Build a Dynamic AI Chatbot with Custom Python Logic

This Dify Chatflow template empowers you to create a fully customized AI conversational agent. It utilizes a core Python script to call the Dify API, allowing you to pass dynamic variables and process user input before generating a tailored AI response. This approach moves beyond simple prompts, enabling sophisticated, real-time chat interactions for advanced customer support or internal helpdesks.

Workflow Overview

What is this?: This is an advanced Dify Chatflow template designed to provide dynamic, AI-powered chat responses. It connects to the Dify API through a custom Python script, allowing you to process user inputs and variables before generating a response. This creates a flexible and powerful conversational experience that can be adapted to numerous specific use cases.
What problem does it solve?: Standard chatbots often lack the flexibility to handle complex, multi-variable queries or integrate custom logic on the fly. This template solves that by giving you a 'code' node to intercept user input, interact with any API (in this case, Dify's own), and shape the AI's response based on real-time data, preventing generic and unhelpful replies.
What will you get?: You will get a fully functional template that enables you to build highly interactive and intelligent chatbots. This will allow you to automate complex customer service inquiries with personalized answers, create internal helpdesk bots that pull data from your systems, and achieve a new level of conversational AI responsiveness that can be deployed in minutes.

Apps Included

How to Use

Prerequisites

An active Dify account (Cloud or self-hosted).

A Dify API Key (referred to as 'agent_id' in the workflow) with permissions to access the chat API.

Basic understanding of how to pass variables in a Dify Chatflow.

Setup Steps

Import the Workflow

Download the YAML file for this workflow and import it into your Dify workspace to create a new Chatflow application.

Configure Start Node Variables

In the 'Start' node, you will see three input variables. The `agent_id` is where you must paste your Dify API Key. The `var_name` and `var_input` fields are placeholders for any custom data you wish to pass to the Dify API 'inputs' object.

Review the Python Script

Click on the 'Code' node to inspect the Python script. It is pre-configured to make a POST request to the Dify chat-messages endpoint. You can customize the `data` payload here to match your specific needs if required.

Test the Chatflow

Open the chat debugger in Dify. Provide a value for `agent_id`, `var_input`, and a test query. Run the flow to see the AI-generated response appear in the 'Answer' node.

Pro Tips

Enhance the Python script to include error handling. For instance, add a 'try-except' block to catch API connection errors and return a fallback message.

Expand the `inputs` in the API call by adding more variables to the 'Start' node. This allows you to build even more sophisticated and context-aware agents.

Store the `conversation_id` returned by the API to maintain chat history across multiple interactions with the same user.

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Information

Published date8/15/2025
Last updated8/15/2025

Platform

Dify