initial commit

app.py

@@ -0,0 +1,122 @@
+import gradio as gr
+from transformers import pipeline
+from fine_tune_hf import FinetuneHFModel
+
+fine_tune_model = FinetuneHFModel()
+
+playground = gr.Blocks()
+
+
+def review_training_choices(choice):
+    print(choice)
+    if choice == "Use Pipeline":
+        return gr.Row(visible=True)
+    else:
+        return gr.Row(visible=False)
+
+
+def show_optional_fields(task):
+    if task == "question-answering":
+        return gr.TextArea(visible=True)
+    return gr.TextArea(visible=False)
+
+
+def test_pipeline(task, model=None, prompt=None, context=None):
+    if model:
+        test = pipeline(task, model=model)
+    else:
+        if task == "ner":
+            test = pipeline(task, grouped_entities=True)
+        else:
+            test = pipeline(task)
+    if task == "question-answering":
+        if not context:
+            return "Context is required"
+        else:
+            result = test(question=prompt, context=context)
+    else:
+        result = test(prompt)
+    match task:
+        case "text-generation":
+            return gr.TextArea(result[0]["generated_text"])
+        case "fill-mask":
+            return gr.TextArea(result[0]["sequence"])
+        case "summarization":
+            return gr.TextArea(result[0]["summary_text"])
+        case "ner":
+            ner_result = "\n".join(
+                f"{k}={v}" for item in result for k, v in item.items() if k not in ["start", "end", "index"])
+            return gr.TextArea(ner_result.rstrip("\n"))
+
+        case "question-answering":
+            return gr.TextArea(result)
+
+
+with playground:
+    gr.Markdown("""
+                Try your ideas here. Select from Text, Image or Audio
+                """)
+    with gr.Tabs():
+        with gr.TabItem("Text"):
+            with gr.Row():
+                with gr.Column(scale=4):
+                    radio = gr.Radio(
+                        ["Use Pipeline", "Fine Tune"],
+                        label="Select Use Pipeline to try out HF    models or Fine Tune to test it on your own datasets",
+                        value="Use Pipeline",
+                        interactive=True,
+                    )
+                with gr.Column(scale=1):
+                    test_pipeline_button = gr.Button(
+                        value="Test", variant="primary", size="sm")
+            with gr.Row(visible=True) as use_pipeline:
+                with gr.Column():
+                    task_dropdown = gr.Dropdown(
+                        [("Text Generation", "text-generation"), ("Fill Mask",
+                                                                  "fill-mask"), ("Summarization", "summarization"), ("Named Entity Recognition", "ner"), ("Question Answering", "question-answering")],
+                        label="task",
+                    )
+                    model_dropdown = gr.Dropdown(
+                        [],
+                        label="model",
+                        allow_custom_value=True,
+                        interactive=True
+                    )
+                    prompt_textarea = gr.TextArea(
+                        label="prompt", value="Enter your prompt here", text_align="left")
+                    context_for_question_answer = gr.TextArea(
+                        label="Context", value="Enter Context for your question here", visible=False, interactive=True)
+                    task_dropdown.change(show_optional_fields, inputs=[
+                                         task_dropdown], outputs=[context_for_question_answer])
+                with gr.Column():
+                    text = gr.TextArea(label="Generated Text")
+            radio.change(review_training_choices,
+                         inputs=radio, outputs=use_pipeline)
+            test_pipeline_button.click(test_pipeline, inputs=[
+                                       task_dropdown, model_dropdown, prompt_textarea, context_for_question_answer], outputs=text)
+        with gr.TabItem("Image"):
+            with gr.Row():
+                with gr.Column(scale=3):
+                    radio = gr.Radio(
+                        ["Use Pipeline", "Fine Tune"],
+                        label="Select Use Pipeline to try out HF    models or Fine Tune to test it on your own datasets",
+                        value="Use Pipeline",
+                        interactive=True
+                    )
+                with gr.Column(scale=1):
+                    test_pipeline_button = gr.Button(
+                        value="Test", variant="primary", size="sm")
+        with gr.TabItem("Audio"):
+            with gr.Row():
+                with gr.Column(scale=3):
+                    radio = gr.Radio(
+                        ["Use Pipeline", "Fine Tune"],
+                        label="Select Use Pipeline to try out HF    models or Fine Tune to test it on your own datasets",
+                        value="Use Pipeline",
+                        interactive=True
+                    )
+                with gr.Column(scale=1):
+                    test_pipeline_button = gr.Button(
+                        value="Test", variant="primary", size="sm")
+
+playground.launch(share=True)