[31388f42] Implement hierarchical search strategy for more robust role discovery
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@@ -48,15 +48,17 @@ def extract_role_with_llm(name, company, search_results):
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{context}
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TASK:
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Extract the exact Job Title / Role. Look for terms like "Geschäftsführer", "CEO", "CFO", "Leiter", "Head of", "Manager", "Inhaber", "Arzt".
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Extract the professional Job Title / Role.
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Look for:
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- Management: "Geschäftsführer", "Vorstand", "CFO", "Mitglied der Klinikleitung"
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- Department Heads: "Leiter", "Bereichsleitung", "Head of", "Pflegedienstleitung"
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- Specialized: "Arzt", "Ingenieur", "Einkäufer"
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RULES:
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1. If multiple roles appear (e.g. "CFO & CEO"), pick the most senior one current role.
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2. Return ONLY the role string. No full sentences.
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3. If absolutely no role is mentioned in the snippets, return "Unbekannt".
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Example Input: "Georg Stahl ... CFO at KLEMM..."
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Example Output: CFO
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1. Extract the most specific and senior current role.
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2. Return ONLY the role string (e.g. "Bereichsleitung Patientenmanagement").
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3. Maximum length: 60 characters.
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4. If no role is found, return "Unbekannt".
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"""
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url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={api_key}"
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@@ -64,8 +66,8 @@ def extract_role_with_llm(name, company, search_results):
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response = requests.post(url, headers={'Content-Type': 'application/json'}, json={"contents": [{"parts": [{"text": prompt}]}]})
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if response.status_code == 200:
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role = response.json()['candidates'][0]['content']['parts'][0]['text'].strip()
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# Cleanup: remove punctuation at the end
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role = role.rstrip('.')
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# Remove markdown formatting if any
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role = role.replace('**', '').replace('"', '').rstrip('.')
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return None if "Unbekannt" in role else role
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else:
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print(f"DEBUG: Gemini API Error {response.status_code}: {response.text}")
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@@ -76,40 +78,52 @@ def extract_role_with_llm(name, company, search_results):
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def lookup_person_role(name, company):
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"""
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Searches for a person's role via SerpAPI and extracts it using LLM.
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Uses a multi-step search strategy to find the best snippets.
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"""
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if not SERP_API_KEY:
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print("Error: SERP_API key not found in .env")
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return None
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# Broad query to find role/position
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query = f'{name} {company} Position Job'
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# Step 1: Highly specific search
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queries = [
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f'site:linkedin.com "{name}" "{company}"',
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f'"{name}" "{company}" position',
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f'{name} {company}'
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]
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params = {
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"engine": "google",
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"q": query,
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"api_key": SERP_API_KEY,
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"num": 5,
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"hl": "de", # Force German UI
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"gl": "de" # Force German Location
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}
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all_results = []
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for query in queries:
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params = {
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"engine": "google",
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"q": query,
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"api_key": SERP_API_KEY,
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"num": 3,
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"hl": "de",
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"gl": "de"
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}
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try:
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response = requests.get("https://serpapi.com/search", params=params)
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response.raise_for_status()
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data = response.json()
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organic_results = data.get("organic_results", [])
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if not organic_results:
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return None
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try:
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response = requests.get("https://serpapi.com/search", params=params)
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response.raise_for_status()
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data = response.json()
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results = data.get("organic_results", [])
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if results:
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all_results.extend(results)
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# If we have good results, we don't necessarily need more searches
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if len(all_results) >= 3:
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break
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except Exception as e:
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print(f"SerpAPI lookup failed for query '{query}': {e}")
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# Delegate extraction to LLM
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return extract_role_with_llm(name, company, organic_results)
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except Exception as e:
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print(f"SerpAPI lookup failed: {e}")
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if not all_results:
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return None
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# Delegate extraction to LLM with the best results found
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return extract_role_with_llm(name, company, all_results)
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if __name__ == "__main__":
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# Test cases
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print(f"Markus Drees: {lookup_person_role('Markus Drees', 'Ärztehaus Rünthe')}")
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print(f"Georg Stahl: {lookup_person_role('Georg Stahl', 'Klemm Bohrtechnik GmbH')}")
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print(f"Steve Trüby: {lookup_person_role('Steve Trüby', 'RehaKlinikum Bad Säckingen GmbH')}")
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