Floke
c6a37a3c17
This commit introduces the foundational elements for the new "Company Explorer" web application, marking a significant step away from the legacy Google Sheets / CLI system. Key changes include: - Project Structure: A new directory with separate (FastAPI) and (React/Vite) components. - Data Persistence: Migration from Google Sheets to a local SQLite database () using SQLAlchemy. - Core Utilities: Extraction and cleanup of essential helper functions (LLM wrappers, text utilities) into . - Backend Services: , , for AI-powered analysis, and logic. - Frontend UI: Basic React application with company table, import wizard, and dynamic inspector sidebar. - Docker Integration: Updated and for multi-stage builds and sideloading. - Deployment & Access: Integrated into central Nginx proxy and dashboard, accessible via . Lessons Learned & Fixed during development: - Frontend Asset Loading: Addressed issues with Vite's path and FastAPI's . - TypeScript Configuration: Added and . - Database Schema Evolution: Solved errors by forcing a new database file and correcting override. - Logging: Implemented robust file-based logging (). This new foundation provides a powerful and maintainable platform for future B2B robotics lead generation.
113 lines
3.9 KiB
Python
113 lines
3.9 KiB
Python
from sqlalchemy import create_engine, Column, Integer, String, Text, DateTime, ForeignKey, Float, Boolean, JSON
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from sqlalchemy.ext.declarative import declarative_base
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from sqlalchemy.orm import sessionmaker, relationship
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from datetime import datetime
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from .config import settings
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# Setup
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engine = create_engine(settings.DATABASE_URL, connect_args={"check_same_thread": False})
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SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
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Base = declarative_base()
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# ==============================================================================
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# MODELS
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# ==============================================================================
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class Company(Base):
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__tablename__ = "companies"
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id = Column(Integer, primary_key=True, index=True)
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# Core Identity
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name = Column(String, index=True)
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website = Column(String, index=True) # Normalized Domain preferred
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crm_id = Column(String, unique=True, index=True, nullable=True) # Link to D365
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# Classification
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industry_crm = Column(String, nullable=True) # The "allowed" industry
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industry_ai = Column(String, nullable=True) # The AI suggested industry
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# Location
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city = Column(String, nullable=True)
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country = Column(String, default="DE")
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# Workflow Status
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status = Column(String, default="NEW", index=True)
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# Granular Process Tracking (Timestamps)
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created_at = Column(DateTime, default=datetime.utcnow)
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updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
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last_scraped_at = Column(DateTime, nullable=True)
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last_wiki_search_at = Column(DateTime, nullable=True)
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last_classification_at = Column(DateTime, nullable=True)
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last_signal_check_at = Column(DateTime, nullable=True)
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# Relationships
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signals = relationship("Signal", back_populates="company", cascade="all, delete-orphan")
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enrichment_data = relationship("EnrichmentData", back_populates="company", cascade="all, delete-orphan")
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class Signal(Base):
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"""
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Represents a specific sales signal or potential.
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Example: type='has_spa', value='true', proof='Wellnessbereich mit 2000qm'
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"""
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__tablename__ = "signals"
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id = Column(Integer, primary_key=True, index=True)
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company_id = Column(Integer, ForeignKey("companies.id"))
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signal_type = Column(String, index=True) # e.g. "robotics_cleaning_potential"
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confidence = Column(Float, default=0.0) # 0.0 to 1.0
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value = Column(String) # "High", "Medium", "Yes", "No"
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proof_text = Column(Text, nullable=True) # Snippet from website/source
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created_at = Column(DateTime, default=datetime.utcnow)
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company = relationship("Company", back_populates="signals")
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class EnrichmentData(Base):
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"""
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Stores raw data blobs (HTML, API responses) to allow re-processing.
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"""
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__tablename__ = "enrichment_data"
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id = Column(Integer, primary_key=True, index=True)
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company_id = Column(Integer, ForeignKey("companies.id"))
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source_type = Column(String) # "website_scrape", "wikipedia_api", "google_serp"
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content = Column(JSON) # The raw data
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created_at = Column(DateTime, default=datetime.utcnow)
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company = relationship("Company", back_populates="enrichment_data")
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class ImportLog(Base):
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"""
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Logs bulk imports (e.g. from Excel lists).
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"""
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__tablename__ = "import_logs"
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id = Column(Integer, primary_key=True)
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filename = Column(String)
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import_type = Column(String) # "crm_dump" or "event_list"
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total_rows = Column(Integer)
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imported_rows = Column(Integer)
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duplicate_rows = Column(Integer)
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created_at = Column(DateTime, default=datetime.utcnow)
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# ==============================================================================
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# UTILS
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# ==============================================================================
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def init_db():
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Base.metadata.create_all(bind=engine)
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def get_db():
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db = SessionLocal()
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try:
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yield db
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finally:
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db.close() |