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Update app.py
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app.py
CHANGED
@@ -5,6 +5,7 @@ from huggingface_hub import InferenceClient
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import gradio as gr
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from pydantic import BaseModel, Field
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from typing import Optional, Literal
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class PromptInput(BaseModel):
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text: str = Field(..., description="The initial prompt text")
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@@ -19,7 +20,7 @@ class RefinementOutput(BaseModel):
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class PromptRefiner:
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def __init__(self, api_token: str):
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self.client = InferenceClient(token=api_token)
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def refine_prompt(self, prompt_input: PromptInput) -> RefinementOutput:
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if prompt_input.meta_prompt_choice == "morphosis":
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@@ -55,12 +56,18 @@ class PromptRefiner:
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response_content = response.choices[0].message.content.strip()
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except HfHubHTTPError as e:
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return (
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"Error: Model timeout. Please
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"",
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"The selected model is currently experiencing high traffic.",
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{}
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)
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-
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try:
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json_match = re.search(r'<json>\s*(.*?)\s*</json>', response_content, re.DOTALL)
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if json_match:
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import gradio as gr
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from pydantic import BaseModel, Field
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from typing import Optional, Literal
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from huggingface_hub.utils._errors import HfHubHTTPError
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class PromptInput(BaseModel):
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text: str = Field(..., description="The initial prompt text")
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class PromptRefiner:
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def __init__(self, api_token: str):
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self.client = InferenceClient(token=api_token,timeout=300)
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def refine_prompt(self, prompt_input: PromptInput) -> RefinementOutput:
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if prompt_input.meta_prompt_choice == "morphosis":
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response_content = response.choices[0].message.content.strip()
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except HfHubHTTPError as e:
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return (
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"Error: Model timeout. Please again later.",
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"",
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"The selected model is currently experiencing high traffic.",
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{}
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)
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except Exception as e:
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return (
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f"Error: {str(e)}",
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"",
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"An unexpected error occurred.",
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{}
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)
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try:
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json_match = re.search(r'<json>\s*(.*?)\s*</json>', response_content, re.DOTALL)
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if json_match:
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