#chatbot

This versatile chatbot supports multiple AI models and messaging platforms, offering features such as image sending, keyword-triggered responses, and content moderation. It's compatible with platforms like Mirai, go-cqhttp, Telegram, Discord, and WeChat, and provides API services as an HTTP server. With notable support for AI models like ChatGPT, Bing Chat, and ChatGLM-6B, it's designed for diverse user needs including text RPGs and life assistance.

Discover a flexible platform for building customizable chatbots utilizing Cohere's advanced language models. Improve interaction with tailored personas, efficient chat history management, and engage through Streamlit demos, suitable for support, sales, and education.

Mirai Console's OpenAI Plugin provides powerful interaction capabilities through chat, Q&A, and image generation, using models like GPT-3.5-turbo and text-davinci-003. Users configure settings with API keys and proxies, and customize via yml files. Supports prompts, economy system integration, and permission checks for tailored user experiences, boosting engagement in Mirai.

The project offers a Python framework for creating and interacting with a GPT-3 powered chatbot, requiring OpenAI key usage. It provides a foundational codebase that supports customization and diverse application development. Emphasizing efficient token management, the project suggests using the Davinci engine for superior results. It is designed as a flexible tool for advancing AI technological explorations, characterized by straightforward setup and user-oriented design guidelines.

The Python Chatbot AI enables straightforward creation of functional chatbots with minimal coding. Its key features include bot AI integration, chat handling, REST API integration, and Python function execution. The tool supports capabilities such as conversational memory, conditional logic, and topic-based dialogue management. Demonstrated in samples like Facebook Messenger and Microsoft Bots, this open-source project offers flexibility across various platforms, providing developers a robust solution for enhancing user interaction with automation.

The project aims to provide reliable access to the OpenAI API by using Cloudflare Workers and Pages, efficiently mitigating geographical limitations. It provides comprehensive guides for deploying via Docker and setting up proxy APIs, while noting limited SSE support. Instructions are available for replacing api.openai.com with custom domains using Cloudflare, supporting seamless integration and enhancing stability. This is suitable for developers looking for scalable deployment solutions of OpenAI API across various environments.

Canopy is an open-source framework built on the Pinecone vector database that streamlines the development of Retrieval Augmented Generation (RAG) applications. It offers efficient text data handling through chunking, embedding, and optimized query processes while managing chat history effectively. Its configurable server setup ensures seamless integration with existing or custom chat applications. Additionally, the CLI tool allows interactive evaluation of RAG workflows, enhancing users' exploration of context retrieval and generation.

Discover how to deploy a QA bot with OpenAI API, Pinecone database, and Streamlit. This guide provides a step-by-step process to establish a basic knowledge-retrieval system. Learn to prepare text for embedding models and upload them to Pinecone DB. Explore integrating a chat app in Streamlit to query movie data from Pinecone's embeddings, all while managing environment variables and API keys effectively.

Learn how a refactored chatbot uses the Llama2-7B model by Meta, supported by Andreessen Horowitz and operated on Replicate, offering a lightweight deployment option on Streamlit Community Cloud. Perfect for tech enthusiasts, discover the steps to obtain a Replicate API token and explore larger models such as Llama2-13B and Llama2-70B. Access additional resources and technical information through the Llama 2 website, GitHub, and various articles.

Designed with OpenAI's API, this AI-powered chatbot offers long-term memory and advanced logic for personalized and complex interactions. Customizable prompts allow versatile applications from language teaching to specific enterprise uses. Secure user experience is maintained with KYC authentication via Google Login.

The platform delivers an AI-driven chatbot tailored for video and image interaction, with updates like instruction tuning enhancing performance across benchmarks such as VideoChat2_phi3 and VideoChat2_HD. It supports long video understanding, diverse tasks, and integrates with systems such as ChatGPT, StableLM, and MOSS, highlighting its continuous development in AI and video comprehension. Contribute to this third-party project and explore its extensive applications without any promotional exaggeration.

Discover a versatile Chinese chatbot allowing custom dataset training, integrating GPT models for improved interaction. Features Seq2Seq and GPT branches with future updates for MindSpore and multimodal dialogues. Enhanced distributed training and RLHF align with cutting-edge AI advancements.

LangChain UI is an open-source, no-code tool that facilitates the creation and hosting of custom chatbots. Leveraging LangChain, it offers extensive customization using external data sources, plugins, and prompts. Features include API endpoints, flexible database, and authentication support, along with embedding options and thematic customizations. Utilizing Next.js, Chakra UI, Prisma, and NextAuth, LangChain UI aims to enhance the development of smart applications. Interaction with chatbots is facilitated by the LangChain UI API, with future plans to transition to Javascript for operations.

Dialogbot provides dialogue model technology integrating search-based, task-based, and generative models for effective dialogue responses. It supports applications such as query answering, task guidance, and interactive chat, enhancing AI communications. Features include local and web search dialogues, network-driven task dialogues, and generative chat using GPT2. The system's flexibility and ease of integration make it suitable for developers implementing advanced dialogue models in AI projects.

Discover Chatbot with advanced LLM inference via WebSocket and HTTP APIs. Utilize the platform on your server, supporting models like Llama 2 and StableBeluga2. Benefit from the WebSocket API's speed or opt for the flexibility of the HTTP API. Tailored for research, features like token streaming and sampling control are provided, offering a powerful, customizable experience. Explore easy integration for a comprehensive chatbot solution.

The project provides Python scripts to create a multi-document reader and chatbot using LangChain and OpenAI, compatible with .pdf, .dox, and .txt formats. It maintains chat history and uses embeddings and vector stores for relevant data transmission to LLM prompts, enhancing interactions. The setup process involves repository cloning, virtual environment configuration, and necessary package installation. While the framework is basic, it's expandable through further exploration such as prompt template optimization and advanced LLM integration for enhanced response quality.

This Golang-based open-source chatbot leverages machine learning for customizable and privacy-focused solutions, presenting an alternative to services like DialogFlow. It allows developers to train new models easily and integrate seamlessly with mobile devices through its Progressive Web Application format. With support for multiple languages, this chatbot is designed for flexible and user-friendly deployment in various projects.

Learn to transform website content into an AI-driven Q&A chatbot via Langchain and the OpenAI API. This repository provides scripts for building semantic embeddings, direct Q&A, and chat functions. Langchain processes the sitemap to generate semantic vectors within a Faiss knowledge base. Zendesk integration is included for improved response accuracy. This tool is designed for boosting user engagement through precise automated information retrieval.

A bot application on Tencent QQ combining chatbot functionality with AI art creation, primarily for Chinese users. It facilitates user interaction through text prompts, with potential uses in voice services, group management, and image analysis. Utilizing stable-diffusion-webui and self-hosted LLM, it enables easy switching between GPT-3 and local models. Adaptable for English speakers with documented variables and configuration. Scenarios include OpenAI API access, image drawing commands, and group management via hashtag instructions.

Errbot is an open-source chatbot framework designed for flexible and interactive scripting in various chat environments. It natively supports IRC, Telegram, and XMPP, with additional compatibility for platforms like Slack and Discord via plugins. Administered through chatops, it simplifies plugin management, enhances security, and allows system configuration directly from chats. Written in Python, Errbot is known for its extensibility, pre-configured storage options, and robust webhook integration, catering to developers seeking customizable and efficient chatbot solutions.

Gain insights into using Rasa Core and Rasa NLU to build sophisticated chatbots, with a specific focus on integrating Chinese language support. The project details version management and introduces a stable 1.10.18 pipeline featuring BERT components for enhanced language processing. Learn how to install, train, and test models through command line and HTTP server, facilitating effortless chatbot deployment. Engage with the Rasa community to expand knowledge and networking opportunities within social groups.