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false | 0 | \"\")[]): T[] {\n return arr.filter((item): item is T => Boolean(item));\n}\n\n/**\n * Converts a BeeAI Message to LangChain content format.\n * Supports text, image, and file content types.\n * @param message - The BeeAI message to convert\n * @returns String content or array of content parts\n */\nfunction toLCContent(\n message: Message,\n): string | { type: string; text?: string; url?: string; [key: string]: any }[] {\n if (message instanceof ToolMessage) {\n const toolResult = message.getToolResults()[0];\n if (!toolResult) {\n Logger.root.warn(\"ToolMessage has no tool results, returning empty string\");\n return \"\";\n }\n\n if (\"value\" in toolResult.output && isString(toolResult.output.value)) {\n return toolResult.output.value;\n }\n\n return JSON.stringify(toolResult.output);\n }\n\n const lcContent: ({ type: string; text?: string; url?: string; [key: string]: any } | null)[] =\n [];\n\n for (const part of message.content) {\n if (part.type === \"text\") {\n lcContent.push({ type: \"text\", text: part.text });\n } else if (part.type === \"image\") {\n const imageUrl = part.image instanceof URL ? part.image.toString() : String(part.image);\n lcContent.push({ type: \"image\", url: imageUrl });\n } else if (part.type === \"file\") {\n lcContent.push({\n type: \"file\",\n file_data: part.data,\n format: part.mediaType,\n ...(part.filename && { filename: part.filename }),\n });\n } else {\n lcContent.push(null);\n }\n }\n\n return removeFalsy(lcContent);\n}\n\n/**\n * Converts tool call input to LangChain arguments format.\n * Parses JSON strings and handles broken JSON gracefully.\n * @param input - The tool call input (object or JSON string)\n * @returns Tool arguments as a record object\n */\nfunction toLCToolArgs(input: unknown): Record {\n if (isPlainObject(input)) {\n return input;\n }\n\n if (isString(input)) {\n try {\n const parsed = parseBrokenJson(input, { pair: [\"{\", \"}\"] });\n if (isPlainObject(parsed)) {\n return parsed;\n }\n } catch (error) {\n Logger.root.warn(\n \"Failed to parse tool arguments: \" +\n (error instanceof Error ? error.message : String(error)),\n );\n }\n }\n\n return {};\n}\n\n/**\n * Converts AssistantMessage tool calls to LangChain format.\n * @param message - The assistant message with tool calls\n * @returns Array of LangChain tool call objects\n */\nfunction toLCToolCalls(message: AssistantMessage) {\n return message.getToolCalls().map((toolCall) => ({\n id: toolCall.toolCallId,\n name: toolCall.toolName,\n args: toLCToolArgs(toolCall.input),\n type: \"tool_call\" as const,\n }));\n}\n\n/**\n * Converts LangChain message content to BeeAI TextPart array.\n * Handles strings, arrays, and text objects. Filters out empty values.\n * @param content - The LangChain message content\n * @returns Array of BeeAI TextPart objects\n */\nfunction toBeeAITextParts(content: unknown): TextPart[] {\n if (typeof content === \"string\") {\n return content ? [{ type: \"text\", text: content }] : [];\n }\n\n if (!Array.isArray(content)) {\n if (content !== null && content !== undefined) {\n Logger.root.warn(`Unexpected content type in toBeeAITextParts: ${typeof content}`);\n }\n return [];\n }\n\n return content.flatMap((part) => {\n if (typeof part === \"string\") {\n return part ? [{ type: \"text\", text: part }] : [];\n }\n\n if (\n part &&\n typeof part === \"object\" &&\n \"type\" in part &&\n part.type === \"text\" &&\n \"text\" in part\n ) {\n return [{ type: \"text\", text: String(part.text ?? \"\") }];\n }\n\n return [];\n });\n}\n\n/**\n * Converts LangChain message content to BeeAI content parts for UserMessage.\n * Supports text, image (URL or base64), and file content types.\n * @param content - The LangChain message content\n * @returns Array of TextPart, ImagePart, or FilePart objects\n */\nfunction toBeeAIUserContentParts(content: unknown): (TextPart | ImagePart | FilePart)[] {\n if (typeof content === \"string\") {\n return content ? [{ type: \"text\", text: content }] : [];\n }\n\n if (!Array.isArray(content)) {\n if (content !== null && content !== undefined) {\n Logger.root.warn(`Unexpected content type in toBeeAIContentParts: ${typeof content}`);\n }\n return [];\n }\n\n const results: (TextPart | ImagePart | FilePart | null)[] = [];\n\n for (const part of content) {\n if (typeof part === \"string\") {\n if (part) {\n results.push({ type: \"text\", text: part });\n }\n continue;\n }\n\n if (!part || typeof part !== \"object\" || !(\"type\" in part)) {\n continue;\n }\n\n if (part.type === \"text\" && \"text\" in part) {\n results.push({ type: \"text\", text: String(part.text ?? \"\") });\n continue;\n }\n\n if (part.type === \"image\") {\n let imageUrl = \"\";\n\n if (\"url\" in part && part.url) {\n imageUrl = String(part.url);\n } else if (\"data\" in part && \"mime_type\" in part) {\n imageUrl = `data:${part.mime_type};base64,${part.data}`;\n }\n\n if (imageUrl) {\n results.push({\n type: \"image\",\n image: imageUrl,\n });\n }\n continue;\n }\n\n if (part.type === \"file\") {\n let fileData = \"\";\n let mediaType = \"application/octet-stream\";\n let filename: string | undefined;\n\n if (\"file_id\" in part && part.file_id) {\n fileData = String(part.file_id);\n } else if (\"file_data\" in part && part.file_data) {\n fileData = String(part.file_data);\n }\n\n if (\"format\" in part && part.format) {\n mediaType = String(part.format);\n } else if (\"mime_type\" in part && part.mime_type) {\n mediaType = String(part.mime_type);\n }\n\n if (\"filename\" in part && part.filename) {\n filename = String(part.filename);\n }\n\n if (fileData) {\n results.push({\n type: \"file\",\n data: fileData,\n mediaType,\n ...(filename && { filename }),\n });\n }\n }\n }\n\n return removeFalsy(results);\n}\n\n/**\n * Converts a LangChain tool call to BeeAI ToolCallPart format.\n * @param toolCall - The LangChain tool call object\n * @returns BeeAI ToolCallPart\n */\nfunction toBeeAIToolCall(toolCall: { id?: string; name?: string; args?: unknown }): ToolCallPart {\n return {\n type: \"tool-call\",\n toolCallId: toolCall.id ?? \"\",\n toolName: toolCall.name ?? \"\",\n input: toolCall.args ?? {},\n };\n}\n\n/**\n * Converts a LangChain ToolMessage to BeeAI ToolResultPart.\n * Falls back to artifact field if content is empty.\n * @param message - The LangChain tool message\n * @returns BeeAI ToolResultPart object\n */\nfunction toBeeAIToolResult(message: LCToolMessage): ToolResultPart {\n let content: string;\n if (typeof message.content === \"string\" && message.content !== \"\") {\n content = message.content;\n } else if (message.content !== undefined && message.content !== null && message.content !== \"\") {\n content = JSON.stringify(message.content);\n } else if (\"artifact\" in message && message.artifact !== undefined && message.artifact !== null) {\n content =\n typeof message.artifact === \"string\" ? message.artifact : JSON.stringify(message.artifact);\n } else {\n content = typeof message.content === \"string\" ? message.content : \"\";\n }\n\n return {\n type: \"tool-result\",\n toolCallId: message.tool_call_id,\n toolName: String(message.response_metadata?.tool_name ?? \"unknown\"),\n output: {\n type: \"text\",\n value: content,\n },\n };\n}\n\n/**\n * Converts BeeAI Messages to LangChain BaseMessage format.\n * Handles UserMessage, AssistantMessage, ToolMessage, and SystemMessage.\n * ToolMessages with multiple results are split into separate messages with ID suffixes.\n * Unknown types fallback to LCUserMessage.\n * @param messages - Array of BeeAI messages\n * @returns Array of LangChain BaseMessage objects\n */\nexport function toLCMessages(messages: Message[]): LCBaseMessage[] {\n const output: LCBaseMessage[] = [];\n\n for (const msg of messages) {\n if (msg instanceof UserMessage) {\n output.push(new LCUserMessage({ content: toLCContent(msg), id: msg.id }));\n continue;\n }\n\n if (msg instanceof AssistantMessage) {\n output.push(\n new LCAIMessage({\n content: toLCContent(msg),\n id: msg.id,\n tool_calls: toLCToolCalls(msg),\n }),\n );\n continue;\n }\n\n if (msg instanceof ToolMessage) {\n const toolResults = msg.getToolResults();\n for (let i = 0; i < toolResults.length; i++) {\n const toolResult = toolResults[i];\n const messageId = toolResults.length > 1 ? msg.id + \"-\" + i : msg.id;\n output.push(\n new LCToolMessage({\n id: messageId,\n content:\n \"value\" in toolResult.output && isString(toolResult.output.value)\n ? toolResult.output.value\n : JSON.stringify(toolResult.output),\n tool_call_id: toolResult.toolCallId,\n response_metadata: { tool_name: toolResult.toolName },\n }),\n );\n }\n continue;\n }\n\n if (msg instanceof SystemMessage) {\n output.push(new LCSystemMessage({ content: toLCContent(msg), id: msg.id }));\n continue;\n }\n\n output.push(new LCUserMessage({ content: toLCContent(msg), id: msg.id }));\n }\n\n return output;\n}\n\n/**\n * Converts LangChain BaseMessages to BeeAI Message format.\n * Handles LCUserMessage, LCAIMessage, AIMessageChunk, LCSystemMessage, and LCToolMessage.\n * Throws ValueError for unknown message types.\n * @param messages - Array of LangChain messages\n * @returns Array of BeeAI Message objects\n */\nexport function toBeeAIMessages(messages: LCBaseMessage[]): Message[] {\n return messages.map((msg) => {\n if (msg instanceof LCUserMessage) {\n return new UserMessage(toBeeAIUserContentParts(msg.content), msg.response_metadata, msg.id);\n }\n\n if (msg instanceof LCAIMessage || msg instanceof AIMessageChunk) {\n return new AssistantMessage(\n [...toBeeAITextParts(msg.content), ...(msg.tool_calls ?? []).map(toBeeAIToolCall)],\n msg.response_metadata,\n msg.id,\n );\n }\n\n if (msg instanceof LCSystemMessage) {\n return new SystemMessage(toBeeAITextParts(msg.content), msg.response_metadata, msg.id);\n }\n\n if (msg instanceof LCToolMessage) {\n return new ToolMessage(toBeeAIToolResult(msg), msg.response_metadata, msg.id);\n }\n\n // Use .type property (LangChain 1.x) with fallback to constructor.name\n const typeName = \"type\" in msg && msg.type ? String(msg.type) : msg.constructor.name;\n throw new ValueError(\"Unsupported message type: \" + typeName);\n });\n}\n\n/**\n * Converts a BeeAI Tool to LangChain DynamicStructuredTool.\n * Wraps the tool's run method and extracts text content from results.\n * @param tool - The BeeAI tool to convert\n * @returns Promise resolving to LangChain DynamicStructuredTool\n */\nexport async function beeaiToolToLCTool(tool: any): Promise {\n const schema = await tool.inputSchema();\n\n return new DynamicStructuredTool({\n name: tool.name,\n description: tool.description,\n schema,\n func: async (input: any) => {\n const result = await tool.run(input);\n return result.getTextContent();\n },\n });\n}\n"]}