Update app.py

app.py

@@ -1,21 +1,23 @@
 import subprocess
 
-# Install packages using pip from Python
-subprocess.check_call(["pip", "install", "langchain_community", "langchain"])
-
+# Instalar un paquete utilizando pip desde Python
+subprocess.check_call(["pip", "install", "langchain_community","langchain"])
 # Import necessary libraries
 import streamlit as st
 from langchain.chains import ConversationChain
-from langchain_core.messages import AIMessage, HumanMessage
-from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain.chains.conversation.memory import ConversationEntityMemory
+from langchain.chains.conversation.prompt import ENTITY_MEMORY_CONVERSATION_TEMPLATE
 import os
+from getpass import getpass
+from langchain import HuggingFaceHub
 from langchain_community.llms import HuggingFaceEndpoint
-from langchain.memory import ChatMessageHistory
+
+
+
 
 # Set Streamlit page configuration
 st.set_page_config(page_title='🧠MemoryBot🤖', layout='wide')
-
-# Initialize session states
+# Initialize session states. Un session state es como un diccionario
 if "generated" not in st.session_state:
     st.session_state["generated"] = []
 if "past" not in st.session_state:
@@ -33,17 +35,19 @@ def get_text():
         (str): The text entered by the user
     """
     input_text = st.text_input("You: ", st.session_state["input"], key="input",
-                               placeholder="Your AI assistant here! Ask me anything ...",
-                               label_visibility='hidden')
+                            placeholder="Your AI assistant here! Ask me anything ...", 
+                            label_visibility='hidden')
     return input_text
 
-# Function to start a new chat
+# #parte para hacer un chat nuevo 
 def new_chat():
     """
     Clears session state and starts a new chat.
     """
-    save = ["User: " + past for past in reversed(st.session_state["past"])]
-    save.extend(["Bot: " + gen for gen in reversed(st.session_state["generated"])])
+    save = []
+    for i in range(len(st.session_state['generated'])-1, -1, -1):
+        save.append("User:" + st.session_state["past"][i])
+        save.append("Bot:" + st.session_state["generated"][i])        
     st.session_state["stored_session"].append(save)
     st.session_state["generated"] = []
     st.session_state["past"] = []
@@ -52,70 +56,66 @@ def new_chat():
     st.session_state.entity_memory.buffer.clear()
 
 # Add a button to start a new chat
-st.sidebar.button("New Chat", on_click=new_chat, type='primary')
+st.sidebar.button("New Chat", on_click = new_chat, type='primary')
+
+
+
 
 # Move K outside of the sidebar expander
-K = st.sidebar.number_input('(#) Summary of prompts to consider', min_value=3, max_value=1000)
+K = st.sidebar.number_input(' (#)Summary of prompts to consider', min_value=3, max_value=1000)
 
 # Set up the Streamlit app layout
 st.title("Personalized chatbot")
 
-# Create prompt
-prompt = ChatPromptTemplate.from_messages([
-    ("system", "You are a helpful assistant. Answer all questions to the best of your ability."),
-    MessagesPlaceholder(variable_name="messages"),
-])
 
-# Create an instance of HuggingFaceEndpoint
-llm = HuggingFaceEndpoint(repo_id='google/gemma-7b',
-                          temperature=0.5,
-                          model_kwargs={"max_length": 128},
-                          huggingfacehub_api_token=os.environ.get("HUGGINGFACEHUB_API_TOKEN", ""))
 
-# Get the user input
-user_input = get_text()
+# Create an OpenAI instance
+llm = HuggingFaceEndpoint(repo_id='mistral-community/Mixtral-8x22B-v0.1', 
+                          temperature=0.3, 
+                          model_kwargs = {"max_length":128},
+                          huggingfacehub_api_token = os.environ["HUGGINGFACEHUB_API_TOKEN"])
+
+
 
-# Create a ChatMessageHistory object if not already created
-if 'entity_memory' not in st.session_state:
-    st.session_state.entity_memory = ChatMessageHistory()
 
-# Create the ConversationChain object with the specified configuration
-conversation = ConversationChain(llm=llm,
-                                 memory=st.session_state.entity_memory)
 
 
 
-#Create prompt 
-prompt = ChatPromptTemplate.from_messages(
-    [
-        (
-            "system",
-            "You are a helpful assistant. Answer all questions to the best of your ability.",
-        ),
-        MessagesPlaceholder(variable_name="messages"),
-    ]
-)
+# Create a ConversationEntityMemory object if not already created
+if 'entity_memory' not in st.session_state:
+    st.session_state.entity_memory = ConversationEntityMemory(llm=llm, k=K )
+    
+    # Create the ConversationChain object with the specified configuration
+Conversation = ConversationChain(llm=llm, 
+                                 prompt=ENTITY_MEMORY_CONVERSATION_TEMPLATE,
+                                 memory=st.session_state.entity_memory
+    )  
+
 
-chain = prompt | conversation
+# Get the user input
+user_input = get_text()
 
 # Generate the output using the ConversationChain object and the user input, and add the input/output to the session
 if user_input:
-    output = chain.invoke({"messages": user_input})
-    st.session_state["past"].append(user_input)
-    st.session_state["generated"].append(output)
+    output = Conversation.run(input=user_input)  
+    st.session_state.past.append(user_input)  
+    st.session_state.generated.append(output)  
+
 
 # Display the conversation history using an expander, and allow the user to download it
 with st.expander("Conversation", expanded=True):
-    for past, gen in zip(reversed(st.session_state["past"]), reversed(st.session_state["generated"])):
-        st.info(f"User: {past}", icon="🧐")
-        st.success(f"Bot: {gen}", icon="🤖")
+    for i in range(len(st.session_state['generated'])-1, -1, -1):
+        st.info(st.session_state["past"][i],icon="🧐")
+        st.success(st.session_state["generated"][i], icon="🤖")
+
+
 
 # Display stored conversation sessions in the sidebar
-for i, sublist in enumerate(st.session_state.get("stored_session", [])):
-    with st.sidebar.expander(label=f"Conversation-Session:{i}"):
-        st.write(sublist)
+for i, sublist in enumerate(st.session_state.stored_session):
+        with st.sidebar.expander(label= f"Conversation-Session:{i}"):
+            st.write(sublist)
 
 # Allow the user to clear all stored conversation sessions
-if st.session_state.get("stored_session"):
+if st.session_state.stored_session:   
     if st.sidebar.checkbox("Clear-all"):
-        del st.session_state["stored_session"]
+        del st.session_state.stored_session