CodCodingCode commited on
Commit
d1e0ac0
·
1 Parent(s): 01e6a62

fixed local running bug

Browse files
Files changed (1) hide show
  1. app.py +19 -15
app.py CHANGED
@@ -42,7 +42,7 @@ model.eval()
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  # === Role Agent with instruction/input/output format ===
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  class RoleAgent:
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- def __init__(self, role_instruction, tokenizer, model):
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  self.tokenizer = tokenizer
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  self.model = model
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  self.role_instruction = role_instruction
@@ -53,18 +53,18 @@ class RoleAgent:
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  f"Input: {input_text}\n"
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  f"Output:"
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  )
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- print("tokenizer is:", tokenizer, "— type:", type(tokenizer))
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- encoding = tokenizer(prompt, return_tensors="pt")
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- inputs = {k: v.to(model.device) for k, v in encoding.items()}
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- outputs = model.generate(
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  **inputs,
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  max_new_tokens=256,
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  do_sample=True,
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  temperature=0.7,
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- pad_token_id=tokenizer.eos_token_id,
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  )
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- response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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  thinking = ""
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  answer = response
@@ -78,20 +78,24 @@ class RoleAgent:
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  # === Agents ===
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  summarizer = RoleAgent(
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- "You are a clinical summarizer trained to extract structured vignettes from doctor–patient dialogues.",
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- tokenizer,
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- model,
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  )
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  diagnoser = RoleAgent(
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- "You are a board-certified diagnostician that diagnoses patients.", tokenizer, model
 
 
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  )
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  questioner = RoleAgent(
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- "You are a physician asking questions to diagnose a patient.", tokenizer, model
 
 
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  )
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  treatment_agent = RoleAgent(
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- "You are a board-certified clinician. Based on the diagnosis and patient vignette provided below, suggest a concise treatment plan that could realistically be initiated by a primary care physician or psychiatrist.",
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- tokenizer,
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- model,
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  )
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  # === Role Agent with instruction/input/output format ===
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  class RoleAgent:
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+ def __init__(self, role_instruction, tokenizer=tokenizer, model=model):
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  self.tokenizer = tokenizer
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  self.model = model
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  self.role_instruction = role_instruction
 
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  f"Input: {input_text}\n"
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  f"Output:"
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  )
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+ print("tokenizer is:", self.tokenizer, "— type:", type(self.tokenizer))
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+ encoding = self.tokenizer(prompt, return_tensors="pt")
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+ inputs = {k: v.to(self.model.device) for k, v in encoding.items()}
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+ outputs = self.model.generate(
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  **inputs,
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  max_new_tokens=256,
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  do_sample=True,
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  temperature=0.7,
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+ pad_token_id=self.tokenizer.eos_token_id,
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  )
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+ response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
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  thinking = ""
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  answer = response
 
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  # === Agents ===
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  summarizer = RoleAgent(
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+ role_instruction="You are a clinical summarizer trained to extract structured vignettes from doctor–patient dialogues.",
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+ tokenizer=tokenizer,
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+ model=model,
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  )
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  diagnoser = RoleAgent(
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+ role_instruction="You are a board-certified diagnostician that diagnoses patients.",
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+ tokenizer=tokenizer,
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+ model=model,
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  )
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  questioner = RoleAgent(
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+ role_instruction="You are a physician asking questions to diagnose a patient.",
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+ tokenizer=tokenizer,
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+ model=model,
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  )
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  treatment_agent = RoleAgent(
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+ role_instruction="You are a board-certified clinician. Based on the diagnosis and patient vignette provided below, suggest a concise treatment plan that could realistically be initiated by a primary care physician or psychiatrist.",
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+ tokenizer=tokenizer,
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+ model=model,
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  )
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