Update app.py

app.py

@@ -1,59 +1,41 @@
 import gradio as gr
-import requests
-import json
-import base64
+from PIL import Image
+import pytesseract
+import openai
+import os
 
-API_KEY = "your_api_key"  # Replace with your actual API key
+# Ensure you have your OpenAI API key set as an environment variable
+openai.api_key = os.getenv("OPENAI_API_KEY")
 
-def encode_image_to_base64(image):
-    encoded_image = base64.b64encode(image).decode("utf-8")
-    return encoded_image
-
-def extract_text_from_image(encoded_image):
-    url = "https://api.openai.com/v1/images/generations"
-    headers = {
-        "Content-Type": "application/json",
-        "Authorization": f"Bearer {API_KEY}",
-    }
-    data = {
-        "prompt": "Extract the text from the document image.",
-        "image": encoded_image,
-        "n": 1,
-        "size": "1024x1024",
-    }
-    response = requests.post(url, headers=headers, data=json.dumps(data))
-    extracted_text = response.json()["data"][0]["text"]
-    return extracted_text
-
-def summarize_text(text):
-    url = "https://api.openai.com/v1/completions"
-    headers = {
-        "Content-Type": "application/json",
-        "Authorization": f"Bearer {API_KEY}",
-    }
-    data = {
-        "prompt": f"Summarize the following text:\n\n{text}\n\nSummary:",
-        "max_tokens": 100,
-        "n": 1,
-        "stop": None,
-        "temperature": 0.7,
-    }
-    response = requests.post(url, headers=headers, data=json.dumps(data))
-    summary = response.json()["choices"][0]["text"]
-    return summary
-
-def document_summarizer(image):
-    encoded_image = encode_image_to_base64(image)
-    extracted_text = extract_text_from_image(encoded_image)
-    summary = summarize_text(extracted_text)
+def extract_and_summarize(image):
+    # Extract text from image
+    text = pytesseract.image_to_string(image)
+    
+    # Prepare the prompt for GPT-4
+    prompt = f"Please summarize the following text:\n\n{text}"
+    
+    # Call GPT-4 API for summarization
+    response = openai.ChatCompletion.create(
+        model="gpt-4",
+        messages=[
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": prompt}
+        ]
+    )
+    
+    # Extract summary from GPT-4 response
+    summary = response['choices'][0]['message']['content']
+    
     return summary
 
+# Define Gradio interface
 iface = gr.Interface(
-    fn=document_summarizer,
-    inputs=gr.inputs.Image(type="file", label="Upload Document Image"),
-    outputs="text",
-    title="Document Image Summarizer",
-    description="Upload an image of a document and get a summary of its content.",
+    fn=extract_and_summarize,
+    inputs=gr.Image(type="pil", label="Upload Document Image"),
+    outputs=gr.Textbox(label="Summarized Text"),
+    title="Document Summarizer",
+    description="Upload an image of a document and get a summarized text."
 )
 
-iface.launch()
+# Launch the interface
+iface.launch()