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LLMStack Alternatives
Similar projects and alternatives to LLMStack
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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Directus
The Modern Data Stack 🐰 — Directus is an instant REST+GraphQL API and intuitive no-code data collaboration app for any SQL database.
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prql
PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement
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LocalAI
:robot: The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. It allows to generate Text, Audio, Video, Images. Also with voice cloning capabilities.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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lowdefy
The config web stack for business apps - build internal tools, client portals, web apps, admin panels, dashboards, web sites, and CRUD apps with YAML or JSON.
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buzz
Buzz transcribes and translates audio offline on your personal computer. Powered by OpenAI's Whisper.
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spider
scripts and baselines for Spider: Yale complex and cross-domain semantic parsing and text-to-SQL challenge
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anything-llm
The all-in-one Desktop & Docker AI application with full RAG and AI Agent capabilities.
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langflow
⛓️ Langflow is a dynamic graph where each node is an executable unit. Its modular and interactive design fosters rapid experimentation and prototyping, pushing hard on the limits of creativity.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better LLMStack alternative or higher similarity.
LLMStack reviews and mentions
Posts with mentions or reviews of LLMStack.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-14.
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Vanna.ai: Chat with your SQL database
We have recently added support to query data from SingleStore to our agent framework, LLMStack (https://github.com/trypromptly/LLMStack). Out of the box performance performance when prompting with just the table schemas is pretty good with GPT-4.
The more domain specific knowledge needed for queries, the harder it has gotten in general. We've had good success `teaching` the model different concepts in relation to the dataset and giving it example questions and queries greatly improved performance.
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FFmpeg Lands CLI Multi-Threading as Its "Most Complex Refactoring" in Decades
This will hopefully improve the startup times for FFmpeg when streaming from virtual display buffers. We use FFmpeg in LLMStack (low-code framework to build and run LLM agents) to stream browser video. We use playwright to automate browser interactions and provide that as tool to the LLM. When this tool is invoked, we stream the video of these browser interactions with FFmpeg by streaming the virtual display buffer the browser is using.
There is a noticeable delay booting up this pipeline for each tool invoke right now. We are working on putting in some optimizations but improvements in FFmpeg will definitely help. https://github.com/trypromptly/LLMStack is the project repo for the curious.
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Show HN: IncarnaMind-Chat with your multiple docs using LLMs
We built https://github.com/trypromptly/LLMStack to serve exactly this persona. A low-code platform to quickly build RAG pipelines and other LLM applications.
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A Comprehensive Guide for Building Rag-Based LLM Applications
Kudos to the team for a very detailed notebook going into things like pipeline evaluation wrt performance and costs etc. Even if we ignore the framework specific bits, it is a great guide to follow when building RAG systems in production.
We have been building RAG systems in production for a few months and have been tinkering with different strategies to get the most performance out of these pipelines. As others have pointed out, vector database may not be the right strategy for every problem. Similarly there are things like lost in the middle problems (https://arxiv.org/abs/2307.03172) that one may have to deal with. We put together our learnings building and optimizing these pipelines in a post at https://llmstack.ai/blog/retrieval-augmented-generation.
https://github.com/trypromptly/LLMStack is a low-code platform we open-sourced recently that ships these RAG pipelines out of the box with some app templates if anyone wants to try them out.
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Building a Blog in Django
Django has been my go to framework for any new web project I start for more than a decade. Its batteries-included approach meant that one could go pretty far with just Django alone. Included admin interface and the views/templating setup was what first drew me to the project.
Django project itself has kept pace with recent developments in web development. I still remember migrations being an external project, getting merged in and the transition that followed. Ecosystem is pretty powerful too with projects like drf, channels, social-auth etc., covering most things we need to run in production.
https://github.com/trypromptly/LLMStack is a recent project I built entirely with Django. It uses django channels for websockets, drf for API and reactjs for the frontend.
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Show HN: Rivet – open-source AI Agent dev env with real-world applications
We recently opensourced a similar platform for building workflows by chaining LLMs visually along with LocalAI support.
Check it out at https://github.com/trypromptly/LLMStack. Like you said, it was fairly easy to integrate LocalAI and is a great project.
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Show HN: Retool AI
Would you mind expanding why it was tough to get started with Retool?
We are building https://github.com/trypromptly/LLMStack, a low-code platform to build LLM apps with a goal of making it easy for non-tech people to leverage LLMs in their workflows. Would love to learn about your experience with retool and incorporate some of that feedback into LLMStack.
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We built a self-hosted low-code platform to build LLM apps locally and open-sourced it
We built LLMStack for our internal purposes and pulled it out into its own repo and open sourced it at https://github.com/trypromptly/LLMStack.
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LLMStack: self-hosted low-code platform to build LLM apps locally with LocalAI support
LLMStack (https://github.com/trypromptly/LLMStack) is a no-code platform to build LLM apps that we have been working on for a few months and open-sourced recently. It comes with everything out of the box that one needs to build LLM apps locally or in an enterprise setting.
- LLMStack: a self-hosted low-code platform to build LLM apps locally
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A note from our sponsor - InfluxDB
www.influxdata.com | 2 May 2024
Stats
Basic LLMStack repo stats
20
1,112
9.9
4 days ago
trypromptly/LLMStack is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
LLMStack is marked as "self-hosted". This means that it can be used as a standalone application on its own.
The primary programming language of LLMStack is Python.
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