Create app.py

app.py

@@ -0,0 +1,45 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load Mistral-Nemo-Instruct-2407
+model = pipeline(
+    "text-generation",
+    model="mistralai/Mistral-Nemo-Instruct-2407",  # Official model name
+    torch_dtype=torch.float16  # Reduce memory usage
+)
+
+def generate_test_cases(requirement):
+    prompt = f"""
+    Generate test cases for '{requirement}' in JSON format. Output only the array. No explanations.
+
+    Example format:
+    [
+        {{
+            "id": 1,
+            "title": "Valid Login",
+            "steps": ["Enter valid email", "Enter valid password"],
+            "expected_result": "Redirect to dashboard"
+        }},
+        {{
+            "id": 2,
+            "title": "Invalid Password",
+            "steps": ["Enter valid email", "Enter wrong password"],
+            "expected_result": "Error message displayed"
+        }}
+    ]
+    """  
+    result = model(prompt, max_length=300)[0]["generated_text"]
+    return result.strip()  # Remove extra whitespace
+
+# Create Gradio interface
+demo = gr.Interface(
+    fn=generate_test_cases,
+    inputs="text",
+    outputs="text",
+    title="Test Case Generator",
+    description="Enter a requirement to generate test cases."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)