Update services/location_service.py

services/location_service.py

@@ -30,6 +30,31 @@ class LocationService:
             return {k: v for k, v in {"city": city, "state": state, "country": country}.items() if v is not None}
         else:
             return None
+
+    @staticmethod
+    def get_llm_response(system_prompt) -> str:
+        url = "https://api.openai.com/v1/chat/completions"
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {os.getenv('OPENAI_API_KEY')}",
+            "OpenAI-Organization": os.getenv('ORG_ID')
+        }
+    
+        data = {
+            "model": "gpt-4o-mini",
+            "max_tokens": 2000,
+            "messages": [{"role": "user", "content": f"{system_prompt}"}],
+            "temperature": 0.0
+        }
+        try:
+            response = requests.post(url, headers=headers, json=data)
+            output = response.json()
+        except Exception as e:
+            print(f"Error Occurred {e}")
+            return f"Error Occurred {e}"
+    
+        return output['choices'][0]['message']['content']
+    
     @staticmethod
     def system_prompt(location : str) -> str:
         return f"""You are a Text Analyser where you will extract city , state , country from given piece of text given below.You will strictly extract following keys from the text country , state , city.
@@ -58,7 +83,7 @@ class LocationService:
         if location:
             # Assuming `app.nlp` is already initialized elsewhere and accessible
             llm_prompt = LocationService.system_prompt(location)
-            response = model.generate_content(llm_prompt)
+            response = LocationService.get_llm_response(llm_prompt)
             # Extract city, state, and country using the logic from extract_location_entities
             location_entities = json.loads(response.text)