Update app.py
Browse files
app.py
CHANGED
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@@ -6,83 +6,18 @@ import google.generativeai as genai
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from PIL import Image
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def process_file(api_key, file, instructions):
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model = genai.GenerativeModel('gemini-2.5-pro-latest')
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if file.name.endswith('.csv'):
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df = pd.read_csv(file.name)
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else:
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df = pd.read_excel(file.name)
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except Exception as e:
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return [f"File Error: {str(e)}"] * 3
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# Enhanced prompt with visualization requirements
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prompt = f"""Generate exactly 3 distinct matplotlib visualization codes for this dataset:
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Columns: {list(df.columns)}
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Data types: {dict(df.dtypes)}
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Sample data: {df.head(3).to_dict()}
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Requirements:
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1. 1920x1080 resolution (figsize=(16,9), dpi=120)
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2. Professional styling (seaborn style, grid lines)
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3. Clear labels and titles
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4. Diverse chart types (at least 1 must be non-basic)
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User instructions: {instructions or 'No specific instructions'}
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Format response strictly as:
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# Visualization 1
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plt.figure(figsize=(16,9), dpi=120)
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[code]
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plt.tight_layout()
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# Visualization 2
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...
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"""
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response = model.generate_content(prompt)
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code_blocks = response.text.split("# Visualization ")[1:4] # Force 3 max
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visualizations = []
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for i, block in enumerate(code_blocks, 1):
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try:
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# HD configuration
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plt.figure(figsize=(16, 9), dpi=120)
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plt.style.use('seaborn')
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# Clean and execute code
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cleaned_code = '\n'.join([line.strip() for line in block.split('\n')[1:] if line.strip()])
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exec(cleaned_code, {'df': df, 'plt': plt})
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plt.title(f"Visualization {i}", fontsize=14)
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plt.tight_layout()
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# Save HD image
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buf = io.BytesIO()
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plt.savefig(buf, format='png', dpi=120, bbox_inches='tight')
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plt.close()
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buf.seek(0)
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visualizations.append(Image.open(buf))
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except Exception as e:
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print(f"Visualization {i} failed: {str(e)}")
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visualizations.append(Image.new('RGB', (1920, 1080), color=(73, 109, 137)))
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# Ensure exactly 3 outputs with fallback
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while len(visualizations) < 3:
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visualizations.append(Image.new('RGB', (1920, 1080), color=(73, 109, 137)))
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return visualizations[:3]
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# Gradio interface with HD layout
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with gr.Blocks(theme=gr.themes.Default(spacing_size="xl")) as demo:
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gr.Markdown("# **HD Data Visualizer** πβ¨")
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with gr.Row():
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api_key = gr.Textbox(label="π Gemini API Key", type="password")
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file = gr.File(label="π Upload Dataset", file_types=[".csv", ".xlsx"])
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instructions = gr.Textbox(label="π‘ Custom Instructions (optional)",
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submit = gr.Button("π Generate Visualizations", variant="primary")
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with gr.Row():
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from PIL import Image
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def process_file(api_key, file, instructions):
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# ... [keep the existing process_file function identical] ...
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# Fixed Gradio interface with compatible theme settings
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with gr.Blocks(theme=gr.themes.Default(spacing_size="lg")) as demo: # Changed from "xl" to "lg"
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gr.Markdown("# **HD Data Visualizer** πβ¨")
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with gr.Row():
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api_key = gr.Textbox(label="π Gemini API Key", type="password")
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file = gr.File(label="π Upload Dataset", file_types=[".csv", ".xlsx"])
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instructions = gr.Textbox(label="π‘ Custom Instructions (optional)",
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placeholder="E.g.: Focus on time series patterns...")
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submit = gr.Button("π Generate Visualizations", variant="primary")
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with gr.Row():
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