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Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
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@@ -13,39 +13,57 @@ from datetime import datetime
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import sqlite3
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from datetime import datetime
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# Initialize the database
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def init_db(file='logs.db'):
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conn = sqlite3.connect(file)
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c = conn.cursor()
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c.execute('''CREATE TABLE IF NOT EXISTS logs
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conn.commit()
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conn.close()
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# Log a request
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def log_request(prompt, is_negative, steps, cfg_scale, sampler, seed, strength, use_dev,
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log_message += f"enhance_prompt_style='{enhance_prompt_style}', enhance_prompt_option={enhance_prompt_option}, "
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log_message += f"nemo_enhance_prompt_style='{nemo_enhance_prompt_style}', use_mistral_nemo={use_mistral_nemo}"
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if huggingface_api_key:
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log_message += f"huggingface_api_key='{huggingface_api_key}'"
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conn = sqlite3.connect('acces_log.log')
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c = conn.cursor()
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c.execute(
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conn.commit()
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conn.close()
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# os.makedirs('assets', exist_ok=True)
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if not os.path.exists('icon.png'):
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os.system("wget -O icon.png https://huggingface.co/spaces/K00B404/FLUX.1-Dev-Serverless-darn-enhanced-prompt/resolve/main/edge.png")
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API_URL_DEV = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
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API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
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timeout = 100
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# Set up logging
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logging.basicConfig(filename='access.log', level=logging.INFO,
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@@ -53,15 +71,6 @@ logging.basicConfig(filename='access.log', level=logging.INFO,
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def log_requestold(prompt, is_negative, steps, cfg_scale, sampler, seed, strength, use_dev, enhance_prompt_style, enhance_prompt_option, nemo_enhance_prompt_style, use_mistral_nemo, huggingface_api_key):
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log_message = f"Request: prompt='{prompt}', is_negative={is_negative}, steps={steps}, cfg_scale={cfg_scale}, "
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log_message += f"sampler='{sampler}', seed={seed}, strength={strength}, use_dev={use_dev}, "
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log_message += f"enhance_prompt_style='{enhance_prompt_style}', enhance_prompt_option={enhance_prompt_option}, "
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log_message += f"nemo_enhance_prompt_style='{nemo_enhance_prompt_style}', use_mistral_nemo={use_mistral_nemo}"
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if huggingface_api_key:
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log_message += f"huggingface_api_key='{huggingface_api_key}'"
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logging.info(log_message)
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def check_ubuse(prompt,word_list=["little girl"]):
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for word in word_list:
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if word in prompt:
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@@ -141,33 +150,36 @@ def mistral_nemo_call(prompt, API_TOKEN, model="mistralai/Mistral-Nemo-Instruct-
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):
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response += message.choices[0].delta.content
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return response
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api_url = API_URL_DEV if use_dev else API_URL
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#
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is_api_call = huggingface_api_key is not None
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if is_api_call:
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# Use
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API_TOKEN = os.getenv("HF_READ_TOKEN")
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else:
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# Validate the API key if it's an API call
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if huggingface_api_key == "":
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raise gr.Error("API key is required for API calls.")
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API_TOKEN = huggingface_api_key
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headers = {"Authorization": f"Bearer {API_TOKEN}"}
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if
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return None, None, None
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key = random.randint(0, 999)
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prompt = check_ubuse(prompt)
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#prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
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print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
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original_prompt = prompt
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@@ -181,7 +193,7 @@ def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Ka
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final_prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
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print(f'\033[1mGeneration {key}:\033[0m {final_prompt}')
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#
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if seed == -1:
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seed = random.randint(1, 1000000000)
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@@ -207,7 +219,7 @@ def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Ka
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image = Image.open(io.BytesIO(image_bytes))
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print(f'\033[1mGeneration {key} completed!\033[0m ({final_prompt})')
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# Save the image
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output_path = f"./output_{key}.png"
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image.save(output_path)
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except Exception as e:
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print(f"Error when trying to open the image: {e}")
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return None, None, None
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title_html="""
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<center>
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@@ -431,7 +441,9 @@ with gr.Blocks( css=css) as app:
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seed_output = gr.Textbox(label="Seed Used", elem_id="seed-output")
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final_prompt_output = gr.Textbox(label="Final Prompt", elem_id="final-prompt-output")
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# Adjust the click function to include the API key, use_dev, and enhance_prompt_option as inputs
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text_button.click(query, inputs=
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app.launch(show_api=True, share=False)
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import sqlite3
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from datetime import datetime
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import sqlite3
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from datetime import datetime
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# Initialize the database
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def init_db(file='logs.db'):
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conn = sqlite3.connect(file)
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c = conn.cursor()
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c.execute('''CREATE TABLE IF NOT EXISTS logs (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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timestamp TEXT,
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prompt TEXT,
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is_negative INTEGER,
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steps INTEGER,
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cfg_scale REAL,
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sampler TEXT,
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seed INTEGER,
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strength REAL,
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use_dev INTEGER,
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enhance_prompt_style TEXT,
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enhance_prompt_option INTEGER,
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nemo_enhance_prompt_style TEXT,
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use_mistral_nemo INTEGER
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)''')
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conn.commit()
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conn.close()
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# Log a request
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def log_request(prompt, is_negative, steps, cfg_scale, sampler, seed, strength, use_dev,
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enhance_prompt_style, enhance_prompt_option, nemo_enhance_prompt_style, use_mistral_nemo):
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conn = sqlite3.connect('logs.db')
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c = conn.cursor()
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c.execute('''INSERT INTO logs (timestamp, prompt, is_negative, steps, cfg_scale, sampler, seed, strength, use_dev,
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enhance_prompt_style, enhance_prompt_option, nemo_enhance_prompt_style, use_mistral_nemo)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
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(datetime.now().isoformat(), prompt, is_negative, steps, cfg_scale, sampler, seed, strength,
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use_dev, enhance_prompt_style, enhance_prompt_option, nemo_enhance_prompt_style, use_mistral_nemo))
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conn.commit()
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conn.close()
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# os.makedirs('assets', exist_ok=True)
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if not os.path.exists('icon.png'):
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os.system("wget -O icon.png https://huggingface.co/spaces/K00B404/FLUX.1-Dev-Serverless-darn-enhanced-prompt/resolve/main/edge.png")
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API_URL_DEV = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
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API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
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timeout = 100
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init_db()
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# Set up logging
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logging.basicConfig(filename='access.log', level=logging.INFO,
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def check_ubuse(prompt,word_list=["little girl"]):
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for word in word_list:
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if word in prompt:
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):
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response += message.choices[0].delta.content
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return response
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def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1,
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strength=0.7, huggingface_api_key=None, use_dev=False,
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enhance_prompt_style="generic", enhance_prompt_option=False,
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nemo_enhance_prompt_style="generic", use_mistral_nemo=False):
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# Log the request (WITHOUT storing API keys)
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log_request(prompt, is_negative, steps, cfg_scale, sampler, seed, strength, use_dev,
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enhance_prompt_style, enhance_prompt_option, nemo_enhance_prompt_style, use_mistral_nemo)
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# Determine API URL
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api_url = API_URL_DEV if use_dev else API_URL
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# API key handling
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is_api_call = huggingface_api_key is not None
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if is_api_call:
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API_TOKEN = os.getenv("HF_READ_TOKEN") # Use env var in GUI mode
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else:
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if huggingface_api_key == "":
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raise gr.Error("API key is required for API calls.")
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API_TOKEN = huggingface_api_key
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headers = {"Authorization": f"Bearer {API_TOKEN}"}
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if not prompt: # Simplified check
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return None, None, None
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key = random.randint(0, 999)
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prompt = check_ubuse(prompt)
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print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
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original_prompt = prompt
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final_prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
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print(f'\033[1mGeneration {key}:\033[0m {final_prompt}')
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# Ensure seed is always positive
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if seed == -1:
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seed = random.randint(1, 1000000000)
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image = Image.open(io.BytesIO(image_bytes))
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print(f'\033[1mGeneration {key} completed!\033[0m ({final_prompt})')
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# Save the image and return path
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output_path = f"./output_{key}.png"
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image.save(output_path)
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except Exception as e:
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print(f"Error when trying to open the image: {e}")
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return None, None, None
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title_html="""
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<center>
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seed_output = gr.Textbox(label="Seed Used", elem_id="seed-output")
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final_prompt_output = gr.Textbox(label="Final Prompt", elem_id="final-prompt-output")
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inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, huggingface_api_key, use_dev, enhance_prompt_style,enhance_prompt_option, enhance_prompt_style, use_mistral_nemo]
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# Adjust the click function to include the API key, use_dev, and enhance_prompt_option as inputs
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text_button.click(query, inputs=inputs, outputs=[image_output, seed_output, final_prompt_output])
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app.launch(show_api=True, share=False)
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