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perf: expand Fast-Track eligibility and reduce grounding pressure to eliminate 429s

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Nubenetes Bot
2026-05-20 16:27:50 +02:00
parent c5002febdb
commit 9a5ed83e88
1 changed files with 19 additions and 12 deletions
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31
src/v2_optimizer.py
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@@ -308,14 +308,20 @@ class V2VisionEngine:
for l in to_evaluate:
nu = normalize_url(l["url"])
is_github = "github.com" in nu
# We prioritize items that ALREADY have a valid description or stars
has_desc = len(l.get("description", "")) > 40
has_stars = l.get("gh_stars") is not None
if (is_github and not has_stars) or (not is_github and not has_desc):
grounded_track.append(l)
else:
# Fast-Track Eligibility:
# 1. Has AI summary (previous run)
# 2. Is GitHub and has stars (metadata present)
# 3. Has decent manual description (> 40 chars)
has_ai_summary = l.get("ai_summary") is not None and len(l.get("ai_summary")) > 50
has_stars = l.get("gh_stars") is not None
has_desc = len(l.get("description", "")) > 40
if has_ai_summary or has_stars or has_desc:
fast_track.append(l)
else:
# Grounded-Track is ONLY for "Unknown" resources with zero context
grounded_track.append(l)
log_event(f"[*] Agent Phase 1: Analyst Evaluation ({len(to_evaluate)} resources)...")
log_event(f" [>] Fast-Track: {len(fast_track)} | Grounded-Track: {len(grounded_track)}")
@@ -331,9 +337,9 @@ class V2VisionEngine:
f"{dynamic_mandates}\n"
f"{self.library_criteria}\n"
"PHASE 5: TECHNICAL SYNTHESIS (FAST-TRACK)\n"
"- Use provided metadata and descriptions to classify maturity and summary.\n"
"- Use provided metadata, AI summaries, and descriptions to classify maturity.\n"
"Respond ONLY JSON: {{\"results\": [{{ \"idx\": int, \"year\": \"YYYY\", \"stars\": 0-5, \"hierarchy\": [\"Area\", \"Topic\", ...], \"tags\": [\"...\"], \"summary\": \"Synthesis...\", \"language\": \"...\", \"type\": \"...\", \"complexity\": \"...\", \"is_microservice\": bool }}, ...]}}\n\n"
"LINKS:\n" + "\n".join([f"{idx}. {l['title']} ({l['url']}) | GH Stars: {l.get('gh_stars')} | Desc: {l.get('description')}" for idx, l in enumerate(batch)])
"LINKS:\n" + "\n".join([f"{idx}. {l['title']} ({l['url']}) | Stars: {l.get('gh_stars', l.get('stars'))} | Existing Summary: {l.get('ai_summary', l.get('description'))}" for idx, l in enumerate(batch)])
)
try:
data = await call_gemini_with_retry(prompt, prefer_flash=True, use_grounding=False, role="Analyst-Fast")
@@ -343,7 +349,8 @@ class V2VisionEngine:
item = batch[idx].copy()
eval_data = {
"year": str(res.get("year", "N/A")), "stars": min(max(int(res.get("stars", 0)), 0), 5),
"ai_summary": res.get("summary", ""), "language": res.get("language", "English"),
"ai_summary": res.get("summary", item.get("ai_summary", "")),
"language": res.get("language", "English"),
"resource_type": res.get("type", "Reference"), "complexity": res.get("complexity", "Intermediate"),
"hierarchy": res.get("hierarchy", ["General"]), "tags": res.get("tags", []),
"is_microservice": bool(res.get("is_microservice", False)),
@@ -353,10 +360,10 @@ class V2VisionEngine:
analyst_results.append(item)
except:
for l in batch: analyst_results.append(l)
await asyncio.sleep(1.0) # Increased wait between batches to absorb 429s
await asyncio.sleep(0.5)
# 1.2 Grounded-Track: Small Batches, WITH GROUNDING (Slower but precise)
BATCH_SIZE_GROUNDED = 10
BATCH_SIZE_GROUNDED = 5 # Reduced batch for grounding to avoid 429
for i in range(0, len(grounded_track), BATCH_SIZE_GROUNDED):
batch = grounded_track[i:i+BATCH_SIZE_GROUNDED]
prompt = (
@@ -386,7 +393,7 @@ class V2VisionEngine:
analyst_results.append(item)
except:
for l in batch: analyst_results.append(l)
await asyncio.sleep(2.0) # Grounding is heavy, more sleep needed
await asyncio.sleep(5.0) # Grounding is very expensive in terms of quota
# --- AGENT PHASE 2: SELECTIVE AUDIT (MCP-Grounded) ---
# Identify candidates for high-trust verification