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将附件/多模态查询与编辑工具从 generalist 迁移到 public。

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同时移除 network_ops 的转发壳文件，统一工具入口并更新对应测试引用，降低重复维护成本。

Made-with: Cursor
This commit is contained in:
oliver 2026-05-01 04:13:43 +08:00
parent 5d67303d22
commit 1c71a29ec1
10 changed files with 84 additions and 126 deletions
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6
runtime/tools/experts/network_ops/image_query.py
View file

@ -1,6 +0,0 @@
from __future__ import annotations
from oclaw.runtime.tools.experts.generalist.image_query import query_image_attachment_tool
__all__ = ["query_image_attachment_tool"]

10
runtime/tools/experts/network_ops/tabular_query.py
View file

@ -1,10 +0,0 @@
from __future__ import annotations
from oclaw.runtime.tools.experts.generalist.tabular_query import (
analyze_tabular_attachment_full_scan_tool,
query_tabular_attachment_tool,
run_tabular_sql_tool,
)
__all__ = ["query_tabular_attachment_tool", "run_tabular_sql_tool", "analyze_tabular_attachment_full_scan_tool"]

6
runtime/tools/experts/network_ops/text_query.py
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@ -1,6 +0,0 @@
from __future__ import annotations
from oclaw.runtime.tools.experts.generalist.text_query import query_text_attachment_tool
__all__ = ["query_text_attachment_tool"]

6
runtime/tools/experts/network_ops/video_query.py
View file

@ -1,6 +0,0 @@
from __future__ import annotations
from oclaw.runtime.tools.experts.generalist.video_query import query_video_attachment_tool
__all__ = ["query_video_attachment_tool"]

4
runtime/tools/experts/generalist/image_edit.py → runtime/tools/public/image_edit_tool.py
View file

@ -47,13 +47,11 @@ def image_edit_tool() -> ToolSpec:
client_kwargs["base_url"] = base_url
client = OpenAI(**client_kwargs)
# OpenAI SDK expects a file-like object for edits.
img_file = io.BytesIO(blob)
img_file.name = "input.png" # type: ignore[attr-defined]
b64_out: str | None = None
try:
# Preferred: image edit endpoint (if supported by the gateway/model).
resp = client.images.edit( # type: ignore[attr-defined]
model=model,
image=img_file,
@ -63,7 +61,6 @@ def image_edit_tool() -> ToolSpec:
data0 = resp.data[0] if getattr(resp, "data", None) else None
b64_out = getattr(data0, "b64_json", None) if data0 is not None else None
except Exception:
# Fallback: generate a new image from prompt (still returns an image, but not true edit).
try:
resp = client.images.generate( # type: ignore[attr-defined]
model=model,
@ -126,4 +123,3 @@ def image_edit_tool() -> ToolSpec:
__all__ = ["image_edit_tool"]

1
runtime/tools/experts/generalist/image_query.py → runtime/tools/public/query_image_attachment_tool.py
View file

@ -72,4 +72,3 @@ def query_image_attachment_tool() -> ToolSpec:
__all__ = ["query_image_attachment_tool"]

1
runtime/tools/experts/generalist/text_query.py → runtime/tools/public/query_text_attachment_tool.py
View file

@ -38,4 +38,3 @@ def query_text_attachment_tool() -> ToolSpec:
__all__ = ["query_text_attachment_tool"]

171
runtime/tools/experts/generalist/video_query.py → runtime/tools/public/query_video_attachment_tool.py
View file

@ -1,10 +1,10 @@
from __future__ import annotations
import io
import json
import os
import subprocess
import tempfile
import io
import json
from pathlib import Path
from typing import Any
@ -144,7 +144,6 @@ def query_video_attachment_tool() -> ToolSpec:
if p is None:
return {"ok": False, "error": "attachment_not_found"}
# Basic metadata (no heavy deps). Prefer ffprobe if present.
if task == "meta":
fp = _ffprobe_json(p)
norm = _normalized_video_meta(fp)
@ -163,93 +162,88 @@ def query_video_attachment_tool() -> ToolSpec:
"note": "Use task=transcript to extract audio transcript (requires ffmpeg + OpenAI key).",
}
# transcript: extract audio then transcribe via OpenAI, store as text chunks.
if task == "transcript":
if not _ffmpeg_exists():
if not _ffmpeg_exists():
return {
"ok": False,
"error": "ffmpeg_missing",
"hint": "Install ffmpeg (ffmpeg/ffprobe on PATH) to enable transcript extraction.",
}
api_key = str(os.getenv("OPENAI_API_KEY") or "").strip()
if not api_key:
return {"ok": False, "error": "OPENAI_API_KEY_missing"}
try:
with tempfile.TemporaryDirectory() as td:
wav = Path(td) / "audio.wav"
subprocess.run(
["ffmpeg", "-y", "-i", str(p), "-vn", "-ac", "1", "-ar", "16000", str(wav)],
capture_output=True,
text=True,
timeout=60,
)
if not wav.exists() or wav.stat().st_size <= 0:
return {"ok": False, "error": "audio_extract_failed"}
try:
from openai import OpenAI
except Exception as e:
return {"ok": False, "error": f"openai_package_missing: {type(e).__name__}: {e}"}
base_url = str(os.getenv("OPENAI_BASE_URL") or "").strip()
client_kwargs: dict[str, Any] = {"api_key": api_key}
if base_url:
client_kwargs["base_url"] = base_url
client = OpenAI(**client_kwargs)
model = str(args.get("model") or os.getenv("OPENAI_AUDIO_TRANSCRIPTION_MODEL") or OPENAI_DEFAULT_AUDIO_TRANSCRIPTION_MODEL).strip()
prompt = str(args.get("prompt") or "").strip()
wav_bytes = wav.read_bytes()
f = io.BytesIO(wav_bytes)
f.name = "audio.wav" # type: ignore[attr-defined]
try:
resp = client.audio.transcriptions.create( # type: ignore[attr-defined]
model=model,
file=f,
**({"prompt": prompt} if prompt else {}),
)
text = str(getattr(resp, "text", "") or "")
except Exception as e:
return {"ok": False, "error": f"transcription_failed: {type(e).__name__}: {e}"}
if not text.strip():
return {"ok": False, "error": "empty_transcript"}
name = str(meta.name if meta else p.name)
text_name = f"{name}.transcript.txt"
cfg_chunk_size, cfg_chunk_overlap = _video_transcript_chunk_defaults()
chunk_size = int(args.get("chunk_size") or cfg_chunk_size)
chunk_overlap = int(args.get("chunk_overlap") or cfg_chunk_overlap)
text_meta = save_text_document(
attachment_id=str(attachment_id),
name=text_name,
text=text,
source_kind="video_transcript",
chunk_size=chunk_size,
chunk_overlap=chunk_overlap,
)
preview = text[:1200]
note = (
"Use query_text_attachment(text_id=...) to retrieve exact evidence with offsets."
if lang.startswith("en")
else "后续请用 query_text_attachment(text_id=...) 按需检索证据（支持 offset/top_k/关键词）。"
)
return {
"ok": False,
"error": "ffmpeg_missing",
"hint": "Install ffmpeg (ffmpeg/ffprobe on PATH) to enable transcript extraction.",
"ok": True,
"task": "transcript",
"attachment_id": attachment_id,
"name": text_name,
"text_id": str(text_meta.get("text_id") or ""),
"chars": int(text_meta.get("chars") or 0),
"chunks": int(text_meta.get("chunks") or 0),
"preview": preview,
"note": note,
}
api_key = str(os.getenv("OPENAI_API_KEY") or "").strip()
if not api_key:
return {"ok": False, "error": "OPENAI_API_KEY_missing"}
try:
with tempfile.TemporaryDirectory() as td:
wav = Path(td) / "audio.wav"
subprocess.run(
["ffmpeg", "-y", "-i", str(p), "-vn", "-ac", "1", "-ar", "16000", str(wav)],
capture_output=True,
text=True,
timeout=60,
)
if not wav.exists() or wav.stat().st_size <= 0:
return {"ok": False, "error": "audio_extract_failed"}
try:
from openai import OpenAI
except Exception as e:
return {"ok": False, "error": f"openai_package_missing: {type(e).__name__}: {e}"}
base_url = str(os.getenv("OPENAI_BASE_URL") or "").strip()
client_kwargs: dict[str, Any] = {"api_key": api_key}
if base_url:
client_kwargs["base_url"] = base_url
client = OpenAI(**client_kwargs)
model = str(args.get("model") or os.getenv("OPENAI_AUDIO_TRANSCRIPTION_MODEL") or OPENAI_DEFAULT_AUDIO_TRANSCRIPTION_MODEL).strip()
prompt = str(args.get("prompt") or "").strip()
# OpenAI SDK expects a file-like object with a name.
wav_bytes = wav.read_bytes()
f = io.BytesIO(wav_bytes)
f.name = "audio.wav" # type: ignore[attr-defined]
# Best-effort: different gateways may accept different param names; keep it minimal.
try:
resp = client.audio.transcriptions.create( # type: ignore[attr-defined]
model=model,
file=f,
**({"prompt": prompt} if prompt else {}),
)
text = str(getattr(resp, "text", "") or "")
except Exception as e:
return {"ok": False, "error": f"transcription_failed: {type(e).__name__}: {e}"}
if not text.strip():
return {"ok": False, "error": "empty_transcript"}
# Persist transcript as a long text document so the model can query evidence by text_id.
name = str(meta.name if meta else p.name)
text_name = f"{name}.transcript.txt"
cfg_chunk_size, cfg_chunk_overlap = _video_transcript_chunk_defaults()
chunk_size = int(args.get("chunk_size") or cfg_chunk_size)
chunk_overlap = int(args.get("chunk_overlap") or cfg_chunk_overlap)
text_meta = save_text_document(
attachment_id=str(attachment_id),
name=text_name,
text=text,
source_kind="video_transcript",
chunk_size=chunk_size,
chunk_overlap=chunk_overlap,
)
preview = text[:1200]
note = (
"Use query_text_attachment(text_id=...) to retrieve exact evidence with offsets."
if lang.startswith("en")
else "后续请用 query_text_attachment(text_id=...) 按需检索证据（支持 offset/top_k/关键词）。"
)
return {
"ok": True,
"task": "transcript",
"attachment_id": attachment_id,
"name": text_name,
"text_id": str(text_meta.get("text_id") or ""),
"chars": int(text_meta.get("chars") or 0),
"chunks": int(text_meta.get("chunks") or 0),
"preview": preview,
"note": note,
}
except Exception as e:
return {"ok": False, "error": f"transcript_failed: {type(e).__name__}: {e}"}
except Exception as e:
return {"ok": False, "error": f"transcript_failed: {type(e).__name__}: {e}"}
return ToolSpec(
name="query_video_attachment",
@ -275,4 +269,3 @@ def query_video_attachment_tool() -> ToolSpec:
__all__ = ["query_video_attachment_tool"]

3
runtime/tools/experts/generalist/tabular_query.py → runtime/tools/public/tabular_attachment_tools.py
View file

@ -36,7 +36,7 @@ def query_tabular_attachment_tool() -> ToolSpec:
columns=cols,
limit=int(args.get("limit") or 50),
offset=int(args.get("offset") or 0),
where_contains=where_contains, # {"column":"...", "keyword":"..."}
where_contains=where_contains,
sheet=sheet,
)
@ -147,4 +147,3 @@ def analyze_tabular_attachment_full_scan_tool() -> ToolSpec:
__all__ = ["query_tabular_attachment_tool", "run_tabular_sql_tool", "analyze_tabular_attachment_full_scan_tool"]