requirements.txt

gradio
requests
matplotlib

app.py

@@ -0,0 +1,36 @@
+import gradio as gr
+import requests
+import matplotlib.pyplot as plt
+import io
+
+API_KEY = "AIzaSyB_mGS8XANkAnb486014uIDf0tMG64eLX0"
+
+def generate_plot(text_prompt):
+    # Gemini prompt
+    gemini_prompt = f"Generate Python matplotlib code to visualize: {text_prompt}"
+
+    url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key={API_KEY}"
+    headers = {"Content-Type": "application/json"}
+    data = {
+        "contents": [{"parts": [{"text": gemini_prompt}]}]
+    }
+
+    # Gemini response
+    response = requests.post(url, headers=headers, json=data)
+    code = response.json()['candidates'][0]['content']['parts'][0]['text']
+
+    # Plot from Gemini code
+    plt.clf()
+    exec(code, globals())
+
+    # Save plot as image
+    buf = io.BytesIO()
+    plt.savefig(buf, format='png')
+    buf.seek(0)
+
+    return buf.getvalue()
+
+gr.Interface(fn=generate_plot,
+             inputs=gr.Textbox(label="Describe the Data to Visualize"),
+             outputs=gr.Image(type="file", label="Generated Graph"),
+             title="Text to Graph using Gemini AI").launch()