💻 programming

voice-chat-pdf

Voice chat with documents using OpenAI real-time API

#machine learning
#OpenAI
#Document processing
#Voice interaction
#LlamaIndex
voice-chat-pdf

Product Details

voice-chat-pdf is an example based on the LlamaIndex project and built using Next.js. It allows users to interact with PDF documents through voice through a simple RAG system. This project requires an OpenAI API key to access the real-time API and generate embedding vectors of documents within the project for voice interaction. It demonstrates how advanced machine learning techniques can be applied to improve the efficiency and convenience of document interaction.

Main Features

1
Voice interaction using OpenAI real-time API
2
Supports manual mode and Voice Activity Detection (VAD) mode
3
You can freely interrupt the model's response
4
Supports interaction with your own documents
5
The project is built on LlamaIndexTS and provides Typescript features
6
OpenAI API key needs to be set in the project
7
Start the development server via command line tools

How to Use

1
First, install the project dependencies.
2
Secondly, the embedding vector of the document located in the ./data directory is generated.
3
Then, run the development server.
4
Open the browser and visit http://localhost:3000 to view the results.
5
On startup, enter your API key.
6
To start a conversation, you need to connect a microphone.
7
Choose manual or VAD session mode and switch when needed.
8
You can interrupt the model's response at any time during the session.

Target Users

The target audience is primarily developers and technology enthusiasts who are interested in using the latest artificial intelligence technology to enhance document processing and interaction. This product is suitable for those who want to integrate voice interaction capabilities in their applications, as well as researchers interested in natural language processing and machine learning.

Examples

Developers can use it to create a chatbot that can voice interact with user documents.

Technology enthusiasts can use this program to learn how to integrate speech recognition and natural language processing technology into their projects.

Researchers can use this project to explore potential applications of real-time voice interaction in document analysis and processing.

Quick Access

Visit Website →

Categories

💻 programming
› AI chatbot
› AI voice assistant

Related Recommendations

Discover more similar quality AI tools

rag-chatbot

rag-chatbot

rag-chatbot is a chatbot model based on artificial intelligence technology that allows users to interact with multiple PDF files through natural language. The model uses the latest machine learning technologies, such as Huggingface and Ollama, to understand PDF content and generate answers. Its importance lies in its ability to process large amounts of document information and provide users with fast and accurate question and answer services. Product background information indicates that this is an open source project aimed at improving the efficiency of document processing through technological innovation. The project is currently free and is mainly aimed at developers and technology enthusiasts.

llm rag
💻 programming
gradio-bot

gradio-bot

gradio-bot is a tool that turns Hugging Face Space or Gradio apps into Discord bots. It allows developers to quickly deploy existing machine learning models or applications to the Discord platform through simple command line operations to achieve automated interaction. This not only improves the accessibility of the application, but also provides developers with a new channel for direct interaction with users.

machine learning robot
💻 programming
curiosity

curiosity

curiosity is a chatbot project based on the ReAct framework, aiming to explore and build a Perplexity-like user interaction experience through LangGraph and FastHTML technology stack. The core of the project is a simple ReAct agent that uses Tavily search to enhance text generation. Supports three different LLMs (Large Language Models), including OpenAI's gpt-4o-mini, Groq's llama3-groq-8b-8192-tool-use-preview, and Ollama's llama3.1. The project builds the front-end via FastHTML, which overall provides a fast user experience, although there may be some challenges during debugging.

chatbot LLMs
💻 programming
MemoryScope

MemoryScope

MemoryScope is a framework that provides long-term memory capabilities for large language model (LLM) chatbots. It enables chatbots to store and retrieve memory fragments through memory databases and work libraries, thereby achieving personalized user interaction experience. Through operations such as memory retrieval and memory integration, this product enables the robot to understand and remember the user's habits and preferences, providing users with a more personalized and coherent conversation experience. MemoryScope supports multiple model APIs, including openai and dashscope, and can be used in conjunction with existing agent frameworks such as AutoGen and AgentScope, providing rich customization and scalability.

chatbot LLM
💻 programming
kotaemon

kotaemon

kotaemon is an open source, RAG (Retrieval-Augmented Generation) model-based tool designed to interact with user documents through a chat interface. It supports multiple language model API providers and local language models, and provides a clean and customizable user interface suitable for end users to perform document Q&A and developers to build their own RAG Q&A process.

Open source chatbot
💻 programming
ChatCat

ChatCat

ChatCat is a web application designed to enable users to seamlessly create, deploy and manage AI-powered chatbots. These chatbots are trained to extract content from user-provided URLs and can provide real-time, context-aware responses. The application leverages the Together API to provide advanced AI capabilities, ensuring a high-quality interactive experience.

AI chatbot
💻 programming
LLaMA Assistant for Mac

LLaMA Assistant for Mac

LLaMA Assistant for Mac is a desktop client developed based on the llama-cpp-python library and is designed to assist users with predefined requirements. It uses a lot of code from other projects, but replaces the ollama parts with llama-cpp-python to achieve a solution more consistent with Python programming style.

automation assistant
💻 programming
Meta-Llama-3.1-405B-Instruct

Meta-Llama-3.1-405B-Instruct

Meta Llama 3.1 is a series of large-scale pre-trained and instruction-tuned generative models in multiple languages, including 8B, 70B and 405B sized versions. These models are optimized for multilingual conversation use cases and outperform many open and closed source chat models on common industry benchmarks. The model uses an optimized transformer architecture and is tuned through supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to match human preferences for usefulness and safety.

Multi-language support Large language model
💻 programming
Meta-Llama-3.1-8B-Instruct

Meta-Llama-3.1-8B-Instruct

Meta Llama 3.1 is a series of pre-trained and instruction-tuned multilingual large language models (LLMs) supporting 8 languages, optimized for conversational use cases, and improved safety and usefulness through supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF).

Multi-language support language model
💻 programming
Typebot.io

Typebot.io

Typebot is an open source chatbot builder that allows users to visually create advanced chatbots, embed them into any web/mobile application, and collect results in real time. It provides more than 34 building blocks, such as text, pictures, videos, audio, conditional branches, logic scripts, etc., and supports multiple integration methods, such as Webhook, OpenAI, Google Sheets, etc. Typebot supports custom themes to match brand identity and provides in-depth analysis capabilities to help users gain insight into the chatbot's performance.

chatbot Self-hosted
💻 programming
Enchanted

Enchanted

Enchanted is an open source, Ollama-compatible app for macOS/iOS/visionOS that allows users to talk to private self-hosted language models such as Llama 2, Mistral, Vicuna, and more. It's basically a ChatGPT application interface connected to a private model. Enchanted's goal is to provide a product that allows for unfiltered, secure, private and multi-modal experiences across all devices in the iOS ecosystem (macOS, iOS, Watch, Vision Pro).

language model multimodal
💻 programming
TalkWithGemini

TalkWithGemini

TalkWithGemini is a cross-platform application that supports one-click free deployment. Users can interact with Gemini models through this application. It supports multi-modal interaction methods such as image recognition and voice dialogue to improve work efficiency.

multimodal Cross-platform
💻 programming
GLM-4V-9B

GLM-4V-9B

GLM-4V-9B is a new generation of pre-training model launched by Zhipu AI. It supports Chinese and English bilingual multi-round dialogue at 1120*1120 high resolution, as well as visual understanding capabilities. In the multi-modal evaluation, GLM-4V-9B demonstrated excellent performance beyond GPT-4-turbo-2024-04-09, Gemini 1.0 Pro, Qwen-VL-Max and Claude 3 Opus.

multimodal Pre-trained model
💻 programming
GPT Computer Assistant

GPT Computer Assistant

gpt-computer-assistant is an application designed for Windows, macOS and Ubuntu operating systems to provide an alternative ChatGPT application. It allows users to easily install through Python libraries, and plans to provide native installation scripts (.exe). The product is powered by Upsonic Tiger, a platform that provides a feature center for large language model (LLM) agents. Key benefits of the product include cross-platform compatibility, ease of installation and use, and future support for native models.

openai chatgpt
💻 programming
GLM-4-9B-Chat

GLM-4-9B-Chat

GLM-4-9B-Chat is an open source version of the new generation pre-training model GLM-4 series launched by Zhipu AI. It has advanced functions such as multi-round dialogue, web browsing, code execution, custom tool invocation, and long text reasoning. It supports 26 languages ​​including Japanese, Korean, and German, and has launched a model that supports 1M context length.

Multi-language support Pre-trained model
💻 programming
CogVLM2

CogVLM2

CogVLM2 is a second-generation multi-modal pre-trained dialogue model developed by the Tsinghua University team. It has achieved significant improvements in multiple benchmark tests and supports 8K content length and 1344*1344 image resolution. CogVLM2 series models provide open source versions that support Chinese and English, with performance comparable to some non-open source models.

multimodal Pre-trained model
💻 programming