Upload app.py

app.py

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+from pyexpat import model
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+from streamlit_lottie import st_lottie
+import json
+import pandas as pd
+import requests
+import torch
+import tensorflow as tf
+import streamlit as st
+from streamlit_option_menu import option_menu
+
+logo = "https://www.google.com/url?sa=i&url=https%3A%2F%2Ffr.depositphotos.com%2Fvector-images%2Frobot-logo.html&psig=AOvVaw14rAtmwJQVSpRFXFY6us7z&ust=1647274982461000&source=images&cd=vfe&ved=0CAsQjRxqFwoTCPjhzdO_w_YCFQAAAAAdAAAAABAD"
+st.set_page_config(page_icon = logo, page_title ="Bonsoir !", layout = "wide")
+
+@st.cache(allow_output_mutation=True)
+def load_tokenizer():
+        tokenizer = GPT2Tokenizer.from_pretrained("gpt2-large")
+        model = GPT2LMHeadModel.from_pretrained("gpt2-large", pad_token_id=tokenizer.eos_token_id)
+        return tokenizer
+
+@st.cache(allow_output_mutation=True)
+def load_model():
+        model = GPT2LMHeadModel.from_pretrained("gpt2-large", pad_token_id=tokenizer.eos_token_id)
+        return  model
+
+tokenizer =load_tokenizer()
+model = load_model()
+
+def reponse(question, temp=0.5, long=40):
+    
+    input_ids = tokenizer.encode(question, return_tensors='pt')
+    output = model.generate(input_ids, max_length=long, temperature =temp, num_beams=5, no_repeat_ngram_size=2, early_stopping=True)
+    rep = tokenizer.decode(output[0], skip_special_tokens=True)
+    return rep
+
+def load_animation(url: str):
+    r = requests.get(url)
+    if r.status_code != 200 :
+        return None
+    return r.json()
+
+url = "https://assets10.lottiefiles.com/packages/lf20_96bovdur.json"
+robot = load_animation(url)
+
+
+def contact_message():
+    st.header(":mailbox: Let's Get In Touch !")
+
+    name, message = st.columns((1,2))
+    with name:
+        contact_form = """<form action="https://formsubmit.co/[email protected]" method="POST">
+     <input type="text" name="name" placeholder = "Ton Nom" required>
+     <input type="email" name="email" placeholder = "Ton E-mail" required>
+     </form>"""
+        st.markdown(contact_form, unsafe_allow_html=True)
+
+    with message :
+        contact_form2 = """<form action="https://formsubmit.co/[email protected]" method="POST">
+        <textarea name="message" placeholder="Ecris moi !"></textarea>
+        <button type="submit">Send</button>
+    """
+        st.markdown(contact_form2, unsafe_allow_html=True)
+
+    with open("style2.txt") as f:
+        st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
+
+
+
+def robot():
+    robot = load_animation(url)
+    col1, col2, col3 = st.columns((5,1,5))
+
+    with col1:
+
+        st.subheader("Choose the length of my answer")
+        long = st.number_input("Be aware that long answers require more time to think !", min_value=10, max_value=250, step =10)
+
+        st.subheader("Ask me something")
+        question = st.text_input('Be aware that I speak only english for the moment !',max_chars = 60)
+        question = str(question)
+
+        ok = st.button('Ask me')
+        
+
+    with col3:
+        st_lottie(robot, speed=1, loop=True, quality = "low",height =300, width = 300)
+        if ok:
+            rep = reponse(question, long = long)
+            
+
+            rep_style = f'<p style="font-family:Lucida Handwriting; color:#00008B; font-size: 20px;">{rep}</p>'
+            st.markdown(rep_style, unsafe_allow_html=True)
+            
+
+
+
+
+def main():
+    st.title("Shall we chat ? Ask me a question")
+
+    with st.sidebar:
+
+        choice = option_menu(
+            menu_title = "Ask Me",
+            options = ["Question", "Envoie Moi Un Message"],
+            icons=["chat","envelope"],
+            menu_icon="robot"
+        )
+
+    if choice == "Envoie Moi Un Message":
+        contact_message()
+    
+    elif choice == "Question":
+        robot()
+
+    st.sidebar.subheader(":notebook_with_decorative_cover: Par Maxime Le Tutour")
+
+    st.sidebar.write(" :blue_book: [**Mon LinkedIn**](https://share.streamlit.io/mesmith027/streamlit_webapps/main/MC_pi/streamlit_app.py)", unsafe_allow_html =True)
+
+    
+    
+
+
+
+
+        
+
+
+       
+            
+
+
+
+print("ok")
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+if __name__ == '__main__':
+	main()