File size: 3,507 Bytes
30bf68a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 | from __future__ import annotations
from dataclasses import dataclass
from typing import Any, Iterable
from openai import OpenAI
from inference.prompts import REQUIRED_ACTIONS, SYSTEM_PROMPT, build_user_prompt, heuristic_action, sanitize_action_text
@dataclass
class ModelWrapper:
client: OpenAI | None
model_name: str
temperature: float
max_tokens: int
offline: bool
def generate_action(
self,
step: int,
config_text: str,
error_message: str,
history: list[str],
available_actions: Iterable[str] | None = None,
) -> str:
fallback = heuristic_action(config_text, error_message, available_actions, history)
if self.offline or self.client is None:
return fallback
user_prompt = build_user_prompt(
step=step,
config_text=config_text,
error_message=error_message,
history=history,
available_actions=available_actions,
)
try:
completion = self.client.chat.completions.create(
model=self.model_name,
messages=[
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": user_prompt},
],
temperature=max(float(self.temperature), 0.0),
max_tokens=max(16, int(self.max_tokens)),
stream=False,
)
generated = str(completion.choices[0].message.content or "")
return sanitize_action_text(generated, fallback=fallback)
except Exception:
return fallback
def generate_candidates(
self,
step: int,
config_text: str,
error_message: str,
history: list[str],
count: int,
available_actions: Iterable[str] | None = None,
) -> list[str]:
candidates = [heuristic_action(config_text, error_message, available_actions, history)]
for idx in range(max(1, count)):
action = self.generate_action(
step=step,
config_text=config_text,
error_message=error_message,
history=history + [f"candidate={idx}"],
available_actions=available_actions,
)
if action:
candidates.append(action)
deduped: list[str] = []
seen: set[str] = set()
for candidate in candidates:
normalized = candidate.strip()
if not normalized or normalized in seen:
continue
seen.add(normalized)
deduped.append(normalized)
return deduped
def score_action_candidate(observation_text: str, action_text: str, hacking_predicate: Any) -> float:
obs = (observation_text or "").lower()
action = (action_text or "").lower()
score = 0.0
selected_tool = action.split(":", 1)[0].strip()
if selected_tool in REQUIRED_ACTIONS:
score += 0.5
else:
score -= 0.5
if "npm tset" in obs and "edit_config" in action and "npm test" in action:
score += 2.0
if "yaml" in obs and "edit_config" in action:
score += 1.2
if "missing" in obs and "analyze_error" in action:
score += 0.8
if "validate_fix" in action or "submit_solution" in action:
score += 0.5
if hacking_predicate(action_text):
score -= 3.0
score += min(len(action_text) / 240.0, 0.2)
return score
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