| """CPU Space adapter for the existing classroom app and saved research outputs.""" |
| import json |
| import os |
| from pathlib import Path |
| import shutil |
| import sys |
| import time |
| from shared_usage import SharedUsage,SharedLimit |
|
|
| ROOT=Path(__file__).resolve().parent/'brain_lab' |
| sys.path.insert(0,str(ROOT)) |
| import server as lab |
| from fastapi import Request,HTTPException |
| from fastapi.responses import FileResponse,JSONResponse |
| from backend import credentials,mario,ml,mindeye_live |
|
|
| app=lab.app |
| ml.torch.set_num_threads(int(os.environ.get('BRAIN_LAB_THREADS','2'))) |
| ml.DEVICE='cpu' |
| if sys.platform!='darwin' or not mario.JAVA.is_file(): |
| mario.JAVA=Path(shutil.which('java') or '/unavailable-java') |
| mario.JAVAC=Path(shutil.which('javac') or '/unavailable-javac') |
| |
| |
| def space_key(provider): |
| name={'openrouter':'BRAIN_LAB_OPENROUTER_API_KEY','perplexity':'BRAIN_LAB_PERPLEXITY_API_KEY'}.get(provider) |
| return os.environ.get(name,'').strip() if name else '' |
| credentials.get_key=space_key |
| lab.sketch_provider.get_key=credentials.get_key |
| shared_usage=SharedUsage(ROOT/'data/shared_recognition_usage.sqlite3', |
| daily=max(1,min(2000,int(os.environ.get('BRAIN_LAB_SHARED_DAILY','200')))), |
| per_minute=max(1,min(60,int(os.environ.get('BRAIN_LAB_SHARED_PER_MINUTE','20'))))) |
| _seen={} |
|
|
|
|
| def owner_key_needed(config): |
| keys=config.get('api_keys',{});provider=config.get('provider','openrouter') |
| return bool((not keys.get(provider) and space_key(provider)) or |
| (not keys.get('openrouter') and space_key('openrouter'))) |
|
|
|
|
| @app.middleware('http') |
| async def cpu_space_policy(request,call_next): |
| path=request.url.path |
| if request.method=='POST' and (path=='/api/tribe/jobs' or path=='/api/tribe/demo' or |
| path.startswith('/api/mindeye/live/') or path=='/api/cinema'): |
| return JSONResponse({'detail':'New large-model predictions are not enabled on this CPU Space. The saved Cinema clips and published MindEye2 replay are ready to use.'},status_code=503) |
| |
| |
| if path.startswith('/api/'): |
| sid=request.headers.get('X-Lab-Session','classroom');now=time.monotonic() |
| with lab.STATE_LOCK: |
| for old,stamp in list(_seen.items()): |
| if old!=sid and now-stamp>1800: |
| state=lab.STATES.pop(old,None);_seen.pop(old,None) |
| if state and state.get('mario'): |
| try:state['mario'].close() |
| except OSError:pass |
| _seen[sid]=now |
| response=await call_next(request) |
| response.headers['X-Brain-Lab-Edition']='spaces-cpu' |
| return response |
|
|
|
|
| @app.get('/healthz') |
| def health(): |
| return {'app':'Brain Lab','edition':'spaces-cpu','saved_clips':len(lab.clip_library._clips()), |
| 'large_model_jobs_enabled':False, |
| 'api_keys':'owner-space-secrets' if space_key('openrouter') else 'visitor-session-only'} |
|
|
|
|
| |
| |
| app.router.routes=[r for r in app.router.routes if getattr(r,'path','') not in |
| ['/api/tribe/results/{ident}','/api/mindeye/live/status','/api/sketch/config','/api/sketch']] |
|
|
|
|
| @app.get('/api/tribe/results/{ident}') |
| def cached_response(ident:str): |
| if not ident.isalnum() or len(ident)!=32: |
| return JSONResponse({'detail':'Saved prediction not found.'},status_code=404) |
| path=ROOT/'data/space_results'/(ident+'.json.gz') |
| if not path.is_file():return JSONResponse({'detail':'Saved prediction not found.'},status_code=404) |
| return FileResponse(path,media_type='application/json',headers={'Content-Encoding':'gzip'}) |
|
|
|
|
| @app.get('/api/mindeye/live/status') |
| def live_status(): |
| result=mindeye_live.status() |
| result.update(hosted_cpu=True,installed=False,recorded_scan_tested=False,recorded_examples=[], |
| note='Fresh fMRI decoding is not configured on this CPU Space. Published research comparisons remain available.') |
| return result |
|
|
|
|
| @app.get('/api/sketch/config') |
| def sketch_config(request:Request): |
| config=lab.session(request)[1]['sketch_config'] |
| result=lab.sketch_provider.config_status(config) |
| shared=bool(result['key_configured'] and owner_key_needed(config)) |
| result.update(hosted=True,global_storage_available=False,shared_key_enabled=shared, |
| key_source='classroom' if shared else 'visitor' if result['key_configured'] else 'missing', |
| shared_allowance=shared_usage.summary() if shared else None) |
| return result |
|
|
|
|
| @app.post('/api/sketch/config') |
| def set_sketch_config(body:lab.SketchConfig,request:Request): |
| if body.save_globally: |
| return JSONResponse({'detail':'Keys can be used only for this visitor session; global key storage is disabled on the public site.'},status_code=400) |
| _,state=lab.session(request);state['sketch_config']['provider']=body.provider |
| if body.api_key:state['sketch_config'].setdefault('api_keys',{})[body.provider]=body.api_key |
| return sketch_config(request) |
|
|
|
|
| @app.post('/api/sketch') |
| def recognize(body:lab.SketchRequest,request:Request): |
| _,state=lab.session(request);lab.require(state,'occipital','thalamus') |
| if body.hint:lab.require(state,'wernicke','association','frontal') |
| image=ml.decode_image(body.image);config=state['sketch_config'] |
| |
| blank=lab.np.count_nonzero(lab.np.asarray(image.convert('L'))<220)<8 |
| if owner_key_needed(config) and not blank: |
| try: |
| with shared_usage.lease():return lab.sketch_provider.recognize(image,config,body.hint) |
| except SharedLimit as error:raise HTTPException(429,str(error)) from None |
| return lab.sketch_provider.recognize(image,config,body.hint) |
|
|
