#ChatClient

[govindhtech]

Spring AI 1.0 and Google Cloud to Build Intelligent Apps

Spring AI 1.0

After extensive development, Spring AI 1.0 provides a robust and dependable AI engineering solution for your Java ecosystem. This is calculated to position Java and Spring at the forefront of the AI revolution, not just another library.

Spring Boot is used by so many enterprises that integrating AI into business logic and data has never been easier. Spring AI 1.0 lets developers effortlessly integrate cutting-edge AI models into their apps, bringing up new possibilities. Prepare to implement smart JVM app features!

Spring AI 1.0 is a powerful and comprehensive Java AI engineering solution. Its goal is to lead the AI revolution with Java and Spring. Spring AI 1.0 integrates AI into business logic and data without the integration issues many Spring Boot-using enterprises confront. It lets developers use cutting-edge AI models in their apps, expanding possibilities.

Spring AI supports multiple AI models:

Images produced by text-command image models.

Audio-to-text transcription models.

Vectors are formed by embedding models that transform random data into them for semantic similarity search.

Chat models can edit documents and write poetry, but they are tolerant and easily sidetracked.

The following elements in Spring AI 1.0 enable conversation models overcome their limits and improve:

Use system prompts to set and manage model behaviour.

Memory is added to the model to capture conversational context and memory.

Making tool calling feasible for AI models to access external features.

Including confidential information in the request with rapid filling.

Retrieval Augmented Generation (RAG) uses vector stores to retrieve and use business data to inform the model's solution.

Evaluation to ensure output accuracy employs a different model.

Linking AI apps to other services using the Model Context Protocol (MCP), which works with all programming languages, to develop agentic workflows for complex tasks.

Spring AI integrates seamlessly with Spring Boot and follows Spring developers' convention-over-configuration setup by providing well-known abstractions and startup dependencies via Spring Initialisation. This lets Spring Boot app developers quickly integrate AI models utilising their logic and data.

When using Gemini models in Vertex AI, Google Cloud connectivity is required. A Google Cloud environment must be created by establishing or selecting a project, enabling the Vertex AI API in the console, billing, and the gcloud CLI.

Use gcloud init, config set project, and auth application-default login to configure local development authentication.

The Spring Initialiser must generate GraalVM Native Support, Spring Web, Spring Boot Actuator, Spring Data JDBC, Vertex AI Gemini, Vertex AI Embeddings, PGvector Vector Database, MCP Client, and Docker Compose Support to build a Spring AI and Google Cloud application. The site recommends using the latest Java version, especially GraalVM, which compiles code into native images instead of JRE-based apps to save RAM and speed up startup. Set application properties during configuration.characteristics for application name, database connection options, Vertex AI project ID and location for chat and embedding models (gemini-2.5-pro-preview-05-06), actuator endpoints, Docker Compose administration, and PGvector schema initialisation.

PostgreSQL database with a vector type plugin that stores data with Spring AI's VectorStore abstraction? Database schema and data can be initialised on startup using schema.sql and data.sql files, and Spring Boot's Docker Compose can start the database container automatically. Spring Data JDBC creates database interaction and data access entities.

The ChatClient manages chat model interactions and is a one-stop shop. ChatClients need autoconfigured ChatModels like Google's Gemini. Developers can create several ChatClients with different parameters and conditions using ChatClient.Builder. ChatClients can be used with PromptChatMemoryAdvisor or QuestionAnswerAdvisor to handle chat memory or VectorStore data for RAG.

Spring AI simplifies tool calls by annotating methods and arguments with @Tool and @ToolParam. The model evaluates tool relevance using annotation descriptions and structure. New default tools can be added to ChatClient.

Spring AI also integrates with the Model Context Protocol (MCP), which separates tools into services and makes them available to LLMs in any language.

For Google Cloud production deployments, Spring AI apps work with pgVector-supporting databases like Google Cloud SQL or AlloyDB. AlloyDB is built for AI applications with its high performance, availability (99.99% SLA including maintenance), and scalability.

FAQ

How is spring AI?

The Spring AI application framework simplifies Spring ecosystem AI application development. It allows Java developers to easily integrate AI models and APIs without retraining, inspired by LangChain and LlamaIndex.

Essentials and Ideas:

AI integration:

Spring AI integrates AI models with enterprise data and APIs.

Abstraction and Portability:

Its portable APIs work across vector database and AI model manufacturers.

Spring Boot compatibility:

It integrates with Spring Boot and provides observability tools, starters, and autoconfiguration.

Support the Model:

It supports text-to-image, embedding, chat completion, and other AI models.

Quick Templates:

Template engines let Spring AI manage and produce AI model prompts.

Vector databases:

It uses popular vector database providers to store and retrieve embeddings.

Tools and Function Calling:

Models can call real-time data access functions and tools.

Observability:

It tracks AI activity with observability solutions.

Assessing and Preventing Hallucinations:

Spring AI helps evaluate content and reduce hallucinations.

[draegerit]

ChatGPT - Chat Client mit Python / Flask erstellen

In diesem Beitrag möchte ich dir gerne zeigen, wie du einen kleinen Chat Client für ChatGPT mit Python / Flask erstellst. Dabei lassen wir uns das Programm selber von ChatGPT generieren.

Die künstliche Intelligenz ChatGPT habe ich dir bereits in diversen Beiträgen auf meinem Blog vorgestellt. Ein großer Vorteil ist, dass diese sich von vielen antrainierten Modellen bedient und somit für die Codegenerierung bestens geeignet ist. Dabei können wir mit dem System schreiben, wie mit einem erfahrenen Entwickler. Stellen wir uns also vor, wir schreiben mit einem Softwareentwickler, welcher viele Jahre Erfahrung hat. Als Entwicklungsumgebung nutze ich PyCharm welches in der Community Edition kostenfrei ist. Dieses Tool kannst du unter https://www.jetbrains.com/pycharm für Windows, macOS und Linux herunterladen. Ich gehe jedoch davon aus, dass du bereits eine Entwicklungsumgebung installiert und einsatzbereit hast.

Leeres Projekt in PyCharm erstellen

Erstellen wir zunächst ein leeres Projekt in PyCharm. Von ChatGPT lassen wir uns lediglich die Dateien bzw. den Code erstellen. Über den Wizard erstellst du in wenigen Schritten ein leeres Projekt. Zunächst wählen wir die Schaltfläche "New Project" (1), um im nächsten Fenster den Projektnamen / Ordnernamen (2) einzugeben. Wenn du mehrere Versionen von Python installiert hast, musst du unter Base Interpreter (3) den korrekten Python Interpreter wählen. Sollten Fehler auftreten oder andere Hinweise zur Konfiguration existieren, dann wird dieses im Bereich der Nummer 4 angezeigt. Wenn alles okay ist, dann wird die Schaltfläche "Create" (5) freigegeben und nach einem Klick auf diesen wird das Projekt erstellt.

Das leere Projekt enthält bereits die Datei main.py in welche wir den Code für den Chat Client einfügen werden.

Hinweise zum Programmieren mit ChatGPT

Wenn du dir von ChatGPT Quellcode erzeugen lässt, dann empfiehlt es sich, dass du diesen nicht von selbst änderst, sondern die Änderungen dir von ChatGPT selber erzeugen lässt. Das hat den Hintergrund, dass wenn du später im selben Chat dir ein neues Feature hinzufügen lassen möchtest, dann kennt ChatGPT sozusagen nichts von deinen lokalen Änderungen.

Einen Chat Client von ChatGPT erstellen lassen

Loggen wir uns also nun unter https://chat.openai.com/ ein und stellen die nachfolgende Anfrage an das System. Write me a ChatClient to communicate with ChatGPT from a website that build with flask. Als Antwort erhalten wir eine Ausgabe mit den beiden Quellcodedateien app.py sowie index.html für die GUI. Des Weiteren eine sehr gute Erläuterung zum Code. ChatGPT_generate_ChatClient_Python_FlaskHerunterladen Inhalt der Datei app.py from flask import Flask, render_template from flask_socketio import SocketIO, emit app = Flask(__name__) app.config = 'secret!' socketio = SocketIO(app) @app.route('/') def index(): return render_template('index.html') @socketio.on('chat message') def handle_message(message): # Use ChatGPT to generate a response response = generate_response(message) # Send the response back to the client emit('bot response', response) def generate_response(message): # Use ChatGPT to generate a response based on the input message # ... return response if __name__ == '__main__': socketio.run(app) Inhalt der Webseite index.html ChatClient Send Funktion "generate_response" Die Funktion "generate_response" ist in der ersten Anfrage leer. Hier musste ich erneut mit einer weiteren Anfrage mit dem Code ausgeben lassen. import openai import os openai.api_key = os.environ def generate_response(message): prompt = f"User: {message}nBot: " response = openai.Completion.create( engine="text-davinci-002", prompt=prompt, max_tokens=1024, n=1, stop=None, temperature=0.7, ).choices.text.strip() return response In dem Code wird der API_KEY aus den Umgebungsvariablen gelesen. Diese musst du je nach Betriebssystem setzen. In meinem Fall verwende ich ein Windows 10 und habe diese wie folgt gesetzt: - Startmenü (1) > Eingabe von "umgebungs" (2), - Auswahl von "Systemumgebungsvariablen bearbeiten (3), - Schaltfläche "Umgebungsvariablen" (4) betätigen, - Auswahl des Eintrages "OPENAI_API_KEY" (5) oder Schaltfläche "Neu.." für das Erzeugen, - Schaltfläche "Bearbeiten..." (6) betätigen, - Eingeben des API_KEYs (7) und bestätigen mit Schaltfläche "OK" (8), - Fenster über die Schaltflächen "OK" (9) & (10) verlassen

Alternativ kannst du in das Feld "openai.api_key" auch direkt mit deinem API_KEY befüllen, jedoch bist du dann nicht mehr so flexibel. openai.api_key = os.environ Installieren der Abhängigkeiten Damit wir das Programm ausführen können, müssen wir die Abhängigkeiten installieren. pip install flask pip install flask-socketio

Ausführen des Projektes

Das Projekt kannst du nun auf der Konsole aus PyCharm starten. Dazu öffnen wir das lokale Terminalfenster (1) und geben "python app.py" (2) ein und bestätigen dieses mit Enter.

Es erfolgt dann die Ausgabe vom Server auf welcher IP-Adresse & Port dieser gestartet ist, über die können wir jetzt im Browser die Seite erreichen. WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5000 Press CTRL+C to quit Auf der Seite ist ein Eingabefeld und eine Schaltfläche für das Absenden einer Anfrage an ChatGPT. Die Antwort wird direkt auf der Seite angezeigt.

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[miraculous-imvu]

Welcome to our blog! 

We are 2 guys that enjoy spending time on a 3d Chatclient called IMVU. We roleplay as LadyBug/Marinette and CatNoir/Adrien on there and make a LOT of pictures of our avatars. Thinking maybe more people might like the pictures we make we decided to create this blog. Note that we try our best to make the characters look as accurate as possible but sometimes we dont have the right material to make it work. Also we love to add our own twist to the characters by coming up with new looks for them. You can expect MariChat, LadyNoir and Adrienette on here. Request for pictures are always welcome and if we can make it work we will do so. Hope you will all enjoy our blog~

Now let us introduce ourselves~

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Name: Daniel Age: 30 Gender: Male Country: The Netherlands Character: Cat Noir/ Adrien Agreste

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Name: Alex Age: 25 Gender: Male Country: Canada Character: LadyBug/ Marinette Dupain-Cheng

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[lighting-philips]

How The New Range Of Hue Dimmer Switch Has Revolutionized Lighting Décor

First, it was the mood lighting, then came the Wi-Fi-enabled lighting. The new age of lighting has just started with the Philips hue dimmer switch. Looks like there are many more surprises in store for the modern lifestyle.

The Hue Range of light bulbs and switches is connected by Wi-Fi and operational through an application on your Smartphone.

The user can access the lights remotely and control the illumination levels at all times.

Features

The Hue dimmer switch is a breakthrough in lighting accessories. It is a one-of-a-kind light accessory.

This switch works     like a remote control that can be next to where you are.

You can easily     control the lighting from your position and switch it on or off.

Regulating the     brightness of the lighting is the next best thing with the dimmer     switches.

It comes with several     levels of dimming options for the lights so that you can opt for one     according to your choice.

Installing the switch     is easy. It can be mounted on the wall or kept for use like a remote     control.

There is no use of     wires connected to a board on the wall to connect switches with lights.

One remote switch can     control up to 50 lights. It has made life less complicated.

The latest range of dimmer switches spoils one for choice. They look smart and sleek, easy to manage without wires, and easy to organize your home lighting. 

The Hue App

A hue dimmer switch is accessible through the Hue app on your phone. The app is available for free download on your Android or iOS app store.

Installing the app and syncing it with your lighting system is an easy step process. You can configure your phone with the app in a few steps that will be displayed on the app interface.

Follow the steps and you will be ready to use your dimmer switch. 

Easy And Quick Installation

Normally we are used to several hours with an electrician fixing up switchboards and wires. With the Philips Hue dimmer switch it is now easy. It is easily fixed on the wall with adhesive tape or simple screws. You can also have it with you and use it like a remote switch wherever you are seated. 

Battery Powered

The Hue dimmer switch is a wireless battery-operated switch. no electrical connection is required. The package comes with the first set of the battery. 

The new range of battery-operated switches considerably improves the wall décor. The complicated wiring network is now redundant without the wired connections on the board and the wall.

Undoubtedly, it improves the décor standards of a homely premise where the lighting suits your mood and requirements. 

You can log on to https://www.philips-hue.com/ or call us at 000 800 050 7777 or chat with us at https://home-e31.niceincontact.com/incontact/chatclient/index.html

[jarviscodinghub]

Project 5: Chat Program solved

Project 5: Chat Program solved

Write a multi-threaded chat client program. Your chat client should get the user name and port number from the command line. The user name should default to Anonymous and the port number should default to 4688. For example, this command line: java ChatClient Frodo 4600 would use Frodo for the user name and connect to port 4600 on the server. The user should be able to specify a user name without…

[digital-dynasty]

Bytecode im Browser: Mit WebAssembly und Rust zur Web-Anwendung

Am Beispiel eines Chatsystems demonstrieren die Autoren die Programmierung eines browserbasierten Chatclients und -servers mit Rust und Wasm. Read more www.heise.de/hintergrund/…... www.digital-dynasty.net/de/teamblogs/…

http://www.digital-dynasty.net/de/teamblogs/bytecode-im-browser-mit-webassembly-und-rust-zur-web-anwendung

[programmingsolver]

Assignment #1 Solution

Refresh programming skills

The Program:

Design and implement a simple chat system that works for one pair of users, i.e., create two programs: a chat server and a chat client. The final version of your programs must accomplish the following tasks:

chatserve starts on host A.

chatserve on host A waits on a port (specified by command-line) for a client request.

chatclient starts on host B,…

[brandmania1]

Clients From Hell! How To Make 6-Figures Avoiding Them

Land Clients On Facebook Chat: http://www.pauljames.com/chatclients Clients From Hell! How To Make 6-Figures Avoiding Them How to land social media marketing agency clients, website design clients, logo design clients, seo clients, facebook ad clients and more! I talk about the things I do to avoid clients from hell and how to make 6-figures just by […]

L'articolo Clients From Hell! How To Make 6-Figures Avoiding Them proviene da B|M Inspiration for Success.

from B|M Inspiration for Success https://www.brandmania.it/make-money/clients-from-hell-how-to-make-6-figures-avoiding-them/

[techvandaag]

Slack-concurrent Microsoft Teams krijgt uitgebreide gratis versie

Microsoft maakt van Slack-concurrent Teams een gratis versie. De zakelijke chatclient is al beschikbaar sinds eind 2016 en vandaag gebruiken meer dan 200.000 bedrijven de dienst. Om aan populariteit te winnen, komt er een gratis versie met heel wat meer opties dan de gratis versie van Slack Microsoft Teams wordt vandaag door 200.000 bedrijven gebruikt, […] http://dlvr.it/QbPqJX

[aboutict]

Google onthult sms-uitbreiding Chat en pauzeert ontwikkeling Allo

Google heeft Chat onthuld, een set functies die van de standaard-sms-app op Android een chatclient maakt. Met Chat werkt Android Berichten als een rcs-client. Android Berichten krijgt geen end-to-end encryptie. http://dlvr.it/QQ8WQ2

[askanything-online-blog]

Twilio Chat typing() is not working

Twilio Chat typing() is not working

i’m successfully integrate the twilio chat api on javascript, however i got problem on .typing() function, it seems the typing function is not triggering the

‘typingStarted’ and ‘typingEnded’, can i have some advice?

here is my code

var chatChannel; var chatClient; var username; $.post("/tokens", function(data) { username = data.username; chatClient = new Twilio.Chat.Client(data.token);…

[aboutict]

Google: desktopversie Allo komt over enkele weken

Google heeft laten weten dat een desktopversie van chatsoftware Allo binnen enkele weken beschikbaar moet komen. De internetgigant had al beloofd met een desktopversie te komen van zijn nieuwe chatclient. http://dlvr.it/PTJP5t