Win11 本地部署 OpenClaw 通过 WSL 实现飞书机器人

1. 飞书侧配置

1.1 登录飞书开放平台

飞书开放平台登录页

1.2 应用配置

应用创建页

应用详情

权限设置

权限确认

1.3 权限配置

{
  "scopes": {
    "tenant": [
      "base:app:copy",
      "base:app:create",
      "base:app:read",
      "base:app:update",
      "base:collaborator:create",
      "base:collaborator:delete",
      "base:collaborator:read"

(base) gpu3090@DESKTOP-8IU6393:~/openclaw$ openclaw onboard Config warnings: - plugins.entries.feishu: plugin feishu: duplicate plugin id detected; later plugin may be overridden (/home/gpu3090/.nvm/versions/node/v22.12.0/lib/node_modules/openclaw/extensions/feishu/index.ts) 🦞 OpenClaw 2026.2.23 (b817600) — Your messages, your servers, your control. │ ◇ Config warnings ────────────────────────────────────────────────────────────────────────────────────╮ │ │ │ │ - plugins.entries.feishu: plugin feishu: duplicate plugin id detected; later plugin may │ │ │ │ be overridden │ │ │ │ (/home/gpu3090/.nvm/versions/node/v22.12.0/lib/node_modules/openclaw/extensions/feishu/index.ts) │ │ │ ├──────────────────────────────────────────────────────────────────────────────────────────────────────╯ │ ◇ Doctor changes ────────────────────────────╮ │ │ │ │ feishu configured, enabled automatically. │ │ │ ├─────────────────────────────────────────────╯ │ ◇ Doctor ──────────────────────────────────────────────╮ │ │ │ │ Run "openclaw doctor --fix" to apply these changes. │ │ │ ├───────────────────────────────────────────────────────╯ Config warnings: - plugins.entries.feishu: plugin feishu: duplicate plugin id detected; later plugin may be overridden (/home/gpu3090/.nvm/versions/node/v22.12.0/lib/node_modules/openclaw/extensions/feishu/index.ts) 12:00:52 [plugins] plugins.allow is empty; discovered non-bundled plugins may auto-load: feishu (/home/gpu3090/.openclaw/extensions/feishu/index.ts). Set plugins.allow to explicit trusted ids. Config warnings: - plugins.entries.feishu: plugin feishu: duplicate plugin id detected; later plugin may be overridden (/home/gpu3090/.nvm/versions/node/v22.12.0/lib/node_modules/openclaw/extensions/feishu/index.ts) 12:01:01 [plugins] feishu_doc: Registered feishu_doc, feishu_app_scopes 12:01:01 [plugins] feishu_wiki: Registered feishu_wiki tool 12:01:01 [plugins] feishu_drive: Registered feishu_drive tool 12:01:01 [plugins] feishu_bitable: Registered bitable tools 12:01:01 [plugins] feishu: loaded without install/load-path provenance; treat as untracked local code and pin trust via plugins.allow or install records (/home/gpu3090/.openclaw/extensions/feishu/index.ts) ... │ ◇ Feishu: ok Agents: main (default) Heartbeat interval: 30m (main) Session store (main): /home/gpu3090/.openclaw/agents/main/sessions/sessions.json (1 entries) - agent:main:main (1m ago) │ ◇ Control UI ─────────────────────────────────────────────────────────────────────────────────────╮ │ │ │ │ Web UI: http://127.0.0.1:18789/ │ │ │ │ Web UI (with token): │ │ │ │ http://127.0.0.1:18789/#token=*** │ │ │ │ Gateway WS: ws://127.0.0.1:18789 │ │ │ │ Gateway: reachable │ │ │ │ Docs: https://docs.openclaw.ai/web/control-ui │ │ │ ├───────────────────────────────────────────────────────────────────────────────────────────╯ ... (base) gpu3090@DESKTOP-8IU6393:~/openclaw$ openclaw pairing approve feishu ZMBRUDJ8 ... Approved feishu sender ou_ca33d772eb1cdf7fd9dbfa225f53ce4d.

PS C:\Users\Administrator> wsl -u gpu3090 Now using node v22.12.0 (npm v10.9.0) (base) gpu3090@DESKTOP-8IU6393:/mnt/c/Users/Administrator$ cd (base) gpu3090@DESKTOP-8IU6393:~$ OLLAMA_HOST=0.0.0.0:12346 OLLAMA_MODELS=/home/gpu3090/.ollama/models ollama serve [1]15030 (base) gpu3090@DESKTOP-8IU6393:~$ time=2026-02-24T20:10:33.806+08:00 level=INFO source=routes.go:1663 msg="server config"env="map[CUDA_VISIBLE_DEVICES: GGML_VK_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY:http://127.0.0.1:7897 HTTP_PROXY:http://127.0.0.1:7897 NO_PROXY:172.31.*,172.30.*,172.29.*,172.28.*,172.27.*,172.26.*,172.25.*,172.24.*,172.23.*,172.22.*,172.21.*,172.20.*,172.19.*,172.18.*,172.17.*,172.16.*,10.*,192.168.*,127.*,localhost,<local> OLLAMA_CONTEXT_LENGTH:0 OLLAMA_DEBUG:INFO OLLAMA_EDITOR: OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://0.0.0.0:12346 OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:/home/gpu3090/.ollama/models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NO_CLOUD:false OLLAMA_NUM_PARALLEL:1 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_REMOTES:[ollama.com] OLLAMA_SCHED_SPREAD:false OLLAMA_VULKAN:false ROCR_VISIBLE_DEVICES: http_proxy:http://127.0.0.1:7897 https_proxy:http://127.0.0.1:7897 no_proxy:172.31.*,172.30.*,172.29.*,172.28.*,172.27.*,172.26.*,172.25.*,172.24.*,172.23.*,172.22.*,172.21.*,172.20.*,172.19.*,172.18.*,172.17.*,172.16.*,10.*,192.168.*,127.*,localhost,<local>]"time=2026-02-24T20:10:33.810+08:00 level=INFO source=routes.go:1665 msg="Ollama cloud disabled: false" time=2026-02-24T20:10:34.150+08:00 level=INFO source=images.go:473 msg="total blobs: 53" time=2026-02-24T20:10:34.313+08:00 level=INFO source=images.go:480 msg="total unused blobs removed: 0" time=2026-02-24T20:10:34.458+08:00 level=INFO source=routes.go:1718 msg="Listening on [::]:12346 (version 0.16.3)" time=2026-02-24T20:10:34.473+08:00 level=INFO source=runner.go:67 msg="discovering available GPUs..." time=2026-02-24T20:10:34.502+08:00 level=INFO source=server.go:431 msg="starting runner"cmd="/usr/local/bin/ollama runner --ollama-engine --port 46037" time=2026-02-24T20:10:36.614+08:00 level=INFO source=runner.go:106 msg="experimental Vulkan support disabled. To enable, set OLLAMA_VULKAN=1" time=2026-02-24T20:10:36.615+08:00 level=INFO source=server.go:431 msg="starting runner"cmd="/usr/local/bin/ollama runner --ollama-engine --port 46237" time=2026-02-24T20:10:38.176+08:00 level=INFO source=server.go:431 msg="starting runner"cmd="/usr/local/bin/ollama runner --ollama-engine --port 46265" time=2026-02-24T20:10:38.186+08:00 level=INFO source=server.go:431 msg="starting runner"cmd="/usr/local/bin/ollama runner --ollama-engine --port 45607" time=2026-02-24T20:10:38.416+08:00 level=INFO source=types.go:42 msg="inference compute"id=GPU-67135303-3c02-f35c-3e58-dc2c1b4892fc filter_id=""library=CUDA compute=8.9name=CUDA0 description="NVIDIA GeForce RTX 4090 D"libdirs=ollama,cuda_v13 driver=13.0pci_id=0000:07:00.0 type=discrete total="24.0 GiB"available="20.5 GiB" time=2026-02-24T20:10:38.416+08:00 level=INFO source=routes.go:1768 msg="vram-based default context"total_vram="24.0 GiB"default_num_ctx=32768 time=2026-02-24T20:10:55.284+08:00 level=INFO source=server.go:431 msg="starting runner"cmd="/usr/local/bin/ollama runner --ollama-engine --port 45515" time=2026-02-24T20:10:55.902+08:00 level=INFO source=server.go:247 msg="enabling flash attention" time=2026-02-24T20:10:55.903+08:00 level=INFO source=server.go:431 msg="starting runner"cmd="/usr/local/bin/ollama runner --ollama-engine --model /home/gpu3090/.ollama/models/blobs/sha256-e7b273f9636059a689e3ddcab3716e4f65abe0143ac978e46673ad0e52d09efb --port 46267" time=2026-02-24T20:10:55.903+08:00 level=INFO source=sched.go:491 msg="system memory"total="62.7 GiB"free="60.9 GiB"free_swap="16.0 GiB" time=2026-02-24T20:10:55.903+08:00 level=INFO source=sched.go:498 msg="gpu memory"id=GPU-67135303-3c02-f35c-3e58-dc2c1b4892fc library=CUDA available="20.0 GiB"free="20.4 GiB"minimum="457.0 MiB"overhead="0 B" time=2026-02-24T20:10:55.903+08:00 level=INFO source=server.go:757 msg="loading model""model layers"=25requested=-1 time=2026-02-24T20:10:55.919+08:00 level=INFO source=runner.go:1411 msg="starting ollama engine" time=2026-02-24T20:10:55.941+08:00 level=INFO source=runner.go:1446 msg="Server listening on 127.0.0.1:46267" time=2026-02-24T20:10:55.949+08:00 level=INFO source=runner.go:1284 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:32768 KvCacheType: NumThreads:12 GPULayers:25[ID:GPU-67135303-3c02-f35c-3e58-dc2c1b4892fc Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}" time=2026-02-24T20:10:56.075+08:00 level=INFO source=ggml.go:136 msg=""architecture=gptoss file_type=MXFP4 name=""description=""num_tensors=459num_key_values=32 load_backend: loaded CPU backend from /usr/local/lib/ollama/libggml-cpu-haswell.so ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 CUDA devices: Device 0: NVIDIA GeForce RTX 4090 D, compute capability 8.9, VMM: yes, ID: GPU-67135303-3c02-f35c-3e58-dc2c1b4892fc load_backend: loaded CUDA backend from /usr/local/lib/ollama/cuda_v13/libggml-cuda.so time=2026-02-24T20:10:56.244+08:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 CUDA.0.ARCHS=750,800,860,870,890,900,1000,1030,1100,1200,1210 CUDA.0.USE_GRAPHS=1 CUDA.0.PEER_MAX_BATCH_SIZE=128compiler=cgo(gcc)" time=2026-02-24T20:10:58.623+08:00 level=INFO source=runner.go:1284 msg=load request="{Operation:alloc LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:32768 KvCacheType: NumThreads:12 GPULayers:25[ID:GPU-67135303-3c02-f35c-3e58-dc2c1b4892fc Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}" time=2026-02-24T20:10:59.089+08:00 level=INFO source=runner.go:1284 msg=load request="{Operation:commit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:32768 KvCacheType: NumThreads:12 GPULayers:25[ID:GPU-67135303-3c02-f35c-3e58-dc2c1b4892fc Layers:25(0..24)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}" time=2026-02-24T20:10:59.089+08:00 level=INFO source=ggml.go:482 msg="offloading 24 repeating layers to GPU" time=2026-02-24T20:10:59.089+08:00 level=INFO source=ggml.go:489 msg="offloading output layer to GPU" time=2026-02-24T20:10:59.089+08:00 level=INFO source=ggml.go:494 msg="offloaded 25/25 layers to GPU" time=2026-02-24T20:10:59.089+08:00 level=INFO source=device.go:240 msg="model weights"device=CUDA0 size="11.8 GiB" time=2026-02-24T20:10:59.089+08:00 level=INFO source=device.go:245 msg="model weights"device=CPU size="1.1 GiB" time=2026-02-24T20:10:59.089+08:00 level=INFO source=device.go:251 msg="kv cache"device=CUDA0 size="876.0 MiB" time=2026-02-24T20:10:59.089+08:00 level=INFO source=device.go:262 msg="compute graph"device=CUDA0 size="202.3 MiB" time=2026-02-24T20:10:59.089+08:00 level=INFO source=device.go:267 msg="compute graph"device=CPU size="5.6 MiB" time=2026-02-24T20:10:59.089+08:00 level=INFO source=device.go:272 msg="total memory"size="13.9 GiB" time=2026-02-24T20:10:59.089+08:00 level=INFO source=sched.go:566 msg="loaded runners"count=1 time=2026-02-24T20:10:59.089+08:00 level=INFO source=server.go:1350 msg="waiting for llama runner to start responding" time=2026-02-24T20:10:59.090+08:00 level=INFO source=server.go:1384 msg="waiting for server to become available"status="llm server loading model" time=2026-02-24T20:13:29.638+08:00 level=INFO source=server.go:1388 msg="llama runner started in 150.89 seconds" [GIN]2026/02/24 - 20:13:33 |200| 2m36s |127.0.0.1 | POST "/v1/chat/completions" [GIN]2026/02/24 - 20:14:13 |200|2.66893432s |127.0.0.1 | POST "/v1/chat/completions" [GIN]2026/02/24 - 20:14:15 |200|1.55337028s |127.0.0.1 | POST "/v1/chat/completions" [GIN]2026/02/24 - 20:14:19 |200|3.807682829s |127.0.0.1 | POST "/v1/chat/completions" [GIN]2026/02/24 - 20:16:44 |200|4.57320368s |127.0.0.1 | POST "/v1/chat/completions" ggml_backend_cuda_device_get_memory device GPU-67135303-3c02-f35c-3e58-dc2c1b4892fc utilizing NVML memory reporting free: 7589896192 total: 25757220864 time=2026-02-24T20:21:55.251+08:00 level=INFO source=server.go:431 msg="starting runner"cmd="/usr/local/bin/ollama runner --ollama-engine --port 46347" time=2026-02-24T20:23:16.264+08:00 level=INFO source=server.go:431 msg="starting runner"cmd="/usr/local/bin/ollama runner --ollama-engine --port 44657" time=2026-02-24T20:23:16.818+08:00 level=INFO source=server.go:247 msg="enabling flash attention" time=2026-02-24T20:23:16.819+08:00 level=INFO source=server.go:431 msg="starting runner"cmd="/usr/local/bin/ollama runner --ollama-engine --model /home/gpu3090/.ollama/models/blobs/sha256-e7b273f9636059a689e3ddcab3716e4f65abe0143ac978e46673ad0e52d09efb --port 44781" time=2026-02-24T20:23:16.820+08:00 level=INFO source=sched.go:491 msg="system memory"total="62.7 GiB"free="60.9 GiB"free_swap="16.0 GiB" time=2026-02-24T20:23:16.820+08:00 level=INFO source=sched.go:498 msg="gpu memory"id=GPU-67135303-3c02-f35c-3e58-dc2c1b4892fc library=CUDA available="20.0 GiB"free="20.4 GiB"minimum="457.0 MiB"overhead="0 B"

Win11 本地部署 OpenClaw 通过 WSL 实现飞书机器人

1. 飞书侧配置

1.1 登录飞书开放平台

1.2 应用配置

1.3 权限配置

更多推荐文章

相关免费在线工具

2. WSL 侧配置

2.1 OpenClaw 飞书配置

2.2 启动 Ollama 大模型

Win11 本地部署 OpenClaw 通过 WSL 实现飞书机器人

1. 飞书侧配置

1.1 登录飞书开放平台

1.2 应用配置

1.3 权限配置

微信扫一扫，关注极客日志

更多推荐文章

相关免费在线工具

2. WSL 侧配置

2.1 OpenClaw 飞书配置

2.2 启动 Ollama 大模型