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README.md

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@@ -24,19 +24,20 @@ Introducing the NestJS library. Whether you're building a virtual assistant, or
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### AI Assistant library features
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- **Function calling**: The library provides a way to create functions, which allows you to extend the assistant's capabilities with custom logic.
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- **TTS (Text-to-Speech)**: The library provides a way to convert text to speech, which allows you to create voice-based interactions with the assistant.
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- **STT (Speech-to-Text)**: The library provides a way to convert speech to text, which allows you to create voice-based interactions with the assistant.
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- **File support**: The library provides a way to add files to the assistant, which allows you to extend the assistant's knowledge base with custom data.
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- **WebSockets**: The library provides a WebSocket server for real-time communication between the client and the assistant.
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- **REST API**: The library provides a REST API for communication with the assistant.
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- **Function calling**: create functions, so assistant can execute your custom logic!
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- **TTS (Text-to-Speech)**: convert text to speech, so you can hear your assistant!
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- **STT (Speech-to-Text)**: convert speech to text, so you can make conversation easier!
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- **File support**: add files to the assistant, so you can extend assistant's knowledge base with custom data!
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- **WebSockets**: establish WebSocket server for real-time communication between the client and the assistant!
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- **REST API**: Just use ready REST API for communication with the assistant!
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- **Vision with GPT-4o** - use the GPT-4o and make your assistant understand images and generate text based on them!
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#### Additional features in the repository
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The repository not only contains a library but also provides additional features. You don't have to build everything from scratch. You can just clone the repository and run it to take advantage of the features above and below:
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The repository contains a library but also provides additional features. You can just clone the repository and use it instantly to gain from all features:
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- **Embedded chatbot**: The library provides a way to embed the chatbot on various websites through JavaScript scripts.
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- **Chatbot client application**: The repository includes an example client application (SPA) with a chatbot.
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- **Embedded chatbot**: embed the chatbot on various websites through JavaScript scripts!
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- **Chatbot client application**: use ready client application (SPA) with a chatbot!
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## 🏆 Getting started
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nest new project-name
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```
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Now you have to install the packages. Go to the next step.
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### Step 1: Installation
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Make sure you are in the root directory of your project.
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Install the library and `openai` package using npm:
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```bash
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npm i @boldare/openai-assistant openai --save
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```
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The library is installed but we have to configure it. Go to the next step.
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### Step 2: Env variables
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Set up your environment variables, create environment variables in the `.env` file in the root directory of the project, and populate it with the necessary secrets. The assistant ID is optional and serves as a unique identifier for your assistant. When the environment variable is not set, the assistant will be created automatically. You can use the assistant ID to connect to an existing assistant, which can be found in the OpenAI platform after creating an assistant.
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Please note that the `.env` file should not be committed to the repository. *Add the `.env` file to the `.gitignore`* file to prevent it from being committed.
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This was the first step needed to run the library. The next step is to configure the assistant.
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### Step 3: Configuration
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The library provides a way to configure the assistant with the `AssistantModule.forRoot` method. The method takes a configuration object as an argument. Create a new configuration file like in a [sample configuration file (chat.config.ts)](apps%2Fapi%2Fsrc%2Fapp%2Fchat%2Fchat.config.ts) and fill it with the necessary configuration.

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