Update app.py

app.py

@@ -1,3 +1,177 @@
+import streamlit as st
+import openai
+import random
+
+# Fetch the OpenAI API key from Streamlit secrets
+openai_api_key = st.secrets["openai_api_key"]
+
+# Initialize the OpenAI service with API key
+openai.api_key = openai_api_key
+
+# Fetch Pinecone API key and environment from Streamlit secrets
+# pinecone_api_key = st.secrets["pinecone_api_key"]
+pinecone_api_key = '555c0e70-331d-4b43-aac7-5b3aac5078d6'
+# pinecone_environment = st.secrets["pinecone_environment"]
+
+# AUTHENTICATE/INITIALIZE PINCONE SERVICE
+from pinecone import Pinecone
+pc = Pinecone(api_key=pinecone_api_key)
+# pc = Pinecone (api_key= 'YOUR_API_KEY')
+
+# Define the name of the Pinecone index
+index_name = 'mimtssinkqa'
+
+# Initialize the OpenAI embeddings object 
+from langchain_openai import OpenAIEmbeddings
+embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)
+
+# LOAD VECTOR STORE FROM EXISTING INDEX
+from langchain_community.vectorstores import Pinecone
+vector_store = Pinecone.from_existing_index(index_name='mimtssinkqa', embedding=embeddings)
+
+def ask_with_memory(vector_store, query, chat_history=[]):
+    from langchain_openai import ChatOpenAI
+    from langchain.chains import ConversationalRetrievalChain
+    from langchain.memory import ConversationBufferMemory
+
+    from langchain.prompts import ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate
+
+    llm = ChatOpenAI(model_name='gpt-3.5-turbo', temperature=0.5)
+    
+    retriever = vector_store.as_retriever(search_type='similarity', search_kwargs={'k': 3})
+    
+    memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
+
+    system_template = r'''
+    Use the following pieces of context to answer the user's question. The title of the article is Intensifying literacy Instruction: Essential Practices. Do not mention the Header unless asked.
+    ----------------
+    Context: ```{context}```
+    '''
+
+    user_template = '''
+    Question: ```{question}```
+    Chat History: ```{chat_history}```
+    '''
+
+    messages= [
+        SystemMessagePromptTemplate.from_template(system_template),
+        HumanMessagePromptTemplate.from_template(user_template)
+    ]
+
+    qa_prompt = ChatPromptTemplate.from_messages (messages)
+
+    chain = ConversationalRetrievalChain.from_llm(llm=llm, retriever=retriever, memory=memory,chain_type='stuff', combine_docs_chain_kwargs={'prompt': qa_prompt}, verbose=False
+    )
+
+    result = chain.invoke({'question': query, 'chat_history': st.session_state['history']})
+    # Append to chat history as a dictionary
+    st.session_state['history'].append((query, result['answer']))
+    
+    return (result['answer'])
+
+# Initialize chat history
+if 'history' not in st.session_state:
+    st.session_state['history'] = []
+    
+# # STREAMLIT APPLICATION SETUP WITH PASSWORD
+
+# Define the correct password
+# correct_password = "MiBLSi"
+
+#Add the image with a specified width
+image_width = 300  # Set the desired width in pixels
+st.image('MTSS.ai_Logo.png', width=image_width)
+st.subheader('Ink QA™ | Dynamic PDFs')
+
+# Using Markdown for formatted text
+st.markdown("""
+Resource: **Intensifying Literacy Instruction: Essential Practices**
+""", unsafe_allow_html=True)
+
+with st.sidebar:
+    # Password input field
+    # password = st.text_input("Enter Password:", type="password")
+    
+    st.image('mimtss.png', width=200)
+    st.image('Literacy_Cover.png', width=200)
+    st.link_button("View | Download", "https://mimtsstac.org/sites/default/files/session-documents/Intensifying%20Literacy%20Instruction%20-%20Essential%20Practices%20%28NATIONAL%29.pdf")
+        
+    Audio_Header_text = """
+    **Tune into Dr. St. Martin's introduction**"""
+    st.markdown(Audio_Header_text)
+        
+    # Path or URL to the audio file
+    audio_file_path = 'Audio_Introduction_Literacy.m4a'
+    # Display the audio player widget
+    st.audio(audio_file_path, format='audio/mp4', start_time=0)
+        
+    # Citation text with Markdown formatting
+    citation_Content_text = """
+    **Citation**  
+    St. Martin, K., Vaughn, S., Troia, G., Fien, & H., Coyne, M. (2023). *Intensifying literacy instruction: Essential practices, Version 2.0*. Lansing, MI: MiMTSS Technical Assistance Center, Michigan Department of Education.
+        
+    **Table of Contents**  
+    * **Introduction**: pg. 1  
+    * **Intensifying Literacy Instruction: Essential Practices**: pg. 4  
+    * **Purpose**: pg. 4  
+    * **Practice 1**: Knowledge and Use of a Learning Progression for Developing Skilled Readers and Writers: pg. 6
+    * **Practice 2**: Design and Use of an Intervention Platform as the Foundation for Effective Intervention: pg. 13
+    * **Practice 3**: On-going Data-Based Decision Making for Providing and Intensifying Interventions: pg. 16
+    * **Practice 4**: Adaptations to Increase the Instructional Intensity of the Intervention: pg. 20
+    * **Practice 5**: Infrastructures to Support Students with Significant and Persistent Literacy Needs: pg. 24
+    * **Motivation and Engagement**: pg. 28
+    * **Considerations for Understanding How Students' Learning and Behavior are Enhanced**: pg. 28
+    * **Summary**: pg. 29
+    * **Endnotes**: pg. 30
+    * **Acknowledgment**: pg. 39
+    """
+    st.markdown(citation_Content_text)
+
+# if password == correct_password:
+# Define a list of possible placeholder texts
+placeholders = [
+    'Example: Summarize the article in 200 words or less',
+    'Example: What are the essential practices?',
+    'Example: I am a teacher, why is this resource important?',
+    'Example: How can this resource support my instruction in reading and writing?',
+    'Example: Does this resource align with the learning progression for developing skilled readers and writers?',
+    'Example: How does this resource address the needs of students scoring below the 20th percentile?',
+    'Example: Are there assessment tools included in this resource to monitor student progress?',
+    'Example: Does this resource provide guidance on data collection and analysis for monitoring student outcomes?',
+    "Example: How can this resource be used to support students' social-emotional development?",
+    "Example: How does this resource align with the district's literacy goals and objectives?",
+    'Example: What research and evidence support the effectiveness of this resource?',
+    'Example: Does this resource provide guidance on implementation fidelity'
+]
+
+# Select a random placeholder from the list
+if 'placeholder' not in st.session_state:
+    st.session_state.placeholder = random.choice(placeholders)
+    
+q = st.text_input(label='Ask a question or make a request ', value='', placeholder=st.session_state.placeholder)
+# q = st.text_input(label='Ask a question or make a request ', value='')
+    
+if q:
+    with st.spinner('Thinking...'):
+        answer = ask_with_memory(vector_store, q, st.session_state.history)
+    
+    # Display the response in a text area
+    st.text_area('Response: ', value=answer, height=400, key="response_text_area")
+    
+    st.success('Powered by MTSS GPT. AI can make mistakes. Consider checking important information.')
+
+    # Prepare chat history text for display
+    # history_text = "\n\n".join(f"Q: {entry[0]}\nA: {entry[1]}" for entry in st.session_state.history)
+    # Prepare chat history text for display in reverse order
+    history_text = "\n\n".join(f"Q: {entry[0]}\nA: {entry[1]}" for entry in reversed(st.session_state.history))
+
+    # Display chat history
+    st.text_area('Chat History', value=history_text, height=800)
+
+
+
+
+
 # import streamlit as st
 # import pinecone
 # from langchain.embeddings.openai import OpenAIEmbeddings
@@ -170,171 +344,3 @@
 
 
 
-import streamlit as st
-import openai
-import random
-
-# Fetch the OpenAI API key from Streamlit secrets
-openai_api_key = st.secrets["openai_api_key"]
-
-# Initialize the OpenAI service with API key
-openai.api_key = openai_api_key
-
-# Fetch Pinecone API key and environment from Streamlit secrets
-pinecone_api_key = st.secrets["pinecone_api_key"]
-# pinecone_environment = st.secrets["pinecone_environment"]
-
-# AUTHENTICATE/INITIALIZE PINCONE SERVICE
-from pinecone import Pinecone
-# pc = Pinecone(api_key=pinecone_api_key)
-# pc = Pinecone (api_key= 'YOUR_API_KEY')
-
-# Define the name of the Pinecone index
-index_name = 'mimtssinkqa'
-
-# Initialize the OpenAI embeddings object 
-from langchain_openai import OpenAIEmbeddings
-embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)
-
-# LOAD VECTOR STORE FROM EXISTING INDEX
-from langchain_community.vectorstores import Pinecone
-vector_store = Pinecone.from_existing_index(index_name='mimtssinkqa', embedding=embeddings)
-
-def ask_with_memory(vector_store, query, chat_history=[]):
-    from langchain_openai import ChatOpenAI
-    from langchain.chains import ConversationalRetrievalChain
-    from langchain.memory import ConversationBufferMemory
-
-    from langchain.prompts import ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate
-
-    llm = ChatOpenAI(model_name='gpt-3.5-turbo', temperature=0.5)
-    
-    retriever = vector_store.as_retriever(search_type='similarity', search_kwargs={'k': 3})
-    
-    memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
-
-    system_template = r'''
-    Use the following pieces of context to answer the user's question. The title of the article is Intensifying literacy Instruction: Essential Practices. Do not mention the Header unless asked.
-    ----------------
-    Context: ```{context}```
-    '''
-
-    user_template = '''
-    Question: ```{question}```
-    Chat History: ```{chat_history}```
-    '''
-
-    messages= [
-        SystemMessagePromptTemplate.from_template(system_template),
-        HumanMessagePromptTemplate.from_template(user_template)
-    ]
-
-    qa_prompt = ChatPromptTemplate.from_messages (messages)
-
-    chain = ConversationalRetrievalChain.from_llm(llm=llm, retriever=retriever, memory=memory,chain_type='stuff', combine_docs_chain_kwargs={'prompt': qa_prompt}, verbose=False
-    )
-
-    result = chain.invoke({'question': query, 'chat_history': st.session_state['history']})
-    # Append to chat history as a dictionary
-    st.session_state['history'].append((query, result['answer']))
-    
-    return (result['answer'])
-
-# Initialize chat history
-if 'history' not in st.session_state:
-    st.session_state['history'] = []
-    
-# # STREAMLIT APPLICATION SETUP WITH PASSWORD
-
-# Define the correct password
-# correct_password = "MiBLSi"
-
-#Add the image with a specified width
-image_width = 300  # Set the desired width in pixels
-st.image('MTSS.ai_Logo.png', width=image_width)
-st.subheader('Ink QA™ | Dynamic PDFs')
-
-# Using Markdown for formatted text
-st.markdown("""
-Resource: **Intensifying Literacy Instruction: Essential Practices**
-""", unsafe_allow_html=True)
-
-with st.sidebar:
-    # Password input field
-    # password = st.text_input("Enter Password:", type="password")
-    
-    st.image('mimtss.png', width=200)
-    st.image('Literacy_Cover.png', width=200)
-    st.link_button("View | Download", "https://mimtsstac.org/sites/default/files/session-documents/Intensifying%20Literacy%20Instruction%20-%20Essential%20Practices%20%28NATIONAL%29.pdf")
-        
-    Audio_Header_text = """
-    **Tune into Dr. St. Martin's introduction**"""
-    st.markdown(Audio_Header_text)
-        
-    # Path or URL to the audio file
-    audio_file_path = 'Audio_Introduction_Literacy.m4a'
-    # Display the audio player widget
-    st.audio(audio_file_path, format='audio/mp4', start_time=0)
-        
-    # Citation text with Markdown formatting
-    citation_Content_text = """
-    **Citation**  
-    St. Martin, K., Vaughn, S., Troia, G., Fien, & H., Coyne, M. (2023). *Intensifying literacy instruction: Essential practices, Version 2.0*. Lansing, MI: MiMTSS Technical Assistance Center, Michigan Department of Education.
-        
-    **Table of Contents**  
-    * **Introduction**: pg. 1  
-    * **Intensifying Literacy Instruction: Essential Practices**: pg. 4  
-    * **Purpose**: pg. 4  
-    * **Practice 1**: Knowledge and Use of a Learning Progression for Developing Skilled Readers and Writers: pg. 6
-    * **Practice 2**: Design and Use of an Intervention Platform as the Foundation for Effective Intervention: pg. 13
-    * **Practice 3**: On-going Data-Based Decision Making for Providing and Intensifying Interventions: pg. 16
-    * **Practice 4**: Adaptations to Increase the Instructional Intensity of the Intervention: pg. 20
-    * **Practice 5**: Infrastructures to Support Students with Significant and Persistent Literacy Needs: pg. 24
-    * **Motivation and Engagement**: pg. 28
-    * **Considerations for Understanding How Students' Learning and Behavior are Enhanced**: pg. 28
-    * **Summary**: pg. 29
-    * **Endnotes**: pg. 30
-    * **Acknowledgment**: pg. 39
-    """
-    st.markdown(citation_Content_text)
-
-# if password == correct_password:
-# Define a list of possible placeholder texts
-placeholders = [
-    'Example: Summarize the article in 200 words or less',
-    'Example: What are the essential practices?',
-    'Example: I am a teacher, why is this resource important?',
-    'Example: How can this resource support my instruction in reading and writing?',
-    'Example: Does this resource align with the learning progression for developing skilled readers and writers?',
-    'Example: How does this resource address the needs of students scoring below the 20th percentile?',
-    'Example: Are there assessment tools included in this resource to monitor student progress?',
-    'Example: Does this resource provide guidance on data collection and analysis for monitoring student outcomes?',
-    "Example: How can this resource be used to support students' social-emotional development?",
-    "Example: How does this resource align with the district's literacy goals and objectives?",
-    'Example: What research and evidence support the effectiveness of this resource?',
-    'Example: Does this resource provide guidance on implementation fidelity'
-]
-
-# Select a random placeholder from the list
-if 'placeholder' not in st.session_state:
-    st.session_state.placeholder = random.choice(placeholders)
-    
-q = st.text_input(label='Ask a question or make a request ', value='', placeholder=st.session_state.placeholder)
-# q = st.text_input(label='Ask a question or make a request ', value='')
-    
-if q:
-    with st.spinner('Thinking...'):
-        answer = ask_with_memory(vector_store, q, st.session_state.history)
-    
-    # Display the response in a text area
-    st.text_area('Response: ', value=answer, height=400, key="response_text_area")
-    
-    st.success('Powered by MTSS GPT. AI can make mistakes. Consider checking important information.')
-
-    # Prepare chat history text for display
-    # history_text = "\n\n".join(f"Q: {entry[0]}\nA: {entry[1]}" for entry in st.session_state.history)
-    # Prepare chat history text for display in reverse order
-    history_text = "\n\n".join(f"Q: {entry[0]}\nA: {entry[1]}" for entry in reversed(st.session_state.history))
-
-    # Display chat history
-    st.text_area('Chat History', value=history_text, height=800)