fix(youtube): pass full transcripts to LLM instead of truncating to 200 chars

TRANSCRIPT_MAX_WORDS raised from 500 to 5000 so the LLM gets the full
content of most videos (up to ~25 minutes). Removed the second 200-char
truncation in render.py that was reducing transcripts to a single sentence
before the judge agent ever saw them.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Matt Van Horn
2026-03-23 17:28:01 -07:00
parent 6a5a0013c0
commit 499074b564
2 changed files with 2 additions and 5 deletions
+1 -4
View File
@@ -258,10 +258,7 @@ def render_compact(report: schema.Report, limit: int = 15, missing_keys: str = "
lines.append(f" {item.title}") lines.append(f" {item.title}")
lines.append(f" {item.url}") lines.append(f" {item.url}")
if item.transcript_snippet: if item.transcript_snippet:
snippet = item.transcript_snippet[:200] lines.append(f" Transcript: {item.transcript_snippet}")
if len(item.transcript_snippet) > 200:
snippet += "..."
lines.append(f" Transcript: {snippet}")
lines.append(f" *{item.why_relevant}*") lines.append(f" *{item.why_relevant}*")
lines.append("") lines.append("")
+1 -1
View File
@@ -33,7 +33,7 @@ TRANSCRIPT_LIMITS = {
} }
# Max words to keep from each transcript # Max words to keep from each transcript
TRANSCRIPT_MAX_WORDS = 500 TRANSCRIPT_MAX_WORDS = 5000
from .relevance import token_overlap_relevance as _compute_relevance from .relevance import token_overlap_relevance as _compute_relevance