Create app.py

app.py

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+import os
+from dotenv import load_dotenv
+import gradio as gr
+from agents import Agent, Runner, AsyncOpenAI, OpenAIChatCompletionsModel
+from agents.run import RunConfig
+import asyncio
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Retrieve the Gemini API key from environment variables
+gemini_api_key = os.getenv("GEMINI_API_KEY")
+
+# Check if the API key is present; if not, raise an error
+if not gemini_api_key:
+    raise ValueError("GEMINI_API_KEY is not set. Please ensure it is defined in your .env file.")
+
+# Configure the AsyncOpenAI client for Gemini API
+external_client = AsyncOpenAI(
+    api_key=gemini_api_key,
+    base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
+)
+
+# Define the model
+model = OpenAIChatCompletionsModel(
+    model="gemini-2.0-flash",
+    openai_client=external_client
+)
+
+# Configure the run settings
+config = RunConfig(
+    model=model,
+    model_provider=external_client,
+    tracing_disabled=True
+)
+
+# Define the translation function
+async def translate_urdu_to_english(urdu_text):
+    agent = Agent(
+        name="Translator",
+        instructions="You are a translator, always translate Urdu sentences into English Language.",
+        model=model
+    )
+    result = await Runner.run(agent, urdu_text, run_config=config)
+    return result.final_output
+
+# Gradio interface function
+def gradio_translate(urdu_input):
+    # Run the async translation function within Gradio
+    return asyncio.run(translate_urdu_to_english(urdu_input))
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=gradio_translate,
+    inputs=gr.Textbox(label="Urdu Input", placeholder="Enter Urdu sentence here..."),
+    outputs=gr.Textbox(label="English Translation"),
+    title="Urdu to English Translator",
+    description="Enter an Urdu sentence to get its English translation using the Gemini API."
+)
+
+# Launch the Gradio app
+if __name__ == "__main__":
+    iface.launch()