Upload app.py

app.py

@@ -0,0 +1,166 @@
+import gradio as gr
+import os
+from gradio_interfaces.conversation_labeling.interface_utils import *
+
+maxim = 'quantity'
+submaxims = ["The response provides a sufficient amount of information.",
+             "The response does not contain unnecessary details."]
+checkbox_choices = [
+    ["Yes", "No", "NA"],
+    ["Yes", "No", "NA"]
+]
+
+conversation_data = load_from_jsonl('./unlabeled/conversations_unlabeled.jsonl')
+max_conversation_length = max([len(conversation['transcript']) for conversation in conversation_data])
+conversation = get_conversation(conversation_data)
+
+
+def save_labels(conv_id, skipped, submaxim_0=None, submaxim_1=None):
+    data = {
+        'conv_id': conv_id,
+        'maxim': maxim,
+        'skipped': skipped,
+        'submaxim_0': submaxim_0,
+        'submaxim_1': submaxim_1,
+    }
+    os.makedirs("./labels", exist_ok=True)
+
+    with open(f"./labels/{maxim}_human_labels_{conv_id}.json", 'w') as f:
+        json.dump(data, f, indent=4)
+
+
+def update_interface(new_conversation):
+    new_conv_id = new_conversation['conv_id']
+    new_transcript = pad_transcript(new_conversation['transcript'], max_conversation_length)
+
+    markdown_blocks = [None] * max_conversation_length
+    for i in range(max_conversation_length):
+        if new_transcript[i]['speaker'] != '':
+            markdown_blocks[i] = gr.Markdown(f"""  **{new_transcript[i]['speaker']}**:      {new_transcript[i]['response']}""",
+                                             visible=True)
+        else:
+            markdown_blocks[i] = gr.Markdown("", visible=False)
+
+    new_last_response = gr.Text(value=get_last_response(new_transcript),
+                                label="",
+                                lines=1,
+                                container=False,
+                                interactive=False,
+                                autoscroll=True,
+                                visible=True)
+    new_radio_0_base = gr.Radio(label=submaxims[0],
+                                choices=checkbox_choices[0],
+                                value=None,
+                                visible=True)
+    new_radio_1_base = gr.Radio(label=submaxims[1],
+                                choices=checkbox_choices[1],
+                                value=None,
+                                visible=True)
+    conv_len = gr.Number(value=len(new_transcript), visible=False)
+
+    return [new_conv_id] + list(markdown_blocks) + [new_last_response] + [new_radio_0_base] + [new_radio_1_base] + [conv_len]
+
+
+def submit(*args):
+    conv_id = args[0]
+    submaxim_0 = args[-3]
+    submaxim_1 = args[-2]
+
+    save_labels(conv_id, skipped=False, submaxim_0=submaxim_0, submaxim_1=submaxim_1)
+
+    new_conversation = get_conversation(conversation_data)
+    return update_interface(new_conversation)
+
+
+def skip(*args):
+    conv_id = args[0]
+    save_labels(conv_id, skipped=True)
+
+    new_conversation = get_conversation(conversation_data)
+    return update_interface(new_conversation)
+
+
+with gr.Blocks(theme=gr.themes.Default()) as interface:
+    conv_id = conversation['conv_id']
+    transcript = conversation['transcript']
+    conv_len = gr.Number(value=len(transcript), visible=False)
+    padded_transcript = pad_transcript(transcript, max_conversation_length)
+
+    markdown_blocks = [None] * max_conversation_length
+    with gr.Column(scale=1, min_width=600):
+        with gr.Group():
+            gr.Markdown("""<span style='font-size: 16px;'>&nbsp;&nbsp;&nbsp;&nbsp;**Conversational context** </span>""",
+                        visible=True)
+        for i in range(max_conversation_length):
+            markdown_blocks[i] = gr.Markdown(f"""&nbsp;&nbsp;**{padded_transcript[i]['speaker']}**: &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;{padded_transcript[i]['response']}""")
+            if i >= conv_len.value:
+                markdown_blocks[i].visible = False
+
+        with gr.Row():
+            with gr.Group(elem_classes="bottom-aligned-group"):
+                speaker_adapted = gr.Markdown(
+                    f"""<span style='font-size: 16px;'>&nbsp;&nbsp;&nbsp;&nbsp;**Response to label** </span>""",
+                    visible=True)
+                last_response = gr.Textbox(value=get_last_response(transcript),
+                                           label="",
+                                           lines=1,
+                                           container=False,
+                                           interactive=False,
+                                           autoscroll=True,
+                                           visible=True)
+                radio_submaxim_0_base = gr.Radio(label=submaxims[0],
+                                                 choices=checkbox_choices[0],
+                                                 value=None,
+                                                 visible=True)
+                radio_submaxim_1_base = gr.Radio(label=submaxims[1],
+                                                 choices=checkbox_choices[1],
+                                                 value=None,
+                                                 visible=True)
+
+    submit_button = gr.Button("Submit")
+    skip_button = gr.Button("Skip")
+
+    conv_id_element = gr.Text(value=conv_id, visible=False)
+    input_list = [conv_id_element] + \
+                 markdown_blocks + \
+                 [last_response] + \
+                 [radio_submaxim_0_base] + \
+                 [radio_submaxim_1_base] + \
+                 [conv_len]
+    submit_button.click(
+        fn=submit,
+        inputs=input_list,
+        outputs=[conv_id_element,
+                 *markdown_blocks,
+                 last_response,
+                 radio_submaxim_0_base,
+                 radio_submaxim_1_base,
+                 conv_len]
+    )
+    skip_button.click(
+        fn=skip,
+        inputs=input_list,
+        outputs=[conv_id_element,
+                 *markdown_blocks,
+                 last_response,
+                 radio_submaxim_0_base,
+                 radio_submaxim_1_base,
+                 conv_len]
+    )
+
+css = """
+#textbox_id textarea {
+    background-color: white;
+}
+
+.bottom-aligned-group {
+    display: flex;
+    flex-direction: column;
+    justify-content: flex-end;
+    height: 100%;
+}
+"""
+interface.css = css
+interface.launch()
+
+