Upload app.py

app.py

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+import streamlit as st
+import pinecone
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import Pinecone, Chroma
+from langchain.chains import RetrievalQA
+from langchain.chat_models import ChatOpenAI
+import tiktoken
+import random
+
+# Fetch the OpenAI API key from Streamlit secrets
+openai_api_key = st.secrets["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"]
+
+# Initialize Pinecone
+pinecone.init(api_key=pinecone_api_key, environment=pinecone_environment)
+
+# Define the name of the Pinecone index
+index_name = 'mi-resource-qa'
+
+# Initialize the OpenAI embeddings object with the hardcoded API key
+embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)
+
+# Define functions
+def insert_or_fetch_embeddings(index_name):
+    if index_name in pinecone.list_indexes():
+        vector_store = Pinecone.from_existing_index(index_name, embeddings)
+        return vector_store
+    else:
+        raise ValueError(f"Index {index_name} does not exist. Please create it before fetching.")
+
+# Initialize or fetch Pinecone vector store
+vector_store = insert_or_fetch_embeddings(index_name)
+
+# Define the metadata for filtering
+# metadata = {'source': '/Users/cheynelevesseur/Desktop/Python_Code/Projects/LLM/Intensifying Literacy Instruction - Essential Practices (NATIONAL).pdf'}
+
+# calculate embedding cost using tiktoken
+def calculate_embedding_cost(text):
+    import tiktoken
+    enc = tiktoken.encoding_for_model('text-embedding-ada-002')
+    total_tokens = len(enc.encode(text))
+    # print(f'Total Tokens: {total_tokens}')
+    # print(f'Embedding Cost in USD: {total_tokens / 1000 * 0.0004:.6f}')
+    return total_tokens, total_tokens / 1000 * 0.0004
+
+def ask_with_memory(vector_store, query, chat_history=[]):
+    from langchain.chains import ConversationalRetrievalChain
+    from langchain.chat_models import ChatOpenAI
+    
+    llm = ChatOpenAI(model_name='gpt-3.5-turbo', temperature=1, openai_api_key=openai_api_key)
+    retriever = vector_store.as_retriever(search_type='similarity', search_kwargs={'k': 3})
+
+    chain= ConversationalRetrievalChain.from_llm(llm, retriever)
+    result = chain({'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 = '/Users/cheynelevesseur/Desktop/Python_Code/Projects/LLM/Streamlit_Document_Reader_Simple/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='')
+
+k = 3  # Set k to 3
+
+# # Initialize chat history if not present
+# if 'history' not in st.session_state:
+#     st.session_state.history = []
+    
+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)