test2

app.py

@@ -9,43 +9,43 @@ rg.init(
     #extra_headers={"Authorization": f"Bearer YOUR_HF_TOKEN"}
 )
 
-banking_ds = load_dataset("argilla/banking_sentiment_setfit", split="train")
-
-# Argilla expects labels in the annotation column
-banking_ds = banking_ds.rename_column("label", "annotation")
-
-# Build argilla dataset from datasets
-argilla_ds = rg.read_datasets(banking_ds, task="TextClassification")
-
-rg.log(argilla_ds, "banking_sentiment")
-
-# def evaluate_response(prompt, response, quality, feedback):
-#     record = rg.FeedbackRecord(
-#         fields={"prompt": prompt, "llm_response": response},
-#         responses=[{
-#             "values": {
-#                 "quality": quality,
-#                 "feedback": feedback
-#             }
-#         }]
-#     )
-#     dataset = rg.FeedbackDataset.from_argilla("llm-eval")
-#     dataset.add_records(record)
-#     return "Evaluation submitted!"
-
-# with gr.Blocks() as demo:
-#     gr.Markdown("## LLM Response Evaluation")
-#     with gr.Row():
-#         prompt = gr.Textbox(label="Original Prompt")
-#         response = gr.Textbox(label="LLM Response")
-#     quality = gr.Radio([1,2,3,4,5], label="Quality Rating")
-#     feedback = gr.Textbox(label="Additional Feedback")
-#     submit = gr.Button("Submit")
-#     output = gr.Textbox()
-#     submit.click(
-#         fn=evaluate_response,
-#         inputs=[prompt, response, quality, feedback],
-#         outputs=output
-#     )
-
-# demo.launch()
+# banking_ds = load_dataset("argilla/banking_sentiment_setfit", split="train")
+
+# # Argilla expects labels in the annotation column
+# banking_ds = banking_ds.rename_column("label", "annotation")
+
+# # Build argilla dataset from datasets
+# argilla_ds = rg.read_datasets(banking_ds, task="TextClassification")
+
+# rg.log(argilla_ds, "banking_sentiment")
+
+def evaluate_response(prompt, response, quality, feedback):
+    record = rg.FeedbackRecord(
+        fields={"prompt": prompt, "llm_response": response},
+        responses=[{
+            "values": {
+                "quality": quality,
+                "feedback": feedback
+            }
+        }]
+    )
+    dataset = rg.FeedbackDataset.from_argilla("llm-eval")
+    dataset.add_records(record)
+    return "Evaluation submitted!"
+
+with gr.Blocks() as demo:
+    gr.Markdown("## LLM Response Evaluation")
+    with gr.Row():
+        prompt = gr.Textbox(label="Original Prompt")
+        response = gr.Textbox(label="LLM Response")
+    quality = gr.Radio([1,2,3,4,5], label="Quality Rating")
+    feedback = gr.Textbox(label="Additional Feedback")
+    submit = gr.Button("Submit")
+    output = gr.Textbox()
+    submit.click(
+        fn=evaluate_response,
+        inputs=[prompt, response, quality, feedback],
+        outputs=output
+    )
+
+demo.launch()