lingma-ipc-proxy

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A standalone Go backend that talks to Lingma over Lingma's local pipe or websocket transport and exposes:

• GET /v1/models
• POST /v1/messages
• POST /v1/chat/completions

Current scope:

• supports both non-streaming and streaming responses
• one request at a time
• supports Windows named-pipe transport and local websocket transport
• directly uses Lingma IPC, not DOM/CDP

Run

cd C:\Workspace\Personal\lingma-ipc-proxy
go run .\cmd\lingma-ipc-proxy

Config File

The proxy can load a JSON config file so you do not need to carry a long command line every time.

Default lookup:

./lingma-ipc-proxy.json

You can also point to an explicit file:

.\dist\lingma-ipc-proxy.exe --config .\config.example.json

Resolution order:

• built-in defaults
• JSON config file
• environment variables
• command-line flags

An example config is included at:

• config.example.json

A practical setup is to copy it to lingma-ipc-proxy.json, adjust the values once, and then start the proxy without a long flag list.

Recommended layout:

{
  "host": "127.0.0.1",
  "port": 8095,
  "transport": "auto",
  "mode": "chat",
  "session_mode": "reuse",
  "timeout": 120,
  "cwd": "C:/Workspace/Personal/lingma-ipc-proxy",
  "shell_type": "powershell",
  "current_file_path": "",
  "pipe": "",
  "websocket_url": ""
}

Build

Build a Windows executable:

cd C:\Workspace\Personal\lingma-ipc-proxy
.\scripts\build.ps1

Default output:

dist\lingma-ipc-proxy.exe

Release

GitHub Actions can publish a GitHub Release automatically.

Trigger rules:

• push a tag matching v*, for example v0.1.0
• or run the Release workflow manually and pass a tag

Example:

git tag v0.1.0
git push origin v0.1.0

Release assets:

• lingma-ipc-proxy_<tag>_windows_amd64.exe
• lingma-ipc-proxy_<tag>_windows_amd64.zip
• lingma-ipc-proxy_<tag>_sha256.txt

Direct Go build command:

$env:CGO_ENABLED = "0"
$env:GOOS = "windows"
$env:GOARCH = "amd64"
go build -trimpath -ldflags "-s -w" -o .\dist\lingma-ipc-proxy.exe .\cmd\lingma-ipc-proxy

Run the built binary:

.\dist\lingma-ipc-proxy.exe --host 127.0.0.1 --port 8095 --session-mode auto
.\dist\lingma-ipc-proxy.exe --transport websocket --ws-url ws://127.0.0.1:36510 --port 8095

Windows Service

For this project, the correct deployment shape is a native local process, not Docker. The proxy talks to Lingma over local pipe or websocket transport, so it should run on the same host as Lingma itself.

NSSM

Build first:

.\scripts\build.ps1

Install with NSSM:

.\scripts\install-nssm-service.ps1 -NssmPath C:\Tools\nssm\nssm.exe

This wraps:

nssm.exe install LingmaIpcProxy C:\Workspace\Personal\lingma-ipc-proxy\dist\lingma-ipc-proxy.exe --host 127.0.0.1 --port 8095 --session-mode auto
nssm.exe set LingmaIpcProxy AppDirectory C:\Workspace\Personal\lingma-ipc-proxy
nssm.exe start LingmaIpcProxy

WinSW

Prepare the executable:

.\scripts\build.ps1

Put a WinSW binary at:

dist\WinSW-x64.exe

Then generate the wrapper files:

.\scripts\install-winsw-service.ps1

That script creates:

• LingmaIpcProxy.exe
• LingmaIpcProxy.xml

Then install/start:

.\LingmaIpcProxy.exe install
.\LingmaIpcProxy.exe start

The WinSW XML template lives at:

• scripts\lingma-ipc-proxy.xml.template

Flags

go run .\cmd\lingma-ipc-proxy --port 8095 --session-mode auto

• --host
• --port
• --transport
• --pipe
• --ws-url
• --cwd
• --current-file-path
• --mode
• --shell-type
• --session-mode
  • reuse: keep using the sticky Lingma session
  • fresh: create a temporary session for the request and delete it after completion
  • auto: single-turn requests reuse; requests with system/history use a temporary fresh session and delete it after completion
• --timeout

Environment

• LINGMA_PROXY_TRANSPORT
• LINGMA_IPC_PIPE
• LINGMA_PROXY_WS_URL
• LINGMA_PROXY_HOST
• LINGMA_PROXY_PORT
• LINGMA_PROXY_CWD
• LINGMA_PROXY_CURRENT_FILE_PATH
• LINGMA_PROXY_MODE
• LINGMA_PROXY_SHELL_TYPE
• LINGMA_PROXY_SESSION_MODE
• LINGMA_PROXY_TIMEOUT_SECONDS

Examples

Anthropic non-streaming:

$body = @{
  model = "dashscope_qwen3_coder"
  messages = @(
    @{ role = "user"; content = "请只回复：ANTHROPIC_OK" }
  )
  stream = $false
} | ConvertTo-Json -Depth 8

Invoke-RestMethod `
  -Method Post `
  -Uri http://127.0.0.1:8095/v1/messages `
  -ContentType "application/json" `
  -Body $body

Anthropic streaming:

$body = @{
  model = "dashscope_qwen3_coder"
  messages = @(
    @{ role = "user"; content = "请只回复：ANTHROPIC_STREAM_OK" }
  )
  stream = $true
} | ConvertTo-Json -Depth 8

curl.exe -N `
  -H "Content-Type: application/json" `
  -d $body `
  http://127.0.0.1:8095/v1/messages

OpenAI non-streaming:

$body = @{
  model = "dashscope_qwen3_coder"
  messages = @(
    @{ role = "user"; content = "请只回复：OPENAI_OK" }
  )
  stream = $false
} | ConvertTo-Json -Depth 8

Invoke-RestMethod `
  -Method Post `
  -Uri http://127.0.0.1:8095/v1/chat/completions `
  -ContentType "application/json" `
  -Body $body

OpenAI streaming:

$body = @{
  model = "dashscope_qwen3_coder"
  messages = @(
    @{ role = "user"; content = "请只回复：OPENAI_STREAM_OK" }
  )
  stream = $true
} | ConvertTo-Json -Depth 8

curl.exe -N `
  -H "Content-Type: application/json" `
  -d $body `
  http://127.0.0.1:8095/v1/chat/completions

Streaming shape

Anthropic streaming emits SSE events compatible with the messages API shape:

• message_start
• content_block_start
• content_block_delta
• content_block_stop
• message_delta
• message_stop

OpenAI streaming emits chat.completion.chunk payloads as data: lines and ends with:

• data: [DONE]