UI with chat history.

.gitignore

@@ -1,2 +1,3 @@
 .env
-/langchain-docs
+/langchain-docs
+__pycache__/

main.py

@@ -0,0 +1,49 @@
+from backend.core import run_llm
+import streamlit as st
+from streamlit_chat import message
+from typing import Set
+
+st.header("Peter's LangChain chatbot")
+prompt = st.text_input("Ask me anything about LangChain", placeholder="...")
+
+# Initialize session state variables if they don't exist yet.
+if "user_prompt_history" not in st.session_state:
+    st.session_state.user_prompt_history = []
+
+if "chat_answers_history" not in st.session_state:
+    st.session_state.chat_answers_history = []
+
+
+# Format sources links (referencing LangChain urls) as a clean enumerated list.
+def create_sources_string(source_urls: Set[str]) -> str:
+    if not source_urls:
+        return ""
+    sources_list = list(source_urls)
+    sources_list.sort()
+    sources_string = "sources:\n"
+    for i, source in enumerate(sources_list):
+        sources_string += f"{i+1}. {source}\n"
+    return sources_string
+
+
+if prompt:
+    with st.spinner("Thinking..."):
+        generated_response = run_llm(query=prompt)
+        sources = set(
+            [doc.metadata["source"]
+                for doc in generated_response["source_documents"]
+             ]
+        )
+        formatted_response = (
+            f"{generated_response['result']} \n\n Sources: {create_sources_string(sources)}"
+        )
+
+        # Add the user's prompt and the chatbot's response to the session state variables.
+        st.session_state.user_prompt_history.append(prompt)
+        st.session_state.chat_answers_history.append(formatted_response)
+
+if st.session_state.chat_answers_history:
+    for generated_response, user_query in zip(
+            st.session_state.chat_answers_history, st.session_state.user_prompt_history):
+        message(user_query, is_user=True)
+        message(generated_response, is_user=False)