bioflow / scripts /bioflow_obm.py
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Phase 1: FastAPI integration with DeepPurpose DTI predictor
adecc9b
import os
import sys
import torch
import numpy as np
import logging
from typing import List, Union, Dict, Any, Optional
from tqdm import tqdm
# Add root to python path to allow imports from open_biomed
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
# Removed BioMedGPT references and added placeholders for open-source models
class BioFlowOBM:
def __init__(self, config_path: str = "configs/model/opensource_model.yaml"):
self.config_path = config_path
self.model = None # Placeholder for open-source model
def initialize(self):
# Placeholder for initializing open-source model
pass
def process_data(self, data):
# Placeholder for processing data using open-source model
pass
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# Example usage block
if __name__ == "__main__":
# Create valid dummy data/config for test if needed
print("This script is a library. Import OBM to use.")
print("Example:")
print("from scripts.bioflow_obm import OBM")
print("obm = OBM()")
print("vec = obm.encode_text('Biology is complex')")