@copilotkit/runtime/dist/agent/converters/tanstack.cjs.map

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{"version":3,"file":"tanstack.cjs","names":["EventType"],"sources":["../../../src/agent/converters/tanstack.ts"],"sourcesContent":["import {\n  BaseEvent,\n  EventType,\n  RunAgentInput,\n  Message,\n  TextMessageChunkEvent,\n  ToolCallArgsEvent,\n  ToolCallEndEvent,\n  ToolCallStartEvent,\n  ToolCallResultEvent,\n  StateSnapshotEvent,\n  StateDeltaEvent,\n  ReasoningStartEvent,\n  ReasoningMessageStartEvent,\n  ReasoningMessageContentEvent,\n  ReasoningMessageEndEvent,\n  ReasoningEndEvent,\n} from \"@ag-ui/client\";\nimport { randomUUID } from \"@copilotkit/shared\";\n\ntype ContentPartSource =\n  | { type: \"data\"; value: string; mimeType: string }\n  | { type: \"url\"; value: string; mimeType?: string };\n\n/**\n * A TanStack AI content part (text, image, audio, video, or document).\n */\nexport type TanStackContentPart =\n  | { type: \"text\"; content: string }\n  | { type: \"image\"; source: ContentPartSource }\n  | { type: \"audio\"; source: ContentPartSource }\n  | { type: \"video\"; source: ContentPartSource }\n  | { type: \"document\"; source: ContentPartSource };\n\n/**\n * Message format expected by TanStack AI's `chat()`.\n *\n * Content is typed as `any[]` for the multimodal case so messages are directly\n * passable to any adapter without casts — different adapters constrain which\n * modalities they accept (e.g. OpenAI only allows text + image).\n * Use `TanStackContentPart` to inspect individual parts if needed.\n */\nexport interface TanStackChatMessage {\n  role: \"user\" | \"assistant\" | \"tool\";\n  // eslint-disable-next-line @typescript-eslint/no-explicit-any\n  content: string | null | any[];\n  name?: string;\n  toolCalls?: Array<{\n    id: string;\n    type: \"function\";\n    function: { name: string; arguments: string };\n  }>;\n  toolCallId?: string;\n}\n\n/**\n * Result of converting RunAgentInput to TanStack AI format.\n */\nexport interface TanStackInputResult {\n  /** Chat messages (only user/assistant/tool roles; all others excluded) */\n  messages: TanStackChatMessage[];\n  /** System prompts extracted from system/developer messages, context, and state */\n  systemPrompts: string[];\n}\n\n/**\n * Converts AG-UI user message content to TanStack AI format.\n * Handles plain strings, multimodal parts (image/audio/video/document),\n * and legacy BinaryInputContent for backward compatibility.\n */\nfunction convertUserContent(\n  content: unknown,\n): string | null | TanStackContentPart[] {\n  if (!content) return null;\n  if (typeof content === \"string\") return content;\n  if (!Array.isArray(content)) return null;\n  if (content.length === 0) return \"\";\n\n  const parts: TanStackContentPart[] = [];\n\n  for (const part of content) {\n    if (!part || typeof part !== \"object\" || !(\"type\" in part)) continue;\n\n    switch ((part as { type: string }).type) {\n      case \"text\": {\n        const text = (part as { text?: string }).text;\n        if (text != null) parts.push({ type: \"text\", content: text });\n        break;\n      }\n\n      case \"image\":\n      case \"audio\":\n      case \"video\":\n      case \"document\": {\n        const source = (part as { source?: any }).source;\n        if (!source) break;\n        const partType = (part as { type: string }).type as\n          | \"image\"\n          | \"audio\"\n          | \"video\"\n          | \"document\";\n        if (source.type === \"data\") {\n          parts.push({\n            type: partType,\n            source: {\n              type: \"data\",\n              value: source.value,\n              mimeType: source.mimeType,\n            },\n          });\n        } else if (source.type === \"url\") {\n          parts.push({\n            type: partType,\n            source: {\n              type: \"url\",\n              value: source.value,\n              ...(source.mimeType ? { mimeType: source.mimeType } : {}),\n            },\n          });\n        }\n        break;\n      }\n\n      // Legacy BinaryInputContent backward compatibility\n      case \"binary\": {\n        const legacy = part as {\n          mimeType?: string;\n          data?: string;\n          url?: string;\n        };\n        const mimeType = legacy.mimeType ?? \"application/octet-stream\";\n        const isImage = mimeType.startsWith(\"image/\");\n\n        if (legacy.data) {\n          const partType = isImage ? \"image\" : \"document\";\n          parts.push({\n            type: partType,\n            source: { type: \"data\", value: legacy.data, mimeType },\n          });\n        } else if (legacy.url) {\n          const partType = isImage ? \"image\" : \"document\";\n          parts.push({\n            type: partType,\n            source: { type: \"url\", value: legacy.url, mimeType },\n          });\n        }\n        break;\n      }\n    }\n  }\n\n  return parts.length > 0 ? parts : \"\";\n}\n\n/**\n * Converts a RunAgentInput into the format expected by TanStack AI's `chat()`.\n *\n * - Keeps only user/assistant/tool messages (activity, reasoning, and other roles are also excluded)\n * - Extracts system/developer messages into `systemPrompts`\n * - Appends context entries and application state to `systemPrompts`\n * - Preserves tool calls on assistant messages and toolCallId on tool messages\n */\nexport function convertInputToTanStackAI(\n  input: RunAgentInput,\n): TanStackInputResult {\n  // Allowlist: only pass user/assistant/tool messages to TanStack.\n  // Other roles (system, developer, activity, reasoning) are either\n  // extracted into systemPrompts or not applicable.\n  const chatRoles = new Set([\"user\", \"assistant\", \"tool\"]);\n  const messages: TanStackChatMessage[] = input.messages\n    .filter((m: Message) => chatRoles.has(m.role))\n    .map((m: Message): TanStackChatMessage => {\n      const msg: TanStackChatMessage = {\n        role: m.role as \"user\" | \"assistant\" | \"tool\",\n        content:\n          m.role === \"user\"\n            ? convertUserContent(m.content)\n            : typeof m.content === \"string\"\n              ? m.content\n              : null,\n      };\n      if (m.role === \"assistant\" && \"toolCalls\" in m && m.toolCalls) {\n        msg.toolCalls = m.toolCalls.map((tc) => ({\n          id: tc.id,\n          type: \"function\" as const,\n          function: {\n            name: tc.function.name,\n            arguments: tc.function.arguments,\n          },\n        }));\n      }\n      if (m.role === \"tool\" && \"toolCallId\" in m) {\n        msg.toolCallId = (m as Record<string, unknown>).toolCallId as string;\n      }\n      return msg;\n    });\n\n  const systemPrompts: string[] = [];\n  for (const m of input.messages) {\n    if ((m.role === \"system\" || m.role === \"developer\") && m.content) {\n      systemPrompts.push(\n        typeof m.content === \"string\" ? m.content : JSON.stringify(m.content),\n      );\n    }\n  }\n\n  if (input.context?.length) {\n    for (const ctx of input.context) {\n      systemPrompts.push(`${ctx.description}:\\n${ctx.value}`);\n    }\n  }\n\n  if (\n    input.state !== undefined &&\n    input.state !== null &&\n    typeof input.state === \"object\" &&\n    Object.keys(input.state).length > 0\n  ) {\n    systemPrompts.push(\n      `Application State:\\n\\`\\`\\`json\\n${JSON.stringify(input.state, null, 2)}\\n\\`\\`\\``,\n    );\n  }\n\n  return { messages, systemPrompts };\n}\n\n/**\n * Converts a TanStack AI stream into AG-UI `BaseEvent` objects.\n *\n * This is a pure converter — it does NOT emit lifecycle events\n * (RUN_STARTED / RUN_FINISHED / RUN_ERROR). The caller (Agent class)\n * is responsible for those.\n */\nexport async function* convertTanStackStream(\n  stream: AsyncIterable<unknown>,\n  abortSignal: AbortSignal,\n): AsyncGenerator<BaseEvent> {\n  const messageId = randomUUID();\n  const toolNamesById = new Map<string, string>();\n  // Track the reasoning lifecycle at two granularities so closeReasoningIfOpen\n  // emits exactly the events still owed. A single boolean conflates the run\n  // (REASONING_START → REASONING_END) with the message\n  // (REASONING_MESSAGE_START → REASONING_MESSAGE_END) and produces a duplicate\n  // REASONING_MESSAGE_END when upstream emits MSG_END but not END before\n  // text/tools resume.\n  let reasoningRunOpen = false;\n  let reasoningMessageOpen = false;\n  let reasoningMessageId = randomUUID();\n\n  function* closeReasoningIfOpen(): Generator<BaseEvent> {\n    if (reasoningMessageOpen) {\n      reasoningMessageOpen = false;\n      const msgEnd: ReasoningMessageEndEvent = {\n        type: EventType.REASONING_MESSAGE_END,\n        messageId: reasoningMessageId,\n      };\n      yield msgEnd;\n    }\n    if (reasoningRunOpen) {\n      reasoningRunOpen = false;\n      const end: ReasoningEndEvent = {\n        type: EventType.REASONING_END,\n        messageId: reasoningMessageId,\n      };\n      yield end;\n    }\n  }\n\n  // TanStack's chat() engine runs a multi-turn agent loop: after the model\n  // returns tool calls, the engine tries to execute them and re-prompt. This\n  // produces a second round of TOOL_CALL_START / TOOL_CALL_END events that\n  // duplicate the ones from the first streaming pass. The CopilotKit runtime\n  // handles tool execution externally (via the frontend SDK), so we must stop\n  // converting events once the TanStack adapter signals the first turn is\n  // complete with RUN_FINISHED.\n  let runFinished = false;\n\n  for await (const chunk of stream) {\n    if (abortSignal.aborted) break;\n\n    const raw = chunk as Record<string, unknown>;\n    const type = raw.type as string;\n\n    // Stop converting after the first RUN_FINISHED — any subsequent events\n    // come from TanStack's internal tool-execution loop and would produce\n    // duplicate TOOL_CALL_END events that violate the ag-ui verify middleware.\n    if (type === \"RUN_FINISHED\") {\n      runFinished = true;\n      continue;\n    }\n    if (runFinished) continue;\n\n    if (type === \"TEXT_MESSAGE_CONTENT\" && raw.delta != null) {\n      yield* closeReasoningIfOpen();\n      const textEvent: TextMessageChunkEvent = {\n        type: EventType.TEXT_MESSAGE_CHUNK,\n        role: \"assistant\",\n        messageId,\n        delta: raw.delta as string,\n      };\n      yield textEvent;\n    } else if (type === \"TOOL_CALL_START\") {\n      yield* closeReasoningIfOpen();\n      toolNamesById.set(raw.toolCallId as string, raw.toolCallName as string);\n      const startEvent: ToolCallStartEvent = {\n        type: EventType.TOOL_CALL_START,\n        parentMessageId: messageId,\n        toolCallId: raw.toolCallId as string,\n        toolCallName: raw.toolCallName as string,\n      };\n      yield startEvent;\n    } else if (type === \"TOOL_CALL_ARGS\") {\n      yield* closeReasoningIfOpen();\n      const argsEvent: ToolCallArgsEvent = {\n        type: EventType.TOOL_CALL_ARGS,\n        toolCallId: raw.toolCallId as string,\n        delta: raw.delta as string,\n      };\n      yield argsEvent;\n    } else if (type === \"TOOL_CALL_END\") {\n      yield* closeReasoningIfOpen();\n      const endEvent: ToolCallEndEvent = {\n        type: EventType.TOOL_CALL_END,\n        toolCallId: raw.toolCallId as string,\n      };\n      yield endEvent;\n    } else if (type === \"TOOL_CALL_RESULT\") {\n      yield* closeReasoningIfOpen();\n      const toolCallId = raw.toolCallId as string;\n      const toolName = toolNamesById.get(toolCallId);\n      // Accept the payload from either `content` (canonical TanStack shape)\n      // or `result` (alternate shape used by some adapters / tests). Both\n      // state-tool detection and the final TOOL_CALL_RESULT serialization\n      // must read the same field, otherwise STATE_SNAPSHOT/STATE_DELTA can\n      // be silently dropped when upstream uses `result`.\n      const rawPayload = raw.content ?? raw.result;\n\n      const parsedContent =\n        typeof rawPayload === \"string\" ? safeParse(rawPayload) : rawPayload;\n\n      if (\n        toolName === \"AGUISendStateSnapshot\" &&\n        parsedContent &&\n        typeof parsedContent === \"object\" &&\n        \"snapshot\" in parsedContent\n      ) {\n        const stateSnapshotEvent: StateSnapshotEvent = {\n          type: EventType.STATE_SNAPSHOT,\n          snapshot: (parsedContent as Record<string, unknown>).snapshot,\n        };\n        yield stateSnapshotEvent;\n      }\n\n      if (\n        toolName === \"AGUISendStateDelta\" &&\n        parsedContent &&\n        typeof parsedContent === \"object\" &&\n        \"delta\" in parsedContent\n      ) {\n        const stateDeltaEvent: StateDeltaEvent = {\n          type: EventType.STATE_DELTA,\n          delta: (parsedContent as Record<string, unknown>).delta as never,\n        };\n        yield stateDeltaEvent;\n      }\n\n      let serializedContent: string;\n      if (typeof rawPayload === \"string\") {\n        serializedContent = rawPayload;\n      } else {\n        try {\n          serializedContent = JSON.stringify(rawPayload ?? null);\n        } catch {\n          serializedContent = \"[Unserializable tool result]\";\n        }\n      }\n\n      const resultEvent: ToolCallResultEvent = {\n        type: EventType.TOOL_CALL_RESULT,\n        role: \"tool\",\n        messageId: randomUUID(),\n        toolCallId,\n        content: serializedContent,\n      };\n      yield resultEvent;\n      toolNamesById.delete(toolCallId);\n    } else if (type === \"REASONING_START\") {\n      // If a prior reasoning run is still open (no REASONING_END before this\n      // new START), close it cleanly first so MSG_END / END pair correctly.\n      yield* closeReasoningIfOpen();\n      reasoningRunOpen = true;\n      reasoningMessageId = (raw.messageId as string) ?? randomUUID();\n      const startEvt: ReasoningStartEvent = {\n        type: EventType.REASONING_START,\n        messageId: reasoningMessageId,\n      };\n      yield startEvt;\n    } else if (type === \"REASONING_MESSAGE_START\") {\n      reasoningMessageOpen = true;\n      const evt: ReasoningMessageStartEvent = {\n        type: EventType.REASONING_MESSAGE_START,\n        messageId: reasoningMessageId,\n        role: \"reasoning\",\n      };\n      yield evt;\n    } else if (type === \"REASONING_MESSAGE_CONTENT\") {\n      const evt: ReasoningMessageContentEvent = {\n        type: EventType.REASONING_MESSAGE_CONTENT,\n        messageId: reasoningMessageId,\n        delta: raw.delta as string,\n      };\n      yield evt;\n    } else if (type === \"REASONING_MESSAGE_END\") {\n      reasoningMessageOpen = false;\n      const evt: ReasoningMessageEndEvent = {\n        type: EventType.REASONING_MESSAGE_END,\n        messageId: reasoningMessageId,\n      };\n      yield evt;\n    } else if (type === \"REASONING_END\") {\n      // If upstream sends REASONING_END while a message is still open, emit\n      // the missing REASONING_MESSAGE_END FIRST so the closing pair stays in\n      // order (MSG_END before END). 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