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[2f988f42] fix(company-explorer): Implement robust quantitative potential and atomic opener generation\n\n- Refactored ClassificationService for two-stage metric extraction (direct area and proxy).- Enhanced MetricParser for targeted value matching and robust number parsing.- Implemented persona-specific 'Atomic Opener' generation using segmented pains.- Fixed logging configuration and Pydantic response models.- Added dedicated debugging script and updated documentation (GEMINI.md, MIGRATION_PLAN.md).

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Floke
2026-02-21 08:01:07 +00:00
parent 62a924a168
commit 45acbeefb9
13 changed files with 666 additions and 534 deletions
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company-explorer/backend/database.py
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@@ -68,6 +68,10 @@ class Company(Base):
metric_source_url = Column(Text, nullable=True) # URL where the proof was found
metric_confidence = Column(Float, nullable=True) # 0.0 - 1.0
metric_confidence_reason = Column(Text, nullable=True) # Why is it high/low?
# NEW: AI-generated Marketing Openers
ai_opener = Column(Text, nullable=True)
ai_opener_secondary = Column(Text, nullable=True)
# Relationships
signals = relationship("Signal", back_populates="company", cascade="all, delete-orphan")