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core[minor]: Message transformers (#5789)
* core[minor]: Message transformers * chore: lint files * mergeMessageRuns * use concat on messages to concat * cleanup tests * newline string content * implemented rest of code and tests * fixed another test * cr * use factory for shared test vars/funcs * added entrypoint, fixed circ dep * test circ dep * format and drop unnecessary entrypoint * docs and allow for returning runnables in each func * ported another doc * ported last doc * add missing md link * cr * added min core version notes to docs
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‎docs/core_docs/docs/how_to/filter_messages.ipynb

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‎docs/core_docs/docs/how_to/index.mdx

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@@ -74,6 +74,14 @@ These are the core building blocks you can use when building applications.
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- [How to: stream a response back](/docs/how_to/chat_streaming)
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- [How to: track token usage](/docs/how_to/chat_token_usage_tracking)
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### Messages
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[Messages](/docs/concepts/##message-types) are the input and output of chat models. They have some `content` and a `role`, which describes the source of the message.
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- [How to: trim messages](/docs/how_to/trim_messages/)
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- [How to: filter messages](/docs/how_to/filter_messages/)
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- [How to: merge consecutive messages of the same type](/docs/how_to/merge_message_runs/)
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### LLMs
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What LangChain calls [LLMs](/docs/concepts/#llms) are older forms of language models that take a string in and output a string.

‎docs/core_docs/docs/how_to/merge_message_runs.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "ac47bfab-0f4f-42ce-8bb6-898ef22a0338",
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"metadata": {},
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"source": [
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"# How to merge consecutive messages of the same type\n",
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"\n",
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":::note\n",
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"The `mergeMessageRuns` function is available in `@langchain/core` version `0.2.8` and above.\n",
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":::\n",
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"\n",
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"Certain models do not support passing in consecutive messages of the same type (a.k.a. \"runs\" of the same message type).\n",
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"\n",
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"The `mergeMessageRuns` utility makes it easy to merge consecutive messages of the same type.\n",
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"\n",
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"## Basic usage"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "1a215bbb-c05c-40b0-a6fd-d94884d517df",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{\n",
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" \"role\": \"system\",\n",
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" \"content\": \"you're a good assistant.\\nyou always respond with a joke.\"\n",
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"}\n",
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"\n",
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"{\n",
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" \"role\": \"human\",\n",
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" \"content\": [\n",
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" {\n",
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" \"type\": \"text\",\n",
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" \"text\": \"i wonder why it's called langchain\"\n",
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" },\n",
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" {\n",
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" \"type\": \"text\",\n",
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" \"text\": \"and who is harrison chasing anyways\"\n",
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" }\n",
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" ]\n",
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"}\n",
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"\n",
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"{\n",
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" \"role\": \"ai\",\n",
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" \"content\": \"Well, I guess they thought \\\"WordRope\\\" and \\\"SentenceString\\\" just didn't have the same ring to it!\\nWhy, he's probably chasing after the last cup of coffee in the office!\"\n",
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"}\n"
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]
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}
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],
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"source": [
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"import { HumanMessage, SystemMessage, AIMessage, mergeMessageRuns } from \"@langchain/core/messages\";\n",
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"\n",
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"const messages = [\n",
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" new SystemMessage(\"you're a good assistant.\"),\n",
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" new SystemMessage(\"you always respond with a joke.\"),\n",
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" new HumanMessage({ content: [{\"type\": \"text\", \"text\": \"i wonder why it's called langchain\"}] }),\n",
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" new HumanMessage(\"and who is harrison chasing anyways\"),\n",
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" new AIMessage(\n",
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" 'Well, I guess they thought \"WordRope\" and \"SentenceString\" just didn\\'t have the same ring to it!'\n",
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" ),\n",
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" new AIMessage(\"Why, he's probably chasing after the last cup of coffee in the office!\"),\n",
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"];\n",
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"\n",
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"const merged = mergeMessageRuns(messages);\n",
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"console.log(merged.map((x) => JSON.stringify({\n",
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" role: x._getType(),\n",
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" content: x.content,\n",
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"}, null, 2)).join(\"\\n\\n\"));"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0544c811-7112-4b76-8877-cc897407c738",
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"metadata": {},
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"source": [
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"Notice that if the contents of one of the messages to merge is a list of content blocks then the merged message will have a list of content blocks. And if both messages to merge have string contents then those are concatenated with a newline character."
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]
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},
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{
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"cell_type": "markdown",
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"id": "1b2eee74-71c8-4168-b968-bca580c25d18",
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"metadata": {},
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"source": [
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"## Chaining\n",
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"\n",
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"`mergeMessageRuns` can be used in an imperatively (like above) or declaratively, making it easy to compose with other components in a chain:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "6d5a0283-11f8-435b-b27b-7b18f7693592",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"AIMessage {\n",
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" lc_serializable: true,\n",
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" lc_kwargs: {\n",
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" content: [],\n",
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" additional_kwargs: {\n",
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" id: 'msg_01LsdS4bjQ3EznH7Tj4xujV1',\n",
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" type: 'message',\n",
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" role: 'assistant',\n",
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" model: 'claude-3-sonnet-20240229',\n",
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" stop_reason: 'end_turn',\n",
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" stop_sequence: null,\n",
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" usage: [Object]\n",
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" },\n",
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" tool_calls: [],\n",
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" usage_metadata: { input_tokens: 84, output_tokens: 3, total_tokens: 87 },\n",
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" invalid_tool_calls: [],\n",
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" response_metadata: {}\n",
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" },\n",
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" lc_namespace: [ 'langchain_core', 'messages' ],\n",
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" content: [],\n",
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" name: undefined,\n",
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" additional_kwargs: {\n",
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" id: 'msg_01LsdS4bjQ3EznH7Tj4xujV1',\n",
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" type: 'message',\n",
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" role: 'assistant',\n",
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" model: 'claude-3-sonnet-20240229',\n",
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" stop_reason: 'end_turn',\n",
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" stop_sequence: null,\n",
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" usage: { input_tokens: 84, output_tokens: 3 }\n",
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" },\n",
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" response_metadata: {\n",
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" id: 'msg_01LsdS4bjQ3EznH7Tj4xujV1',\n",
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" model: 'claude-3-sonnet-20240229',\n",
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" stop_reason: 'end_turn',\n",
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" stop_sequence: null,\n",
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" usage: { input_tokens: 84, output_tokens: 3 }\n",
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" },\n",
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" id: undefined,\n",
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" tool_calls: [],\n",
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" invalid_tool_calls: [],\n",
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" usage_metadata: { input_tokens: 84, output_tokens: 3, total_tokens: 87 }\n",
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"}\n"
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]
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}
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],
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"source": [
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"import { ChatAnthropic } from \"@langchain/anthropic\";\n",
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"import { mergeMessageRuns } from \"@langchain/core/messages\";\n",
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"\n",
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"const llm = new ChatAnthropic({ model: \"claude-3-sonnet-20240229\", temperature: 0 });\n",
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"// Notice we don't pass in messages. This creates\n",
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"// a RunnableLambda that takes messages as input\n",
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"const merger = mergeMessageRuns();\n",
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"const chain = merger.pipe(llm);\n",
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"await chain.invoke(messages);"
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]
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},
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{
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"cell_type": "markdown",
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"id": "72e90dce-693c-4842-9526-ce6460fe956b",
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"metadata": {},
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"source": [
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"Looking at [the LangSmith trace](https://smith.langchain.com/public/48d256fb-fd7e-48a0-bdfd-217ab74ad01d/r) we can see that before the messages are passed to the model they are merged.\n",
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"\n",
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"Looking at just the merger, we can see that it's a Runnable object that can be invoked like all Runnables:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "460817a6-c327-429d-958e-181a8c46059c",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[\n",
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" SystemMessage {\n",
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" lc_serializable: true,\n",
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" lc_kwargs: {\n",
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" content: \"you're a good assistant.\\nyou always respond with a joke.\",\n",
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" name: undefined,\n",
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" additional_kwargs: {},\n",
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" response_metadata: {},\n",
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" id: undefined\n",
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" },\n",
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" lc_namespace: [ 'langchain_core', 'messages' ],\n",
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" content: \"you're a good assistant.\\nyou always respond with a joke.\",\n",
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" name: undefined,\n",
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" additional_kwargs: {},\n",
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" response_metadata: {},\n",
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" id: undefined\n",
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" },\n",
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" HumanMessage {\n",
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" lc_serializable: true,\n",
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" lc_kwargs: {\n",
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" content: [Array],\n",
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" name: undefined,\n",
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" additional_kwargs: {},\n",
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" response_metadata: {},\n",
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" id: undefined\n",
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" },\n",
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" lc_namespace: [ 'langchain_core', 'messages' ],\n",
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" content: [ [Object], [Object] ],\n",
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" name: undefined,\n",
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" additional_kwargs: {},\n",
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" response_metadata: {},\n",
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" id: undefined\n",
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" },\n",
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" AIMessage {\n",
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" lc_serializable: true,\n",
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" lc_kwargs: {\n",
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" content: `Well, I guess they thought \"WordRope\" and \"SentenceString\" just didn't have the same ring to it!\\n` +\n",
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" \"Why, he's probably chasing after the last cup of coffee in the office!\",\n",
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" name: undefined,\n",
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" additional_kwargs: {},\n",
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" response_metadata: {},\n",
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" id: undefined,\n",
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" tool_calls: [],\n",
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" invalid_tool_calls: [],\n",
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" usage_metadata: undefined\n",
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" },\n",
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" lc_namespace: [ 'langchain_core', 'messages' ],\n",
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" content: `Well, I guess they thought \"WordRope\" and \"SentenceString\" just didn't have the same ring to it!\\n` +\n",
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" \"Why, he's probably chasing after the last cup of coffee in the office!\",\n",
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" name: undefined,\n",
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" additional_kwargs: {},\n",
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" response_metadata: {},\n",
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" id: undefined,\n",
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" tool_calls: [],\n",
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" invalid_tool_calls: [],\n",
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" usage_metadata: undefined\n",
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" }\n",
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"]\n"
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]
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}
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],
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"source": [
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"await merger.invoke(messages)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4548d916-ce21-4dc6-8f19-eedb8003ace6",
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"metadata": {},
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"source": [
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"## API reference\n",
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"\n",
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"For a complete description of all arguments head to the [API reference](https://api.js.langchain.com/functions/langchain_core_messages.mergeMessageRuns.html)."
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]
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}
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