Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,96 @@
-import altair as alt
-import numpy as np
-import pandas as pd
+# streamlit_app.py
+
+import os
+import time
+import requests
 import streamlit as st
+from datetime import datetime
+from typing import Generator, Dict, Any
+from requests.exceptions import RequestException
+
+# ----------------- Configuration -----------------
+st.set_page_config(page_title="Perplexity Chat", layout="wide")
+
+# ----------------- Sidebar Settings -----------------
+st.sidebar.header("Settings")
+default_date = datetime.strptime("2023-01-01", "%Y-%m-%d").date()
+start_date = st.sidebar.date_input("Start Date", default_date)
+search_after_date_filter = start_date.strftime("%-m/%-d/%Y")
+
+# Load API key from environment variable
+api_key = os.environ["PERPLEXITY_API_KEY"]
+
+if not api_key:
+    st.error("Environment variable PERPLEXITY_API_KEY not found.")
+    st.stop()
+
+model = "sonar-deep-research"
+search_mode = "sec"
+
+# ----------------- Session State -----------------
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# ----------------- Chat UI -----------------
+st.title("📚 Perplexity AI Chat Interface")
+st.caption("Ask questions and get responses powered by Perplexity AI.")
+
+# Display chat history
+for msg in st.session_state.messages:
+    with st.chat_message(msg["role"]):
+        st.markdown(msg["content"])
+
+# ----------------- Streaming Response -----------------
+def stream_response(response_text: str) -> Generator[str, None, None]:
+    """Yield the response one word at a time for streaming effect."""
+    for word in response_text.split():
+        yield word + " "
+        time.sleep(0.03)
+
+def call_perplexity_api(user_query: str) -> str:
+    """Send user query to Perplexity API with retry logic."""
+    url = "https://api.perplexity.ai/chat/completions"
+    headers = {
+        "accept": "application/json",
+        "authorization": f"Bearer {api_key}",
+        "content-type": "application/json"
+    }
+    payload = {
+        "model": model,
+        "messages": [{"role": "user", "content": user_query}],
+        "stream": False,
+        "search_mode": search_mode,
+        "search_after_date_filter": search_after_date_filter
+    }
+
+    retries = 3
+    for attempt in range(retries):
+        try:
+            response = requests.post(url, headers=headers, json=payload, timeout=120)
+            response.raise_for_status()
+            return response.json()["choices"][0]["message"]["content"]
+        except RequestException as err:
+            if attempt < retries - 1:
+                wait_time = 2 ** attempt
+                time.sleep(wait_time)
+            else:
+                raise err
+
+# ----------------- Chat Input -----------------
+user_input = st.chat_input("Enter your question here...")
+
+if user_input:
+    # Display user message
+    with st.chat_message("user"):
+        st.markdown(user_input)
+    st.session_state.messages.append({"role": "user", "content": user_input})
 
-"""
-# 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])),
-    ))
+    # Display assistant response with spinner
+    with st.chat_message("assistant"):
+        with st.spinner("Thinking..."):
+            try:
+                full_response = call_perplexity_api(user_input)
+                streamed = st.write_stream(stream_response(full_response))
+                st.session_state.messages.append({"role": "assistant", "content": full_response})
+            except requests.RequestException as err:
+                st.error(f"Error: {err}")