first commit

.gitignore

@@ -0,0 +1,10 @@
+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+
+# Virtual environments
+.venv

.python-version

@@ -0,0 +1 @@
+3.11

app.py

@@ -0,0 +1,123 @@
+import gradio as gr
+import plotly.express as px
+import numpy as np
+import pandas as pd
+from sklearn.metrics import confusion_matrix
+from PIL import Image
+from io import BytesIO
+
+def generate_plot(
+    x_sequence: str, 
+    y_sequence: str, 
+    plot_type: str, 
+    x_label: str, 
+    y_label: str, 
+    width: int, 
+    height: int
+) -> Image:
+    """
+    Generate a plot based on the provided x and y sequences and plot type.
+
+    Parameters:
+    - x_sequence (str): A comma-separated string of x values.
+    - y_sequence (str): A comma-separated string of y values.
+    - plot_type (str): The type of plot to generate ('Bar', 'Scatter', 'Confusion Matrix').
+    - x_label (str): Label for the x-axis.
+    - y_label (str): Label for the y-axis.
+    - width (int): Width of the plot.
+    - height (int): Height of the plot.
+
+    Returns:
+    - Image: A PIL Image object of the generated plot.
+    """
+    # Convert the input sequences to lists of numbers
+    try:
+        x_data = list(map(float, x_sequence.split(",")))
+        y_data = list(map(float, y_sequence.split(",")))
+    except ValueError:
+        return "Invalid input. Please enter sequences of numbers separated by commas."
+
+    # Ensure the x and y sequences have the same length
+    if len(x_data) != len(y_data):
+        return "The x and y sequences must have the same length."
+
+    # Create a DataFrame for plotting
+    df = pd.DataFrame({"x": x_data, "y": y_data})
+
+    # Set default width and height if not provided
+    width = width if width else 800
+    height = height if height else 600
+
+    # Generate the plot based on the selected type
+    if plot_type == "Bar":
+        fig = px.bar(
+            df,
+            x="x",
+            y="y",
+            title="Bar Plot",
+            labels={"x": x_label, "y": y_label},
+            width=width,
+            height=height,
+        )
+    elif plot_type == "Scatter":
+        fig = px.scatter(
+            df,
+            x="x",
+            y="y",
+            title="Scatter Plot",
+            labels={"x": x_label, "y": y_label},
+            width=width,
+            height=height,
+        )
+    elif plot_type == "Confusion Matrix":
+        # For demonstration, create a confusion matrix from the sequence
+        y_true = np.random.randint(0, 2, len(y_data))
+        y_pred = np.array(y_data) > 0.5
+        cm = confusion_matrix(y_true, y_pred)
+        fig = px.imshow(
+            cm, text_auto=True, title="Confusion Matrix", width=width, height=height
+        )
+    else:
+        return "Invalid plot type selected."
+
+    # Convert the plot to a PNG image
+    img_bytes = fig.to_image(
+        format="png", width=width, height=height, scale=2, engine="kaleido"
+    )
+    return Image.open(BytesIO(img_bytes))
+
+
+# Define the Gradio interface using the new syntax
+app = gr.Interface(
+    fn=generate_plot,
+    inputs=[
+        gr.Textbox(
+            lines=2,
+            placeholder="Enter x sequence of numbers separated by commas",
+            label="X",
+        ),
+        gr.Textbox(
+            lines=2,
+            placeholder="Enter y sequence of numbers separated by commas",
+            label="Y",
+        ),
+        gr.Radio(["Bar", "Scatter", "Confusion Matrix"], label="Type", value="Bar"),
+        gr.Textbox(
+            placeholder="Enter x-axis label (optional)", label="X_Label", value=""
+        ),
+        gr.Textbox(
+            placeholder="Enter y-axis label (optional)", label="Y_Label", value=""
+        ),
+        gr.Number(
+            value=800,
+            label="Width",
+        ),
+        gr.Number(value=600, label="Height"),
+    ],
+    outputs=gr.Image(type="pil", label="Generated Plot"),
+    title="Plotly Plot Generator",
+    description="Generate plots using Plotly based on inputted sequences. Choose from Bar, Scatter, or Confusion Matrix plots.",
+)
+
+# Launch the app
+app.launch()

pyproject.toml

@@ -0,0 +1,13 @@
+[project]
+name = "agent-plotly"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "gradio>=5.12.0",
+    "ipykernel>=6.29.5",
+    "plotly>=5.24.1",
+    "scikit-learn>=1.6.1",
+    "smolagents>=1.2.2",
+]