Update app.py

app.py

@@ -169,92 +169,92 @@ Models = {
 
 st.sidebar.markdown(f"### Selected Model: {Models[Lng]}")
 
-
-if not img_file.endswith(".pdf"):
-    cropped_img = Image.open(img_file)
-    if not realtime_update:
-        st.write("Double click to save crop")
-
-    # col1, col2 = st.columns(2)
-    # with col1:
-    #     st.subheader("Input: Upload and Crop Your Image")
-    # # Get a cropped image from the frontend
-    #     cropped_img = st_cropper(
-    #         img,
-    #         realtime_update=realtime_update,
-    #         box_color="#FF0000",
-    #         aspect_ratio=aspect_ratio,
-    #         should_resize_image=True,
-    #     )
-
-    # with col2:
-    # # Manipulate cropped image at will
-    #     st.subheader("Output: Preview and Analyze")
-    #     # _ = cropped_img.thumbnail((150, 150))
-    #     st.image(cropped_img)
-
-    button = st.sidebar.button("Run OCR")
-
-    if button:
-        with st.spinner('Running OCR...'):
-            if Lng == "Arabic":
-                ocr_text = predict_arabic(cropped_img)
-            elif Lng == "English":
-                ocr_text = predict_nougat(cropped_img)
-            elif Lng == "French":
-                ocr_text = predict_tesseract(cropped_img)
-            elif Lng == "Korean":
-                ocr_text = predict_english(cropped_img)
-            elif Lng == "Chinese":
-                ocr_text = predict_english(cropped_img)
-
-        st.subheader(f"OCR Results for {Lng}")
-        st.write(ocr_text)
-        text_file = BytesIO(ocr_text.encode())
-        st.download_button('Download Text', text_file,
-                           file_name='ocr_text.txt')
-
-elif input_file is not "" or img_file.endswith(".pdf"):
-    button = st.sidebar.button("Run OCR")
-
-    if button:
-        with st.spinner('Running OCR...'):
-            ocr_text = inference_nougat(None, input_file)
-            st.subheader(f"OCR Results for the PDF file")
+if img_file:
+    if not img_file.endswith(".pdf"):
+        cropped_img = Image.open(img_file)
+        if not realtime_update:
+            st.write("Double click to save crop")
+    
+        # col1, col2 = st.columns(2)
+        # with col1:
+        #     st.subheader("Input: Upload and Crop Your Image")
+        # # Get a cropped image from the frontend
+        #     cropped_img = st_cropper(
+        #         img,
+        #         realtime_update=realtime_update,
+        #         box_color="#FF0000",
+        #         aspect_ratio=aspect_ratio,
+        #         should_resize_image=True,
+        #     )
+    
+        # with col2:
+        # # Manipulate cropped image at will
+        #     st.subheader("Output: Preview and Analyze")
+        #     # _ = cropped_img.thumbnail((150, 150))
+        #     st.image(cropped_img)
+    
+        button = st.sidebar.button("Run OCR")
+    
+        if button:
+            with st.spinner('Running OCR...'):
+                if Lng == "Arabic":
+                    ocr_text = predict_arabic(cropped_img)
+                elif Lng == "English":
+                    ocr_text = predict_nougat(cropped_img)
+                elif Lng == "French":
+                    ocr_text = predict_tesseract(cropped_img)
+                elif Lng == "Korean":
+                    ocr_text = predict_english(cropped_img)
+                elif Lng == "Chinese":
+                    ocr_text = predict_english(cropped_img)
+    
+            st.subheader(f"OCR Results for {Lng}")
             st.write(ocr_text)
             text_file = BytesIO(ocr_text.encode())
             st.download_button('Download Text', text_file,
                                file_name='ocr_text.txt')
-
-        # openai.api_key = ""
-
-        # if "openai_model" not in st.session_state:
-        #     st.session_state["openai_model"] = "gpt-3.5-turbo"
-
-        # if "messages" not in st.session_state:
-        #     st.session_state.messages = []
-
-        # for message in st.session_state.messages:
-        #     with st.chat_message(message["role"]):
-        #         st.markdown(message["content"])
-
-        # if prompt := st.chat_input("How can I help?"):
-        #     st.session_state.messages.append({"role": "user", "content": ocr_text + prompt})
-        #     with st.chat_message("user"):
-        #         st.markdown(prompt)
-
-        #     with st.chat_message("assistant"):
-        #         message_placeholder = st.empty()
-        #         full_response = ""
-        #         for response in openai.ChatCompletion.create(
-        #             model=st.session_state["openai_model"],
-        #             messages=[
-        #                 {"role": m["role"], "content": m["content"]}
-        #                 for m in st.session_state.messages
-        #             ],
-        #             stream=True,
-        #         ):
-        #             full_response += response.choices[0].delta.get("content", "")
-        #             message_placeholder.markdown(full_response + "▌")
-        #         message_placeholder.markdown(full_response)
-        #     st.session_state.messages.append({"role": "assistant", "content": full_response})
+    
+    elif input_file is not "" or img_file.endswith(".pdf"):
+        button = st.sidebar.button("Run OCR")
+    
+        if button:
+            with st.spinner('Running OCR...'):
+                ocr_text = inference_nougat(None, input_file)
+                st.subheader(f"OCR Results for the PDF file")
+                st.write(ocr_text)
+                text_file = BytesIO(ocr_text.encode())
+                st.download_button('Download Text', text_file,
+                                   file_name='ocr_text.txt')
+    
+            # openai.api_key = ""
+    
+            # if "openai_model" not in st.session_state:
+            #     st.session_state["openai_model"] = "gpt-3.5-turbo"
+    
+            # if "messages" not in st.session_state:
+            #     st.session_state.messages = []
+    
+            # for message in st.session_state.messages:
+            #     with st.chat_message(message["role"]):
+            #         st.markdown(message["content"])
+    
+            # if prompt := st.chat_input("How can I help?"):
+            #     st.session_state.messages.append({"role": "user", "content": ocr_text + prompt})
+            #     with st.chat_message("user"):
+            #         st.markdown(prompt)
+    
+            #     with st.chat_message("assistant"):
+            #         message_placeholder = st.empty()
+            #         full_response = ""
+            #         for response in openai.ChatCompletion.create(
+            #             model=st.session_state["openai_model"],
+            #             messages=[
+            #                 {"role": m["role"], "content": m["content"]}
+            #                 for m in st.session_state.messages
+            #             ],
+            #             stream=True,
+            #         ):
+            #             full_response += response.choices[0].delta.get("content", "")
+            #             message_placeholder.markdown(full_response + "▌")
+            #         message_placeholder.markdown(full_response)
+            #     st.session_state.messages.append({"role": "assistant", "content": full_response})