Update app.py

app.py

@@ -23,19 +23,19 @@ st.set_page_config(
 
 
 # Split large response into smaller chunks (for translation)
-# def split_text_into_chunks(text, max_length=450):
-#     lines = text.split('\n')
-#     chunks = []
-#     current = ""
-#     for line in lines:
-#         if len(current) + len(line) + 1 <= max_length:
-#             current += line + '\n'
-#         else:
-#             chunks.append(current.strip())
-#             current = line + '\n'
-#     if current:
-#         chunks.append(current.strip())
-#     return chunks
+def split_text_into_chunks(text, max_length=450):
+    lines = text.split('\n')
+    chunks = []
+    current = ""
+    for line in lines:
+        if len(current) + len(line) + 1 <= max_length:
+            current += line + '\n'
+        else:
+            chunks.append(current.strip())
+            current = line + '\n'
+    if current:
+        chunks.append(current.strip())
+    return chunks
 
 
 def set_background(image_file):
@@ -166,21 +166,33 @@ if uploaded_file:
 
     # Prompt LLM
     template = """
-        You are a helpful medical assistant.
-
-        Here is a prescription text extracted from an image:
-
-        {prescription_text}
-
-        Please do the following:
-
-        1. Extract only the medicine names mentioned in the prescription (ignore any other text).
-        2. For each medicine, provide:
-           - When to take it (timing and dosage)
-           - Possible side effects
-           - Any special instructions
-
-        Format your answer as bullet points, listing only medicines and their details.
+    You are a helpful and structured medical assistant.
+    
+    Below is a prescription text extracted from an image:
+    
+    {prescription_text}
+    
+    Your tasks:
+    
+    1. Identify and list only the **medicine names** mentioned (ignore other irrelevant text).
+    2. For each identified medicine, provide the following:
+       - Dosage and Timing
+       - Possible Side Effects
+       - Special Instructions
+    
+    🧾 Format your response clearly and neatly as follows:
+    
+    - Medicine Name 1
+      - Dosage and Timing: ...
+      - Side Effects: ...
+      - Special Instructions: ...
+    
+    - Medicine Name 2
+      - Dosage and Timing: ...
+      - Side Effects: ...
+      - Special Instructions: ...
+    
+    Ensure each medicine starts with a new bullet point and all details are on separate lines.
     """
     
     prompt = PromptTemplate(input_variables=["prescription_text"], template=template)
@@ -211,7 +223,7 @@ if uploaded_file:
         with st.spinner("Analyzing with LLM..."):
             response = chain.run(prescription_text=text)
         st.markdown("#### 💡 AI-based Medicine Analysis")
-        st.success(response)
+        st.text_area("LLM Output", response, height=600)
 
         # Save txt and image
         txt_path = "medicine_analysis.txt"
@@ -229,35 +241,35 @@ if uploaded_file:
             with open(img_path, "rb") as img_file:
                 st.download_button("🖼️ English Image", data=img_file, file_name="medicine_analysis.png", mime="image/png")
 
-    # if response and st.button("🌐 Translate to Hindi"):
-    #     with st.spinner("Translating to Hindi..."):
-    #         target_lang = "hi"
-    #         translator = Translator(to_lang=target_lang)
-    #         chunks = split_text_into_chunks(response, max_length=450)
-
-    #         hindi_chunks = []
-    #         for chunk in chunks:
-    #             try:
-    #                 translated = translator.translate(chunk)
-    #                 hindi_chunks.append(translated)
-    #             except Exception as e:
-    #                 hindi_chunks.append("[Error translating chunk]")
-
-    #         hindi_text = "\n\n".join(hindi_chunks)
-
-    #     st.markdown("#### 🌐 Hindi Translation")
-    #     st.text_area("Translated Output (Hindi)", hindi_text, height=300)
-
-    #     hindi_img_path = "hindi_output.png"
-    #     save_text_as_image(hindi_text, hindi_img_path)
-
-    #     st.markdown("#### 📥 Download (Hindi)")
-    #     col3, col4 = st.columns(2)
-    #     with col3:
-    #         st.download_button("⬇️ Hindi TXT", data=hindi_text.encode(), file_name="hindi_medicine_analysis.txt")
-    #     with col4:
-    #         with open(hindi_img_path, "rb") as img_file:
-    #             st.download_button("🖼️ Hindi Image", data=img_file, file_name="hindi_medicine_analysis.png", mime="image/png")
+    if response and st.button("🌐 Translate to Hindi"):
+        with st.spinner("Translating to Hindi..."):
+            target_lang = "hi"
+            translator = Translator(to_lang=target_lang)
+            chunks = split_text_into_chunks(response, max_length=450)
+
+            hindi_chunks = []
+            for chunk in chunks:
+                try:
+                    translated = translator.translate(chunk)
+                    hindi_chunks.append(translated)
+                except Exception as e:
+                    hindi_chunks.append("[Error translating chunk]")
+
+            hindi_text = "\n\n".join(hindi_chunks)
+
+        st.markdown("#### 🌐 Hindi Translation")
+        st.text_area("Translated Output (Hindi)", hindi_text, height=600)
+
+        hindi_img_path = "hindi_output.png"
+        save_text_as_image(hindi_text, hindi_img_path)
+
+        st.markdown("#### 📥 Download (Hindi)")
+        col3, col4 = st.columns(2)
+        with col3:
+            st.download_button("⬇️ Hindi TXT", data=hindi_text.encode(), file_name="hindi_medicine_analysis.txt")
+        with col4:
+            with open(hindi_img_path, "rb") as img_file:
+                st.download_button("🖼️ Hindi Image", data=img_file, file_name="hindi_medicine_analysis.png", mime="image/png")
 
     try:
         os.remove(orig_path)