Update app.py

app.py

@@ -91,45 +91,9 @@ def main():
     import streamlit as st
     if "photo" not in st.session_state:
         st.session_state["photo"]="not done"
-    a, b = st.columns([1, 1])
     def change_photo_state():
         st.session_state["photo"]="done"
     with st.container():
-        with a:
-            #import torch
-            from streamlit_option_menu import option_menu
-            from streamlit_chat import message as st_message
-            from transformers import BlenderbotTokenizer
-            from transformers import BlenderbotForConditionalGeneration
-            st.title("Simple Chatbot for fun!")
-            
-            @st.experimental_singleton
-            def get_models():
-                # it may be necessary for other frameworks to cache the model
-                # seems pytorch keeps an internal state of the conversation
-                model_name = "facebook/blenderbot-400M-distill"
-                tokenizer = BlenderbotTokenizer.from_pretrained(model_name)
-                model = BlenderbotForConditionalGeneration.from_pretrained(model_name)
-                return tokenizer, model
-            if "history" not in st.session_state:
-                st.session_state.history = []
-            st.title("Hello Chatbot")
-            def main():
-                st.text_input("Talk to the bot", key="input_text", on_change=generate_answer)
-                def generate_answer():
-                    tokenizer, model = get_models()
-                    user_message = st.session_state.input_text
-                    inputs = tokenizer(st.session_state.input_text, return_tensors="pt")
-                    result = model.generate(**inputs)
-                    message_bot = tokenizer.decode(
-                        result[0], skip_special_tokens=True
-                    )  # .replace("<s>", "").replace("</s>", "")
-                    st.session_state.history.append({"message": user_message, "is_user": True})
-                    st.session_state.history.append({"message": message_bot, "is_user": False})
-                from copyreg import clear_extension_cache
-                for chat in st.session_state.history:
-                    st_message(**chat) 
-        with b:
             c2, c3 = st.columns([1,1])
             message = st.text_input("Type your text here!")
             camera_photo = c2.camera_input("Capture a photo to summarize: ", on_change=change_photo_state)
@@ -195,19 +159,52 @@ def main():
                     if c8.button("Bangla"):
                         bansum(text)
                     if c9.button("English"): 
-                        engsum(text)  
-        # if st.button("English Text Generation"): 
-        #     def query(payload):
-        #     	response = requests.post(API_URL2, headers=headers2, json=payload)
-        #     	return response.json()
-                
-        #     out = query({
-        #     	"inputs": text,
-        #     })
-        #     if isinstance(out, list) and out[0].get("generated_text"):
-        #         text_output = out[0]["generated_text"]
-        #         st.success(text_output)
-        #         #text=text_output
+                        engsum(text) 
+             
+    with st.container():
+        from streamlit_chat import message as st_message
+        from transformers import BlenderbotTokenizer
+        from transformers import BlenderbotForConditionalGeneration
+        st.title("Simple Chatbot for fun!")
+        
+        @st.experimental_singleton
+        def get_models():
+            # it may be necessary for other frameworks to cache the model
+            # seems pytorch keeps an internal state of the conversation
+            model_name = "facebook/blenderbot-400M-distill"
+            tokenizer = BlenderbotTokenizer.from_pretrained(model_name)
+            model = BlenderbotForConditionalGeneration.from_pretrained(model_name)
+            return tokenizer, model
+        if "history" not in st.session_state:
+            st.session_state.history = []
+        st.title("Hello Chatbot")
+        def main():
+            st.text_input("Talk to the bot", key="input_text", on_change=generate_answer)
+            def generate_answer():
+                tokenizer, model = get_models()
+                user_message = st.session_state.input_text
+                inputs = tokenizer(st.session_state.input_text, return_tensors="pt")
+                result = model.generate(**inputs)
+                message_bot = tokenizer.decode(
+                    result[0], skip_special_tokens=True
+                )  # .replace("<s>", "").replace("</s>", "")
+                st.session_state.history.append({"message": user_message, "is_user": True})
+                st.session_state.history.append({"message": message_bot, "is_user": False})
+            from copyreg import clear_extension_cache
+            for chat in st.session_state.history:
+                st_message(**chat)
+    # if st.button("English Text Generation"): 
+    #     def query(payload):
+    #     	response = requests.post(API_URL2, headers=headers2, json=payload)
+    #     	return response.json()
+            
+    #     out = query({
+    #     	"inputs": text,
+    #     })
+    #     if isinstance(out, list) and out[0].get("generated_text"):
+    #         text_output = out[0]["generated_text"]
+    #         st.success(text_output)
+    #         #text=text_output
 
 
 if __name__ == "__main__":