Session.Info = {
  id: SessionID,           // 唯一标识
  slug: string,            // URL 友好 slug
  projectID: ProjectID,     // 所属项目
  directory: string,       // 工作目录
  parentID?: SessionID,     // 父会话（Task 子 Agent 时使用）
  title: string,           // 会话标题
  summary?: {
    additions: number,
    deletions: number,
    files: string[],
    diffs: string,
  },
  share?: { url: string },  // 分享链接
  time: {
    created: number,
    updated: number,
    compacting?: number,   // 上次压缩时间
    archived?: number,     // 归档时间
  }
}

type MessageV2 = {
  id: MessageID
  sessionID: SessionID
  role: "user" | "assistant"
  parts: (
    | TextPart       // 文本内容
    | ToolPart       // 工具调用
    | ReasoningPart  // 思考过程
    | PatchPart      // 文件变更快照
    | FilePart       // 文件引用
  )[]
  time: { created: number; updated: number }
}

type TextPart = {
  type: "text"
  text: string
}

type ToolPart = {
  type: "tool_use" | "tool_result"
  id: string
  tool: string
  state: {
    status: "running" | "completed" | "error"
    input?: unknown
    output?: string
    metadata?: Record<string, unknown>
    title?: string
    time: { start: number; end?: number }
    attachments?: FilePart[]
  }
}

type ReasoningPart = {
  type: "reasoning"
  id: string
  text: string
}

type PatchPart = {
  type: "patch"
  hash: string
  files: string[]  // 变更的文件列表
}

// packages/opencode/src/session/system.ts
export function provider(model: Provider.Model) {
  if (model.api.id.includes("gpt-4") || model.api.id.includes("o1") || model.api.id.includes("o3"))
    return [PROMPT_BEAST]
  if (model.api.id.includes("gpt")) {
    if (model.api.id.includes("codex")) return [PROMPT_CODEX]
    return [PROMPT_GPT]
  }
  if (model.api.id.includes("gemini-")) return [PROMPT_GEMINI]
  if (model.api.id.includes("claude")) return [PROMPT_ANTHROPIC]
  if (model.api.id.toLowerCase().includes("trinity")) return [PROMPT_TRINITY]
  if (model.api.id.toLowerCase().includes("kimi")) return [PROMPT_KIMI]
  return [PROMPT_DEFAULT]
}

// packages/opencode/src/session/llm.ts (lines 1-127)
export async function stream(input: StreamRequest) {
  // 1. 获取语言模型和配置
  const [language, cfg, provider, auth] = await Promise.all([
    Provider.getLanguage(input.model),
    Config.get(),
    Provider.getProvider(input.model.providerID),
    Auth.get(input.model.providerID),
  ])

  // 2. 构建系统提示（三层合并）
  const system: string[] = []
  system.push([
    ...(input.agent.prompt ? [input.agent.prompt] : SystemPrompt.provider(input.model)),
    ...input.system,
    ...(input.user.system ? [input.user.system] : []),
  ].filter(x => x).join("\n"))

  // 3. 插件钩子：允许插件转换系统提示
  await Plugin.trigger("experimental.chat.system.transform", { model: input.model }, { system })

  // 4. 解析工具（基于权限）
  const tools = await resolveTools(input)

  // 5. 转换消息格式
  const messages = isWorkflow
    ? input.messages
    : [
        ...system.map((x): ModelMessage => ({ role: "system", content: x })),
        ...input.messages,
      ]

  // 6. 调用 AI SDK
  return streamText({
    model: wrapLanguageModel({ ... }),
    activeTools: Object.keys(tools).filter((x) => x !== "invalid"),
    tools,
    maxOutputTokens,
    abortSignal: input.abort,
    messages,
    temperature: params.temperature,
    topP: params.topP,
    maxRetries: input.retries ?? 0,
  })
}

// packages/opencode/src/session/llm.ts
async experimental_repairToolCall(failed: { toolCall: ToolCall; reason: string }) {
  // 当工具调用参数不符合 schema 时，自动修复
  // 利用 AI 生成正确的参数
}

function isOverflow({ cfg, tokens, model }): boolean {
  const maxTokens = cfg.provider?.[model.providerID]?.maxTokens ?? DEFAULT_MAX_TOKENS
  return tokens.total > maxTokens * OVERFLOW_RATIO
}

// packages/opencode/src/session/compaction.ts
async function compact(sessionID: SessionID): Promise<void> {
  // 1. 获取旧消息
  const messages = yield* Session.messages(sessionID)

  // 2. 使用 compaction agent 生成摘要
  const summary = yield* Agent.generate({
    description: "Summarize conversation for context compaction",
  })

  // 3. 将摘要注入为 system prompt
  // 4. 删除旧消息
  // 5. 更新 compacting 时间戳
}

// packages/opencode/src/agent/prompt/compaction.txt
"You are a helpful AI assistant tasked with summarizing conversations."

Focus on:
- What was accomplished
- Current work in progress
- Files being modified
- Next steps
- User constraints and technical decisions to persist

// packages/opencode/src/session/retry.ts
export const policy = (options?: RetryOptions) =>
  Schedule.exponential(options?.delay ?? "100 millis", 2).pipe(
    Schedule.intersect(Schedule.elapsed()),
    Schedule.whileInput((cause) =>
      Cause.isFailure(cause) && isRetryable(cause) && options?.count < 3
    ),
  )