Create app.py

app.py

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+import streamlit as st
+import chromadb
+import pandas as pd
+import os
+
+# Fetch environment variables (defaults to your provided HF Space)
+CHROMA_HOST = os.getenv("CHROMA_HOST", "vish85521-chromadb.hf.space")
+CHROMA_PORT = os.getenv("CHROMA_PORT", "443")
+CHROMA_SSL = os.getenv("CHROMA_SSL", "True").lower() in ("true", "1", "t")
+
+st.set_page_config(page_title="ChromaDB Monitor", page_icon="📊", layout="wide")
+st.title("📊 ChromaDB Monitor")
+
+@st.cache_resource
+def get_chroma_client():
+    return chromadb.HttpClient(
+        host=CHROMA_HOST,
+        port=CHROMA_PORT,
+        ssl=CHROMA_SSL
+    )
+
+try:
+    with st.spinner(f"Connecting to {CHROMA_HOST}..."):
+        client = get_chroma_client()
+        
+        # Check heartbeats to ensure connection is alive
+        tenant_heartbeat = client.heartbeat()
+        st.success(f"Connected successfully! (Heartbeat: {tenant_heartbeat})")
+
+    collections = client.list_collections()
+
+    if not collections:
+        st.warning("No collections found in this ChromaDB instance.")
+    else:
+        # Extract collection names for the dropdown
+        collection_names = [c.name for c in collections]
+        selected_collection = st.selectbox("Select a Collection to Monitor", collection_names)
+
+        if selected_collection:
+            col = client.get_collection(selected_collection)
+            count = col.count()
+            st.metric(label="Total Documents in Collection", value=count)
+
+            if count > 0:
+                st.subheader("Sample Data (Top 10 Rows)")
+                # Peek grabs a small sample of the data without doing a similarity search
+                results = col.peek(limit=10)
+
+                # Flatten the ChromaDB output into a readable Pandas DataFrame
+                if results and results.get("ids"):
+                    df = pd.DataFrame({
+                        "ID": results["ids"],
+                        "Metadata": [str(m) for m in results["metadatas"]],
+                        "Document": results["documents"]
+                    })
+                    st.dataframe(df, use_container_width=True)
+                else:
+                    st.info("Collection data cannot be peeked or is empty.")
+
+except Exception as e:
+    st.error(f"Failed to connect to ChromaDB.")
+    st.error(f"Error Details: {e}")
+    st.code(f"Host: {CHROMA_HOST}\nPort: {CHROMA_PORT}\nSSL: {CHROMA_SSL}")