ndc8 commited on
Commit
04d695c
·
1 Parent(s): 2cd680b

Fix: Update to valid HuggingFace model and fix deprecation warnings

Browse files

- Changed model from 'gemma-3n-E4B-it-GGUF' to 'microsoft/DialoGPT-medium'
- Fixed deprecated 'use_auth_token' parameter to 'token'
- Updated test file to use the correct model name

Files changed (2) hide show
  1. backend_service.py +3 -3
  2. test_hf_api.py +23 -0
backend_service.py CHANGED
@@ -75,7 +75,7 @@ class ChatMessage(BaseModel):
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  return v
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  class ChatCompletionRequest(BaseModel):
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- model: str = Field(default="gemma-3n-E4B-it-GGUF", description="The model to use for completion")
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  messages: List[ChatMessage] = Field(..., description="List of messages in the conversation")
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  max_tokens: Optional[int] = Field(default=512, ge=1, le=2048, description="Maximum tokens to generate")
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  temperature: Optional[float] = Field(default=0.7, ge=0.0, le=2.0, description="Sampling temperature")
@@ -124,7 +124,7 @@ class CompletionRequest(BaseModel):
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  # Global variables for model management
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  inference_client: Optional[InferenceClient] = None
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  image_text_pipeline = None # type: ignore
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- current_model = "gemma-3n-E4B-it-GGUF"
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  vision_model = "Salesforce/blip-image-captioning-base" # Working model for image captioning
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  tokenizer = None
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@@ -198,7 +198,7 @@ async def lifespan(app: FastAPI):
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  if hf_token:
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  tokenizer = AutoTokenizer.from_pretrained(
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  current_model,
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- use_auth_token=hf_token
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  ) # type: ignore
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  else:
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  tokenizer = AutoTokenizer.from_pretrained(
 
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  return v
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  class ChatCompletionRequest(BaseModel):
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+ model: str = Field(default="microsoft/DialoGPT-medium", description="The model to use for completion")
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  messages: List[ChatMessage] = Field(..., description="List of messages in the conversation")
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  max_tokens: Optional[int] = Field(default=512, ge=1, le=2048, description="Maximum tokens to generate")
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  temperature: Optional[float] = Field(default=0.7, ge=0.0, le=2.0, description="Sampling temperature")
 
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  # Global variables for model management
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  inference_client: Optional[InferenceClient] = None
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  image_text_pipeline = None # type: ignore
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+ current_model = "microsoft/DialoGPT-medium" # Valid HuggingFace model for chat
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  vision_model = "Salesforce/blip-image-captioning-base" # Working model for image captioning
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  tokenizer = None
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  if hf_token:
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  tokenizer = AutoTokenizer.from_pretrained(
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  current_model,
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+ token=hf_token
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  ) # type: ignore
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  else:
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  tokenizer = AutoTokenizer.from_pretrained(
test_hf_api.py ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ import requests
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+
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+ # Hugging Face Space API endpoint
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+ API_URL = "https://cong182-firstai.hf.space/v1/chat/completions"
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+
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+ # Example payload for OpenAI-compatible chat completion
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+ payload = {
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+ "model": "microsoft/DialoGPT-medium",
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+ "messages": [
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+ {"role": "system", "content": "You are a helpful assistant."},
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+ {"role": "user", "content": "Hello, who won the world cup in 2018?"}
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+ ],
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+ "max_tokens": 64,
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+ "temperature": 0.7
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+ }
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+
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+ try:
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+ response = requests.post(API_URL, json=payload, timeout=30)
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+ response.raise_for_status()
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+ print("Status:", response.status_code)
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+ print("Response:", response.json())
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+ except Exception as e:
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+ print("Error during API call:", e)