Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,43 @@
-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 requests
+import os
+# ---------------- CONFIG ----------------
+HF_TOKEN = os.getenv("HF_TOKEN")
+API_URL = "https://api-inference.huggingface.co/models/google/flan-t5-small"
+headers = {
+    "Authorization": f"Bearer {HF_TOKEN}",
+    "Content-Type": "application/json"
+}
+# ---------------- UI ----------------
+st.title("🤖 My First AI Chatbot")
+user_input = st.text_input("Ask something:")
+# ---------------- FUNCTION ----------------
+def query(payload):
+    try:
+        response = requests.post(
+            API_URL,
+            headers=headers,
+            json=payload,
+            timeout=30
+        )
+        # Handle API errors safely
+        if response.status_code != 200:
+            return {"error": f"HTTP {response.status_code}: {response.text[:200]}"}
+        return response.json()
+    except Exception as e:
+        return {"error": str(e)}
+# ---------------- MAIN ----------------
+if st.button("Send"):
+    if not user_input.strip():
+        st.warning("Please enter a question.")
+    else:
+        output = query({"inputs": user_input})
+        # ---------------- SAFE OUTPUT HANDLING ----------------
+        if "error" in output:
+            st.error(output["error"])
+        else:
+            try:
+                answer = output[0]["generated_text"]
+                st.success(answer)
+            except:
+                st.error("Unexpected response format from model.")