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refactor: rename teacher/student to optimizer/target, remove best skills, fix slow update

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- Rename teacher -> optimizer, student -> target across all code, configs, docs, prompts
- CLI: --teacher_model -> --optimizer_model, --student_model -> --target_model
- Remove best_skill files, keep only initial skills
- Fix slow update gate (force write into skill)
- Fix SLOW_UPDATE marker stripping
- Remove deep_reflect and meta_reflect mechanisms
- Update .env.example with export prefix and azure_cli docs
- Add endpoint empty validation in azure_openai.py

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
Cuzyoung
2026-05-24 19:15:03 +00:00
parent 6e165d5347
commit 4a1b984d87
70 changed files with 1083 additions and 2068 deletions
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skillopt/envs/spreadsheetbench/codegen_agent.py
+21 -21
View File
@@ -30,12 +30,12 @@ def _timeout_handler(signum, frame):
from skillopt.model.azure_openai import (
get_reasoning_effort,
get_student_client,
get_target_client,
_needs_responses_api,
tracker,
)
from skillopt.model import get_codex_exec_config, get_student_backend, is_student_exec_backend
from skillopt.model.codex_harness import prepare_workspace, render_skill_md, run_student_exec
from skillopt.model import get_codex_exec_config, get_target_backend, is_target_exec_backend
from skillopt.model.codex_harness import prepare_workspace, render_skill_md, run_target_exec
from skillopt.prompts import load_prompt
from skillopt.envs.spreadsheetbench.executor import run_generated_code
from skillopt.envs.spreadsheetbench.evaluator import evaluate
@@ -44,13 +44,13 @@ from skillopt.envs.spreadsheetbench.evaluator import evaluate
# ── Eval feedback helper (no golden value leakage) ─────────────────────────
def _build_eval_feedback(verify_report: str) -> str:
"""Build Student feedback from a verify report, hiding expected values.
"""Build Target feedback from a verify report, hiding expected values.
The verify report contains lines like:
Sheet1!D2: got=None, expected=0 ✗
Sheet1!D10: got=None, expected=None ✓
We strip the ``expected=...`` part so the Student sees only its own
We strip the ``expected=...`` part so the Target sees only its own
output and whether each cell is correct or wrong.
"""
import re
@@ -203,7 +203,7 @@ def _llm_call_with_retry(call_fn, *, retries: int = 5, timeout: int = 120):
def _get_deployment() -> str:
from skillopt.model import azure_openai as _llm
return _llm.STUDENT_DEPLOYMENT
return _llm.TARGET_DEPLOYMENT
def _build_codex_skill(skill_content: str) -> str:
@@ -242,7 +242,7 @@ def _build_codex_task(
return (
f"{prompt}\n\n"
"## Codex Harness Task\n"
"- Read `.agents/skills/skillopt-student/SKILL.md` before writing code; do not call a Skill tool.\n"
"- Read `.agents/skills/skillopt-target/SKILL.md` before writing code; do not call a Skill tool.\n"
"- Read and optionally inspect `input.xlsx` in this workspace.\n"
"- Write the final Python solution to `solution.py`.\n"
"- The script should use the provided `INPUT_PATH` and `OUTPUT_PATH` variables.\n"
@@ -296,7 +296,7 @@ def _prepare_codex_workspace(
diagnostic_trace_context=diagnostic_trace_context,
)
prompt = (
"Read `.agents/skills/skillopt-student/SKILL.md` directly; do not call a Skill tool.\n"
"Read `.agents/skills/skillopt-target/SKILL.md` directly; do not call a Skill tool.\n"
"Read `task.md`, inspect `input.xlsx` if useful, and write the final solution to `solution.py`.\n"
"You may run `python run_solution.py` to validate the script locally.\n"
"In your final response, briefly confirm whether `solution.py` was written and summarize the approach."
@@ -319,7 +319,7 @@ def _run_exec_backend(
model: str,
timeout: int,
) -> tuple[str, str]:
return run_student_exec(
return run_target_exec(
work_dir=work_dir,
prompt=prompt,
model=model,
@@ -416,7 +416,7 @@ def run_single(
Returns ``{"code": str, "raw": str, "n_turns": 1}``.
"""
if is_student_exec_backend():
if is_target_exec_backend():
deadline = time.time() + task_timeout
deployment = _get_deployment()
work_dir, skill_md, task_md, prompt = _prepare_codex_workspace(
@@ -449,12 +449,12 @@ def run_single(
"raw": raw or final_message,
"n_turns": 1,
"conversation": [{"role": "assistant", "content": final_message or raw}],
"student_system_prompt": skill_md,
"student_user_prompt": f"{prompt}\n\n## Task File\n\n{task_md}",
"target_system_prompt": skill_md,
"target_user_prompt": f"{prompt}\n\n## Task File\n\n{task_md}",
}
deadline = time.time() + task_timeout
client = get_student_client()
client = get_target_client()
deployment = _get_deployment()
system = _build_system(skill_content)
user = _build_user(
@@ -483,8 +483,8 @@ def run_single(
"raw": raw,
"n_turns": 1,
"conversation": [{"role": "assistant", "content": raw}],
"student_system_prompt": system,
"student_user_prompt": user,
"target_system_prompt": system,
"target_user_prompt": user,
}
@@ -520,7 +520,7 @@ def run_multi(
Returns ``{"code": str, "raw": str, "n_turns": int, "conversation": [...]}``.
"""
if is_student_exec_backend():
if is_target_exec_backend():
deadline = time.time() + task_timeout
deployment = _get_deployment()
work_dir, skill_md, task_md, initial_prompt = _prepare_codex_workspace(
@@ -613,12 +613,12 @@ def run_multi(
"raw": raw or final_message,
"n_turns": len([m for m in conversation if m["role"] == "assistant"]),
"conversation": conversation,
"student_system_prompt": skill_md,
"student_user_prompt": f"{initial_prompt}\n\n## Task File\n\n{task_md}",
"target_system_prompt": skill_md,
"target_user_prompt": f"{initial_prompt}\n\n## Task File\n\n{task_md}",
}
deadline = time.time() + task_timeout
client = get_student_client()
client = get_target_client()
deployment = _get_deployment()
system = _build_system(skill_content)
user = _build_user(
@@ -699,6 +699,6 @@ def run_multi(
"raw": raw,
"n_turns": turn + 1,
"conversation": conversation,
"student_system_prompt": system,
"student_user_prompt": user,
"target_system_prompt": system,
"target_user_prompt": user,
}