#Streamlit

Streamlit provides an efficient platform for turning Python scripts into interactive web applications. Suitable for dashboards, reports, or chat applications, it enables quick prototyping and immediate feedback. With straightforward Pythonic code and real-time editing, Streamlit is supported by an open-source community. The Community Cloud platform facilitates easy deployment and management of applications. Simple installation and rich resources, including Streamlit Components and an inspiring gallery, support extended functionality. Streamlit is free under the Apache 2.0 license, offering a budget-friendly option for data applications.

RAGs is a Streamlit app designed for configuring RAG pipelines through natural language instructions. The application draws inspiration from OpenAI’s GPTs and facilitates task description, RAG parameter configuration, and RAG agent interaction. Users can adjust parameters like system prompts, summarization settings, and retrieval methods, providing a tailored querying solution. It is compatible with various LLMs and embedding models for versatile application. The default setup employs OpenAI, but it allows exploration of alternative models for customizing and querying RAG agents, ensuring efficient data interactions supported by community involvement.

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.

PDF Analyzer App enables detailed analysis of PDFs or TXT documents by supporting question-answer interactions based on the provided content. It employs advanced retrieval techniques like similarity search and support vector machines to deliver precise answers, making it a useful tool for professionals requiring swift document insights. Developed by Mehmet Balioglu, this application maintains a focus on easy user engagement and efficient data handling.

CSV-AI uses LangChain, OpenAI, and Streamlit to enhance CSV file processing by enabling seamless interaction, summarization, and analysis. Key features involve intuitive navigation, detailed data summarization, and robust analysis with filtering, sorting, and visualization options. Start by cloning the repo, installing dependencies, and using Streamlit to run the app in your browser. The platform values community insights and contributions for ongoing improvements.

Discover comprehensive tutorials on Python, Streamlit, Machine Learning, Bioinformatics, and AI technologies including OpenAI and ChatGPT. These resources cater to both learners and professionals aiming to sharpen their skills in automation and data analysis. From introductory guides to advanced subjects, enrich your understanding of Python programming, machine learning automation, bioinformatics, and AI-driven web applications. Follow step-by-step video content and insightful blog articles designed for efficient navigation of today's digital challenges, suitable for those keen on keeping up with the rapid pace of tech development.

MLX Chat is a web interface for MLX's mlx-lm, built with Streamlit for ease of use. It provides straightforward installation, update, and execution of ML models, with the ability to utilize a custom model.txt for customization. This project is suitable for developers and data scientists looking for efficient model deployment. Users should note potential issues with the latest library versions. Additional models and resources are available via the mlx-community on Hugging Face.

Barfi is a Python library offering a seamless integration of visual Flow Based Programming into existing workflows through a user-friendly interface. It utilizes modular `barfi.Block`s and `barfi.ComputeEngine` for task customization and flexibility. Unlike existing solutions, Barfi integrates within current environments using a Streamlit widget, with Jupyter-Notebook compatibility planned, ensuring adaptability and accessibility across domains.

Keras-llm-robot utilizes Langchain and Fastchat frameworks in a Streamlit UI for offline deployment of Hugging Face models, with features like model integration, multimodal support, and customizations including quantization and fine-tuning. It also offers tools for retrieval, speech, and image recognition, plus environment setup guides for multiple OSs, ideal for developers exploring AI model deployment.

docGPT facilitates seamless communication with various document formats including PDF, DOCX, CSV, and TXT, enhancing workflow without expensive API keys or subscriptions using 'gpt4free'. Deploy it easily on platforms like Streamlit for flexible access. Leveraging LangChain's capabilities, docGPT empowers users to address complex queries, including those beyond 2020. Suitable for diverse use cases, it provides guidance on deploying personalized models such as OpenAI's gpt-3.5-turbo.

Renumics RAG offers a platform for visualizing retrieval-augmented generation using LangChain and Streamlit, suitable for both GPU and CPU setups. It supports configurations with OpenAI, Azure, and Hugging Face models, allowing the indexing and querying of customized data. The integrated web app facilitates interactive questioning, while Renumics Spotlight enhances visual exploration for detailed analysis of documents and queries, making it a robust tool for scalable data management in AI projects.

This project delivers an intuitive interface for the OpenAI Assistants API, simplifying the setup process with ASSISTANT IDs. Offering features like file handling, streaming API, and support for various assistant profiles, it boosts user engagement and efficiency. Compatible with Azure OpenAI, it facilitates easy deployment through Streamlit Cloud or Docker, with strong authentication protocols. Designed for versatile applications, it offers a seamless experience with quick setup and detailed environment configurations. A great choice for developers pursuing streamlined assistant integrations in flexible environments.

The Python application facilitates interaction with PDFs via natural language inquiries, utilizing an LLM for accurate content-based responses. It employs OpenAI embeddings and integrates Langchain for smooth functionality. Featuring a GUI built on Streamlit, the tool is intuitive for extracting and querying PDF information. It serves as an instructional resource, supported by a detailed Youtube tutorial, offering a step-by-step guide for learners and developers to implement this AI-powered document solution.

PDFChat facilitates interaction with PDF documents using advanced AI technologies such as langchain, OpenAI Embeddings, and GPT-3.5. The app uses Streamlit for an intuitive interface that ensures smooth document interaction. Users need to clone the repository, set up a conda environment, and configure the OpenAI API for installation. This tool is suitable for those looking for a straightforward method to converse with and extract insights from PDFs, offering a novel approach to document engagement. Discover the easy setup at http://localhost:8501.

This tool utilizes the latest ChatGPT API and state-of-the-art AI technologies such as Streamlit, LlamaIndex, and LangChain to streamline PDF parsing and lecture slide management. It features advanced models like gpt-3.5-turbo and supports customizable prompts, local storage options, and multi-document querying for a comprehensive and efficient user experience.

Explore a range of templates and examples for creating Streamlit Components with flexible frontends using different web technologies and a Python API. These components are designed for seamless integration into Streamlit apps and can be made available through PyPI. The repository provides comprehensive instructions on setting up a Python environment, creating the component frontend, and running associated Streamlit apps. It also showcases examples for non-React templates and collaboration with third-party tools, supporting contributions from the community.

Explore complete tools, prompts, frameworks, and a rich knowledge hub essential for building Large Language Model (LLM) agents. The project converts user inputs into interactive Streamlit apps, leveraging GPT-3.5-turbo for automatic LangChain code. Supporting various LLM models, DemoGPT continuously adopts new tech developments. Its workflow includes planning, task creation, code snippet generation, and final app assembly. Future updates will focus on integrating with external APIs and streamlining workflows for effective LLM development.

Discover a collection of practical examples utilizing local large language models in the Local Assistant Examples repository. Originating from a guide on locally implementing Retrieval-Augmented Generation (RAG) models with Langchain, Ollama, and Streamlit, this repository has evolved to include a wider range of educational materials. Each example, complete with its own README, is structured to facilitate clear understanding and implementation. This project is designed for educational use, providing simplified insights into LLM applications away from production intricacies. Stay informed as new examples become available.

Discover the RAG Agent for document summarization, query handling, and intent detection. Supports .pdf, .txt, .docx uploads for efficient document management on the agentic-rag platform.

Explore how to effortlessly generate professional emails using this ChatGPT-powered app, despite its current inactivity due to API changes. For those interested in self-hosting, refer to the GitHub repository for setup instructions. This application, designed with user simplicity and efficiency in mind, illustrates the ease of email creation under the MIT License. Reach out to the developer for more information.

chatgpt-finetune-ui provides a Python-based WebUI to finetune GPT-3.5-turbo, aiming to streamline the adjustment process. With straightforward installation through OpenAI and Streamlit, it's designed to be accessible and adaptable. Execute via a basic Streamlit command, offering flexible server setups for efficient deployment. Suitable for developers looking for an intuitive platform to refine AI models. Explore the experimental demo for a practical understanding of its functionalities, fostering an effective interaction with cutting-edge AI technology.

NewsNerd HackerBot provides access to top Hacker News stories, sentiment analysis on comments, and linked article insights. Users can filter by keywords for a detailed understanding. Accessible via Streamlit Cloud or locally with simple installation.

The autonomous-hr-chatbot is a prototype that utilizes AI to manage HR inquiries efficiently. Through the integration of LangChain's agents, ChatGPT, and Pinecone's vector database, this application processes HR queries with ease. It features a Streamlit front-end for seamless interaction and includes tools such as ChatGPT-generated HR policy documents, a dummy employee data handler, and a calculator for complex computations. This project demonstrates the potential of AI tools in improving organizational workflows and data management.

RAGxplorer is an open-source tool for creating Retrieval Augmented Generation (RAG) visualizations. This platform allows users to enhance their data analysis with easy installation, streamlined Jupyter notebooks, and a Streamlit demo for practical insights. Discover its extensive features and collaborate on GitHub, all under the MIT license. The project draws inspiration from DeepLearning.AI and is supported by the Streamlit community.

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.

Explore a diverse range of applications utilizing LangChain for large language model capabilities. This collection includes examples like chatbots, document summarization, and generative Q&A, presented through interactive Streamlit apps. Understand AI technologies better through projects demonstrating LLM observability and search queries with APIs such as OpenAI, Chroma, and Pinecone. Perfect for developers and AI researchers looking for practical insights into cutting-edge AI tools.

Access Snowflake data easily with natural language queries, simplifying SQL processes. This tool enables swift data-driven decision-making by converting conversational language into SQL, delivering real-time insights through an intuitive interface. Supporting advanced models like GPT-4o, it provides precise query results and maintains interaction context. Enhanced by Snowflake integration and self-healing SQL, this application improves data access efficiency and overall user experience.

This mini-app on Streamlit generates Tweet texts using OpenAI's GPT models and incorporates DALL·E for image creation. Users enter a topic and optional mood, generating a unique Tweet and accompanying image. Note that style transfer may be affected by Twitter API limitations. This app is perfect for exploring the potential of GPTs in Tweet generation, complete with visual elements. For feedback or questions, contact [email protected].

Utilize OpenAI's GPT-3 to efficiently automate the process of composing medium to long-sized emails. This tool reduces the time and effort involved in writing professional emails, while conserving mental energy. Set up your local environment effortlessly with Streamlit and deploy web applications using Heroku CLI. Experience a user-friendly interface for seamless email generation directly in Gmail.

ChatMol integrates LLMs into PyMOL, permitting natural language use for task automation and Q&A. It supports command line, miniGUI, and browser interfaces, providing flexibility in PyMOL operations. ChatMol-Lite offers rapid responses without an API key requirement. Learn more on its official site for insights into molecular visualization and analysis.