diff --git a/docs/core_docs/docs/integrations/toolkits/openapi.ipynb b/docs/core_docs/docs/integrations/toolkits/openapi.ipynb
index aed7938407f4..12851b13fe99 100644
--- a/docs/core_docs/docs/integrations/toolkits/openapi.ipynb
+++ b/docs/core_docs/docs/integrations/toolkits/openapi.ipynb
@@ -216,8 +216,6 @@
"source": [
"import { createReactAgent } from \"@langchain/langgraph/prebuilt\"\n",
"\n",
- "import { ChatOpenAI } from \"@langchain/openai\";\n",
- "\n",
"const agentExecutor = createReactAgent({ llm, tools });"
]
},
diff --git a/docs/core_docs/docs/integrations/tools/duckduckgo_search.ipynb b/docs/core_docs/docs/integrations/tools/duckduckgo_search.ipynb
index 972f48899208..939a9471be48 100644
--- a/docs/core_docs/docs/integrations/tools/duckduckgo_search.ipynb
+++ b/docs/core_docs/docs/integrations/tools/duckduckgo_search.ipynb
@@ -31,7 +31,7 @@
"\n",
"| Class | Package | Serializable | [PY support](https://python.langchain.com/docs/integrations/tools/ddg/) | Package latest |\n",
"| :--- | :--- | :---: | :---: | :---: |\n",
- "| [DuckDuckGoSearch](https://api.js.langchain.com/classes/langchain_community_tools_duckduckgo_search.DuckDuckGoSearch.html) | [@langchain/community](https://api.js.langchain.com/modules/langchain_community_tools_duckduckgo_search.html) | beta | ✅ |  |\n",
+ "| [DuckDuckGoSearch](https://api.js.langchain.com/classes/langchain_community_tools_duckduckgo_search.DuckDuckGoSearch.html) | [@langchain/community](https://api.js.langchain.com/modules/langchain_community_tools_duckduckgo_search.html) | ❌ | ✅ |  |\n",
"\n",
"## Setup\n",
"\n",
@@ -169,7 +169,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 1,
"id": "af3123ad-7a02-40e5-b58e-7d56e23e5830",
"metadata": {},
"outputs": [],
@@ -261,61 +261,70 @@
"source": [
"## With an agent\n",
"\n",
- "We can also pass the `DuckDuckGoSearch` tool to an agent:"
+ "We can also pass the `DuckDuckGoSearch` tool to an agent. First, ensure you have the LangGraph package installed.\n",
+ "\n",
+ "```{=mdx}\n",
+ "\n",
+ " @langchain/langgraph\n",
+ "\n",
+ "```"
]
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 3,
"id": "77a05a61",
"metadata": {},
+ "outputs": [],
+ "source": [
+ "import { DuckDuckGoSearch } from \"@langchain/community/tools/duckduckgo_search\";\n",
+ "import { createReactAgent } from \"@langchain/langgraph/prebuilt\";\n",
+ "\n",
+ "// Define the tools the agent will have access to.\n",
+ "const toolsForAgent = [new DuckDuckGoSearch({ maxResults: 1 })];\n",
+ "\n",
+ "const agentExecutor = createReactAgent({ llm, tools: toolsForAgent });"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "3130e547",
+ "metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "{\n",
- " input: \"What is Anthropic's estimated revenue for 2024?\",\n",
- " output: 'Anthropic has projected that it will generate more than $850 million in annualized revenue by the end of 2024.'\n",
- "}\n"
+ "[\n",
+ " {\n",
+ " name: 'duckduckgo-search',\n",
+ " args: { input: 'Anthropic estimated revenue 2024' },\n",
+ " type: 'tool_call',\n",
+ " id: 'call_eZwbyemMAu8tgQw4VqJs65hF'\n",
+ " }\n",
+ "]\n",
+ "[{\"title\":\"Anthropic forecasts more than $850 mln in annualized revenue rate by ...\",\"link\":\"https://www.reuters.com/technology/anthropic-forecasts-more-than-850-mln-annualized-revenue-rate-by-2024-end-report-2023-12-26/\",\"snippet\":\"Dec 26 (Reuters) - Artificial intelligence startup Anthropic has projected it will generate more than $850 million in annualized revenue by the end of 2024, the Information reported on Tuesday ...\"}]\n",
+ "Anthropic is projected to generate more than $850 million in annualized revenue by the end of 2024.\n"
]
}
],
"source": [
- "import { DuckDuckGoSearch } from \"@langchain/community/tools/duckduckgo_search\";\n",
- "import { ChatOpenAI } from \"@langchain/openai\";\n",
- "import type { ChatPromptTemplate } from \"@langchain/core/prompts\";\n",
- "\n",
- "import { pull } from \"langchain/hub\";\n",
- "import { AgentExecutor, createOpenAIFunctionsAgent } from \"langchain/agents\";\n",
+ "const exampleQuery = \"What is Anthropic's estimated revenue for 2024?\"\n",
"\n",
- "// Define the tools the agent will have access to.\n",
- "const toolsForAgent = [new DuckDuckGoSearch({ maxResults: 1 })];\n",
+ "const events = await agentExecutor.stream(\n",
+ " { messages: [[\"user\", exampleQuery]]},\n",
+ " { streamMode: \"values\", }\n",
+ ")\n",
"\n",
- "// Get the prompt to use - you can modify this!\n",
- "// If you want to see the prompt in full, you can at:\n",
- "// https://smith.langchain.com/hub/hwchase17/openai-functions-agent\n",
- "const promptForAgent = await pull(\n",
- " \"hwchase17/openai-functions-agent\"\n",
- ");\n",
- "const llmForAgent = new ChatOpenAI({\n",
- " model: \"gpt-4-turbo-preview\",\n",
- " temperature: 0,\n",
- "});\n",
- "const agent = await createOpenAIFunctionsAgent({\n",
- " llm: llmForAgent,\n",
- " tools: toolsForAgent,\n",
- " prompt: promptForAgent,\n",
- "});\n",
- "const agentExecutor = new AgentExecutor({\n",
- " agent,\n",
- " tools: toolsForAgent,\n",
- "});\n",
- "const agentResult = await agentExecutor.invoke({\n",
- " input: \"What is Anthropic's estimated revenue for 2024?\",\n",
- "});\n",
- "\n",
- "console.log(agentResult);"
+ "for await (const event of events) {\n",
+ " const lastMsg = event.messages[event.messages.length - 1];\n",
+ " if (lastMsg.tool_calls?.length) {\n",
+ " console.dir(lastMsg.tool_calls, { depth: null });\n",
+ " } else if (lastMsg.content) {\n",
+ " console.log(lastMsg.content);\n",
+ " }\n",
+ "}"
]
},
{