Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,44 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+from langchain.chat_models import ChatOpenAI
+from langchain.chains import ConversationChain
+from langchain.memory import ConversationBufferMemory
+import os
+
+# Set OpenRouter API Key and Base URL
+os.environ["OPENAI_API_KEY"] = st.secrets["OPENAI_API_KEY"]
+os.environ['OPENAI_API_BASE'] = 'https://openrouter.ai/api/v1'
+
+# Set up the model
+llm = ChatOpenAI(
+    temperature=0.7,
+    model_name="deepseek/deepseek-chat-v3-0324:free"  # correct model path
+)
+
+# Set up memory
+if "memory" not in st.session_state:
+    st.session_state.memory = ConversationBufferMemory()
+
+conversation = ConversationChain(
+    llm=llm,
+    memory=st.session_state.memory,
+    verbose=False
+)
+
+# Streamlit UI
+st.set_page_config(page_title="LLM Chatbot", page_icon="🤖")
+
+st.title("Langchain Chatbot by Muhammad Izhan")
+
+user_input = st.text_input("You:", key="input")
+
+if user_input:
+    response = conversation.predict(input=user_input)
+    st.session_state.memory.chat_memory.add_user_message(user_input)
+    st.session_state.memory.chat_memory.add_ai_message(response)
+    st.write(f"**Bot:** {response}")
+
+# Show chat history
+if st.checkbox("Show Chat History"):
+    for message in st.session_state.memory.chat_memory.messages:
+        role = "You" if message.type == "human" else "Bot"
+        st.markdown(f"**{role}:** {message.content}")