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2 Commits
Author SHA1 Message Date
felis b2c0c6ccdb fix pipelines 2026-06-02 22:43:12 -07:00
felis 40a4274fd3 use fun-asr-nano model instead 2026-06-02 20:24:31 -07:00
10 changed files with 130 additions and 12 deletions
+3 -3
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@@ -69,8 +69,8 @@ The checked-in `docker-compose.yml` mounts local `./config.toml` there for the A
## Services And Ports
- Frontend: `http://localhost:3000`
- Backend API: `http://localhost:8080`
- API docs: `http://localhost:8080/docs`
- Backend API: `http://localhost:8081`
- API docs: `http://localhost:8081/docs`
- Redis: `localhost:6379` when exposed by Compose
- PostgreSQL: only started by Compose when using the `local-db` profile
@@ -145,7 +145,7 @@ The frontend reads the backend URL from `frontend/public/config.js` at runtime:
```js
window.__EVANESCERE_FRONTEND_CONFIG__ = {
apiBaseUrl: "http://192.168.1.44:8080"
apiBaseUrl: "http://192.168.1.44:8081"
};
```
+1 -1
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@@ -10,7 +10,7 @@ services:
build: .
command: uvicorn evanescere.api:app --host 0.0.0.0 --port 8000
ports:
- "8080:8000"
- "8081:8000"
volumes:
- ./config.toml:/etc/evanescere/config.toml:ro
- ./storage:/data/evanescere
+1 -1
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@@ -1,3 +1,3 @@
window.__EVANESCERE_FRONTEND_CONFIG__ = {
apiBaseUrl: "http://192.168.1.44:8080"
apiBaseUrl: "http://192.168.1.44:8081"
};
+1 -1
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@@ -9,7 +9,7 @@ import type {
const runtimeApiBase = window.__EVANESCERE_FRONTEND_CONFIG__?.apiBaseUrl;
export const apiBaseUrl = (runtimeApiBase || "http://localhost:8080").replace(
export const apiBaseUrl = (runtimeApiBase || "http://localhost:8081").replace(
/\/$/,
"",
);
+6
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@@ -232,13 +232,16 @@ def run_pipeline(session: Session, video_id: int, run_id: int | None = None) ->
video.processing_status = "running"
update_run(run, "media", "running")
prepare_media(session, video)
session.commit()
update_run(run, "transcribe", "running")
transcribe_video(session, video)
session.commit()
if settings.suggest_enabled:
update_run(run, "suggest", "running")
suggest_clips(session, video)
session.commit()
if settings.render_enabled:
clips = session.scalars(
@@ -250,12 +253,15 @@ def run_pipeline(session: Session, video_id: int, run_id: int | None = None) ->
render_clip_by_id(session, clip.id)
if settings.upload_enabled:
upload_clip_by_id(session, clip.id)
session.commit()
video.processing_status = "done"
update_run(run, "done", "done")
session.commit()
logger.info("pipeline done video_id=%s run_id=%s", video_id, run_id)
except Exception as exc:
video.processing_status = "failed"
update_run(run, "failed", "failed", str(exc))
session.commit()
logger.exception("pipeline failed video_id=%s run_id=%s", video_id, run_id)
raise
+16 -5
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@@ -35,7 +35,7 @@ class FunAsrClient:
"model": self.model,
"language": "zh",
"response_format": "verbose_json",
"timestamp_granularities[]": "segment",
"timestamp_granularities": "segment",
},
files={"file": (audio_path.name, audio_file, "audio/wav")},
timeout=None,
@@ -45,8 +45,12 @@ class FunAsrClient:
logger.info("funasr request done audio=%s keys=%s", audio_path, sorted(payload.keys()))
return payload
def normalize_segments(payload: dict[str, Any]) -> list[dict[str, Any]]:
def normalize_segments(
payload: dict[str, Any],
*,
fallback_start_sec: float = 0.0,
fallback_end_sec: float | None = None,
) -> list[dict[str, Any]]:
raw_segments = payload.get("segments") or payload.get("sentence_info") or []
logger.debug("normalizing asr segments raw_count=%s", len(raw_segments))
normalized: list[dict[str, Any]] = []
@@ -71,10 +75,17 @@ def normalize_segments(payload: dict[str, Any]) -> list[dict[str, Any]]:
}
)
if not normalized and payload.get("text"):
logger.warning(
"asr response contained text but no timestamped segments; "
"falling back to the known audio bounds"
)
end_sec = fallback_end_sec
if end_sec is None:
end_sec = float(payload.get("duration") or fallback_start_sec + 0.1)
normalized.append(
{
"start_sec": 0.0,
"end_sec": 0.1,
"start_sec": fallback_start_sec,
"end_sec": max(fallback_start_sec + 0.1, end_sec),
"text": str(payload["text"]).strip(),
"speaker": None,
"confidence": None,
+38
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@@ -190,6 +190,7 @@ def chunk_transcript(
def parse_clip_response(content: str) -> list[ClipCandidate]:
try:
payload = json.loads(content)
payload = normalize_clip_payload(payload)
parsed = ClipCandidateResponse.model_validate(payload)
except (json.JSONDecodeError, ValidationError) as exc:
logger.error("invalid clip json content_prefix=%s", content[:1000])
@@ -197,6 +198,43 @@ def parse_clip_response(content: str) -> list[ClipCandidate]:
return parsed.clips
def normalize_clip_payload(payload: object) -> dict:
if not isinstance(payload, dict):
return {"clips": []}
if "clips" not in payload and "candidates" in payload:
payload = payload | {"clips": payload["candidates"]}
clips = payload.get("clips")
if not isinstance(clips, list):
return payload
normalized_clips = []
for clip in clips:
if not isinstance(clip, dict):
normalized_clips.append(clip)
continue
normalized = dict(clip)
normalized["score"] = normalize_score(normalized.get("score", 0))
normalized_clips.append(normalized)
return payload | {"clips": normalized_clips}
def normalize_score(value: object) -> float:
try:
score = float(value)
except (TypeError, ValueError):
logger.warning("invalid llm score=%r; using 0", value)
return 0.0
if score > 1:
original = score
if score <= 10:
score = score / 10
elif score <= 100:
score = score / 100
else:
score = 1.0
logger.debug("normalized llm score original=%s normalized=%s", original, score)
return max(0.0, min(1.0, score))
def overlap_ratio(left: ClipCandidate, right: ClipCandidate) -> float:
overlap = max(0, min(left.end_sec, right.end_sec) - max(left.start_sec, right.start_sec))
shortest = min(left.end_sec - left.start_sec, right.end_sec - right.start_sec)
+4 -1
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@@ -182,7 +182,10 @@ def bootstrap_existing(client: WebDavClient, session: Session) -> BootstrapResul
session.add(video)
inserted += 1
logger.debug("bootstrap existing file=%s size=%s", file.filename, file.size_bytes)
elif video.ingest_status == "observing" and video.processing_status == "pending":
elif (
video.ingest_status in {"observing", "stable", "queued"}
and video.processing_status in {"pending", "queued"}
):
video.size_bytes = file.size_bytes
video.ingest_status = "existing_done"
video.processing_status = "done"
+16
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@@ -0,0 +1,16 @@
from evanescere.services.asr import normalize_segments
def test_normalize_segments_uses_known_audio_bounds_when_timestamps_are_missing():
assert normalize_segments(
{"text": "你好", "segments": []}, fallback_start_sec=0, fallback_end_sec=15
) == [
{
"start_sec": 0,
"end_sec": 15,
"text": "你好",
"speaker": None,
"confidence": None,
"metadata": {"text": "你好", "segments": []},
}
]
+44
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@@ -30,6 +30,50 @@ def test_parse_clip_response():
assert candidates[0].title_zh == "标题"
def test_parse_clip_response_accepts_candidates_key_and_score_out_of_ten():
candidates = parse_clip_response(
"""
{
"candidates": [
{
"start_sec": 10,
"end_sec": 60,
"title_zh": "标题",
"summary_zh": "摘要",
"reason": "有趣",
"score": 8.5,
"tags": ["反应"],
"subtitle_priority": "high"
}
]
}
"""
)
assert candidates[0].score == 0.85
def test_parse_clip_response_normalizes_score_out_of_hundred():
candidates = parse_clip_response(
"""
{
"clips": [
{
"start_sec": 10,
"end_sec": 60,
"title_zh": "标题",
"summary_zh": "摘要",
"reason": "有趣",
"score": 92,
"tags": ["反应"],
"subtitle_priority": "high"
}
]
}
"""
)
assert candidates[0].score == 0.92
def test_dedupe_and_rank_candidates_filters_short_and_overlapping():
candidates = [
ClipCandidate(