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Pivot Node — Venorly
Fizibilite skoru dusukse (50/100 altinda) 3 alternatif pivot onerisi uretir.
Sadece buyer_leads_node'dan sonra, sadece dusuk skor durumunda calisir.
Bagimliliklar: lib/llm.py, langchain_core (ikisi zaten mevcut)
Dis etki: state["report_json"]["pivot_suggestions"] doldurulur.
"""
from typing import Any
_PIVOT_SCORE_THRESHOLD = 50 # Bu esik altinda pivot onerisi uretilir
def pivot_node(state: Any) -> Any:
"""
Weighted score < 50 ise LLM'den 3 somut pivot onerisi ister.
Her pivot: farkli hedef kitle, komsul problem veya yeni is modeli.
"""
report_json = state.get("report_json") or {}
es = report_json.get("executive_summary") or {}
score = es.get("weighted_score")
# Skor yeterince yuksekse pivot gerekmez
if score is None or float(score) >= _PIVOT_SCORE_THRESHOLD:
print(f"[PivotNode] Skor {score}/100 — pivot gerekmiyor.")
return state
print(f"[PivotNode] Skor {score}/100 — 3 pivot onerisi uretiliyor...")
idea_title = report_json.get("idea_title", "")
decision = es.get("decision", "")
market = report_json.get("market") or {}
competition = report_json.get("competition") or {}
technical = report_json.get("technical") or {}
prompt = (
f'Asagidaki startup fikri fizibilite skorunda basarisiz oldu ({score}/100, karar: {decision}).\n\n'
f'Fikir: {idea_title}\n'
f'Pazar: TAM={market.get("tam","")} | CAGR={market.get("cagr","")}\n'
f'Rekabet durumu: {competition.get("gap_summary","")[:200]}\n'
f'Teknik stack: {technical.get("stack","")}\n\n'
'GOREV: Bu fikrin neden dusuk skor aldigini analiz et ve 3 somut, farkli pivot onerisi sun.\n'
'Her pivot icin:\n'
'- Yeni hedef kitle VEYA komsul problem VEYA farkli is modeli sec\n'
'- Mevcut altyapiyi (teknoloji) yeniden kullanabilecek sekilde tasarla\n'
'- 1 cumlelik net aciklama yap\n\n'
'FORMAT — sadece 3 satir, baska hicbir sey:\n'
'1. [Pivot aciklamasi — 1 cumle]\n'
'2. [Pivot aciklamasi — 1 cumle]\n'
'3. [Pivot aciklamasi — 1 cumle]'
)
pivots = []
try:
from lib.llm import get_llm
from langchain_core.messages import HumanMessage
response = get_llm(temp=0.7).invoke([HumanMessage(content=prompt)]).content.strip()
for line in response.split('\n'):
line = line.strip()
if line and line[0].isdigit() and '.' in line:
pivot_text = line.split('.', 1)[-1].strip()
if pivot_text:
pivots.append(pivot_text)
pivots = pivots[:3]
print(f"[PivotNode] {len(pivots)} pivot onerisi uretildi ✅")
except Exception as e:
print(f"[PivotNode] LLM hatasi (devam): {e}")
return state
if not pivots:
return state
# report_json'a ekle
updated_json = {**report_json, "pivot_suggestions": pivots}
_t = state.get("trace", []) + [{
"node": "pivot",
"score": score,
"pivots_generated": len(pivots),
}]
return {**state, "report_json": updated_json, "trace": _t}
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