'])}",
|
||||
)
|
||||
out.append(f"- posthash: `{c['posthash']}`")
|
||||
out.append("")
|
||||
|
||||
out.append("## Where this report goes")
|
||||
out.append("")
|
||||
out.append("- **Per-repo actions** (`.pr-review.json:instructions`, "
|
||||
"`patterns.deny`, `severity_threshold`): edit the file on "
|
||||
"`main` via a regular PR. The next PR review picks up the "
|
||||
"change automatically.")
|
||||
out.append("- **Cross-repo actions** (shared house-rules): update the "
|
||||
"`PRAGENT_ADDITIONAL_CONTEXT_URL` document on Nexus "
|
||||
"raw-hosted (`canalhandia/architecture.md` etc).")
|
||||
out.append("- **Benchmark gate** (DoorDash pattern): before changing "
|
||||
"the model / prompt / context window, replay this report "
|
||||
"against the labeled `posthash` corpus. If a candidate "
|
||||
"addendum flips ≥ 1 currently-accepted finding into "
|
||||
"false-positive, drop it.")
|
||||
out.append("")
|
||||
out.append(f"_Generated from `{db_path}` by `feedback_analyze.py`._")
|
||||
return "\n".join(out)
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# CLI
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def main() -> int:
|
||||
p = argparse.ArgumentParser(description="Build the daily feedback report.")
|
||||
p.add_argument("--db", default=os.environ.get(
|
||||
"PRAGENT_FEEDBACK_DB", "/data/feedback.db",
|
||||
))
|
||||
p.add_argument("--since", type=int, default=None,
|
||||
help="Unix timestamp; only include findings posted since")
|
||||
p.add_argument("--json", action="store_true",
|
||||
help="Emit structured JSON instead of markdown")
|
||||
p.add_argument("--out", default="-",
|
||||
help="Write to this path instead of stdout ('-' = stdout)")
|
||||
args = p.parse_args()
|
||||
|
||||
out = analyze(args.db, since_ts=args.since, as_json=args.json)
|
||||
if args.out == "-":
|
||||
print(out)
|
||||
else:
|
||||
with open(args.out, "w") as f:
|
||||
f.write(out)
|
||||
print(f"wrote {args.out}", file=sys.stderr)
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import sys
|
||||
raise SystemExit(main())
|
||||
@@ -0,0 +1,386 @@
|
||||
"""pragent pilot — feedback harvester.
|
||||
|
||||
For each PR the webhook server is about to review, walk back through the
|
||||
Gitea-side state of every bot comment from every prior review on that PR
|
||||
and record:
|
||||
- reactions on the review body + on each inline comment
|
||||
- thread-resolved state (Gitea's `resolver` field; non-empty = resolved)
|
||||
- replies (issue-comments with `review_comment_id` matching ours)
|
||||
- the bot's own findings_count + inline_count per review (for the
|
||||
restraint metric)
|
||||
|
||||
Everything is best-effort. A single 404 or 5xx is logged and skipped — we
|
||||
must never abort a review because the feedback DB had a hiccup.
|
||||
|
||||
The harvester is intentionally separate from `review_pr` so it can be
|
||||
called independently (e.g. by the daily analyzer's "backfill" mode) and
|
||||
tested in isolation against a mocked Gitea client.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import re
|
||||
import time
|
||||
import urllib.parse
|
||||
import urllib.request
|
||||
from typing import Optional
|
||||
|
||||
import ai_review # used as ai_review.gitea_get(...) so test mocks land on the binding
|
||||
|
||||
from feedback import (
|
||||
init,
|
||||
record_inline_finding,
|
||||
record_reaction,
|
||||
record_reply,
|
||||
record_review,
|
||||
record_thread_state,
|
||||
posthash,
|
||||
)
|
||||
|
||||
log = logging.getLogger("pragent.feedback.harvest")
|
||||
|
||||
# Reviewer identity — only collect feedback on comments authored by us.
|
||||
# Avoids harvesting reactions on human comments (which we never want to
|
||||
# count toward "bot usefulness").
|
||||
REVIEWER_LOGIN = "pragent-bot"
|
||||
|
||||
# Reactions content tokens Gitea uses. We track +1 / -1 explicitly; the
|
||||
# others are stored as-is so the analyzer can mine them (👀 eyes,
|
||||
# laugh, hooray, confused, heart, rocket, …) without hardcoding a list
|
||||
# that drifts across Gitea versions.
|
||||
POSITIVE_REACTIONS = {"+1", "heart", "hooray", "laugh", "rocket"}
|
||||
NEGATIVE_REACTIONS = {"-1", "confused"}
|
||||
# Note: Gitea's `eyes` reaction (👀) means "I'm watching" — not approval
|
||||
# or disapproval. Treated as neutral by the analyzer.
|
||||
|
||||
# Phrases that, in a reply, indicate the author thinks the bot's finding
|
||||
# was wrong. Casing + punctuation ignored; substring match is good enough
|
||||
# (false positives in the analyzer cost a human minute; false negatives
|
||||
# hide regressions).
|
||||
FALSE_POSITIVE_PHRASES = (
|
||||
"false positive", "not actually", "this is fine", "this is intentional",
|
||||
"not a bug", "intentional", "wrong here", "isn't actually",
|
||||
"is not actually", "don't think this is", "i disagree", "this isn't right",
|
||||
"this is correct", "this is expected", "by design", "this is by design",
|
||||
)
|
||||
|
||||
# Gitea review-comment payload includes a 'body' field that may carry our
|
||||
# sha marker + severity header. We extract severity + path/line from it
|
||||
# as a fallback when the finding wasn't already seeded at post-time (old
|
||||
# reviews before feedback.py existed).
|
||||
SEV_RE = re.compile(r"\*\*\[(CRITICAL|HIGH|MEDIUM|LOW|INFO)\]\*\*", re.IGNORECASE)
|
||||
PATH_LINE_RE = re.compile(r"`([^?:\n]+?):(\d+)`")
|
||||
SHA_MARKER_RE = re.compile(r"<!--\s*pragent:sha=([0-9a-f]+)\s*-->", re.IGNORECASE)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Low-level HTTP — tolerant JSON parse (Gitea sometimes returns `null` where
|
||||
# we expect `[]`, e.g. reactions on a fresh comment)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _gitea_get_json(api: str, repo: str, path: str, token: str) -> tuple[int, object]:
|
||||
status, raw = ai_review.gitea_get(api, repo, path, token)
|
||||
if status != 200:
|
||||
return status, None
|
||||
try:
|
||||
return status, json.loads(raw.decode("utf-8", errors="replace"))
|
||||
except (json.JSONDecodeError, ValueError):
|
||||
return status, None
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Parse helpers
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _parse_severity(body: str) -> str:
|
||||
m = SEV_RE.search(body or "")
|
||||
return m.group(1).upper() if m else "INFO"
|
||||
|
||||
|
||||
def _parse_path_line(body: str) -> tuple[Optional[str], Optional[int]]:
|
||||
m = PATH_LINE_RE.search(body or "")
|
||||
if not m:
|
||||
return None, None
|
||||
path = m.group(1).strip()
|
||||
try:
|
||||
return path, int(m.group(2))
|
||||
except ValueError:
|
||||
return path, None
|
||||
|
||||
|
||||
def _parse_sha(body: str) -> Optional[str]:
|
||||
m = SHA_MARKER_RE.search(body or "")
|
||||
return m.group(1) if m else None
|
||||
|
||||
|
||||
def _is_negation_reply(body: str) -> bool:
|
||||
if not body:
|
||||
return False
|
||||
norm = body.lower()
|
||||
return any(p in norm for p in FALSE_POSITIVE_PHRASES)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Reaction classification (cheap, used by the analyzer — not the harvester
|
||||
# itself)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def classify_reaction(content: str) -> str:
|
||||
"""Bucket a reaction into 'positive', 'negative', or 'neutral'."""
|
||||
c = (content or "").strip().lower()
|
||||
if c in POSITIVE_REACTIONS:
|
||||
return "positive"
|
||||
if c in NEGATIVE_REACTIONS:
|
||||
return "negative"
|
||||
return "neutral"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Main harvest entry
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def harvest_for_pr(
|
||||
*,
|
||||
api: str,
|
||||
token: str,
|
||||
repo: str,
|
||||
pr_index: int,
|
||||
db_path: str,
|
||||
page_size: int = 50,
|
||||
) -> dict:
|
||||
"""Walk every bot-authored review on the given PR and record reactions
|
||||
+ thread state + replies. Returns a stats dict for logging.
|
||||
|
||||
`db_path` is the SQLite file path (env: `PRAGENT_FEEDBACK_DB`,
|
||||
typically `/data/feedback.db` mounted via the `feedback-data` PVC).
|
||||
"""
|
||||
conn = init(db_path)
|
||||
stats = {
|
||||
"reviews_seen": 0, "findings_seen": 0,
|
||||
"reactions_recorded": 0, "thread_states_recorded": 0,
|
||||
"replies_recorded": 0, "errors": 0,
|
||||
}
|
||||
|
||||
try:
|
||||
# 1. List every review on the PR (paginated, but PRs rarely have >page_size)
|
||||
status, payload = _gitea_get_json(
|
||||
api, repo, f"pulls/{pr_index}/reviews?per_page={page_size}", token,
|
||||
)
|
||||
if status != 200 or not isinstance(payload, list):
|
||||
log.info("harvest: reviews list failed status=%d", status)
|
||||
stats["errors"] += 1
|
||||
return stats
|
||||
|
||||
for rev in payload:
|
||||
user = (rev.get("user") or {}).get("login", "")
|
||||
if user != REVIEWER_LOGIN:
|
||||
continue
|
||||
stats["reviews_seen"] += 1
|
||||
|
||||
review_id_gitea = rev.get("id")
|
||||
head_sha = rev.get("commit_id", "")
|
||||
review_body = rev.get("body", "") or ""
|
||||
body_sha = _parse_sha(review_body)
|
||||
# Trust the sha marker inside the body — Gitea's commit_id field is
|
||||
# for the LAST commit, not necessarily the reviewed head. If we
|
||||
# can't find a marker, fall back to commit_id.
|
||||
effective_sha = body_sha or head_sha
|
||||
created_at = _parse_iso_ts(rev.get("created_at", ""))
|
||||
|
||||
db_review_id = record_review(
|
||||
conn, repo=repo, pr=pr_index, head_sha=effective_sha,
|
||||
review_id_gitea=review_id_gitea,
|
||||
posted_at=created_at,
|
||||
)
|
||||
|
||||
# 2. Inline comments for this review
|
||||
if review_id_gitea is None:
|
||||
continue
|
||||
rstatus, rpayload = _gitea_get_json(
|
||||
api, repo, f"pulls/{pr_index}/reviews/{review_id_gitea}/comments",
|
||||
token,
|
||||
)
|
||||
if rstatus != 200 or not isinstance(rpayload, list):
|
||||
stats["errors"] += 1
|
||||
continue
|
||||
|
||||
for ic in rpayload:
|
||||
ic_id = ic.get("id")
|
||||
if ic_id is None:
|
||||
continue
|
||||
ic_body = ic.get("body", "") or ""
|
||||
ic_path = ic.get("path")
|
||||
ic_line = ic.get("position") or ic.get("line")
|
||||
ic_severity = _parse_severity(ic_body)
|
||||
# Fall back to body parse when Gitea didn't echo path/line
|
||||
if not ic_path or not ic_line:
|
||||
bp, bl = _parse_path_line(ic_body)
|
||||
ic_path = ic_path or bp
|
||||
ic_line = ic_line or bl
|
||||
|
||||
if not ic_path or not ic_line:
|
||||
log.info(
|
||||
"harvest: inline %s missing path/line, skipping", ic_id,
|
||||
)
|
||||
continue
|
||||
|
||||
finding_id = record_inline_finding(
|
||||
conn, review_id=db_review_id, repo=repo, pr=pr_index,
|
||||
path=ic_path, line=ic_line, severity=ic_severity,
|
||||
problem=_strip_severity_header(ic_body),
|
||||
fix="", suggestion="",
|
||||
comment_id=ic_id,
|
||||
posted_at=created_at,
|
||||
)
|
||||
stats["findings_seen"] += 1
|
||||
if finding_id is None:
|
||||
continue
|
||||
|
||||
# 3. Reactions on the inline comment
|
||||
react_status, react_payload = _gitea_get_json(
|
||||
api, repo, f"issues/comments/{ic_id}/reactions", token,
|
||||
)
|
||||
if react_status == 200 and isinstance(react_payload, list):
|
||||
for r in react_payload:
|
||||
ruser = (r.get("user") or {}).get("login", "") or "?"
|
||||
rcontent = (r.get("content") or "").strip()
|
||||
if not rcontent:
|
||||
continue
|
||||
if record_reaction(
|
||||
conn, comment_id=ic_id, user=ruser,
|
||||
content=rcontent,
|
||||
created_at=_parse_iso_ts(r.get("created_at", "")),
|
||||
):
|
||||
stats["reactions_recorded"] += 1
|
||||
|
||||
# 4. Thread state (Gitea's `resolver` field on the inline
|
||||
# comment). Non-empty string = resolved.
|
||||
resolver = (ic.get("resolver") or "").strip()
|
||||
if ic.get("resolver") is not None: # field present, even if ""
|
||||
record_thread_state(
|
||||
conn, finding_id=finding_id,
|
||||
resolved=bool(resolver),
|
||||
)
|
||||
stats["thread_states_recorded"] += 1
|
||||
|
||||
# 5. Replies on this review (issue-comments whose
|
||||
# `review_comment_id` points at one of our inline comments).
|
||||
# Some Gitea versions don't expose `review_comment_id` on the
|
||||
# issue-comment endpoint — in that case `replies` stays
|
||||
# empty; we degrade gracefully.
|
||||
try:
|
||||
_harvest_replies(
|
||||
api=api, repo=repo, token=token,
|
||||
pr_index=pr_index, review_id=review_id_gitea,
|
||||
inline_comments=rpayload, conn=conn,
|
||||
stats=stats,
|
||||
)
|
||||
except Exception as e:
|
||||
log.info("harvest: replies fetch failed: %s", e)
|
||||
stats["errors"] += 1
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
return stats
|
||||
|
||||
|
||||
def _harvest_replies(
|
||||
*, api: str, repo: str, token: str, pr_index: int,
|
||||
review_id: int, inline_comments: list, conn, stats: dict,
|
||||
) -> None:
|
||||
"""Fetch issue comments on this PR; record those whose
|
||||
`review_comment_id` matches one of our inline comment IDs.
|
||||
Gitea 1.26 doesn't include that field — we fall back to fetching each
|
||||
inline comment individually via `issues/comments/{id}` (does include
|
||||
the field) only if the bulk fetch is empty.
|
||||
"""
|
||||
inline_ids = {c.get("id") for c in inline_comments if c.get("id") is not None}
|
||||
if not inline_ids:
|
||||
return
|
||||
|
||||
status, payload = _gitea_get_json(
|
||||
api, repo, f"issues/{pr_index}/comments?per_page=100", token,
|
||||
)
|
||||
if status != 200 or not isinstance(payload, list):
|
||||
return
|
||||
|
||||
# Build mapping inline_id -> finding_id (one SELECT instead of N)
|
||||
rows = conn.execute(
|
||||
"SELECT comment_id, id FROM inline_finding WHERE comment_id IN ("
|
||||
+ ",".join("?" * len(inline_ids)) + ")",
|
||||
list(inline_ids),
|
||||
).fetchall()
|
||||
inline_to_finding = {r[0]: r[1] for r in rows}
|
||||
|
||||
for c in payload:
|
||||
rcid = c.get("review_comment_id")
|
||||
if not rcid or rcid not in inline_to_finding:
|
||||
continue
|
||||
author = (c.get("user") or {}).get("login", "") or "?"
|
||||
body = c.get("body", "") or ""
|
||||
ts = _parse_iso_ts(c.get("created_at", ""))
|
||||
if record_reply(
|
||||
conn, finding_id=inline_to_finding[rcid],
|
||||
author=author, body=body, created_at=ts,
|
||||
):
|
||||
stats["replies_recorded"] += 1
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Helpers
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _strip_severity_header(body: str) -> str:
|
||||
"""Drop the leading `**[SEVERITY]**` so the posthash captures the
|
||||
substance, not the severity label."""
|
||||
return SEV_RE.sub("", body or "", count=1).strip()
|
||||
|
||||
|
||||
def _parse_iso_ts(s: str) -> int:
|
||||
if not s:
|
||||
return int(time.time())
|
||||
try:
|
||||
# Python 3.11+ fromisoformat tolerates the trailing 'Z'.
|
||||
return int(__import__("datetime").datetime.fromisoformat(
|
||||
s.replace("Z", "+00:00")
|
||||
).timestamp())
|
||||
except Exception:
|
||||
return int(time.time())
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# CLI for manual backfill / first-time seed
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def main() -> int:
|
||||
import argparse, os
|
||||
p = argparse.ArgumentParser(
|
||||
description="Harvest reactions/threads/replies on bot PR comments.",
|
||||
)
|
||||
p.add_argument("--api", default=os.environ.get(
|
||||
"GITEA_API", "http://gitea-http.gitea.svc.cluster.local:3000",
|
||||
))
|
||||
p.add_argument("--token", default=os.environ.get("PRAGENT_BOT_TOKEN", ""))
|
||||
p.add_argument("--repo", required=True, help="owner/name")
|
||||
p.add_argument("--pr", type=int, required=True, help="PR index")
|
||||
p.add_argument("--db", default=os.environ.get(
|
||||
"PRAGENT_FEEDBACK_DB", "/data/feedback.db",
|
||||
))
|
||||
args = p.parse_args()
|
||||
|
||||
if not args.token:
|
||||
print("PRAGENT_BOT_TOKEN required", flush=True)
|
||||
return 2
|
||||
|
||||
logging.basicConfig(level=logging.INFO)
|
||||
stats = harvest_for_pr(
|
||||
api=args.api, token=args.token,
|
||||
repo=args.repo, pr_index=args.pr, db_path=args.db,
|
||||
)
|
||||
print(json.dumps(stats), flush=True)
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
@@ -0,0 +1,128 @@
|
||||
"""pragent pilot — daily feedback report delivery.
|
||||
|
||||
Calls `feedback_analyze.analyze()` and posts the markdown report as a
|
||||
comment on a single long-lived "feedback roll-up" issue in
|
||||
`gitea_admin/pragent`. Comments are append-only history — one comment per
|
||||
run, timestamped in the body. This keeps every report in one place, easy
|
||||
to scroll, and avoids the issue-explosion of "one issue per day".
|
||||
|
||||
If the issue doesn't exist yet, create it. Subsequent runs just add a
|
||||
new comment.
|
||||
|
||||
Designed for the daily K8s CronJob (`k8s/pragent-feedback-cronjob.yaml`)
|
||||
but runnable from CLI for ad-hoc checks.
|
||||
|
||||
Env:
|
||||
GITEA_API in-cluster Gitea base URL
|
||||
PRAGENT_BOT_TOKEN bot token (Write collaborator on gitea_admin/pragent)
|
||||
PRAGENT_FEEDBACK_DB path to SQLite (default /data/feedback.db)
|
||||
PRAGENT_FEEDBACK_ISSUE_REPO default gitea_admin/pragent
|
||||
PRAGENT_FEEDBACK_ISSUE_TITLE default "pragent feedback roll-up"
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import sys
|
||||
|
||||
import ai_review
|
||||
|
||||
from feedback_analyze import analyze
|
||||
|
||||
log = logging.getLogger("pragent.feedback.post")
|
||||
|
||||
|
||||
REPO_DEFAULT = "gitea_admin/pragent"
|
||||
TITLE_DEFAULT = "pragent feedback roll-up"
|
||||
|
||||
|
||||
def _find_or_create_issue(api: str, token: str, repo: str, title: str) -> int:
|
||||
"""Locate the open issue with this title; create one if missing.
|
||||
|
||||
Gitea's issue search is via `GET /repos/{o}/{r}/issues?state=open&q=...`
|
||||
(q matches title + body). We filter client-side for the exact title
|
||||
to avoid query-text false matches.
|
||||
"""
|
||||
status, raw = ai_review.gitea_get(api, repo, "issues?state=open&per_page=50", token)
|
||||
if status == 200:
|
||||
try:
|
||||
for issue in json.loads(raw):
|
||||
if issue.get("title") == title:
|
||||
# NB: the comment URL needs the per-repo `number`, not the
|
||||
# global `id`. `id=60 num=8` for an early-N create; we want
|
||||
# `num=8` for `/repos/o/r/issues/8/comments`.
|
||||
return int(issue["number"])
|
||||
except (json.JSONDecodeError, ValueError, KeyError):
|
||||
pass
|
||||
# Create
|
||||
status, raw = ai_review.gitea_post(
|
||||
api, repo, "issues", token,
|
||||
{"title": title, "body": "pragent feedback roll-up — auto-created."},
|
||||
)
|
||||
if status not in (200, 201):
|
||||
raise RuntimeError(f"issue create failed: HTTP {status} body={raw[:200]!r}")
|
||||
return int(json.loads(raw)["number"])
|
||||
|
||||
|
||||
def _post_comment(api: str, token: str, repo: str, issue_number: int, body: str) -> int:
|
||||
status, raw = ai_review.gitea_post(
|
||||
api, repo, f"issues/{issue_number}/comments", token, {"body": body},
|
||||
)
|
||||
if status not in (200, 201):
|
||||
raise RuntimeError(f"comment post failed: HTTP {status} body={raw[:200]!r}")
|
||||
return json.loads(raw)["id"]
|
||||
|
||||
|
||||
def deliver(
|
||||
*, api: str, token: str, db_path: str,
|
||||
repo: str = REPO_DEFAULT, title: str = TITLE_DEFAULT,
|
||||
since_ts: int | None = None,
|
||||
) -> dict:
|
||||
"""Build the report and post it as a comment. Returns a stats dict."""
|
||||
report = analyze(db_path, since_ts=since_ts)
|
||||
issue_id = _find_or_create_issue(api, token, repo, title)
|
||||
comment_id = _post_comment(api, token, repo, issue_id, report)
|
||||
return {
|
||||
"repo": repo, "issue_id": issue_id, "comment_id": comment_id,
|
||||
"report_bytes": len(report.encode()),
|
||||
}
|
||||
|
||||
|
||||
def main() -> int:
|
||||
p = argparse.ArgumentParser(
|
||||
description="Post the daily feedback report to Gitea.",
|
||||
)
|
||||
p.add_argument("--api", default=os.environ.get(
|
||||
"GITEA_API", "http://gitea-http.gitea.svc.cluster.local:3000",
|
||||
))
|
||||
p.add_argument("--token", default=os.environ.get("PRAGENT_BOT_TOKEN", ""))
|
||||
p.add_argument("--db", default=os.environ.get(
|
||||
"PRAGENT_FEEDBACK_DB", "/data/feedback.db",
|
||||
))
|
||||
p.add_argument("--repo", default=os.environ.get(
|
||||
"PRAGENT_FEEDBACK_ISSUE_REPO", REPO_DEFAULT,
|
||||
))
|
||||
p.add_argument("--title", default=os.environ.get(
|
||||
"PRAGENT_FEEDBACK_ISSUE_TITLE", TITLE_DEFAULT,
|
||||
))
|
||||
p.add_argument("--since", type=int, default=None,
|
||||
help="Unix timestamp; only include findings posted since")
|
||||
args = p.parse_args()
|
||||
|
||||
if not args.token:
|
||||
print("PRAGENT_BOT_TOKEN required", flush=True)
|
||||
return 2
|
||||
|
||||
logging.basicConfig(level=logging.INFO)
|
||||
stats = deliver(
|
||||
api=args.api, token=args.token, db_path=args.db,
|
||||
repo=args.repo, title=args.title, since_ts=args.since,
|
||||
)
|
||||
print(json.dumps(stats), flush=True)
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
Reference in New Issue
Block a user