Build an AI Powered Phone Agent 📞🤖 with Retell, Google Calendar and RAG — n8n 工作流

复杂度🔗 Webhook29 个节点 AI👁 22,555 次查看作者:Davide Boizza

概览

This Workflow simulates an AI-powered phone agent with RetellAI with two main functions:

📅 Appointment Booking – It can schedule appointments directly into Google Calendar.
🧠 RAG-based Information Retrieval – It provides answers using a Retrieval-Augmented Generation (RAG) system. For example, it can respond to questions such as store opening hours, return policies, or product details.

The guide also explains how to purchase a dedicated phone number (with a +1 prefix) and link it to the AI a

使用的节点

HTTP RequestTelegramGoogle DriveGoogle CalendarAI AgentBasic LLM ChainEmbeddings OpenAIOpenAI Chat ModelStructured Output ParserToken SplitterDefault Data LoaderQdrant Vector StoreVector Store Question Answer Tool

工作流预览

STEP 3 - RETELL AI
- Register on Retell AI (10$ FREE credits)
- Create an Agent an set "Voice & Language" and add you
- In Webhook setti
STEP 4
Intercept the "end call" event and get the full call tr
- Add your CHAT_ID in Telegram node
STEP 1
Create Qdrant Collection
Change:
- QDRANTURL
- COLLECTION
STEP 2
Documents vectorization with Qdrant and Google Drive
Change:
- QDRANTURL
- COLLECTION
STEP 5
If required, create the event in the calendar
- Enter the title and description of the event
STEP 6
If required retrive the informations by RAG system
Create your first AI Phone Agent
Build, test, deploy, and monitor AI phone agents. Retel
Conv
MY NEW YOUTUBE CHANNEL
👉 Subscribe to my new YouTube channel. Here I’ll share
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toolembedmodelembedmodelmodelmodeldocparserparser
F
Filter
OpenAI Chat Model
Structured Output Parser
N
n8n_rag_function
Retrive Qdrant Vector St…
Embeddings OpenAI2
RAG
OpenAI Chat Model2
R
Respond to Webhook
OpenAI Chat Model1
Telegram
Google Calendar
OpenAI Chat Model3
Structured Output Parser1
N
n8n_call
N
n8n_check_available
W
When clicking ‘Test work…
Qdrant Vector Store
Create collection
Refresh collection
Get folder
Download Files
Embeddings OpenAI
Default Data Loader
Token Splitter
S
Set call fields
Extract key points
Concert start date
Retrive Agent
29 nodes25 edges

工作原理

  1. 1

    触发器

    工作流由 webhook 触发器启动。

  2. 2

    处理

    数据流经 29 个节点, connecting agent, chainllm, documentdefaultdataloader。

  3. 3

    输出

    工作流完成自动化并将结果发送到配置的目标。

节点详情 (29)

HT

HTTP Request

httpRequest

#1
TE

Telegram

telegram

#2
GO

Google Drive

googleDrive

#3
GO

Google Calendar

googleCalendar

#4
AI

AI Agent

n8n-nodes-langchain.agent

#5
BA

Basic LLM Chain

n8n-nodes-langchain.chainLlm

#6
EM

Embeddings OpenAI

n8n-nodes-langchain.embeddingsOpenAi

#7
OP

OpenAI Chat Model

n8n-nodes-langchain.lmChatOpenAi

#8
ST

Structured Output Parser

n8n-nodes-langchain.outputParserStructured

#9
TO

Token Splitter

n8n-nodes-langchain.textSplitterTokenSplitter

#10
DE

Default Data Loader

n8n-nodes-langchain.documentDefaultDataLoader

#11
QD

Qdrant Vector Store

n8n-nodes-langchain.vectorStoreQdrant

#12
VE

Vector Store Question Answer Tool

n8n-nodes-langchain.toolVectorStore

#13

如何导入此工作流

  1. 1点击右侧 下载 JSON 按钮保存工作流文件。
  2. 2打开你的 n8n 实例,依次点击 工作流 → 新建 → 从文件导入
  3. 3选择下载的 build-an-ai-powered-phone-agent-with-retell-google-calendar-and-rag 文件并点击导入。
  4. 4为每个服务节点配置 凭证(API 密钥、OAuth 等)。
  5. 5点击 测试工作流 验证一切正常,然后激活它。

或直接在 n8n → 从 JSON 导入 中粘贴:

{ "name": "Build an AI Powered Phone Agent 📞🤖 with Retell, Google Calendar and RAG", "nodes": [...], ...}

集成

agentchainllmdocumentdefaultdataloaderembeddingsopenaifiltergooglecalendargoogledrivehttprequestlmchatopenaimanualtriggeroutputparserstructuredrespondtowebhooksettelegramtextsplittertokensplittertoolvectorstorevectorstoreqdrantwebhook

获取此工作流

一键下载并导入

下载 JSON在 n8n.io 上查看
节点29
复杂度high
触发器webhook
查看次数22,555
分类AI

创建者

Davide Boizza

Davide Boizza

@n3witalia

标签

agentchainllmdocumentdefaultdataloaderembeddingsopenaifiltergooglecalendargoogledrivehttprequestlmchatopenaimanualtrigger

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