Create app.py

app.py

@@ -0,0 +1,29 @@
+import os
+import gradio as gr
+from gradio_client import Client
+
+MY_HF_TOKEN_KEY = os.environ["MY_HF_TOKEN_KEY"]
+
+client = Client("Ghana-NLP/Khaya-image-caption-backend",hf_token=MY_HF_TOKEN_KEY)
+
+def generate(filepath,language):
+    output = client.predict(filepath,language,api_name="/predict")
+    return output
+
+with gr.Blocks() as demo:
+    title = gr.Markdown(
+    """
+    # African Language Image Captioning
+    Based on the Khaya AI & Lesan APIs and the BLIP model"
+    """)    
+    language_selector = gr.Dropdown(["Twi","Dagbani","Ewe","Ga","Gurene","Fante","Hausa", "Kikuyu", "Kimeru", "Luo","Shona","Swahili","Tigrinya","Yoruba"],value="Twi",label="Choose Language! (default is Twi)", info="Language:")
+    inputs = [gr.Image(type="pil"),language_selector)]
+    outputs = [gr.Textbox(label="English Caption"), gr.Textbox(label="African Language Caption"),
+               gr.Image(label="Output image with predicted instances", type="pil")]
+    examples = [["https://raw.githubusercontent.com/gradio-app/gradio/main/test/test_files/bus.png"],
+                ["https://raw.githubusercontent.com/gradio-app/gradio/main/test/test_files/rotated_image.jpeg"]]
+    btn = gr.Button("Generate African Language Caption")
+    btn.click(generate, inputs=inputs, outputs=outputs)
+
+if __name__ == "__main__":
+    demo.queue(max_size=20).launch()