mirror of
https://github.com/hansjone/oclaw.git
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oliver
420abac9f1
- Rename platform/ to svc/ to avoid shadowing stdlib platform. - Replace from oclaw.* with from svc/runtime/interfaces; update -m CLI paths. - tests/conftest: prepend repo root to sys.path (no parent-folder package name). - CI: paths and offline_eval script under repo root. - Ops scripts: PYTHONPATH must be repo root for python -m runtime.* (fixes gateway/WhatsApp sidecar startup). - Fix default oclaw.json path in tabular/file attachment limits; stabilize attachment test config. Co-authored-by: Cursor <cursoragent@cursor.com>
101 lines
3 KiB
Python
101 lines
3 KiB
Python
from __future__ import annotations
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import hashlib
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Any
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from svc.embeddings.embedding_client import build_default_embedding_client
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from svc.persistence.sqlite_store import SqliteStore
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from svc.config.paths import PROJECT_ROOT
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def _default_workspace_root() -> Path:
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import os
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override = (os.getenv("AIA_WORKSPACE_ROOT") or "").strip()
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if override:
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return Path(override).expanduser().resolve()
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return Path(PROJECT_ROOT).resolve()
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@dataclass(frozen=True)
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class IndexStats:
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files_seen: int
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chunks_upserted: int
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embeddings_upserted: int
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def _chunk_id(source: str, text: str) -> str:
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raw = f"{source}\n{text}".encode("utf-8", errors="ignore")
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return hashlib.sha1(raw).hexdigest()
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def _iter_files(root: Path, patterns: list[str], *, max_files: int) -> list[Path]:
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files: list[Path] = []
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for pat in patterns:
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for p in root.glob(pat):
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if p.is_dir():
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continue
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files.append(p)
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if len(files) >= max_files:
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return files
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# de-dup by path
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uniq = []
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seen = set()
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for p in files:
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rp = str(p)
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if rp in seen:
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continue
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seen.add(rp)
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uniq.append(p)
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return uniq[:max_files]
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def index_workspace(
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store: SqliteStore,
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*,
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root: str | None = None,
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patterns: list[str] | None = None,
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max_files: int = 200,
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max_chars_per_chunk: int = 1600,
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) -> IndexStats:
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r = Path(root).resolve() if root else _default_workspace_root()
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pats = patterns or ["**/*.py", "README*.md", "**/*.md"]
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files = _iter_files(r, pats, max_files=max(1, int(max_files)))
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client = build_default_embedding_client()
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chunks_upserted = 0
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embeds_upserted = 0
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for p in files:
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try:
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text = p.read_text(encoding="utf-8", errors="replace")
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except Exception:
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continue
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rel = str(p.relative_to(r))
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# naive chunking by chars (good enough for MVP)
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for idx in range(0, len(text), max(200, int(max_chars_per_chunk))):
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chunk = text[idx : idx + int(max_chars_per_chunk)].strip()
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if not chunk:
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continue
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source = f"workspace:{rel}#c{idx//max_chars_per_chunk:04d}"
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cid = _chunk_id(source, chunk)
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store.upsert_knowledge_chunk(
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chunk_id=cid,
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source=source,
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content=chunk,
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metadata={"source": source, "path": rel, "offset": idx},
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)
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chunks_upserted += 1
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try:
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emb = client.embed(chunk[:8000])
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store.upsert_knowledge_embedding(chunk_id=cid, model=emb.model, vector=emb.vector)
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embeds_upserted += 1
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except Exception:
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continue
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return IndexStats(files_seen=len(files), chunks_upserted=chunks_upserted, embeddings_upserted=embeds_upserted)
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__all__ = ["IndexStats", "index_workspace"]
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