streamlit app

download_model.py

@@ -1,7 +0,0 @@
-from huggingface_hub import hf_hub_download
-
-REPO_ID = "TheBloke/Llama-2-7B-Chat-GGUF"
-FILENAME = "llama-2-7b-chat.Q5_K_M.gguf"
-
-hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
-

streamlit_app.py

@@ -0,0 +1,48 @@
+import streamlit as st
+from app import llm_chain
+import time 
+from langchain_community.callbacks.streamlit import (
+    StreamlitCallbackHandler,
+)
+st.set_page_config(
+    layout="wide",
+    page_title="Khatir Bot",
+    page_icon="🤖",
+)
+
+
+
+def generate_response(prompt):
+    response = llm_chain.invoke(prompt)['text']
+    for word in response.split():
+        yield word + " "
+        time.sleep(0.05)
+
+st.title("Khatir Bot")
+
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# Accept user input
+if prompt := st.chat_input("What is up?"):
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    # Display user message in chat message container
+    with st.chat_message("user"):
+        st.markdown(prompt)
+
+    # Display assistant response in chat message container
+    with st.chat_message("assistant"):
+        st_callback = StreamlitCallbackHandler(st.empty())
+        response = st.write_stream(llm_chain.invoke(
+            {"question":prompt}, {"callbacks": [st_callback]}
+        ))
+
+    # Add assistant response to chat history
+    st.session_state.messages.append({"role": "assistant", "content": response})