Floke
2c7bb262ef
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.
78 lines
3.2 KiB
Python
78 lines
3.2 KiB
Python
import json
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import logging
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import os
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from typing import Dict, Any, List
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from ..lib.core_utils import call_gemini
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from ..config import settings
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logger = logging.getLogger(__name__)
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ALLOWED_INDUSTRIES_FILE = os.path.join(os.path.dirname(__file__), "../data/allowed_industries.json")
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class ClassificationService:
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def __init__(self):
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self.allowed_industries = self._load_allowed_industries()
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def _load_allowed_industries(self) -> List[str]:
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try:
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with open(ALLOWED_INDUSTRIES_FILE, 'r', encoding='utf-8') as f:
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return json.load(f)
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except Exception as e:
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logger.error(f"Failed to load allowed industries: {e}")
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return ["Sonstige"]
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def analyze_robotics_potential(self, company_name: str, website_text: str) -> Dict[str, Any]:
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"""
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Analyzes the company for robotics potential based on website content.
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Returns strict JSON.
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"""
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if not website_text or len(website_text) < 100:
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return {"error": "Insufficient text content"}
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prompt = f"""
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You are a Senior B2B Market Analyst for 'Roboplanet', a robotics distributor.
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Your job is to analyze a target company based on their website text and determine their potential for using robots.
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--- TARGET COMPANY ---
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Name: {company_name}
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Website Content (Excerpt):
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{website_text[:15000]}
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--- ALLOWED INDUSTRIES (STRICT) ---
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You MUST assign the company to exactly ONE of these industries. If unsure, choose the closest match or "Sonstige".
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{json.dumps(self.allowed_industries, ensure_ascii=False)}
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--- ANALYSIS TASKS ---
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1. **Industry Classification:** Pick one from the list.
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2. **Robotics Potential Scoring (0-100):**
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- **Cleaning:** Does the company manage large floors, hospitals, hotels, or public spaces? (Keywords: Hygiene, Cleaning, SPA, Facility Management)
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- **Transport/Logistics:** Do they move goods internally? (Keywords: Warehouse, Intralogistics, Production line, Hospital logistics)
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- **Security:** Do they have large perimeters or night patrols? (Keywords: Werkschutz, Security, Monitoring)
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- **Service:** Do they interact with guests/patients? (Keywords: Reception, Restaurant, Nursing)
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3. **Explanation:** A short, strategic reason for the scoring (German).
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--- OUTPUT FORMAT (JSON ONLY) ---
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{{
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"industry": "String (from list)",
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"summary": "Short business summary (German)",
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"potentials": {{
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"cleaning": {{ "score": 0-100, "reason": "..." }},
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"transport": {{ "score": 0-100, "reason": "..." }},
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"security": {{ "score": 0-100, "reason": "..." }},
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"service": {{ "score": 0-100, "reason": "..." }}
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}}
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}}
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"""
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try:
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response_text = call_gemini(
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prompt=prompt,
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json_mode=True,
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temperature=0.2 # Low temp for consistency
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)
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return json.loads(response_text)
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except Exception as e:
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logger.error(f"Classification failed: {e}")
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return {"error": str(e)}
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