evadb
Adala
evadb | Adala | |
---|---|---|
27 | 5 | |
2,578 | 732 | |
0.9% | 8.7% | |
9.5 | 9.1 | |
16 days ago | 1 day ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
evadb
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Show HN: Stargazers Reloaded – LLM-Powered Analyses of Your GitHub Community
Hey friends!
We have built an app for getting insights about your favorite GitHub community using large language models.
The app uses LLMs to analyze the GitHub profiles of users who have starred the repository, capturing key details like the topics they are interested in. It takes screenshots of the stargazer's GitHub webpage, extracts text using an OCR model, and extracts insights embedded in the extracted text using LLMs.
This app is inspired by the “original” Stargazers app written by Spencer Kimball (CEO of CockroachDB). While the original app exclusively used the GitHub API, this LLM-powered app built using EvaDB additionally extracts insights from unstructured data obtained from the stargazers’ webpages.
Our analysis of the fast-growing GPT4All community showed that the majority of the stargazers are proficient in Python and JavaScript, and 43% of them are interested in Web Development. Web developers love open-source LLMs!
We found that directly using GPT-4 to generate the “golden” table is super expensive — costing $60 to process the information of 1000 stargazers. To maintain accuracy while also reducing cost, we set up an LLM model cascade in a SQL query, running GPT-3.5 before GPT-4, that lowers the cost to $5.5 for analyzing 1000 GitHub stargazers.
We’ve been working on this app for a month now and are excited to open source it today :)
Some useful links:
* Blog Post - https://medium.com/evadb-blog/stargazers-reloaded-llm-powere...
* GitHub Repository - https://github.com/pchunduri6/stargazers-reloaded/
* EvaDB - https://github.com/georgia-tech-db/evadb
Please let us know what you think!
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Language Model UXes in 2027
The discord link seems to be not working. Just a heads up.
The YOLO example on your Github page is super interesting. We are finding it easier to get LLMs to write functions with a more constrained function interface in EvaDB. Here is an example of an YOLO function in EvaDB: https://github.com/georgia-tech-db/evadb/blob/staging/evadb/....
Once the function is loaded, it can be used in queries in this way:
SELECT id, Yolo(data)
- EvaDB: Bring AI to your Database System
- Show HN: I wrote a RDBMS (SQLite clone) from scratch in pure Python
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Gorilla: Large Language Model Connected with APIs
Neat idea, @shishirpatil! We are developing EvaDB [1] for shipping simpler, faster, and cost-effective AI apps. Can you share your thoughts on transforming the output of the Gorilla LLM to functions in EvaDB apps -- like this function that uses the HuggingFace API -- https://evadb.readthedocs.io/en/stable/source/tutorials/07-o...?
[1] https://github.com/georgia-tech-db/eva
- PrivateGPT in SQL
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Eva AI-Relational Database System
Thanks for checking! Currently, we have a Docker image for deploying EVA [1]. We plan to release a Terraform config soon that will make it easier to deploy EVA DB on an AWS/Azure server with GPUs.
[1] https://github.com/georgia-tech-db/eva/tree/master/docker
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This week's top indie A.I projects, launches and resources
EVA AI-Relational Database System; build simpler and faster AI-powered apps
- Show HN: EVA – AI-Relational Database System
Adala
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Ask HN: Are you using a GPT to prompt-engineer another GPT?
We recently open sourced an agent framework [1] for automating data processing and labeling where the prompt is refined trough iterations (i.e. automatic prompt tuning). We tested it on the Math reasoning dataset GSM8k and where able to improve the baseline accuracy (GPT4) by 45% -> 74% using 25 labeled examples (I'll put the notebook and blog post linked below [2][3]). Results are definitively very interesting, if not surprising with some skills, and we see more and more of our open source users and customers showing interested in the framework for automating labeling / having it as a data processing / labeling copilot.
[1] https://github.com/HumanSignal/Adala
[2] https://github.com/HumanSignal/Adala/blob/master/examples/gs...
[3] https://labelstud.io/blog/mastering-math-reasoning-with-adal...
- Adala: Autonomous Data Agent Framework
- Show HN: Adala framework – Applying LLM skills to various data processing tasks
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Adala: Reliable Open Source Agent Framework for Data Processing
We have just open sourced Adala - a robust framework for implementing agents that specialize in advanced data processing tasks, starting with data labeling and generation.
- Show HN: Adala – Autonomous Data (Labeling) Agent
What are some alternatives?
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
langroid - Harness LLMs with Multi-Agent Programming
emdash - 📚🧙♂️ Wisdom indexer — use AI to organize text snippets so you can actually remember & learn from what you read
agents-aea - A framework for autonomous economic agent (AEA) development
jsonformer - A Bulletproof Way to Generate Structured JSON from Language Models
DemoGPT - Create 🦜️🔗 LangChain apps by just using prompts🌟 Star to support our work! | 只需使用句子即可创建 LangChain 应用程序。 给个star支持我们的工作吧!
MindsDB - The platform for customizing AI from enterprise data
GPT-HTN-Planner - A Hierarchical Task Network planner utilizing LLMs like OpenAI's GPT-4 to create complex plans from natural language that can be converted into an executable form.
gpt-json - Structured and typehinted GPT responses in Python
micro-gpt - MiniAGI is a minimal general-purpose autonomous agent based on GPT-3.5 / GPT-4. Can analyze stock prices, perform network security tests, create art, and order pizza. [Moved to: https://github.com/muellerberndt/mini-agi]
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
automata - Automata: The Future is Self-Written