Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,72 @@
-import altair as alt
-import numpy as np
-import pandas as pd
+# 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])),
+#     ))
+
+
 import streamlit as st
+import asyncio
+import nest_asyncio
+from your_chatbot_module import MCP_ChatBot  # Assuming you put your chatbot code in a module
+
+nest_asyncio.apply()
+
+@st.cache_resource
+def get_chatbot_instance():
+    api_key = st.secrets["LLAMA_API_KEY"]  # Use Hugging Face Secrets for API key
+    return MCP_ChatBot(api_key=api_key)
+
+chatbot = get_chatbot_instance()
+
+st.title("MCP Chatbot on Hugging Face Spaces")
+
+user_input = st.text_input("Enter your query:")
+
+if st.button("Send") and user_input:
+    # Run the async chatbot query in the event loop
+    response_steps = asyncio.run(chatbot.connect_and_process(user_input))
+    # Extract final answer from steps
+    final_answer = ""
+    for step in response_steps:
+        if step.get("type") == "final_answer":
+            final_answer = step.get("content")
+            break
+    st.markdown("### Response:")
+    st.write(final_answer)
 
-"""
-# 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])),
-    ))