
Helicone AI
Langfuse
LangSmith
Portkey
liteLLM
OpenRouter
LangChain
Openlayer
Think Python
Google's Python Class
The New Boston video series
A Byte of Python
Hackr.io
Learn Python The Hard Way
Corey Schafer Youtube
Udacity - CS101
Helicone AI
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Based on our record, Think Python should be more popular than Helicone AI. It has been mentiond 9 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Helicone takes the simplest possible approach to LLM monitoring: it's a proxy. Change your OpenAI base URL from api.openai.com to oai.helicone.ai, add your Helicone API key as a header, and every LLM request is logged โ latency, tokens, cost, prompts, and completions. No SDK integration, no code changes beyond a URL swap. - Source: dev.to / 20 days ago
You're monitoring production traffic. You need Langfuse / Phoenix / Helicone / Braintrust for that. Online eval is a different problem class: implicit feedback, drift detection, hallucination rates on your data, not on HellaSwag. - Source: dev.to / about 1 month ago
For many teams, especially those starting out or with simpler needs, commercial solutions like Portkey, Helicone, OpenPipe, or LiteLLM Proxy offer off-the-shelf capabilities that cover many common proxy use cases (caching, logging, cost tracking). NeuroLink itself can be seen as an SDK that complements these, allowing you to integrate with them or build similar features on top. - Source: dev.to / 3 months ago
TL;DR: Go with Langfuse if you want open-source and self-hosted. Pick Helicone if you want the fastest setup (2 minutes, no SDK). Stick with LangSmith if your stack already runs on LangChain. And if your org already pays for Datadog, their LLM module slots right in. - Source: dev.to / 4 months ago
Hey HN, we're Justin and Cole, the founders of Helicone (https://helicone.ai) or self-deploy with our new fully open-source helm chart (https://helicone.ai/selfhost). Yet even with detailed traces, probabilistic systems are notoriously hard to debug at scale. So, we released evaluators (either via LLM-as-judge or custom Python evaluators leveraging the CodeSandbox SDK - https://codesandbox.io/docs/sdk/sandboxes).... - Source: Hacker News / over 1 year ago
This course actually starts with an introduction to Python. Since you don't have access yet, you can give Think Python a whirl - https://greenteapress.com/wp/think-python/ and for a more interactive experience, I really enjoyed this one - https://scrimba.com/learn/python. Source: about 3 years ago
Start with Think Python or learn x in y..both are free resources and good for basic understanding and practise. Source: about 3 years ago
This free book taught me Python many years ago https://greenteapress.com/wp/think-python/. Source: about 4 years ago
In terms of learning the basics of Python programming, you can get the first edition of Think Python in PDF form for free. Source: over 4 years ago
Computer Science โ For understanding software development. As for a programming language to learn, I recommend Python or Javascript. Try Crash Course's Computer Science videos, the free Think Python book, and/or Part 1 of The Modern JavaScript Tutorial. Source: over 4 years ago
Langfuse - Langfuse is an open-source LLM engineering platform that helps teams collaboratively debug, analyze, and iterate on their LLM applications.
Google's Python Class - Assorted educational materials provided by Google.
LangSmith - Build and deploy LLM applications with confidence
The New Boston video series - Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.
Portkey - Build production-grade & reliable AI apps with Portkey
A Byte of Python - A Byte of Python is a Python programming tutorial and learning book that teaches you how to program with the Python programming language.