Spaces:
Sleeping
Sleeping
fix space calls
Browse files
app.py
CHANGED
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@@ -272,13 +272,13 @@ class PicletGeneratorService:
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print(f"Generating caption for image...")
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result = client.predict(
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"/stream_chat",
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handle_file(image_path), # Wrap path so client uploads file
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"Descriptive", # caption_type
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"medium-length", # caption_length
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[], # extra_options
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"", # name_input
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"Describe this image in detail, identifying any recognizable objects, brands, logos, or specific models. Be specific about product names and types." # custom_prompt
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)
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# JoyCaption returns tuple: (prompt_used, caption_text) in .data
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@@ -303,11 +303,11 @@ class PicletGeneratorService:
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print(f"Generating text...")
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result = client.predict(
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"/chat",
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prompt, # message
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[], # history
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"You are a helpful assistant that creates Pokemon-style monster concepts based on real-world objects.", # system_prompt
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0.7 # temperature
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)
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# Extract response text (GPT-OSS formats with Analysis and Response)
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@@ -491,13 +491,13 @@ CRITICAL RULES:
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print(f"Generating image with prompt: {full_prompt[:100]}...")
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result = client.predict(
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"/infer",
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full_prompt, # prompt
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0, # seed
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True, # randomize_seed
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1024, # width
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1024, # height
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4 # num_inference_steps
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)
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# Extract image URL and seed
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print(f"Generating caption for image...")
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result = client.predict(
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handle_file(image_path), # Wrap path so client uploads file
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"Descriptive", # caption_type
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"medium-length", # caption_length
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[], # extra_options
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"", # name_input
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"Describe this image in detail, identifying any recognizable objects, brands, logos, or specific models. Be specific about product names and types.", # custom_prompt
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api_name="/stream_chat"
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)
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# JoyCaption returns tuple: (prompt_used, caption_text) in .data
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print(f"Generating text...")
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result = client.predict(
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prompt, # message
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[], # history
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"You are a helpful assistant that creates Pokemon-style monster concepts based on real-world objects.", # system_prompt
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0.7, # temperature
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api_name="/chat"
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)
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# Extract response text (GPT-OSS formats with Analysis and Response)
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print(f"Generating image with prompt: {full_prompt[:100]}...")
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result = client.predict(
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full_prompt, # prompt
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0, # seed
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True, # randomize_seed
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1024, # width
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1024, # height
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4, # num_inference_steps
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api_name="/infer"
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)
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# Extract image URL and seed
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