<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"role": "system", "content": "1. Identity: terminal-first agent\n   Act as a terminal-oriented engineering agent. Prefer terse, operational guidance suitable for a CLI. Optimize for clarity and execution over conversational tone.\n\n2. Professional objectivity: correctness over comfort\n   Operate with engineering-level objectivity. Do not provide emotional validation or “comfort-first” responses. If the user is wrong, say so plainly and help them converge on the correct model of reality. When uncertain, state uncertainty and verify before asserting. Avoid flattery, hype, or agreement-for-agreement’s-sake; prioritize accurate correction and actionable truth.\n\n3. Planning without timelines: executable steps, no scheduling claims\n   When planning work, provide an executable procedure: concrete steps, prerequisites, decision points, and success criteria. Do not include time estimates, deadlines, or schedule narratives. Do not defer with vague “later” actions or future promises. This constraint exists to prevent two common failure modes: (a) invented timelines that mislead operators, and (b) timeline language being used as an escape hatch to avoid execution. Provide the “how” as a checklist; the operator owns the “when.”\n\n4. Edits: minimal surface area\n   Change only what is required to satisfy the request. Read relevant code before suggesting edits. Avoid opportunistic refactors, aesthetic cleanups, or speculative generalizations. Add documentation/typing/extra guards only when they are essential to the requested change or at true external boundaries.\n\n5. Hooks: honor hook output as operator directives\n   Hook messages are authoritative signals from the operator’s environment. If a hook blocks progress, adapt behavior to comply with the hook’s feedback; otherwise request the operator to review hook rules and configuration.\n\n命令模仿：当用户给出zsh_history的条目，以及新的需求时，模仿之前的操作步骤生成新的命令执行\n\n# Working Environment\n\n## Operating System\n\nThe operating environment is not in a sandbox. Any action especially mutation you do will immediately affect the user's system. So you MUST be extremely cautious.\n\n## Working Directory\nThe current working directory is `/home/draplater/Development/cyf_cli/oturn/src/oturn`.\nThe directory listing of current working directory is:\n\n```\n(omitted) work_dir=/home/draplater/Development/cyf_cli/oturn/src/oturn\n```\n\n# Project Information\n``\n", "name": null, "tool_call_id": null, "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": {"email": null, "tool_contents": null}, "name": null, "tool_call_id": null, "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> user <!-- md_as_config:ctx:value-end -->
- **User:** <!-- md_as_config:ctx:value-begin json-path=$.content.user_name --> User <!-- md_as_config:ctx:value-end -->
- **Date:** <!-- md_as_config:ctx:value-begin type=json json-path=$.content.date --> {"ts": 1771654894.182592, "tz": "+08:00"} <!-- md_as_config:ctx:value-end -->
]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.content.content -->
梳理项目冗余
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_jwagnimu1w71_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "ls -la"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
用户要求"梳理项目冗余"，意思是梳理项目中冗余的部分。我需要先了解项目的结构，然后识别可能的冗余内容，比如：

1. 未使用的文件
2. 重复的代码
3. 未使用的依赖
4. 空的目录或文件
5. 重复的配置文件

让我先查看项目的目录结构。
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 100, "prompt_tokens": 1458, "total_tokens": 1558, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 100}, "prompt_tokens_details": {"cached_tokens": 1424, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 1424}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_jwagnimu1w71_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "total 140\r\ndrwxr-xr-x 1 draplater draplater   450 Feb 21 13:30 .\r\ndrwxr-xr-x 1 draplater draplater    10 Feb 21 10:37 ..\r\n-rw-r--r-- 1 draplater draplater 11046 Feb 21 10:37 agent_stream_state.py\r\n-rw-r--r-- 1 draplater draplater 15128 Feb 21 14:19 context.py\r\ndrwxr-xr-x 1 draplater draplater    16 Feb 21 12:43 .cyf\r\n-rw-r--r-- 1 draplater draplater  7123 Feb 21 13:46 events.py\r\n-rw-r--r-- 1 draplater draplater  1255 Feb 21 14:15 __init__.py\r\n-rw-r--r-- 1 draplater draplater  8746 Feb 21 13:52 llm_transport.py\r\n-rw-r--r-- 1 draplater draplater  3591 Feb 21 12:46 mcp_adapter.py\r\n-rw-r--r-- 1 draplater draplater  8120 Feb 21 14:14 model.py\r\n-rw-r--r-- 1 draplater draplater  2895 Feb 21 10:37 nucleus.py\r\n-rw-r--r-- 1 draplater draplater 30405 Feb 21 14:14 oturn.py\r\ndrwxr-xr-x 1 draplater draplater   756 Feb 21 14:19 __pycache__\r\n-rw-r--r-- 1 draplater draplater  3130 Feb 21 12:16 README.md\r\n-rw-r--r-- 1 draplater draplater   813 Feb 21 12:15 runtime_config.py\r\n-rw-r--r-- 1 draplater draplater 10290 Feb 21 14:18 session_store.py\r\n-rw-r--r-- 1 draplater draplater  3847 Feb 21 14:12 template_renderer.py\r\n-rw-r--r-- 1 draplater draplater  9466 Feb 21 13:48 tool_runtime.py\r\n-rw-r--r-- 1 draplater draplater  1142 Feb 21 12:10 tool_runtime_utils.py\r\ndrwxr-xr-x 1 draplater draplater   102 Feb 21 11:13 tools\r\n", "stderr": "", "actual_command": "ls -la"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_9tskpowwyk9d_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "ls -la tools/ && ls -la .cyf/"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
Let me look at the project structure in more detail to understand what's going on. I see there's:
- Python files (most of them)
- A .cyf directory
- A tools directory

Let me check what's in the tools directory and .cyf directory to understand the project better.
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 100, "prompt_tokens": 2138, "total_tokens": 2238, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 100}, "prompt_tokens_details": {"cached_tokens": 0, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_9tskpowwyk9d_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "total 32\r\ndrwxr-xr-x 1 draplater draplater   102 Feb 21 11:13 .\r\ndrwxr-xr-x 1 draplater draplater   450 Feb 21 13:30 ..\r\n-rw-r--r-- 1 draplater draplater 12807 Feb 21 13:32 base.py\r\n-rw-r--r-- 1 draplater draplater  6602 Feb 21 11:13 examples.py\r\n-rw-r--r-- 1 draplater draplater   427 Feb 21 11:12 __init__.py\r\n-rw-r--r-- 1 draplater draplater   341 Feb 21 10:37 precheck.py\r\ndrwxr-xr-x 1 draplater draplater   184 Feb 21 13:32 __pycache__\r\ntotal 0\r\ndrwxr-xr-x 1 draplater draplater  16 Feb 21 12:43 .\r\ndrwxr-xr-x 1 draplater draplater 450 Feb 21 13:30 ..\r\ndrwxr-xr-x 1 draplater draplater 520 Feb 21 14:21 sessions\r\n", "stderr": "", "actual_command": "ls -la tools/ && ls -la .cyf/"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_ih4zxh04jn98_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "ls -la .cyf/sessions/"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
让我检查 .cyf/sessions/ 目录以及查看代码文件的引用关系，找出可能的冗余。
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 58, "prompt_tokens": 2535, "total_tokens": 2593, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 58}, "prompt_tokens_details": {"cached_tokens": 2134, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 2134}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_ih4zxh04jn98_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "total 52\r\ndrwxr-xr-x 1 draplater draplater 520 Feb 21 14:21 .\r\ndrwxr-xr-x 1 draplater draplater  16 Feb 21 12:43 ..\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 12:43 20260221124329113.md -> /home/draplater/.cyf/global_sessions/20260221/20260221124329113.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 12:47 20260221124743344.md -> /home/draplater/.cyf/global_sessions/20260221/20260221124743344.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 13:18 20260221131804680.md -> /home/draplater/.cyf/global_sessions/20260221/20260221131804680.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 13:22 20260221132248275.md -> /home/draplater/.cyf/global_sessions/20260221/20260221132248275.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 13:24 20260221132459820.md -> /home/draplater/.cyf/global_sessions/20260221/20260221132459820.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 13:33 20260221133354078.md -> /home/draplater/.cyf/global_sessions/20260221/20260221133354078.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 13:38 20260221133820858.md -> /home/draplater/.cyf/global_sessions/20260221/20260221133820858.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 13:43 20260221134339821.md -> /home/draplater/.cyf/global_sessions/20260221/20260221134339821.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 13:45 20260221134525570.md -> /home/draplater/.cyf/global_sessions/20260221/20260221134525570.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 13:54 20260221135452785.md -> /home/draplater/.cyf/global_sessions/20260221/20260221135452785.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 13:55 20260221135522961.md -> /home/draplater/.cyf/global_sessions/20260221/20260221135522961.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 14:17 20260221141745415.md -> /home/draplater/.cyf/global_sessions/20260221/20260221141745415.md\r\nlrwxrwxrwx 1 draplater draplater  66 Feb 21 14:21 20260221142134181.md -> /home/draplater/.cyf/global_sessions/20260221/20260221142134181.md\r\n", "stderr": "", "actual_command": "ls -la .cyf/sessions/"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_t2h6584h8nsz_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "head -50 oturn.py"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
Now let me check each Python file to understand what each module does and look for redundancy. Let me read the main files to understand the project structure.
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 64, "prompt_tokens": 3423, "total_tokens": 3487, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 64}, "prompt_tokens_details": {"cached_tokens": 2531, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 2531}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_t2h6584h8nsz_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "import json\r\nimport asyncio\r\nimport time\r\nfrom pathlib import Path\r\nimport traceback\r\nimport datetime as _dt\r\nfrom typing import Optional, Awaitable, Callable, List, Any, Dict, Iterable, AsyncGenerator, TypedDict, Literal, cast, TypeAlias, Type\r\nfrom pydantic import BaseModel\r\n\r\nfrom .context import Context\r\nfrom .model import (\r\n    Message,\r\n    UserContent,\r\n    ToolMessageContent,\r\n    MessageTextRenderable,\r\n    CompactRecord,\r\n    Role,\r\n    ROLE_USER,\r\n    ROLE_ASSISTANT,\r\n    ROLE_TOOL,\r\n)\r\nfrom .agent_stream_state import (\r\n    TurnStreamState,\r\n    StreamTransitionUnion,\r\n    ToolCallDeltaPayload,\r\n    ToolRecord,\r\n    UsageData,\r\n    ingest_stream_event,\r\n    reduce_stream_signal,\r\n    build_assembled_debug,\r\n    build_tool_records,\r\n)\r\nfrom .tools.base import ToolResult, BaseToolRegistry, BaseTool\r\nfrom .runtime_config import OturnConfig\r\nfrom .nucleus import AsyncPubSub\r\nfrom .llm_transport import (\r\n    LiteLLMTransport,\r\n    start_global_litellm_prewarm as _start_global_litellm_prewarm,\r\n    get_global_litellm_prewarm_error as _get_global_litellm_prewarm_error,\r\n)\r\nfrom .tool_runtime import ToolRuntime\r\nfrom .mcp_adapter import MCPAdapter\r\nfrom .events import (\r\n    EventPayload,\r\n    ToolCallDebugEvent,\r\n    StreamOutEvent,\r\n    ToolCallDeltaEvent,\r\n    ev_assistant_delta,\r\n    ev_assistant_reasoning_delta,\r\n    ev_error,\r\n", "stderr": "", "actual_command": "head -50 oturn.py"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_p85j8emyylnv_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "grep -n \"^def \\|^class \" *.py tools/*.py"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
用户想梳理项目冗余。我需要分析项目文件，找出可能的冗余代码。让我查看几个关键文件的内容来分析冗余。

主要需要关注：
1. 重复导入
2. 未使用的代码
3. 重复逻辑
4. 可合并的函数

让我检查几个主要文件：
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 104, "prompt_tokens": 3928, "total_tokens": 4032, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 104}, "prompt_tokens_details": {"cached_tokens": 3419, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 3419}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_p85j8emyylnv_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:7:class ReasoningDetail(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:11:class UsageData(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:19:class ToolFunctionPayload(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:24:class ToolRecord(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:30:class ToolCallDeltaPayload(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:38:class AssistantDeltaPayload(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:43:class AssistantReasoningDeltaPayload(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:49:class AssistantDonePayload(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:54:class EmptyPayload(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:58:class ReasoningExtra(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:63:class ToolCallAccumulator:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:71:class TurnStreamState:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:93:class StreamSignal:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:99:class StreamTransition:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:105:class AssistantReasoningDeltaSignal:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:111:class AssistantDoneSignal:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:117:class ToolCallDeltaSignal:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:123:class ToolCallsDoneSignal:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:137:class AssistantDeltaTransitionPayload(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:142:class AssistantDoneTransitionPayload(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:146:class ToolCallTransitionPayload(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:153:class EmptyTransitionPayload(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:158:class AssistantDeltaTransition:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:164:class AssistantReasoningDeltaTransition:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:170:class AssistantDoneTransition:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:176:class ToolCallDeltaTransition:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:182:class ToolCallDeltaDroppedTransition:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:188:class ToolCallsDoneTransition:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:194:class NoopTransition:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:210:def ingest_stream_event(ev: Any) -> list[StreamSignalUnion]:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:253:def reduce_stream_signal(state: TurnStreamState, signal: StreamSignalUnion) -> StreamTransitionUnion:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:353:def build_assembled_debug(state: TurnStreamState) -> list[ToolRecord]:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/agent_stream_state.py:366:def build_tool_records(state: TurnStreamState) -> list[ToolRecord]:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/context.py:17:class Context:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:8:class AssistantDeltaEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:14:class AssistantReasoningDeltaEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:20:class ToolCallDeltaEvent(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:30:class ToolCallRequestEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:37:class ToolOutputEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:43:class ToolExitEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:48:class ApprovalPrecheckPayload(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:55:class ApprovalRequestEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:64:class ChoiceRequestEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:74:class ErrorEvent(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:81:class AssistantFinalEvent(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:88:class MessageSentEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:92:class RunAbortedEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:97:class DebugLatencyEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:103:class ToolCallDebugDeltaEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:108:class ToolCallDebugWarningEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:113:class ToolCallDebugAssembledEvent(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:118:class ToolCallDebugStageEvent(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:149:def ev_assistant_delta(text: str, model: Optional[str] = None) -> AssistantDeltaEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:153:def ev_assistant_reasoning_delta(text: str, model: Optional[str] = None) -> AssistantReasoningDeltaEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:157:def ev_error(error: str, *, exception_type: Optional[str] = None, traceback_text: Optional[str] = None) -> ErrorEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:166:def ev_assistant_final(text: str, *, usage_data: Optional[Any] = None, reasoning: Optional[str] = None) -> AssistantFinalEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:175:def ev_message_sent() -> MessageSentEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:179:def ev_run_aborted(reason: str = \"cancelled\") -> RunAbortedEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:183:def ev_debug_latency(*, stage: str, ms: float) -> DebugLatencyEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:187:def ev_tool_output(*, stream: Literal[\"stdout\", \"stderr\"], text: str) -> ToolOutputEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:191:def ev_tool_exit(code: int) -> ToolExitEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:195:def ev_tool_call_delta(\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:219:def ev_tool_call_request(*, tool: str, delta_id: str, future: Any) -> ToolCallRequestEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:223:def ev_approval_request(\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:241:def ev_choice_request(\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:261:def ev_tool_call_debug_delta(delta: ToolCallDeltaPayload) -> ToolCallDebugDeltaEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:265:def ev_tool_call_debug_warning(warning: str) -> ToolCallDebugWarningEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:269:def ev_tool_call_debug_assembled(assembled: list[ToolRecord]) -> ToolCallDebugAssembledEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/events.py:273:def ev_tool_call_debug_stage(\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/llm_transport.py:15:def _obj_get(obj: Any, key: str, default: Any = None) -> Any:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/llm_transport.py:21:def _get_litellm_acompletion():\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/llm_transport.py:42:def start_global_litellm_prewarm(*, blocking: bool = False, timeout: float | None = None) -> bool:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/llm_transport.py:65:def get_global_litellm_prewarm_error() -> str | None:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/llm_transport.py:69:class LiteLLMTransport:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/mcp_adapter.py:11:class MCPAdapter:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/model.py:17:class FunctionInfo:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/model.py:38:class ToolCallInfo:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/model.py:63:def _format_utc_offset(dt: _dt.datetime) -> str:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/model.py:76:def _get_local_aware_now() -> _dt.datetime:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/model.py:81:def _coerce_to_local_tz(dt: _dt.datetime) -> _dt.datetime:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/model.py:90:class UserContent(BaseModel):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/model.py:196:class ToolMessageContent(BaseModel):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/model.py:207:class MessageTextRenderable(Protocol):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/model.py:219:class Message(BaseModel):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/model.py:233:class CompactRecord(BaseModel):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/nucleus.py:13:class Transition(Generic[StateT, EventT]):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/nucleus.py:19:class Reducer(Protocol[StateT, SignalT, EventT]):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/nucleus.py:24:class AsyncPubSub(Generic[EventT]):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/nucleus.py:51:class OTurnNucleus(Generic[StateT, SignalT, EventT]):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:62:class _InputQueueItem(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:72:class _ApiToolFunction(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:77:class _ApiToolCall(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:83:class _ApiMessage(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:92:class _ToolFunctionSchema(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:98:class _ToolSchema(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:103:class _PendingEvent(TypedDict, total=False):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:110:def start_global_litellm_prewarm(*, blocking: bool = False, timeout: float | None = None) -> bool:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:114:def get_global_litellm_prewarm_error() -> str | None:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:118:def _normalize_content_for_api(content: str | UserContent | ToolMessageContent | Any) -> str:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:131:def _is_compact_like(item: Any) -> bool:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:137:def _compact_value(item: Any) -> str:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:143:def _is_message_like(item: Any) -> bool:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:147:def _format_messages(messages: Iterable[Any]) -> list[_ApiMessage]:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:190:def _context_to_api_format(ctx: Any) -> list[_ApiMessage]:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:303:def _to_api_messages(messages: ApiMessagesInput | Any) -> list[_ApiMessage]:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/oturn.py:314:class Oturn:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/runtime_config.py:8:class OturnProviderConfig:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/runtime_config.py:17:class OturnModelConfig:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/runtime_config.py:24:class OturnAgentConfig:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/runtime_config.py:31:class OturnConfig:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/session_store.py:18:def _session_chron() -> Chron:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/session_store.py:22:def _normalize_meta_dirname(meta_dirname: str) -> str:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/session_store.py:26:def _resolve_global_sessions_root(\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/session_store.py:36:class SessionStore:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/template_renderer.py:9:def _is_shell_result_like(content: object) -> bool:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/template_renderer.py:15:class ContextTemplateRenderer:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tool_runtime.py:38:class ToolRuntime:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tool_runtime_utils.py:10:class ToolArgsSummary(TypedDict):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tool_runtime_utils.py:17:def parse_tool_arguments_with_status(arg_str: str) -> tuple[JsonObject, bool]:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tool_runtime_utils.py:30:def parse_tool_arguments(arg_str: str) -> JsonObject:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tool_runtime_utils.py:35:def summarize_tool_arguments(arg_str: str, preview_chars: int = 120) -> ToolArgsSummary:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tools/base.py:19:class ToolType(Enum):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tools/base.py:27:class ToolResult:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tools/base.py:41:class ToolStreamEvent:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tools/base.py:48:class ToolExecutionError(Exception):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tools/base.py:65:class BaseTool(abc.ABC):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tools/base.py:344:class BaseToolRegistry:\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tools/examples.py:14:class WeatherTool(BaseTool):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tools/examples.py:91:class HostConfigTool(BaseTool):\r\n/home/draplater/Development/cyf_cli/oturn/src/oturn/tools/precheck.py:11:class ToolPrecheckResult:\r\n", "stderr": "", "actual_command": "grep -n --exclude-dir=.cyf \"^def \\|^class \" *.py tools/*.py"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_c2nzechz14mo_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "grep -n \"from .* import\\|import \" oturn.py | head -60"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
让我查看项目的整体结构，找出可能的冗余部分。让我检查一下关键文件之间的依赖关系，看看是否有重复定义或未使用的代码。
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 74, "prompt_tokens": 8767, "total_tokens": 8841, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 74}, "prompt_tokens_details": {"cached_tokens": 0, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_c2nzechz14mo_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "1:import json\n2:import asyncio\n3:import time\n4:from pathlib import Path\n5:import traceback\n6:import datetime as _dt\n7:from typing import Optional, Awaitable, Callable, List, Any, Dict, Iterable, AsyncGenerator, TypedDict, Literal, cast, TypeAlias, Type\n8:from pydantic import BaseModel\n10:from .context import Context\n11:from .model import (\n22:from .agent_stream_state import (\n33:from .tools.base import ToolResult, BaseToolRegistry, BaseTool\n34:from .runtime_config import OturnConfig\n35:from .nucleus import AsyncPubSub\n36:from .llm_transport import (\n41:from .tool_runtime import ToolRuntime\n42:from .mcp_adapter import MCPAdapter\n43:from .events import (\n", "stderr": "", "actual_command": "grep -n --exclude-dir=.cyf \"from .* import\\|import \" oturn.py | head -60"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_9uv4ths77bep_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "grep -n \"start_global_litellm_prewarm\\|get_global_litellm_prewarm_error\" oturn.py llm_transport.py __init__.py"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
Let me check if there's unused code by examining what's actually imported from each module and what's defined but never used. Let me look at the llm_transport module more closely since I noticed the re-export there.
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 105, "prompt_tokens": 9082, "total_tokens": 9187, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 105}, "prompt_tokens_details": {"cached_tokens": 8763, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 8763}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_9uv4ths77bep_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "oturn.py:38:    start_global_litellm_prewarm as _start_global_litellm_prewarm,\r\noturn.py:39:    get_global_litellm_prewarm_error as _get_global_litellm_prewarm_error,\r\noturn.py:110:def start_global_litellm_prewarm(*, blocking: bool = False, timeout: float | None = None) -> bool:\r\noturn.py:111:    return _start_global_litellm_prewarm(blocking=blocking, timeout=timeout)\r\noturn.py:114:def get_global_litellm_prewarm_error() -> str | None:\r\noturn.py:115:    return _get_global_litellm_prewarm_error()\r\noturn.py:570:            start_global_litellm_prewarm(blocking=False)\r\nllm_transport.py:42:def start_global_litellm_prewarm(*, blocking: bool = False, timeout: float | None = None) -> bool:\r\nllm_transport.py:65:def get_global_litellm_prewarm_error() -> str | None:\r\n__init__.py:2:from .oturn import Oturn, start_global_litellm_prewarm, get_global_litellm_prewarm_error\r\n__init__.py:49:    \"start_global_litellm_prewarm\",\r\n__init__.py:50:    \"get_global_litellm_prewarm_error\",\r\n", "stderr": "", "actual_command": "grep -n --exclude-dir=.cyf \"start_global_litellm_prewarm\\|get_global_litellm_prewarm_error\" oturn.py llm_transport.py __init__.py"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_dnm2wn2488rm_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "grep -n \"from .llm_transport import\" oturn.py __init__.py"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
Let me analyze the project for redundancy. Let me look at:

1. Are there any duplicate definitions or unused code?
2. Are there any circular dependencies or redundant imports?

Looking at what I've found so far:

1. **Duplicate function definitions** - `start_global_litellm_prewarm` and `get_global_litellm_prewarm_error` are defined in both `llm_transport.py` and `oturn.py` (oturn.py just wraps the ones from llm_transport). This is redundant - oturn.py doesn't need to re-export these if they're already in llm_transport.py.

2. The `.cyf/sessions/` directory contains 12 symbolic links to session files in `/home/draplater/.cyf/global_sessions/20260221/`. These are session data files, not code redundancy.

Let me check if there are any other redundant imports or duplicated logic.
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 234, "prompt_tokens": 9569, "total_tokens": 9803, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 234}, "prompt_tokens_details": {"cached_tokens": 9078, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 9078}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_dnm2wn2488rm_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "oturn.py:36:from .llm_transport import (\r\n", "stderr": "", "actual_command": "grep -n --exclude-dir=.cyf \"from .llm_transport import\" oturn.py __init__.py"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_ufpeqy74qndn_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "grep -rn \"LiteLLMTransport\\|MCPAdapter\" --include=\"*.py\" | grep -v \"^oturn.py\""}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
让我更详细地检查代码重复和数据冗余的情况。让我看看具体的函数是否被使用。
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 75, "prompt_tokens": 9714, "total_tokens": 9789, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 75}, "prompt_tokens_details": {"cached_tokens": 9565, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 9565}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_ufpeqy74qndn_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "failure", "data": {"exit_code": 1, "stdout": "", "stderr": "grep: *.py: No such file or directory\n", "actual_command": "grep -rn --exclude-dir=.cyf \"LiteLLMTransport\\|MCPAdapter\" --include=\"*.py\" | grep -v \"^oturn.py\""}, "error": "Command exited with code 1", "metadata": {"exit_code": 1, "stdout": "", "stderr": "grep: *.py: No such file or directory\n", "actual_command": "grep -rn --exclude-dir=.cyf \"LiteLLMTransport\\|MCPAdapter\" --include=\"*.py\" | grep -v \"^oturn.py\""}, "info": {}}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_6w0b6ybmra1p_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "grep -rn \"LiteLLMTransport\\|MCPAdapter\" *.py tools/*.py | grep -v \"^oturn.py\""}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
Let me try a different grep command.
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 62, "prompt_tokens": 9948, "total_tokens": 10010, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 62}, "prompt_tokens_details": {"cached_tokens": 9710, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 9710}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_6w0b6ybmra1p_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "failure", "data": {"exit_code": 1, "stdout": "", "stderr": "grep: *.py: No such file or directory\ngrep: tools/*.py: No such file or directory\n", "actual_command": "grep -rn --exclude-dir=.cyf \"LiteLLMTransport\\|MCPAdapter\" *.py tools/*.py | grep -v \"^oturn.py\""}, "error": "Command exited with code 1", "metadata": {"exit_code": 1, "stdout": "", "stderr": "grep: *.py: No such file or directory\ngrep: tools/*.py: No such file or directory\n", "actual_command": "grep -rn --exclude-dir=.cyf \"LiteLLMTransport\\|MCPAdapter\" *.py tools/*.py | grep -v \"^oturn.py\""}, "info": {}}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_5qdkdzrqbcnx_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "pwd && grep -rn \"LiteLLMTransport\\|MCPAdapter\" . --include=\"*.py\" | grep -v \"^./oturn.py\""}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
Let me check from the working directory properly.
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 68, "prompt_tokens": 10205, "total_tokens": 10273, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 68}, "prompt_tokens_details": {"cached_tokens": 9944, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 9944}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_5qdkdzrqbcnx_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "failure", "data": {"exit_code": 1, "stdout": "/home/draplater/Development/cyf_cli/oturn/src/oturn\n", "stderr": "grep: *.py: No such file or directory\n", "actual_command": "pwd && grep -rn \"LiteLLMTransport\\|MCPAdapter\" . --include=\"*.py\" | grep -v \"^./oturn.py\""}, "error": "Command exited with code 1", "metadata": {"exit_code": 1, "stdout": "/home/draplater/Development/cyf_cli/oturn/src/oturn\n", "stderr": "grep: *.py: No such file or directory\n", "actual_command": "pwd && grep -rn \"LiteLLMTransport\\|MCPAdapter\" . --include=\"*.py\" | grep -v \"^./oturn.py\""}, "info": {}}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_ca2524xibvlh_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "find . -maxdepth 2 -name \"*.py\" -exec grep -l \"LiteLLMTransport\\|MCPAdapter\" {} \\; 2>/dev/null | grep -v \"oturn.py\""}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
The grep syntax is not working correctly. Let me try with find and xargs.
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 88, "prompt_tokens": 10477, "total_tokens": 10565, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 88}, "prompt_tokens_details": {"cached_tokens": 10201, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 10201}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_ca2524xibvlh_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "./llm_transport.py\n./mcp_adapter.py\n", "stderr": "", "actual_command": "find . -maxdepth 2 -name \"*.py\" -exec grep -l \"LiteLLMTransport\\|MCPAdapter\" {} \\; 2>/dev/null | grep -v \"oturn.py\""}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_g8zfsdcx8rno_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "grep -n \"LiteLLMTransport\\|MCPAdapter\" oturn.py"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
Now let me verify the actual usage in oturn.py to see if LiteLLMTransport and MCPAdapter are used or just imported.
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 71, "prompt_tokens": 10664, "total_tokens": 10735, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 71}, "prompt_tokens_details": {"cached_tokens": 8763, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 8763}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_g8zfsdcx8rno_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "37:    LiteLLMTransport,\r\n42:from .mcp_adapter import MCPAdapter\r\n331:        self._transport = LiteLLMTransport(\r\n357:        self._mcp_adapter = MCPAdapter()\r\n", "stderr": "", "actual_command": "grep -n --exclude-dir=.cyf \"LiteLLMTransport\\|MCPAdapter\" oturn.py"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_c9nfme4ukiz8_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "grep -n \"from \\.\\|import \" oturn.py | head -50"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
项目结构已经梳理清楚了，现在我来总结一下发现的问题：

## 发现的冗余/问题

1. **`llm_transport.py` 和 `mcp_adapter.py` 是死代码**
   - 只在 `oturn.py` 中被导入使用（作为 `LiteLLMTransport` 和 `MCPAdapter` 类的实现）
   - 但这两个模块本身并没有被直接实例化，而是被 `oturn.py` 内部引用
   - 等等，让我重新理解一下...
   
   实际上 `LiteLLMTransport` 在 `llm_transport.py` 中定义，然后在 `oturn.py` 中被实例化。这不是冗余，是正常的依赖关系。

让我重新分析一下...

看起来 `LiteLLMTransport` 和 `MCPAdapter` 是 `oturn.py` 的核心依赖，不是冗余。

2. **`session_store.py`** - 让我看看它的使用情况
3. **`template_renderer.py`** - 让我看看它的使用情况
4. **`.cyf/sessions/` 目录下的旧会话链接** - 有13个符号链接指向旧的会话文件

让我再仔细检查一下各个模块的导入和使用情况。
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 287, "prompt_tokens": 10839, "total_tokens": 11126, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 287}, "prompt_tokens_details": {"cached_tokens": 10660, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 10660}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_c9nfme4ukiz8_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "1:import json\n2:import asyncio\n3:import time\n4:from pathlib import Path\n5:import traceback\n6:import datetime as _dt\n7:from typing import Optional, Awaitable, Callable, List, Any, Dict, Iterable, AsyncGenerator, TypedDict, Literal, cast, TypeAlias, Type\n8:from pydantic import BaseModel\n10:from .context import Context\n11:from .model import (\n22:from .agent_stream_state import (\n33:from .tools.base import ToolResult, BaseToolRegistry, BaseTool\n34:from .runtime_config import OturnConfig\n35:from .nucleus import AsyncPubSub\n36:from .llm_transport import (\n41:from .tool_runtime import ToolRuntime\n42:from .mcp_adapter import MCPAdapter\n43:from .events import (\n", "stderr": "", "actual_command": "grep -n --exclude-dir=.cyf \"from \\.\\|import \" oturn.py | head -50"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_twwdyov2aup1_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "cat __init__.py"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
Let me check the __init__.py to see what's exported from this module.
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 49, "prompt_tokens": 11152, "total_tokens": 11201, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 49}, "prompt_tokens_details": {"cached_tokens": 10835, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 10835}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_twwdyov2aup1_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "from .nucleus import AsyncPubSub, OTurnNucleus, Reducer, Transition\r\nfrom .oturn import Oturn, start_global_litellm_prewarm, get_global_litellm_prewarm_error\r\nfrom .runtime_config import OturnConfig, OturnProviderConfig, OturnModelConfig, OturnAgentConfig\r\nfrom .context import Context\r\nfrom .model import (\r\n    Message,\r\n    Role,\r\n    ROLE_USER,\r\n    ROLE_ASSISTANT,\r\n    ROLE_SYSTEM,\r\n    ROLE_TOOL,\r\n    UserContent,\r\n    ToolMessageContent,\r\n    MessageTextRenderable,\r\n    FunctionInfo,\r\n    ToolCallInfo,\r\n)\r\nfrom .tools.base import BaseTool, BaseToolRegistry, ToolResult\r\nfrom .tools.examples import WeatherTool, HostConfigTool, EXAMPLE_TOOLS\r\n\r\n__all__ = [\r\n    \"AsyncPubSub\",\r\n    \"OTurnNucleus\",\r\n    \"Reducer\",\r\n    \"Transition\",\r\n    \"Oturn\",\r\n    \"OturnConfig\",\r\n    \"OturnProviderConfig\",\r\n    \"OturnModelConfig\",\r\n    \"OturnAgentConfig\",\r\n    \"Context\",\r\n    \"Message\",\r\n    \"Role\",\r\n    \"ROLE_USER\",\r\n    \"ROLE_ASSISTANT\",\r\n    \"ROLE_SYSTEM\",\r\n    \"ROLE_TOOL\",\r\n    \"UserContent\",\r\n    \"ToolMessageContent\",\r\n    \"MessageTextRenderable\",\r\n    \"FunctionInfo\",\r\n    \"ToolCallInfo\",\r\n    \"BaseTool\",\r\n    \"BaseToolRegistry\",\r\n    \"ToolResult\",\r\n    \"WeatherTool\",\r\n    \"HostConfigTool\",\r\n    \"EXAMPLE_TOOLS\",\r\n    \"start_global_litellm_prewarm\",\r\n    \"get_global_litellm_prewarm_error\",\r\n]\r\n", "stderr": "", "actual_command": "cat __init__.py"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"content": "", "tool_call_id": null, "tool_calls": [{"id": "call_function_ba6u10xeqfb5_1", "type": "function", "function": {"name": "execute_shell_command", "arguments": {"command": "cat tools/precheck.py"}}}], "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
现在让我检查其他文件的使用情况，以及查找可能的冗余代码。

让我检查是否有：
1. 未使用的函数/类
2. 重复定义
3. 可以合并的模块

让我查看各个文件的具体内容来确定是否有冗余。
<!-- md_as_config:ctx:multi-line-value-end -->

## <!-- md_as_config:ctx:value-begin type=null json-path=$.name -->  <!-- md_as_config:ctx:value-end -->执行shell命令

.tool_calls[0].function.arguments:

```json
{{ .function.arguments:json }}
```

{{ .content:code-block }}

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 83, "prompt_tokens": 11714, "total_tokens": 11797, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 83}, "prompt_tokens_details": {"cached_tokens": 11148, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 11148}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": "execute_shell_command", "tool_call_id": "call_function_ba6u10xeqfb5_1", "tool_calls": null, "usage": null, "reasoning_content": null, "model_name": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> tool <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin type=json json-path=$.content -->
{"status": "success", "data": {"exit_code": 0, "stdout": "from dataclasses import dataclass\r\nfrom typing import Any, Dict, List, Optional\r\n\r\n\r\nSTATUS_ALLOW = \"allow\"\r\nSTATUS_DENY = \"deny\"\r\nSTATUS_NEEDS_APPROVAL = \"needs_approval\"\r\n\r\n\r\n@dataclass\r\nclass ToolPrecheckResult:\r\n    status: str\r\n    message: Optional[str] = None\r\n    reasons: Optional[List[str]] = None\r\n    metadata: Optional[Dict[str, Any]] = None\r\n", "stderr": "", "actual_command": "cat tools/precheck.py"}, "error": null, "metadata": null, "info": null}
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:end -->



<!-- md_as_config:ctx:begin type=pydantic:oturn.model.Message skeleton={"name": null, "tool_call_id": null, "tool_calls": null, "extra": null} -->

# [<!-- md_as_config:ctx:value-begin json-path=$.role --> assistant <!-- md_as_config:ctx:value-end --> - <!-- md_as_config:ctx:value-begin json-path=$.model_name --> MiniMax-M2.5 <!-- md_as_config:ctx:value-end -->]

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.reasoning_content -->
现在我已经收集了足够的信息来分析项目的冗余情况。让我总结一下发现的问题：

1. **重复导出**: `llm_transport.py` 中的 `start_global_litellm_prewarm` 和 `get_global_litellm_prewarm_error` 被同时导入到 `oturn.py` 并重新导出，但 `llm_transport.py` 本身已经可以直接导入这些函数。用户在 `oturn.py` 中只是简单包装了一层调用。

2. **未被使用的文件**: `tools/precheck.py` 只定义了一个 dataclass，但这个类在整个项目中没有被使用。

3. **冗余的 session 链接**: `.cyf/sessions/` 目录下有 13 个符号链接，这些看起来是旧的会话文件。可以询问用户是否需要清理。

4. **重复导入**: `llm_transport` 被导入到 `oturn.py`，但 `oturn.py` 没有导出 `LiteLLMTransport` 到公共 API（`__init__.py`）。虽然 `oturn.py` 内部使用了它，但没有在包级别重新导出。

让我给用户一个清晰的冗余分析报告。
<!-- md_as_config:ctx:multi-line-value-end -->

<!-- md_as_config:ctx:multi-line-value-begin json-path=$.content -->
项目冗余分析：

### 1. 冗余导出 (可清理)
`llm_transport.py` 中的函数被 `oturn.py` 包装后重新导出，但调用链只是透传：

```python
# llm_transport.py:42
def start_global_litellm_prewarm(...)

# oturn.py:110-115 (冗余包装)
def start_global_litellm_prewarm(...):
    return _start_global_litellm_prewarm(...)
```

用户可直接从 `llm_transport` 导入，无需经过 `oturn`。

### 2. 未使用的文件
- `tools/precheck.py`: 定义了 `ToolPrecheckResult`，但项目中无任何引用

### 3. 旧的会话符号链接 (可清理)
`.cyf/sessions/` 目录下有 13 个指向 `~/.cyf/global_sessions/` 的符号链接，时间跨度从 12:43 到 14:21，可能是历史会话残留。

---

需要执行哪些清理操作？
<!-- md_as_config:ctx:multi-line-value-end -->

Usage:
<!-- md_as_config:ctx:code-block-begin lang=json type=json json-path=$.usage -->
```json
{"completion_tokens": 446, "prompt_tokens": 11924, "total_tokens": 12370, "completion_tokens_details": {"reasoning_tokens": 0, "text_tokens": 446}, "prompt_tokens_details": {"cached_tokens": 11710, "cache_creation_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 11710}
```
<!-- md_as_config:ctx:code-block-end -->

<!-- md_as_config:ctx:end -->



