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feat(agent-runner): integrate AgentRunner Protocol v1 with plugin system
Phase 0 integration complete - verified minimal loop with local-agent stub runner. Changes: - Add AgentRunOrchestrator for plugin-based agent execution - Add AgentResultNormalizer for Protocol v1 result conversion - Add AgentRunnerDescriptor for runner ID parsing (plugin:author/name/runner) - Update chat handler to use new orchestrator instead of direct runner lookup - Add plugin handler methods for list_agent_runners and run_agent - Add connector methods for AgentRunner protocol forwarding - Update pipeline API to include runner options in metadata - Add integration docs and implementation plan Integration verified: - Runner: plugin:langbot/local-agent/default - Input: "你好" - Output: [stub] Echo: 你好 - Date: 2026-05-10 10:09 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
huanghuoguoguo
370
docs/agent-runner-pluginization/IMPLEMENTATION_PLAN.md
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docs/agent-runner-pluginization/IMPLEMENTATION_PLAN.md
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# Agent Runner 插件化最终实现计划
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本文档面向实现 agent，用来把当前 PoC 分支直接推进到最终架构。这个分支不按线上渐进发布节奏处理，因此可以接受一次性破坏内部 runner 实现和 Pipeline AI 配置结构；但最终必须提供历史配置迁移。
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## 1. 最终状态
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LangBot 最终只保留 Agent Runner 的宿主能力：
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- 发现 runner：`AgentRunnerRegistry`
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- 选择 runner：Pipeline 配置和未来事件绑定配置
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- 构造上下文：`AgentRunContext`
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- 裁剪资源：模型、工具、知识库、文件、存储、平台能力
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- 调度执行：`AgentRunOrchestrator`
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- 归一结果：`AgentRunResult` -> 当前 Pipeline 的 `Message` / `MessageChunk`
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- 隔离错误：插件异常、协议错误、超时、结果过大不能破坏主流程
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- 迁移旧配置：把旧内置 runner 配置迁到官方 AgentRunner 插件配置
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LangBot 不再长期维护内置业务 runner 分支。`local-agent`、Dify、n8n、Coze、DashScope、Langflow、Tbox 等都迁到官方 AgentRunner 插件。
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## 2. 高层架构
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```text
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Pipeline MessageProcessor / future EventRouter
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v
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AgentRunOrchestrator
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|
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+--> AgentRunnerRegistry
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| +--> plugin runtime LIST_AGENT_RUNNERS
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| +--> descriptor cache / validation
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|
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+--> AgentRunContextBuilder
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+--> AgentResourceBuilder
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+--> AgentResultNormalizer
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|
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v
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PluginRuntimeConnector.run_agent()
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|
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v
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SDK Runtime RUN_AGENT -> plugin AgentRunner.run()
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```
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关键约束：
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- `ChatMessageHandler` 不解析 `plugin:*`，不实例化 wrapper，不知道 runner 组件细节。
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- `PipelineService.get_pipeline_metadata()` 不直接访问插件 runtime，而是读取 registry。
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- 旧 `RequestRunner` 只作为迁移参考，不作为最终运行路径。
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- EBA 只做字段预留，不在本轮实现 EventBus、EventRouter、平台动作执行。
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## 3. 新增 LangBot 模块
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建议新增：
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```text
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src/langbot/pkg/agent/
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__init__.py
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runner/
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__init__.py
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descriptor.py
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errors.py
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id.py
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registry.py
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context_builder.py
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resource_builder.py
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orchestrator.py
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result_normalizer.py
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config_migration.py
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```
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### 3.1 descriptor.py
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定义 LangBot 内部使用的 descriptor：
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```python
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class AgentRunnerDescriptor(BaseModel):
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id: str
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source: Literal["plugin"]
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label: dict[str, str]
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description: dict[str, str] | None = None
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plugin_author: str
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plugin_name: str
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runner_name: str
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plugin_version: str | None = None
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protocol_version: str = "1"
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config_schema: list[dict[str, Any]] = []
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capabilities: dict[str, bool] = {}
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permissions: dict[str, list[str]] = {}
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raw_manifest: dict[str, Any] = {}
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```
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`source == "builtin"` 不作为最终目标。如果实现阶段需要临时 adapter，必须标记为测试过渡代码，并在官方插件跑通后删除。
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### 3.2 id.py
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统一 runner id 解析和生成：
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- 插件 runner id：`plugin:{author}/{plugin_name}/{runner_name}`
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- `parse_runner_id(id)` 返回结构化对象
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- 禁止业务代码手写字符串 split
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- PoC 已存在的 `plugin:author/name/runner` 继续作为合法 id
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### 3.3 registry.py
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职责：
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- 调用 `ap.plugin_connector.list_agent_runners(bound_plugins=None)` 拉取插件 runner
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- 校验 manifest：
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- `kind == AgentRunner`
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- `metadata.name` 存在
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- `metadata.label` 存在
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- `spec.protocol_version` 兼容，默认 `1`
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- `spec.config` 是 list，默认空
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- `spec.capabilities` 是 dict，默认空
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- `spec.permissions` 是 dict，默认空
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- 输出 `AgentRunnerDescriptor`
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- 缓存 discovery 结果，提供 `refresh()`
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- 单个插件 manifest 失败只记录 warning，不影响其它 runner
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刷新触发点：
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- 插件安装、卸载、升级、重启后
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- Pipeline metadata 请求时发现缓存为空
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- 可选 TTL，优先保证正确性
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### 3.4 context_builder.py
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把当前 Pipeline query 直接转换成 SDK v1 `AgentRunContext`。
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当前消息 Pipeline 的最小字段：
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- `run_id`: 新 UUID，不使用 query id 作为全局 run id
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- `trigger.type`: `message.received`
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- `conversation`: launcher、sender、bot、pipeline、历史消息
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- `event`: message event envelope 子集
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- `actor`: sender
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- `subject`: 当前消息或 launcher
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- `messages`: `query.messages`
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- `input`: 从 `query.user_message` 和 `query.message_chain` 构造
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- `resources`: 由 `resource_builder` 注入
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- `runtime`: host/version/workspace/bot/pipeline/query/trace/deadline
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- `config`: 当前 runner id 对应的实例配置
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保留 SDK legacy helper 是 SDK 的责任，LangBot 不再构造 PoC 的 `query_id/session/messages/user_message/extra_config` 上下文。
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### 3.5 resource_builder.py
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执行前做三层裁剪：
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1. runner manifest 声明的 `spec.permissions`
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2. Pipeline 的 `extensions_preferences`
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3. runner 实例配置中选择的资源范围
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输出写入 `ctx.resources`，至少覆盖：
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- models：可调用模型 UUID、类型、能力摘要
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- tools：可见工具 manifest，使用当前 bound plugins / MCP server 范围
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- knowledge_bases：可检索知识库列表
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- storage：plugin storage / workspace storage 权限摘要
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- files：允许读取的配置文件、知识文件摘要
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- platform_capabilities：本阶段只声明，不执行平台动作
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注意：旧的 unrestricted proxy action 必须在 Phase 2 被二次校验，不能只靠 context 声明。
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### 3.6 result_normalizer.py
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只接受 SDK v1 result：
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- `message.delta`
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- `message.completed`
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- `tool.call.started`
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- `tool.call.completed`
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- `state.updated`
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- `run.completed`
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- `run.failed`
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- `action.requested` 允许实验性返回，但本阶段只记录 telemetry，不执行
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映射：
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- `message.delta.data.chunk` -> `provider_message.MessageChunk`
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- `message.completed.data.message` -> `provider_message.Message`
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- `run.completed.data.message` -> `provider_message.Message`
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- `run.failed` -> 抛出受控异常，让 `ChatMessageHandler` 使用现有错误策略
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- 工具和状态事件默认不 yield 到 Pipeline，只记录 debug/telemetry
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防护：
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- 未知 type warning 后忽略
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- 单 result 序列化大小限制
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- provider message schema 校验失败转 `run.failed`
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- 插件没有输出任何消息时，按 runner failed 处理
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### 3.7 orchestrator.py
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核心入口：
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```python
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async def run_from_query(query: pipeline_query.Query) -> AsyncGenerator[Message | MessageChunk, None]:
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runner_id = resolve_runner_id(query.pipeline_config)
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descriptor = await registry.get(runner_id, bound_plugins=query.variables.get("_pipeline_bound_plugins"))
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ctx = await context_builder.from_query(query, descriptor)
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async for raw in plugin_connector.run_agent(...):
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async for message in result_normalizer.normalize(raw):
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yield message
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```
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必须覆盖：
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- runner id 不存在
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- 插件系统关闭
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- runner 不在 bound plugins 范围内
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- 插件 runtime 断连
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- runner 协议版本不兼容
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- run 超时
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- task cancellation
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## 4. 配置模型直接切换
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目标格式：
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```json
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{
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"ai": {
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"runner": {
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"id": "plugin:langbot/local-agent/default",
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"expire-time": 0
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},
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"runner_config": {
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"plugin:langbot/local-agent/default": {}
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}
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}
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}
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```
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兼容读取：
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- 优先读 `ai.runner.id`
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- 没有 `id` 时读旧 `ai.runner.runner`
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- 旧内置 runner 名通过迁移表映射：
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- `local-agent` -> `plugin:langbot/local-agent/default`
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- `dify-service-api` -> `plugin:langbot/dify-agent/default`
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- `n8n-service-api` -> `plugin:langbot/n8n-agent/default`
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- `coze-api` -> `plugin:langbot/coze-agent/default`
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- `dashscope-app-api` -> `plugin:langbot/dashscope-agent/default`
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- `langflow-api` -> `plugin:langbot/langflow-agent/default`
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- `tbox-app-api` -> `plugin:langbot/tbox-agent/default`
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写入策略：
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- 新 UI 只写 `ai.runner.id` 和 `ai.runner_config`
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- 后端 update 接口接受旧字段，但保存时归一成新格式
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- migration 最后统一落库
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## 5. 需要修改的 LangBot 范围
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必须修改：
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- `src/langbot/pkg/core/app.py`
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- 增加 `agent_runner_registry` / `agent_run_orchestrator` 属性
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- `src/langbot/pkg/core/stages/build_app.py`
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- 初始化 Agent 子系统
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- `src/langbot/pkg/pipeline/process/handlers/chat.py`
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- 删除 `PluginAgentRunnerWrapper`
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- 删除内置 runner 查找逻辑
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- 调用 orchestrator
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- `src/langbot/pkg/api/http/service/pipeline.py`
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- metadata 从 registry 生成
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- `src/langbot/pkg/plugin/connector.py`
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- `list_agent_runners()` / `run_agent()` 增加协议校验和 bound plugin 参数
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- `src/langbot/pkg/plugin/handler.py`
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- proxy action 二次权限校验
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- `src/langbot/pkg/pipeline/preproc/preproc.py`
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- 不再只为 `local-agent` 构造工具、知识库、模型
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- 对所有 agent runner 保留 multimodal input
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- `src/langbot/pkg/pipeline/pipelinemgr.py`
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- runner name 监控改读 `runner.id`
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- `src/langbot/templates/metadata/pipeline/ai.yaml`
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- runner 字段从 `runner` 迁到 `id`
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- `src/langbot/templates/default-pipeline-config.json`
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- 默认 runner 改为官方 local-agent 插件 id
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- `web/src/app/home/pipelines/components/pipeline-form/PipelineFormComponent.tsx`
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- 当前 runner 改读 `ai.runner.id`
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- runner 配置区改写入 `ai.runner_config[id]`
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最终删除或停用：
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|
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- `src/langbot/pkg/provider/runner.py` 的业务注册路径
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- `src/langbot/pkg/provider/runners/*` 的运行入口
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可以暂时保留文件作为官方插件迁移参考，但不应被运行时引用。
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## 6. 实现顺序
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### Step 1：接入新版 SDK
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- 更新 LangBot 依赖到包含 SDK v1 AgentRunner 协议的版本
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- 删除 LangBot 中对旧 `AgentRunReturn` 类型名的依赖
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- 确认 `langbot_plugin` 的本地 editable / lockfile 指向正确 SDK
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|
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### Step 2：Agent 子系统骨架
|
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|
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- 新增 descriptor/id/errors
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- 新增 registry，先只 list plugin runner
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- 为 registry 加单测，使用 fake connector
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### Step 3：Pipeline metadata 切 registry
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|
||||
- `get_pipeline_metadata()` 只通过 registry 输出 runner option
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||||
- 插件 runner config stage 从 descriptor.config_schema 生成
|
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- schema 错误不影响 metadata 返回
|
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|
||||
### Step 4：Orchestrator 替换 ChatMessageHandler
|
||||
|
||||
- 新增 context builder / result normalizer / orchestrator
|
||||
- `chat.py` 删除 wrapper 和 runner 查找
|
||||
- 维持现有流式卡片和 resp_messages 行为
|
||||
|
||||
### Step 5：新配置读写
|
||||
|
||||
- 后端 resolve runner id 支持新旧配置
|
||||
- 前端表单改 `runner.id` + `runner_config`
|
||||
- 默认配置改官方 local-agent 插件 id
|
||||
|
||||
### Step 6：权限和资源裁剪
|
||||
|
||||
- resource builder 根据 manifest / pipeline / instance config 裁剪
|
||||
- proxy action 校验 resource scope
|
||||
- 禁止插件用 unrestricted API 访问未授权知识库、工具、模型
|
||||
|
||||
### Step 7：删除内置 runner 运行分支
|
||||
|
||||
- 官方插件 ready 后移除内置 runner registry
|
||||
- 删除或隔离 provider runners 的运行引用
|
||||
- 测试旧 runner 名只能通过 migration 映射到插件 id
|
||||
|
||||
### Step 8：历史配置迁移
|
||||
|
||||
- 写 persistence migration
|
||||
- 更新 default pipeline config
|
||||
- 对已存在 Pipeline 执行旧字段到新字段迁移
|
||||
- 对监控/日志里的 runner 字段改用新 id
|
||||
|
||||
## 7. 测试要求
|
||||
|
||||
单测：
|
||||
|
||||
- runner id parse / format
|
||||
- registry manifest 校验、失败隔离、bound plugins 过滤
|
||||
- context builder 从 query 生成完整 v1 context
|
||||
- resource builder 三层裁剪
|
||||
- result normalizer 对每种 result type 的映射
|
||||
- 旧配置 resolve 和 migration
|
||||
|
||||
集成测试：
|
||||
|
||||
- fake AgentRunner 插件可被 Pipeline 选择
|
||||
- streaming 输出仍能更新 message card
|
||||
- 插件异常返回用户可理解错误，不中断 runtime
|
||||
- runner 不在 bound plugins 时不可执行
|
||||
- 未授权工具 / 知识库 / 模型 proxy 调用被拒绝
|
||||
- 旧 `local-agent` Pipeline 配置迁到官方插件 id
|
||||
|
||||
## 8. 验收标准
|
||||
|
||||
- LangBot Pipeline 可以选择插件 AgentRunner 并完成非流式和流式回复。
|
||||
- `ChatMessageHandler` 不包含插件 runner 解析和 wrapper。
|
||||
- `PipelineService` 不直接拼插件 runner metadata。
|
||||
- 所有 runner 配置使用 `ai.runner.id` + `ai.runner_config`。
|
||||
- 旧内置 runner 不再作为 LangBot 内部运行分支执行。
|
||||
- 插件只能访问 `ctx.resources` 授权的模型、工具、知识库和文件。
|
||||
- EBA 相关字段只作为 context/result 预留，不执行平台动作。
|
||||
192
docs/agent-runner-pluginization/OFFICIAL_RUNNER_PLUGINS.md
Normal file
192
docs/agent-runner-pluginization/OFFICIAL_RUNNER_PLUGINS.md
Normal file
@@ -0,0 +1,192 @@
|
||||
# 官方 AgentRunner 插件仓库计划
|
||||
|
||||
本文档描述内置 `RequestRunner` 迁出 LangBot 后，官方 runner 插件仓库应如何组织。建议新建仓库：
|
||||
|
||||
```text
|
||||
/home/glwuy/langbot-app/langbot-official-agent-runners
|
||||
```
|
||||
|
||||
远端仓库名建议：`langbot-official-agent-runners`。
|
||||
|
||||
## 1. 为什么新仓库
|
||||
|
||||
官方 runner 插件会和 LangBot 主仓库、SDK 仓库以不同节奏迭代：
|
||||
|
||||
- LangBot 主仓库只维护宿主协议和调度。
|
||||
- SDK 仓库维护 AgentRunner 组件和 runtime 协议。
|
||||
- 官方 runner 插件承载业务 runner 的具体实现和第三方平台适配。
|
||||
|
||||
不要把官方 runner 插件继续留在 LangBot 主仓库，否则容易重新形成“宿主和业务 runner 绑死”的结构。
|
||||
|
||||
## 2. 仓库结构
|
||||
|
||||
建议采用 monorepo：
|
||||
|
||||
```text
|
||||
langbot-official-agent-runners/
|
||||
README.md
|
||||
pyproject.toml
|
||||
packages/
|
||||
local-agent/
|
||||
manifest.yaml
|
||||
components/default.yaml
|
||||
main.py
|
||||
src/
|
||||
tests/
|
||||
dify-agent/
|
||||
n8n-agent/
|
||||
coze-agent/
|
||||
dashscope-agent/
|
||||
langflow-agent/
|
||||
tbox-agent/
|
||||
shared/
|
||||
langbot_agent_runner_utils/
|
||||
__init__.py
|
||||
context.py
|
||||
config.py
|
||||
streaming.py
|
||||
tool_calling.py
|
||||
errors.py
|
||||
tests/
|
||||
fixtures/
|
||||
integration/
|
||||
```
|
||||
|
||||
先用一个仓库统一迁移，避免每个 runner 复制 SDK helper、测试夹具、发布脚本。
|
||||
|
||||
## 3. 插件命名和 runner id
|
||||
|
||||
固定映射：
|
||||
|
||||
| 旧 runner | 官方插件 | runner id |
|
||||
| --- | --- | --- |
|
||||
| `local-agent` | `langbot/local-agent` | `plugin:langbot/local-agent/default` |
|
||||
| `dify-service-api` | `langbot/dify-agent` | `plugin:langbot/dify-agent/default` |
|
||||
| `n8n-service-api` | `langbot/n8n-agent` | `plugin:langbot/n8n-agent/default` |
|
||||
| `coze-api` | `langbot/coze-agent` | `plugin:langbot/coze-agent/default` |
|
||||
| `dashscope-app-api` | `langbot/dashscope-agent` | `plugin:langbot/dashscope-agent/default` |
|
||||
| `langflow-api` | `langbot/langflow-agent` | `plugin:langbot/langflow-agent/default` |
|
||||
| `tbox-app-api` | `langbot/tbox-agent` | `plugin:langbot/tbox-agent/default` |
|
||||
|
||||
每个插件可以后续提供多个 runner，但迁移目标的默认 runner 统一叫 `default`。
|
||||
|
||||
## 4. 迁移优先级
|
||||
|
||||
### Batch 1：打通协议
|
||||
|
||||
1. `local-agent`
|
||||
2. `dify-agent`
|
||||
|
||||
原因：
|
||||
|
||||
- `local-agent` 覆盖模型、工具、知识库、流式、会话历史，是能力最完整的基准。
|
||||
- `dify-agent` 代表外部 Agent 平台调用，配置和错误处理能验证传统 service API runner 的迁移方式。
|
||||
|
||||
### Batch 2：迁移外部 workflow runner
|
||||
|
||||
1. `n8n-agent`
|
||||
2. `langflow-agent`
|
||||
|
||||
这批主要验证 webhook/workflow 输入输出、timeout、外部 conversation id。
|
||||
|
||||
### Batch 3：迁移平台 Agent API
|
||||
|
||||
1. `coze-agent`
|
||||
2. `dashscope-agent`
|
||||
3. `tbox-agent`
|
||||
|
||||
这批主要验证平台特有响应格式、引用资料、文件/图片输入。
|
||||
|
||||
## 5. 每个官方插件的组件要求
|
||||
|
||||
每个插件至少包含：
|
||||
|
||||
```yaml
|
||||
apiVersion: langbot/v1
|
||||
kind: AgentRunner
|
||||
metadata:
|
||||
name: default
|
||||
label:
|
||||
en_US: Dify Agent
|
||||
zh_Hans: Dify Agent
|
||||
description:
|
||||
en_US: Run a Dify application as a LangBot AgentRunner.
|
||||
zh_Hans: 将 Dify 应用作为 LangBot AgentRunner 运行。
|
||||
spec:
|
||||
protocol_version: "1"
|
||||
config: []
|
||||
capabilities:
|
||||
streaming: true
|
||||
tool_calling: false
|
||||
knowledge_retrieval: false
|
||||
multimodal_input: false
|
||||
event_context: true
|
||||
platform_api: false
|
||||
interrupt: false
|
||||
stateful_session: true
|
||||
permissions:
|
||||
models: []
|
||||
tools: []
|
||||
knowledge_bases: []
|
||||
storage: ["plugin"]
|
||||
files: []
|
||||
platform_api: []
|
||||
execution:
|
||||
python:
|
||||
path: ./main.py
|
||||
attr: DefaultAgentRunner
|
||||
```
|
||||
|
||||
## 6. local-agent 插件要求
|
||||
|
||||
`local-agent` 是最关键的官方插件，应等价迁移当前：
|
||||
|
||||
- model primary/fallback 选择
|
||||
- prompt
|
||||
- max-round
|
||||
- knowledge-bases
|
||||
- rerank-model
|
||||
- rerank-top-k
|
||||
- function calling
|
||||
- streaming
|
||||
- multimodal input
|
||||
- conversation history
|
||||
- monitoring metadata
|
||||
|
||||
与 LangBot 主仓库的责任边界：
|
||||
|
||||
- LangBot 构造 `ctx.messages`、`ctx.input`、`ctx.resources`
|
||||
- 插件负责选择模型、拼请求、调用 LLM、处理 tool call loop、输出 result stream
|
||||
- 插件不能绕过 `ctx.resources` 调用未授权模型、工具或知识库
|
||||
|
||||
## 7. 外部 runner 插件要求
|
||||
|
||||
外部平台 runner 迁移时遵循：
|
||||
|
||||
- 旧配置字段尽量保持同名，便于 migration 复制
|
||||
- 输出统一转换为 `AgentRunResult`
|
||||
- 外部 API timeout 从 runner config 读取
|
||||
- 平台 conversation id 存 plugin storage 或 context runtime state，不能依赖 LangBot 内置 conversation uuid 私有结构
|
||||
- 流式支持按平台能力声明，没有流式就只发 `message.completed`
|
||||
|
||||
## 8. 发布和安装策略
|
||||
|
||||
最终 LangBot 安装或升级时需要保证官方 runner 插件可用。可选方案：
|
||||
|
||||
1. 首次启动检测缺失官方 runner 插件并提示安装。
|
||||
2. 打包发行版时预装官方 runner 插件。
|
||||
3. 在 migration 前检查对应插件是否存在，不存在则自动安装或阻止迁移。
|
||||
|
||||
建议实现顺序：
|
||||
|
||||
- 开发阶段使用本地路径插件。
|
||||
- 发布前支持 marketplace 安装。
|
||||
- 历史配置 migration 只在官方插件可用时执行。
|
||||
|
||||
## 9. 验收标准
|
||||
|
||||
- 每个旧 runner 都有对应官方 AgentRunner 插件。
|
||||
- 旧 runner 配置能无损复制到新 `runner_config[id]`。
|
||||
- LangBot 主仓库不再通过 `RequestRunner` 执行业务 runner。
|
||||
- 官方插件测试覆盖非流式、流式、错误、timeout、配置缺失。
|
||||
- `local-agent` 插件能完成模型 fallback、tool calling、知识库检索。
|
||||
63
docs/agent-runner-pluginization/PHASE0_INTEGRATION_RECORD.md
Normal file
63
docs/agent-runner-pluginization/PHASE0_INTEGRATION_RECORD.md
Normal file
@@ -0,0 +1,63 @@
|
||||
# Agent Runner Pluginization Phase 0 Integration Test Record
|
||||
|
||||
## Test Summary
|
||||
|
||||
**Status**: PASSED
|
||||
|
||||
**Date**: 2026-05-10 10:09
|
||||
|
||||
## Test Configuration
|
||||
|
||||
- **LangBot Branch**: feat/agent-runner-plugin
|
||||
- **SDK Branch**: feat/agent-runner-plugin
|
||||
- **Runner Repo**: langbot-agent-runner (new)
|
||||
|
||||
## Test Scenario
|
||||
|
||||
- **Selected Runner**: `plugin:langbot/local-agent/default`
|
||||
- **Input**: `1`
|
||||
- **Expected Output**: `[stub] Echo: 1`
|
||||
- **Actual Output**: `[stub] Echo: 1`
|
||||
|
||||
## Verified Chain
|
||||
|
||||
```
|
||||
Frontend selects plugin:langbot/local-agent/default
|
||||
-> LangBot pipeline
|
||||
-> AgentRunOrchestrator
|
||||
-> SDK runtime RUN_AGENT
|
||||
-> langbot-agent-runner/local-agent DefaultAgentRunner
|
||||
-> AgentRunResult
|
||||
-> LangBot response
|
||||
```
|
||||
|
||||
## Key Components Verified
|
||||
|
||||
### LangBot Host
|
||||
- AgentRunOrchestrator resolves runner ID via ConfigMigration
|
||||
- AgentRunContextBuilder builds SDK v1 context
|
||||
- AgentResultNormalizer normalizes SDK v1 results
|
||||
- ChatMessageHandler delegates to orchestrator (single resp_message_id, streaming pop/append)
|
||||
|
||||
### SDK Runtime
|
||||
- RUN_AGENT action dispatches to plugin runner
|
||||
- AgentRunner component manifest parsing
|
||||
- LIST_AGENT_RUNNERS returns runner metadata
|
||||
|
||||
### langbot-agent-runner Plugin
|
||||
- DefaultAgentRunner stub implementation
|
||||
- AgentRunner manifest with protocol_version, capabilities, permissions
|
||||
- Echo response validates SDK v1 result format
|
||||
|
||||
## Next Steps (Phase 1)
|
||||
|
||||
1. Implement real Dify runner (external API runner validation)
|
||||
2. Update frontend to save `ai.runner.id` + `ai.runner_config`
|
||||
3. Add persistence migration for old config format
|
||||
4. Update pipeline templates
|
||||
5. Add proxy action secondary permission validation
|
||||
|
||||
## Related Documents
|
||||
|
||||
- [IMPLEMENTATION_PLAN.md](./IMPLEMENTATION_PLAN.md)
|
||||
- [OFFICIAL_RUNNER_PLUGINS.md](./OFFICIAL_RUNNER_PLUGINS.md)
|
||||
@@ -105,6 +105,9 @@ classifiers = [
|
||||
"Topic :: Communications :: Chat",
|
||||
]
|
||||
|
||||
[tool.uv.sources]
|
||||
langbot-plugin = { path = "../langbot-plugin-sdk", editable = true }
|
||||
|
||||
[project.urls]
|
||||
Homepage = "https://langbot.app"
|
||||
Documentation = "https://docs.langbot.app"
|
||||
@@ -223,4 +226,3 @@ skip-magic-trailing-comma = false
|
||||
|
||||
# Like Black, automatically detect the appropriate line ending.
|
||||
line-ending = "auto"
|
||||
|
||||
|
||||
37
src/langbot/pkg/agent/__init__.py
Normal file
37
src/langbot/pkg/agent/__init__.py
Normal file
@@ -0,0 +1,37 @@
|
||||
"""Agent runner subsystem for LangBot."""
|
||||
from __future__ import annotations
|
||||
|
||||
from .runner.descriptor import AgentRunnerDescriptor
|
||||
from .runner.id import parse_runner_id, format_runner_id, RunnerIdParts, is_plugin_runner_id
|
||||
from .runner.errors import (
|
||||
AgentRunnerError,
|
||||
RunnerNotFoundError,
|
||||
RunnerNotAuthorizedError,
|
||||
RunnerProtocolError,
|
||||
RunnerExecutionError,
|
||||
)
|
||||
from .runner.registry import AgentRunnerRegistry
|
||||
from .runner.context_builder import AgentRunContextBuilder
|
||||
from .runner.resource_builder import AgentResourceBuilder
|
||||
from .runner.result_normalizer import AgentResultNormalizer
|
||||
from .runner.orchestrator import AgentRunOrchestrator
|
||||
from .runner.config_migration import ConfigMigration
|
||||
|
||||
__all__ = [
|
||||
'AgentRunnerDescriptor',
|
||||
'parse_runner_id',
|
||||
'format_runner_id',
|
||||
'is_plugin_runner_id',
|
||||
'RunnerIdParts',
|
||||
'AgentRunnerError',
|
||||
'RunnerNotFoundError',
|
||||
'RunnerNotAuthorizedError',
|
||||
'RunnerProtocolError',
|
||||
'RunnerExecutionError',
|
||||
'AgentRunnerRegistry',
|
||||
'AgentRunContextBuilder',
|
||||
'AgentResourceBuilder',
|
||||
'AgentResultNormalizer',
|
||||
'AgentRunOrchestrator',
|
||||
'ConfigMigration',
|
||||
]
|
||||
36
src/langbot/pkg/agent/runner/__init__.py
Normal file
36
src/langbot/pkg/agent/runner/__init__.py
Normal file
@@ -0,0 +1,36 @@
|
||||
"""Agent runner modules."""
|
||||
from __future__ import annotations
|
||||
|
||||
from .descriptor import AgentRunnerDescriptor
|
||||
from .id import parse_runner_id, format_runner_id, RunnerIdParts
|
||||
from .errors import (
|
||||
AgentRunnerError,
|
||||
RunnerNotFoundError,
|
||||
RunnerNotAuthorizedError,
|
||||
RunnerProtocolError,
|
||||
RunnerExecutionError,
|
||||
)
|
||||
from .registry import AgentRunnerRegistry
|
||||
from .context_builder import AgentRunContextBuilder
|
||||
from .resource_builder import AgentResourceBuilder
|
||||
from .result_normalizer import AgentResultNormalizer
|
||||
from .orchestrator import AgentRunOrchestrator
|
||||
from .config_migration import ConfigMigration
|
||||
|
||||
__all__ = [
|
||||
'AgentRunnerDescriptor',
|
||||
'parse_runner_id',
|
||||
'format_runner_id',
|
||||
'RunnerIdParts',
|
||||
'AgentRunnerError',
|
||||
'RunnerNotFoundError',
|
||||
'RunnerNotAuthorizedError',
|
||||
'RunnerProtocolError',
|
||||
'RunnerExecutionError',
|
||||
'AgentRunnerRegistry',
|
||||
'AgentRunContextBuilder',
|
||||
'AgentResourceBuilder',
|
||||
'AgentResultNormalizer',
|
||||
'AgentRunOrchestrator',
|
||||
'ConfigMigration',
|
||||
]
|
||||
196
src/langbot/pkg/agent/runner/config_migration.py
Normal file
196
src/langbot/pkg/agent/runner/config_migration.py
Normal file
@@ -0,0 +1,196 @@
|
||||
"""Configuration migration for agent runner IDs."""
|
||||
from __future__ import annotations
|
||||
|
||||
import typing
|
||||
|
||||
from .id import is_plugin_runner_id
|
||||
|
||||
|
||||
# Mapping from old built-in runner names to official plugin runner IDs
|
||||
OLD_RUNNER_TO_PLUGIN_RUNNER_ID = {
|
||||
'local-agent': 'plugin:langbot/local-agent/default',
|
||||
'dify-service-api': 'plugin:langbot/dify-agent/default',
|
||||
'n8n-service-api': 'plugin:langbot/n8n-agent/default',
|
||||
'coze-api': 'plugin:langbot/coze-agent/default',
|
||||
'dashscope-app-api': 'plugin:langbot/dashscope-agent/default',
|
||||
'langflow-api': 'plugin:langbot/langflow-agent/default',
|
||||
'tbox-app-api': 'plugin:langbot/tbox-agent/default',
|
||||
}
|
||||
|
||||
|
||||
class ConfigMigration:
|
||||
"""Configuration migration helper for agent runner IDs.
|
||||
|
||||
Responsibilities:
|
||||
- Resolve runner ID from new ai.runner.id or old ai.runner.runner
|
||||
- Map old built-in runner names to official plugin runner IDs
|
||||
- Extract runner config from ai.runner_config or old ai.<runner-name>
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def resolve_runner_id(pipeline_config: dict[str, typing.Any]) -> str | None:
|
||||
"""Resolve runner ID from pipeline configuration.
|
||||
|
||||
Priority:
|
||||
1. New format: ai.runner.id (must be plugin:* format)
|
||||
2. Old format: ai.runner.runner (mapped to plugin:* if built-in)
|
||||
|
||||
Args:
|
||||
pipeline_config: Pipeline configuration dict
|
||||
|
||||
Returns:
|
||||
Runner ID string, or None if not configured
|
||||
"""
|
||||
ai_config = pipeline_config.get('ai', {})
|
||||
runner_config = ai_config.get('runner', {})
|
||||
|
||||
# Check new format first
|
||||
runner_id = runner_config.get('id')
|
||||
if runner_id:
|
||||
if is_plugin_runner_id(runner_id):
|
||||
return runner_id
|
||||
# If it's not a plugin ID, try to map it as old runner name
|
||||
return OLD_RUNNER_TO_PLUGIN_RUNNER_ID.get(runner_id, runner_id)
|
||||
|
||||
# Check old format
|
||||
old_runner_name = runner_config.get('runner')
|
||||
if old_runner_name:
|
||||
# If already plugin:* format, return directly
|
||||
if is_plugin_runner_id(old_runner_name):
|
||||
return old_runner_name
|
||||
# Map old built-in runner to official plugin ID
|
||||
mapped_id = OLD_RUNNER_TO_PLUGIN_RUNNER_ID.get(old_runner_name)
|
||||
if mapped_id:
|
||||
return mapped_id
|
||||
# Return old name if no mapping exists (will error in registry)
|
||||
return old_runner_name
|
||||
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def resolve_runner_config(
|
||||
pipeline_config: dict[str, typing.Any],
|
||||
runner_id: str,
|
||||
) -> dict[str, typing.Any]:
|
||||
"""Resolve runner instance configuration from pipeline configuration.
|
||||
|
||||
Priority:
|
||||
1. New format: ai.runner_config[runner_id]
|
||||
2. Old format: ai.<runner-name> (mapped from runner_id if applicable)
|
||||
|
||||
Args:
|
||||
pipeline_config: Pipeline configuration dict
|
||||
runner_id: Resolved runner ID
|
||||
|
||||
Returns:
|
||||
Runner configuration dict (empty if not found)
|
||||
"""
|
||||
ai_config = pipeline_config.get('ai', {})
|
||||
|
||||
# Check new format
|
||||
runner_configs = ai_config.get('runner_config', {})
|
||||
if runner_id in runner_configs:
|
||||
return runner_configs[runner_id]
|
||||
|
||||
# Check old format: ai.<old_runner_name>
|
||||
# Try to find old runner name from runner_id
|
||||
old_runner_name = None
|
||||
for old_name, mapped_id in OLD_RUNNER_TO_PLUGIN_RUNNER_ID.items():
|
||||
if mapped_id == runner_id:
|
||||
old_runner_name = old_name
|
||||
break
|
||||
|
||||
if old_runner_name:
|
||||
old_config = ai_config.get(old_runner_name, {})
|
||||
if old_config:
|
||||
return old_config
|
||||
|
||||
# If runner_id is plugin:* format, try extracting runner_name as config key
|
||||
if is_plugin_runner_id(runner_id):
|
||||
# Some configs might use just the runner_name component as key
|
||||
# But this is legacy behavior - prefer ai.runner_config[id]
|
||||
pass
|
||||
|
||||
return {}
|
||||
|
||||
@staticmethod
|
||||
def get_old_runner_name(runner_id: str) -> str | None:
|
||||
"""Get old runner name from mapped runner ID.
|
||||
|
||||
Args:
|
||||
runner_id: Plugin runner ID
|
||||
|
||||
Returns:
|
||||
Old runner name if mapped, None otherwise
|
||||
"""
|
||||
for old_name, mapped_id in OLD_RUNNER_TO_PLUGIN_RUNNER_ID.items():
|
||||
if mapped_id == runner_id:
|
||||
return old_name
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def get_expire_time(pipeline_config: dict[str, typing.Any]) -> int:
|
||||
"""Get conversation expire time from configuration.
|
||||
|
||||
Args:
|
||||
pipeline_config: Pipeline configuration dict
|
||||
|
||||
Returns:
|
||||
Expire time in seconds (0 means no expiry)
|
||||
"""
|
||||
ai_config = pipeline_config.get('ai', {})
|
||||
runner_config = ai_config.get('runner', {})
|
||||
return runner_config.get('expire-time', 0)
|
||||
|
||||
@staticmethod
|
||||
def migrate_pipeline_config(pipeline_config: dict[str, typing.Any]) -> dict[str, typing.Any]:
|
||||
"""Migrate pipeline config to new format.
|
||||
|
||||
This converts old ai.runner.runner and ai.<runner-name> to
|
||||
new ai.runner.id and ai.runner_config format.
|
||||
|
||||
Args:
|
||||
pipeline_config: Original pipeline configuration
|
||||
|
||||
Returns:
|
||||
Migrated pipeline configuration
|
||||
"""
|
||||
# Create copy
|
||||
new_config = dict(pipeline_config)
|
||||
ai_config = new_config.get('ai', {})
|
||||
if not ai_config:
|
||||
return new_config
|
||||
|
||||
runner_config = ai_config.get('runner', {})
|
||||
runner_configs = ai_config.get('runner_config', {})
|
||||
|
||||
# Resolve runner ID
|
||||
runner_id = ConfigMigration.resolve_runner_id(pipeline_config)
|
||||
if runner_id:
|
||||
# Set new format
|
||||
runner_config['id'] = runner_id
|
||||
# Remove old runner field if present
|
||||
if 'runner' in runner_config and is_plugin_runner_id(runner_config['runner']):
|
||||
# Already migrated plugin:* format, keep as id
|
||||
pass
|
||||
elif 'runner' in runner_config:
|
||||
# Old built-in runner name, remove after migration
|
||||
old_name = runner_config['runner']
|
||||
if old_name in OLD_RUNNER_TO_PLUGIN_RUNNER_ID:
|
||||
del runner_config['runner']
|
||||
|
||||
# Migrate runner config
|
||||
resolved_config = ConfigMigration.resolve_runner_config(pipeline_config, runner_id)
|
||||
if resolved_config:
|
||||
runner_configs[runner_id] = resolved_config
|
||||
# Remove old runner config block
|
||||
for old_name, mapped_id in OLD_RUNNER_TO_PLUGIN_RUNNER_ID.items():
|
||||
if mapped_id == runner_id and old_name in ai_config:
|
||||
del ai_config[old_name]
|
||||
|
||||
# Update configs
|
||||
ai_config['runner'] = runner_config
|
||||
ai_config['runner_config'] = runner_configs
|
||||
new_config['ai'] = ai_config
|
||||
|
||||
return new_config
|
||||
254
src/langbot/pkg/agent/runner/context_builder.py
Normal file
254
src/langbot/pkg/agent/runner/context_builder.py
Normal file
@@ -0,0 +1,254 @@
|
||||
"""Agent run context builder for converting Query to SDK v1 AgentRunContext."""
|
||||
from __future__ import annotations
|
||||
|
||||
import uuid
|
||||
import time
|
||||
import typing
|
||||
|
||||
from langbot_plugin.api.entities.builtin.pipeline import query as pipeline_query
|
||||
|
||||
from ...core import app
|
||||
from .descriptor import AgentRunnerDescriptor
|
||||
from .config_migration import ConfigMigration
|
||||
|
||||
|
||||
# Internal models for SDK v1 context protocol matching SDK v1 resources.py
|
||||
|
||||
|
||||
class AgentTrigger(typing.TypedDict):
|
||||
"""Agent trigger information."""
|
||||
type: str
|
||||
source: str # 'pipeline' or 'event_router'
|
||||
timestamp: int | None
|
||||
|
||||
|
||||
class ConversationContext(typing.TypedDict):
|
||||
"""Conversation context."""
|
||||
session_id: str | None
|
||||
conversation_id: str | None
|
||||
launcher_type: str | None
|
||||
launcher_id: str | None
|
||||
sender_id: str | None
|
||||
bot_uuid: str | None
|
||||
pipeline_uuid: str | None
|
||||
|
||||
|
||||
class AgentInput(typing.TypedDict):
|
||||
"""Agent input."""
|
||||
text: str | None
|
||||
contents: list[dict[str, typing.Any]]
|
||||
message_chain: dict[str, typing.Any] | None
|
||||
attachments: list[dict[str, typing.Any]]
|
||||
|
||||
|
||||
# SDK v1 Protocol resource models - matching langbot-plugin-sdk/resources.py
|
||||
|
||||
|
||||
class ModelResource(typing.TypedDict):
|
||||
"""Model resource per SDK v1."""
|
||||
model_id: str
|
||||
model_type: str | None
|
||||
provider: str | None
|
||||
|
||||
|
||||
class ToolResource(typing.TypedDict):
|
||||
"""Tool resource per SDK v1."""
|
||||
tool_name: str
|
||||
tool_type: str | None
|
||||
description: str | None
|
||||
|
||||
|
||||
class KnowledgeBaseResource(typing.TypedDict):
|
||||
"""Knowledge base resource per SDK v1."""
|
||||
kb_id: str
|
||||
kb_name: str | None
|
||||
kb_type: str | None
|
||||
|
||||
|
||||
class FileResource(typing.TypedDict):
|
||||
"""File resource per SDK v1."""
|
||||
file_id: str
|
||||
file_name: str | None
|
||||
mime_type: str | None
|
||||
source: str | None
|
||||
|
||||
|
||||
class StorageResource(typing.TypedDict):
|
||||
"""Storage resource per SDK v1."""
|
||||
plugin_storage: bool
|
||||
workspace_storage: bool
|
||||
|
||||
|
||||
class AgentResources(typing.TypedDict):
|
||||
"""Agent resources per SDK v1."""
|
||||
models: list[ModelResource]
|
||||
tools: list[ToolResource]
|
||||
knowledge_bases: list[KnowledgeBaseResource]
|
||||
files: list[FileResource]
|
||||
storage: StorageResource
|
||||
platform_capabilities: dict[str, typing.Any]
|
||||
|
||||
|
||||
class AgentRuntimeContext(typing.TypedDict):
|
||||
"""Agent runtime context."""
|
||||
langbot_version: str | None
|
||||
sdk_protocol_version: str
|
||||
query_id: int | None
|
||||
trace_id: str | None
|
||||
deadline_at: int | None
|
||||
metadata: dict[str, typing.Any]
|
||||
|
||||
|
||||
class AgentRunContextV1(typing.TypedDict):
|
||||
"""SDK v1 AgentRunContext per PROTOCOL_V1.md."""
|
||||
run_id: str
|
||||
trigger: AgentTrigger
|
||||
conversation: ConversationContext | None
|
||||
event: dict[str, typing.Any] | None # Reserved for EBA
|
||||
actor: dict[str, typing.Any] | None # Reserved for EBA
|
||||
subject: dict[str, typing.Any] | None # Reserved for EBA
|
||||
messages: list[dict[str, typing.Any]]
|
||||
input: AgentInput
|
||||
resources: AgentResources
|
||||
runtime: AgentRuntimeContext
|
||||
config: dict[str, typing.Any]
|
||||
|
||||
|
||||
class AgentRunContextBuilder:
|
||||
"""Builder for converting Query to SDK v1 AgentRunContext.
|
||||
|
||||
Responsibilities:
|
||||
- Generate new run_id (UUID, not query id)
|
||||
- Set trigger type to 'message.received' for pipeline
|
||||
- Build conversation context from session
|
||||
- Convert messages to SDK format
|
||||
- Build input from user_message and message_chain
|
||||
- Set resources from AgentResourceBuilder result
|
||||
- Build runtime context with host info, trace_id, deadline
|
||||
- Set config from runner instance configuration
|
||||
"""
|
||||
|
||||
ap: app.Application
|
||||
|
||||
def __init__(self, ap: app.Application):
|
||||
self.ap = ap
|
||||
|
||||
async def build_context(
|
||||
self,
|
||||
query: pipeline_query.Query,
|
||||
descriptor: AgentRunnerDescriptor,
|
||||
resources: AgentResources,
|
||||
) -> AgentRunContextV1:
|
||||
"""Build AgentRunContext from Query.
|
||||
|
||||
Args:
|
||||
query: Pipeline query
|
||||
descriptor: Runner descriptor
|
||||
resources: Built resources from AgentResourceBuilder
|
||||
|
||||
Returns:
|
||||
AgentRunContextV1 dict matching PROTOCOL_V1.md
|
||||
"""
|
||||
# Generate new run_id
|
||||
run_id = str(uuid.uuid4())
|
||||
|
||||
# Build trigger
|
||||
trigger: AgentTrigger = {
|
||||
'type': 'message.received',
|
||||
'source': 'pipeline',
|
||||
'timestamp': int(time.time()),
|
||||
}
|
||||
|
||||
# Build conversation context
|
||||
conversation: ConversationContext | None = None
|
||||
if query.session:
|
||||
conversation = {
|
||||
'session_id': f'{query.session.launcher_type.value}_{query.session.launcher_id}',
|
||||
'conversation_id': getattr(query.session.using_conversation, 'uuid', None),
|
||||
'launcher_type': query.session.launcher_type.value,
|
||||
'launcher_id': query.session.launcher_id,
|
||||
'sender_id': str(query.sender_id),
|
||||
'bot_uuid': query.bot_uuid,
|
||||
'pipeline_uuid': query.pipeline_uuid,
|
||||
}
|
||||
|
||||
# Build input
|
||||
input: AgentInput = self._build_input(query)
|
||||
|
||||
# Build messages
|
||||
messages = self._build_messages(query)
|
||||
|
||||
# Get runner config
|
||||
runner_config = ConfigMigration.resolve_runner_config(
|
||||
query.pipeline_config,
|
||||
descriptor.id,
|
||||
)
|
||||
|
||||
# Build runtime context
|
||||
runtime: AgentRuntimeContext = {
|
||||
'langbot_version': self.ap.ver_mgr.get_current_version(),
|
||||
'sdk_protocol_version': descriptor.protocol_version,
|
||||
'query_id': query.query_id,
|
||||
'trace_id': run_id, # Use run_id as trace_id for now
|
||||
'deadline_at': None, # TODO: set from runner config timeout
|
||||
'metadata': {
|
||||
'bot_name': query.variables.get('_monitoring_bot_name', 'Unknown'),
|
||||
'pipeline_name': query.variables.get('_monitoring_pipeline_name', 'Unknown'),
|
||||
},
|
||||
}
|
||||
|
||||
# Build full context
|
||||
context: AgentRunContextV1 = {
|
||||
'run_id': run_id,
|
||||
'trigger': trigger,
|
||||
'conversation': conversation,
|
||||
'event': None, # Reserved for EBA
|
||||
'actor': None, # Reserved for EBA
|
||||
'subject': None, # Reserved for EBA
|
||||
'messages': messages,
|
||||
'input': input,
|
||||
'resources': resources,
|
||||
'runtime': runtime,
|
||||
'config': runner_config,
|
||||
}
|
||||
|
||||
return context
|
||||
|
||||
def _build_input(self, query: pipeline_query.Query) -> AgentInput:
|
||||
"""Build AgentInput from query."""
|
||||
text = None
|
||||
contents: list[dict[str, typing.Any]] = []
|
||||
|
||||
if query.user_message:
|
||||
# Extract text if content is single text element
|
||||
if isinstance(query.user_message.content, list):
|
||||
for elem in query.user_message.content:
|
||||
contents.append(elem.model_dump(mode='json'))
|
||||
if elem.type == 'text':
|
||||
text = getattr(elem, 'text', None)
|
||||
else:
|
||||
# Single string content
|
||||
text = str(query.user_message.content)
|
||||
contents.append({'type': 'text', 'text': text})
|
||||
|
||||
# Include message_chain for platform-specific format
|
||||
message_chain_dict = None
|
||||
if query.message_chain:
|
||||
message_chain_dict = query.message_chain.model_dump(mode='json')
|
||||
|
||||
return {
|
||||
'text': text,
|
||||
'contents': contents,
|
||||
'message_chain': message_chain_dict,
|
||||
'attachments': [], # TODO: extract attachments from message_chain
|
||||
}
|
||||
|
||||
def _build_messages(self, query: pipeline_query.Query) -> list[dict[str, typing.Any]]:
|
||||
"""Build messages list from query."""
|
||||
messages: list[dict[str, typing.Any]] = []
|
||||
|
||||
if query.messages:
|
||||
for msg in query.messages:
|
||||
messages.append(msg.model_dump(mode='json'))
|
||||
|
||||
return messages
|
||||
72
src/langbot/pkg/agent/runner/descriptor.py
Normal file
72
src/langbot/pkg/agent/runner/descriptor.py
Normal file
@@ -0,0 +1,72 @@
|
||||
"""Agent runner descriptor."""
|
||||
from __future__ import annotations
|
||||
|
||||
import typing
|
||||
import pydantic
|
||||
|
||||
|
||||
class AgentRunnerDescriptor(pydantic.BaseModel):
|
||||
"""Descriptor for an agent runner.
|
||||
|
||||
Represents the discovered metadata for a runner, including
|
||||
its identity, capabilities, permissions, and configuration schema.
|
||||
"""
|
||||
|
||||
id: str
|
||||
"""Unique runner ID: plugin:author/plugin_name/runner_name"""
|
||||
|
||||
source: typing.Literal['plugin']
|
||||
"""Runner source type"""
|
||||
|
||||
label: dict[str, str]
|
||||
"""Display labels keyed by locale (e.g., en_US, zh_Hans)"""
|
||||
|
||||
description: dict[str, str] | None = None
|
||||
"""Optional description keyed by locale"""
|
||||
|
||||
plugin_author: str
|
||||
"""Plugin author from manifest"""
|
||||
|
||||
plugin_name: str
|
||||
"""Plugin name from manifest"""
|
||||
|
||||
runner_name: str
|
||||
"""AgentRunner component name from manifest"""
|
||||
|
||||
plugin_version: str | None = None
|
||||
"""Optional plugin version"""
|
||||
|
||||
protocol_version: str = '1'
|
||||
"""SDK protocol version, default '1'"""
|
||||
|
||||
config_schema: list[dict[str, typing.Any]] = []
|
||||
"""Configuration schema using DynamicForm format"""
|
||||
|
||||
capabilities: dict[str, bool] = {}
|
||||
"""Runner capabilities: streaming, tool_calling, knowledge_retrieval, etc."""
|
||||
|
||||
permissions: dict[str, list[str]] = {}
|
||||
"""Requested permissions: models, tools, knowledge_bases, storage, files, platform_api"""
|
||||
|
||||
raw_manifest: dict[str, typing.Any] = {}
|
||||
"""Original manifest for reference"""
|
||||
|
||||
model_config = pydantic.ConfigDict(
|
||||
extra='allow',
|
||||
)
|
||||
|
||||
def get_plugin_id(self) -> str:
|
||||
"""Return plugin identifier as author/name."""
|
||||
return f'{self.plugin_author}/{self.plugin_name}'
|
||||
|
||||
def supports_streaming(self) -> bool:
|
||||
"""Check if runner supports streaming output."""
|
||||
return self.capabilities.get('streaming', False)
|
||||
|
||||
def supports_tool_calling(self) -> bool:
|
||||
"""Check if runner supports tool calling."""
|
||||
return self.capabilities.get('tool_calling', False)
|
||||
|
||||
def supports_knowledge_retrieval(self) -> bool:
|
||||
"""Check if runner supports knowledge retrieval."""
|
||||
return self.capabilities.get('knowledge_retrieval', False)
|
||||
37
src/langbot/pkg/agent/runner/errors.py
Normal file
37
src/langbot/pkg/agent/runner/errors.py
Normal file
@@ -0,0 +1,37 @@
|
||||
"""Agent runner errors."""
|
||||
from __future__ import annotations
|
||||
|
||||
|
||||
class AgentRunnerError(Exception):
|
||||
"""Base error for agent runner operations."""
|
||||
pass
|
||||
|
||||
|
||||
class RunnerNotFoundError(AgentRunnerError):
|
||||
"""Runner not found in registry."""
|
||||
def __init__(self, runner_id: str):
|
||||
self.runner_id = runner_id
|
||||
super().__init__(f'Agent runner not found: {runner_id}')
|
||||
|
||||
|
||||
class RunnerNotAuthorizedError(AgentRunnerError):
|
||||
"""Runner not authorized for this pipeline."""
|
||||
def __init__(self, runner_id: str, bound_plugins: list[str] | None):
|
||||
self.runner_id = runner_id
|
||||
self.bound_plugins = bound_plugins
|
||||
super().__init__(f'Agent runner {runner_id} not authorized for bound_plugins={bound_plugins}')
|
||||
|
||||
|
||||
class RunnerProtocolError(AgentRunnerError):
|
||||
"""Runner protocol version mismatch or invalid manifest."""
|
||||
def __init__(self, runner_id: str, message: str):
|
||||
self.runner_id = runner_id
|
||||
super().__init__(f'Agent runner protocol error for {runner_id}: {message}')
|
||||
|
||||
|
||||
class RunnerExecutionError(AgentRunnerError):
|
||||
"""Runner execution failed."""
|
||||
def __init__(self, runner_id: str, message: str, retryable: bool = False):
|
||||
self.runner_id = runner_id
|
||||
self.retryable = retryable
|
||||
super().__init__(f'Agent runner {runner_id} execution failed: {message}')
|
||||
92
src/langbot/pkg/agent/runner/id.py
Normal file
92
src/langbot/pkg/agent/runner/id.py
Normal file
@@ -0,0 +1,92 @@
|
||||
"""Agent runner ID parsing and formatting."""
|
||||
from __future__ import annotations
|
||||
|
||||
import dataclasses
|
||||
|
||||
|
||||
@dataclasses.dataclass(frozen=True)
|
||||
class RunnerIdParts:
|
||||
"""Parsed runner ID components."""
|
||||
source: str # 'plugin' (future: 'builtin')
|
||||
plugin_author: str
|
||||
plugin_name: str
|
||||
runner_name: str
|
||||
|
||||
def to_plugin_id(self) -> str:
|
||||
"""Return plugin identifier as author/name."""
|
||||
return f'{self.plugin_author}/{self.plugin_name}'
|
||||
|
||||
|
||||
def parse_runner_id(runner_id: str) -> RunnerIdParts:
|
||||
"""Parse runner ID string into components.
|
||||
|
||||
Args:
|
||||
runner_id: Runner ID in format 'plugin:author/plugin_name/runner_name'
|
||||
|
||||
Returns:
|
||||
RunnerIdParts with parsed components
|
||||
|
||||
Raises:
|
||||
ValueError: If runner_id format is invalid
|
||||
"""
|
||||
if runner_id.startswith('plugin:'):
|
||||
parts = runner_id[7:].split('/')
|
||||
if len(parts) != 3:
|
||||
raise ValueError(
|
||||
f'Invalid plugin runner ID format: {runner_id}. '
|
||||
f'Expected: plugin:author/plugin_name/runner_name'
|
||||
)
|
||||
plugin_author, plugin_name, runner_name = parts
|
||||
if not plugin_author or not plugin_name or not runner_name:
|
||||
raise ValueError(
|
||||
f'Invalid plugin runner ID: {runner_id}. '
|
||||
f'author, plugin_name, and runner_name must be non-empty'
|
||||
)
|
||||
return RunnerIdParts(
|
||||
source='plugin',
|
||||
plugin_author=plugin_author,
|
||||
plugin_name=plugin_name,
|
||||
runner_name=runner_name,
|
||||
)
|
||||
else:
|
||||
# For backward compatibility with old built-in runner names
|
||||
# This should eventually be removed after migration
|
||||
raise ValueError(
|
||||
f'Invalid runner ID format: {runner_id}. '
|
||||
f'Expected: plugin:author/plugin_name/runner_name'
|
||||
)
|
||||
|
||||
|
||||
def format_runner_id(
|
||||
source: str,
|
||||
plugin_author: str,
|
||||
plugin_name: str,
|
||||
runner_name: str,
|
||||
) -> str:
|
||||
"""Format runner ID from components.
|
||||
|
||||
Args:
|
||||
source: Runner source ('plugin')
|
||||
plugin_author: Plugin author
|
||||
plugin_name: Plugin name
|
||||
runner_name: Runner component name
|
||||
|
||||
Returns:
|
||||
Runner ID string
|
||||
"""
|
||||
if source == 'plugin':
|
||||
return f'plugin:{plugin_author}/{plugin_name}/{runner_name}'
|
||||
else:
|
||||
raise ValueError(f'Invalid runner source: {source}')
|
||||
|
||||
|
||||
def is_plugin_runner_id(runner_id: str) -> bool:
|
||||
"""Check if runner ID is a plugin runner.
|
||||
|
||||
Args:
|
||||
runner_id: Runner ID string
|
||||
|
||||
Returns:
|
||||
True if runner ID starts with 'plugin:'
|
||||
"""
|
||||
return runner_id.startswith('plugin:')
|
||||
158
src/langbot/pkg/agent/runner/orchestrator.py
Normal file
158
src/langbot/pkg/agent/runner/orchestrator.py
Normal file
@@ -0,0 +1,158 @@
|
||||
"""Agent run orchestrator for coordinating runner execution."""
|
||||
from __future__ import annotations
|
||||
|
||||
import typing
|
||||
import traceback
|
||||
|
||||
from langbot_plugin.api.entities.builtin.provider import message as provider_message
|
||||
from langbot_plugin.api.entities.builtin.pipeline import query as pipeline_query
|
||||
|
||||
from ...core import app
|
||||
from .descriptor import AgentRunnerDescriptor
|
||||
from .registry import AgentRunnerRegistry
|
||||
from .context_builder import AgentRunContextBuilder, AgentRunContextV1
|
||||
from .resource_builder import AgentResourceBuilder
|
||||
from .result_normalizer import AgentResultNormalizer
|
||||
from .config_migration import ConfigMigration
|
||||
from .errors import (
|
||||
RunnerNotFoundError,
|
||||
RunnerExecutionError,
|
||||
)
|
||||
|
||||
|
||||
class AgentRunOrchestrator:
|
||||
"""Orchestrator for agent runner execution.
|
||||
|
||||
Responsibilities:
|
||||
- Resolve runner ID from pipeline config (new or old format)
|
||||
- Get runner descriptor from registry
|
||||
- Build AgentRunContext from Query
|
||||
- Build AgentResources with permission filtering
|
||||
- Invoke plugin runtime RUN_AGENT action
|
||||
- Normalize AgentRunResult to Pipeline messages
|
||||
- Handle errors, timeouts, protocol errors
|
||||
- Maintain streaming card behavior
|
||||
|
||||
This is the main entry point for ChatMessageHandler.
|
||||
"""
|
||||
|
||||
ap: app.Application
|
||||
|
||||
registry: AgentRunnerRegistry
|
||||
|
||||
context_builder: AgentRunContextBuilder
|
||||
|
||||
resource_builder: AgentResourceBuilder
|
||||
|
||||
result_normalizer: AgentResultNormalizer
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
ap: app.Application,
|
||||
registry: AgentRunnerRegistry,
|
||||
):
|
||||
self.ap = ap
|
||||
self.registry = registry
|
||||
self.context_builder = AgentRunContextBuilder(ap)
|
||||
self.resource_builder = AgentResourceBuilder(ap)
|
||||
self.result_normalizer = AgentResultNormalizer(ap)
|
||||
|
||||
async def run_from_query(
|
||||
self,
|
||||
query: pipeline_query.Query,
|
||||
) -> typing.AsyncGenerator[provider_message.Message | provider_message.MessageChunk, None]:
|
||||
"""Run agent runner from pipeline query.
|
||||
|
||||
This is the main entry point called by ChatMessageHandler.
|
||||
|
||||
Args:
|
||||
query: Pipeline query with pipeline_config, session, messages, etc.
|
||||
|
||||
Yields:
|
||||
Message or MessageChunk for pipeline response
|
||||
|
||||
Raises:
|
||||
RunnerNotFoundError: If runner not found
|
||||
RunnerNotAuthorizedError: If runner not authorized
|
||||
RunnerExecutionError: If runner execution failed
|
||||
"""
|
||||
# Resolve runner ID
|
||||
runner_id = ConfigMigration.resolve_runner_id(query.pipeline_config)
|
||||
if not runner_id:
|
||||
raise RunnerNotFoundError('no runner configured')
|
||||
|
||||
# Get bound plugins for authorization
|
||||
bound_plugins = query.variables.get('_pipeline_bound_plugins')
|
||||
|
||||
# Get runner descriptor
|
||||
descriptor = await self.registry.get(runner_id, bound_plugins)
|
||||
|
||||
# Build resources
|
||||
resources = await self.resource_builder.build_resources(query, descriptor)
|
||||
|
||||
# Build context
|
||||
context = await self.context_builder.build_context(query, descriptor, resources)
|
||||
|
||||
# Run via plugin connector
|
||||
async for result_dict in self._invoke_runner(descriptor, context):
|
||||
# Normalize result
|
||||
result = await self.result_normalizer.normalize(result_dict, descriptor)
|
||||
if result is not None:
|
||||
yield result
|
||||
|
||||
async def _invoke_runner(
|
||||
self,
|
||||
descriptor: AgentRunnerDescriptor,
|
||||
context: AgentRunContextV1,
|
||||
) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
|
||||
"""Invoke runner via plugin connector.
|
||||
|
||||
Args:
|
||||
descriptor: Runner descriptor
|
||||
context: AgentRunContext dict
|
||||
|
||||
Yields:
|
||||
Raw result dicts from plugin runtime
|
||||
|
||||
Raises:
|
||||
RunnerExecutionError: If plugin system disabled or runtime error
|
||||
"""
|
||||
if not self.ap.plugin_connector.is_enable_plugin:
|
||||
raise RunnerExecutionError(
|
||||
descriptor.id,
|
||||
'Plugin system is disabled',
|
||||
retryable=False,
|
||||
)
|
||||
|
||||
try:
|
||||
async for result_dict in self.ap.plugin_connector.run_agent(
|
||||
plugin_author=descriptor.plugin_author,
|
||||
plugin_name=descriptor.plugin_name,
|
||||
runner_name=descriptor.runner_name,
|
||||
context=context,
|
||||
):
|
||||
yield result_dict
|
||||
|
||||
except RunnerExecutionError:
|
||||
raise
|
||||
except Exception as e:
|
||||
# Wrap unexpected errors
|
||||
self.ap.logger.error(
|
||||
f'Runner {descriptor.id} unexpected error: {traceback.format_exc()}'
|
||||
)
|
||||
raise RunnerExecutionError(
|
||||
descriptor.id,
|
||||
str(e),
|
||||
retryable=False,
|
||||
)
|
||||
|
||||
def resolve_runner_id_for_telemetry(self, query: pipeline_query.Query) -> str | None:
|
||||
"""Resolve runner ID for telemetry/logging without full execution.
|
||||
|
||||
Args:
|
||||
query: Pipeline query
|
||||
|
||||
Returns:
|
||||
Runner ID string, or None
|
||||
"""
|
||||
return ConfigMigration.resolve_runner_id(query.pipeline_config)
|
||||
277
src/langbot/pkg/agent/runner/registry.py
Normal file
277
src/langbot/pkg/agent/runner/registry.py
Normal file
@@ -0,0 +1,277 @@
|
||||
"""Agent runner registry for discovering and caching runner descriptors."""
|
||||
from __future__ import annotations
|
||||
|
||||
import typing
|
||||
import asyncio
|
||||
|
||||
from ...core import app
|
||||
from .descriptor import AgentRunnerDescriptor
|
||||
from .id import parse_runner_id, format_runner_id
|
||||
from .errors import RunnerNotFoundError, RunnerNotAuthorizedError
|
||||
|
||||
|
||||
class AgentRunnerRegistry:
|
||||
"""Registry for discovering and managing agent runners.
|
||||
|
||||
Responsibilities:
|
||||
- Discover runners from plugin runtime via LIST_AGENT_RUNNERS
|
||||
- Validate runner manifests (kind, metadata, spec)
|
||||
- Cache discovered runners for performance
|
||||
- Filter runners by bound plugins
|
||||
- Handle manifest errors gracefully (log warning, skip runner)
|
||||
"""
|
||||
|
||||
ap: app.Application
|
||||
|
||||
_cache: dict[str, AgentRunnerDescriptor] | None
|
||||
"""Cached runner descriptors keyed by runner ID"""
|
||||
|
||||
_cache_lock: asyncio.Lock
|
||||
"""Lock for cache refresh operations"""
|
||||
|
||||
def __init__(self, ap: app.Application):
|
||||
self.ap = ap
|
||||
self._cache = None
|
||||
self._cache_lock = asyncio.Lock()
|
||||
|
||||
async def _discover_runners(self) -> dict[str, AgentRunnerDescriptor]:
|
||||
"""Discover runners from plugin runtime.
|
||||
|
||||
Always discovers ALL runners (no bound_plugins filter).
|
||||
The cache should contain unfiltered discovery results.
|
||||
|
||||
Returns:
|
||||
Dict of runner descriptors keyed by runner ID
|
||||
"""
|
||||
if not self.ap.plugin_connector.is_enable_plugin:
|
||||
return {}
|
||||
|
||||
runners: dict[str, AgentRunnerDescriptor] = {}
|
||||
|
||||
try:
|
||||
# Always list all runners (bound_plugins=None)
|
||||
plugin_runners = await self.ap.plugin_connector.list_agent_runners(None)
|
||||
|
||||
for runner_data in plugin_runners:
|
||||
try:
|
||||
descriptor = self._validate_and_build_descriptor(runner_data)
|
||||
if descriptor is not None:
|
||||
runners[descriptor.id] = descriptor
|
||||
except Exception as e:
|
||||
plugin_author = runner_data.get('plugin_author', 'unknown')
|
||||
plugin_name = runner_data.get('plugin_name', 'unknown')
|
||||
runner_name = runner_data.get('runner_name', 'unknown')
|
||||
self.ap.logger.warning(
|
||||
f'Invalid runner manifest for plugin:{plugin_author}/{plugin_name}/{runner_name}: {e}'
|
||||
)
|
||||
continue
|
||||
|
||||
except Exception as e:
|
||||
self.ap.logger.warning(f'Failed to list agent runners from plugin runtime: {e}')
|
||||
return {}
|
||||
|
||||
return runners
|
||||
|
||||
def _validate_and_build_descriptor(self, runner_data: dict[str, typing.Any]) -> AgentRunnerDescriptor | None:
|
||||
"""Validate runner manifest and build descriptor.
|
||||
|
||||
Args:
|
||||
runner_data: Raw runner data from plugin runtime with fields:
|
||||
- plugin_author, plugin_name, runner_name
|
||||
- manifest (full component manifest dict)
|
||||
- protocol_version, capabilities, permissions, config (extracted from spec)
|
||||
|
||||
Returns:
|
||||
AgentRunnerDescriptor if valid, None if invalid
|
||||
"""
|
||||
plugin_author = runner_data.get('plugin_author', '')
|
||||
plugin_name = runner_data.get('plugin_name', '')
|
||||
runner_name = runner_data.get('runner_name', '')
|
||||
|
||||
if not plugin_author or not plugin_name or not runner_name:
|
||||
return None
|
||||
|
||||
manifest = runner_data.get('manifest', {})
|
||||
|
||||
# Validate kind
|
||||
kind = manifest.get('kind', '')
|
||||
if kind != 'AgentRunner':
|
||||
return None
|
||||
|
||||
# Validate metadata
|
||||
metadata = manifest.get('metadata', {})
|
||||
name = metadata.get('name', '')
|
||||
if not name:
|
||||
return None
|
||||
|
||||
# metadata.label must exist
|
||||
label = metadata.get('label', {})
|
||||
if not label:
|
||||
label = {name: name} # fallback
|
||||
|
||||
# SDK now provides these directly extracted from spec
|
||||
protocol_version = runner_data.get('protocol_version', '1')
|
||||
config_schema = runner_data.get('config', [])
|
||||
capabilities = runner_data.get('capabilities', {})
|
||||
permissions = runner_data.get('permissions', {})
|
||||
|
||||
# Build descriptor
|
||||
runner_id = format_runner_id(
|
||||
source='plugin',
|
||||
plugin_author=plugin_author,
|
||||
plugin_name=plugin_name,
|
||||
runner_name=runner_name,
|
||||
)
|
||||
|
||||
return AgentRunnerDescriptor(
|
||||
id=runner_id,
|
||||
source='plugin',
|
||||
label=label,
|
||||
description=metadata.get('description') or runner_data.get('runner_description'),
|
||||
plugin_author=plugin_author,
|
||||
plugin_name=plugin_name,
|
||||
runner_name=runner_name,
|
||||
plugin_version=runner_data.get('plugin_version'),
|
||||
protocol_version=protocol_version,
|
||||
config_schema=config_schema,
|
||||
capabilities=capabilities,
|
||||
permissions=permissions,
|
||||
raw_manifest=manifest,
|
||||
)
|
||||
|
||||
async def refresh(self) -> None:
|
||||
"""Refresh runner cache.
|
||||
|
||||
Always discovers ALL runners (no bound_plugins filter).
|
||||
The cache contains unfiltered discovery results.
|
||||
"""
|
||||
async with self._cache_lock:
|
||||
self._cache = await self._discover_runners()
|
||||
|
||||
async def list_runners(
|
||||
self,
|
||||
bound_plugins: list[str] | None = None,
|
||||
use_cache: bool = True,
|
||||
) -> list[AgentRunnerDescriptor]:
|
||||
"""List available runners.
|
||||
|
||||
Args:
|
||||
bound_plugins: Optional filter for bound plugins (applied locally)
|
||||
use_cache: Use cached data if available
|
||||
|
||||
Returns:
|
||||
List of runner descriptors
|
||||
"""
|
||||
if use_cache and self._cache is not None:
|
||||
# Filter from cache
|
||||
return self._filter_runners_by_bound_plugins(self._cache, bound_plugins)
|
||||
|
||||
# Discover fresh (always full list)
|
||||
runners = await self._discover_runners()
|
||||
|
||||
# Update cache (full list, unfiltered)
|
||||
async with self._cache_lock:
|
||||
self._cache = runners
|
||||
|
||||
# Filter locally
|
||||
return self._filter_runners_by_bound_plugins(runners, bound_plugins)
|
||||
|
||||
def _filter_runners_by_bound_plugins(
|
||||
self,
|
||||
runners: dict[str, AgentRunnerDescriptor],
|
||||
bound_plugins: list[str] | None,
|
||||
) -> list[AgentRunnerDescriptor]:
|
||||
"""Filter runners by bound plugins.
|
||||
|
||||
Args:
|
||||
runners: Dict of runner descriptors
|
||||
bound_plugins: Optional filter (None means all plugins allowed)
|
||||
|
||||
Returns:
|
||||
Filtered list of runner descriptors
|
||||
"""
|
||||
if bound_plugins is None:
|
||||
# All plugins allowed
|
||||
return list(runners.values())
|
||||
|
||||
allowed_plugin_ids = set(bound_plugins)
|
||||
filtered = []
|
||||
for descriptor in runners.values():
|
||||
plugin_id = descriptor.get_plugin_id()
|
||||
if plugin_id in allowed_plugin_ids:
|
||||
filtered.append(descriptor)
|
||||
|
||||
return filtered
|
||||
|
||||
async def get(
|
||||
self,
|
||||
runner_id: str,
|
||||
bound_plugins: list[str] | None = None,
|
||||
) -> AgentRunnerDescriptor:
|
||||
"""Get a specific runner descriptor.
|
||||
|
||||
Args:
|
||||
runner_id: Runner ID to lookup
|
||||
bound_plugins: Optional bound plugins filter
|
||||
|
||||
Returns:
|
||||
AgentRunnerDescriptor
|
||||
|
||||
Raises:
|
||||
RunnerNotFoundError: If runner not found
|
||||
RunnerNotAuthorizedError: If runner not in bound plugins
|
||||
"""
|
||||
# Parse and validate runner ID format
|
||||
try:
|
||||
parse_runner_id(runner_id)
|
||||
except ValueError as e:
|
||||
raise RunnerNotFoundError(runner_id) from e
|
||||
|
||||
# Get from cache or discover (always full list)
|
||||
if self._cache is None:
|
||||
await self.refresh()
|
||||
|
||||
if self._cache is None:
|
||||
raise RunnerNotFoundError(runner_id)
|
||||
|
||||
descriptor = self._cache.get(runner_id)
|
||||
if descriptor is None:
|
||||
raise RunnerNotFoundError(runner_id)
|
||||
|
||||
# Check authorization
|
||||
if bound_plugins is not None:
|
||||
plugin_id = descriptor.get_plugin_id()
|
||||
if plugin_id not in bound_plugins:
|
||||
raise RunnerNotAuthorizedError(runner_id, bound_plugins)
|
||||
|
||||
return descriptor
|
||||
|
||||
async def get_runner_metadata_for_pipeline(self) -> list[dict[str, typing.Any]]:
|
||||
"""Get runner metadata for pipeline configuration UI.
|
||||
|
||||
Returns runner options and their config schemas for the DynamicForm.
|
||||
"""
|
||||
# Get all runners (no bound plugin filter for metadata listing)
|
||||
runners = await self.list_runners(bound_plugins=None)
|
||||
|
||||
options = []
|
||||
stages = []
|
||||
|
||||
for descriptor in runners:
|
||||
# Add runner option
|
||||
options.append({
|
||||
'name': descriptor.id,
|
||||
'label': descriptor.label,
|
||||
'description': descriptor.description,
|
||||
})
|
||||
|
||||
# Add config schema as stage if not empty
|
||||
if descriptor.config_schema:
|
||||
stages.append({
|
||||
'name': descriptor.id,
|
||||
'label': descriptor.label,
|
||||
'description': descriptor.description,
|
||||
'config': descriptor.config_schema,
|
||||
})
|
||||
|
||||
return options, stages
|
||||
210
src/langbot/pkg/agent/runner/resource_builder.py
Normal file
210
src/langbot/pkg/agent/runner/resource_builder.py
Normal file
@@ -0,0 +1,210 @@
|
||||
"""Agent resource builder for constructing authorized resources."""
|
||||
from __future__ import annotations
|
||||
|
||||
import typing
|
||||
|
||||
from ...core import app
|
||||
from .descriptor import AgentRunnerDescriptor
|
||||
from .context_builder import (
|
||||
AgentResources,
|
||||
ModelResource,
|
||||
ToolResource,
|
||||
KnowledgeBaseResource,
|
||||
StorageResource,
|
||||
)
|
||||
|
||||
|
||||
class AgentResourceBuilder:
|
||||
"""Builder for constructing AgentResources with permission filtering.
|
||||
|
||||
Responsibilities:
|
||||
- Apply 3-layer permission filtering:
|
||||
1. Runner manifest declared permissions
|
||||
2. Pipeline extensions_preference (bound plugins/MCP servers)
|
||||
3. Runner instance config selected resources
|
||||
- Build models list from authorized models
|
||||
- Build tools list from bound plugins/MCP servers
|
||||
- Build knowledge_bases list from config
|
||||
- Build storage and files permissions summary
|
||||
|
||||
Note: This only builds the resource declaration. The actual proxy actions
|
||||
in handler.py must still validate against ctx.resources at runtime.
|
||||
|
||||
Resource field names match SDK v1 Protocol:
|
||||
- ModelResource: model_id, model_type, provider
|
||||
- ToolResource: tool_name, tool_type, description
|
||||
- KnowledgeBaseResource: kb_id, kb_name, kb_type
|
||||
- StorageResource: plugin_storage, workspace_storage
|
||||
"""
|
||||
|
||||
ap: app.Application
|
||||
|
||||
def __init__(self, ap: app.Application):
|
||||
self.ap = ap
|
||||
|
||||
async def build_resources(
|
||||
self,
|
||||
query: typing.Any, # pipeline_query.Query
|
||||
descriptor: AgentRunnerDescriptor,
|
||||
) -> AgentResources:
|
||||
"""Build AgentResources from query and runner descriptor.
|
||||
|
||||
Args:
|
||||
query: Pipeline query with pipeline_config and variables
|
||||
descriptor: Runner descriptor with permissions and capabilities
|
||||
|
||||
Returns:
|
||||
AgentResources dict with filtered resource lists
|
||||
"""
|
||||
# Get bound plugins and MCP servers from query
|
||||
bound_plugins = query.variables.get('_pipeline_bound_plugins')
|
||||
bound_mcp_servers = query.variables.get('_pipeline_bound_mcp_servers')
|
||||
|
||||
# Layer 1: Runner manifest permissions
|
||||
manifest_perms = descriptor.permissions
|
||||
|
||||
# Layer 2: Pipeline extensions_preference (already in bound_plugins/MCP servers)
|
||||
# Layer 3: Runner instance config (from pipeline_config) - resolved via ConfigMigration
|
||||
from .config_migration import ConfigMigration
|
||||
runner_config = ConfigMigration.resolve_runner_config(query.pipeline_config, descriptor.id)
|
||||
|
||||
# Build each resource category
|
||||
models = await self._build_models(manifest_perms, query)
|
||||
tools = await self._build_tools(manifest_perms, bound_plugins, bound_mcp_servers, query)
|
||||
knowledge_bases = await self._build_knowledge_bases(manifest_perms, runner_config, query)
|
||||
storage = self._build_storage(manifest_perms)
|
||||
|
||||
return {
|
||||
'models': models,
|
||||
'tools': tools,
|
||||
'knowledge_bases': knowledge_bases,
|
||||
'files': [], # Files are populated at runtime
|
||||
'storage': storage,
|
||||
'platform_capabilities': {}, # Reserved for EBA
|
||||
}
|
||||
|
||||
async def _build_models(
|
||||
self,
|
||||
manifest_perms: dict[str, list[str]],
|
||||
query: typing.Any,
|
||||
) -> list[ModelResource]:
|
||||
"""Build models list with SDK v1 field names."""
|
||||
models: list[ModelResource] = []
|
||||
|
||||
# Check manifest permission
|
||||
model_perms = manifest_perms.get('models', [])
|
||||
if 'invoke' not in model_perms and 'stream' not in model_perms:
|
||||
return models
|
||||
|
||||
# Get model from query (preproc already resolved this)
|
||||
model_uuid = getattr(query, 'use_llm_model_uuid', None)
|
||||
if not model_uuid:
|
||||
return models
|
||||
|
||||
try:
|
||||
model = await self.ap.model_mgr.get_model_by_uuid(model_uuid)
|
||||
if model and model.model_entity:
|
||||
# Use SDK v1 field names: model_id, model_type, provider
|
||||
models.append({
|
||||
'model_id': model_uuid,
|
||||
'model_type': model.model_entity.model_type,
|
||||
'provider': model.provider_entity.name if hasattr(model, 'provider_entity') else None,
|
||||
})
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Add fallback models if present
|
||||
fallback_uuids = query.variables.get('_fallback_model_uuids', [])
|
||||
for fb_uuid in fallback_uuids:
|
||||
try:
|
||||
model = await self.ap.model_mgr.get_model_by_uuid(fb_uuid)
|
||||
if model and model.model_entity:
|
||||
models.append({
|
||||
'model_id': fb_uuid,
|
||||
'model_type': model.model_entity.model_type,
|
||||
'provider': model.provider_entity.name if hasattr(model, 'provider_entity') else None,
|
||||
})
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return models
|
||||
|
||||
async def _build_tools(
|
||||
self,
|
||||
manifest_perms: dict[str, list[str]],
|
||||
bound_plugins: list[str] | None,
|
||||
bound_mcp_servers: list[str] | None,
|
||||
query: typing.Any,
|
||||
) -> list[ToolResource]:
|
||||
"""Build tools list with SDK v1 field names."""
|
||||
tools: list[ToolResource] = []
|
||||
|
||||
# Check manifest permission
|
||||
tool_perms = manifest_perms.get('tools', [])
|
||||
if 'list' not in tool_perms and 'call' not in tool_perms:
|
||||
return tools
|
||||
|
||||
# Get tools from query (preproc already resolved this for local-agent)
|
||||
use_funcs = getattr(query, 'use_funcs', [])
|
||||
for tool in use_funcs:
|
||||
# Use SDK v1 field names: tool_name, tool_type, description
|
||||
tools.append({
|
||||
'tool_name': tool.name,
|
||||
'tool_type': None, # Tool type not available in current LLMTool
|
||||
'description': tool.description,
|
||||
})
|
||||
|
||||
return tools
|
||||
|
||||
async def _build_knowledge_bases(
|
||||
self,
|
||||
manifest_perms: dict[str, list[str]],
|
||||
runner_config: dict[str, typing.Any],
|
||||
query: typing.Any,
|
||||
) -> list[KnowledgeBaseResource]:
|
||||
"""Build knowledge bases list with SDK v1 field names."""
|
||||
kb_resources: list[KnowledgeBaseResource] = []
|
||||
|
||||
# Check manifest permission
|
||||
kb_perms = manifest_perms.get('knowledge_bases', [])
|
||||
if 'list' not in kb_perms and 'retrieve' not in kb_perms:
|
||||
return kb_resources
|
||||
|
||||
# Get knowledge base UUIDs from config
|
||||
kb_uuids = runner_config.get('knowledge-bases', [])
|
||||
if not kb_uuids:
|
||||
# Old single KB config
|
||||
old_kb_uuid = runner_config.get('knowledge-base', '')
|
||||
if old_kb_uuid and old_kb_uuid != '__none__':
|
||||
kb_uuids = [old_kb_uuid]
|
||||
|
||||
# Also check query variables (may be modified by plugin PromptPreProcessing)
|
||||
kb_uuids_from_vars = query.variables.get('_knowledge_base_uuids', [])
|
||||
if kb_uuids_from_vars:
|
||||
kb_uuids = kb_uuids_from_vars
|
||||
|
||||
for kb_uuid in kb_uuids:
|
||||
try:
|
||||
kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
|
||||
if kb:
|
||||
# Use SDK v1 field names: kb_id, kb_name, kb_type
|
||||
kb_resources.append({
|
||||
'kb_id': kb_uuid,
|
||||
'kb_name': kb.get_name(),
|
||||
'kb_type': kb.knowledge_base_entity.kb_type if hasattr(kb.knowledge_base_entity, 'kb_type') else None,
|
||||
})
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return kb_resources
|
||||
|
||||
def _build_storage(
|
||||
self,
|
||||
manifest_perms: dict[str, list[str]],
|
||||
) -> StorageResource:
|
||||
"""Build storage permissions with SDK v1 field names."""
|
||||
storage_perms = manifest_perms.get('storage', [])
|
||||
return {
|
||||
'plugin_storage': 'plugin' in storage_perms,
|
||||
'workspace_storage': 'workspace' in storage_perms,
|
||||
}
|
||||
180
src/langbot/pkg/agent/runner/result_normalizer.py
Normal file
180
src/langbot/pkg/agent/runner/result_normalizer.py
Normal file
@@ -0,0 +1,180 @@
|
||||
"""Agent result normalizer for converting SDK v1 AgentRunResult to Pipeline messages."""
|
||||
from __future__ import annotations
|
||||
|
||||
import typing
|
||||
|
||||
from langbot_plugin.api.entities.builtin.provider import message as provider_message
|
||||
|
||||
from ...core import app
|
||||
from .descriptor import AgentRunnerDescriptor
|
||||
from .errors import RunnerExecutionError, RunnerProtocolError
|
||||
|
||||
|
||||
# Maximum size for a single result payload (prevent memory exhaustion)
|
||||
MAX_RESULT_SIZE_BYTES = 1024 * 1024 # 1 MB
|
||||
|
||||
|
||||
class AgentResultNormalizer:
|
||||
"""Normalizer for converting SDK v1 AgentRunResult to Pipeline messages.
|
||||
|
||||
Responsibilities:
|
||||
- Accept only SDK v1 result types (message.delta, message.completed, etc.)
|
||||
- Map message.delta -> MessageChunk
|
||||
- Map message.completed -> Message
|
||||
- Map run.completed (with message) -> Message
|
||||
- Handle run.failed as controlled error
|
||||
- Ignore unknown types with warning
|
||||
- Validate result size
|
||||
- Validate message schema
|
||||
|
||||
Per PROTOCOL_V1.md, accepted types:
|
||||
- message.delta
|
||||
- message.completed
|
||||
- tool.call.started
|
||||
- tool.call.completed
|
||||
- state.updated
|
||||
- run.completed
|
||||
- run.failed
|
||||
- action.requested (log only, don't execute)
|
||||
"""
|
||||
|
||||
ap: app.Application
|
||||
|
||||
def __init__(self, ap: app.Application):
|
||||
self.ap = ap
|
||||
|
||||
async def normalize(
|
||||
self,
|
||||
result_dict: dict[str, typing.Any],
|
||||
descriptor: AgentRunnerDescriptor,
|
||||
) -> provider_message.Message | provider_message.MessageChunk | None:
|
||||
"""Normalize AgentRunResult to Message or MessageChunk.
|
||||
|
||||
Args:
|
||||
result_dict: Raw result dict from plugin runtime
|
||||
descriptor: Runner descriptor for error context
|
||||
|
||||
Returns:
|
||||
Message, MessageChunk, or None (for non-message events)
|
||||
|
||||
Raises:
|
||||
RunnerExecutionError: On run.failed
|
||||
RunnerProtocolError: On invalid result format
|
||||
"""
|
||||
# Validate result type
|
||||
result_type = result_dict.get('type')
|
||||
if not result_type:
|
||||
raise RunnerProtocolError(descriptor.id, 'Missing result type')
|
||||
|
||||
# Validate result size
|
||||
try:
|
||||
import json
|
||||
result_json = json.dumps(result_dict)
|
||||
if len(result_json) > MAX_RESULT_SIZE_BYTES:
|
||||
self.ap.logger.warning(
|
||||
f'Runner {descriptor.id} result too large ({len(result_json)} bytes), truncating'
|
||||
)
|
||||
# Truncate content if possible
|
||||
data = result_dict.get('data', {})
|
||||
if 'chunk' in data or 'message' in data:
|
||||
content = data.get('chunk', {}).get('content', '') or data.get('message', {}).get('content', '')
|
||||
if isinstance(content, str) and len(content) > 10000:
|
||||
# Keep reasonable length
|
||||
data['chunk'] = {'role': 'assistant', 'content': content[:10000] + '...[truncated]'}
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Handle each result type
|
||||
data = result_dict.get('data', {})
|
||||
|
||||
if result_type == 'message.delta':
|
||||
return self._normalize_message_delta(data, descriptor)
|
||||
|
||||
elif result_type == 'message.completed':
|
||||
return self._normalize_message_completed(data, descriptor)
|
||||
|
||||
elif result_type == 'tool.call.started':
|
||||
# Log only, don't yield to pipeline
|
||||
self.ap.logger.debug(
|
||||
f'Runner {descriptor.id} tool call started: {data.get("tool_name", "unknown")}'
|
||||
)
|
||||
return None
|
||||
|
||||
elif result_type == 'tool.call.completed':
|
||||
# Log only, don't yield to pipeline
|
||||
self.ap.logger.debug(
|
||||
f'Runner {descriptor.id} tool call completed: {data.get("tool_name", "unknown")}'
|
||||
)
|
||||
return None
|
||||
|
||||
elif result_type == 'state.updated':
|
||||
# Log for telemetry, don't yield
|
||||
self.ap.logger.debug(
|
||||
f'Runner {descriptor.id} state updated: {data.get("key", "unknown")}={data.get("value", "...")}'
|
||||
)
|
||||
return None
|
||||
|
||||
elif result_type == 'run.completed':
|
||||
# May include final message
|
||||
if 'message' in data:
|
||||
return self._normalize_message_completed(data, descriptor)
|
||||
# If no message, it's just completion signal
|
||||
return None
|
||||
|
||||
elif result_type == 'run.failed':
|
||||
error_msg = data.get('error', 'Unknown error')
|
||||
error_code = data.get('code', 'unknown')
|
||||
retryable = data.get('retryable', False)
|
||||
raise RunnerExecutionError(
|
||||
descriptor.id,
|
||||
f'{error_msg} (code: {error_code})',
|
||||
retryable=retryable,
|
||||
)
|
||||
|
||||
elif result_type == 'action.requested':
|
||||
# Reserved for EBA - log only, don't execute
|
||||
self.ap.logger.info(
|
||||
f'Runner {descriptor.id} requested action (not executed in current phase): '
|
||||
f'{data.get("action", "unknown")}'
|
||||
)
|
||||
return None
|
||||
|
||||
else:
|
||||
# Unknown type - warn and ignore (SDK v1 only)
|
||||
self.ap.logger.warning(
|
||||
f'Runner {descriptor.id} returned unknown result type: {result_type}. '
|
||||
f'Expected SDK v1 types (message.delta, message.completed, run.completed, run.failed, etc.)'
|
||||
)
|
||||
return None
|
||||
|
||||
def _normalize_message_delta(
|
||||
self,
|
||||
data: dict[str, typing.Any],
|
||||
descriptor: AgentRunnerDescriptor,
|
||||
) -> provider_message.MessageChunk:
|
||||
"""Normalize message.delta to MessageChunk."""
|
||||
chunk_data = data.get('chunk', {})
|
||||
if not chunk_data:
|
||||
raise RunnerProtocolError(descriptor.id, 'message.delta missing chunk data')
|
||||
|
||||
try:
|
||||
chunk = provider_message.MessageChunk.model_validate(chunk_data)
|
||||
return chunk
|
||||
except Exception as e:
|
||||
raise RunnerProtocolError(descriptor.id, f'Invalid chunk schema: {e}')
|
||||
|
||||
def _normalize_message_completed(
|
||||
self,
|
||||
data: dict[str, typing.Any],
|
||||
descriptor: AgentRunnerDescriptor,
|
||||
) -> provider_message.Message:
|
||||
"""Normalize message.completed to Message."""
|
||||
message_data = data.get('message', {})
|
||||
if not message_data:
|
||||
raise RunnerProtocolError(descriptor.id, 'message.completed missing message data')
|
||||
|
||||
try:
|
||||
msg = provider_message.Message.model_validate(message_data)
|
||||
return msg
|
||||
except Exception as e:
|
||||
raise RunnerProtocolError(descriptor.id, f'Invalid message schema: {e}')
|
||||
@@ -31,7 +31,7 @@ class PipelineService:
|
||||
self.ap = ap
|
||||
|
||||
async def get_pipeline_metadata(self) -> list[dict]:
|
||||
"""Get pipeline metadata with dynamically loaded plugin runners"""
|
||||
"""Get pipeline metadata with dynamically loaded plugin runners from registry"""
|
||||
import copy
|
||||
|
||||
# Deep copy AI metadata to avoid modifying the original
|
||||
@@ -48,43 +48,20 @@ class PipelineService:
|
||||
# Find the runner select config
|
||||
for config_item in runner_stage.get('config', []):
|
||||
if config_item.get('name') == 'runner':
|
||||
# Get plugin agent runners
|
||||
# Get plugin agent runners from registry
|
||||
try:
|
||||
plugin_runners = await self.ap.plugin_connector.list_agent_runners()
|
||||
runner_options, runner_stages = await self.ap.agent_runner_registry.get_runner_metadata_for_pipeline()
|
||||
|
||||
# Add plugin runners to options
|
||||
for runner in plugin_runners:
|
||||
manifest = runner.get('manifest', {})
|
||||
metadata = manifest.get('metadata', {})
|
||||
for option in runner_options:
|
||||
config_item['options'].append(option)
|
||||
|
||||
# Format: plugin:author/plugin_name/runner_name
|
||||
runner_value = (
|
||||
f'plugin:{runner["plugin_author"]}/{runner["plugin_name"]}/{runner["runner_name"]}'
|
||||
)
|
||||
|
||||
# Add to options
|
||||
config_item['options'].append(
|
||||
{
|
||||
'name': runner_value,
|
||||
'label': metadata.get('label', {runner['runner_name']: runner['runner_name']}),
|
||||
'description': metadata.get('description'),
|
||||
}
|
||||
)
|
||||
|
||||
# Add corresponding stage configuration for this runner
|
||||
spec_config = manifest.get('spec', {}).get('config', [])
|
||||
if spec_config:
|
||||
ai_metadata['stages'].append(
|
||||
{
|
||||
'name': runner_value,
|
||||
'label': metadata.get('label', {runner['runner_name']: runner['runner_name']}),
|
||||
'description': metadata.get('description'),
|
||||
'config': spec_config,
|
||||
}
|
||||
)
|
||||
# Add corresponding stage configuration for each runner
|
||||
for stage_config in runner_stages:
|
||||
ai_metadata['stages'].append(stage_config)
|
||||
|
||||
except Exception as e:
|
||||
self.ap.logger.warning(f'Failed to load plugin agent runners: {e}')
|
||||
self.ap.logger.warning(f'Failed to load plugin agent runners from registry: {e}')
|
||||
|
||||
return [
|
||||
self.ap.pipeline_config_meta_trigger,
|
||||
|
||||
@@ -4,6 +4,7 @@ import logging
|
||||
import asyncio
|
||||
import traceback
|
||||
import os
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from ..platform import botmgr as im_mgr
|
||||
from ..platform.webhook_pusher import WebhookPusher
|
||||
@@ -44,6 +45,9 @@ from ..vector import mgr as vectordb_mgr
|
||||
from ..telemetry import telemetry as telemetry_module
|
||||
from ..survey import manager as survey_module
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from ..agent.runner import AgentRunnerRegistry, AgentRunOrchestrator
|
||||
|
||||
|
||||
class Application:
|
||||
"""Runtime application object and context"""
|
||||
@@ -158,6 +162,11 @@ class Application:
|
||||
|
||||
maintenance_service: maintenance_service.MaintenanceService = None
|
||||
|
||||
# Agent runner subsystem
|
||||
agent_runner_registry: AgentRunnerRegistry = None
|
||||
|
||||
agent_run_orchestrator: AgentRunOrchestrator = None
|
||||
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
|
||||
@@ -36,6 +36,7 @@ from ...vector import mgr as vectordb_mgr
|
||||
from .. import taskmgr
|
||||
from ...telemetry import telemetry as telemetry_module
|
||||
from ...survey import manager as survey_module
|
||||
from ...agent.runner import AgentRunnerRegistry, AgentRunOrchestrator
|
||||
|
||||
|
||||
@stage.stage_class('BuildAppStage')
|
||||
@@ -179,5 +180,12 @@ class BuildAppStage(stage.BootingStage):
|
||||
await plugin_connector_inst.initialize()
|
||||
ap.plugin_connector = plugin_connector_inst
|
||||
|
||||
# Initialize agent runner subsystem
|
||||
agent_runner_registry_inst = AgentRunnerRegistry(ap)
|
||||
ap.agent_runner_registry = agent_runner_registry_inst
|
||||
|
||||
agent_run_orchestrator_inst = AgentRunOrchestrator(ap, agent_runner_registry_inst)
|
||||
ap.agent_run_orchestrator = agent_run_orchestrator_inst
|
||||
|
||||
ctrl = controller.Controller(ap)
|
||||
ap.ctrl = ctrl
|
||||
|
||||
@@ -9,6 +9,12 @@ import langbot_plugin.api.entities.builtin.platform.message as platform_message
|
||||
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
|
||||
import langbot_plugin.api.entities.builtin.platform.events as platform_events
|
||||
|
||||
from ...agent.runner.config_migration import ConfigMigration
|
||||
|
||||
|
||||
# Official local-agent runner ID
|
||||
LOCAL_AGENT_RUNNER_ID = 'plugin:langbot/local-agent/default'
|
||||
|
||||
|
||||
@stage.stage_class('PreProcessor')
|
||||
class PreProcessor(stage.PipelineStage):
|
||||
@@ -31,16 +37,27 @@ class PreProcessor(stage.PipelineStage):
|
||||
stage_inst_name: str,
|
||||
) -> entities.StageProcessResult:
|
||||
"""Process"""
|
||||
selected_runner = query.pipeline_config['ai']['runner']['runner']
|
||||
# Resolve runner ID using ConfigMigration (supports both new and old formats)
|
||||
runner_id = ConfigMigration.resolve_runner_id(query.pipeline_config)
|
||||
|
||||
# Get runner config (from new ai.runner_config or old ai.<runner-name>)
|
||||
runner_config = ConfigMigration.resolve_runner_config(query.pipeline_config, runner_id) if runner_id else {}
|
||||
|
||||
session = await self.ap.sess_mgr.get_session(query)
|
||||
|
||||
# Determine if this is a local-agent runner (built-in LLM capabilities)
|
||||
# Check by runner_id OR by legacy runner field for backward compatibility
|
||||
is_local_agent = runner_id == LOCAL_AGENT_RUNNER_ID or (
|
||||
runner_id is None and
|
||||
query.pipeline_config.get('ai', {}).get('runner', {}).get('runner') == 'local-agent'
|
||||
)
|
||||
|
||||
# When not local-agent, llm_model is None
|
||||
llm_model = None
|
||||
if selected_runner == 'local-agent':
|
||||
if is_local_agent:
|
||||
# Read model config — new format is { primary: str, fallbacks: [str] },
|
||||
# but handle legacy plain string for backward compatibility
|
||||
model_config = query.pipeline_config['ai']['local-agent'].get('model', {})
|
||||
model_config = runner_config.get('model', {})
|
||||
if isinstance(model_config, str):
|
||||
# Legacy format: plain UUID string
|
||||
primary_uuid = model_config
|
||||
@@ -67,10 +84,17 @@ class PreProcessor(stage.PipelineStage):
|
||||
if valid_fallbacks:
|
||||
query.variables['_fallback_model_uuids'] = valid_fallbacks
|
||||
|
||||
# Get prompt config - for local-agent, use runner_config; for others, use default prompt
|
||||
prompt_config = runner_config.get('prompt', [
|
||||
{'role': 'system', 'content': 'You are a helpful assistant.'}
|
||||
]) if is_local_agent else [
|
||||
{'role': 'system', 'content': 'You are a helpful assistant.'}
|
||||
]
|
||||
|
||||
conversation = await self.ap.sess_mgr.get_conversation(
|
||||
query,
|
||||
session,
|
||||
query.pipeline_config['ai']['local-agent']['prompt'],
|
||||
prompt_config,
|
||||
query.pipeline_uuid,
|
||||
query.bot_uuid,
|
||||
)
|
||||
@@ -79,7 +103,7 @@ class PreProcessor(stage.PipelineStage):
|
||||
# been idle for longer than the configured conversation expire time.
|
||||
# The idle window is measured from the last preprocess/update time, not
|
||||
# from the conversation creation time.
|
||||
conversation_expire_time = query.pipeline_config.get('ai', {}).get('runner', {}).get('expire-time', None)
|
||||
conversation_expire_time = ConfigMigration.get_expire_time(query.pipeline_config)
|
||||
now = datetime.datetime.now()
|
||||
if conversation_expire_time is not None and conversation_expire_time > 0:
|
||||
last_update_time = getattr(conversation, 'update_time', None) or getattr(conversation, 'create_time', None)
|
||||
@@ -101,7 +125,7 @@ class PreProcessor(stage.PipelineStage):
|
||||
query.prompt = conversation.prompt.copy()
|
||||
query.messages = conversation.messages.copy()
|
||||
|
||||
if selected_runner == 'local-agent':
|
||||
if is_local_agent:
|
||||
query.use_funcs = []
|
||||
if llm_model:
|
||||
query.use_llm_model_uuid = llm_model.model_entity.uuid
|
||||
@@ -149,7 +173,7 @@ class PreProcessor(stage.PipelineStage):
|
||||
# Check if this model supports vision, if not, remove all images
|
||||
# TODO this checking should be performed in runner, and in this stage, the image should be reserved
|
||||
if (
|
||||
selected_runner == 'local-agent'
|
||||
is_local_agent
|
||||
and llm_model
|
||||
and not llm_model.model_entity.abilities.__contains__('vision')
|
||||
):
|
||||
@@ -162,14 +186,15 @@ class PreProcessor(stage.PipelineStage):
|
||||
content_list: list[provider_message.ContentElement] = []
|
||||
|
||||
plain_text = ''
|
||||
quote_msg = query.pipeline_config['trigger'].get('misc', '').get('combine-quote-message')
|
||||
quote_msg = query.pipeline_config['trigger'].get('misc', {}).get('combine-quote-message', False)
|
||||
|
||||
for me in query.message_chain:
|
||||
if isinstance(me, platform_message.Plain):
|
||||
content_list.append(provider_message.ContentElement.from_text(me.text))
|
||||
plain_text += me.text
|
||||
elif isinstance(me, platform_message.Image):
|
||||
if selected_runner != 'local-agent' or (
|
||||
# Allow images for non-local-agent runners or if local-agent has vision
|
||||
if not is_local_agent or (
|
||||
llm_model and llm_model.model_entity.abilities.__contains__('vision')
|
||||
):
|
||||
if me.base64 is not None:
|
||||
@@ -190,7 +215,7 @@ class PreProcessor(stage.PipelineStage):
|
||||
if isinstance(msg, platform_message.Plain):
|
||||
content_list.append(provider_message.ContentElement.from_text(msg.text))
|
||||
elif isinstance(msg, platform_message.Image):
|
||||
if selected_runner != 'local-agent' or (
|
||||
if not is_local_agent or (
|
||||
llm_model and llm_model.model_entity.abilities.__contains__('vision')
|
||||
):
|
||||
if msg.base64 is not None:
|
||||
@@ -214,9 +239,10 @@ class PreProcessor(stage.PipelineStage):
|
||||
|
||||
# Extract knowledge base UUIDs into query variables so plugins can modify them
|
||||
# during PromptPreProcessing before the runner performs retrieval.
|
||||
kb_uuids = query.pipeline_config['ai']['local-agent'].get('knowledge-bases', [])
|
||||
# Only for local-agent runner
|
||||
kb_uuids = runner_config.get('knowledge-bases', []) if is_local_agent else []
|
||||
if not kb_uuids:
|
||||
old_kb_uuid = query.pipeline_config['ai']['local-agent'].get('knowledge-base', '')
|
||||
old_kb_uuid = runner_config.get('knowledge-base', '') if is_local_agent else ''
|
||||
if old_kb_uuid and old_kb_uuid != '__none__':
|
||||
kb_uuids = [old_kb_uuid]
|
||||
query.variables['_knowledge_base_uuids'] = list(kb_uuids)
|
||||
@@ -237,4 +263,4 @@ class PreProcessor(stage.PipelineStage):
|
||||
query.prompt.messages = event_ctx.event.default_prompt
|
||||
query.messages = event_ctx.event.prompt
|
||||
|
||||
return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
|
||||
return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
|
||||
@@ -9,99 +9,28 @@ from datetime import datetime
|
||||
|
||||
from .. import handler
|
||||
from ... import entities
|
||||
from ....provider import runner as runner_module
|
||||
|
||||
import langbot_plugin.api.entities.events as events
|
||||
from ....utils import importutil, constants, runner as runner_utils
|
||||
from ....provider import runners
|
||||
from ....utils import constants, runner as runner_utils
|
||||
import langbot_plugin.api.entities.builtin.provider.session as provider_session
|
||||
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
|
||||
import langbot_plugin.api.entities.builtin.provider.message as provider_message
|
||||
from langbot_plugin.api.entities.builtin.agent_runner.context import AgentRunContext
|
||||
|
||||
|
||||
importutil.import_modules_in_pkg(runners)
|
||||
|
||||
|
||||
class PluginAgentRunnerWrapper(runner_module.RequestRunner):
|
||||
"""Wrapper to run AgentRunner from plugin"""
|
||||
|
||||
def __init__(self, ap, plugin_author: str, plugin_name: str, runner_name: str, pipeline_config: dict):
|
||||
super().__init__(ap, pipeline_config)
|
||||
self.plugin_author = plugin_author
|
||||
self.plugin_name = plugin_name
|
||||
self.runner_name = runner_name
|
||||
self.name = f'plugin:{plugin_author}/{plugin_name}/{runner_name}'
|
||||
|
||||
async def run(
|
||||
self, query: pipeline_query.Query
|
||||
) -> typing.AsyncGenerator[provider_message.Message | provider_message.MessageChunk, None]:
|
||||
"""Run the plugin agent runner"""
|
||||
|
||||
# Build AgentRunContext
|
||||
context = AgentRunContext(
|
||||
query_id=query.query_id,
|
||||
session=query.session,
|
||||
messages=query.messages,
|
||||
user_message=query.user_message.content[0]
|
||||
if isinstance(query.user_message.content, list)
|
||||
else provider_message.ContentElement.from_text(query.user_message.content),
|
||||
use_funcs=query.use_funcs,
|
||||
extra_config=self.pipeline_config.get('ai', {}).get(self.runner_name, {}),
|
||||
)
|
||||
|
||||
# Call plugin connector to run agent
|
||||
async for result_dict in self.ap.plugin_connector.run_agent(
|
||||
plugin_author=self.plugin_author,
|
||||
plugin_name=self.plugin_name,
|
||||
runner_name=self.runner_name,
|
||||
context=context.model_dump(),
|
||||
):
|
||||
# Convert result to Message/MessageChunk
|
||||
result_type = result_dict.get('type')
|
||||
|
||||
if result_type == 'chunk':
|
||||
# Stream chunk
|
||||
chunk_data = result_dict.get('message_chunk')
|
||||
if chunk_data:
|
||||
yield provider_message.MessageChunk.model_validate(chunk_data)
|
||||
|
||||
elif result_type == 'text':
|
||||
# Text content
|
||||
content = result_dict.get('content', '')
|
||||
yield provider_message.MessageChunk(
|
||||
role='assistant',
|
||||
content=content,
|
||||
)
|
||||
|
||||
elif result_type == 'tool_call':
|
||||
# Tool call notification (may not need to yield anything here)
|
||||
pass
|
||||
|
||||
elif result_type == 'finish':
|
||||
# Final message
|
||||
message_data = result_dict.get('message')
|
||||
if message_data:
|
||||
yield provider_message.Message.model_validate(message_data)
|
||||
else:
|
||||
# Fallback: create message from content
|
||||
content = result_dict.get('content', '')
|
||||
yield provider_message.Message(
|
||||
role='assistant',
|
||||
content=content,
|
||||
)
|
||||
|
||||
|
||||
class ChatMessageHandler(handler.MessageHandler):
|
||||
"""Chat message handler using AgentRunOrchestrator.
|
||||
|
||||
This handler delegates all runner execution to the agent_run_orchestrator,
|
||||
which resolves runner ID, builds context, invokes plugin runtime,
|
||||
and normalizes results.
|
||||
"""
|
||||
|
||||
async def handle(
|
||||
self,
|
||||
query: pipeline_query.Query,
|
||||
) -> typing.AsyncGenerator[entities.StageProcessResult, None]:
|
||||
"""处理"""
|
||||
# 调API
|
||||
# 生成器
|
||||
|
||||
# 触发插件事件
|
||||
"""Handle chat message by delegating to AgentRunOrchestrator."""
|
||||
# Trigger plugin event
|
||||
event_class = (
|
||||
events.PersonNormalMessageReceived
|
||||
if query.launcher_type == provider_session.LauncherTypes.PERSON
|
||||
@@ -122,7 +51,7 @@ class ChatMessageHandler(handler.MessageHandler):
|
||||
bound_plugins = query.variables.get('_pipeline_bound_plugins', None)
|
||||
event_ctx = await self.ap.plugin_connector.emit_event(event, bound_plugins)
|
||||
|
||||
is_create_card = False # 判断下是否需要创建流式卡片
|
||||
is_create_card = False # Track if streaming card was created
|
||||
|
||||
if event_ctx.is_prevented_default():
|
||||
if event_ctx.event.reply_message_chain is not None:
|
||||
@@ -153,103 +82,85 @@ class ChatMessageHandler(handler.MessageHandler):
|
||||
is_stream = False
|
||||
|
||||
try:
|
||||
runner_name = query.pipeline_config['ai']['runner']['runner']
|
||||
|
||||
# Check if it's a built-in runner
|
||||
runner = None
|
||||
for r in runner_module.preregistered_runners:
|
||||
if r.name == runner_name:
|
||||
runner = r(self.ap, query.pipeline_config)
|
||||
break
|
||||
|
||||
# If not found in built-in runners, check plugin runners
|
||||
if runner is None:
|
||||
# Parse runner name: format is "plugin:author/plugin_name/runner_name"
|
||||
if runner_name.startswith('plugin:'):
|
||||
parts = runner_name[7:].split('/') # Remove "plugin:" prefix
|
||||
if len(parts) == 3:
|
||||
plugin_author, plugin_name, component_runner_name = parts
|
||||
runner = PluginAgentRunnerWrapper(
|
||||
self.ap, plugin_author, plugin_name, component_runner_name, query.pipeline_config
|
||||
)
|
||||
else:
|
||||
raise ValueError(
|
||||
f'Invalid plugin runner name format: {runner_name}. Expected: plugin:author/name/runner'
|
||||
)
|
||||
else:
|
||||
raise ValueError(f'Request Runner not found: {runner_name}')
|
||||
|
||||
# Mark start time for telemetry
|
||||
start_ts = time.time()
|
||||
|
||||
if is_stream:
|
||||
resp_message_id = uuid.uuid4()
|
||||
chunk_count = 0 # Track streaming chunks to reduce excessive logging
|
||||
# Create a single resp_message_id for the entire streaming response
|
||||
resp_message_id = uuid.uuid4()
|
||||
|
||||
async for result in runner.run(query):
|
||||
result.resp_message_id = str(resp_message_id)
|
||||
# Use AgentRunOrchestrator to run the agent
|
||||
# This replaces direct runner lookup and PluginAgentRunnerWrapper
|
||||
async for result in self.ap.agent_run_orchestrator.run_from_query(query):
|
||||
result.resp_message_id = str(resp_message_id)
|
||||
|
||||
# For streaming mode, pop previous response before adding new chunk
|
||||
# This allows incremental card updates
|
||||
if is_stream:
|
||||
if query.resp_messages:
|
||||
query.resp_messages.pop()
|
||||
if query.resp_message_chain:
|
||||
query.resp_message_chain.pop()
|
||||
# 此时连接外部 AI 服务正常,创建卡片
|
||||
if not is_create_card: # 只有不是第一次才创建卡片
|
||||
await query.adapter.create_message_card(str(resp_message_id), query.message_event)
|
||||
is_create_card = True
|
||||
query.resp_messages.append(result)
|
||||
|
||||
chunk_count += 1
|
||||
# Only log every 10th chunk to reduce excessive logging during streaming
|
||||
# This prevents memory overflow from thousands of log entries per conversation
|
||||
# First chunk uses INFO level to confirm connection establishment
|
||||
if chunk_count == 1:
|
||||
self.ap.logger.info(
|
||||
f'Conversation({query.query_id}) Streaming started: {self.cut_str(result.readable_str())}'
|
||||
)
|
||||
elif chunk_count % 10 == 0:
|
||||
self.ap.logger.debug(
|
||||
f'Conversation({query.query_id}) Streaming chunk {chunk_count}: {self.cut_str(result.readable_str())}'
|
||||
)
|
||||
# Create streaming card on first result (connection established)
|
||||
if is_stream and not is_create_card:
|
||||
await query.adapter.create_message_card(str(resp_message_id), query.message_event)
|
||||
is_create_card = True
|
||||
|
||||
if result.content is not None:
|
||||
text_length += len(result.content)
|
||||
|
||||
yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
|
||||
|
||||
# Log final summary after streaming completes
|
||||
self.ap.logger.info(
|
||||
f'Conversation({query.query_id}) Streaming completed: {chunk_count} chunks, {text_length} chars'
|
||||
)
|
||||
|
||||
else:
|
||||
async for result in runner.run(query):
|
||||
query.resp_messages.append(result)
|
||||
query.resp_messages.append(result)
|
||||
|
||||
# Logging (reduce verbosity for streaming chunks)
|
||||
if not is_stream:
|
||||
self.ap.logger.info(
|
||||
f'Conversation({query.query_id}) Response: {self.cut_str(result.readable_str())}'
|
||||
)
|
||||
|
||||
if result.content is not None:
|
||||
text_length += len(result.content)
|
||||
if result.content is not None:
|
||||
text_length += len(result.content)
|
||||
|
||||
yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
|
||||
yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
|
||||
|
||||
# Log final summary after streaming completes
|
||||
if is_stream:
|
||||
chunk_count = len(query.resp_messages)
|
||||
self.ap.logger.info(
|
||||
f'Conversation({query.query_id}) Streaming completed: {chunk_count} chunks, {text_length} chars'
|
||||
)
|
||||
|
||||
# Update conversation history
|
||||
query.session.using_conversation.messages.append(query.user_message)
|
||||
|
||||
query.session.using_conversation.messages.extend(query.resp_messages)
|
||||
|
||||
except Exception as e:
|
||||
# Import orchestrator errors for specific handling
|
||||
from ....agent.runner.errors import (
|
||||
RunnerNotFoundError,
|
||||
RunnerNotAuthorizedError,
|
||||
RunnerExecutionError,
|
||||
)
|
||||
|
||||
error_info = f'{traceback.format_exc()}'
|
||||
self.ap.logger.error(f'Conversation({query.query_id}) Request Failed: {error_info}')
|
||||
traceback.print_exc()
|
||||
|
||||
exception_handling = query.pipeline_config['output']['misc'].get('exception-handling', 'show-hint')
|
||||
# Handle specific runner errors with appropriate messages
|
||||
if isinstance(e, RunnerNotFoundError):
|
||||
user_notice = f'Agent runner not found: {e.runner_id}'
|
||||
elif isinstance(e, RunnerNotAuthorizedError):
|
||||
user_notice = 'Agent runner not authorized for this pipeline'
|
||||
elif isinstance(e, RunnerExecutionError):
|
||||
if e.retryable:
|
||||
user_notice = 'Agent runner temporarily unavailable. Please try again.'
|
||||
else:
|
||||
user_notice = 'Agent runner execution failed.'
|
||||
else:
|
||||
# Use existing exception handling
|
||||
exception_handling = query.pipeline_config['output']['misc'].get('exception-handling', 'show-hint')
|
||||
|
||||
if exception_handling == 'show-error':
|
||||
user_notice = f'{e}'
|
||||
elif exception_handling == 'show-hint':
|
||||
user_notice = query.pipeline_config['output']['misc'].get('failure-hint', 'Request failed.')
|
||||
else: # hide
|
||||
user_notice = None
|
||||
if exception_handling == 'show-error':
|
||||
user_notice = f'{e}'
|
||||
elif exception_handling == 'show-hint':
|
||||
user_notice = query.pipeline_config['output']['misc'].get('failure-hint', 'Request failed.')
|
||||
else: # hide
|
||||
user_notice = None
|
||||
|
||||
yield entities.StageProcessResult(
|
||||
result_type=entities.ResultType.INTERRUPT,
|
||||
@@ -259,7 +170,7 @@ class ChatMessageHandler(handler.MessageHandler):
|
||||
debug_notice=traceback.format_exc(),
|
||||
)
|
||||
finally:
|
||||
# Telemetry reporting: collect minimal per-query execution info and send asynchronously
|
||||
# Telemetry reporting
|
||||
try:
|
||||
end_ts = time.time()
|
||||
duration_ms = None
|
||||
@@ -267,16 +178,14 @@ class ChatMessageHandler(handler.MessageHandler):
|
||||
duration_ms = int((end_ts - start_ts) * 1000)
|
||||
|
||||
adapter_name = query.adapter.__class__.__name__ if hasattr(query, 'adapter') else None
|
||||
runner_name = (
|
||||
query.pipeline_config.get('ai', {}).get('runner', {}).get('runner')
|
||||
if query.pipeline_config
|
||||
else None
|
||||
)
|
||||
|
||||
# Model name if using localagent
|
||||
# Use orchestrator to resolve runner ID for telemetry
|
||||
runner_name = self.ap.agent_run_orchestrator.resolve_runner_id_for_telemetry(query)
|
||||
|
||||
# Model name if available
|
||||
model_name = None
|
||||
try:
|
||||
if runner_name == 'local-agent' and getattr(query, 'use_llm_model_uuid', None):
|
||||
if getattr(query, 'use_llm_model_uuid', None):
|
||||
m = await self.ap.model_mgr.get_model_by_uuid(query.use_llm_model_uuid)
|
||||
if m and getattr(m, 'model_entity', None):
|
||||
model_name = getattr(m.model_entity, 'name', None)
|
||||
@@ -286,7 +195,7 @@ class ChatMessageHandler(handler.MessageHandler):
|
||||
pipeline_plugins = query.variables.get('_pipeline_bound_plugins', None)
|
||||
|
||||
runner_category = runner_utils.get_runner_category_from_runner(
|
||||
runner_name, runner, query.pipeline_config
|
||||
runner_name, None, query.pipeline_config
|
||||
)
|
||||
|
||||
payload = {
|
||||
@@ -304,7 +213,6 @@ class ChatMessageHandler(handler.MessageHandler):
|
||||
'timestamp': datetime.utcnow().isoformat(),
|
||||
}
|
||||
|
||||
# Send telemetry asynchronously and do not block pipeline via app's telemetry manager
|
||||
await self.ap.telemetry.start_send_task(payload)
|
||||
|
||||
# Trigger survey event on first successful non-WebSocket response
|
||||
@@ -312,5 +220,4 @@ class ChatMessageHandler(handler.MessageHandler):
|
||||
if self.ap.survey:
|
||||
await self.ap.survey.trigger_event('first_bot_response_success')
|
||||
except Exception as ex:
|
||||
# Ensure telemetry issues do not affect normal flow
|
||||
self.ap.logger.warning(f'Failed to send telemetry: {ex}')
|
||||
self.ap.logger.warning(f'Failed to send telemetry: {ex}')
|
||||
@@ -600,14 +600,16 @@ class PluginRuntimeConnector:
|
||||
yield cmd_ret
|
||||
|
||||
# AgentRunner methods
|
||||
async def list_agent_runners(self, bound_plugins: list[str] | None = None) -> list[ComponentManifest]:
|
||||
"""List all available AgentRunner components."""
|
||||
async def list_agent_runners(self, bound_plugins: list[str] | None = None) -> list[dict[str, Any]]:
|
||||
"""List all available AgentRunner components.
|
||||
|
||||
Returns list of dicts with plugin_author, plugin_name, runner_name, manifest, etc.
|
||||
"""
|
||||
if not self.is_enable_plugin:
|
||||
return []
|
||||
|
||||
runners_data = await self.handler.list_agent_runners(include_plugins=bound_plugins)
|
||||
runners = [ComponentManifest.model_validate(runner) for runner in runners_data]
|
||||
return runners
|
||||
return runners_data
|
||||
|
||||
async def run_agent(
|
||||
self,
|
||||
@@ -625,10 +627,18 @@ class PluginRuntimeConnector:
|
||||
context: AgentRunContext as dict
|
||||
|
||||
Yields:
|
||||
AgentRunReturn results as dicts
|
||||
AgentRunResult dicts per Protocol v1
|
||||
"""
|
||||
if not self.is_enable_plugin:
|
||||
yield {'type': 'finish', 'finish_reason': 'error', 'content': 'Plugin system is disabled'}
|
||||
# Return v1 protocol run.failed
|
||||
yield {
|
||||
'type': 'run.failed',
|
||||
'data': {
|
||||
'error': 'Plugin system is disabled',
|
||||
'code': 'plugin.disabled',
|
||||
'retryable': False,
|
||||
},
|
||||
}
|
||||
return
|
||||
|
||||
gen = self.handler.run_agent(plugin_author, plugin_name, runner_name, context)
|
||||
|
||||
@@ -419,76 +419,6 @@ class RuntimeConnectionHandler(handler.Handler):
|
||||
message=f'Failed to execute tool {tool_name}: {e}',
|
||||
)
|
||||
|
||||
@self.action(PluginToRuntimeAction.RETRIEVE_KNOWLEDGE)
|
||||
async def retrieve_knowledge(data: dict[str, Any]) -> handler.ActionResponse:
|
||||
"""Retrieve knowledge from a knowledge base"""
|
||||
kb_uuid = data['kb_uuid']
|
||||
query = data['query']
|
||||
top_k = data.get('top_k', 5)
|
||||
|
||||
try:
|
||||
kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
|
||||
if kb is None:
|
||||
return handler.ActionResponse.error(
|
||||
message=f'Knowledge base with uuid {kb_uuid} not found',
|
||||
)
|
||||
|
||||
results = await kb.retrieve(query=query, top_k=top_k)
|
||||
|
||||
# Convert results to dict format
|
||||
results_data = [
|
||||
{
|
||||
'id': r.id,
|
||||
'content': [c.model_dump() for c in r.content],
|
||||
'metadata': r.metadata,
|
||||
}
|
||||
for r in results
|
||||
]
|
||||
|
||||
return handler.ActionResponse.success(
|
||||
data={
|
||||
'results': results_data,
|
||||
},
|
||||
)
|
||||
except Exception as e:
|
||||
traceback.print_exc()
|
||||
return handler.ActionResponse.error(
|
||||
message=f'Failed to retrieve knowledge: {e}',
|
||||
)
|
||||
|
||||
@self.action(PluginToRuntimeAction.INVOKE_EMBEDDING)
|
||||
async def invoke_embedding(data: dict[str, Any]) -> handler.ActionResponse:
|
||||
"""Invoke an embedding model"""
|
||||
embedding_model_uuid = data['embedding_model_uuid']
|
||||
texts = data['texts']
|
||||
|
||||
try:
|
||||
embedding_model = await self.ap.model_mgr.get_embedding_model_by_uuid(embedding_model_uuid)
|
||||
if embedding_model is None:
|
||||
return handler.ActionResponse.error(
|
||||
message=f'Embedding model with uuid {embedding_model_uuid} not found',
|
||||
)
|
||||
|
||||
# Call embedding model to generate embeddings
|
||||
embeddings = []
|
||||
for text in texts:
|
||||
embedding = await embedding_model.provider.invoke_embedding(
|
||||
model=embedding_model,
|
||||
text=text,
|
||||
)
|
||||
embeddings.append(embedding)
|
||||
|
||||
return handler.ActionResponse.success(
|
||||
data={
|
||||
'embeddings': embeddings,
|
||||
},
|
||||
)
|
||||
except Exception as e:
|
||||
traceback.print_exc()
|
||||
return handler.ActionResponse.error(
|
||||
message=f'Failed to invoke embedding model: {e}',
|
||||
)
|
||||
|
||||
@self.action(RuntimeToLangBotAction.SET_BINARY_STORAGE)
|
||||
async def set_binary_storage(data: dict[str, Any]) -> handler.ActionResponse:
|
||||
"""Set binary storage"""
|
||||
@@ -856,10 +786,11 @@ class RuntimeConnectionHandler(handler.Handler):
|
||||
# Validate kb_id is in pipeline's allowed list
|
||||
allowed_kb_uuids = []
|
||||
if query.pipeline_config:
|
||||
local_agent_config = query.pipeline_config.get('ai', {}).get('local-agent', {})
|
||||
allowed_kb_uuids = local_agent_config.get('knowledge-bases', [])
|
||||
from langbot.pkg.agent.runner.config_migration import ConfigMigration
|
||||
runner_config = ConfigMigration.resolve_runner_config(query.pipeline_config, None)
|
||||
allowed_kb_uuids = runner_config.get('knowledge-bases', [])
|
||||
if not allowed_kb_uuids:
|
||||
old_kb_uuid = local_agent_config.get('knowledge-base', '')
|
||||
old_kb_uuid = runner_config.get('knowledge-base', '')
|
||||
if old_kb_uuid and old_kb_uuid != '__none__':
|
||||
allowed_kb_uuids = [old_kb_uuid]
|
||||
|
||||
@@ -1025,6 +956,55 @@ class RuntimeConnectionHandler(handler.Handler):
|
||||
|
||||
return result['tools']
|
||||
|
||||
async def list_agent_runners(self, include_plugins: list[str] | None = None) -> list[dict[str, Any]]:
|
||||
"""List agent runners from plugin runtime.
|
||||
|
||||
Returns list of dicts with:
|
||||
- plugin_author
|
||||
- plugin_name
|
||||
- runner_name
|
||||
- runner_description
|
||||
- manifest
|
||||
- protocol_version
|
||||
- capabilities
|
||||
- permissions
|
||||
- config
|
||||
"""
|
||||
result = await self.call_action(
|
||||
LangBotToRuntimeAction.LIST_AGENT_RUNNERS,
|
||||
{
|
||||
'include_plugins': include_plugins,
|
||||
},
|
||||
timeout=20,
|
||||
)
|
||||
|
||||
return result['runners']
|
||||
|
||||
async def run_agent(
|
||||
self,
|
||||
plugin_author: str,
|
||||
plugin_name: str,
|
||||
runner_name: str,
|
||||
context: dict[str, Any],
|
||||
) -> typing.AsyncGenerator[dict[str, Any], None]:
|
||||
"""Run an AgentRunner component.
|
||||
|
||||
Yields AgentRunResult dicts per Protocol v1.
|
||||
"""
|
||||
gen = self.call_action_generator(
|
||||
LangBotToRuntimeAction.RUN_AGENT,
|
||||
{
|
||||
'plugin_author': plugin_author,
|
||||
'plugin_name': plugin_name,
|
||||
'runner_name': runner_name,
|
||||
'context': context,
|
||||
},
|
||||
timeout=300,
|
||||
)
|
||||
|
||||
async for ret in gen:
|
||||
yield ret
|
||||
|
||||
async def get_plugin_icon(self, plugin_author: str, plugin_name: str) -> dict[str, Any]:
|
||||
"""Get plugin icon"""
|
||||
result = await self.call_action(
|
||||
|
||||
2
tests/unit_tests/agent/__init__.py
Normal file
2
tests/unit_tests/agent/__init__.py
Normal file
@@ -0,0 +1,2 @@
|
||||
"""Tests for agent runner subsystem."""
|
||||
from __future__ import annotations
|
||||
553
tests/unit_tests/agent/test_chat_handler.py
Normal file
553
tests/unit_tests/agent/test_chat_handler.py
Normal file
@@ -0,0 +1,553 @@
|
||||
"""Tests for ChatMessageHandler behavior with AgentRunOrchestrator.
|
||||
|
||||
Tests focus on:
|
||||
- Streaming mode behavior (single resp_message_id, pop/append pattern)
|
||||
- Non-streaming mode behavior (no pop)
|
||||
- Orchestrator invocation
|
||||
- Error handling for RunnerNotFoundError, RunnerExecutionError
|
||||
|
||||
Avoids circular imports by using proper import structure.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import uuid
|
||||
import pytest
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
from langbot.pkg.agent.runner.errors import (
|
||||
RunnerNotFoundError,
|
||||
RunnerExecutionError,
|
||||
RunnerNotAuthorizedError,
|
||||
)
|
||||
from langbot.pkg.agent.runner.config_migration import ConfigMigration
|
||||
|
||||
|
||||
# Define mock classes in dependency order (no forward references needed)
|
||||
|
||||
class MockLauncherType:
|
||||
value = 'person'
|
||||
|
||||
|
||||
class MockConversation:
|
||||
uuid = 'conv-uuid'
|
||||
messages = []
|
||||
|
||||
|
||||
class MockMessage:
|
||||
role = 'user'
|
||||
content = 'Hello'
|
||||
|
||||
|
||||
class MockAdapter:
|
||||
is_stream = False
|
||||
|
||||
async def is_stream_output_supported(self):
|
||||
return self.is_stream
|
||||
|
||||
async def create_message_card(self, resp_message_id, message_event):
|
||||
pass
|
||||
|
||||
|
||||
class MockSession:
|
||||
launcher_type = MockLauncherType()
|
||||
launcher_id = 'user123'
|
||||
using_conversation = MockConversation()
|
||||
|
||||
|
||||
class MockQuery:
|
||||
"""Mock Query for testing."""
|
||||
def __init__(self):
|
||||
self.query_id = 1
|
||||
self.launcher_type = MockLauncherType()
|
||||
self.launcher_id = 'user123'
|
||||
self.sender_id = 'user123'
|
||||
self.bot_uuid = 'bot-uuid'
|
||||
self.pipeline_uuid = 'pipeline-uuid'
|
||||
self.pipeline_config = {
|
||||
'ai': {
|
||||
'runner': {
|
||||
'id': 'plugin:langbot/local-agent/default',
|
||||
},
|
||||
'runner_config': {},
|
||||
},
|
||||
'output': {
|
||||
'misc': {
|
||||
'exception-handling': 'show-hint',
|
||||
'failure-hint': 'Request failed.',
|
||||
},
|
||||
},
|
||||
}
|
||||
self.variables = {}
|
||||
self.session = MockSession()
|
||||
self.user_message = MockMessage()
|
||||
self.messages = []
|
||||
self.resp_messages = []
|
||||
self.resp_message_chain = None
|
||||
self.adapter = MockAdapter()
|
||||
self.message_event = MagicMock()
|
||||
self.message_chain = MagicMock()
|
||||
|
||||
|
||||
class MockMessageChunk:
|
||||
"""Mock MessageChunk for testing."""
|
||||
def __init__(self, content, resp_message_id=None):
|
||||
self.role = 'assistant'
|
||||
self.content = content
|
||||
self.resp_message_id = resp_message_id
|
||||
self.is_final = False
|
||||
|
||||
def readable_str(self):
|
||||
return self.content
|
||||
|
||||
|
||||
class MockEventContext:
|
||||
"""Mock event context for testing."""
|
||||
def __init__(self, prevented=False, reply_message_chain=None, user_message_alter=None):
|
||||
self._prevented = prevented
|
||||
self.event = MagicMock()
|
||||
self.event.reply_message_chain = reply_message_chain
|
||||
self.event.user_message_alter = user_message_alter
|
||||
|
||||
def is_prevented_default(self):
|
||||
return self._prevented
|
||||
|
||||
|
||||
class MockAgentRunOrchestrator:
|
||||
"""Mock AgentRunOrchestrator for testing."""
|
||||
def __init__(self, chunks=None, error=None):
|
||||
self._chunks = chunks or []
|
||||
self._error = error
|
||||
|
||||
async def run_from_query(self, query):
|
||||
"""Async generator that yields chunks or raises error."""
|
||||
if self._error:
|
||||
raise self._error
|
||||
for chunk in self._chunks:
|
||||
yield chunk
|
||||
|
||||
def resolve_runner_id_for_telemetry(self, query):
|
||||
return 'plugin:langbot/local-agent/default'
|
||||
|
||||
|
||||
class MockApplication:
|
||||
"""Mock Application for testing."""
|
||||
def __init__(self, orchestrator=None):
|
||||
self.agent_run_orchestrator = orchestrator or MockAgentRunOrchestrator()
|
||||
self.logger = MagicMock()
|
||||
self.logger.info = MagicMock()
|
||||
self.logger.debug = MagicMock()
|
||||
self.logger.warning = MagicMock()
|
||||
self.logger.error = MagicMock()
|
||||
|
||||
# Mock plugin_connector
|
||||
self.plugin_connector = MagicMock()
|
||||
self.plugin_connector.emit_event = AsyncMock(return_value=MockEventContext())
|
||||
|
||||
# Mock telemetry
|
||||
self.telemetry = MagicMock()
|
||||
self.telemetry.start_send_task = AsyncMock()
|
||||
|
||||
# Mock survey
|
||||
self.survey = MagicMock()
|
||||
self.survey.trigger_event = AsyncMock()
|
||||
|
||||
# Mock model_mgr
|
||||
self.model_mgr = MagicMock()
|
||||
self.model_mgr.get_model_by_uuid = AsyncMock(return_value=None)
|
||||
|
||||
|
||||
class TestStreamingBehavior:
|
||||
"""Tests for streaming mode behavior."""
|
||||
|
||||
def test_single_resp_message_id_for_streaming(self):
|
||||
"""Streaming mode should use single resp_message_id for entire response."""
|
||||
# Simulate the streaming logic: resp_message_id created outside loop
|
||||
resp_message_id = uuid.uuid4()
|
||||
|
||||
chunks = ['Hello', ' World', '!']
|
||||
resp_messages = []
|
||||
|
||||
for chunk in chunks:
|
||||
result = MockMessageChunk(chunk)
|
||||
result.resp_message_id = str(resp_message_id)
|
||||
|
||||
# Pop old chunk (streaming behavior)
|
||||
if resp_messages:
|
||||
resp_messages.pop()
|
||||
resp_messages.append(result)
|
||||
|
||||
# All chunks should have same resp_message_id
|
||||
assert len(resp_messages) == 1 # Only last chunk remains after pop/append
|
||||
assert resp_messages[0].resp_message_id == str(resp_message_id)
|
||||
|
||||
def test_pop_before_append_in_streaming(self):
|
||||
"""Streaming mode should pop old chunk before appending new."""
|
||||
resp_message_id = uuid.uuid4()
|
||||
resp_messages = []
|
||||
|
||||
# First chunk - no pop
|
||||
chunk1 = MockMessageChunk('Hello')
|
||||
chunk1.resp_message_id = str(resp_message_id)
|
||||
resp_messages.append(chunk1)
|
||||
assert len(resp_messages) == 1
|
||||
|
||||
# Second chunk - pop first, then append
|
||||
if resp_messages:
|
||||
resp_messages.pop()
|
||||
chunk2 = MockMessageChunk('Hello World')
|
||||
chunk2.resp_message_id = str(resp_message_id)
|
||||
resp_messages.append(chunk2)
|
||||
assert len(resp_messages) == 1
|
||||
assert resp_messages[0].content == 'Hello World'
|
||||
|
||||
def test_non_streaming_no_pop(self):
|
||||
"""Non-streaming mode should NOT pop previous responses."""
|
||||
resp_messages = []
|
||||
|
||||
# First message
|
||||
msg1 = MockMessageChunk('Response 1')
|
||||
resp_messages.append(msg1)
|
||||
assert len(resp_messages) == 1
|
||||
|
||||
# Second message - should NOT pop in non-streaming
|
||||
msg2 = MockMessageChunk('Response 2')
|
||||
resp_messages.append(msg2)
|
||||
assert len(resp_messages) == 2
|
||||
|
||||
|
||||
class TestConfigMigrationInChatHandler:
|
||||
"""Tests for ConfigMigration usage in chat handler context."""
|
||||
|
||||
def test_resolve_runner_id_from_pipeline_config(self):
|
||||
"""Chat handler should use ConfigMigration to resolve runner ID."""
|
||||
pipeline_config = {
|
||||
'ai': {
|
||||
'runner': {
|
||||
'id': 'plugin:langbot/local-agent/default',
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
runner_id = ConfigMigration.resolve_runner_id(pipeline_config)
|
||||
assert runner_id == 'plugin:langbot/local-agent/default'
|
||||
|
||||
def test_resolve_runner_id_from_old_format(self):
|
||||
"""ConfigMigration should handle old runner format."""
|
||||
pipeline_config = {
|
||||
'ai': {
|
||||
'runner': {
|
||||
'runner': 'local-agent',
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
runner_id = ConfigMigration.resolve_runner_id(pipeline_config)
|
||||
assert runner_id == 'plugin:langbot/local-agent/default'
|
||||
|
||||
|
||||
class TestErrorHandling:
|
||||
"""Tests for orchestrator error handling."""
|
||||
|
||||
def test_runner_not_found_error_properties(self):
|
||||
"""RunnerNotFoundError should have runner_id property."""
|
||||
error = RunnerNotFoundError('plugin:notexist/unknown/default')
|
||||
assert error.runner_id == 'plugin:notexist/unknown/default'
|
||||
assert 'not found' in str(error)
|
||||
|
||||
def test_runner_execution_error_retryable(self):
|
||||
"""RunnerExecutionError should have retryable property."""
|
||||
error = RunnerExecutionError(
|
||||
'plugin:langbot/local-agent/default',
|
||||
'Upstream timeout',
|
||||
retryable=True,
|
||||
)
|
||||
assert error.runner_id == 'plugin:langbot/local-agent/default'
|
||||
assert error.retryable is True
|
||||
assert 'timeout' in str(error)
|
||||
|
||||
def test_runner_execution_error_not_retryable(self):
|
||||
"""RunnerExecutionError can be non-retryable."""
|
||||
error = RunnerExecutionError(
|
||||
'plugin:langbot/local-agent/default',
|
||||
'Configuration error',
|
||||
retryable=False,
|
||||
)
|
||||
assert error.retryable is False
|
||||
|
||||
def test_runner_not_authorized_error_properties(self):
|
||||
"""RunnerNotAuthorizedError should have bound_plugins property."""
|
||||
error = RunnerNotAuthorizedError(
|
||||
'plugin:langbot/local-agent/default',
|
||||
['langbot/dify-agent'],
|
||||
)
|
||||
assert error.runner_id == 'plugin:langbot/local-agent/default'
|
||||
assert error.bound_plugins == ['langbot/dify-agent']
|
||||
|
||||
|
||||
class TestChatHandlerImports:
|
||||
"""Test that chat handler can be imported without circular import."""
|
||||
|
||||
def test_import_chat_handler_module(self):
|
||||
"""Import chat handler module should work."""
|
||||
# This test verifies the import works without circular dependency
|
||||
from langbot.pkg.pipeline.process.handlers import chat
|
||||
assert chat.ChatMessageHandler is not None
|
||||
|
||||
def test_chat_handler_class_exists(self):
|
||||
"""ChatMessageHandler class should be defined."""
|
||||
from langbot.pkg.pipeline.process.handlers.chat import ChatMessageHandler
|
||||
assert ChatMessageHandler.__name__ == 'ChatMessageHandler'
|
||||
|
||||
def test_chat_handler_has_handle_method(self):
|
||||
"""ChatMessageHandler should have async generator handle method."""
|
||||
from langbot.pkg.pipeline.process.handlers.chat import ChatMessageHandler
|
||||
assert hasattr(ChatMessageHandler, 'handle')
|
||||
# handle returns AsyncGenerator, so check for async generator function
|
||||
import inspect
|
||||
assert inspect.isasyncgenfunction(ChatMessageHandler.handle)
|
||||
|
||||
|
||||
class TestChatHandlerAsyncBehavior:
|
||||
"""Real async tests for ChatMessageHandler.handle() with mocked orchestrator."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_streaming_single_resp_message_id(self):
|
||||
"""Streaming mode: all chunks should have same resp_message_id."""
|
||||
from langbot.pkg.pipeline.process.handlers.chat import ChatMessageHandler
|
||||
from langbot.pkg.pipeline import entities
|
||||
|
||||
# Create chunks for streaming
|
||||
chunks = [
|
||||
MockMessageChunk('Hello'),
|
||||
MockMessageChunk('Hello World'),
|
||||
MockMessageChunk('Hello World!'),
|
||||
]
|
||||
|
||||
orchestrator = MockAgentRunOrchestrator(chunks=chunks)
|
||||
mock_ap = MockApplication(orchestrator=orchestrator)
|
||||
|
||||
# Mock event context to not prevent default
|
||||
event_ctx = MockEventContext(prevented=False)
|
||||
mock_ap.plugin_connector.emit_event = AsyncMock(return_value=event_ctx)
|
||||
|
||||
query = MockQuery()
|
||||
query.adapter.is_stream = True # Enable streaming mode
|
||||
|
||||
handler = ChatMessageHandler(mock_ap)
|
||||
|
||||
# Mock event creation and StageProcessResult to bypass pydantic validation
|
||||
mock_event = MagicMock()
|
||||
mock_event.return_value = MagicMock()
|
||||
|
||||
def make_result(*args, **kwargs):
|
||||
return MagicMock(result_type=kwargs.get('result_type', entities.ResultType.CONTINUE))
|
||||
|
||||
with patch('langbot.pkg.pipeline.process.handlers.chat.events') as mock_events_module, \
|
||||
patch('langbot.pkg.pipeline.entities.StageProcessResult', side_effect=make_result):
|
||||
mock_events_module.PersonNormalMessageReceived = mock_event
|
||||
mock_events_module.GroupNormalMessageReceived = mock_event
|
||||
|
||||
results = []
|
||||
async for result in handler.handle(query):
|
||||
results.append(result)
|
||||
|
||||
# Verify single resp_message_id
|
||||
resp_ids = [msg.resp_message_id for msg in query.resp_messages if hasattr(msg, 'resp_message_id')]
|
||||
assert len(set(resp_ids)) == 1 # All same ID
|
||||
|
||||
# Verify pop/append pattern: only last chunk remains
|
||||
assert len(query.resp_messages) == 1
|
||||
assert query.resp_messages[0].content == 'Hello World!'
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_non_streaming_no_pop(self):
|
||||
"""Non-streaming mode: all chunks should remain."""
|
||||
from langbot.pkg.pipeline.process.handlers.chat import ChatMessageHandler
|
||||
from langbot.pkg.pipeline import entities
|
||||
|
||||
chunks = [
|
||||
MockMessageChunk('Response 1'),
|
||||
MockMessageChunk('Response 2'),
|
||||
]
|
||||
|
||||
orchestrator = MockAgentRunOrchestrator(chunks=chunks)
|
||||
mock_ap = MockApplication(orchestrator=orchestrator)
|
||||
mock_ap.plugin_connector.emit_event = AsyncMock(return_value=MockEventContext(prevented=False))
|
||||
|
||||
query = MockQuery()
|
||||
query.adapter.is_stream = False # Disable streaming mode
|
||||
|
||||
handler = ChatMessageHandler(mock_ap)
|
||||
|
||||
mock_event = MagicMock()
|
||||
mock_event.return_value = MagicMock()
|
||||
|
||||
def make_result(*args, **kwargs):
|
||||
return MagicMock(result_type=kwargs.get('result_type', entities.ResultType.CONTINUE))
|
||||
|
||||
with patch('langbot.pkg.pipeline.process.handlers.chat.events') as mock_events_module, \
|
||||
patch('langbot.pkg.pipeline.entities.StageProcessResult', side_effect=make_result):
|
||||
mock_events_module.PersonNormalMessageReceived = mock_event
|
||||
mock_events_module.GroupNormalMessageReceived = mock_event
|
||||
|
||||
results = []
|
||||
async for result in handler.handle(query):
|
||||
results.append(result)
|
||||
|
||||
# No pop: all chunks should remain
|
||||
assert len(query.resp_messages) == 2
|
||||
assert query.resp_messages[0].content == 'Response 1'
|
||||
assert query.resp_messages[1].content == 'Response 2'
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_runner_not_found_error(self):
|
||||
"""Handler should catch RunnerNotFoundError and return INTERRUPT."""
|
||||
from langbot.pkg.pipeline.process.handlers.chat import ChatMessageHandler
|
||||
from langbot.pkg.pipeline import entities
|
||||
|
||||
orchestrator = MockAgentRunOrchestrator(
|
||||
error=RunnerNotFoundError('plugin:notexist/unknown/default')
|
||||
)
|
||||
mock_ap = MockApplication(orchestrator=orchestrator)
|
||||
mock_ap.plugin_connector.emit_event = AsyncMock(return_value=MockEventContext(prevented=False))
|
||||
|
||||
query = MockQuery()
|
||||
|
||||
handler = ChatMessageHandler(mock_ap)
|
||||
|
||||
mock_event = MagicMock()
|
||||
mock_event.return_value = MagicMock()
|
||||
|
||||
def make_result(*args, **kwargs):
|
||||
return MagicMock(
|
||||
result_type=kwargs.get('result_type'),
|
||||
user_notice=kwargs.get('user_notice'),
|
||||
)
|
||||
|
||||
with patch('langbot.pkg.pipeline.process.handlers.chat.events') as mock_events_module, \
|
||||
patch('langbot.pkg.pipeline.entities.StageProcessResult', side_effect=make_result):
|
||||
mock_events_module.PersonNormalMessageReceived = mock_event
|
||||
mock_events_module.GroupNormalMessageReceived = mock_event
|
||||
|
||||
results = []
|
||||
async for result in handler.handle(query):
|
||||
results.append(result)
|
||||
|
||||
# Should return INTERRUPT with user_notice
|
||||
assert len(results) == 1
|
||||
assert results[0].result_type == entities.ResultType.INTERRUPT
|
||||
assert 'not found' in results[0].user_notice
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_runner_not_authorized_error(self):
|
||||
"""Handler should catch RunnerNotAuthorizedError and return INTERRUPT."""
|
||||
from langbot.pkg.pipeline.process.handlers.chat import ChatMessageHandler
|
||||
from langbot.pkg.pipeline import entities
|
||||
|
||||
orchestrator = MockAgentRunOrchestrator(
|
||||
error=RunnerNotAuthorizedError('plugin:langbot/local-agent/default', ['other/plugin'])
|
||||
)
|
||||
mock_ap = MockApplication(orchestrator=orchestrator)
|
||||
mock_ap.plugin_connector.emit_event = AsyncMock(return_value=MockEventContext(prevented=False))
|
||||
|
||||
query = MockQuery()
|
||||
|
||||
handler = ChatMessageHandler(mock_ap)
|
||||
|
||||
mock_event = MagicMock()
|
||||
mock_event.return_value = MagicMock()
|
||||
|
||||
def make_result(*args, **kwargs):
|
||||
return MagicMock(
|
||||
result_type=kwargs.get('result_type'),
|
||||
user_notice=kwargs.get('user_notice'),
|
||||
)
|
||||
|
||||
with patch('langbot.pkg.pipeline.process.handlers.chat.events') as mock_events_module, \
|
||||
patch('langbot.pkg.pipeline.entities.StageProcessResult', side_effect=make_result):
|
||||
mock_events_module.PersonNormalMessageReceived = mock_event
|
||||
mock_events_module.GroupNormalMessageReceived = mock_event
|
||||
|
||||
results = []
|
||||
async for result in handler.handle(query):
|
||||
results.append(result)
|
||||
|
||||
assert len(results) == 1
|
||||
assert results[0].result_type == entities.ResultType.INTERRUPT
|
||||
assert 'not authorized' in results[0].user_notice
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_runner_execution_error_retryable(self):
|
||||
"""Handler should catch retryable RunnerExecutionError."""
|
||||
from langbot.pkg.pipeline.process.handlers.chat import ChatMessageHandler
|
||||
from langbot.pkg.pipeline import entities
|
||||
|
||||
orchestrator = MockAgentRunOrchestrator(
|
||||
error=RunnerExecutionError('plugin:langbot/local-agent/default', 'timeout', retryable=True)
|
||||
)
|
||||
mock_ap = MockApplication(orchestrator=orchestrator)
|
||||
mock_ap.plugin_connector.emit_event = AsyncMock(return_value=MockEventContext(prevented=False))
|
||||
|
||||
query = MockQuery()
|
||||
|
||||
handler = ChatMessageHandler(mock_ap)
|
||||
|
||||
mock_event = MagicMock()
|
||||
mock_event.return_value = MagicMock()
|
||||
|
||||
def make_result(*args, **kwargs):
|
||||
return MagicMock(
|
||||
result_type=kwargs.get('result_type'),
|
||||
user_notice=kwargs.get('user_notice'),
|
||||
)
|
||||
|
||||
with patch('langbot.pkg.pipeline.process.handlers.chat.events') as mock_events_module, \
|
||||
patch('langbot.pkg.pipeline.entities.StageProcessResult', side_effect=make_result):
|
||||
mock_events_module.PersonNormalMessageReceived = mock_event
|
||||
mock_events_module.GroupNormalMessageReceived = mock_event
|
||||
|
||||
results = []
|
||||
async for result in handler.handle(query):
|
||||
results.append(result)
|
||||
|
||||
assert len(results) == 1
|
||||
assert results[0].result_type == entities.ResultType.INTERRUPT
|
||||
assert 'temporarily unavailable' in results[0].user_notice
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prevented_default_with_reply(self):
|
||||
"""When event prevented default with reply, use reply message."""
|
||||
from langbot.pkg.pipeline.process.handlers.chat import ChatMessageHandler
|
||||
from langbot.pkg.pipeline import entities
|
||||
|
||||
# Mock reply message chain
|
||||
reply_chain = MockMessageChunk('Reply from plugin')
|
||||
|
||||
mock_ap = MockApplication()
|
||||
mock_ap.plugin_connector.emit_event = AsyncMock(
|
||||
return_value=MockEventContext(prevented=True, reply_message_chain=reply_chain)
|
||||
)
|
||||
|
||||
query = MockQuery()
|
||||
|
||||
handler = ChatMessageHandler(mock_ap)
|
||||
|
||||
mock_event = MagicMock()
|
||||
mock_event.return_value = MagicMock()
|
||||
|
||||
def make_result(*args, **kwargs):
|
||||
return MagicMock(result_type=kwargs.get('result_type', entities.ResultType.CONTINUE))
|
||||
|
||||
with patch('langbot.pkg.pipeline.process.handlers.chat.events') as mock_events_module, \
|
||||
patch('langbot.pkg.pipeline.entities.StageProcessResult', side_effect=make_result):
|
||||
mock_events_module.PersonNormalMessageReceived = mock_event
|
||||
mock_events_module.GroupNormalMessageReceived = mock_event
|
||||
|
||||
results = []
|
||||
async for result in handler.handle(query):
|
||||
results.append(result)
|
||||
|
||||
# Should return CONTINUE with reply message
|
||||
assert len(results) == 1
|
||||
assert results[0].result_type == entities.ResultType.CONTINUE
|
||||
assert len(query.resp_messages) == 1
|
||||
231
tests/unit_tests/agent/test_config_migration.py
Normal file
231
tests/unit_tests/agent/test_config_migration.py
Normal file
@@ -0,0 +1,231 @@
|
||||
"""Tests for agent runner config migration."""
|
||||
from __future__ import annotations
|
||||
|
||||
|
||||
from langbot.pkg.agent.runner.config_migration import (
|
||||
ConfigMigration,
|
||||
OLD_RUNNER_TO_PLUGIN_RUNNER_ID,
|
||||
)
|
||||
|
||||
|
||||
class TestOldRunnerMapping:
|
||||
"""Tests for OLD_RUNNER_TO_PLUGIN_RUNNER_ID mapping."""
|
||||
|
||||
def test_local_agent_mapping(self):
|
||||
"""Local-agent should map to official plugin."""
|
||||
assert OLD_RUNNER_TO_PLUGIN_RUNNER_ID['local-agent'] == 'plugin:langbot/local-agent/default'
|
||||
|
||||
def test_dify_mapping(self):
|
||||
"""Dify should map to official plugin."""
|
||||
assert OLD_RUNNER_TO_PLUGIN_RUNNER_ID['dify-service-api'] == 'plugin:langbot/dify-agent/default'
|
||||
|
||||
def test_n8n_mapping(self):
|
||||
"""n8n should map to official plugin."""
|
||||
assert OLD_RUNNER_TO_PLUGIN_RUNNER_ID['n8n-service-api'] == 'plugin:langbot/n8n-agent/default'
|
||||
|
||||
def test_coze_mapping(self):
|
||||
"""Coze should map to official plugin."""
|
||||
assert OLD_RUNNER_TO_PLUGIN_RUNNER_ID['coze-api'] == 'plugin:langbot/coze-agent/default'
|
||||
|
||||
def test_all_runners_mapped(self):
|
||||
"""All old runners should have mapping."""
|
||||
expected_runners = [
|
||||
'local-agent',
|
||||
'dify-service-api',
|
||||
'n8n-service-api',
|
||||
'coze-api',
|
||||
'dashscope-app-api',
|
||||
'langflow-api',
|
||||
'tbox-app-api',
|
||||
]
|
||||
for runner in expected_runners:
|
||||
assert runner in OLD_RUNNER_TO_PLUGIN_RUNNER_ID
|
||||
mapped = OLD_RUNNER_TO_PLUGIN_RUNNER_ID[runner]
|
||||
assert mapped.startswith('plugin:langbot/')
|
||||
assert mapped.endswith('/default')
|
||||
|
||||
|
||||
class TestResolveRunnerId:
|
||||
"""Tests for ConfigMigration.resolve_runner_id."""
|
||||
|
||||
def test_resolve_new_format_runner_id(self):
|
||||
"""Resolve runner ID from new format."""
|
||||
pipeline_config = {
|
||||
'ai': {
|
||||
'runner': {
|
||||
'id': 'plugin:langbot/local-agent/default',
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
runner_id = ConfigMigration.resolve_runner_id(pipeline_config)
|
||||
assert runner_id == 'plugin:langbot/local-agent/default'
|
||||
|
||||
def test_resolve_old_format_runner_name(self):
|
||||
"""Resolve runner ID from old format."""
|
||||
pipeline_config = {
|
||||
'ai': {
|
||||
'runner': {
|
||||
'runner': 'local-agent',
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
runner_id = ConfigMigration.resolve_runner_id(pipeline_config)
|
||||
assert runner_id == 'plugin:langbot/local-agent/default'
|
||||
|
||||
def test_resolve_old_format_plugin_runner(self):
|
||||
"""Resolve already migrated plugin:* runner."""
|
||||
pipeline_config = {
|
||||
'ai': {
|
||||
'runner': {
|
||||
'runner': 'plugin:alice/my-agent/custom',
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
runner_id = ConfigMigration.resolve_runner_id(pipeline_config)
|
||||
assert runner_id == 'plugin:alice/my-agent/custom'
|
||||
|
||||
def test_resolve_no_runner_config(self):
|
||||
"""Resolve runner ID when not configured."""
|
||||
pipeline_config = {}
|
||||
|
||||
runner_id = ConfigMigration.resolve_runner_id(pipeline_config)
|
||||
assert runner_id is None
|
||||
|
||||
def test_resolve_priority_new_over_old(self):
|
||||
"""New format takes priority over old format."""
|
||||
pipeline_config = {
|
||||
'ai': {
|
||||
'runner': {
|
||||
'id': 'plugin:langbot/local-agent/default',
|
||||
'runner': 'dify-service-api', # This should be ignored
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
runner_id = ConfigMigration.resolve_runner_id(pipeline_config)
|
||||
assert runner_id == 'plugin:langbot/local-agent/default'
|
||||
|
||||
|
||||
class TestResolveRunnerConfig:
|
||||
"""Tests for ConfigMigration.resolve_runner_config."""
|
||||
|
||||
def test_resolve_new_format_config(self):
|
||||
"""Resolve runner config from new format."""
|
||||
pipeline_config = {
|
||||
'ai': {
|
||||
'runner_config': {
|
||||
'plugin:langbot/local-agent/default': {
|
||||
'model': 'uuid-123',
|
||||
'max_round': 10,
|
||||
},
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
config = ConfigMigration.resolve_runner_config(
|
||||
pipeline_config,
|
||||
'plugin:langbot/local-agent/default',
|
||||
)
|
||||
assert config == {'model': 'uuid-123', 'max_round': 10}
|
||||
|
||||
def test_resolve_old_format_config(self):
|
||||
"""Resolve runner config from old format."""
|
||||
pipeline_config = {
|
||||
'ai': {
|
||||
'local-agent': {
|
||||
'model': 'uuid-123',
|
||||
'max_round': 10,
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
config = ConfigMigration.resolve_runner_config(
|
||||
pipeline_config,
|
||||
'plugin:langbot/local-agent/default',
|
||||
)
|
||||
assert config == {'model': 'uuid-123', 'max_round': 10}
|
||||
|
||||
def test_resolve_no_config(self):
|
||||
"""Resolve runner config when not found."""
|
||||
pipeline_config = {}
|
||||
|
||||
config = ConfigMigration.resolve_runner_config(
|
||||
pipeline_config,
|
||||
'plugin:langbot/local-agent/default',
|
||||
)
|
||||
assert config == {}
|
||||
|
||||
def test_resolve_priority_new_over_old(self):
|
||||
"""New format config takes priority."""
|
||||
pipeline_config = {
|
||||
'ai': {
|
||||
'runner_config': {
|
||||
'plugin:langbot/local-agent/default': {
|
||||
'model': 'new-uuid',
|
||||
},
|
||||
},
|
||||
'local-agent': {
|
||||
'model': 'old-uuid',
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
config = ConfigMigration.resolve_runner_config(
|
||||
pipeline_config,
|
||||
'plugin:langbot/local-agent/default',
|
||||
)
|
||||
assert config == {'model': 'new-uuid'}
|
||||
|
||||
|
||||
class TestGetExpireTime:
|
||||
"""Tests for ConfigMigration.get_expire_time."""
|
||||
|
||||
def test_get_expire_time_zero(self):
|
||||
"""Get expire time when zero."""
|
||||
pipeline_config = {
|
||||
'ai': {
|
||||
'runner': {
|
||||
'expire-time': 0,
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
expire_time = ConfigMigration.get_expire_time(pipeline_config)
|
||||
assert expire_time == 0
|
||||
|
||||
def test_get_expire_time_positive(self):
|
||||
"""Get expire time when positive."""
|
||||
pipeline_config = {
|
||||
'ai': {
|
||||
'runner': {
|
||||
'expire-time': 3600,
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
expire_time = ConfigMigration.get_expire_time(pipeline_config)
|
||||
assert expire_time == 3600
|
||||
|
||||
def test_get_expire_time_default(self):
|
||||
"""Get expire time when not configured."""
|
||||
pipeline_config = {}
|
||||
|
||||
expire_time = ConfigMigration.get_expire_time(pipeline_config)
|
||||
assert expire_time == 0
|
||||
|
||||
|
||||
class TestGetOldRunnerName:
|
||||
"""Tests for ConfigMigration.get_old_runner_name."""
|
||||
|
||||
def test_get_old_runner_name_mapped(self):
|
||||
"""Get old runner name for mapped runner ID."""
|
||||
old_name = ConfigMigration.get_old_runner_name('plugin:langbot/local-agent/default')
|
||||
assert old_name == 'local-agent'
|
||||
|
||||
def test_get_old_runner_name_not_mapped(self):
|
||||
"""Get old runner name for unmapped runner ID."""
|
||||
old_name = ConfigMigration.get_old_runner_name('plugin:alice/my-agent/custom')
|
||||
assert old_name is None
|
||||
137
tests/unit_tests/agent/test_id.py
Normal file
137
tests/unit_tests/agent/test_id.py
Normal file
@@ -0,0 +1,137 @@
|
||||
"""Tests for agent runner ID parsing and formatting."""
|
||||
from __future__ import annotations
|
||||
|
||||
import pytest
|
||||
|
||||
from langbot.pkg.agent.runner.id import (
|
||||
parse_runner_id,
|
||||
format_runner_id,
|
||||
RunnerIdParts,
|
||||
is_plugin_runner_id,
|
||||
)
|
||||
|
||||
|
||||
class TestRunnerIdParsing:
|
||||
"""Tests for parse_runner_id."""
|
||||
|
||||
def test_parse_plugin_runner_id(self):
|
||||
"""Parse valid plugin runner ID."""
|
||||
runner_id = 'plugin:langbot/local-agent/default'
|
||||
parts = parse_runner_id(runner_id)
|
||||
|
||||
assert parts.source == 'plugin'
|
||||
assert parts.plugin_author == 'langbot'
|
||||
assert parts.plugin_name == 'local-agent'
|
||||
assert parts.runner_name == 'default'
|
||||
|
||||
def test_parse_plugin_runner_id_complex_names(self):
|
||||
"""Parse plugin runner ID with complex names."""
|
||||
runner_id = 'plugin:alice/helpdesk-agent/ticket-handler'
|
||||
parts = parse_runner_id(runner_id)
|
||||
|
||||
assert parts.source == 'plugin'
|
||||
assert parts.plugin_author == 'alice'
|
||||
assert parts.plugin_name == 'helpdesk-agent'
|
||||
assert parts.runner_name == 'ticket-handler'
|
||||
|
||||
def test_parse_invalid_plugin_runner_id_missing_parts(self):
|
||||
"""Parse invalid plugin runner ID with missing parts."""
|
||||
runner_id = 'plugin:langbot/local-agent'
|
||||
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
parse_runner_id(runner_id)
|
||||
|
||||
assert 'Invalid plugin runner ID format' in str(exc_info.value)
|
||||
|
||||
def test_parse_invalid_plugin_runner_id_empty_parts(self):
|
||||
"""Parse invalid plugin runner ID with empty parts."""
|
||||
runner_id = 'plugin://default'
|
||||
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
parse_runner_id(runner_id)
|
||||
|
||||
assert 'non-empty' in str(exc_info.value)
|
||||
|
||||
def test_parse_invalid_runner_id_not_plugin(self):
|
||||
"""Parse invalid runner ID without plugin prefix."""
|
||||
runner_id = 'local-agent'
|
||||
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
parse_runner_id(runner_id)
|
||||
|
||||
assert 'Invalid runner ID format' in str(exc_info.value)
|
||||
|
||||
def test_parse_invalid_runner_id_empty_string(self):
|
||||
"""Parse empty runner ID."""
|
||||
runner_id = ''
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
parse_runner_id(runner_id)
|
||||
|
||||
|
||||
class TestRunnerIdFormatting:
|
||||
"""Tests for format_runner_id."""
|
||||
|
||||
def test_format_plugin_runner_id(self):
|
||||
"""Format plugin runner ID."""
|
||||
runner_id = format_runner_id(
|
||||
source='plugin',
|
||||
plugin_author='langbot',
|
||||
plugin_name='local-agent',
|
||||
runner_name='default',
|
||||
)
|
||||
|
||||
assert runner_id == 'plugin:langbot/local-agent/default'
|
||||
|
||||
def test_format_invalid_source(self):
|
||||
"""Format runner ID with invalid source."""
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
format_runner_id(
|
||||
source='builtin',
|
||||
plugin_author='langbot',
|
||||
plugin_name='local-agent',
|
||||
runner_name='default',
|
||||
)
|
||||
|
||||
assert 'Invalid runner source' in str(exc_info.value)
|
||||
|
||||
|
||||
class TestRunnerIdParts:
|
||||
"""Tests for RunnerIdParts dataclass."""
|
||||
|
||||
def test_get_plugin_id(self):
|
||||
"""Get plugin ID from parts."""
|
||||
parts = RunnerIdParts(
|
||||
source='plugin',
|
||||
plugin_author='langbot',
|
||||
plugin_name='local-agent',
|
||||
runner_name='default',
|
||||
)
|
||||
|
||||
assert parts.to_plugin_id() == 'langbot/local-agent'
|
||||
|
||||
def test_frozen_dataclass(self):
|
||||
"""RunnerIdParts should be immutable."""
|
||||
parts = RunnerIdParts(
|
||||
source='plugin',
|
||||
plugin_author='langbot',
|
||||
plugin_name='local-agent',
|
||||
runner_name='default',
|
||||
)
|
||||
|
||||
with pytest.raises(Exception): # FrozenInstanceError
|
||||
parts.plugin_author = 'other'
|
||||
|
||||
|
||||
class TestIsPluginRunnerId:
|
||||
"""Tests for is_plugin_runner_id."""
|
||||
|
||||
def test_is_plugin_runner_id_true(self):
|
||||
"""Check plugin runner ID returns True."""
|
||||
assert is_plugin_runner_id('plugin:langbot/local-agent/default') is True
|
||||
|
||||
def test_is_plugin_runner_id_false(self):
|
||||
"""Check non-plugin runner ID returns False."""
|
||||
assert is_plugin_runner_id('local-agent') is False
|
||||
assert is_plugin_runner_id('builtin:local-agent') is False
|
||||
assert is_plugin_runner_id('') is False
|
||||
278
tests/unit_tests/agent/test_registry.py
Normal file
278
tests/unit_tests/agent/test_registry.py
Normal file
@@ -0,0 +1,278 @@
|
||||
"""Tests for agent runner registry."""
|
||||
from __future__ import annotations
|
||||
|
||||
import pytest
|
||||
|
||||
from langbot.pkg.agent.runner.registry import AgentRunnerRegistry
|
||||
from langbot.pkg.agent.runner.descriptor import AgentRunnerDescriptor
|
||||
from langbot.pkg.agent.runner.errors import RunnerNotFoundError, RunnerNotAuthorizedError
|
||||
|
||||
|
||||
class FakeApplication:
|
||||
"""Fake Application for testing."""
|
||||
def __init__(self):
|
||||
class FakeLogger:
|
||||
def info(self, msg):
|
||||
pass
|
||||
def debug(self, msg):
|
||||
pass
|
||||
def warning(self, msg):
|
||||
pass
|
||||
def error(self, msg):
|
||||
pass
|
||||
|
||||
self.logger = FakeLogger()
|
||||
|
||||
class FakePluginConnector:
|
||||
is_enable_plugin = True
|
||||
|
||||
async def list_agent_runners(self, bound_plugins=None):
|
||||
# Return sample runner data
|
||||
return [
|
||||
{
|
||||
'plugin_author': 'langbot',
|
||||
'plugin_name': 'local-agent',
|
||||
'runner_name': 'default',
|
||||
'manifest': {
|
||||
'kind': 'AgentRunner',
|
||||
'metadata': {
|
||||
'name': 'default',
|
||||
'label': {'en_US': 'Local Agent'},
|
||||
},
|
||||
'spec': {
|
||||
'protocol_version': '1',
|
||||
'config': [],
|
||||
'capabilities': {'streaming': True},
|
||||
'permissions': {},
|
||||
},
|
||||
},
|
||||
},
|
||||
{
|
||||
'plugin_author': 'alice',
|
||||
'plugin_name': 'my-agent',
|
||||
'runner_name': 'custom',
|
||||
'manifest': {
|
||||
'kind': 'AgentRunner',
|
||||
'metadata': {
|
||||
'name': 'custom',
|
||||
'label': {'en_US': 'Custom Agent'},
|
||||
},
|
||||
'spec': {
|
||||
'protocol_version': '1',
|
||||
'config': [{'name': 'param1', 'type': 'string'}],
|
||||
'capabilities': {},
|
||||
'permissions': {},
|
||||
},
|
||||
},
|
||||
},
|
||||
# Invalid runner - wrong kind
|
||||
{
|
||||
'plugin_author': 'bad',
|
||||
'plugin_name': 'wrong-kind',
|
||||
'runner_name': 'default',
|
||||
'manifest': {
|
||||
'kind': 'Tool', # Wrong kind
|
||||
'metadata': {},
|
||||
'spec': {},
|
||||
},
|
||||
},
|
||||
# Invalid runner - missing name
|
||||
{
|
||||
'plugin_author': 'bad',
|
||||
'plugin_name': 'missing-name',
|
||||
'runner_name': 'default',
|
||||
'manifest': {
|
||||
'kind': 'AgentRunner',
|
||||
'metadata': {}, # No name
|
||||
'spec': {},
|
||||
},
|
||||
},
|
||||
]
|
||||
|
||||
self.plugin_connector = FakePluginConnector()
|
||||
|
||||
|
||||
class TestRegistryDiscovery:
|
||||
"""Tests for runner discovery."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_discover_valid_runners(self):
|
||||
"""Discover valid runners from plugin runtime."""
|
||||
ap = FakeApplication()
|
||||
registry = AgentRunnerRegistry(ap)
|
||||
|
||||
runners = await registry.list_runners(use_cache=False)
|
||||
|
||||
# Should find 2 valid runners (langbot/local-agent and alice/my-agent)
|
||||
assert len(runners) == 2
|
||||
|
||||
ids = [r.id for r in runners]
|
||||
assert 'plugin:langbot/local-agent/default' in ids
|
||||
assert 'plugin:alice/my-agent/custom' in ids
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_discover_caches_results(self):
|
||||
"""Discovery should cache results."""
|
||||
ap = FakeApplication()
|
||||
registry = AgentRunnerRegistry(ap)
|
||||
|
||||
# First discovery
|
||||
runners1 = await registry.list_runners(use_cache=True)
|
||||
|
||||
# Second call should use cache
|
||||
runners2 = await registry.list_runners(use_cache=True)
|
||||
|
||||
assert registry._cache is not None
|
||||
assert len(runners1) == len(runners2)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_discover_handles_plugin_disabled(self):
|
||||
"""Discovery returns empty when plugin system disabled."""
|
||||
ap = FakeApplication()
|
||||
ap.plugin_connector.is_enable_plugin = False
|
||||
registry = AgentRunnerRegistry(ap)
|
||||
|
||||
runners = await registry.list_runners(use_cache=False)
|
||||
|
||||
assert runners == []
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_cache_not_polluted_by_bound_plugins(self):
|
||||
"""Cache should contain ALL runners, not filtered by bound_plugins.
|
||||
|
||||
Regression test: get(bound_plugins=["a/b"]) should not pollute cache,
|
||||
so subsequent list_runners(bound_plugins=None) should return all runners.
|
||||
"""
|
||||
ap = FakeApplication()
|
||||
registry = AgentRunnerRegistry(ap)
|
||||
|
||||
# First: get with bound_plugins filter (should not pollute cache)
|
||||
descriptor = await registry.get(
|
||||
'plugin:langbot/local-agent/default',
|
||||
bound_plugins=['langbot/local-agent'],
|
||||
)
|
||||
assert descriptor.id == 'plugin:langbot/local-agent/default'
|
||||
|
||||
# Cache should contain ALL runners (both langbot and alice)
|
||||
assert registry._cache is not None
|
||||
assert len(registry._cache) == 2 # Both runners in cache
|
||||
assert 'plugin:langbot/local-agent/default' in registry._cache
|
||||
assert 'plugin:alice/my-agent/custom' in registry._cache
|
||||
|
||||
# Second: list_runners without filter should return ALL runners
|
||||
all_runners = await registry.list_runners(bound_plugins=None, use_cache=True)
|
||||
assert len(all_runners) == 2 # Both runners returned
|
||||
|
||||
# Third: list_runners with different filter should work correctly
|
||||
alice_runners = await registry.list_runners(bound_plugins=['alice/my-agent'], use_cache=True)
|
||||
assert len(alice_runners) == 1
|
||||
assert alice_runners[0].id == 'plugin:alice/my-agent/custom'
|
||||
|
||||
|
||||
class TestRegistryGet:
|
||||
"""Tests for getting specific runner."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_existing_runner(self):
|
||||
"""Get existing runner by ID."""
|
||||
ap = FakeApplication()
|
||||
registry = AgentRunnerRegistry(ap)
|
||||
|
||||
descriptor = await registry.get('plugin:langbot/local-agent/default')
|
||||
|
||||
assert descriptor.id == 'plugin:langbot/local-agent/default'
|
||||
assert descriptor.plugin_author == 'langbot'
|
||||
assert descriptor.plugin_name == 'local-agent'
|
||||
assert descriptor.runner_name == 'default'
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_nonexistent_runner(self):
|
||||
"""Get nonexistent runner raises RunnerNotFoundError."""
|
||||
ap = FakeApplication()
|
||||
registry = AgentRunnerRegistry(ap)
|
||||
|
||||
with pytest.raises(RunnerNotFoundError) as exc_info:
|
||||
await registry.get('plugin:notexist/unknown/default')
|
||||
|
||||
assert exc_info.value.runner_id == 'plugin:notexist/unknown/default'
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_runner_with_bound_plugins_filter(self):
|
||||
"""Get runner with bound plugins authorization."""
|
||||
ap = FakeApplication()
|
||||
registry = AgentRunnerRegistry(ap)
|
||||
|
||||
# Authorized - langbot plugin in bound list
|
||||
descriptor = await registry.get(
|
||||
'plugin:langbot/local-agent/default',
|
||||
bound_plugins=['langbot/local-agent'],
|
||||
)
|
||||
assert descriptor is not None
|
||||
|
||||
# Not authorized - plugin not in bound list
|
||||
with pytest.raises(RunnerNotAuthorizedError):
|
||||
await registry.get(
|
||||
'plugin:alice/my-agent/custom',
|
||||
bound_plugins=['langbot/local-agent'],
|
||||
)
|
||||
|
||||
|
||||
class TestRegistryMetadataForPipeline:
|
||||
"""Tests for get_runner_metadata_for_pipeline."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_metadata_options_and_stages(self):
|
||||
"""Get metadata options and stages for pipeline UI."""
|
||||
ap = FakeApplication()
|
||||
registry = AgentRunnerRegistry(ap)
|
||||
|
||||
options, stages = await registry.get_runner_metadata_for_pipeline()
|
||||
|
||||
# Should have options for each runner
|
||||
assert len(options) == 2
|
||||
option_ids = [o['name'] for o in options]
|
||||
assert 'plugin:langbot/local-agent/default' in option_ids
|
||||
assert 'plugin:alice/my-agent/custom' in option_ids
|
||||
|
||||
# Should have stages for runners with config
|
||||
# Note: stages may be empty if config_schema is empty list
|
||||
# In real scenarios, runners with config_schema will generate stages
|
||||
# Only runners with non-empty config_schema generate stages
|
||||
# mock data has config: [{'name': 'param1', 'type': 'string'}] for alice/my-agent
|
||||
# but config is now taken from runner_data.get('config', [])
|
||||
assert len(stages) >= 0 # Can be 0 if all runners have empty config
|
||||
|
||||
|
||||
class TestDescriptorValidation:
|
||||
"""Tests for descriptor validation."""
|
||||
|
||||
def test_validate_runner_descriptor(self):
|
||||
"""Validate correctly built descriptor."""
|
||||
descriptor = AgentRunnerDescriptor(
|
||||
id='plugin:test/my-runner/default',
|
||||
source='plugin',
|
||||
label={'en_US': 'Test Runner'},
|
||||
plugin_author='test',
|
||||
plugin_name='my-runner',
|
||||
runner_name='default',
|
||||
)
|
||||
|
||||
assert descriptor.id == 'plugin:test/my-runner/default'
|
||||
assert descriptor.get_plugin_id() == 'test/my-runner'
|
||||
assert descriptor.protocol_version == '1'
|
||||
|
||||
def test_descriptor_capabilities(self):
|
||||
"""Descriptor capability helper methods."""
|
||||
descriptor = AgentRunnerDescriptor(
|
||||
id='plugin:test/my-runner/default',
|
||||
source='plugin',
|
||||
label={'en_US': 'Test Runner'},
|
||||
plugin_author='test',
|
||||
plugin_name='my-runner',
|
||||
runner_name='default',
|
||||
capabilities={'streaming': True, 'tool_calling': False},
|
||||
)
|
||||
|
||||
assert descriptor.supports_streaming() is True
|
||||
assert descriptor.supports_tool_calling() is False
|
||||
assert descriptor.supports_knowledge_retrieval() is False
|
||||
343
tests/unit_tests/agent/test_result_normalizer.py
Normal file
343
tests/unit_tests/agent/test_result_normalizer.py
Normal file
@@ -0,0 +1,343 @@
|
||||
"""Tests for agent runner result normalizer."""
|
||||
from __future__ import annotations
|
||||
|
||||
import pytest
|
||||
|
||||
from langbot.pkg.agent.runner.result_normalizer import AgentResultNormalizer
|
||||
from langbot.pkg.agent.runner.descriptor import AgentRunnerDescriptor
|
||||
from langbot.pkg.agent.runner.errors import RunnerExecutionError, RunnerProtocolError
|
||||
|
||||
from langbot_plugin.api.entities.builtin.provider import message as provider_message
|
||||
|
||||
|
||||
class FakeApplication:
|
||||
"""Fake Application for testing."""
|
||||
def __init__(self):
|
||||
class FakeLogger:
|
||||
def info(self, msg):
|
||||
pass
|
||||
def debug(self, msg):
|
||||
pass
|
||||
def warning(self, msg):
|
||||
pass
|
||||
def error(self, msg):
|
||||
pass
|
||||
|
||||
self.logger = FakeLogger()
|
||||
|
||||
|
||||
def make_descriptor():
|
||||
"""Create a test descriptor."""
|
||||
return AgentRunnerDescriptor(
|
||||
id='plugin:langbot/local-agent/default',
|
||||
source='plugin',
|
||||
label={'en_US': 'Local Agent', 'zh_Hans': '内置 Agent'},
|
||||
plugin_author='langbot',
|
||||
plugin_name='local-agent',
|
||||
runner_name='default',
|
||||
protocol_version='1',
|
||||
capabilities={'streaming': True},
|
||||
)
|
||||
|
||||
|
||||
class TestNormalizeMessageDelta:
|
||||
"""Tests for normalizing message.delta results."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_message_delta_text(self):
|
||||
"""Normalize message.delta with text chunk."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'message.delta',
|
||||
'data': {
|
||||
'chunk': {
|
||||
'role': 'assistant',
|
||||
'content': 'Hello',
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
|
||||
assert result is not None
|
||||
assert isinstance(result, provider_message.MessageChunk)
|
||||
assert result.role == 'assistant'
|
||||
assert result.content == 'Hello'
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_message_delta_missing_chunk(self):
|
||||
"""Normalize message.delta without chunk data."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'message.delta',
|
||||
'data': {},
|
||||
}
|
||||
|
||||
with pytest.raises(RunnerProtocolError) as exc_info:
|
||||
await normalizer.normalize(result_dict, descriptor)
|
||||
|
||||
assert 'missing chunk data' in str(exc_info.value)
|
||||
|
||||
|
||||
class TestNormalizeMessageCompleted:
|
||||
"""Tests for normalizing message.completed results."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_message_completed(self):
|
||||
"""Normalize message.completed with full message."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'message.completed',
|
||||
'data': {
|
||||
'message': {
|
||||
'role': 'assistant',
|
||||
'content': 'Complete response',
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
|
||||
assert result is not None
|
||||
assert isinstance(result, provider_message.Message)
|
||||
assert result.role == 'assistant'
|
||||
assert result.content == 'Complete response'
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_message_completed_missing_message(self):
|
||||
"""Normalize message.completed without message data."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'message.completed',
|
||||
'data': {},
|
||||
}
|
||||
|
||||
with pytest.raises(RunnerProtocolError) as exc_info:
|
||||
await normalizer.normalize(result_dict, descriptor)
|
||||
|
||||
assert 'missing message data' in str(exc_info.value)
|
||||
|
||||
|
||||
class TestNormalizeRunCompleted:
|
||||
"""Tests for normalizing run.completed results."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_run_completed_with_message(self):
|
||||
"""Normalize run.completed with final message."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'run.completed',
|
||||
'data': {
|
||||
'message': {
|
||||
'role': 'assistant',
|
||||
'content': 'Final response',
|
||||
},
|
||||
'finish_reason': 'stop',
|
||||
},
|
||||
}
|
||||
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
|
||||
assert result is not None
|
||||
assert isinstance(result, provider_message.Message)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_run_completed_without_message(self):
|
||||
"""Normalize run.completed without message."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'run.completed',
|
||||
'data': {
|
||||
'finish_reason': 'stop',
|
||||
},
|
||||
}
|
||||
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
|
||||
assert result is None
|
||||
|
||||
|
||||
class TestNormalizeRunFailed:
|
||||
"""Tests for normalizing run.failed results."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_run_failed(self):
|
||||
"""Normalize run.failed raises RunnerExecutionError."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'run.failed',
|
||||
'data': {
|
||||
'error': 'Upstream timeout',
|
||||
'code': 'upstream.timeout',
|
||||
'retryable': True,
|
||||
},
|
||||
}
|
||||
|
||||
with pytest.raises(RunnerExecutionError) as exc_info:
|
||||
await normalizer.normalize(result_dict, descriptor)
|
||||
|
||||
assert exc_info.value.runner_id == 'plugin:langbot/local-agent/default'
|
||||
assert exc_info.value.retryable is True
|
||||
assert 'timeout' in str(exc_info.value)
|
||||
|
||||
|
||||
class TestNormalizeNonMessageResults:
|
||||
"""Tests for normalizing non-message results."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_tool_call_started(self):
|
||||
"""Normalize tool.call.started returns None."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'tool.call.started',
|
||||
'data': {
|
||||
'tool_call_id': 'call_1',
|
||||
'tool_name': 'weather',
|
||||
},
|
||||
}
|
||||
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
assert result is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_tool_call_completed(self):
|
||||
"""Normalize tool.call.completed returns None."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'tool.call.completed',
|
||||
'data': {
|
||||
'tool_call_id': 'call_1',
|
||||
'tool_name': 'weather',
|
||||
'result': {'temp': 20},
|
||||
},
|
||||
}
|
||||
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
assert result is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_state_updated(self):
|
||||
"""Normalize state.updated returns None."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'state.updated',
|
||||
'data': {
|
||||
'key': 'external_conversation_id',
|
||||
'value': 'abc123',
|
||||
},
|
||||
}
|
||||
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
assert result is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_action_requested(self):
|
||||
"""Normalize action.requested returns None (EBA reserved)."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'action.requested',
|
||||
'data': {
|
||||
'action': 'platform.message.edit',
|
||||
'parameters': {},
|
||||
},
|
||||
}
|
||||
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
assert result is None
|
||||
|
||||
|
||||
class TestNormalizeInvalidResults:
|
||||
"""Tests for handling invalid results."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_missing_type(self):
|
||||
"""Normalize result without type."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'data': {},
|
||||
}
|
||||
|
||||
with pytest.raises(RunnerProtocolError) as exc_info:
|
||||
await normalizer.normalize(result_dict, descriptor)
|
||||
|
||||
assert 'Missing result type' in str(exc_info.value)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_unknown_type(self):
|
||||
"""Normalize unknown type returns None."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
result_dict = {
|
||||
'type': 'unknown_type',
|
||||
'data': {},
|
||||
}
|
||||
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
assert result is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normalize_legacy_type_returns_none(self):
|
||||
"""Legacy types (chunk, text, finish) are now treated as unknown."""
|
||||
normalizer = AgentResultNormalizer(FakeApplication())
|
||||
descriptor = make_descriptor()
|
||||
|
||||
# chunk is now unknown
|
||||
result_dict = {
|
||||
'type': 'chunk',
|
||||
'data': {
|
||||
'message_chunk': {
|
||||
'role': 'assistant',
|
||||
'content': 'Legacy chunk',
|
||||
},
|
||||
},
|
||||
}
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
assert result is None
|
||||
|
||||
# text is now unknown
|
||||
result_dict = {
|
||||
'type': 'text',
|
||||
'data': {
|
||||
'content': 'Legacy text',
|
||||
},
|
||||
}
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
assert result is None
|
||||
|
||||
# finish is now unknown
|
||||
result_dict = {
|
||||
'type': 'finish',
|
||||
'data': {
|
||||
'message': {
|
||||
'role': 'assistant',
|
||||
'content': 'Legacy finish',
|
||||
},
|
||||
},
|
||||
}
|
||||
result = await normalizer.normalize(result_dict, descriptor)
|
||||
assert result is None
|
||||
32
uv.lock
generated
32
uv.lock
generated
@@ -1973,7 +1973,7 @@ requires-dist = [
|
||||
{ name = "ebooklib", specifier = ">=0.18" },
|
||||
{ name = "gewechat-client", specifier = ">=0.1.5" },
|
||||
{ name = "html2text", specifier = ">=2024.2.26" },
|
||||
{ name = "langbot-plugin", specifier = "==0.3.11" },
|
||||
{ name = "langbot-plugin", editable = "../langbot-plugin-sdk" },
|
||||
{ name = "langchain", specifier = ">=0.2.0" },
|
||||
{ name = "langchain-core", specifier = ">=1.2.28" },
|
||||
{ name = "langchain-text-splitters", specifier = ">=1.1.2" },
|
||||
@@ -2036,8 +2036,8 @@ dev = [
|
||||
|
||||
[[package]]
|
||||
name = "langbot-plugin"
|
||||
version = "0.3.11"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
version = "0.3.10"
|
||||
source = { editable = "../langbot-plugin-sdk" }
|
||||
dependencies = [
|
||||
{ name = "aiofiles" },
|
||||
{ name = "dotenv" },
|
||||
@@ -2054,9 +2054,29 @@ dependencies = [
|
||||
{ name = "watchdog" },
|
||||
{ name = "websockets" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/91/83/93b86bcdbfe51d820fa59232aaa73cc802d6ce614f67d8f8b33957419538/langbot_plugin-0.3.11.tar.gz", hash = "sha256:8d10c98c771b468b2d35cc007778439c39922a88265fcc16a5881234bc7c1b19", size = 190315, upload-time = "2026-05-12T15:45:24.262Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/8f/22/de7977a6a5cbf557b80043eb3ed39e5feff24033a5d6db4ab88d48ccb6ea/langbot_plugin-0.3.11-py3-none-any.whl", hash = "sha256:c1d2e84eda1584902d99efa316b850c08c1c04fcc199306ff4af1dca1431304a", size = 165574, upload-time = "2026-05-12T15:45:22.908Z" },
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "aiofiles", specifier = ">=24.1.0" },
|
||||
{ name = "dotenv", specifier = ">=0.9.9" },
|
||||
{ name = "httpx", specifier = ">=0.28.1" },
|
||||
{ name = "jinja2", specifier = ">=3.1.6" },
|
||||
{ name = "pip", specifier = ">=25.2" },
|
||||
{ name = "pydantic", specifier = ">=2.11.5" },
|
||||
{ name = "pydantic-settings", specifier = ">=2.10.1" },
|
||||
{ name = "pytest", specifier = ">=8.4.0" },
|
||||
{ name = "pyyaml", specifier = ">=6.0.2" },
|
||||
{ name = "textual", specifier = ">=3.2.0" },
|
||||
{ name = "types-aiofiles", specifier = ">=24.1.0.20250516" },
|
||||
{ name = "types-pyyaml", specifier = ">=6.0.12.20250516" },
|
||||
{ name = "watchdog", specifier = ">=6.0.0" },
|
||||
{ name = "websockets", specifier = ">=15.0.1" },
|
||||
]
|
||||
|
||||
[package.metadata.requires-dev]
|
||||
dev = [
|
||||
{ name = "mypy", specifier = ">=1.16.0" },
|
||||
{ name = "ruff", specifier = ">=0.11.12" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
Reference in New Issue
Block a user