Spaces:
Sleeping
Sleeping
File size: 9,851 Bytes
e07e1fe 83fe832 e07e1fe 83fe832 e07e1fe 83fe832 e07e1fe 83fe832 e07e1fe 83fe832 f35a40c e07e1fe 83fe832 e07e1fe cb9c774 f35a40c 0e1846b 599e176 0e1846b f35a40c 599e176 f35a40c 599e176 0e1846b f35a40c 0e1846b f35a40c cb9c774 599e176 f35a40c 599e176 0e1846b 599e176 0e1846b 599e176 0e1846b 599e176 0e1846b f35a40c 599e176 f35a40c 599e176 f35a40c 0e1846b f35a40c 0e1846b f35a40c 599e176 cb9c774 f35a40c 599e176 f35a40c 599e176 f35a40c 599e176 f35a40c cb9c774 599e176 f35a40c 0e1846b f35a40c 599e176 f35a40c 599e176 f35a40c 599e176 cb9c774 f35a40c 599e176 f35a40c 599e176 f35a40c 599e176 f35a40c cb9c774 599e176 cb9c774 f35a40c 0e1846b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 |
import gradio as gr
from datasets import load_dataset
import pandas as pd
DATASETS = {
"CS1": "withmartian/cs1_dataset",
"CS2": "withmartian/cs2_dataset",
"CS3": "withmartian/cs3_dataset",
"CS2 Synonyms": "withmartian/cs2_dataset_synonyms",
"CS3 Synonyms": "withmartian/cs3_dataset_synonyms",
"CS4 Synonyms": "withmartian/cs4_dataset_synonyms",
}
COLUMNS = ["create_statement", "english_prompt", "sql_statement"]
def load_preview(dataset_name):
try:
ds = load_dataset(DATASETS[dataset_name], split="train")
df = pd.DataFrame(ds).head(500)
if all(col in df.columns for col in COLUMNS):
df = df[COLUMNS]
return df
except Exception as e:
return pd.DataFrame({"Error": [str(e)]})
def filter_dataframe(df, search_query):
if not search_query or df.empty or "Error" in df.columns:
return df
mask = df.astype(str).apply(
lambda row: row.str.contains(search_query, case=False, na=False).any(),
axis=1
)
return df[mask]
def dataset_viewer(shared_instruction, shared_schema):
gr.HTML("""
<div style="text-align: center; padding: 2rem 1.5rem; background: linear-gradient(135deg, #2A2A2A 0%, #3A3A3A 100%); border-radius: 16px; margin-bottom: 1.5rem; box-shadow: 0 4px 12px rgba(0,0,0,0.3);">
<h2 style="font-size: 2rem; font-weight: 700; margin-bottom: 0.5rem; color: #FF6B4A;">Dataset Explorer</h2>
<p style="font-size: 1rem; opacity: 0.9; line-height: 1.6; color: #D0D0D0;">
Browse, search, and explore TinySQL datasets
</p>
</div>
""")
gr.HTML("""
<div style="background: linear-gradient(135deg, #2A2A2A 0%, #3A3A3A 100%); border-radius: 12px; padding: 1.5rem; margin: 1rem 0; border-left: 4px solid #FF6B4A;">
<p style="color: #D0D0D0; margin: 0; line-height: 1.6;">
<strong style="color: #FF6B4A;">Quick Start:</strong> Select a dataset, click Load Dataset, then use search to filter. Pick any row and send it to the Model Demo tab.
</p>
</div>
""")
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("### Controls")
dataset_dropdown = gr.Dropdown(
choices=list(DATASETS.keys()),
value="CS1",
label="Choose Dataset",
info="Select complexity level"
)
# Better formatted model guide card
gr.HTML("""
<div style="background: #2A2A2A; border-radius: 12px; padding: 1.5rem; margin: 1.5rem 0; border: 1px solid #3A3A3A;">
<h4 style="color: #FF6B4A; font-size: 1rem; margin: 0 0 1.25rem 0; font-weight: 700; border-bottom: 2px solid #3A3A3A; padding-bottom: 0.75rem;">Dataset Complexity Levels</h4>
<div style="margin-bottom: 1.5rem;">
<div style="color: #4CAF50; font-weight: 600; font-size: 0.95rem; margin-bottom: 0.5rem;">Basic Level</div>
<div style="margin-left: 1rem; color: #999; font-size: 0.85rem; line-height: 1.8;">
<div><strong style="color: #D0D0D0;">CS1:</strong> Basic SELECT-FROM queries</div>
<div><strong style="color: #D0D0D0;">CS2:</strong> Adds ORDER BY clauses</div>
</div>
</div>
<div style="margin-bottom: 1.5rem;">
<div style="color: #FF9800; font-weight: 600; font-size: 0.95rem; margin-bottom: 0.5rem;">Intermediate Level</div>
<div style="margin-left: 1rem; color: #999; font-size: 0.85rem; line-height: 1.8;">
<div><strong style="color: #D0D0D0;">CS3:</strong> Aggregations (COUNT, SUM, AVG)</div>
<div><strong style="color: #D0D0D0;">CS4:</strong> Adds WHERE filters</div>
</div>
</div>
<div>
<div style="color: #f44336; font-weight: 600; font-size: 0.95rem; margin-bottom: 0.5rem;">Advanced Level</div>
<div style="margin-left: 1rem; color: #999; font-size: 0.85rem; line-height: 1.8;">
<div><strong style="color: #D0D0D0;">CS5:</strong> Multi-table JOINs</div>
</div>
</div>
<div style="margin-top: 1.5rem; padding-top: 1.25rem; border-top: 1px solid #3A3A3A;">
<div style="color: #FF6B4A; font-weight: 600; font-size: 0.9rem; margin-bottom: 0.5rem;">Synonym Variants</div>
<div style="color: #999; font-size: 0.85rem; line-height: 1.6;">Natural language variations with semantic mappings</div>
</div>
</div>
""")
load_btn = gr.Button("Load Dataset", variant="primary", size="lg")
gr.Markdown("### Test Example")
row_selector = gr.Number(
label="Row Number",
value=0,
minimum=0,
precision=0,
info="Pick a row to test"
)
send_to_model_btn = gr.Button("Run in Model Demo", variant="primary")
with gr.Column(scale=3):
gr.Markdown("### Dataset Preview")
search_box = gr.Textbox(
label="Search",
placeholder="Search across all columns...",
lines=1
)
# HuggingFace-style table
gr.HTML("""
<style>
/* True HuggingFace-style table */
.dataframe-container {
border-radius: 8px !important;
overflow: hidden !important;
border: 1px solid #374151 !important;
}
.dataframe table {
border-collapse: collapse !important;
width: 100% !important;
font-size: 0.875rem !important;
}
.dataframe thead {
background: #1f2937 !important;
}
.dataframe thead th {
color: #9ca3af !important;
font-weight: 600 !important;
text-align: left !important;
padding: 0.75rem 1rem !important;
border-bottom: 1px solid #374151 !important;
font-size: 0.75rem !important;
text-transform: uppercase !important;
letter-spacing: 0.05em !important;
}
.dataframe tbody tr {
background: #111827 !important;
border-bottom: 1px solid #1f2937 !important;
transition: background-color 0.15s ease !important;
}
.dataframe tbody tr:hover {
background: #1f2937 !important;
}
.dataframe tbody td {
padding: 0.75rem 1rem !important;
color: #d1d5db !important;
font-size: 0.875rem !important;
line-height: 1.5 !important;
max-width: 400px !important;
overflow: hidden !important;
text-overflow: ellipsis !important;
}
.dataframe tbody tr:last-child {
border-bottom: none !important;
}
</style>
""")
df_display = gr.Dataframe(
headers=COLUMNS,
datatype=["str", "str", "str"],
interactive=False,
wrap=True,
label="Results",
elem_classes="dataframe-container"
)
stats_display = gr.Markdown("Click **Load Dataset** to begin exploring")
df_state = gr.State(value=pd.DataFrame())
def load_and_display(dataset_name):
df = load_preview(dataset_name)
if "Error" in df.columns:
return df, df, "Error loading dataset"
stats = f"**Loaded {len(df)} rows** • Columns: {', '.join(COLUMNS)}"
return df, df, stats
load_btn.click(
fn=load_and_display,
inputs=dataset_dropdown,
outputs=[df_state, df_display, stats_display]
)
def search_and_display(df, query):
if df.empty:
return df, "Load a dataset first"
filtered_df = filter_dataframe(df, query)
stats = f"**Showing {len(filtered_df)} of {len(df)} rows**"
if query:
stats += f" • Search: '{query}'"
return filtered_df, stats
search_box.change(
fn=search_and_display,
inputs=[df_state, search_box],
outputs=[df_display, stats_display]
)
def send_to_model(df, row_num):
if df.empty or row_num >= len(df):
return "", "", "Invalid row or no data loaded"
row = df.iloc[int(row_num)]
instruction = row['english_prompt'] if 'english_prompt' in row else ""
schema = row['create_statement'] if 'create_statement' in row else ""
return instruction, schema, f"**Row {row_num} loaded!** Switch to Model Demo tab"
send_to_model_btn.click(
fn=send_to_model,
inputs=[df_state, row_selector],
outputs=[shared_instruction, shared_schema, stats_display]
)
return {'df_state': df_state, 'df_display': df_display} |