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import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
# Load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained("aaditya/Llama3-OpenBioLLM-8B")
model = AutoModelForCausalLM.from_pretrained(
"aaditya/Llama3-OpenBioLLM-8B",
torch_dtype=torch.bfloat16, # Use bfloat16 for better memory efficiency
device_map="auto" # Automatically handle device placement
)
# Define the system prompt
SYSTEM_PROMPT = """You are an advanced medical documentation assistant analyzing clinical documentation. For each case, provide:
Documentation Quality Score (1-10):
- Assess completeness, clarity, and adherence to clinical standards
Diagnostic Confidence (0-100%):
- Evaluate certainty of current diagnosis
- Consider supporting evidence
Key Findings:
- List significant clinical observations
- Note critical vital signs
- Highlight abnormal results
Missing Information:
- Identify crucial missing data
- Note incomplete documentation areas
Recommended Actions:
- Suggest immediate clinical steps
- Propose management changes
Additional Tests:
- Recommend relevant diagnostics
- Suggest appropriate imaging
- Propose lab work
Safety Concerns:
- Flag potential drug interactions
- Highlight clinical red flags
- Note urgent safety issues"""
def analyze_medical_doc(medical_doc):
# Prepare the prompt
prompt = f"{SYSTEM_PROMPT}\n\nPlease analyze this medical documentation:\n\n{medical_doc}\n\nAnalysis:"
# Tokenize input
inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=2048)
inputs = inputs.to(model.device) # Move to same device as model
# Generate response
outputs = model.generate(
**inputs,
max_new_tokens=512,
temperature=0.7,
top_p=0.9,
do_sample=True,
pad_token_id=tokenizer.eos_token_id
)
# Decode and clean up the response
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
# Extract only the generated part (remove the input prompt)
response = response[len(prompt):]
return response.strip()
# Example usage
sample_doc = """
Patient: 45-year-old male
Chief Complaint: Chest pain and shortness of breath
Vitals:
- BP: 145/90
- HR: 98
- RR: 20
- O2 Sat: 95% on RA
History:
- Onset: 2 hours ago
- Character: Sharp, radiating to left arm
- Previous MI: No
- HTN: Yes, on lisinopril
Current Medications:
- Lisinopril 10mg daily
"""
# Get the analysis
analysis = analyze_medical_doc(sample_doc)
print(analysis) |