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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} | |