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Update app.py
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app.py
CHANGED
@@ -74,7 +74,7 @@ from transformers import pipeline
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pipe = pipeline("text-generation", model="HuggingFaceH4/zephyr-7b-beta", torch_dtype=torch.bfloat16, device_map="auto")
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@spaces.GPU(enable_queue=True)
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def get_llm_idea(
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agent_maker_sys = f"""
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You are an AI whose job is to help users create their own chatbot whose personality will reflect the character or scene from an image described by users.
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In particular, you need to respond succintly in a friendly tone, write a system prompt for an LLM, a catchy title for the chatbot, and a very short example user input. Make sure each part is included.
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@@ -100,6 +100,8 @@ Example input: Can you suggest a good cigar brand for a man who enjoys smoking w
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<|user|>
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"""
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outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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return outputs
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@@ -108,11 +110,10 @@ def infer(image_in):
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gr.Info("Getting image description...")
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user_prompt = get_caption_from_MD(image_in)
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#print(f"PROMPT: {prompt}")
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gr.Info("Building a system according to the image caption ...")
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outputs = get_llm_idea(
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pattern = r'\<\|system\|\>(.*?)\<\|assistant\|\>'
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pipe = pipeline("text-generation", model="HuggingFaceH4/zephyr-7b-beta", torch_dtype=torch.bfloat16, device_map="auto")
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@spaces.GPU(enable_queue=True)
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def get_llm_idea(user_prompt):
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agent_maker_sys = f"""
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You are an AI whose job is to help users create their own chatbot whose personality will reflect the character or scene from an image described by users.
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In particular, you need to respond succintly in a friendly tone, write a system prompt for an LLM, a catchy title for the chatbot, and a very short example user input. Make sure each part is included.
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<|user|>
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"""
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prompt = f"{instruction.strip()}\n{user_prompt}</s>"
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#print(f"PROMPT: {prompt}")
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outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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return outputs
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gr.Info("Getting image description...")
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user_prompt = get_caption_from_MD(image_in)
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gr.Info("Building a system according to the image caption ...")
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outputs = get_llm_idea(user_prompt)
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pattern = r'\<\|system\|\>(.*?)\<\|assistant\|\>'
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