init

README.md

@@ -1,8 +1,8 @@
 ---
-title: Question Answering System
+title: Question-Answering System
 emoji: 🏆
-colorFrom: pink
-colorTo: pink
+colorFrom: purple
+colorTo: purple
 sdk: streamlit
 sdk_version: 1.35.0
 app_file: app.py

app.py

@@ -0,0 +1,38 @@
+from openai import OpenAI
+import streamlit as st
+
+
+st.markdown('''
+Hey there, I wrote a book titled "**:green[Hands-On Retrieval-Augmented Generation]**," which includes this example application. If you\'re interested in exploring more practical applications of Retrieval-Augmented Generation, be sure to [check it out](https://herczeg.be)!
+
+[Go to start](https://huggingface.co/spaces/jeroenherczeg/HORAG-LLM) - [Previous](#) - [Next](#) - [Read the book](https://herczeg.be)
+''')
+
+st.header('LLM', divider='rainbow')
+
+client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"])
+
+if "openai_model" not in st.session_state:
+    st.session_state["openai_model"] = "gpt-3.5-turbo"
+
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+if prompt := st.chat_input("What is up?"):
+    st.session_state.messages = []
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    with st.chat_message("user"):
+        st.markdown(prompt)
+
+    with st.chat_message("assistant"):
+        stream = client.chat.completions.create(
+            model=st.session_state["openai_model"],
+            messages=[{"role": "user", "content": prompt}],
+            stream=True,
+        )
+        response = st.write_stream(stream)
+    st.session_state.messages.append({"role": "assistant", "content": response})

requirements.txt

@@ -0,0 +1,2 @@
+openai 
+streamlit