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Update hf_model.py
Browse files- hf_model.py +8 -8
hf_model.py
CHANGED
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@@ -2,7 +2,7 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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from datetime import datetime
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import os
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from
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class HFModel:
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def __init__(self, model_name):
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@@ -17,7 +17,7 @@ class HFModel:
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self.tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
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log_info(f"=== Model Loaded Successfully: {self.friendly_name} ===")
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except Exception as e:
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log_error(f"ERROR Loading Model: {e}")
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raise
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def generate_response(self, input_text, max_length=100, skip_special_tokens=True):
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@@ -28,7 +28,7 @@ class HFModel:
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log_info(f"Generated Response: {response}")
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return response
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except Exception as e:
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log_error(f"ERROR Generating Response: {e}")
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raise
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def stream_response(self, input_text, max_length=100, skip_special_tokens=True):
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@@ -38,7 +38,7 @@ class HFModel:
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response = self.tokenizer.decode(output, skip_special_tokens=skip_special_tokens).strip()
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yield response
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except Exception as e:
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log_error(f"ERROR Streaming Response: {e}")
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raise
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def chat(self, user_input, max_length=100, skip_special_tokens=True):
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@@ -59,7 +59,7 @@ class HFModel:
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return model_response
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except Exception as e:
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log_error(f"ERROR in Chat: {e}")
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raise
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def save_chat_log(self):
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@@ -71,7 +71,7 @@ class HFModel:
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f.write(f"**{role.capitalize()}:**\n\n{content}\n\n---\n\n")
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log_info(f"Chat log saved to {self.log_file}")
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except Exception as e:
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log_error(f"ERROR Saving Chat Log: {e}")
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raise
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def clear_chat_history(self):
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@@ -79,7 +79,7 @@ class HFModel:
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self.chat_history = []
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log_info("Chat history cleared.")
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except Exception as e:
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log_error(f"ERROR Clearing Chat History: {e}")
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raise
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def print_chat_history(self):
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@@ -90,5 +90,5 @@ class HFModel:
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print(f"{role.capitalize()}: {content}\n")
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log_info("Printed chat history to console.")
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except Exception as e:
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log_error(f"ERROR Printing Chat History: {e}")
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raise
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import torch
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from datetime import datetime
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import os
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from mew_log import log_info, log_error # Import your custom logging methods
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class HFModel:
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def __init__(self, model_name):
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self.tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
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log_info(f"=== Model Loaded Successfully: {self.friendly_name} ===")
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except Exception as e:
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log_error(f"ERROR Loading Model: {e}", e)
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raise
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def generate_response(self, input_text, max_length=100, skip_special_tokens=True):
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log_info(f"Generated Response: {response}")
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return response
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except Exception as e:
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log_error(f"ERROR Generating Response: {e}", e)
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raise
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def stream_response(self, input_text, max_length=100, skip_special_tokens=True):
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response = self.tokenizer.decode(output, skip_special_tokens=skip_special_tokens).strip()
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yield response
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except Exception as e:
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log_error(f"ERROR Streaming Response: {e}", e)
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raise
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def chat(self, user_input, max_length=100, skip_special_tokens=True):
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return model_response
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except Exception as e:
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log_error(f"ERROR in Chat: {e}", e)
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raise
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def save_chat_log(self):
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f.write(f"**{role.capitalize()}:**\n\n{content}\n\n---\n\n")
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log_info(f"Chat log saved to {self.log_file}")
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except Exception as e:
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log_error(f"ERROR Saving Chat Log: {e}", e)
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raise
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def clear_chat_history(self):
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self.chat_history = []
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log_info("Chat history cleared.")
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except Exception as e:
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log_error(f"ERROR Clearing Chat History: {e}", e)
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raise
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def print_chat_history(self):
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print(f"{role.capitalize()}: {content}\n")
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log_info("Printed chat history to console.")
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except Exception as e:
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log_error(f"ERROR Printing Chat History: {e}", e)
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raise
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