@langchain/anthropic/dist/utils/message_inputs.cjs.map

Anthropic integrations for LangChain.js

{"version":3,"file":"message_inputs.cjs","names":["imageUrl: string","parsedUrl: URL","messages: BaseMessage[]","HumanMessage","toolCall: ToolCall","content: ContentBlock[]","standardContentBlockConverter","_isAnthropicImageBlockParam","_isAnthropicThinkingBlock","block: AnthropicThinkingBlockParam","_isAnthropicRedactedThinkingBlock","block: AnthropicRedactedThinkingBlockParam","_isAnthropicSearchResultBlock","block: AnthropicSearchResultBlockParam","message: BaseMessage","_formatStandardContent","messages: AnthropicMessageCreateParams[\"messages\"]","result: AnthropicMessageCreateParams[\"messages\"]","content:\n      | string\n      | Array<\n          | AnthropicTextBlockParam\n          | AnthropicImageBlockParam\n          | AnthropicToolUseBlockParam\n          | AnthropicToolResultBlockParam\n          | AnthropicDocumentBlockParam\n          | AnthropicThinkingBlockParam\n          | AnthropicRedactedThinkingBlockParam\n          | AnthropicServerToolUseBlockParam\n          | AnthropicWebSearchToolResultBlockParam\n          | AnthropicSearchResultBlockParam\n        >","msg: (typeof messages)[0]"],"sources":["../../src/utils/message_inputs.ts"],"sourcesContent":["/**\n * This util file contains functions for converting LangChain messages to Anthropic messages.\n */\nimport type Anthropic from \"@anthropic-ai/sdk\";\nimport {\n  type BaseMessage,\n  HumanMessage,\n  ToolMessage,\n  MessageContentComplex,\n  isDataContentBlock,\n  convertToProviderContentBlock,\n  parseBase64DataUrl,\n  ContentBlock,\n  isAIMessage,\n} from \"@langchain/core/messages\";\nimport { ToolCall } from \"@langchain/core/messages/tool\";\nimport {\n  AnthropicImageBlockParam,\n  AnthropicMessageCreateParams,\n  AnthropicTextBlockParam,\n  AnthropicToolResultBlockParam,\n  AnthropicToolUseBlockParam,\n  AnthropicDocumentBlockParam,\n  AnthropicThinkingBlockParam,\n  AnthropicRedactedThinkingBlockParam,\n  AnthropicServerToolUseBlockParam,\n  AnthropicWebSearchToolResultBlockParam,\n  AnthropicSearchResultBlockParam,\n  AnthropicToolResponse,\n  AnthropicContainerUploadBlockParam,\n} from \"../types.js\";\nimport {\n  _isAnthropicImageBlockParam,\n  _isAnthropicRedactedThinkingBlock,\n  _isAnthropicSearchResultBlock,\n  _isAnthropicThinkingBlock,\n  standardContentBlockConverter,\n} from \"./content.js\";\nimport { _formatStandardContent } from \"./standard.js\";\n\nfunction _formatImage(imageUrl: string) {\n  const parsed = parseBase64DataUrl({ dataUrl: imageUrl });\n  if (parsed) {\n    return {\n      type: \"base64\",\n      media_type: parsed.mime_type,\n      data: parsed.data,\n    };\n  }\n  let parsedUrl: URL;\n\n  try {\n    parsedUrl = new URL(imageUrl);\n  } catch {\n    throw new Error(\n      [\n        `Malformed image URL: ${JSON.stringify(\n          imageUrl\n        )}. Content blocks of type 'image_url' must be a valid http, https, or base64-encoded data URL.`,\n        \"Example: data:image/png;base64,/9j/4AAQSk...\",\n        \"Example: https://example.com/image.jpg\",\n      ].join(\"\\n\\n\")\n    );\n  }\n\n  if (parsedUrl.protocol === \"http:\" || parsedUrl.protocol === \"https:\") {\n    return {\n      type: \"url\",\n      url: imageUrl,\n    };\n  }\n\n  throw new Error(\n    [\n      `Invalid image URL protocol: ${JSON.stringify(\n        parsedUrl.protocol\n      )}. Anthropic only supports images as http, https, or base64-encoded data URLs on 'image_url' content blocks.`,\n      \"Example: data:image/png;base64,/9j/4AAQSk...\",\n      \"Example: https://example.com/image.jpg\",\n    ].join(\"\\n\\n\")\n  );\n}\n\nfunction _ensureMessageContents(messages: BaseMessage[]): BaseMessage[] {\n  // Merge runs of human/tool messages into single human messages with content blocks.\n  const updatedMsgs = [];\n  for (const message of messages) {\n    if (message._getType() === \"tool\") {\n      if (typeof message.content === \"string\") {\n        const previousMessage = updatedMsgs[updatedMsgs.length - 1];\n        if (\n          previousMessage?._getType() === \"human\" &&\n          Array.isArray(previousMessage.content) &&\n          \"type\" in previousMessage.content[0] &&\n          previousMessage.content[0].type === \"tool_result\"\n        ) {\n          // If the previous message was a tool result, we merge this tool message into it.\n          (previousMessage.content as MessageContentComplex[]).push({\n            type: \"tool_result\",\n            content: message.content,\n            tool_use_id: (message as ToolMessage).tool_call_id,\n          });\n        } else {\n          // If not, we create a new human message with the tool result.\n          updatedMsgs.push(\n            new HumanMessage({\n              content: [\n                {\n                  type: \"tool_result\",\n                  content: message.content,\n                  tool_use_id: (message as ToolMessage).tool_call_id,\n                },\n              ],\n            })\n          );\n        }\n      } else {\n        updatedMsgs.push(\n          new HumanMessage({\n            content: [\n              {\n                type: \"tool_result\",\n                // rare case: message.content could be undefined\n                ...(message.content != null\n                  ? { content: _formatContent(message) }\n                  : {}),\n                tool_use_id: (message as ToolMessage).tool_call_id,\n              },\n            ],\n          })\n        );\n      }\n    } else {\n      updatedMsgs.push(message);\n    }\n  }\n  return updatedMsgs;\n}\n\nexport function _convertLangChainToolCallToAnthropic(\n  toolCall: ToolCall\n): AnthropicToolResponse {\n  if (toolCall.id === undefined) {\n    throw new Error(`Anthropic requires all tool calls to have an \"id\".`);\n  }\n  return {\n    type: \"tool_use\",\n    id: toolCall.id,\n    name: toolCall.name,\n    input: toolCall.args,\n  };\n}\n\nfunction* _formatContentBlocks(\n  content: ContentBlock[]\n): Generator<Anthropic.Beta.BetaContentBlockParam> {\n  const toolTypes = [\n    \"bash_code_execution_tool_result\",\n    \"input_json_delta\",\n    \"server_tool_use\",\n    \"text_editor_code_execution_tool_result\",\n    \"tool_result\",\n    \"tool_use\",\n    \"web_search_result\",\n    \"web_search_tool_result\",\n  ];\n  const textTypes = [\"text\", \"text_delta\"];\n  for (const contentPart of content) {\n    if (isDataContentBlock(contentPart)) {\n      yield convertToProviderContentBlock(\n        contentPart,\n        standardContentBlockConverter\n      );\n    }\n\n    const cacheControl =\n      \"cache_control\" in contentPart ? contentPart.cache_control : undefined;\n\n    if (contentPart.type === \"image_url\") {\n      let source;\n      if (typeof contentPart.image_url === \"string\") {\n        source = _formatImage(contentPart.image_url);\n      } else if (\n        typeof contentPart.image_url === \"object\" &&\n        contentPart.image_url !== null &&\n        \"url\" in contentPart.image_url &&\n        typeof contentPart.image_url.url === \"string\"\n      ) {\n        source = _formatImage(contentPart.image_url.url);\n      }\n      if (source) {\n        yield {\n          type: \"image\" as const, // Explicitly setting the type as \"image\"\n          source,\n          ...(cacheControl ? { cache_control: cacheControl } : {}),\n        } as Anthropic.Messages.ImageBlockParam;\n      }\n    } else if (_isAnthropicImageBlockParam(contentPart)) {\n      return contentPart;\n    } else if (contentPart.type === \"document\") {\n      // PDF\n      yield {\n        ...contentPart,\n        ...(cacheControl ? { cache_control: cacheControl } : {}),\n      } as Anthropic.Messages.DocumentBlockParam;\n    } else if (_isAnthropicThinkingBlock(contentPart)) {\n      const block: AnthropicThinkingBlockParam = {\n        type: \"thinking\" as const, // Explicitly setting the type as \"thinking\"\n        thinking: contentPart.thinking,\n        signature: contentPart.signature,\n        ...(cacheControl ? { cache_control: cacheControl } : {}),\n      };\n      yield block;\n    } else if (_isAnthropicRedactedThinkingBlock(contentPart)) {\n      const block: AnthropicRedactedThinkingBlockParam = {\n        type: \"redacted_thinking\" as const, // Explicitly setting the type as \"redacted_thinking\"\n        data: contentPart.data,\n        ...(cacheControl ? { cache_control: cacheControl } : {}),\n      };\n      yield block;\n    } else if (_isAnthropicSearchResultBlock(contentPart)) {\n      const block: AnthropicSearchResultBlockParam = {\n        type: \"search_result\" as const, // Explicitly setting the type as \"search_result\"\n        title: contentPart.title,\n        source: contentPart.source,\n        ...(\"cache_control\" in contentPart && contentPart.cache_control\n          ? { cache_control: contentPart.cache_control }\n          : {}),\n        ...(\"citations\" in contentPart && contentPart.citations\n          ? { citations: contentPart.citations }\n          : {}),\n        content: contentPart.content,\n      };\n      yield block as Anthropic.Beta.BetaSearchResultBlockParam;\n    } else if (\n      textTypes.find((t) => t === contentPart.type) &&\n      \"text\" in contentPart\n    ) {\n      // Assuming contentPart is of type MessageContentText here\n      yield {\n        type: \"text\" as const, // Explicitly setting the type as \"text\"\n        text: contentPart.text,\n        ...(cacheControl ? { cache_control: cacheControl } : {}),\n        ...(\"citations\" in contentPart && contentPart.citations\n          ? { citations: contentPart.citations }\n          : {}),\n      } as Anthropic.Messages.TextBlockParam;\n    } else if (toolTypes.find((t) => t === contentPart.type)) {\n      const contentPartCopy = { ...contentPart };\n      if (\"index\" in contentPartCopy) {\n        // Anthropic does not support passing the index field here, so we remove it.\n        delete contentPartCopy.index;\n      }\n\n      if (contentPartCopy.type === \"input_json_delta\") {\n        // `input_json_delta` type only represents yielding partial tool inputs\n        // and is not a valid type for Anthropic messages.\n        contentPartCopy.type = \"tool_use\";\n      }\n\n      if (\"input\" in contentPartCopy) {\n        // Anthropic tool use inputs should be valid objects, when applicable.\n        if (typeof contentPartCopy.input === \"string\") {\n          try {\n            contentPartCopy.input = JSON.parse(contentPartCopy.input);\n          } catch {\n            contentPartCopy.input = {};\n          }\n        }\n      }\n      // TODO: Fix when SDK types are fixed\n      yield {\n        ...contentPartCopy,\n        ...(cacheControl ? { cache_control: cacheControl } : {}),\n        // eslint-disable-next-line @typescript-eslint/no-explicit-any\n      } as any;\n    } else if (contentPart.type === \"container_upload\") {\n      yield {\n        ...contentPart,\n        ...(cacheControl ? { cache_control: cacheControl } : {}),\n      } as AnthropicContainerUploadBlockParam;\n    }\n\n    // Note that we are intentionally dropping any blocks that we don't\n    // recognize. This is to allow for cross-compatibility between different\n    // providers that may have different block types. Ie if we take a message\n    // output from OpenAI and send it to Anthropic, we want to drop any blocks\n    // that Anthropic doesn't understand.\n  }\n}\n\nfunction _formatContent(message: BaseMessage) {\n  const { content } = message;\n\n  if (typeof content === \"string\") {\n    return content;\n  } else {\n    return Array.from(_formatContentBlocks(content));\n  }\n}\n\n/**\n * Formats messages as a prompt for the model.\n * Used in LangSmith, export is important here.\n * @param messages The base messages to format as a prompt.\n * @returns The formatted prompt.\n */\nexport function _convertMessagesToAnthropicPayload(\n  messages: BaseMessage[]\n): AnthropicMessageCreateParams {\n  const mergedMessages = _ensureMessageContents(messages);\n  let system;\n  if (mergedMessages.length > 0 && mergedMessages[0]._getType() === \"system\") {\n    system = messages[0].content;\n  }\n  const conversationMessages =\n    system !== undefined ? mergedMessages.slice(1) : mergedMessages;\n  const formattedMessages = conversationMessages.map((message) => {\n    let role;\n    if (message._getType() === \"human\") {\n      role = \"user\" as const;\n    } else if (message._getType() === \"ai\") {\n      role = \"assistant\" as const;\n    } else if (message._getType() === \"tool\") {\n      role = \"user\" as const;\n    } else if (message._getType() === \"system\") {\n      throw new Error(\n        \"System messages are only permitted as the first passed message.\"\n      );\n    } else {\n      throw new Error(`Message type \"${message.type}\" is not supported.`);\n    }\n    if (\n      isAIMessage(message) &&\n      message.response_metadata?.output_version === \"v1\"\n    ) {\n      return {\n        role,\n        content: _formatStandardContent(message),\n      };\n    }\n    if (isAIMessage(message) && !!message.tool_calls?.length) {\n      if (typeof message.content === \"string\") {\n        if (message.content === \"\") {\n          return {\n            role,\n            content: message.tool_calls.map(\n              _convertLangChainToolCallToAnthropic\n            ),\n          };\n        } else {\n          return {\n            role,\n            content: [\n              { type: \"text\", text: message.content },\n              ...message.tool_calls.map(_convertLangChainToolCallToAnthropic),\n            ],\n          };\n        }\n      } else {\n        const { content } = message;\n        const hasMismatchedToolCalls = !message.tool_calls.every((toolCall) =>\n          content.find(\n            (contentPart) =>\n              (contentPart.type === \"tool_use\" ||\n                contentPart.type === \"input_json_delta\" ||\n                contentPart.type === \"server_tool_use\") &&\n              contentPart.id === toolCall.id\n          )\n        );\n        if (hasMismatchedToolCalls) {\n          console.warn(\n            `The \"tool_calls\" field on a message is only respected if content is a string.`\n          );\n        }\n        return {\n          role,\n          content: _formatContent(message),\n        };\n      }\n    } else {\n      return {\n        role,\n        content: _formatContent(message),\n      };\n    }\n  });\n  return {\n    messages: mergeMessages(\n      formattedMessages as AnthropicMessageCreateParams[\"messages\"]\n    ),\n    system,\n  } as AnthropicMessageCreateParams;\n}\n\nfunction mergeMessages(messages: AnthropicMessageCreateParams[\"messages\"]) {\n  if (!messages || messages.length <= 1) {\n    return messages;\n  }\n\n  const result: AnthropicMessageCreateParams[\"messages\"] = [];\n  let currentMessage = messages[0];\n\n  const normalizeContent = (\n    content:\n      | string\n      | Array<\n          | AnthropicTextBlockParam\n          | AnthropicImageBlockParam\n          | AnthropicToolUseBlockParam\n          | AnthropicToolResultBlockParam\n          | AnthropicDocumentBlockParam\n          | AnthropicThinkingBlockParam\n          | AnthropicRedactedThinkingBlockParam\n          | AnthropicServerToolUseBlockParam\n          | AnthropicWebSearchToolResultBlockParam\n          | AnthropicSearchResultBlockParam\n        >\n  ): Array<\n    | AnthropicTextBlockParam\n    | AnthropicImageBlockParam\n    | AnthropicToolUseBlockParam\n    | AnthropicToolResultBlockParam\n    | AnthropicDocumentBlockParam\n    | AnthropicThinkingBlockParam\n    | AnthropicRedactedThinkingBlockParam\n    | AnthropicServerToolUseBlockParam\n    | AnthropicWebSearchToolResultBlockParam\n    | AnthropicSearchResultBlockParam\n  > => {\n    if (typeof content === \"string\") {\n      return [\n        {\n          type: \"text\",\n          text: content,\n        },\n      ];\n    }\n    return content;\n  };\n\n  const isToolResultMessage = (msg: (typeof messages)[0]) => {\n    if (msg.role !== \"user\") return false;\n\n    if (typeof msg.content === \"string\") {\n      return false;\n    }\n\n    return (\n      Array.isArray(msg.content) &&\n      msg.content.every((item) => item.type === \"tool_result\")\n    );\n  };\n\n  for (let i = 1; i < messages.length; i += 1) {\n    const nextMessage = messages[i];\n\n    if (\n      isToolResultMessage(currentMessage) &&\n      isToolResultMessage(nextMessage)\n    ) {\n      // Merge the messages by combining their content arrays\n      currentMessage = {\n        ...currentMessage,\n        content: [\n          ...normalizeContent(currentMessage.content),\n          ...normalizeContent(nextMessage.content),\n        ],\n      };\n    } else {\n      result.push(currentMessage);\n      currentMessage = nextMessage;\n    }\n  }\n\n  result.push(currentMessage);\n  return 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