community[patch]: anthropic add tool call support new tools api

libs/langchain-anthropic/src/chat_models.ts

@@ -327,7 +327,7 @@ function _formatContent(content: MessageContent) {
  * @param messages The base messages to format as a prompt.
  * @returns The formatted prompt.
  */
-function _formatMessagesForAnthropic(messages: BaseMessage[]): {
+export function formatMessagesForAnthropic(messages: BaseMessage[]): {
   system?: string;
   messages: AnthropicMessage[];
 } {

libs/langchain-anthropic/src/index.ts

@@ -1 +1,2 @@
 export * from "./chat_models.js";
+export * from "./output_parsers.js";

libs/langchain-community/src/chat_models/bedrock/web.ts

@@ -9,19 +9,24 @@ import {
   type BaseChatModelParams,
   BaseChatModel,
   LangSmithParams,
+  BaseChatModelCallOptions,
 } from "@langchain/core/language_models/chat_models";
+import { BaseLanguageModelInput } from "@langchain/core/language_models/base";
+import { Runnable } from "@langchain/core/runnables";
 import { getEnvironmentVariable } from "@langchain/core/utils/env";
 import {
   AIMessageChunk,
   BaseMessage,
   AIMessage,
   ChatMessage,
+  BaseMessageChunk,
 } from "@langchain/core/messages";
 import {
   ChatGeneration,
   ChatGenerationChunk,
   ChatResult,
 } from "@langchain/core/outputs";
+import { StructuredToolInterface } from "@langchain/core/tools";
 
 import {
   BaseBedrockInput,
@@ -225,6 +230,8 @@ export class BedrockChat extends BaseChatModel implements BaseBedrockInput {
     streamProcessingMode: "SYNCHRONOUS" | "ASYNCHRONOUS";
   };
 
+  tools: (StructuredToolInterface | Record<string, unknown>)[] = [];
+
   get lc_aliases(): Record<string, string> {
     return {
       model: "model_id",
@@ -393,7 +400,8 @@ export class BedrockChat extends BaseChatModel implements BaseBedrockInput {
           this.temperature,
           options.stop ?? this.stopSequences,
           this.modelKwargs,
-          this.guardrailConfig
+          this.guardrailConfig,
+          this.tools
         )
       : BedrockLLMInputOutputAdapter.prepareInput(
           provider,
@@ -602,6 +610,18 @@ export class BedrockChat extends BaseChatModel implements BaseBedrockInput {
   _combineLLMOutput() {
     return {};
   }
+
+  bindTools(
+    tools: (StructuredToolInterface | Record<string, unknown>)[],
+    kwargs?: Partial<BaseChatModelCallOptions>
+  ): Runnable<
+    BaseLanguageModelInput,
+    BaseMessageChunk,
+    BaseChatModelCallOptions
+  > {
+    this.tools = tools;
+    return this;
+  }
 }
 
 function isChatGenerationChunk(

libs/langchain-community/src/utils/bedrock.ts

@@ -4,90 +4,19 @@ import {
   AIMessageChunk,
   BaseMessage,
 } from "@langchain/core/messages";
+import { StructuredToolInterface } from "@langchain/core/tools";
+import { isStructuredTool } from "@langchain/core/utils/function_calling";
 import { ChatGeneration, ChatGenerationChunk } from "@langchain/core/outputs";
+import { zodToJsonSchema } from "zod-to-json-schema";
+import {
+  extractToolCalls,
+  formatMessagesForAnthropic,
+} from "@langchain/anthropic";
 
 export type CredentialType =
   | AwsCredentialIdentity
   | Provider<AwsCredentialIdentity>;
 
-function _formatImage(imageUrl: string) {
-  const regex = /^data:(image\/.+);base64,(.+)$/;
-  const match = imageUrl.match(regex);
-  if (match === null) {
-    throw new Error(
-      [
-        "Anthropic only supports base64-encoded images currently.",
-        "Example: data:image/png;base64,/9j/4AAQSk...",
-      ].join("\n\n")
-    );
-  }
-  return {
-    type: "base64",
-    media_type: match[1] ?? "",
-    data: match[2] ?? "",
-    // eslint-disable-next-line @typescript-eslint/no-explicit-any
-  } as any;
-}
-
-function formatMessagesForAnthropic(messages: BaseMessage[]): {
-  system?: string;
-  messages: Record<string, unknown>[];
-} {
-  let system: string | undefined;
-  if (messages.length > 0 && messages[0]._getType() === "system") {
-    if (typeof messages[0].content !== "string") {
-      throw new Error("System message content must be a string.");
-    }
-    system = messages[0].content;
-  }
-  const conversationMessages =
-    system !== undefined ? messages.slice(1) : messages;
-  const formattedMessages = conversationMessages.map((message) => {
-    let role;
-    if (message._getType() === "human") {
-      role = "user" as const;
-    } else if (message._getType() === "ai") {
-      role = "assistant" as const;
-    } else if (message._getType() === "system") {
-      throw new Error(
-        "System messages are only permitted as the first passed message."
-      );
-    } else {
-      throw new Error(`Message type "${message._getType()}" is not supported.`);
-    }
-    if (typeof message.content === "string") {
-      return {
-        role,
-        content: message.content,
-      };
-    } else {
-      return {
-        role,
-        content: message.content.map((contentPart) => {
-          if (contentPart.type === "image_url") {
-            let source;
-            if (typeof contentPart.image_url === "string") {
-              source = _formatImage(contentPart.image_url);
-            } else {
-              source = _formatImage(contentPart.image_url.url);
-            }
-            return {
-              type: "image" as const,
-              source,
-            };
-          } else {
-            return contentPart;
-          }
-        }),
-      };
-    }
-  });
-  return {
-    messages: formattedMessages,
-    system,
-  };
-}
-
 /**
  * format messages for Cohere Command-R and CommandR+ via AWS Bedrock.
  *
@@ -327,7 +256,8 @@ export class BedrockLLMInputOutputAdapter {
           tagSuffix: string;
           streamProcessingMode: "SYNCHRONOUS" | "ASYNCHRONOUS";
         }
-      | undefined = undefined
+      | undefined = undefined,
+    tools: (StructuredToolInterface | Record<string, unknown>)[] = []
   ): Dict {
     const inputBody: Dict = {};
 
@@ -342,6 +272,21 @@ export class BedrockLLMInputOutputAdapter {
       inputBody.max_tokens = maxTokens;
       inputBody.temperature = temperature;
       inputBody.stop_sequences = stopSequences;
+
+      if (tools.length > 0) {
+        inputBody.tools = tools.map((tool) => {
+          if (isStructuredTool(tool)) {
+            return {
+              name: tool.name,
+              description: tool.description,
+              input_schema: zodToJsonSchema(tool.schema),
+            };
+          }
+
+          return tool;
+        });
+      }
+      return { ...inputBody, ...modelKwargs };
     } else if (provider === "cohere") {
       const {
         system,
@@ -516,10 +461,26 @@ function parseMessage(responseBody: any, asChunk?: boolean): ChatGeneration {
       generationInfo,
     });
   } else {
+    // TODO: we are throwing away here the text response, as the interface of this method returns only one
+    const toolCalls = extractToolCalls(responseBody.content);
+
+    if (toolCalls.length > 0) {
+      return {
+        message: new AIMessage({
+          content: "",
+          additional_kwargs: { id },
+          tool_calls: toolCalls,
+        }),
+        text: typeof parsedContent === "string" ? parsedContent : "",
+        generationInfo,
+      };
+    }
+
     return {
       message: new AIMessage({
         content: parsedContent,
         additional_kwargs: { id },
+        tool_calls: toolCalls,
       }),
       text: typeof parsedContent === "string" ? parsedContent : "",
       generationInfo,