mlrun
phidata
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| mlrun | phidata | |
|---|---|---|
| 3 | 14 | |
| 1,294 | 3,622 | |
| 6.0% | 32.9% | |
| 9.9 | 9.9 | |
| 5 days ago | 6 days ago | |
| Python | Python | |
| Apache License 2.0 | Mozilla Public 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.
mlrun
- Discussion on Need of Feature Stores
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I reviewed 50+ open-source MLOps tools. Here’s the result
You should also add MLRun: https://github.com/mlrun/mlrun
- Has anyone here been able to deploy Mlrun successfully on Kubernetes cluster?
phidata
- Show HN: Use function calling to build AI Assistants
- Phidata: Build AI Assistants using function calling
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Chat with ArXiv Papers
Hi HN, I built an app to chat with arXiv papers: https://arxiv.aidev.run
I’m using function calling to interact with the arXiv api, here’s the general flow:
> For a users question, search the knowledge base (pgvector) for the topic/paper
> If knowledge base results are not relevant, search arXiv api for paper, parse it and store it in the knowledge base
> Answer questions or summarize using contents from the knowledge base.
Give it a spin at: https://arxiv.aidev.run and let me know what you think.
Its a work in progress and I’m looking for feedback on how to improve. The read time from the arXiv api is a bit slow – but not much I can do about it.
I used phidata to build this: https://github.com/phidatahq/phidata
Here’s the code if you’re interested: https://github.com/phidatahq/ai-cookbook/blob/main/arxiv_ai/assistant.py
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Chat with PDFs using function calling
- I used phidata to build this: https://github.com/phidatahq/phidata
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Show HN: Hacker News AI built using function calling
Hi HN, I built an AI that can interact with the Hacker News API and answer questions about hackernews stories, whats trending, what on show etc..
Check it out here: https://hn.aidev.run
You can ask questions like:
- What on hackernews about AI?
- What on hackernews about iPhone?
- What's trending on hackernews?
- What are users showing on hackernews?
- What are users asking on hackernews?
- Summarize this story: https://news.ycombinator.com/item?id=39156778
It uses function calling to query the HN api.
To answer questions about a particular topic, it’ll search its knowledge base (a vector db that is periodically updated with the “top stories”) and get details about those stories from the API.
This is pretty barebones and I built it today in < 2 hours, so it probably won’t meet your high standards. If you give it a try, I’d love your feedback on how I can improve it.
If you’re interested, I built this using phidata: https://github.com/phidatahq/phidata
Thanks for reading and would love to hear what you think.
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Show HN: Hacker News AI
- Summarize this story: https://news.ycombinator.com/item?id=39156778
It uses function calling to query the HN api.
To answer questions about a particular topic, it’ll search its knowledge base (a vector db that is periodically updated with the “top stories”) and get details about those stories from the API.
This is pretty barebones and I built it today in < 2 hours, so it probably won’t meet your high standards. If you give it a try, I’d love your feedback on how I can improve it.
If you’re interested, I built this using phidata: https://github.com/phidatahq/phidata
Thanks for reading and would love to hear what you think.
- Show HN: Build AI Assistants using LLM function calling
- AI App Templates pre-built
- Build Autonomous Assistants using LLM function calling
- Build human-like AI products using language models
What are some alternatives?
feast - Feature Store for Machine Learning
hamilton - Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.
dagster-example-pipeline - Template Dagster repo using poetry and a single Docker container; works well with CICD
NeumAI - Neum AI is a best-in-class framework to manage the creation and synchronization of vector embeddings at large scale.
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
SmartSim - SmartSim Infrastructure Library.
AWS Data Wrangler - pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
mosec - A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
hamilton - A scalable general purpose micro-framework for defining dataflows. THIS REPOSITORY HAS BEEN MOVED TO www.github.com/dagworks-inc/hamilton
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
ai-cookbook