Text Classification
PEFT
lora
document-question-answering
structured-decisions
calibration
synthetic-evaluation
Instructions to use botp/Solomon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use botp/Solomon with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download src/solomon/routing.py from botp/Solomon: direct link, hf CLI and curl.
- Browser
- Download file 3.04 kB
-
https://huggingface.co/botp/Solomon/resolve/main/src/solomon/routing.py
- Command line
-
hf download hf://botp/Solomon/src/solomon/routing.py
-
curl -L -o routing.py https://huggingface.co/botp/Solomon/resolve/main/src/solomon/routing.py
3.04 kB
| """Real callback-driven escalation. Internal budget/escalation layer: the answer | |
| contract above it always answers and refuses to emit any deferral field.""" | |
| from dataclasses import dataclass | |
| import math | |
| from numbers import Integral, Real | |
| class Budget: | |
| branches: int = 8 | |
| input_tokens: int = 8192 | |
| generated_tokens: int = 3072 | |
| def route(stages, budget=Budget()): | |
| """stages are (name, reserved_cost, callback). Callback returns answer/confidence/cost. | |
| Reservations are hard maxima enforced by the backend, not optimistic estimates. | |
| Callbacks must honor the reservation passed to them. Overspending fails closed. | |
| """ | |
| used = {'branches':0,'input_tokens':0,'generated_tokens':0} | |
| valid_cost=lambda value:isinstance(value,Integral) and not isinstance(value,bool) and value>=0 | |
| valid_probability=lambda value:isinstance(value,Real) and not isinstance(value,bool) and math.isfinite(value) and 0<=value<=1 | |
| if any(not valid_cost(getattr(budget,k)) for k in used): | |
| raise ValueError('invalid compute budget') | |
| traces, last = [], None | |
| reasons = {'fast':'full_depth','views':'escalated_views','reasoning':'escalated_reasoning','exit':'early_exit'} | |
| for name,reserve,call in stages: | |
| if name not in reasons or set(reserve)!=set(used) or any(not valid_cost(v) for v in reserve.values()): | |
| raise ValueError('invalid stage reservation') | |
| if any(used[k]+reserve.get(k,0) > getattr(budget,k) for k in used): | |
| return {'answer':None,'candidate':last,'abstained':True,'compute':{'stop_reason':'budget_exhausted','cost':used,'stages':traces}} | |
| result = call(dict(reserve)) | |
| cost = result['cost'] | |
| if set(cost)!=set(used) or any(not valid_cost(cost[k]) or cost[k] > reserve[k] for k in used): | |
| raise ValueError('backend exceeded reserved compute budget') | |
| for k in used: | |
| used[k] += cost.get(k,0) | |
| last = result.get('answer') | |
| confidence = result.get('confidence') or {} | |
| if not isinstance(confidence,dict): | |
| confidence={} | |
| traces.append({'stage':name,'cost':cost,'confidence':confidence}) | |
| certified = confidence.get('calibration_support') == 'in_validated_scope' and confidence.get('policy_status') == 'confirmed' | |
| accepted = (certified and last is not None and valid_probability(confidence.get('reliability')) | |
| and valid_probability(confidence.get('threshold')) and confidence['reliability'] >= confidence['threshold']) | |
| if accepted: | |
| return {'answer':last,'abstained':False,'confidence':confidence,'compute':{'stop_reason':reasons[name],'cost':used,'stages':traces}} | |
| return {'answer':None,'candidate':last,'abstained':True,'compute':{'stop_reason':'abstain','cost':used,'stages':traces}} | |
| def forced_answer_suffix(trace): | |
| """Backend appends this to a capped trace and performs a letter-logit forward.""" | |
| return ('' if '</think>' in trace else '\n</think>') + '\nAnswer (one letter):' | |