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Update app.py
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app.py
CHANGED
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@@ -22,7 +22,7 @@ _image_caption_pipeline = pipeline(
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# Global model configuration constants
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_text_generation_pipeline = pipeline("text-generation", model="Qwen/
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# Initialize TTS components once to avoid reloading
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_SPEECH_PIPELINE = pipeline("text-to-speech", model="microsoft/speecht5_tts")
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@@ -82,15 +82,14 @@ def generate_story_content(system_prompt: str, user_prompt: str) -> str:
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try:
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# Prepare chat message structure
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conversation_history = [
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{"role": "
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{"role": "user", "content": user_prompt},
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]
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# Generate the story
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story=_text_generation_pipeline(conversation_history)
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# Extract the stroy result
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stroy_result=story[0]["generated_text"][
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# Process and clean output
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return stroy_result
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@@ -259,15 +258,15 @@ if uploaded_image is not None:
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# Define prompt templates
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PROMPT_TEMPLATES = {
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"educational": {
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"system": "You are a children's educator. Create
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"icon": "π"
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},
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"adventure": {
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"system": "You are a fantasy writer. Create a
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"icon": "π "
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},
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"animal": {
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"system": "You are an animal
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"icon": "π»"
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}
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}
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)
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# Global model configuration constants
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_text_generation_pipeline = pipeline("text-generation", model="Qwen/Qwen3-1.7B")
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# Initialize TTS components once to avoid reloading
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_SPEECH_PIPELINE = pipeline("text-to-speech", model="microsoft/speecht5_tts")
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try:
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# Prepare chat message structure
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conversation_history = [
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{"role": "user", "content": system_prompt+user_prompt+"/no_think"},
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]
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# Generate the story
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story=_text_generation_pipeline(conversation_history)
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# Extract the stroy result
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stroy_result=story[0]["generated_text"][1]["content"][19:]
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# Process and clean output
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return stroy_result
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# Define prompt templates
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PROMPT_TEMPLATES = {
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"educational": {
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"system": "You are a children's educator writer. Create an educational story about ",
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"icon": "π"
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},
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"adventure": {
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"system": "You are a fantasy writer. Create a adventure story about ",
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"icon": "π "
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},
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"animal": {
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"system": "You are an animal themes writer. Create a animal fairy tales about ",
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"icon": "π»"
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}
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}
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