Update app.py

app.py

@@ -6,6 +6,8 @@ import json
 import requests
 from PIL import Image
 from openai import OpenAI
+import easyocr
+from io import BytesIO
 
 # ------------------ App Configuration ------------------
 st.set_page_config(page_title="Document AI Assistant", layout="wide")
@@ -21,6 +23,7 @@ if not OPENAI_API_KEY or not ASSISTANT_ID:
     st.stop()
 
 client = OpenAI(api_key=OPENAI_API_KEY)
+reader = easyocr.Reader(['en'], gpu=False)
 
 # ------------------ Session State Initialization ------------------
 if "messages" not in st.session_state:
@@ -43,11 +46,47 @@ if st.sidebar.button("🔄 Clear Chat"):
 
 show_image = st.sidebar.checkbox("📖 Show Document Image", value=True)
 
-# ------------------ Load Structured Summary/FAQ ------------------
-with open("51940670-Manual-of-Surgical-Pathology-Third-Edition_1_structured_output.json", "r") as f:
-    structured_data = json.load(f)  # This is a list of dicts, not a dict
-
-# ------------------ Three-Column Layout ------------------
+# ------------------ OCR + GPT Summary & FAQ Generator ------------------
+def generate_summary_and_faq_from_image_easyocr(image_url):
+    try:
+        response = requests.get(image_url, stream=True)
+        image = Image.open(BytesIO(response.content)).convert("RGB")
+
+        result = reader.readtext(np.array(image), detail=0)
+        extracted_text = "\n".join(result)
+
+        if not extracted_text.strip():
+            return "No readable text found in image.", []
+
+        prompt = f"""
+You are a pathology assistant. Given this OCR-extracted text from a pathology textbook page, do the following:
+1. Provide a concise summary of the main point (1-2 sentences).
+2. Provide two FAQs with brief answers.
+
+Text:
+{extracted_text[:3000]}
+
+Return only JSON:
+{{
+  "summary": "...",
+  "faqs": [
+    {{"question": "...", "answer": "..."}},
+    {{"question": "...", "answer": "..."}}
+  ]
+}}
+"""
+        response = client.chat.completions.create(
+            model="gpt-3.5-turbo",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.3
+        )
+        result = json.loads(response.choices[0].message.content)
+        return result.get("summary", "No summary generated."), result.get("faqs", [])
+
+    except Exception as e:
+        return f"Error generating summary: {e}", []
+
+# ------------------ Layout ------------------
 left, center, right = st.columns([1, 2, 1])
 
 # ------------------ Left Column: Document Image ------------------
@@ -123,24 +162,15 @@ with center:
         except Exception as e:
             st.error(f"❌ Error: {str(e)}")
 
-# ------------------ Right Column: Summary and FAQ ------------------
+# ------------------ Right Column: OCR-Based Summary + FAQ ------------------
 with right:
-    st.subheader("📌 Summary")
+    st.subheader("📌 Summary & FAQ (via EasyOCR)")
 
-    # Parse page number from image URL if available
     if st.session_state.image_url:
-        match = re.search(r'page_(\d+)', st.session_state.image_url)
-        page_number = int(match.group(1)) if match else 151
-    else:
-        page_number = 151  # default
-
-    # Get entry from structured data
-    page_entry = next((entry for entry in structured_data if entry.get("page") == page_number), None)
-    if page_entry:
-        summary_text = page_entry.get("summary", "No summary available.")
-        faq_list = page_entry.get("faqs", [])
+        with st.spinner("🔍 Extracting text and generating summary..."):
+            summary_text, faq_list = generate_summary_and_faq_from_image_easyocr(st.session_state.image_url)
     else:
-        summary_text = "No summary available."
+        summary_text = "No image selected."
         faq_list = []
 
     st.markdown(summary_text)
@@ -150,4 +180,4 @@ with right:
         for faq in faq_list:
             st.markdown(f"**Q:** {faq.get('question', '')}\n\n**A:** {faq.get('answer', '')}")
     else:
-        st.info("No FAQs available for this page.")
+        st.info("No FAQs available or generated from this page.")