🤖💬 Conversational AI Chatbot with Google Gemini for Text & Image | Telegram

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Conversational AI Chatbot with Google Gemini for Text & Image Telegram Overview Flexible and scalable chatbot template, designed mainly for Spanish conversations but capable of handling E...

Best for

Support Chatbot automation workflows
AI Chatbot automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.set, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatgooglegemini, @n8n/n8n-nodes-langchain.chainllm, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.switch, n8n-nodes-base.code, n8n-nodes-base.httprequest

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Alan Bajaña Granizo.

Original n8n.io source

1.1 Workflow description

Title: 🤖💬 Conversational AI Chatbot with Google Gemini for Text & Image | Telegram
Workflow name: 🤖💬 Conversational AI Chatbot with Google Gemini for Text & Image | Telegram

🤖💬 Conversational AI Chatbot with Google Gemini for Text & Image | Telegram

Overview 📋

Flexible and scalable chatbot template, designed mainly for Spanish conversations but capable of handling English and other languages. Integrates Google Gemini API for text and image generation, and Telegram for messaging. Supports multiple output types with potential for video, audio, and more.

How It Works

Modular Architecture & Extensibility ⚙️

Separate modules for data extraction, intent analysis, and adaptive response generation.
Easily extendable with additional tools, databases, or APIs.

Context & Memory Handling 🧠

Session-based volatile memory maintains conversation coherence.
Allows updates or modifications to previous images based on new requests (e.g., add a hat to a dog 🐶).

Intent Detection & Classification 🔍

Google Gemini accurately classifies user intent.
Two-step validation ensures context-aware, precise replies.

Content Generation & Output ✍️🖼️

Generates text and images based on intent and context.
Designed for Telegram but adaptable to other platforms and media types (audio, video).

Key Benefits ✅

Scalable, customizable, and production-ready architecture.
Supports multiple content formats: text, images, audio, and video.
Dynamic context and memory management for smooth, coherent conversations.
Native integration with Google Gemini and Telegram ensures reliable and seamless operation.
Suitable for diverse use cases and easy to extend with new tools or platforms.

Use Cases 💼

Customer support virtual assistants.
On-demand multimedia content creation.
Marketing and user engagement bots.
AI conversational prototypes and pilots.

Requirements 👨‍💻

n8n instance (self-hosted or cloud)
Google Gemini API credentials
Telegram bot setup (optional but recommended)

Active member of the Polytechnic Artificial Intelligence Club (CIAP) at ESPOL.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - chatPrompt

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 2 - otherPrompt

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 3 - generatePrompt

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 4 - buildPrompt

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 5 - ChatCore

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.9

Block 6 - GeminiModel

Type / Role: @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
Config choices: Version 1

Block 7 - inputProcessor

Type / Role: @n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices: Version 1.6

Block 8 - GeminiModel1

Type / Role: @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
Config choices: Version 1

Block 9 - structuredOutput

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.2

Block 10 - contentType

Type / Role: n8n-nodes-base.switch - switch
Config choices: Version 3.2

Block 11 - textCleaner

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 12 - imageGeneration

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 13 - imageBuilder

Type / Role: n8n-nodes-base.convertToFile - convertToFile
Config choices: Version 1.1

Block 14 - sendImage

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1

Block 15 - sendTextMessage

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1

Block 16 - sessionData

Type / Role: n8n-nodes-base.set - set
Config choices: Version 2

Block 17 - conversationStore

Type / Role: @n8n/n8n-nodes-langchain.memoryManager - memoryManager
Config choices: Version 1.1

Block 18 - memoryRetriever

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 19 - latestContext

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 20 - intentHandler

Type / Role: n8n-nodes-base.switch - switch
Config choices: Version 3.2

Block 21 - userInput

Type / Role: n8n-nodes-base.telegramTrigger - telegramTrigger
Config choices: Version 1

Block 22 - conversationMemory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 23 - errorPreprocessor

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 24 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Showing the first 24 of 28 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	🤖💬 Conversational AI Chatbot with Google Gemini for Text & Image \| Telegram
Complexity	advanced
Nodes	28
Categories	Support Chatbot, AI Chatbot
Author	Alan Bajaña Granizo
Published	24 May 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/4365/4365.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Support Chatbot workflows AI Chatbot workflows

Frequently asked questions

What does 🤖💬 Conversational AI Chatbot with Google Gemini for Text & Image | Telegram do?

Conversational AI Chatbot with Google Gemini for Text & Image Telegram Overview Flexible and scalable chatbot template, designed mainly for Spanish conversations but capable of handling E...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Support Chatbot, AI Chatbot use case.

Alan Bajaña Granizo

1 workflow

Nodes

n8n-nodes-base.set @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.lmchatgooglegemini @n8n/n8n-nodes-langchain.chainllm @n8n/n8n-nodes-langchain.outputparserstructured n8n-nodes-base.switch n8n-nodes-base.code n8n-nodes-base.httprequest

Complexity

advanced

Published 24 May 2025

Likes 0

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Install path: /data/workflows/4365/4365.json

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🤖💬 Conversational AI Chatbot with Google Gemini for Text & Image | Telegram

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

🤖💬 Conversational AI Chatbot with Google Gemini for Text & Image | Telegram

Overview 📋

How It Works

Modular Architecture & Extensibility ⚙️

Context & Memory Handling 🧠

Intent Detection & Classification 🔍

Content Generation & Output ✍️🖼️

Key Benefits ✅

Use Cases 💼

Requirements 👨‍💻

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - chatPrompt

Block 2 - otherPrompt

Block 3 - generatePrompt

Block 4 - buildPrompt

Block 5 - ChatCore

Block 6 - GeminiModel

Block 7 - inputProcessor

Block 8 - GeminiModel1

Block 9 - structuredOutput

Block 10 - contentType

Block 11 - textCleaner

Block 12 - imageGeneration

Block 13 - imageBuilder

Block 14 - sendImage

Block 15 - sendTextMessage

Block 16 - sessionData

Block 17 - conversationStore

Block 18 - memoryRetriever

Block 19 - latestContext

Block 20 - intentHandler

Block 21 - userInput

Block 22 - conversationMemory

Block 23 - errorPreprocessor

Block 24 - Sticky Note

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions