Delete app.py

app.py

@@ -1,79 +0,0 @@
-import streamlit as st
-import json
-import time
-import requests
-from langchain.chains import LLMChain
-from langchain_core.prompts import ChatPromptTemplate, HumanMessagePromptTemplate, MessagesPlaceholder
-from langchain_core.messages import SystemMessage
-from langchain.chains.conversation.memory import ConversationBufferWindowMemory
-from langchain_groq import ChatGroq
-
-
-# Changement du logo et du titre de l'application
-st.set_page_config(page_title="LOG-CHAT", page_icon="BEAC.jpg", layout="centered", menu_items=None)
-st.image("BEAC.jpg")
-# page de chargement
-query_params = st.experimental_get_query_params()
-page = query_params.get("page", ["chatbot"])[0]
-
-
-st.markdown('<div class="content">', unsafe_allow_html=True)
-
-
-if page == "chatbot":
-    st.header("LOG-CHAT")
-
-    def main():
-        groq_api_key = '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'  # Use environment variables or secrets management for API keys
-        st.markdown('<div id="chatbot"></div>', unsafe_allow_html=True)
-        
-        system_prompt = st.text_input("System prompt:", "You are a helpful assistant.")
-        model = st.selectbox('Choose a model', ['llama3-8b-8192', 'mixtral-8x7b-32768', 'gemma-7b-it'])
-        conversational_memory_length = st.slider('Conversational memory length:', 1, 10, value=5)
-
-        memory = ConversationBufferWindowMemory(k=conversational_memory_length, memory_key="chat_history", return_messages=True)
-
-        user_question = st.text_input("Ask me a question:")
-        send_question_to_ai = st.button("Send")
-
-        if 'chat_history' not in st.session_state:
-            st.session_state.chat_history = []
-        else:
-            for message in st.session_state.chat_history:
-                memory.save_context({'input': message['human']}, {'output': message['AI']})
-
-        groq_chat = ChatGroq(groq_api_key=groq_api_key, model_name=model)
-
-        if send_question_to_ai:
-            prompt = ChatPromptTemplate.from_messages(
-                [
-                    SystemMessage(content=system_prompt),
-                    MessagesPlaceholder(variable_name="chat_history"),
-                    HumanMessagePromptTemplate.from_template("{human_input}")
-                ]
-            )
-
-            conversation = LLMChain(
-                llm=groq_chat,
-                prompt=prompt,
-                verbose=True,
-                memory=memory
-            )
-
-            response = conversation.predict(human_input=user_question)
-            message = {'human': user_question, 'AI': response}
-            st.session_state.chat_history.append(message)
-            st.write("chatbot:", response)
-
-    if __name__ == "__main__":
-        main()
-
-
-
-# Footer
-st.markdown("""
-    <footer class="footer">
-        <p>Contact us: <a href="mailto:[email protected]">[email protected]</a></p>
-        <p>© 2024 Your Company. All rights reserved.</p>
-    </footer>
-""", unsafe_allow_html=True)