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import gradio as gr
import pandas as pd
import matplotlib.pyplot as plt
import io
import google.generativeai as genai
from PIL import Image
def process_file(api_key, file, instructions):
genai.configure(api_key=api_key)
model = genai.GenerativeModel('gemini-2.5-pro-latest')
try:
if file.name.endswith('.csv'):
df = pd.read_csv(file.name)
else:
df = pd.read_excel(file.name)
except Exception as e:
return [f"File Error: {str(e)}"] * 3
# Properly terminated prompt string
prompt = f"""Generate exactly 3 distinct matplotlib visualizations for:
Columns: {list(df.columns)}
Data types: {dict(df.dtypes)}
Sample data: {df.head(3).to_dict()}
Requirements:
1. 1920x1080 resolution (figsize=(16,9), dpi=120)
2. Professional styling (seaborn, grid, proper labels)
3. Diverse chart types (include at least 1 advanced visualization)
User instructions: {instructions or 'None provided'}
Format response strictly as:
# Visualization 1
plt.figure(figsize=(16,9), dpi=120)
[code]
plt.tight_layout()
# Visualization 2
...
""" # Closing triple quotes added here
response = model.generate_content(prompt)
code_blocks = response.text.split("# Visualization ")[1:4]
visualizations = []
for i, block in enumerate(code_blocks, 1):
try:
plt.figure(figsize=(16, 9), dpi=120)
plt.style.use('seaborn')
cleaned_code = '\n'.join([line.strip() for line in block.split('\n')[1:] if line.strip()])
exec(cleaned_code, {'df': df, 'plt': plt})
plt.title(f"Visualization {i}", fontsize=14)
plt.tight_layout()
buf = io.BytesIO()
plt.savefig(buf, format='png', dpi=120, bbox_inches='tight')
plt.close()
buf.seek(0)
visualizations.append(Image.open(buf))
except Exception as e:
print(f"Visualization {i} failed: {str(e)}")
visualizations.append(Image.new('RGB', (1920, 1080), color=(73, 109, 137)))
while len(visualizations) < 3:
visualizations.append(Image.new('RGB', (1920, 1080), color=(73, 109, 137)))
return visualizations[:3]
# Gradio interface
with gr.Blocks(theme=gr.themes.Default(spacing_size="lg")) as demo:
gr.Markdown("# **HD Data Visualizer** 📊✨")
with gr.Row():
api_key = gr.Textbox(label="🔑 Gemini API Key", type="password")
file = gr.File(label="📁 Upload Dataset", file_types=[".csv", ".xlsx"])
instructions = gr.Textbox(label="💡 Custom Instructions (optional)",
placeholder="E.g.: Focus on time series patterns...")
submit = gr.Button("🚀 Generate Visualizations", variant="primary")
with gr.Row():
outputs = [gr.Image(label=f"Visualization {i+1}", width=600) for i in range(3)]
submit.click(
process_file,
inputs=[api_key, file, instructions],
outputs=outputs
)
demo.launch() |