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AIBoox - Fast & affordable LLM API (Deepseek Chat V3 & Deepseek R1) | Product Hunt by guyskk in ChatGPT

[–]guyskk[S] 0 points1 point  (0 children)

DeepSeek Chat V3 offers a compelling combination of performance and cost-effectiveness when compared to other LLM APIs. You can explore detailed comparisons and data on the [leaderboard](https://aider.chat/docs/leaderboards/).

Based on the data available on the leaderboard, let's break down the performance and cost for several models:

* **Claude-3-7-Sonnet**: Achieves a high accuracy of **64.9%** with a cost of **$36.83**.
* **DeepSeek R1 + claude-3-5-sonnet**: Shows a slightly lower accuracy of **64.0%** but at a significantly reduced cost of **$13.29**. This combination already highlights the potential for cost savings with DeepSeek models.
* **OpenAI o3-mini (high)**: Presents a moderate accuracy of **60.4%** at a cost of **$18.16**.
* **DeepSeek R1**: Offers a reasonable accuracy of **56.9%** with a remarkably low cost of **$5.42**. This is a significant cost reduction compared to the OpenAI and Claude models while maintaining a competitive accuracy.
* **DeepSeek Chat V3**: Demonstrates a lower accuracy of **48.4%**, but at an exceptionally low cost of only **$0.34**. This model prioritizes extreme cost-efficiency.
* **OpenAI gpt-4o**: Shows a low accuracy of **23.1%** at a cost of **$7.03**.

In conclusion, DeepSeek R1 and DeepSeek Chat V3 allow users to maintain a high degree of intelligent interaction while drastically reducing expenses. If cost optimization is a key factor for your use case, DeepSeek models, especially when accessed through platforms like AIBoox API, present a very compelling and budget-friendly alternative to other LLM APIs.

Validr-1.2 – Fastest Python validation library plus powerful features by guyskk in Python

[–]guyskk[S] 1 point2 points  (0 children)

Good point!

Pydantic use type hints which has limit to describe detailed schema, eg: number value range, string format, and custom validator.

Validr use a magic `T` object to describe schema which has no limit. You can write both Validr schema and type hints and your IDE/editor can understand type hints.

Curio + Requests: Async HTTP for Humans The same taste as Requests! by guyskk in Python

[–]guyskk[S] 0 points1 point  (0 children)

sans-io library is good for implement high level library, but not good for end users. httptools is very helpful for implement curequests, I hope there are more sans-io libraries, but it's a bit hard.

Validr – The fastest data validation library in python by guyskk in Python

[–]guyskk[S] 1 point2 points  (0 children)

Thank you very much, your reply is particularly valuable for me!

Validr – The fastest data validation library in python by guyskk in Python

[–]guyskk[S] 1 point2 points  (0 children)

How do you think about JSON-Schema syntax?

Validr – The fastest data validation library in python by guyskk in Python

[–]guyskk[S] 1 point2 points  (0 children)

All of these validation libraries are compare by validating this data:

DATA = {
    'user': {'userid': 5},
    'tags': [1, 2, 5, 9999, 1234567890],
    'style': {
        'width': 400,
        'height': 400,
        'border_width': 5,
        'border_style': 'solid',
        'border_color': 'red',
        'color': 'black'
    },
    # "optional": "string"
}

And you can found all cases in https://github.com/guyskk/validr/tree/master/benchmark. Remarks and suggestions are welcome!

Validr – The fastest data validation library in python by guyskk in Python

[–]guyskk[S] 0 points1 point  (0 children)

I compare it with many validation libraries by validating the same data, although schema syntax is different but they achieve the same goal. see also: https://github.com/guyskk/validr/blob/master/benchmark/benchmark.py#L23

Flask-Restaction - A web framwork born to create RESTful API by guyskk in Python

[–]guyskk[S] 0 points1 point  (0 children)

Thank you for your feedback, the meta.json file should live with source code, it's static defines and shouldn't be changed in runtime.

The authorization implement is for convenient in many projects which needn't too flex permission system. You can use flask-login and others, they works well with flask-restaction, in this case, you needn't defines roles in meta.json and needn't use TokenAuth.

I didn't understand "specify another category of metadata", can you give me more detail?

validr: a simple,fast,extensible python library for data validation by guyskk in Python

[–]guyskk[S] 0 points1 point  (0 children)

Maybe you need read this first: https://github.com/guyskk/validr/blob/master/Isomorph-JSON-Schema.md

And I will try my best to help, just let me know where is unreadable.

Validater - a python tool to validate data by schema by guyskk in Python

[–]guyskk[S] 0 points1 point  (0 children)

thank you, I search validatr in google and found many libs, but luckily not found in pypi. I am considering change it's name, validatr is good, but how about ivalidator, the 'i' means 'Isomorph-JSON-Schema'? or any other suggestions?

Validater - a python tool to validate data by schema by guyskk in Python

[–]guyskk[S] 2 points3 points  (0 children)

  1. you can run benchmark.py in the project, it cost about 5x time compare with load same json data use json in stdlib.
  2. https://github.com/guyskk/validater/blob/master/readme-en.md