Facelook commited on
Commit
b918222
·
1 Parent(s): 3273c0a

Trial and error.

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Files changed (1) hide show
  1. app.py +21 -9
app.py CHANGED
@@ -18,11 +18,24 @@ class BasicAgent:
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  print("BasicAgent initialized.")
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  print("Loading Qwen2.5-7B-Instruct model...")
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- self.model_name = "Qwen/Qwen2.5-7B-Instruct"
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- self.client = InferenceClient(model=self.model_name)
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- self.tokenizer = None
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- self.model = None
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-
 
 
 
 
 
 
 
 
 
 
 
 
 
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  def __call__(self, question: str) -> str:
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  print(f"Agent received question (first 50 chars): {question[:50]}...")
@@ -54,9 +67,8 @@ class BasicAgent:
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  answer = self.tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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  else:
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- # Fallback to Inference API - using the correct method call for chat completion
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- response = self.client.chat_completion(messages)
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- answer = response.choices[0].message.content
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  print(f"Agent generated response (first 50 chars): {answer[:50]}...")
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  return answer
@@ -192,7 +204,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
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  # --- Build Gradio Interface using Blocks ---
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  with gr.Blocks() as demo:
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- gr.Markdown("# Basic Agent Evaluation Runner (Attempt #1)")
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  gr.Markdown(
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  """
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  **Instructions:**
 
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  print("BasicAgent initialized.")
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  print("Loading Qwen2.5-7B-Instruct model...")
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+ self.model_name = "Qwen/Qwen2.5-1.5B-Instruct"
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+
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+ # Load model and tokenizer
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+ try:
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+ self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
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+ self.model = AutoModelForCausalLM.from_pretrained(
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+ self.model_name,
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+ torch_dtype="auto",
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+ device_map="auto"
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+ )
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+ print(f"Successfully loaded {self.model_name}")
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+ except Exception as e:
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+ print(f"Error loading model: {e}")
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+ # Fallback to HuggingFace Inference API if local loading fails
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+ print("Falling back to InferenceClient")
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+ self.client = InferenceClient(model=self.model_name)
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+ self.tokenizer = None
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+ self.model = None
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  def __call__(self, question: str) -> str:
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  print(f"Agent received question (first 50 chars): {question[:50]}...")
 
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  answer = self.tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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  else:
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+ # Fallback to Inference API
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+ answer = self.client.chat(messages=messages)
 
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  print(f"Agent generated response (first 50 chars): {answer[:50]}...")
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  return answer
 
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  # --- Build Gradio Interface using Blocks ---
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  with gr.Blocks() as demo:
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+ gr.Markdown("# Basic Agent Evaluation Runner")
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  gr.Markdown(
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  """
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  **Instructions:**