Delete rag.py

rag.py

@@ -1,95 +0,0 @@
-import requests
-import os
-import google.generativeai as genai 
-
-from typing import List
-from utils import encode_image
-from PIL import Image
-
-class Rag:
-
-    def get_answer_from_gemini(self, query, imagePaths):
-
-        print(f"Querying Gemini for query={query}, imagePaths={imagePaths}")
-
-        try:
-            genai.configure(api_key=os.environ['GEMINI_API_KEY'])
-            model = genai.GenerativeModel('gemini-1.5-flash')
-            
-            images = [Image.open(path) for path in imagePaths]
-            
-            chat = model.start_chat()
-
-            response = chat.send_message([*images, query])
-
-            answer = response.text
-
-            print(answer)
-            
-            return answer
-        
-        except Exception as e:
-            print(f"An error occurred while querying Gemini: {e}")
-            return f"Error: {str(e)}"
-        
-
-    def get_answer_from_openai(self, query, imagesPaths):
-        print(f"Querying OpenAI for query={query}, imagesPaths={imagesPaths}")
-
-        try:    
-            payload = self.__get_openai_api_payload(query, imagesPaths)
-
-            headers = {
-                "Content-Type": "application/json",
-                "Authorization": f"Bearer {os.environ['OPENAI_API_KEY']}"
-            }
-    
-            response = requests.post(
-                url="https://api.openai.com/v1/chat/completions",
-                headers=headers,
-                json=payload
-            )
-            response.raise_for_status()  # Raise an HTTPError for bad responses
-    
-            answer = response.json()["choices"][0]["message"]["content"]
-    
-            print(answer)
-    
-            return answer
-    
-        except Exception as e:
-            print(f"An error occurred while querying OpenAI: {e}")
-            return None
-
-
-    def __get_openai_api_payload(self, query:str, imagesPaths:List[str]):
-        image_payload = []
-
-        for imagePath in imagesPaths:
-            base64_image = encode_image(imagePath)
-            image_payload.append({
-                "type": "image_url",
-                "image_url": {
-                    "url": f"data:image/jpeg;base64,{base64_image}"
-                }
-            })
-
-        payload = {
-            "model": "gpt-4o",
-            "messages": [
-                {
-                    "role": "user",
-                    "content": [
-                        {
-                            "type": "text",
-                            "text": query
-                        },
-                        *image_payload
-                    ]
-                }
-            ],
-            "max_tokens": 1024
-        }
-
-        return payload
-