working app

src/streamlit_app.py

@@ -1,40 +1,157 @@
-import altair as alt
-import numpy as np
-import pandas as pd
+import json
+from datetime import datetime
+
 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])),
-    ))
+# Set page config
+st.set_page_config(page_title="Conversation Viewer", layout="wide")
+
+@st.cache_data
+def load_conversations(file_path):
+    """Load conversations from JSON file"""
+    with open(file_path, 'r', encoding='utf-8') as f:
+        return json.load(f)
+
+def format_timestamp(timestamp):
+    """Convert timestamp to readable format"""
+    try:
+        if timestamp > 1e12:  # milliseconds
+            timestamp = timestamp / 1000
+        return datetime.fromtimestamp(timestamp).strftime('%Y-%m-%d %H:%M:%S')
+    except:
+        return "N/A"
+
+def search_in_conversation(conv, search_term):
+    """Check if search term exists in conversation"""
+    if not search_term:
+        return True
+
+    search_term = search_term.lower()
+
+    # Search in conversation name
+    if search_term in conv['conv']['name'].lower():
+        return True
+
+    # Search in messages
+    for msg in conv['messages']:
+        if 'content' in msg and search_term in msg['content'].lower():
+            return True
+
+    return False
+
+def display_message(msg):
+    """Display a single message"""
+    if msg['role'] == 'user':
+        with st.chat_message("user"):
+            st.markdown(msg['content'])
+    elif msg['role'] == 'assistant':
+        with st.chat_message("assistant"):
+            # Remove <think> tags if present
+            content = msg['content']
+            if '<think>' in content and '</think>' in content:
+                start = content.find('<think>')
+                end = content.find('</think>') + len('</think>')
+                content = content[:start] + content[end:]
+            st.markdown(content)
+
+def main():
+    st.title("💬 Conversation Viewer")
+
+    # File selector
+    json_file = st.text_input(
+        "JSON File Path",
+        value="conversations_2025-11-01.json",
+        help="Enter the path to your conversations JSON file"
+    )
+
+
+
+    try:
+        conversations = load_conversations(json_file)
+
+        # Sidebar for search and filtering
+        with st.sidebar:
+            st.header("Search & Filter")
+            search_term = st.text_input("🔍 Search conversations", "")
+
+            st.divider()
+
+            # Filter conversations
+            filtered_convs = [
+                conv for conv in conversations
+                if search_in_conversation(conv, search_term)
+            ]
+
+            st.write(f"**{len(filtered_convs)}** conversations found")
+
+            # Sort options
+            sort_by = st.selectbox(
+                "Sort by",
+                ["Most Recent", "Oldest First", "Alphabetical"]
+            )
+
+            if sort_by == "Most Recent":
+                filtered_convs.sort(key=lambda x: x['conv'].get('lastModified', 0), reverse=True)
+            elif sort_by == "Oldest First":
+                filtered_convs.sort(key=lambda x: x['conv'].get('lastModified', 0))
+            else:
+                filtered_convs.sort(key=lambda x: x['conv']['name'])
+
+            st.divider()
+
+            # Conversation list
+            st.subheader("Conversations")
+            selected_conv_id = st.radio(
+                "Select a conversation",
+                options=[conv['conv']['id'] for conv in filtered_convs],
+                format_func=lambda x: next(
+                    (conv['conv']['name'][:50] + "..." if len(conv['conv']['name']) > 50
+                     else conv['conv']['name'])
+                    for conv in filtered_convs if conv['conv']['id'] == x
+                ),
+                label_visibility="collapsed"
+            )
+
+        # Main content area
+        if filtered_convs:
+            # Find selected conversation
+            selected_conv = next(
+                (conv for conv in filtered_convs if conv['conv']['id'] == selected_conv_id),
+                filtered_convs[0]
+            )
+
+            # Display conversation details
+            # have a border around this box
+            st.markdown(f"<div style='border: 1px solid #eee; padding: 10px; border-radius: 5px;'>", unsafe_allow_html=True)
+            st.write(selected_conv['conv']['name'])
+
+            col1, col2, col3 = st.columns(3)
+            with col1:
+                st.metric("Messages", len(selected_conv['messages']) - 1)  # Exclude root
+            with col2:
+                st.metric("Last Modified", format_timestamp(selected_conv['conv']['lastModified']))
+            with col3:
+                st.metric("Conv ID", selected_conv['conv']['id'][:8] + "...")
+
+            st.divider()
+
+            # Display messages
+            messages = [msg for msg in selected_conv['messages'] if msg['role'] != 'root']
+
+            for msg in messages:
+                if msg['role'] in ['user', 'assistant']:
+                    display_message(msg)
+        else:
+            st.info("No conversations found matching your search.")
+
+    except FileNotFoundError:
+        st.error(f"❌ File not found: {json_file}")
+        st.info("Please make sure the file path is correct.")
+    except json.JSONDecodeError:
+        st.error("❌ Invalid JSON file")
+    except Exception as e:
+        st.error(f"❌ Error: {str(e)}")
+
+if __name__ == "__main__":
+    main()
+