Update app.py

app.py

@@ -1,93 +1,59 @@
-import gradio as gr
-import requests
-from MathEngine import calculate, CalculationRequest, app as fastapi_app
-import uvicorn
-from multiprocessing import Process
-from pyngrok import ngrok
-
-# Gradio Interface
-history = []
-current_input = ""
-
-def gradio_calculate(a, b, operation):
-    request = CalculationRequest(a=a, b=b, operation=operation)
-    response = calculate(request)
-    result = response["result"]
-    history.append(f"{a} {operation} {b} = {result}")
-    return "\n".join(history)
-
-def update_input(digit):
-    global current_input
-    current_input += str(digit)
-    return current_input
-
-def clear_input():
-    global current_input
-    current_input = ""
-    return current_input
-
-def backspace():
-    global current_input
-    current_input = current_input[:-1]
-    return current_input
-
-def test_fastapi(a, b, operation):
-    url = f"{ngrok_tunnel}/calculate"
-    payload = {"a": a, "b": b, "operation": operation}
-    headers = {"Content-Type": "application/json"}
-    response = requests.post(url, json=payload, headers=headers)
-    return response.json()
-
-def create_interface():
-    with gr.Blocks() as demo:
-        a = gr.Number(label="A", interactive=True)
-        b = gr.Number(label="B", interactive=True)
-        result = gr.Textbox(label="Result", lines=10, interactive=False)
-        current = gr.Textbox(label="Current Input", interactive=False)
-
-        with gr.Row():
-            for i in range(10):
-                gr.Button(str(i)).click(lambda x=i: update_input(x), inputs=[], outputs=current)
-            gr.Button("Back").click(backspace, inputs=[], outputs=current)
-            gr.Button("Clear").click(clear_input, inputs=[], outputs=current)
-
-        with gr.Row():
-            gr.Button("Set A").click(lambda x: float(current_input), inputs=[], outputs=a)
-            gr.Button("Set B").click(lambda x: float(current_input), inputs=[], outputs=b)
-
-        with gr.Row():
-            gr.Button("Add").click(lambda a, b: gradio_calculate(a, b, "add"), inputs=[a, b], outputs=result)
-            gr.Button("Subtract").click(lambda a, b: gradio_calculate(a, b, "subtract"), inputs=[a, b], outputs=result)
-            gr.Button("Multiply").click(lambda a, b: gradio_calculate(a, b, "multiply"), inputs=[a, b], outputs=result)
-            gr.Button("Divide").click(lambda a, b: gradio_calculate(a, b, "divide"), inputs=[a, b], outputs=result)
-
-        with gr.Row():
-            gr.Button("Test FastAPI Add").click(lambda a, b: test_fastapi(a, b, "add"), inputs=[a, b], outputs=result)
-            gr.Button("Test FastAPI Subtract").click(lambda a, b: test_fastapi(a, b, "subtract"), inputs=[a, b], outputs=result)
-            gr.Button("Test FastAPI Multiply").click(lambda a, b: test_fastapi(a, b, "multiply"), inputs=[a, b], outputs=result)
-            gr.Button("Test FastAPI Divide").click(lambda a, b: test_fastapi(a, b, "divide"), inputs=[a, b], outputs=result)
-
-    return demo
-
-def run_gradio():
-    demo = create_interface()
-    demo.launch()
-
-def run_fastapi():
-    uvicorn.run(fastapi_app, host="0.0.0.0", port=8000)
-
-def run_ngrok():
-    global ngrok_tunnel
-    ngrok_tunnel = ngrok.connect(8000)
-    print(f" * Ngrok tunnel available at: {ngrok_tunnel.public_url}")
-
-if __name__ == "__main__":
-    p1 = Process(target=run_gradio)
-    p2 = Process(target=run_fastapi)
-    p3 = Process(target=run_ngrok)
-    p1.start()
-    p2.start()
-    p3.start()
-    p1.join()
-    p2.join()
-    p3.join()
+from fastapi import FastAPI
+from pydantic import BaseModel
+from transformers import pipeline
+
+app = FastAPI()
+
+# Define request model for math operations
+class CalculationRequest(BaseModel):
+    a: float
+    b: float
+    operation: str
+
+# Load Hugging Face model (example: a simple text generation model)
+model = pipeline('text-generation', model='gpt2')
+
+@app.post("/calculate")
+def calculate(request: CalculationRequest):
+    a = request.a
+    b = request.b
+    operation = request.operation
+
+    if operation == "add":
+        result = a + b
+    elif operation == "subtract":
+        result = a - b
+    elif operation == "multiply":
+        result = a * b
+    elif operation == "divide":
+        result = a / b
+    else:
+        return {"error": "Invalid operation"}
+
+    return {"result": result}
+
+# Example endpoint using Hugging Face model
+@app.post("/generate")
+def generate_text(prompt: str):
+    generated = model(prompt, max_length=50)
+    return {"generated_text": generated[0]['generated_text']}
+
+# New endpoint for testing math operations
+@app.post("/test_math")
+def test_math(request: CalculationRequest):
+    a = request.a
+    b = request.b
+    operation = request.operation
+
+    if operation == "add":
+        result = a + b
+    elif operation == "subtract":
+        result = a - b
+    elif operation == "multiply":
+        result = a * b
+    elif operation == "divide":
+        result = a / b
+    else:
+        return {"error": "Invalid operation"}
+
+    return {"result": result}