init

app.py

@@ -2,62 +2,29 @@ import streamlit as st
 import json
 from datasets import load_dataset
 
-st.set_page_config(page_title="Kaggle Notebooks inspection", layout="wide")
+st.set_page_config(page_title="BIRD SQL inspection", layout="wide")
 
-st.markdown("<h1 style='text-align: center; color: #00BFFF;'>Kaggle Notebooks inspection 🔍</h1>", unsafe_allow_html=True)
+st.markdown("<h1 style='text-align: center; color: #00BFFF;'>BIRD SQL inspection 🔍</h1>", unsafe_allow_html=True)
 
 st.markdown("""
-Here you can inspect Kaggle notebooks that were converted to python scripts and deduplicated.
+Here you can inspect BIRD SQL data with schemas.
 
-In the sidebar, you can choose to display:
-- **dataset description and title** when it exists; this information was already available in Kaggle dataset
-- only files for which we **retrieved extra information on the datasets being loaded** in the notebook using Kaggle API (e.g., column names, types, summary...), which makes up about 8% of the dataset.
-There might be multiple CSV files loaded in the same notebook; we use delimiters `<start_description>` and `<end_description>` to separate them.
 """)
 
 @st.cache()
-def load_data(upvote=0, size=0, has_data_info=False):
-    ds = load_dataset("loubnabnl/kaggle_scripts_final_wdata", split="train")
-    if has_data_info:
-        ds = ds.filter(lambda x: x["has_data_info"])
-    ds = ds.filter(lambda x: x["upvotes"] >= upvote and x["script_nb_tokens"] >= size)
+def load_data():
+    ds = load_dataset("xu3kev/BIRD-SQL-data", split="train")
     return ds
 
-def show_extra_info(e):
-    kv = json.loads(e["kversion"])[0]
-    try:
-        data_v = json.loads(e["dataset_versions"])[0]
-    except:
-        data_v = ""
-    if data_v:
-        data_title = data_v["Title"]
-        import numpy as np
-        description = data_v["Description"] if str(data_v["Description"]) != 'nan' else "<empty_description>"
-        data_text = f"<br>**📚 Dataset description:**<br>Title: **{data_title}**, described as: {description}."
-    else:
-        data_text = ""
-    
-    text = f"The title of the notebook is: **{kv['Title']}** and it has **{kv['TotalVotes']} ⬆️ upvotes**.{data_text}"
-    return text
-
-st.sidebar.header('Notebook Filters')
-vote = st.sidebar.slider("Minimum notebook ⬆️ upvotes", min_value=0, max_value=100, step=1, value=0)
-size = st.sidebar.slider("Length of the notebook in number of tokens (only the script)", min_value=0, max_value=15_000, step=1000, value=0)
-
-st.sidebar.header('Display Settings')
-show_data_metadata = st.sidebar.checkbox("Show associated (not necessarily retrieved) data Title and Description", value=True)
-show_only_files_with_data = st.sidebar.checkbox("Show only files for which we retrieved dataset information", value=False)
-
-samples = load_data(vote, size, show_only_files_with_data)
+
+samples = load_data()
 st.sidebar.header('Sample Selection')
 index_example = st.sidebar.number_input(f"Choose a sample from the existing {len(samples)} notebooks:", min_value=0, max_value=max(0, len(samples)-1), value=0, step=1)
 
-if show_data_metadata:
-    st.markdown(f'<h2 style="color:blue;">Kaggle dataset description:</h2>', unsafe_allow_html=True)
-    st.markdown(show_extra_info(samples[index_example]), unsafe_allow_html=True)
-
-if samples[index_example]["has_data_info"]:
-    st.markdown(f'<h2 style="color:blue;">Retrieved data information:</h2>', unsafe_allow_html=True)
-    st.code(samples[index_example]["retreived_data_description"])
-st.markdown(f'<h2 style="color:blue;">Notebook {index_example} converted to script:</h2>', unsafe_allow_html=True)
-st.code(samples[index_example]["script"])
+db_id = samples[index_example]["db_id"]
+st.markdown(f'<h2 style="color:blue;">{db_id} schema:</h2>', unsafe_allow_html=True)
+st.code(samples[index_example]["schema"])
+st.markdown(f'<h2 style="color:blue;">{index_example} Question:</h2>', unsafe_allow_html=True)
+st.code(samples[index_example]["question"])
+st.markdown(f'<h2 style="color:blue;">{index_example} SQL:</h2>', unsafe_allow_html=True)
+st.code(samples[index_example]["SQL"])