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feat(langgraph): Add tool support to LangGraph templates (#130)
* feat(langgraph): Add tool support to LangGraph templates This PR adds tool calls to LangGraph templates. It creates tools using `@langchain/core/tools` with zod schemas. * Use zodType macro for JSON Schema type mapping * Guard tool import by variant * Add toolcalls to cloudflare too * Check langchain style function args as well * Revert expansion of toolcall args to be in line with OTel
1 parent d559ed5 commit 9452281

6 files changed

Lines changed: 117 additions & 4 deletions

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‎src/runner/templates/agents/browser/langgraph/config.json‎

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@@ -7,7 +7,8 @@
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{ "package": "@sentry/browser", "version": "sentry" },
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{ "package": "@langchain/langgraph", "version": "framework" },
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{ "package": "@langchain/openai", "version": "1.2.12" },
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{ "package": "@langchain/core", "version": "1.1.30" }
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{ "package": "@langchain/core", "version": "1.1.30" },
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{ "package": "zod", "version": "3" }
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],
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"versions": ["1.2.0"],
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"sentryVersions": ["latest"],

‎src/runner/templates/agents/browser/langgraph/template.njk‎

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@@ -9,6 +9,11 @@
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{% extends "base.browser.njk" %}
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{# Macro to render message content - handles both string and multimodal array #}
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{# Macro to convert JSON Schema type to Zod type #}
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{% macro zodType(type_str) -%}
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{% if type_str == 'number' %}z.number(){% elif type_str == 'integer' %}z.number().int(){% elif type_str == 'boolean' %}z.boolean(){% else %}z.string(){% endif %}
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{%- endmacro %}
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{% macro renderLangChainContent(content) %}
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{% if content is string %}
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"{{ content }}"
@@ -34,6 +39,10 @@
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{% endif %}
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const { ChatOpenAI } = await import("@langchain/openai");
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const { HumanMessage, SystemMessage } = await import("@langchain/core/messages");
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{% if variant == "compiled" and agent and agent.tools and agent.tools.length > 0 %}
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const { tool } = await import("@langchain/core/tools");
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const { z } = await import("zod");
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{% endif %}
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{% if variant == "custom-state" %}
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const { StateGraph, Annotation, START, END } = langgraphModule;
@@ -56,7 +65,33 @@
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apiKey: OPENAI_API_KEY,
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});
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const agent = createReactAgent({ llm, tools: [], name: "{{ agent.name }}" });
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{% if agent and agent.tools and agent.tools.length > 0 %}
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const tools = [
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{% for toolDef in agent.tools %}
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tool(async (input) => {
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{% if toolDef.error %}
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throw new Error("{{ toolDef.error }}");
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{% elif toolDef.result is defined %}
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return {{ toolDef.result | dump }};
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{% else %}
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return input;
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{% endif %}
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}, {
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name: "{{ toolDef.name }}",
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description: "{{ toolDef.description }}",
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schema: z.object({
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{% if toolDef.parameters and toolDef.parameters.properties %}
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{% for paramName, paramDef in toolDef.parameters.properties %}
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{{ paramName }}: {{ zodType(paramDef.type) }}{% if paramDef.description %}.describe("{{ paramDef.description }}"){% endif %},
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{% endfor %}
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{% endif %}
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}),
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}),
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{% endfor %}
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];
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{% endif %}
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const agent = createReactAgent({ llm, tools: {% if agent and agent.tools and agent.tools.length > 0 %}tools{% else %}[]{% endif %}, name: "{{ agent.name }}" });
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Sentry.instrumentLangGraph(agent, { recordInputs: true, recordOutputs: true });
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log('LangGraph initialized with instrumentLangGraph on compiled graph');

‎src/runner/templates/agents/cloudflare/langgraph/config.json‎

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@@ -15,6 +15,10 @@
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{
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"package": "@langchain/core",
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"version": "0.3.49"
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},
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{
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"package": "zod",
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"version": "3"
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}
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],
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"versions": ["0.2.67"],

‎src/runner/templates/agents/cloudflare/langgraph/template.njk‎

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Original file line numberDiff line numberDiff line change
@@ -1,5 +1,10 @@
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{% extends "base.cloudflare.njk" %}
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{# Macro to convert JSON Schema type to Zod type #}
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{% macro zodType(type_str) -%}
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{% if type_str == 'number' %}z.number(){% elif type_str == 'integer' %}z.number().int(){% elif type_str == 'boolean' %}z.boolean(){% else %}z.string(){% endif %}
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{%- endmacro %}
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{# Macro to render message content for LangChain/LangGraph - handles both string and multimodal array #}
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{% macro renderLangChainContent(content) %}
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{% if content is string %}
@@ -21,14 +26,44 @@
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import { ChatOpenAI } from "@langchain/openai";
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import { createReactAgent } from "@langchain/langgraph/prebuilt";
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import { HumanMessage, SystemMessage } from "@langchain/core/messages";
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{% if agent and agent.tools and agent.tools.length > 0 %}
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import { tool } from "@langchain/core/tools";
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import { z } from "zod";
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{% endif %}
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{% endblock %}
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{% block dynamic_imports %}
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{% if agent and agent.tools and agent.tools.length > 0 %}
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const tools = [
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{% for toolDef in agent.tools %}
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tool(async (input) => {
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{% if toolDef.error %}
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throw new Error("{{ toolDef.error }}");
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{% elif toolDef.result is defined %}
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return {{ toolDef.result | dump }};
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{% else %}
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return input;
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{% endif %}
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}, {
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name: "{{ toolDef.name }}",
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description: "{{ toolDef.description }}",
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schema: z.object({
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{% if toolDef.parameters and toolDef.parameters.properties %}
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{% for paramName, paramDef in toolDef.parameters.properties %}
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{{ paramName }}: {{ zodType(paramDef.type) }}{% if paramDef.description %}.describe("{{ paramDef.description }}"){% endif %},
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{% endfor %}
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{% endif %}
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}),
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}),
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{% endfor %}
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];
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{% endif %}
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const llm = new ChatOpenAI({
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modelName: {% if causeAPIError %}"invalid-model"{% else %}"{{ inputs[0].model }}"{% endif %},
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openAIApiKey: env.OPENAI_API_KEY,
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});
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const agent = createReactAgent({ llm, tools: [] });
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const agent = createReactAgent({ llm, tools: {% if agent and agent.tools and agent.tools.length > 0 %}tools{% else %}[]{% endif %}, name: "{{ agent.name }}" });
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Sentry.instrumentLangGraph(agent, { recordInputs: true, recordOutputs: true });
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{% endblock %}
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‎src/runner/templates/agents/node/langgraph/config.json‎

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@@ -15,6 +15,10 @@
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{
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"package": "@langchain/core",
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"version": "0.3.49"
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},
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{
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"package": "zod",
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"version": "3"
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}
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],
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"versions": ["0.2.67"],

‎src/runner/templates/agents/node/langgraph/template.njk‎

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Original file line numberDiff line numberDiff line change
@@ -17,14 +17,48 @@
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{%- endif %}
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{% endmacro %}
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{# Macro to convert JSON Schema type to Zod type #}
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{% macro zodType(type_str) -%}
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{% if type_str == 'number' %}z.number(){% elif type_str == 'integer' %}z.number().int(){% elif type_str == 'boolean' %}z.boolean(){% else %}z.string(){% endif %}
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{%- endmacro %}
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{% block dynamic_imports %}
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const { ChatOpenAI } = await import("@langchain/openai");
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const { createReactAgent } = await import("@langchain/langgraph/prebuilt");
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const { HumanMessage, SystemMessage } = await import("@langchain/core/messages");
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{% if agent and agent.tools and agent.tools.length > 0 %}
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const { tool } = await import("@langchain/core/tools");
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const { z } = await import("zod");
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const tools = [
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{% for toolDef in agent.tools %}
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tool(async (input) => {
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{% if toolDef.error %}
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throw new Error("{{ toolDef.error }}");
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{% elif toolDef.result is defined %}
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return {{ toolDef.result | dump }};
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{% else %}
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return input;
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{% endif %}
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}, {
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name: "{{ toolDef.name }}",
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description: "{{ toolDef.description }}",
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schema: z.object({
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{% if toolDef.parameters and toolDef.parameters.properties %}
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{% for paramName, paramDef in toolDef.parameters.properties %}
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{{ paramName }}: {{ zodType(paramDef.type) }}{% if paramDef.description %}.describe("{{ paramDef.description }}"){% endif %},
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{% endfor %}
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{% endif %}
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}),
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}),
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{% endfor %}
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];
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{% endif %}
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const llm = new ChatOpenAI({
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modelName: {% if causeAPIError %}"invalid-model"{% else %}"{{ inputs[0].model }}"{% endif %},
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});
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const agent = createReactAgent({ llm, tools: [], name: "{{ agent.name }}" });
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const agent = createReactAgent({ llm, tools: {% if agent and agent.tools and agent.tools.length > 0 %}tools{% else %}[]{% endif %}, name: "{{ agent.name }}" });
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{% endblock %}
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{% block test %}

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