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Make make_clips.py resilient — timeouts, retries, skip-on-failure

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- 60s timeout + retry on all LLM calls
- 120-300s timeout on all subprocess/ffmpeg calls
- Per-clip error isolation (one failure doesn't kill the run)
- Progress indicators for each clip being processed

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
tcpsyn
2026-03-20 17:36:41 -06:00
parent 4589670b37
commit e0fb3cac68
1 changed files with 142 additions and 114 deletions
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make_clips.py
+93 -65
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@@ -23,6 +23,8 @@ import tempfile
import xml.etree.ElementTree as ET
from pathlib import Path
import time
import requests
from dotenv import load_dotenv
@@ -46,6 +48,50 @@ WIDTH = 1080
HEIGHT = 1920
def _llm_request(prompt: str, max_tokens: int = 2048, temperature: float = 0.3,
timeout: int = 60) -> str | None:
"""Make an LLM API call with timeout and retry. Returns content or None on failure."""
for attempt in range(2):
try:
response = requests.post(
"https://openrouter.ai/api/v1/chat/completions",
headers={
"Authorization": f"Bearer {OPENROUTER_API_KEY}",
"Content-Type": "application/json",
},
json={
"model": "anthropic/claude-sonnet-4-5",
"messages": [{"role": "user", "content": prompt}],
"max_tokens": max_tokens,
"temperature": temperature,
},
timeout=timeout,
)
if response.status_code != 200:
print(f" LLM error (HTTP {response.status_code}): {response.text[:200]}")
if attempt == 0:
print(f" Retrying in 5s...")
time.sleep(5)
continue
return None
return response.json()["choices"][0]["message"]["content"].strip()
except requests.Timeout:
print(f" LLM request timed out ({timeout}s)")
if attempt == 0:
print(f" Retrying in 5s...")
time.sleep(5)
continue
return None
except Exception as e:
print(f" LLM request failed: {e}")
if attempt == 0:
print(f" Retrying in 5s...")
time.sleep(5)
continue
return None
return None
def _build_whisper_prompt(labeled_transcript: str) -> str:
"""Build an initial_prompt for Whisper from the labeled transcript.
@@ -186,7 +232,12 @@ def refine_clip_timestamps(audio_path: str, clips: list[dict],
"ffmpeg", "-y", "-ss", str(seg_start), "-t", str(seg_end - seg_start),
"-i", audio_path, "-ar", "16000", "-ac", "1", seg_path,
]
result = subprocess.run(cmd, capture_output=True, text=True)
try:
result = subprocess.run(cmd, capture_output=True, text=True, timeout=120)
except subprocess.TimeoutExpired:
print(f" Clip {i+1}: ffmpeg timed out (120s), skipping")
refined[i] = []
continue
if result.returncode != 0:
print(f" Clip {i+1}: Failed to extract segment")
refined[i] = []
@@ -279,25 +330,11 @@ IMPORTANT:
Respond with ONLY a JSON array, no markdown or explanation:
[{{"title": "...", "start_time": 0.0, "end_time": 0.0, "caption_text": "..."}}]"""
response = requests.post(
"https://openrouter.ai/api/v1/chat/completions",
headers={
"Authorization": f"Bearer {OPENROUTER_API_KEY}",
"Content-Type": "application/json",
},
json={
"model": "anthropic/claude-sonnet-4-5",
"messages": [{"role": "user", "content": prompt}],
"max_tokens": 2048,
"temperature": 0.3,
},
)
content = _llm_request(prompt, max_tokens=2048, temperature=0.3, timeout=60)
if content is None:
print(" Failed to get clip selections from LLM — aborting")
return []
if response.status_code != 200:
print(f"Error from OpenRouter: {response.text}")
sys.exit(1)
content = response.json()["choices"][0]["message"]["content"].strip()
if content.startswith("```"):
content = re.sub(r"^```(?:json)?\n?", "", content)
content = re.sub(r"\n?```$", "", content)
@@ -307,7 +344,7 @@ Respond with ONLY a JSON array, no markdown or explanation:
except json.JSONDecodeError as e:
print(f"Error parsing LLM response: {e}")
print(f"Response was: {content[:500]}")
sys.exit(1)
return []
# Validate and clamp durations
validated = []
@@ -349,25 +386,11 @@ For each clip, generate:
Respond with ONLY a JSON array matching the clip order:
[{{"description": "...", "hashtags": ["#tag1", "#tag2", ...]}}]"""
response = requests.post(
"https://openrouter.ai/api/v1/chat/completions",
headers={
"Authorization": f"Bearer {OPENROUTER_API_KEY}",
"Content-Type": "application/json",
},
json={
"model": "anthropic/claude-sonnet-4-5",
"messages": [{"role": "user", "content": prompt}],
"max_tokens": 2048,
"temperature": 0.7,
},
)
if response.status_code != 200:
print(f"Error from OpenRouter: {response.text}")
content = _llm_request(prompt, max_tokens=2048, temperature=0.7, timeout=60)
if content is None:
print(" Failed to generate social metadata — skipping")
return clips
content = response.json()["choices"][0]["message"]["content"].strip()
if content.startswith("```"):
content = re.sub(r"^```(?:json)?\n?", "", content)
content = re.sub(r"\n?```$", "", content)
@@ -777,26 +800,11 @@ RULES:
RAW TEXT ({len(words)} words):
{raw_text}"""
try:
response = requests.post(
"https://openrouter.ai/api/v1/chat/completions",
headers={
"Authorization": f"Bearer {OPENROUTER_API_KEY}",
"Content-Type": "application/json",
},
json={
"model": "anthropic/claude-sonnet-4-5",
"messages": [{"role": "user", "content": prompt}],
"max_tokens": 2048,
"temperature": 0,
},
timeout=30,
)
if response.status_code != 200:
print(f" Polish failed ({response.status_code}), using raw text")
polished = _llm_request(prompt, max_tokens=2048, temperature=0, timeout=30)
if polished is None:
print(f" Polish failed, using raw text")
return words
polished = response.json()["choices"][0]["message"]["content"].strip()
polished_words = polished.split()
if len(polished_words) != len(words):
@@ -812,9 +820,6 @@ RAW TEXT ({len(words)} words):
if changes:
print(f" Polished {changes} words")
except Exception as e:
print(f" Polish error: {e}")
return words
@@ -898,8 +903,12 @@ def extract_clip_audio(audio_path: str, start: float, end: float,
output_path,
]
result = subprocess.run(cmd, capture_output=True, text=True)
try:
result = subprocess.run(cmd, capture_output=True, text=True, timeout=120)
return result.returncode == 0
except subprocess.TimeoutExpired:
print(f" ffmpeg audio extraction timed out (120s)")
return False
def generate_background_image(episode_number: int, clip_title: str,
@@ -1153,7 +1162,11 @@ def generate_clip_video(audio_path: str, background_path: str,
output_path,
]
result = subprocess.run(cmd, capture_output=True, text=True)
try:
result = subprocess.run(cmd, capture_output=True, text=True, timeout=300)
except subprocess.TimeoutExpired:
print(f" ffmpeg video generation timed out (300s)")
return False
if result.returncode != 0:
print(f" ffmpeg error: {result.stderr[-300:]}")
return False
@@ -1235,7 +1248,12 @@ def generate_clip_video_remotion(
output_path,
]
result = subprocess.run(cmd, capture_output=True, text=True, cwd=str(REMOTION_DIR))
try:
result = subprocess.run(cmd, capture_output=True, text=True, cwd=str(REMOTION_DIR), timeout=180)
except subprocess.TimeoutExpired:
props_path.unlink(missing_ok=True)
print(f" Remotion render timed out (180s)")
return False
props_path.unlink(missing_ok=True)
if result.returncode != 0:
@@ -1488,6 +1506,9 @@ def main():
print(f"\n[3/{step_total}] Selecting {args.count} best moments with LLM...")
clips = select_clips_with_llm(transcript_text, labeled_transcript,
chapters_json, args.count)
if not clips:
print("\nNo clips selected — aborting.")
return
# Snap to sentence boundaries so clips don't start/end mid-sentence
clips = snap_to_sentences(clips, segments)
@@ -1524,14 +1545,18 @@ def main():
extract_step = 6 if two_pass else 5
print(f"\n[{extract_step}/{step_total}] Extracting audio clips...")
for i, clip in enumerate(clips):
print(f" [{i+1}/{len(clips)}] \"{clip['title']}\"...")
slug = slugify(clip["title"])
mp3_path = output_dir / f"clip-{i+1}-{slug}.mp3"
try:
if extract_clip_audio(str(audio_path), clip["start_time"], clip["end_time"],
str(mp3_path)):
print(f" Clip {i+1} audio: {mp3_path.name}")
else:
print(f" Error extracting clip {i+1} audio")
print(f" Error extracting clip {i+1} audio — skipping")
except Exception as e:
print(f" Clip {i+1} audio failed: {e} — skipping")
video_step = 7 if two_pass else 6
if args.audio_only:
@@ -1553,8 +1578,9 @@ def main():
mp4_path = output_dir / f"clip-{i+1}-{slug}.mp4"
duration = clip["end_time"] - clip["start_time"]
print(f" Clip {i+1}: Generating video...")
print(f" [{i+1}/{len(clips)}] \"{clip['title']}\" ({duration:.0f}s)...")
try:
# Get word timestamps — use refined segments if available
word_source = refined[i] if (two_pass and i in refined and refined[i]) else segments
clip_words = get_words_in_range(word_source, clip["start_time"], clip["end_time"])
@@ -1580,7 +1606,7 @@ def main():
file_size = mp4_path.stat().st_size / (1024 * 1024)
print(f" Clip {i+1} video: {mp4_path.name} ({file_size:.1f} MB)")
else:
print(f" Error generating clip {i+1} video (Remotion)")
print(f" Clip {i+1} video failed (Remotion) — skipping")
else:
# Legacy PIL+ffmpeg renderer
bg_path = str(tmp_dir / f"bg_{i}.png")
@@ -1595,7 +1621,9 @@ def main():
file_size = mp4_path.stat().st_size / (1024 * 1024)
print(f" Clip {i+1} video: {mp4_path.name} ({file_size:.1f} MB)")
else:
print(f" Error generating clip {i+1} video")
print(f" Clip {i+1} video failed (ffmpeg) — skipping")
except Exception as e:
print(f" Clip {i+1} video failed: {e} — skipping")
# Save clips metadata for social upload
metadata_path = output_dir / "clips-metadata.json"