mirror of
https://github.com/microsoft/SkillOpt.git
synced 2026-07-03 14:02:58 +08:00
4a1b984d87
- 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>
404 lines
13 KiB
Python
404 lines
13 KiB
Python
"""ReflACT model API with runtime backend selection for the target path."""
|
|
|
|
from __future__ import annotations
|
|
|
|
from typing import Any
|
|
|
|
from skillopt.model import azure_openai as _openai
|
|
from skillopt.model import claude_backend as _claude
|
|
from skillopt.model import qwen_backend as _qwen
|
|
from skillopt.model.backend_config import ( # noqa: F401
|
|
configure_claude_code_exec,
|
|
configure_codex_exec,
|
|
get_claude_code_exec_config,
|
|
get_codex_exec_config,
|
|
get_target_backend,
|
|
get_optimizer_backend,
|
|
is_target_chat_backend,
|
|
is_target_exec_backend,
|
|
is_optimizer_chat_backend,
|
|
set_target_backend,
|
|
set_optimizer_backend,
|
|
)
|
|
|
|
|
|
def set_backend(name: str | None) -> str:
|
|
"""Backward-compatible global backend setter.
|
|
|
|
Historically the codebase used one shared backend for both optimizer and
|
|
target. Keep that entry point so older scripts continue to work, while
|
|
mapping it onto the split optimizer/target backend model.
|
|
"""
|
|
normalized = str(name or "azure_openai").strip().lower()
|
|
if normalized in {"azure_openai", "openai_chat", "azure", "azure-openai"}:
|
|
set_optimizer_backend("openai_chat")
|
|
set_target_backend("openai_chat")
|
|
return "azure_openai"
|
|
if normalized in {"claude", "claude_chat", "anthropic"}:
|
|
set_optimizer_backend("claude_chat")
|
|
set_target_backend("claude_chat")
|
|
return "claude_chat"
|
|
if normalized == "codex":
|
|
set_optimizer_backend("openai_chat")
|
|
set_target_backend("codex_exec")
|
|
return "codex"
|
|
if normalized in {"codex_exec", "claude_code_exec"}:
|
|
set_optimizer_backend("openai_chat")
|
|
set_target_backend(normalized)
|
|
return normalized
|
|
if normalized in {"qwen", "qwen_chat"}:
|
|
set_optimizer_backend("openai_chat")
|
|
set_target_backend("qwen_chat")
|
|
return "qwen_chat"
|
|
raise ValueError(f"Unsupported legacy backend: {name!r}")
|
|
|
|
|
|
def get_backend_name() -> str:
|
|
"""Best-effort backward-compatible backend summary."""
|
|
optimizer = get_optimizer_backend()
|
|
target = get_target_backend()
|
|
if optimizer == "claude_chat" and target == "claude_chat":
|
|
return "claude_chat"
|
|
if optimizer == "openai_chat" and target == "openai_chat":
|
|
return "azure_openai"
|
|
if optimizer == "openai_chat" and target == "codex_exec":
|
|
return "codex"
|
|
if optimizer == "openai_chat" and target == "qwen_chat":
|
|
return "qwen_chat"
|
|
return f"{optimizer}+{target}"
|
|
|
|
|
|
def chat_optimizer(
|
|
system: str,
|
|
user: str,
|
|
max_completion_tokens: int = 16384,
|
|
retries: int = 5,
|
|
stage: str = "optimizer",
|
|
reasoning_effort: str | None = None,
|
|
timeout: int | None = None,
|
|
) -> tuple[str, dict]:
|
|
if get_optimizer_backend() == "claude_chat":
|
|
return _claude.chat_optimizer(
|
|
system=system,
|
|
user=user,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
timeout=timeout,
|
|
)
|
|
return _openai.chat_optimizer(
|
|
system=system,
|
|
user=user,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
reasoning_effort=reasoning_effort,
|
|
timeout=timeout,
|
|
)
|
|
|
|
|
|
def chat_target(
|
|
system: str,
|
|
user: str,
|
|
max_completion_tokens: int = 16384,
|
|
retries: int = 5,
|
|
stage: str = "target",
|
|
reasoning_effort: str | None = None,
|
|
timeout: int | None = None,
|
|
) -> tuple[str, dict]:
|
|
if get_target_backend() == "claude_chat":
|
|
return _claude.chat_target(
|
|
system=system,
|
|
user=user,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
timeout=timeout,
|
|
)
|
|
if get_target_backend() == "qwen_chat":
|
|
return _qwen.chat_target(
|
|
system=system,
|
|
user=user,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
reasoning_effort=reasoning_effort,
|
|
)
|
|
if not is_target_chat_backend():
|
|
raise NotImplementedError(
|
|
"chat_target is only supported with target_backend=openai_chat, claude_chat, or qwen_chat. "
|
|
"Exec backends are handled in environment-specific rollout code."
|
|
)
|
|
return _openai.chat_target(
|
|
system=system,
|
|
user=user,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
reasoning_effort=reasoning_effort,
|
|
timeout=timeout,
|
|
)
|
|
|
|
|
|
def chat_optimizer_messages(
|
|
messages: list[dict[str, Any]],
|
|
max_completion_tokens: int = 16384,
|
|
retries: int = 5,
|
|
stage: str = "optimizer",
|
|
reasoning_effort: str | None = None,
|
|
*,
|
|
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]:
|
|
if get_optimizer_backend() == "claude_chat":
|
|
return _claude.chat_optimizer_messages(
|
|
messages=messages,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
tools=tools,
|
|
tool_choice=tool_choice,
|
|
return_message=return_message,
|
|
timeout=timeout,
|
|
)
|
|
return _openai.chat_optimizer_messages(
|
|
messages=messages,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
reasoning_effort=reasoning_effort,
|
|
tools=tools,
|
|
tool_choice=tool_choice,
|
|
return_message=return_message,
|
|
timeout=timeout,
|
|
)
|
|
|
|
|
|
def chat_target_messages(
|
|
messages: list[dict[str, Any]],
|
|
max_completion_tokens: int = 16384,
|
|
retries: int = 5,
|
|
stage: str = "target",
|
|
reasoning_effort: str | None = None,
|
|
*,
|
|
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]:
|
|
if get_target_backend() == "claude_chat":
|
|
return _claude.chat_target_messages(
|
|
messages=messages,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
tools=tools,
|
|
tool_choice=tool_choice,
|
|
return_message=return_message,
|
|
timeout=timeout,
|
|
)
|
|
if get_target_backend() == "qwen_chat":
|
|
return _qwen.chat_target_messages(
|
|
messages=messages,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
reasoning_effort=reasoning_effort,
|
|
tools=tools,
|
|
tool_choice=tool_choice,
|
|
return_message=return_message,
|
|
)
|
|
if not is_target_chat_backend():
|
|
raise NotImplementedError(
|
|
"chat_target_messages is only supported with target_backend=openai_chat, claude_chat, or qwen_chat. "
|
|
"Exec backends are handled in environment-specific rollout code."
|
|
)
|
|
return _openai.chat_target_messages(
|
|
messages=messages,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
reasoning_effort=reasoning_effort,
|
|
tools=tools,
|
|
tool_choice=tool_choice,
|
|
return_message=return_message,
|
|
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",
|
|
reasoning_effort: str | None = None,
|
|
*,
|
|
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]:
|
|
return _openai.chat_messages_with_deployment(
|
|
deployment=deployment,
|
|
messages=messages,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
reasoning_effort=reasoning_effort,
|
|
tools=tools,
|
|
tool_choice=tool_choice,
|
|
return_message=return_message,
|
|
timeout=timeout,
|
|
)
|
|
|
|
|
|
def chat_with_deployment(
|
|
deployment: str,
|
|
system: str,
|
|
user: str,
|
|
max_completion_tokens: int = 16384,
|
|
retries: int = 5,
|
|
stage: str = "custom",
|
|
reasoning_effort: str | None = None,
|
|
timeout: int | None = None,
|
|
) -> tuple[str, dict]:
|
|
return _openai.chat_with_deployment(
|
|
deployment=deployment,
|
|
system=system,
|
|
user=user,
|
|
max_completion_tokens=max_completion_tokens,
|
|
retries=retries,
|
|
stage=stage,
|
|
reasoning_effort=reasoning_effort,
|
|
timeout=timeout,
|
|
)
|
|
|
|
|
|
def get_token_summary() -> dict:
|
|
summary = _openai.get_token_summary()
|
|
claude_summary = _claude.get_token_summary()
|
|
for stage, values in claude_summary.items():
|
|
if stage == "_total":
|
|
continue
|
|
if stage not in summary:
|
|
summary[stage] = values
|
|
continue
|
|
summary[stage]["calls"] += values["calls"]
|
|
summary[stage]["prompt_tokens"] += values["prompt_tokens"]
|
|
summary[stage]["completion_tokens"] += values["completion_tokens"]
|
|
summary[stage]["total_tokens"] += values["total_tokens"]
|
|
qwen_summary = _qwen.get_token_summary()
|
|
for stage, values in qwen_summary.items():
|
|
if stage == "_total":
|
|
continue
|
|
if stage not in summary:
|
|
summary[stage] = values
|
|
continue
|
|
summary[stage]["calls"] += values["calls"]
|
|
summary[stage]["prompt_tokens"] += values["prompt_tokens"]
|
|
summary[stage]["completion_tokens"] += values["completion_tokens"]
|
|
summary[stage]["total_tokens"] += values["total_tokens"]
|
|
total = {
|
|
"calls": 0,
|
|
"prompt_tokens": 0,
|
|
"completion_tokens": 0,
|
|
"total_tokens": 0,
|
|
}
|
|
for stage, values in summary.items():
|
|
if stage == "_total":
|
|
continue
|
|
total["calls"] += values["calls"]
|
|
total["prompt_tokens"] += values["prompt_tokens"]
|
|
total["completion_tokens"] += values["completion_tokens"]
|
|
total["total_tokens"] += values["total_tokens"]
|
|
summary["_total"] = total
|
|
return summary
|
|
|
|
|
|
def reset_token_tracker() -> None:
|
|
_openai.reset_token_tracker()
|
|
_claude.reset_token_tracker()
|
|
_qwen.reset_token_tracker()
|
|
|
|
|
|
def configure_azure_openai(
|
|
*,
|
|
endpoint: str | None = None,
|
|
api_version: str | None = None,
|
|
api_key: str | None = None,
|
|
auth_mode: str | None = None,
|
|
ad_scope: str | None = None,
|
|
managed_identity_client_id: str | None = None,
|
|
optimizer_endpoint: str | None = None,
|
|
optimizer_api_version: str | None = None,
|
|
optimizer_api_key: str | None = None,
|
|
optimizer_auth_mode: str | None = None,
|
|
optimizer_ad_scope: str | None = None,
|
|
optimizer_managed_identity_client_id: str | None = None,
|
|
target_endpoint: str | None = None,
|
|
target_api_version: str | None = None,
|
|
target_api_key: str | None = None,
|
|
target_auth_mode: str | None = None,
|
|
target_ad_scope: str | None = None,
|
|
target_managed_identity_client_id: str | None = None,
|
|
) -> None:
|
|
_openai.configure_azure_openai(
|
|
endpoint=endpoint,
|
|
api_version=api_version,
|
|
api_key=api_key,
|
|
auth_mode=auth_mode,
|
|
ad_scope=ad_scope,
|
|
managed_identity_client_id=managed_identity_client_id,
|
|
optimizer_endpoint=optimizer_endpoint,
|
|
optimizer_api_version=optimizer_api_version,
|
|
optimizer_api_key=optimizer_api_key,
|
|
optimizer_auth_mode=optimizer_auth_mode,
|
|
optimizer_ad_scope=optimizer_ad_scope,
|
|
optimizer_managed_identity_client_id=optimizer_managed_identity_client_id,
|
|
target_endpoint=target_endpoint,
|
|
target_api_version=target_api_version,
|
|
target_api_key=target_api_key,
|
|
target_auth_mode=target_auth_mode,
|
|
target_ad_scope=target_ad_scope,
|
|
target_managed_identity_client_id=target_managed_identity_client_id,
|
|
)
|
|
|
|
|
|
def configure_qwen_chat(
|
|
*,
|
|
base_url: str | None = None,
|
|
api_key: str | None = None,
|
|
temperature: float | str | None = None,
|
|
timeout_seconds: float | str | None = None,
|
|
max_tokens: int | str | None = None,
|
|
enable_thinking: bool | str | None = None,
|
|
) -> None:
|
|
_qwen.configure_qwen_chat(
|
|
base_url=base_url,
|
|
api_key=api_key,
|
|
temperature=temperature,
|
|
timeout_seconds=timeout_seconds,
|
|
max_tokens=max_tokens,
|
|
enable_thinking=enable_thinking,
|
|
)
|
|
|
|
|
|
def set_reasoning_effort(effort: str | None) -> None:
|
|
_openai.set_reasoning_effort(effort)
|
|
_claude.set_reasoning_effort(effort)
|
|
_qwen.set_reasoning_effort(effort)
|
|
|
|
|
|
def set_target_deployment(deployment: str) -> None:
|
|
_openai.set_target_deployment(deployment)
|
|
_claude.set_target_deployment(deployment)
|
|
_qwen.set_target_deployment(deployment)
|
|
|
|
|
|
def set_optimizer_deployment(deployment: str) -> None:
|
|
_openai.set_optimizer_deployment(deployment)
|
|
_claude.set_optimizer_deployment(deployment)
|