artificialguybr multimodalart HF staff commited on
Commit
7ce51a2
1 Parent(s): 322db57

Fix some issues (#1)

Browse files

- Fix some issues (4ef6d61e1037e33d2d04cb68ea77232b8dc35624)


Co-authored-by: Apolinário from multimodal AI art <multimodalart@users.noreply.huggingface.co>

Files changed (1) hide show
  1. app.py +33 -13
app.py CHANGED
@@ -5,6 +5,9 @@ from PIL import Image
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  import json
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  import os
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  import logging
 
 
 
8
 
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  logging.basicConfig(level=logging.DEBUG)
10
 
@@ -31,27 +34,39 @@ def run_lora(prompt, selected_state, progress=gr.Progress(track_tqdm=True)):
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  selected_lora = loras[selected_lora_index]
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  api_url = f"https://api-inference.huggingface.co/models/{selected_lora['repo']}"
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  trigger_word = selected_lora["trigger_word"]
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- token = os.getenv("API_TOKEN")
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  payload = {"inputs": f"{prompt} {trigger_word}"}
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- headers = {"Authorization": f"Bearer {token}"}
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  # Add a print statement to display the API request
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  print(f"API Request: {api_url}")
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- print(f"API Headers: {headers}")
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  print(f"API Payload: {payload}")
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-
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- response = requests.post(api_url, headers=headers, json=payload)
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- if response.status_code == 200:
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- return Image.open(io.BytesIO(response.content))
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- else:
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- logging.error(f"API Error: {response.status_code}")
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- raise gr.Error("API Error: Unable to fetch the image.") # Raise a Gradio error here
 
 
 
 
 
 
 
 
 
 
 
 
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51
 
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  with gr.Blocks(css="custom.css") as app:
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- title = gr.HTML("<h1>LoRA the Explorer</h1>")
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  selected_state = gr.State()
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  with gr.Row():
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  gallery = gr.Gallery(
@@ -71,11 +86,16 @@ with gr.Blocks(css="custom.css") as app:
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  update_selection,
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  outputs=[prompt, selected_state]
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  )
 
 
 
 
 
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  button.click(
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  fn=run_lora,
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  inputs=[prompt, selected_state],
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  outputs=[result]
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  )
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- app.queue(max_size=20)
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- app.launch()
 
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  import json
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  import os
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  import logging
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+ import math
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+ from tqdm import tqdm
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+ import time
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12
  logging.basicConfig(level=logging.DEBUG)
13
 
 
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  selected_lora = loras[selected_lora_index]
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  api_url = f"https://api-inference.huggingface.co/models/{selected_lora['repo']}"
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  trigger_word = selected_lora["trigger_word"]
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+ #token = os.getenv("API_TOKEN")
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  payload = {"inputs": f"{prompt} {trigger_word}"}
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+ #headers = {"Authorization": f"Bearer {token}"}
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  # Add a print statement to display the API request
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  print(f"API Request: {api_url}")
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+ #print(f"API Headers: {headers}")
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  print(f"API Payload: {payload}")
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+
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+ error_count = 0
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+ pbar = tqdm(total=None, desc="Loading model")
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+ while(True):
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+ response = requests.post(api_url, json=payload)
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+ if response.status_code == 200:
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+ return Image.open(io.BytesIO(response.content))
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+ elif response.status_code == 503:
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+ #503 is triggered when the model is doing cold boot. It also gives you a time estimate from when the model is loaded but it is not super precise
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+ time.sleep(1)
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+ pbar.update(1)
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+ elif response.status_code == 500 and error_count < 5:
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+ print(response.content)
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+ time.sleep(1)
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+ error_count += 1
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+ continue
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+ else:
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+ logging.error(f"API Error: {response.status_code}")
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+ raise gr.Error("API Error: Unable to fetch the image.") # Raise a Gradio error here
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66
 
67
 
68
  with gr.Blocks(css="custom.css") as app:
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+ title = gr.Markdown("# artificialguybr LoRA portfolio")
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  selected_state = gr.State()
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  with gr.Row():
72
  gallery = gr.Gallery(
 
86
  update_selection,
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  outputs=[prompt, selected_state]
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  )
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+ prompt.submit(
90
+ fn=run_lora,
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+ inputs=[prompt, selected_state],
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+ outputs=[result]
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+ )
94
  button.click(
95
  fn=run_lora,
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  inputs=[prompt, selected_state],
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  outputs=[result]
98
  )
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100
+ app.queue(max_size=20, concurrency_count=5)
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+ app.launch()