Create app.py

app.py

@@ -0,0 +1,29 @@
+import streamlit as st
+from datasets import load_dataset
+import os 
+
+HF_TOKEN = os.environ.get("HF_TOKEN", None)
+
+st.set_page_config(page_title="Synthetic textbooks inspection", layout="wide")
+st.title("Synthetic textbooks inspection")
+st.markdown("Inspection of synthetic textbooks generated by `Falcon-180B-chat`")
+
+@st.cache_data()
+def load_data(source="all"):
+    ds = load_dataset("HuggingFaceTB/synthetic_textbooks_subset", split="train", use_auth_token=HF_TOKEN)
+    if source != "all":
+        ds = ds.filter(lambda x: x["source"] == source)
+    return ds
+
+
+source = st.selectbox("Data source", ['all', 'wikihow','khan_academy', 'stanford_courses', 'rw_wikihow', 'rw_stanford'])
+samples = load_data(source)
+n_samples = len(samples)
+
+index = st.number_input(f"Index of the sample (out of {n_samples}):",  min_value=0, max_value=n_samples-1, value=0, step=1)
+st.markdown(f"Displaying source: {source}")
+st.subheader("Prompt")
+st.markdown(samples[index_example]["prompt"])
+
+st.subheader("Textbook")
+st.markdown(samples[index_example]['textbook'])