Create app.py

app.py

@@ -0,0 +1,153 @@
+import json
+import gradio as gr
+import pandas as pd
+import dspy
+
+
+# -----------------------------
+# DSPy Signature
+# -----------------------------
+class GenerateQA(dspy.Signature):
+    """Generate a simple synthetic question-answer example."""
+    topic = dspy.InputField(desc="topic for the synthetic example")
+    difficulty = dspy.InputField(desc="easy, medium, or hard")
+    question = dspy.OutputField(desc="a clear question about the topic")
+    answer = dspy.OutputField(desc="a short correct answer")
+
+
+# -----------------------------
+# Core generator
+# -----------------------------
+def generate_synthetic_data(
+    openai_api_key: str,
+    topic: str,
+    difficulty: str,
+    num_examples: int
+):
+    if not openai_api_key or not openai_api_key.strip():
+        return (
+            pd.DataFrame([{"error": "Please enter your OpenAI API key."}]),
+            json.dumps({"error": "Missing OpenAI API key."}, indent=2)
+        )
+
+    if not topic or not topic.strip():
+        return (
+            pd.DataFrame([{"error": "Please enter a topic."}]),
+            json.dumps({"error": "Missing topic."}, indent=2)
+        )
+
+    try:
+        # Configure DSPy with an OpenAI-compatible LM
+        lm = dspy.LM(
+            model="openai/gpt-4o-mini",
+            api_key=openai_api_key.strip()
+        )
+        dspy.configure(lm=lm)
+
+        generator = dspy.Predict(GenerateQA)
+
+        rows = []
+        for i in range(num_examples):
+            pred = generator(
+                topic=topic.strip(),
+                difficulty=difficulty,
+                config={"temperature": 1.0, "rollout_id": i + 1}
+            )
+
+            rows.append({
+                "topic": topic.strip(),
+                "difficulty": difficulty,
+                "question": pred.question,
+                "answer": pred.answer
+            })
+
+        df = pd.DataFrame(rows)
+        return df, json.dumps(rows, indent=2)
+
+    except Exception as e:
+        error_payload = {"error": str(e)}
+        return pd.DataFrame([error_payload]), json.dumps(error_payload, indent=2)
+
+
+# -----------------------------
+# Example loader
+# -----------------------------
+def load_example(example_topic):
+    return example_topic
+
+
+# -----------------------------
+# Gradio UI
+# -----------------------------
+EXAMPLE_TOPICS = [
+    "machine learning",
+    "prompt engineering",
+    "financial literacy",
+    "cybersecurity basics",
+    "project management"
+]
+
+with gr.Blocks(title="DSPy Synthetic Data Creator") as demo:
+    gr.Markdown(
+        """
+        # DSPy Synthetic Data Creator
+        Generate simple synthetic Q&A examples using DSPy + OpenAI.
+        """
+    )
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            api_key = gr.Textbox(
+                label="OpenAI API Key",
+                placeholder="Paste your OpenAI API key here",
+                type="password"
+            )
+
+            topic = gr.Textbox(
+                label="Topic",
+                placeholder="Example: machine learning"
+            )
+
+            difficulty = gr.Dropdown(
+                choices=["easy", "medium", "hard"],
+                value="easy",
+                label="Difficulty"
+            )
+
+            num_examples = gr.Slider(
+                minimum=1,
+                maximum=20,
+                value=5,
+                step=1,
+                label="Number of Examples"
+            )
+
+            generate_btn = gr.Button("Generate Synthetic Data", variant="primary")
+
+        with gr.Column(scale=1):
+            gr.Markdown("### Example starting inputs")
+            for item in EXAMPLE_TOPICS:
+                example_btn = gr.Button(item)
+                example_btn.click(
+                    fn=load_example,
+                    inputs=gr.State(item),
+                    outputs=topic
+                )
+
+    gr.Markdown("### Generated Table")
+    output_table = gr.Dataframe(
+        headers=["topic", "difficulty", "question", "answer"],
+        datatype=["str", "str", "str", "str"],
+        interactive=False
+    )
+
+    gr.Markdown("### JSON Output")
+    output_json = gr.Code(label="JSON", language="json")
+
+    generate_btn.click(
+        fn=generate_synthetic_data,
+        inputs=[api_key, topic, difficulty, num_examples],
+        outputs=[output_table, output_json]
+    )
+
+demo.launch()