|
from fastapi.middleware.cors import CORSMiddleware |
|
from fastapi import FastAPI, HTTPException, File, UploadFile, Form |
|
from fastapi.responses import JSONResponse, FileResponse |
|
from pydantic import BaseModel |
|
from typing import Optional |
|
import subprocess |
|
import os |
|
import logging |
|
from inference_transform import process_smiles, process_pdb, process_sdf, extract_and_convert_to_sdf, is_valid_smiles |
|
|
|
|
|
logging.basicConfig(level=logging.INFO) |
|
logger = logging.getLogger(__name__) |
|
|
|
app = FastAPI() |
|
app.add_middleware( |
|
CORSMiddleware, |
|
allow_origins=['*'], |
|
allow_credentials=True, |
|
allow_methods=['*'], |
|
allow_headers=['*'] |
|
) |
|
|
|
sdf_file_path = "/root/CHEMISTral7Bv0.3/example/Conformer3D_COMPOUND_CID_240.sdf" |
|
|
|
class InferenceRequest(BaseModel): |
|
prompt: str |
|
max_tokens: int = 256 |
|
temperature: float = 1.0 |
|
|
|
@app.post("/predict_base") |
|
async def predict_base( |
|
prompt: str = Form(...), |
|
max_tokens: int = Form(256), |
|
temperature: float = Form(1.0), |
|
file: Optional[UploadFile] = File(None) |
|
): |
|
try: |
|
if file: |
|
file_path = f"/tmp/{file.filename}" |
|
with open(file_path, "wb") as f: |
|
f.write(file.file.read()) |
|
if file.filename.endswith(".pdb"): |
|
prompt += f" {process_pdb(file_path)}" |
|
elif file.filename.endswith(".sdf"): |
|
prompt += f" {process_sdf(file_path)}" |
|
else: |
|
try: |
|
sdf_file = extract_and_convert_to_sdf(prompt) |
|
if sdf_file: |
|
prompt += f" {sdf_file}" |
|
except ValueError as e: |
|
logger.info(str(e)) |
|
|
|
command = [ |
|
"python", |
|
"/root/CHEMISTral7Bv0.3/mistral_chat_script.py", |
|
"/root/mistral_models/7B-v0.3/", |
|
prompt, |
|
f"--max_tokens={max_tokens}", |
|
f"--temperature={temperature}", |
|
"--instruct" |
|
] |
|
|
|
logger.info(f"Running command: {' '.join(command)}") |
|
result = subprocess.run(command, capture_output=True, text=True) |
|
|
|
if result.returncode != 0: |
|
logger.error(f"Command failed with return code {result.returncode}") |
|
logger.error(f"stderr: {result.stderr}") |
|
raise HTTPException(status_code=500, detail=result.stderr) |
|
|
|
response = result.stdout.strip() |
|
sdf_file_path = "/root/CHEMISTral7Bv0.3/example/Conformer3D_COMPOUND_CID_240.sdf" |
|
|
|
return { |
|
"response": response, |
|
"sdf_file_path": sdf_file_path |
|
} |
|
except Exception as e: |
|
logger.exception("Exception occurred during inference.") |
|
raise HTTPException(status_code=500, detail=str(e)) |
|
|
|
@app.post("/predict") |
|
async def predict_alternative( |
|
prompt: str = Form(...), |
|
max_tokens: int = Form(256), |
|
temperature: float = Form(1.0), |
|
file: Optional[UploadFile] = File(None) |
|
): |
|
try: |
|
if file: |
|
file_path = f"/tmp/{file.filename}" |
|
with open(file_path, "wb") as f: |
|
f.write(await file.read()) |
|
if file.filename.endswith(".pdb"): |
|
prompt += f" {process_pdb(file_path)}" |
|
elif file.filename.endswith(".sdf"): |
|
prompt += f" {process_sdf(file_path)}" |
|
else: |
|
try: |
|
sdf_file = extract_and_convert_to_sdf(prompt) |
|
if sdf_file: |
|
prompt += f" {sdf_file}" |
|
except ValueError as e: |
|
logger.info(str(e)) |
|
|
|
command = [ |
|
"python", |
|
"/root/CHEMISTral7Bv0.3/mistral_chat_script.py", |
|
"/root/mistral_models/7B-v0.3/", |
|
prompt, |
|
f"--max_tokens={max_tokens}", |
|
f"--temperature={temperature}", |
|
"--instruct", |
|
"--lora_path=/root/CHEMISTral7Bv0.3/runs/checkpoints/checkpoint_000300/consolidated/lora.safetensors" |
|
] |
|
logger.info(f"Running command: {' '.join(command)}") |
|
result = subprocess.run(command, capture_output=True, text=True) |
|
if result.returncode != 0: |
|
logger.error(f"Command failed with return code {result.returncode}") |
|
logger.error(f"stderr: {result.stderr}") |
|
raise HTTPException(status_code=500, detail=result.stderr) |
|
|
|
response = result.stdout.strip() |
|
sdf_file_path = "/root/CHEMISTral7Bv0.3/example/Conformer3D_COMPOUND_CID_240.sdf" |
|
|
|
|
|
return FileResponse(sdf_file_path, media_type='chemical/x-mdl-sdfile', filename="Conformer3D_COMPOUND_CID_240.sdf") |
|
|
|
except Exception as e: |
|
logger.exception("Exception occurred during inference.") |
|
raise HTTPException(status_code=500, detail=str(e)) |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
@app.get("/download_sdf") |
|
async def download_sdf(): |
|
try: |
|
return FileResponse(path=sdf_file_path, filename="Conformer3D_COMPOUND_CID_240.sdf") |
|
except Exception as e: |
|
logger.exception("Exception occurred while sending SDF file.") |
|
raise HTTPException(status_code=500, detail=str(e)) |
|
|
|
if __name__ == "__main__": |
|
import uvicorn |
|
uvicorn.run(app, host="0.0.0.0", port=8000) |
|
|
