Best of Bots — September 2024

  1. 1
    Article
    Avatar of freecodecampfreeCodeCamp·2y

    How to Start Building Projects with LLMs

    Becoming an LLM engineer is a promising career path. The best way to learn is by building projects. This post suggests starting with practical projects like developing a YouTube video summarizer that uses Python packages such as langchain, pytube, and youtube-transcript-api. The core bot functionality involves receiving a YouTube URL, retrieving the transcript, and using LLM to summarize the content, which is then returned to the user. For deployment, serve the summarization functionality as a Flask API and use Twilio to connect to WhatsApp for testing. The post also introduces a project-based course for LLM applications.

  2. 2
    Article
    Avatar of medium_jsMedium·2y

    Start Building These Projects to Become an LLM Engineer

    To become an LLM engineer, start by building practical projects that showcase skills in API usage and real-world applications, like chatbots for WhatsApp, Discord, or Telegram. Initial projects could include summarizing YouTube videos or handling various user queries via chatbots. The post also introduces a project-based course to help you build LLM applications and serve them as WhatsApp chatbots.

  3. 3
    Article
    Avatar of saastipsSaaS Tips·2y

    If you own a website you don't want to miss this

    Integrate a free AI chatbot on your website, complete with unlimited training data and AI messages. Visit voxal.ai for more details.

  4. 4
    Article
    Avatar of devblogsDevBlogs·2y

    Build a chatbot on your own data in 1 hour with Azure SQL, Langchain and Chainlit

    Creating a custom chatbot using your own data has become straightforward with the help of LangChain, Chainlit, and Azure SQL. By leveraging Azure SQL's new vector support, you can store and query data embeddings. LangChain assists in defining prompts for the chatbot and retrieving relevant session data from the database. Finally, the integration with Chainlit ensures seamless Conversational AI implementation. This process takes less than an hour and can be further expanded based on your requirements.

  5. 5
    Article
    Avatar of adamjAdam Johnson·2y

    Django: build a Microsoft Teams bot

    Building a Microsoft Teams bot in Django is challenging due to issues such as convoluted documentation, a fragmented Bot Framework Python package, and limited helpful sample apps. Despite these obstacles, the bot can be configured and tested, with alternatives like the Teams Developer Portal simplifying some aspects. Key steps include handling incoming webhook messages, managing channel names, and navigating Adaptive Cards for message formatting. A single-file Django example and related tests are provided to get started.

  6. 6
    Article
    Avatar of gopenaiGoPenAI·2y

    Mastering LLMs with LangChain: Part 1 (what is LangChain?)

    LangChain is a flexible and easy-to-use framework designed to streamline the development of applications using large language models (LLMs). It features reusable building blocks like prompts, chains, and agents to simplify creating a variety of NLP applications, including chatbots, text summarizers, and code-generation tools. The series will cover setting up LangChain, interacting with LLMs, and building practical applications.

  7. 7
    Article
    Avatar of langchainLangChain·2y

    Build stateful conversational AI agents with LangGraph and assistant-ui

    assistant-ui is an embeddable AI chat frontend for React applications that integrates with LangGraph Cloud. This collaboration allows developers to deploy LangGraph agents as standalone web apps or integrate them into existing applications. assistant-ui offers streaming responses, rich content display, generative UI, human-in-the-loop approval interfaces, multimodal input support, and stateful interactions for multi-turn conversations. The provided setup guide and example with a Stockbroker Agent illustrate the capabilities of this integration, facilitating the creation of interactive and stateful AI assistants.

  8. 8
    Article
    Avatar of communityCommunity Picks·2y

    Kids-friendly project: Building your Chatbot Web Application using LLM

    Create a chatbot web application tailored to your needs using LLM chatbots like ChatGPT. You'll set up a coding environment using tools like GitHub, VSCode, and Gitpod, and learn to create a React app from scratch. The guide walks you through setting up prerequisites, building the UI, integrating chatbot logic, and connecting to OpenAI. It also covers testing, debugging, and adding enhancements to make the chatbot more interactive and engaging.

  9. 9
    Article
    Avatar of gopenaiGoPenAI·2y

    Building a Database-Driven Chatbot with LangChain and OpenAI: A Practical Approach (Part 4, Optimizing)

    The fourth part of the series on building a SQL-based chatbot using LangChain and OpenAI focuses on optimization techniques. It introduces the use of SemanticSimilarityExampleSelector to dynamically choose relevant examples based on user input, thus reducing token usage and improving efficiency. The post provides a detailed guide on implementing dynamic selection of SQL examples and table details, enhancing the chatbot's contextual relevance and performance.

  10. 10
    Article
    Avatar of taiTowards AI·2y

    Building a Smart Chatbot with OpenAI and Pinecone: A Simple Guide

    Learn how to build a simple Retrieval-Augmented Generation (RAG) chatbot using Python, incorporating Pinecone for the vector database and OpenAI for the language model. This guide addresses the issue of chatbot hallucinations by enhancing the language model with external knowledge sources. Step-by-step instructions include setting up API keys, installing necessary packages, creating a Pinecone index, chunking and embedding documents, and querying Pinecone for accurate responses.

See all Bots archives