Rijgersberg commited on
Commit
2e8bf47
β€’
1 Parent(s): c79bd97
Files changed (1) hide show
  1. app.py +24 -40
app.py CHANGED
@@ -84,7 +84,7 @@ def donut_chart_total() -> alt.Chart:
84
  source = pd.DataFrame(
85
  {
86
  "values": [annotated_records, pending_records],
87
- "category": ["Completed", "Remaining"],
88
  "colors": ["#4CAF50", "#757575"], # Green for Completed, Grey for Remaining
89
  }
90
  )
@@ -123,7 +123,7 @@ def donut_chart_target() -> alt.Chart:
123
  source = pd.DataFrame(
124
  {
125
  "values": [annotated_records, pending_records],
126
- "category": ["Completed", "Remaining"],
127
  "colors": ["#4CAF50", "#757575"], # Green for Completed, Grey for Remaining
128
  }
129
  )
@@ -154,14 +154,14 @@ def kpi_chart_remaining() -> alt.Chart:
154
 
155
  pending_records = int(os.getenv("TARGET_RECORDS")) - len(target_dataset)
156
  # Assuming you have a DataFrame with user data, create a sample DataFrame
157
- data = pd.DataFrame({"Category": ["Total remaining"], "Value": [pending_records]})
158
 
159
  # Create Altair chart
160
  chart = (
161
  alt.Chart(data)
162
  .mark_text(fontSize=100, align="center", baseline="middle", color="steelblue")
163
  .encode(text="Value:N")
164
- .properties(title="Total remaining", width=250, height=200)
165
  )
166
 
167
  return chart
@@ -177,14 +177,14 @@ def kpi_chart_submitted() -> alt.Chart:
177
  total = len(target_dataset)
178
 
179
  # Assuming you have a DataFrame with user data, create a sample DataFrame
180
- data = pd.DataFrame({"Category": ["Total completed"], "Value": [total]})
181
 
182
  # Create Altair chart
183
  chart = (
184
  alt.Chart(data)
185
  .mark_text(fontSize=100, align="center", baseline="middle", color="steelblue")
186
  .encode(text="Value:N")
187
- .properties(title="Total completed", width=250, height=200)
188
  )
189
 
190
  return chart
@@ -203,7 +203,7 @@ def kpi_chart() -> alt.Chart:
203
 
204
  # Assuming you have a DataFrame with user data, create a sample DataFrame
205
  data = pd.DataFrame(
206
- {"Category": ["Total Contributors"], "Value": [total_annotators]}
207
  )
208
 
209
  # Create Altair chart
@@ -211,7 +211,7 @@ def kpi_chart() -> alt.Chart:
211
  alt.Chart(data)
212
  .mark_text(fontSize=100, align="center", baseline="middle", color="steelblue")
213
  .encode(text="Value:N")
214
- .properties(title="Number of Contributors", width=250, height=200)
215
  )
216
 
217
  return chart
@@ -234,7 +234,7 @@ def obtain_top_5_users(user_ids_annotations: Dict[str, int]) -> pd.DataFrame:
234
  """
235
 
236
  dataframe = pd.DataFrame(
237
- user_ids_annotations.items(), columns=["Name", "Submitted Responses"]
238
  )
239
  dataframe["Name"] = dataframe["Name"].apply(render_hub_user_link)
240
  dataframe = dataframe.sort_values(by="Submitted Responses", ascending=False)
@@ -296,40 +296,24 @@ def main() -> None:
296
  with gr.Blocks(css=css) as demo:
297
  gr.Markdown(
298
  """
299
- # πŸ—£οΈ TKTKTK The Prompt Collective Dashboad
300
 
301
- This Gradio dashboard shows the progress of the first "Data is Better Together" initiative to understand and collect good quality and diverse prompt for the OSS AI community.
302
- If you want to contribute to OSS AI, join [the Prompt Collective HF Space](https://huggingface.co/spaces/DIBT/prompt-collective).
 
 
 
 
 
 
 
303
  """
304
  )
305
 
306
- # gr.Markdown(
307
- # f"""
308
- # ## πŸ“Š Target for Releasing Dataset v2
309
- # How close are we to the target for version 2.0?
310
- # """
311
- # )
312
- # with gr.Row():
313
-
314
- # donut_target_plot = gr.Plot(label="Plot")
315
- # demo.load(
316
- # donut_chart_target,
317
- # inputs=[],
318
- # outputs=[donut_target_plot],
319
- # every=update_interval_charts,
320
- # )
321
-
322
- # gr.Markdown(
323
- # f"""
324
- # ## πŸ“Š Target for Releasing Dataset v1
325
- # Done! Thanks to the awesome DIBT community we've surpassed 10K rated prompts. Open Dataset coming soon!
326
- # """
327
- # )
328
-
329
  gr.Markdown(
330
  f"""
331
- ## πŸš€ Global Progress
332
- Here's what the community has achieved so far!
333
  """
334
  )
335
  with gr.Row():
@@ -360,8 +344,8 @@ def main() -> None:
360
 
361
  gr.Markdown(
362
  """
363
- ## πŸ‘Ύ Contributors Hall of Fame
364
- The number of all contributors and the top contributors:
365
  """
366
  )
367
 
@@ -373,7 +357,7 @@ def main() -> None:
373
  )
374
 
375
  top5_df_plot = gr.Dataframe(
376
- headers=["Name", "Submitted Responses"],
377
  datatype=[
378
  "markdown",
379
  "number",
 
84
  source = pd.DataFrame(
85
  {
86
  "values": [annotated_records, pending_records],
87
+ "category": ["Vertaald", "Nog te gaan"],
88
  "colors": ["#4CAF50", "#757575"], # Green for Completed, Grey for Remaining
89
  }
90
  )
 
123
  source = pd.DataFrame(
124
  {
125
  "values": [annotated_records, pending_records],
126
+ "category": ["Vertaald", "Nog te gaan"],
127
  "colors": ["#4CAF50", "#757575"], # Green for Completed, Grey for Remaining
128
  }
129
  )
 
154
 
155
  pending_records = int(os.getenv("TARGET_RECORDS")) - len(target_dataset)
156
  # Assuming you have a DataFrame with user data, create a sample DataFrame
157
+ data = pd.DataFrame({"Category": ["Nog te gaan"], "Value": [pending_records]})
158
 
159
  # Create Altair chart
160
  chart = (
161
  alt.Chart(data)
162
  .mark_text(fontSize=100, align="center", baseline="middle", color="steelblue")
163
  .encode(text="Value:N")
164
+ .properties(title="Nog te gaan", width=250, height=200)
165
  )
166
 
167
  return chart
 
177
  total = len(target_dataset)
178
 
179
  # Assuming you have a DataFrame with user data, create a sample DataFrame
180
+ data = pd.DataFrame({"Category": ["Totaal vertaald"], "Value": [total]})
181
 
182
  # Create Altair chart
183
  chart = (
184
  alt.Chart(data)
185
  .mark_text(fontSize=100, align="center", baseline="middle", color="steelblue")
186
  .encode(text="Value:N")
187
+ .properties(title="Totaal vertaald", width=250, height=200)
188
  )
189
 
190
  return chart
 
203
 
204
  # Assuming you have a DataFrame with user data, create a sample DataFrame
205
  data = pd.DataFrame(
206
+ {"Category": ["Aantal vertalers"], "Value": [total_annotators]}
207
  )
208
 
209
  # Create Altair chart
 
211
  alt.Chart(data)
212
  .mark_text(fontSize=100, align="center", baseline="middle", color="steelblue")
213
  .encode(text="Value:N")
214
+ .properties(title="Aantal vertalers", width=250, height=200)
215
  )
216
 
217
  return chart
 
234
  """
235
 
236
  dataframe = pd.DataFrame(
237
+ user_ids_annotations.items(), columns=["Username", "Aantal vertalingen"]
238
  )
239
  dataframe["Name"] = dataframe["Name"].apply(render_hub_user_link)
240
  dataframe = dataframe.sort_values(by="Submitted Responses", ascending=False)
 
296
  with gr.Blocks(css=css) as demo:
297
  gr.Markdown(
298
  """
299
+ # πŸ‡³πŸ‡±πŸ‡§πŸ‡ͺ Nederlands - Multilingual Prompt Evaluation Project
300
 
301
+ Hugging Face en @argilla crowdsourcen het [Multilingual Prompt Evaluation Project](https://github.com/huggingface/data-is-better-together/tree/main/prompt_translation): een open meertalige benchmark voor de evaluatie van taalmodellen, en dus ook voor het Nederlands.
302
+
303
+ En zoals altijd: daarvoor is data nodig! Vorige week hebben ze met de community al de beste 500 prompts geselecteerd die de benchmark gaan vormen. In het Engels, uiteraard.
304
+
305
+ **Daarom is nu jouw hulp nodig**: als we samen alle 500 prompts vertalen kunnen we Nederlands toegevoegd krijgen aan het leaderboard.
306
+
307
+ Meedoen is simpel. Ga naar [Annotatie-Space](https://dibt-dutch-prompt-translation-for-dutch.hf.space/), log in of maak een Hugging Face account, en je kunt meteen aan de slag.
308
+
309
+ Alvast bedankt! Oh, je krijgt ook een steuntje in de rug: GPT4 heeft alvast een vertaalsuggestie voor je klaargezet.
310
  """
311
  )
312
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
313
  gr.Markdown(
314
  f"""
315
+ ## πŸš€ Voortgang
316
+ Dit is wat de community tot nu toe heeft bereikt!
317
  """
318
  )
319
  with gr.Row():
 
344
 
345
  gr.Markdown(
346
  """
347
+ ## πŸ‘Ύ Scoreboard
348
+ The totaal aantal vertalers en de vertalers met de meeste bijdragen:
349
  """
350
  )
351
 
 
357
  )
358
 
359
  top5_df_plot = gr.Dataframe(
360
+ headers=["Username", "Aantal vertalingen"],
361
  datatype=[
362
  "markdown",
363
  "number",