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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/model/claude_backend.py
+19 -19
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@@ -19,8 +19,8 @@ CLAUDE_PERMISSION_MODE = os.environ.get("CLAUDE_PERMISSION_MODE", "dontAsk")
CLAUDE_SETTING_SOURCES = os.environ.get("CLAUDE_SETTING_SOURCES", "user,project")
CLAUDE_ALLOW_ATTACHMENT_READ = os.environ.get("CLAUDE_ALLOW_ATTACHMENT_READ", "1").strip().lower() not in {"0", "false", "no"}
TEACHER_DEPLOYMENT = os.environ.get("TEACHER_DEPLOYMENT", "claude-sonnet-4-6")
STUDENT_DEPLOYMENT = os.environ.get("STUDENT_DEPLOYMENT", "claude-sonnet-4-6")
OPTIMIZER_DEPLOYMENT = os.environ.get("OPTIMIZER_DEPLOYMENT", "claude-sonnet-4-6")
TARGET_DEPLOYMENT = os.environ.get("TARGET_DEPLOYMENT", "claude-sonnet-4-6")
REASONING_EFFORT: str | None = None
_VALID_EFFORTS = {"low", "medium", "high", "xhigh", "max"}
@@ -292,7 +292,7 @@ def _compat_message_from_payload(payload: Any) -> CompatAssistantMessage:
def _call_messages(messages: list[dict[str, Any]], max_completion_tokens: int, retries: int, stage: str, *, tools: list[dict[str, Any]] | None = None, tool_choice: str | dict[str, Any] | None = None, return_message: bool = False, deployment: str | None = None, timeout: int | None = None) -> tuple[Any, dict[str, int]]:
del max_completion_tokens
system, prompt, attachments = _build_prompt_from_messages(messages, tools=tools, tool_choice=tool_choice, structured_output=return_message)
model = deployment or STUDENT_DEPLOYMENT
model = deployment or TARGET_DEPLOYMENT
last_err = None
for attempt in range(retries):
try:
@@ -307,14 +307,14 @@ def _call_messages(messages: list[dict[str, Any]], max_completion_tokens: int, r
raise RuntimeError(f"Claude backend failed after {retries} retries: {last_err}")
def chat_teacher(system: str, user: str, max_completion_tokens: int = 16384, retries: int = 5, stage: str = "teacher", timeout: int | None = None) -> tuple[str, dict[str, int]]:
def chat_optimizer(system: str, user: str, max_completion_tokens: int = 16384, retries: int = 5, stage: str = "optimizer", timeout: int | None = None) -> tuple[str, dict[str, int]]:
messages = [{"role": "system", "content": system}, {"role": "user", "content": user}]
return _call_messages(messages, max_completion_tokens, retries, stage, deployment=TEACHER_DEPLOYMENT, timeout=timeout)
return _call_messages(messages, max_completion_tokens, retries, stage, deployment=OPTIMIZER_DEPLOYMENT, timeout=timeout)
def chat_student(system: str, user: str, max_completion_tokens: int = 16384, retries: int = 5, stage: str = "student", timeout: int | None = None) -> tuple[str, dict[str, int]]:
def chat_target(system: str, user: str, max_completion_tokens: int = 16384, retries: int = 5, stage: str = "target", timeout: int | None = None) -> tuple[str, dict[str, int]]:
messages = [{"role": "system", "content": system}, {"role": "user", "content": user}]
return _call_messages(messages, max_completion_tokens, retries, stage, deployment=STUDENT_DEPLOYMENT, timeout=timeout)
return _call_messages(messages, max_completion_tokens, retries, stage, deployment=TARGET_DEPLOYMENT, timeout=timeout)
def chat_with_deployment(deployment: str, system: str, user: str, max_completion_tokens: int = 16384, retries: int = 5, stage: str = "custom", timeout: int | None = None) -> tuple[str, dict[str, int]]:
@@ -322,12 +322,12 @@ def chat_with_deployment(deployment: str, system: str, user: str, max_completion
return _call_messages(messages, max_completion_tokens, retries, stage, deployment=deployment, timeout=timeout)
def chat_teacher_messages(messages: list[dict[str, Any]], max_completion_tokens: int = 16384, retries: int = 5, stage: str = "teacher", *, tools: list[dict[str, Any]] | None = None, tool_choice: str | dict[str, Any] | None = None, return_message: bool = False, timeout: int | None = None) -> tuple[Any, dict[str, int]]:
return _call_messages(messages, max_completion_tokens, retries, stage, tools=tools, tool_choice=tool_choice, return_message=return_message, deployment=TEACHER_DEPLOYMENT, timeout=timeout)
def chat_optimizer_messages(messages: list[dict[str, Any]], max_completion_tokens: int = 16384, retries: int = 5, stage: str = "optimizer", *, tools: list[dict[str, Any]] | None = None, tool_choice: str | dict[str, Any] | None = None, return_message: bool = False, timeout: int | None = None) -> tuple[Any, dict[str, int]]:
return _call_messages(messages, max_completion_tokens, retries, stage, tools=tools, tool_choice=tool_choice, return_message=return_message, deployment=OPTIMIZER_DEPLOYMENT, timeout=timeout)
def chat_student_messages(messages: list[dict[str, Any]], max_completion_tokens: int = 16384, retries: int = 5, stage: str = "student", *, tools: list[dict[str, Any]] | None = None, tool_choice: str | dict[str, Any] | None = None, return_message: bool = False, timeout: int | None = None) -> tuple[Any, dict[str, int]]:
return _call_messages(messages, max_completion_tokens, retries, stage, tools=tools, tool_choice=tool_choice, return_message=return_message, deployment=STUDENT_DEPLOYMENT, timeout=timeout)
def chat_target_messages(messages: list[dict[str, Any]], max_completion_tokens: int = 16384, retries: int = 5, stage: str = "target", *, tools: list[dict[str, Any]] | None = None, tool_choice: str | dict[str, Any] | None = None, return_message: bool = False, timeout: int | None = None) -> tuple[Any, dict[str, int]]:
return _call_messages(messages, max_completion_tokens, retries, stage, tools=tools, tool_choice=tool_choice, return_message=return_message, deployment=TARGET_DEPLOYMENT, timeout=timeout)
def chat_messages_with_deployment(deployment: str, messages: list[dict[str, Any]], max_completion_tokens: int = 16384, retries: int = 5, stage: str = "custom", *, tools: list[dict[str, Any]] | None = None, tool_choice: str | dict[str, Any] | None = None, return_message: bool = False, timeout: int | None = None) -> tuple[Any, dict[str, int]]:
@@ -347,13 +347,13 @@ def set_reasoning_effort(effort: str | None) -> None:
REASONING_EFFORT = effort if effort else None
def set_student_deployment(deployment: str) -> None:
global STUDENT_DEPLOYMENT
STUDENT_DEPLOYMENT = deployment or default_model_for_backend("claude")
os.environ["STUDENT_DEPLOYMENT"] = STUDENT_DEPLOYMENT
def set_target_deployment(deployment: str) -> None:
global TARGET_DEPLOYMENT
TARGET_DEPLOYMENT = deployment or default_model_for_backend("claude")
os.environ["TARGET_DEPLOYMENT"] = TARGET_DEPLOYMENT
def set_teacher_deployment(deployment: str) -> None:
global TEACHER_DEPLOYMENT
TEACHER_DEPLOYMENT = deployment or default_model_for_backend("claude")
os.environ["TEACHER_DEPLOYMENT"] = TEACHER_DEPLOYMENT
def set_optimizer_deployment(deployment: str) -> None:
global OPTIMIZER_DEPLOYMENT
OPTIMIZER_DEPLOYMENT = deployment or default_model_for_backend("claude")
os.environ["OPTIMIZER_DEPLOYMENT"] = OPTIMIZER_DEPLOYMENT