Update app.py
Browse files
app.py
CHANGED
@@ -3,7 +3,7 @@ import pandas as pd
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import matplotlib.pyplot as plt
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import io
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import ast
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from PIL import Image
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import google.generativeai as genai
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def process_file(api_key, file, instructions):
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@@ -13,30 +13,25 @@ def process_file(api_key, file, instructions):
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model = genai.GenerativeModel('gemini-pro')
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# Read uploaded file
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file_path = file.name
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if file_path.endswith('.csv')
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df = pd.read_csv(file_path)
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else:
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df = pd.read_excel(file_path)
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# Generate visualization code
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columns = list(df.columns)
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response = model.generate_content(f"""
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Create 3 matplotlib visualization codes based on: {instructions}
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Data columns: {columns}
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Return
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Allowed plot_types: bar, line, scatter, hist
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Use only DataFrame 'df' and these exact variable names.
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""")
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#
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plots = ast.literal_eval(response.text.split('```')[-2].strip('python\n '))
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if len(plots) != 3:
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raise ValueError("Exactly 3 visualizations required")
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# Generate plots
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images = []
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for plot in plots:
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fig = plt.figure()
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title, plot_type, x, y = plot
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@@ -56,7 +51,7 @@ def process_file(api_key, file, instructions):
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images.append(Image.open(buf))
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plt.close()
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return images
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except Exception as e:
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error_image = Image.new('RGB', (800, 100), (255, 255, 255))
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@@ -71,4 +66,17 @@ with gr.Blocks(theme=gr.themes.Default(spacing_size="lg")) as demo:
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api_key = gr.Textbox(label="Gemini API Key", type="password")
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file = gr.File(label="Upload Dataset", file_types=[".csv", ".xlsx"])
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instructions = gr.Textbox(label="Analysis Instructions
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import matplotlib.pyplot as plt
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import io
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import ast
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from PIL import Image, ImageDraw
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import google.generativeai as genai
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def process_file(api_key, file, instructions):
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model = genai.GenerativeModel('gemini-pro')
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# Read uploaded file
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file_path = file.name
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df = pd.read_csv(file_path) if file_path.endswith('.csv') else pd.read_excel(file_path)
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# Generate visualization code
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response = model.generate_content(f"""
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Create 3 matplotlib visualization codes based on: {instructions}
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Data columns: {list(df.columns)}
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Return Python code as: [('title','plot_type','x','y'), ...]
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Allowed plot_types: bar, line, scatter, hist
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Use only DataFrame 'df' and these exact variable names.
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""")
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# Extract code block safely
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code_block = response.text.split('```python')[1].split('```')[0].strip()
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plots = ast.literal_eval(code_block)
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# Generate visualizations
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images = []
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for plot in plots[:3]: # Ensure max 3 plots
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fig = plt.figure()
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title, plot_type, x, y = plot
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images.append(Image.open(buf))
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plt.close()
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return images if len(images) == 3 else images + [Image.new('RGB', (800, 600), (255,255,255))]*(3-len(images))
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except Exception as e:
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error_image = Image.new('RGB', (800, 100), (255, 255, 255))
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api_key = gr.Textbox(label="Gemini API Key", type="password")
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file = gr.File(label="Upload Dataset", file_types=[".csv", ".xlsx"])
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instructions = gr.Textbox(label="Analysis Instructions")
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submit = gr.Button("Generate Insights", variant="primary")
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with gr.Row():
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outputs = [gr.Image(label=f"Visualization {i+1}", width=600) for i in range(3)]
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submit.click(
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process_file,
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inputs=[api_key, file, instructions],
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outputs=outputs
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)
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if __name__ == "__main__":
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demo.launch()
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