added all relevant assets for streamlit deployment

.gitignore

@@ -0,0 +1,3 @@
+.DS_Store
+
+raw_documents/

bin/clean.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+
+find . -name __pycache__ | xargs rm -rf
+find . -name .pytest_cache | xargs rm -rf
+find . -name .ipynb_checkpoints | xargs rm -rf

main.py

@@ -0,0 +1,40 @@
+import utils
+import os
+
+import openai
+from llama_index import SimpleDirectoryReader
+from llama_index import Document
+from llama_index import VectorStoreIndex
+from llama_index import ServiceContext
+from llama_index.llms import OpenAI
+
+from llama_index.embeddings import HuggingFaceEmbedding
+
+
+openai.api_key = utils.get_openai_api_key()
+
+if __name__ == "__main__":
+
+    documents = SimpleDirectoryReader(
+        input_files=["./raw_documents/HI_knowledge_base.pdf"]
+    ).load_data()
+
+    document = Document(text="\n\n".join([doc.text for doc in documents]))
+
+    ### gpt-4-1106-preview
+    ### gpt-3.5-turbo-1106 / gpt-3.5-turbo
+    llm = OpenAI(model="gpt-3.5-turbo-1106", temperature=0.1)
+    embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-small-en-v1.5")
+
+    service_context = ServiceContext.from_defaults(llm=llm, embed_model=embed_model)
+    index = VectorStoreIndex.from_documents([document], service_context=service_context)
+
+    query_engine = index.as_query_engine()
+
+    response = query_engine.query(
+        ("Intermediate and Long Term Care (ILTC) services are for those who need further care and"
+         "treatment after discharge from the hospital, who may need assistance with their activities of"
+         "daily living. This can be through"
+        )
+    )
+    print(str(response))

streamlit_app.py

@@ -0,0 +1,77 @@
+import streamlit as st
+import os
+
+import openai
+from openai import OpenAI
+
+# App title
+st.set_page_config(page_title="💬 Open AI Chatbot")
+
+# Replicate Credentials
+with st.sidebar:
+    st.title('💬 Open AI Chatbot')
+    st.write('This chatbot is created using the GPT model from Open AI.')
+    if 'OPENAI_API_KEY' in st.secrets:
+        st.success('API key already provided!', icon='✅')
+        openai_api = st.secrets['OPENAI_API_KEY']
+    else:
+        openai_api = st.text_input('Enter OpenAI API token:', type='password')
+        if not (openai_api.startswith('sk-') and len(openai_api)==51):
+            st.warning('Please enter your credentials!', icon='⚠️')
+        else:
+            st.success('Proceed to entering your prompt message!', icon='👉')
+    os.environ['OPENAI_API_KEY'] = openai_api
+
+    st.subheader('Models and parameters')
+    selected_model = st.sidebar.selectbox('Choose an OpenAI model', ['gpt-3.5-turbo-1106', 'gpt-4-1106-preview'], key='selected_model')
+    temperature = st.sidebar.slider('temperature', min_value=0.01, max_value=5.0, value=0.1, step=0.01)
+    st.markdown('📖 Reach out to Sakimilo to learn how to create this app!')
+
+# Store LLM generated responses
+if "messages" not in st.session_state.keys():
+    st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]
+
+# Display or clear chat messages
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.write(message["content"])
+
+def clear_chat_history():
+    st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]
+st.sidebar.button('Clear Chat History', on_click=clear_chat_history)
+
+def generate_llm_response(prompt_input):
+    system_content = ("You are a helpful assistant. "
+                       "You do not respond as 'User' or pretend to be 'User'. "
+                       "You only respond once as 'Assistant'."
+    )
+
+    completion = client.chat.completions.create(
+                    model=selected_model,
+                    messages=[
+                            {"role": "system", "content": system_content},
+                    ] + st.session_state.messages,
+                    temperature=temperature
+    )
+    return completion.choices[0].message.content
+
+# User-provided prompt
+if prompt := st.chat_input(disabled=not openai_api):
+    client = OpenAI()
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    with st.chat_message("user"):
+        st.write(prompt)
+
+# Generate a new response if last message is not from assistant
+if st.session_state.messages[-1]["role"] != "assistant":
+    with st.chat_message("assistant"):
+        with st.spinner("Thinking..."):
+            response = generate_llm_response(prompt)
+            placeholder = st.empty()
+            full_response = ''
+            for item in response:
+                full_response += item
+                placeholder.markdown(full_response)
+            placeholder.markdown(full_response)
+    message = {"role": "assistant", "content": full_response}
+    st.session_state.messages.append(message)

utils.py

@@ -0,0 +1,4 @@
+import os
+
+def get_openai_api_key():
+    return os.getenv("OPENAI_API_KEY")