feat: add Hermes Agent as a first-class backend and transcript source

.gitignore

@@ -61,3 +61,4 @@ docs/让*
 tests/run_*.sh
 tests/launch_*.py
 *.launch.log
+.codegraph/

skillopt/model/__init__.py

@@ -6,6 +6,7 @@
 
 from skillopt.model import azure_openai as _openai
 from skillopt.model import claude_backend as _claude
+from skillopt.model import hermes_backend as _hermes
 from skillopt.model import minimax_backend as _minimax
 from skillopt.model import qwen_backend as _qwen
 from skillopt.model.backend_config import (  # noqa: F401
@@ -55,6 +56,10 @@ def set_backend(name: str | None) -> str:
         set_optimizer_backend("openai_chat")
         set_target_backend("minimax_chat")
         return "minimax_chat"
+    if normalized in {"hermes", "hermes_chat"}:
+        set_optimizer_backend("hermes_chat")
+        set_target_backend("hermes_chat")
+        return "hermes_chat"
     raise ValueError(f"Unsupported legacy backend: {name!r}")
 
 
@@ -74,6 +79,8 @@ def get_backend_name() -> str:
         return "qwen_chat"
     if optimizer == "openai_chat" and target == "minimax_chat":
         return "minimax_chat"
+    if optimizer == "hermes_chat" and target == "hermes_chat":
+        return "hermes_chat"
     return f"{optimizer}+{target}"
 
 
@@ -105,6 +112,15 @@ def chat_optimizer(
             reasoning_effort=reasoning_effort,
             timeout=timeout,
         )
+    if get_optimizer_backend() == "hermes_chat":
+        return _hermes.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,
@@ -153,6 +169,15 @@ def chat_target(
             stage=stage,
             reasoning_effort=reasoning_effort,
         )
+    if get_target_backend() == "hermes_chat":
+        return _hermes.chat_target(
+            system=system,
+            user=user,
+            max_completion_tokens=max_completion_tokens,
+            retries=retries,
+            stage=stage,
+            timeout=timeout,
+        )
     if not is_target_chat_backend():
         raise NotImplementedError(
             "chat_target is only supported with target_backend=openai_chat, claude_chat, qwen_chat, or minimax_chat. "
@@ -204,6 +229,17 @@ def chat_optimizer_messages(
             return_message=return_message,
             timeout=timeout,
         )
+    if get_optimizer_backend() == "hermes_chat":
+        return _hermes.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,
@@ -263,6 +299,17 @@ def chat_target_messages(
             tool_choice=tool_choice,
             return_message=return_message,
         )
+    if get_target_backend() == "hermes_chat":
+        return _hermes.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 not is_target_chat_backend():
         raise NotImplementedError(
             "chat_target_messages is only supported with target_backend=openai_chat, claude_chat, qwen_chat, or minimax_chat. "
@@ -294,6 +341,18 @@ def chat_messages_with_deployment(
     return_message: bool = False,
     timeout: int | None = None,
 ) -> tuple[Any, dict]:
+    if get_optimizer_backend() == "hermes_chat" or get_target_backend() == "hermes_chat":
+        return _hermes.chat_messages_with_deployment(
+            deployment=deployment,
+            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_messages_with_deployment(
         deployment=deployment,
         messages=messages,
@@ -318,6 +377,16 @@ def chat_with_deployment(
     reasoning_effort: str | None = None,
     timeout: int | None = None,
 ) -> tuple[str, dict]:
+    if get_optimizer_backend() == "hermes_chat" or get_target_backend() == "hermes_chat":
+        return _hermes.chat_with_deployment(
+            deployment=deployment,
+            system=system,
+            user=user,
+            max_completion_tokens=max_completion_tokens,
+            retries=retries,
+            stage=stage,
+            timeout=timeout,
+        )
     return _openai.chat_with_deployment(
         deployment=deployment,
         system=system,
@@ -365,6 +434,17 @@ def get_token_summary() -> dict:
         summary[stage]["prompt_tokens"] += values["prompt_tokens"]
         summary[stage]["completion_tokens"] += values["completion_tokens"]
         summary[stage]["total_tokens"] += values["total_tokens"]
+    hermes_summary = _hermes.get_token_summary()
+    for stage, values in hermes_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,
@@ -387,6 +467,7 @@ def reset_token_tracker() -> None:
     _claude.reset_token_tracker()
     _qwen.reset_token_tracker()
     _minimax.reset_token_tracker()
+    _hermes.reset_token_tracker()
 
 
 def configure_azure_openai(

skillopt/model/backend_config.py

@@ -49,10 +49,10 @@ def _parse_int(value: str | None, default: int) -> int:
 def set_optimizer_backend(backend: str) -> None:
     global OPTIMIZER_BACKEND
     OPTIMIZER_BACKEND = normalize_backend_name(backend or "openai_chat")
-    if OPTIMIZER_BACKEND not in {"openai_chat", "claude_chat", "qwen_chat", "minimax_chat"}:
+    if OPTIMIZER_BACKEND not in {"openai_chat", "claude_chat", "qwen_chat", "minimax_chat", "hermes_chat"}:
         raise ValueError(
             f"Unsupported optimizer backend: {OPTIMIZER_BACKEND!r}. "
-            "Supported values are 'openai_chat', 'claude_chat', 'qwen_chat', and 'minimax_chat'."
+            "Supported values are 'openai_chat', 'claude_chat', 'qwen_chat', 'minimax_chat', and 'hermes_chat'."
         )
     os.environ["OPTIMIZER_BACKEND"] = OPTIMIZER_BACKEND
 
@@ -64,10 +64,10 @@ def get_optimizer_backend() -> str:
 def set_target_backend(backend: str) -> None:
     global TARGET_BACKEND
     TARGET_BACKEND = normalize_backend_name(backend or "openai_chat")
-    if TARGET_BACKEND not in {"openai_chat", "claude_chat", "qwen_chat", "minimax_chat", "codex_exec", "claude_code_exec"}:
+    if TARGET_BACKEND not in {"openai_chat", "claude_chat", "qwen_chat", "minimax_chat", "codex_exec", "claude_code_exec", "hermes_chat"}:
         raise ValueError(
             f"Unsupported target backend: {TARGET_BACKEND!r}. "
-            "Supported values are 'openai_chat', 'claude_chat', 'qwen_chat', 'minimax_chat', 'codex_exec', and 'claude_code_exec'."
+            "Supported values are 'openai_chat', 'claude_chat', 'qwen_chat', 'minimax_chat', 'codex_exec', 'claude_code_exec', and 'hermes_chat'."
         )
     os.environ["TARGET_BACKEND"] = TARGET_BACKEND
 
@@ -81,11 +81,11 @@ def is_target_exec_backend() -> bool:
 
 
 def is_optimizer_chat_backend() -> bool:
-    return OPTIMIZER_BACKEND in {"openai_chat", "claude_chat", "qwen_chat", "minimax_chat"}
+    return OPTIMIZER_BACKEND in {"openai_chat", "claude_chat", "qwen_chat", "minimax_chat", "hermes_chat"}
 
 
 def is_target_chat_backend() -> bool:
-    return TARGET_BACKEND in {"openai_chat", "claude_chat", "qwen_chat", "minimax_chat"}
+    return TARGET_BACKEND in {"openai_chat", "claude_chat", "qwen_chat", "minimax_chat", "hermes_chat"}
 
 
 def configure_codex_exec(

skillopt/model/common.py

@@ -26,6 +26,7 @@
     "claude_code_exec": "claude-sonnet-4-6",
     "qwen_chat": "Qwen/Qwen3.5-4B",
     "minimax_chat": "MiniMax-M2.7",
+    "hermes_chat": "hermes",
 }
 
 _BACKEND_ALIASES = {
@@ -44,6 +45,8 @@
     "qwen_chat": "qwen_chat",
     "minimax": "minimax_chat",
     "minimax_chat": "minimax_chat",
+    "hermes": "hermes_chat",
+    "hermes_chat": "hermes_chat",
 }