Upload app.py

app.py

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+############################################################################################################
+# Importing Libraries
+
+import streamlit as st
+import pandas as pd
+import random
+import os
+import time
+import base64
+import logging
+import io
+import config
+from openai import OpenAI
+
+# Set up logging
+logging.basicConfig(filename='app.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s', datefmt='%Y-%m-%d %H:%M:%S')
+
+############################################################################################################
+# Streamlit app layout
+
+# Set the page to wide or centered mode
+st.set_page_config(layout="wide", initial_sidebar_state="expanded")
+
+# Load the terms file into a DataFrame
+df = pd.read_csv(config.default_terms_csv)
+
+# Streamlit app layout
+st.title(config.app_title)
+st.markdown(config.intro_para)
+st.caption(config.app_author)
+
+# API Key Input in sidebar
+
+with st.sidebar:
+    st.header("Configuration")
+    
+    # API Key Input Field
+    api_key = st.text_input(
+        "OpenAI API Key",
+        type="password",
+        key="api_key",
+        help="This is the API key for your OpenAI account. You can find it [here](https://platform.openai.com/api-keys)."
+    )
+    if api_key:
+        st.session_state["OPENAI_API_KEY"] = api_key
+    else:
+        st.warning("Please provide your OpenAI API key to enable chat functionality.")
+
+st.sidebar.title(config.sidebar_title)
+
+with st.sidebar:
+        with st.expander("Click here for instructions."):
+            st.write(config.sidebar_instructions)
+
+
+# File Uploader in sidebar
+
+# Load terms from a CSV file
+def load_terms(file_input):
+    try:
+        if isinstance(file_input, str):
+            data = pd.read_csv(file_input)
+        else:
+            data = pd.read_csv(io.StringIO(file_input.read().decode('utf-8')))
+        return data
+    except Exception as e:
+        st.error(f"An error occurred while loading the file: {str(e)}")
+        logging.exception(f"Error loading file: {e}")
+
+# Function to create a download link for a file
+def create_download_link(file_path, file_name):
+    try:
+        with open(file_path, "rb") as file:
+            file_content = file.read()
+        encoded_content = base64.b64encode(file_content).decode("utf-8")
+        download_link = f'<a href="data:file/csv;base64,{encoded_content}" download="{file_name}">Download {file_name}</a>'
+        return download_link
+    except FileNotFoundError:
+        error_message = f"The file {file_name} was not found."
+        st.error(error_message)
+        logging.exception(error_message)
+    except Exception as e:
+        error_message = f"An error occurred: {str(e)}"
+        st.error(error_message)
+        logging.exception(error_message)
+
+# Function to extract the first column values
+def get_first_column_values(df):
+    if not df.empty:
+        return df.iloc[:, 0].tolist()
+    else:
+        return []
+
+# Download link for the template file
+template_file_path = config.default_terms_csv
+
+# File Uploader
+uploaded_file = st.sidebar.file_uploader(" ", type=["csv"])
+if uploaded_file is not None:
+    logging.info(f"File uploaded: {uploaded_file.name}")
+    st.session_state.uploaded_file = uploaded_file
+
+# Load terms from the file
+if 'uploaded_file' in st.session_state and st.session_state.uploaded_file is not None:
+    terms = load_terms(st.session_state.uploaded_file)
+else:
+    terms = load_terms(template_file_path)
+
+# Extract first column values
+term_list = get_first_column_values(terms)
+
+st.sidebar.markdown(create_download_link(template_file_path, "terms.csv"), unsafe_allow_html=True)
+
+# line break in the sidebar
+st.sidebar.markdown('<hr>', unsafe_allow_html=True)
+
+############################################################################################################
+# Term Selection and session state
+
+# Initialize the session state variables for selected term, context, and display messages
+if 'selected_term' not in st.session_state:
+    st.session_state.selected_term = None
+if 'selected_context' not in st.session_state:
+    st.session_state.selected_context = None
+if 'display_messages' not in st.session_state:
+    st.session_state.display_messages = []
+
+# Initialize session states for the selected term, counter, and display flag
+if 'display_term' not in st.session_state:
+    st.session_state.display_term = False
+if 'initial_message_displayed' not in st.session_state:
+    st.session_state.initial_message_displayed = False
+
+# Initialize state to track the previously selected term
+if 'old_term' not in st.session_state:
+    st.session_state.old_term = None
+
+# Dropdown menu for selecting a term
+selected_term = st.selectbox('**SELECT FROM THE DROPDOWN MENU**', term_list)
+
+if selected_term:
+    # If a new term is selected (including first time selection), reset or show the message
+    if selected_term != st.session_state.old_term:
+        user_message = f"What is one thing you know or want to know about '{selected_term}'? Let's have a conversation! I love to ask follow-up questions. Feel free to answer those or ask any other course relevant question."
+        st.session_state["display_messages"].append({"role": "user", "content": user_message})
+        # Update old_term in session state
+        st.session_state.old_term = selected_term
+    
+    selected_context = terms.loc[terms['TERM'] == selected_term, 'CONTEXT'].values[0]
+    st.session_state.selected_term = selected_term
+    st.session_state.selected_context = selected_context
+    st.session_state.display_term = True
+    
+    # Update the prompt for the API
+    updated_prompt = config.term_prompt(st.session_state.selected_term, st.session_state.selected_context, term_list)
+    
+else:
+    # If nothing is selected or the selection is cleared, reset the old_term
+    st.session_state.old_term = None
+
+# Display the selected term and its context
+if st.session_state.display_term and st.session_state.selected_term:
+    st.header(st.session_state.selected_term)
+
+with st.expander("INSTRUCTIONS FOR STUDENTS:"):
+    st.markdown(config.instructions)
+with st.expander("**INSTRUCTORS**: For a look at the current terms file driving the interaction, click here:"):
+    st.markdown("This is the terms.csv file that drives the interaction. You can edit this file to change the terms and context that the chatbot uses. You may add any term or phrase. You may leave the context blank if you prefer or you can add anything relevant that the GPT does not normally know about the term. This may include relevant learning objectives, course examples, notable scientists, assessment dates, syllabus information, etc.")
+    st.table(df)
+with st.expander("**INSTRUCTORS**: For a look at the prompt driving the chatbot, click here:"):
+    prompt_text = config.term_prompt(st.session_state.selected_term, st.session_state.selected_context, term_list)
+    st.markdown(prompt_text)
+
+############################################################################################################
+# ChatGPT
+
+# Initialize the OpenAI client
+if "OPENAI_API_KEY" in st.session_state:
+    client = OpenAI(api_key=st.session_state["OPENAI_API_KEY"])
+else:
+    client = None
+
+# Initialize the session state variables if they don't exist
+if "openai_model" not in st.session_state:
+    st.session_state["openai_model"] = config.ai_model
+
+if "display_messages" not in st.session_state:
+    st.session_state.display_messages = []
+
+# Update initial_context with the latest selected term and context
+if st.session_state.get('selected_term') and st.session_state.get('selected_context'):
+    updated_prompt = config.term_prompt(st.session_state.selected_term, st.session_state.selected_context, term_list)
+    # Replace the initial context in display_messages with the updated prompt
+    if st.session_state.display_messages:
+        st.session_state.display_messages[0]["content"] = updated_prompt
+    else:
+        st.session_state.display_messages = [{"role": "system", "content": updated_prompt}]
+
+# Get user input
+prompt = st.chat_input("What do you know? What do you want to know?")
+
+# Input for new messages
+if prompt:
+    # Ensure the initial context is in the session state, add the user's message
+    if not st.session_state["display_messages"]:
+        st.session_state["display_messages"].append({"role": "system", "content": updated_prompt})
+    st.session_state["display_messages"].append({"role": "user", "content": prompt})
+
+# Function to reset all chat-related session state
+def reset_chat_history():
+    st.session_state["display_messages"] = []
+    # Reset other chat-related session states if they exist
+    if 'selected_term' in st.session_state:
+        st.session_state.selected_term = None
+    if 'selected_context' in st.session_state:
+        st.session_state.selected_context = None
+    if 'display_term' in st.session_state:
+        st.session_state.display_term = False
+    st.rerun()
+
+# Main chat container
+with st.container(height=400, border=True):
+    # Display chat history in reverse order including new messages
+    for message in st.session_state["display_messages"][1:]:
+        if message["role"] == "user":
+            with st.chat_message("user"):
+                st.markdown(message["content"])
+        else:
+            with st.chat_message("assistant"):
+                st.markdown(message["content"])
+
+# Generate assistant's response and add it to the messages
+    if prompt:
+        if client:
+            with st.chat_message("assistant"):
+                try:
+                    stream = client.chat.completions.create(
+                        model=st.session_state["openai_model"],
+                        messages=[
+                            {"role": m["role"], "content": m["content"]}
+                            for m in st.session_state["display_messages"]
+                        ],
+                        stream=True,
+                        temperature=config.temperature,
+                        max_tokens=config.max_tokens,
+                        frequency_penalty=config.frequency_penalty,
+                        presence_penalty=config.presence_penalty,
+                    )
+                    response = st.write_stream(stream)
+                    # Append the full response to the session state for display
+                    st.session_state["display_messages"].append(
+                        {"role": "assistant", "content": response}
+                    )
+                    logging.info(f"User prompt: {prompt}")  # Log user prompts
+                    logging.info(f"Assistant response: {response}")  # Log assistant responses
+                except Exception as e:
+                    st.error(f"An error occurred: {str(e)}")
+                    logging.exception(f"Error generating response: {e}")  # Log errors
+        else:
+            st.warning("Please provide an OpenAI API key to enable the chat functionality.")
+
+# Add Clear Chat History button between container and warning message
+if st.button("Clear Chat History"):
+    reset_chat_history()
+    logging.info("Chat history cleared")  # Log when chat history is cleared
+
+st.markdown(config.warning_message, unsafe_allow_html=True)
+
+############################################################################################################
+
+# Resources and About Sections in the Sidebar
+
+st.sidebar.title("Resources")
+
+for resource in config.resources:
+    with st.sidebar:
+        with st.sidebar:
+            with st.expander(resource["title"]):
+                st.markdown(f"Description: {resource['description']}")
+                if "url" in resource:
+                    st.markdown(f"[{resource['title']}]({resource['url']})")
+                if "file_path" in resource:
+                    file_path = resource["file_path"]
+                    if os.path.exists(file_path):
+                        with open(file_path, "rb") as file:
+                            file_bytes = file.read()
+                        with st.spinner(f"Loading {resource['title']}..."):
+                            st.download_button(
+                                label=resource["title"],
+                                data=file_bytes,
+                                file_name=os.path.basename(file_path),
+                                mime="application/octet-stream",
+                                help=resource["description"],
+                            )
+                    else:
+                        st.warning(f"File not found: {file_path}")
+
+# Footer
+with st.sidebar:
+    st.markdown("---")
+
+    st.title("About")
+
+   # Using the config objects in your Streamlit app
+    st.markdown(config.app_creation_message, unsafe_allow_html=True)
+    st.markdown(config.app_repo_license_message, unsafe_allow_html=True)