Update app.py

app.py

@@ -1,38 +1,36 @@
 from transformers import BlipForQuestionAnswering, AutoProcessor
 from PIL import Image
 import gradio as gr
-import requests  # To call Groq API
+import openai  # For OpenAI API
 
 # Load the BLIP model and processor
 model = BlipForQuestionAnswering.from_pretrained("Salesforce/blip-vqa-base")
 processor = AutoProcessor.from_pretrained("Salesforce/blip-vqa-base")
 
-# Define Groq API details (Replace with actual API endpoint and key)
-GROQ_API_ENDPOINT = "https://api.groq.com/v1/completions"
-GROQ_API_KEY = "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"  # Replace with your actual Groq API key
+# Set your OpenAI API key
+openai.api_key = "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"  # Replace with your OpenAI API key
 
-# Function to generate the initial answer with BLIP and expand it with Groq API
+# Function to generate the initial answer with BLIP and expand it with OpenAI API
 def qna(image, question):
     # Step 1: Get initial short answer from BLIP
     inputs = processor(image, question, return_tensors="pt")
     out = model.generate(**inputs)
     short_answer = processor.decode(out[0], skip_special_tokens=True)
 
-    # Step 2: Construct prompt for Groq API
+    # Step 2: Construct prompt for OpenAI API
     prompt = f"Question: {question}\nShort Answer: {short_answer}\nProvide a detailed explanation based on this answer."
 
-    # Step 3: Send prompt to Groq API for a paragraph-length answer
-    response = requests.post(
-        GROQ_API_ENDPOINT,
-        headers={"Authorization": f"Bearer {GROQ_API_KEY}"},
-        json={"prompt": prompt, "max_tokens": 200}  # Adjust max_tokens as needed
-    )
-
-    if response.status_code == 200:
-        # Extract generated paragraph from Groq API response
-        detailed_answer = response.json().get("choices")[0].get("text")
-    else:
-        detailed_answer = "Failed to get response from Groq API."
+    # Step 3: Send prompt to OpenAI API for a paragraph-length answer
+    try:
+        response = openai.Completion.create(
+            engine="text-davinci-003",  # Specify model
+            prompt=prompt,
+            max_tokens=200  # Adjust max_tokens as needed for response length
+        )
+        detailed_answer = response.choices[0].text.strip()
+    except Exception as e:
+        print(f"Exception occurred: {e}")
+        detailed_answer = "Failed to get response from OpenAI API."
 
     return detailed_answer