Ajout API job search avec Gradio
Browse files
app.py
CHANGED
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@@ -1,7 +1,118 @@
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import gradio as gr
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import requests
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SERPAPI_KEY = "7aa26c214c77639dc2be2a61cb01ba2811fde874a36d3b04a38b9823655f6706"
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def search_jobs(job_title="", location="", user_desc=None, salary=None, studies=None, domain=None):
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"""
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@@ -160,112 +271,82 @@ def search_jobs(job_title="", location="", user_desc=None, salary=None, studies=
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"jsonrpc": "2.0",
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"result": {
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"success": False,
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"status": "
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"message": "Aucune offre
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"
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"
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"location": location,
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"
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"job_title": job_title,
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"location": location,
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"user_desc": user_desc,
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"salary": salary,
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"studies": studies,
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"domain": domain
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},
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"serpapi_parameters": payload,
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"search_radius_km": 50,
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"fallback_attempted": search_info.get("fallback_query") is not None,
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"fallback_query": search_info.get("fallback_query"),
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"fallback_results_count": search_info.get("fallback_results", 0)
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},
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"jobs": {
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"
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"displayed_count": 0,
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"results": []
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},
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"suggestions": [
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"Essayez
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"Vérifiez l'orthographe de la
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"Élargissez la zone géographique"
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],
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"debug_information": search_info
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},
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"id": None
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}
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# Retourner la liste de jobs avec informations
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jobs_list = []
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for job in jobs_results:
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job_info = {
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"job_id": job.get("job_id", ""),
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"title": job.get("title", ""),
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"
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"company_url": job.get("company_url", ""),
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"location": job.get("location", ""),
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"
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"description":
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"job_highlights": job.get("job_highlights", {}),
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"related_links": job.get("related_links", []),
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"thumbnail": job.get("thumbnail", ""),
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"extensions": job.get("extensions", []),
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"detected_extensions": job.get("detected_extensions", {}),
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"apply_options": job.get("apply_options", []),
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"link": job.get("link", ""),
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"
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}
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jobs_list.append(job_info)
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total_jobs_found = len(jobs_list)
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# Format JSON-RPC 2.0
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"jsonrpc": "2.0",
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"result": {
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"success": True,
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"status": "
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"message": f"
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"
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"
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"processed_keywords": query.split(),
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"location": location,
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"
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"search_parameters": {
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"job_title": job_title,
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"location": location,
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"user_desc": user_desc,
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"salary": salary,
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"studies": studies,
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"domain": domain
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},
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"serpapi_parameters": payload,
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"search_radius_km": 50,
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"fallback_attempted": search_info.get("fallback_query") is not None,
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"fallback_query": search_info.get("fallback_query"),
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"fallback_results_count": search_info.get("fallback_results", 0),
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"serpapi_response_keys": search_info.get("serpapi_response_keys", [])
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},
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"jobs": {
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"results": displayed_jobs
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},
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"
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"
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"
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"unique_companies": len(set([j.get("company_name", "") for j in displayed_jobs if j.get("company_name")])),
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"job_sources": list(set([j.get("via", "") for j in displayed_jobs if j.get("via")]))
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},
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"debug_information": search_info
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},
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"id": None
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}
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except Exception as e:
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return {
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import gradio as gr
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import requests
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import json
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SERPAPI_KEY = "7aa26c214c77639dc2be2a61cb01ba2811fde874a36d3b04a38b9823655f6706"
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MIXTRAL_API_KEY = "VhU4tnowxkqtGOIRoyP7qUlhnXj1kjn5" # Remplace par ta clé Hugging Face
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MIXTRAL_API_URL = "https://api-inference.huggingface.co/models/mistralai/Mixtral-8x7B-Instruct-v0.1"
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def format_jobs_with_mixtral(jobs_data):
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"""
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Utilise Mixtral pour reformater les offres d'emploi en format optimal pour le LLM chat.
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Args:
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jobs_data (dict): Données des offres d'emploi depuis SerpAPI
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Returns:
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dict: Format optimisé pour le LLM chat
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"""
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try:
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# Créer un prompt pour Mixtral
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jobs_json = json.dumps(jobs_data, ensure_ascii=False, indent=2)
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prompt = f"""Tu es un assistant spécialisé dans la présentation d'offres d'emploi.
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Voici des données JSON d'offres d'emploi que tu dois reformater pour qu'elles soient parfaitement présentables par un LLM chat.
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DONNÉES JSON:
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{jobs_json}
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INSTRUCTIONS:
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1. Crée un format JSON-RPC 2.0 optimisé
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2. Résume chaque offre de manière claire et concise
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3. Mets en avant les informations essentielles : titre, entreprise, lieu, salaire, lien
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4. Garde les descriptions courtes mais informatives (max 150 caractères)
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5. Assure-toi que le JSON final fait moins de 25000 caractères
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6. Structure le tout pour que le LLM puisse facilement présenter les résultats à l'utilisateur
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Réponds UNIQUEMENT avec le JSON formaté, sans explication."""
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# Appel à l'API Mixtral
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headers = {
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"Authorization": f"Bearer {MIXTRAL_API_KEY}",
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"Content-Type": "application/json"
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}
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payload = {
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"inputs": prompt,
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"parameters": {
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"max_new_tokens": 2000,
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"temperature": 0.1,
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"return_full_text": False
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}
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}
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response = requests.post(MIXTRAL_API_URL, headers=headers, json=payload, timeout=30)
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if response.status_code == 200:
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mixtral_response = response.json()
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if isinstance(mixtral_response, list) and len(mixtral_response) > 0:
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formatted_text = mixtral_response[0].get("generated_text", "")
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# Essayer de parser le JSON retourné par Mixtral
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try:
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# Nettoyer la réponse (enlever les éventuels markdown)
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if "```json" in formatted_text:
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formatted_text = formatted_text.split("```json")[1].split("```")[0]
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elif "```" in formatted_text:
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formatted_text = formatted_text.split("```")[1].split("```")[0]
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formatted_json = json.loads(formatted_text.strip())
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return formatted_json
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except json.JSONDecodeError:
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# Si le parsing échoue, retourner le format original simplifié
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pass
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# Fallback : format simplifié si Mixtral échoue
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return create_simplified_format(jobs_data)
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except Exception as e:
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# En cas d'erreur avec Mixtral, retourner le format simplifié
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return create_simplified_format(jobs_data)
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def create_simplified_format(jobs_data):
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"""
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Crée un format simplifié en cas d'échec de Mixtral.
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"""
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if not jobs_data.get("result", {}).get("jobs", {}).get("results"):
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return jobs_data
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jobs = jobs_data["result"]["jobs"]["results"]
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simplified_jobs = []
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for job in jobs[:6]: # Limiter à 6 offres max
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simplified_job = {
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"titre": job.get("title", ""),
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"entreprise": job.get("company", ""),
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"lieu": job.get("location", ""),
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"salaire": job.get("salary", "Non spécifié"),
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"description": job.get("description", "")[:120] + "..." if len(job.get("description", "")) > 120 else job.get("description", ""),
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"lien": job.get("link", "")
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}
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simplified_jobs.append(simplified_job)
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return {
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"jsonrpc": "2.0",
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"result": {
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"status": "SUCCESS",
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"message": f"✅ {len(simplified_jobs)} offres d'emploi trouvées",
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"offres": simplified_jobs,
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"info": {
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"recherche": jobs_data.get("result", {}).get("search_info", {}).get("query", ""),
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"lieu": jobs_data.get("result", {}).get("search_info", {}).get("location", "")
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}
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},
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"id": None
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}
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def search_jobs(job_title="", location="", user_desc=None, salary=None, studies=None, domain=None):
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"""
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"jsonrpc": "2.0",
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"result": {
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"success": False,
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"status": "NO_RESULTS",
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"message": "❌ Aucune offre trouvée",
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"search_info": {
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"query": query,
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"location": location,
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"fallback_used": search_info.get("fallback_query") is not None
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},
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"jobs": {
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"total": 0,
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"results": []
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},
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"suggestions": [
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"Essayez un métier plus général",
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"Vérifiez l'orthographe de la ville",
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"Élargissez la zone géographique"
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]
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},
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"id": None
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}
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# Retourner la liste de jobs avec informations essentielles (optimisé pour éviter la troncature)
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jobs_list = []
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for job in jobs_results:
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# Limiter la description pour éviter les JSON trop lourds
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description = job.get("description", "")
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if description and len(description) > 300:
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description = description[:300] + "..."
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job_info = {
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"title": job.get("title", ""),
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"company": job.get("company_name", ""),
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"location": job.get("location", ""),
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"salary": job.get("salary", "Non spécifié"),
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"description": description,
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"posted": job.get("posted_at", ""),
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"type": job.get("schedule_type", ""),
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"source": job.get("via", ""),
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"link": job.get("link", ""),
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"highlights": {
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"qualifications": job.get("job_highlights", {}).get("Qualifications", [])[:3] if job.get("job_highlights", {}).get("Qualifications") else [],
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"responsibilities": job.get("job_highlights", {}).get("Responsibilities", [])[:3] if job.get("job_highlights", {}).get("Responsibilities") else []
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}
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}
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jobs_list.append(job_info)
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total_jobs_found = len(jobs_list)
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# Limiter à 8 résultats max pour éviter la troncature
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displayed_jobs = jobs_list[:8]
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# Format JSON-RPC 2.0 brut pour Mixtral
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raw_result = {
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"jsonrpc": "2.0",
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"result": {
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"success": True,
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"status": "SUCCESS",
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"message": f"✅ {total_jobs_found} offres trouvées ({len(displayed_jobs)} affichées)",
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"search_info": {
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"query": query,
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"location": location,
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"fallback_used": search_info.get("fallback_query") is not None
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},
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"jobs": {
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"total": total_jobs_found,
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"displayed": len(displayed_jobs),
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"results": displayed_jobs
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},
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"stats": {
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"with_salary": len([j for j in displayed_jobs if j.get("salary") and j.get("salary") != "Non spécifié"]),
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"companies": len(set([j.get("company", "") for j in displayed_jobs if j.get("company")]))
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}
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},
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"id": None
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}
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# Passer par Mixtral pour optimiser le format pour le LLM chat
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return format_jobs_with_mixtral(raw_result)
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except Exception as e:
|
| 352 |
return {
|