Chatbots improve user engagement by providing real-time interaction. They can answer queries, guide users, and enhance the overall app experience. Chatbots are highly scalable. As your user base grows, a well-implemented chatbot can handle increased demand with minimal resource allocation.When paired with Firebase, chatbots built in FlutterFlow can support real-time communication. This is ideal for customer support, live FAQs, or messaging-based apps.
Prerequisites
flutterflow
Firebase
Gemini
1. Create a Flutterflow project
Go to the Flutterflow console.
Click on Create a project and follow the instructions to set up a new project.
Firebase Project Setup
Firebase is a Google platform offering tools to build, improve, and scale apps across mobile, web, and desktop, with services like real-time databases, authentication, and serverless backend solutions.
To set up your Firebase project, please follow the steps below:
1. Create a firebase project
Go to the Firebase Console.
Click on Create a project and follow the instructions to set up a new project.
2. Enable Firebase Authentication
In the Firebase console, go to the Authentication section.
Click Get Started and enable the sign-in methods you need (e.g., Email/Password, Google).
3. Connect Firebase with FlutterFlow
Copy the Project ID from your Firebase project.
Open the Settings of your FlutterFlow project.
Choose Firebase Project, paste the copied Firebase Project ID, and connect it with Firebase.
Gemini
Gemini is a family of advanced AI models developed by Google DeepMind. It's designed to be a highly capable, multimodal AI system that integrates text, images, audio, and video processing to deliver diverse functionalities. Gemini builds upon cutting-edge AI technologies to provide tools for natural language understanding, code generation, image generation, and even handling long and complex contexts.
"In FlutterFlow, you can use Gemini with the help of the Gemini API key. For that, you need to enable Gemini and fill in the API key with the Gemini API key."
With the help of Gemini, we can get chat responses and display them on the chat page.
Designing the Chat Interface
Create a Chat Page:
Navigate to the Pages section in FlutterFlow and create a new page named ChatPage.
Design the UI:
Use a ListView widget to display the chat messages.
Add a TextField for user input and a Send Button.
Add Dynamic Data (Firestore Integration):
In the ListView, bind it to the chatschema collection.
Display messages from Firestore by binding the massage field to a Text widget.
Add Image or Icon widgets to indicate the sender (user or chatbot).
Send Button Logic:
Attach an action to the Send Button that:
Saves the user input to the Firestore collection.
Triggers a function to send the message to the chatbot API (such as Gemini or any other service).
Chat Logic
Add Conditional Logic:
Use a Conditional Builder widget to check the sender field in the Firestore data:
If the sender is "user", display the user’s message.
If the sender is "chatbot", display the chatbot’s response.
Set the Visibility Condition on each message item to ensure that only relevant messages are displayed based on the sender.
2. State Management:
Use the Page State or App State variable to store the user’s message, then save it to the database. After that, send the message to the Gemini text prompt, and once the response is received from Gemini, save it to the Page State or App State variable. Then, save the response from that variable to the database.
Store the chatbot response in Firestore and display it in the ListView.
3. Conditional Builder for Message Visibility
Add a Conditional Builder:
Add a Conditional Builder to handle the visibility of each chat message based on the Sender field.
Example condition:
Visibility condition:
If sender == “user”, show a user message.
If sender == “chatbot”, show a chatbot message.
Conclusion:
A chatbot built with FlutterFlow and powered by Gemini offers a scalable and efficient solution for real-time AI interactions. With minimal coding, this approach leverages the strengths of FlutterFlow's no-code interface and Gemini's advanced conversational capabilities.