feat: add managed SSH execution spaces

Add managed SSH Hosts and projects with signed side-by-side GoodBuddy Agent and OpenCode Runtime installation, Ask and Execute workspace access, a Main-owned model bridge, detached Agent lifecycle, durable ACP output recovery, and project activation UI.

Use protocol v2 with bounded FIFO frames over SSH instead of custom credit, priority, batching, or model-message chunking. Mismatched Host Agents now upgrade automatically, an exactly verified Node runtime is reused on-host, and local Portable builds can embed strictly verified Agent artifacts.

Release note: 新增托管 SSH 远程项目，可自动安装或升级签名 Agent/OpenCode Runtime，并在 SSH 断线后继续 Agent 工作和同步未确认输出。

src/main/agent/model-runtime.test.ts

@@ -621,7 +621,7 @@ describe('ModelAgentRuntime', () => {
     const summaryBody = JSON.parse(
       fetcher.mock.calls[0]![1]!.body as string
     ) as { max_tokens: number; system: string; messages: unknown[] }
-    expect(summaryBody.max_tokens).toBe(8_192)
+    expect(summaryBody.max_tokens).toBe(32_000)
     expect(summaryBody.system).toContain('Summarize earlier history.')
     expect(JSON.stringify(summaryBody.messages)).toContain('old-user-')
     expect(JSON.stringify(summaryBody.messages)).not.toContain('new-user-')
@@ -1847,13 +1847,15 @@ describe('ModelAgentRuntime', () => {
     })
     expect(JSON.parse(init?.body as string)).toMatchObject({
       model: 'gpt-5',
-      max_output_tokens: 4096,
       stream: true,
       instructions: expect.stringContaining('GoodBuddy'),
       input: [
         expect.objectContaining({ role: 'user', content: '你好' })
       ]
     })
+    expect(JSON.parse(init?.body as string)).not.toHaveProperty(
+      'max_output_tokens'
+    )
     expect(events).toContainEqual(
       expect.objectContaining({
         type: 'reasoning',
@@ -4418,8 +4420,9 @@ describe('ModelAgentRuntime', () => {
     expect(fetcher).toHaveBeenCalledOnce()
   })
 
-  it('terminates repeated identical tool rounds without exhausting hard limits', async () => {
+  it('allows repeated tool rounds until the run is cancelled', async () => {
     let callId = 0
+    const controller = new AbortController()
     const fetcher = vi.fn<typeof fetch>(async () => {
       callId += 1
       return Response.json({
@@ -4443,7 +4446,16 @@ describe('ModelAgentRuntime', () => {
         ]
       })
     })
-    const toolProvider = createToolProvider()
+    let completedCalls = 0
+    const toolProvider = createToolProvider({
+      callTool: vi.fn(async () => {
+        completedCalls += 1
+        if (completedCalls === 5) {
+          controller.abort()
+        }
+        return createTextToolResult('same result')
+      })
+    })
     const runtime = new ModelAgentRuntime({
       baseUrl: 'http://127.0.0.1:11434/v1',
       model: 'qwen3',
@@ -4460,16 +4472,149 @@ describe('ModelAgentRuntime', () => {
           prompt: 'repeat',
           workMode: 'execute'
         },
-        new AbortController().signal,
+        controller.signal,
         async () => 'once'
       )) {
         void _event
       }
     }
 
-    await expect(consume()).rejects.toThrow('没有取得进展')
-    expect(fetcher).toHaveBeenCalledTimes(3)
-    expect(toolProvider.callTool).toHaveBeenCalledTimes(2)
+    await expect(consume()).rejects.toThrow()
+    expect(fetcher).toHaveBeenCalledTimes(5)
+    expect(toolProvider.callTool).toHaveBeenCalledTimes(5)
+  })
+
+  it('allows more than the legacy 40 tool calls in one model round', async () => {
+    const toolCalls = Array.from({ length: 45 }, (_, index) => ({
+      id: `call-bulk-${index}`,
+      type: 'function',
+      function: {
+        name: 'workspace_read_text',
+        arguments: JSON.stringify({ path: `file-${index}.txt` })
+      }
+    }))
+    const fetcher = vi
+      .fn<typeof fetch>()
+      .mockResolvedValueOnce(
+        Response.json({
+          choices: [
+            {
+              message: {
+                role: 'assistant',
+                content: null,
+                tool_calls: toolCalls
+              }
+            }
+          ]
+        })
+      )
+      .mockResolvedValueOnce(
+        Response.json({
+          choices: [
+            {
+              message: {
+                role: 'assistant',
+                content: 'all tools completed'
+              }
+            }
+          ]
+        })
+      )
+    const toolProvider = createToolProvider()
+    const runtime = new ModelAgentRuntime({
+      baseUrl: 'http://127.0.0.1:11434/v1',
+      model: 'qwen3',
+      protocol: 'openai-chat-completions',
+      authentication: 'none',
+      fetcher,
+      toolProvider
+    })
+    const events = []
+
+    for await (const event of runtime.run(
+      {
+        requestId: crypto.randomUUID(),
+        conversationId: 'conversation-bulk-tools',
+        prompt: 'run all tools',
+        workMode: 'execute'
+      },
+      new AbortController().signal,
+      async () => 'once'
+    )) {
+      events.push(event)
+    }
+
+    expect(toolProvider.callTool).toHaveBeenCalledTimes(45)
+    expect(fetcher).toHaveBeenCalledTimes(2)
+    expect(events.at(-1)).toMatchObject({ type: 'done' })
+  })
+
+  it('continues beyond the legacy 24 model tool rounds', async () => {
+    let modelRound = 0
+    const fetcher = vi.fn<typeof fetch>(async () => {
+      modelRound += 1
+      if (modelRound <= 25) {
+        return Response.json({
+          choices: [
+            {
+              message: {
+                role: 'assistant',
+                content: null,
+                tool_calls: [
+                  {
+                    id: `call-round-${modelRound}`,
+                    type: 'function',
+                    function: {
+                      name: 'workspace_read_text',
+                      arguments: JSON.stringify({
+                        path: `round-${modelRound}.txt`
+                      })
+                    }
+                  }
+                ]
+              }
+            }
+          ]
+        })
+      }
+      return Response.json({
+        choices: [
+          {
+            message: {
+              role: 'assistant',
+              content: 'completed after 25 rounds'
+            }
+          }
+        ]
+      })
+    })
+    const toolProvider = createToolProvider()
+    const runtime = new ModelAgentRuntime({
+      baseUrl: 'http://127.0.0.1:11434/v1',
+      model: 'qwen3',
+      protocol: 'openai-chat-completions',
+      authentication: 'none',
+      fetcher,
+      toolProvider
+    })
+    const events = []
+
+    for await (const event of runtime.run(
+      {
+        requestId: crypto.randomUUID(),
+        conversationId: 'conversation-many-rounds',
+        prompt: 'continue until done',
+        workMode: 'execute'
+      },
+      new AbortController().signal,
+      async () => 'once'
+    )) {
+      events.push(event)
+    }
+
+    expect(toolProvider.callTool).toHaveBeenCalledTimes(25)
+    expect(fetcher).toHaveBeenCalledTimes(26)
+    expect(events.at(-1)).toMatchObject({ type: 'done' })
   })
 
   it('releases provider state for only the requested conversation', async () => {