
Neuron
PHP framework for building agentic AI applications and multi-agent workflows.
Pregled
Ključne funkcije
- Agent and workflow abstractions
- Tool calling and function execution
- Memory and context management
- RAG and vector store integrations
- Multi-provider LLM support
- Structured output handling
Prednosti in slabosti
Prednosti
- Native PHP integration with existing apps
- Supports multiple LLM providers
- Built-in tools, memory, and RAG features
- Open-source and developer-friendly
Slabosti
- Smaller ecosystem than Python AI frameworks
- Requires PHP and AI development knowledge
- Documentation may evolve as project matures
Ocene
Povprečje iz 6 ocen.
Prijavi se za oddajo ocene.
Liam O’Connor
Years in this space
I've evaluated a lot of these over the years. What stands out here is agent and workflow abstractions — handled better than most — and native PHP integration with existing apps. Requires PHP and AI development knowledge is my one real gripe. Worth the time if this is your use case.
George Papadakis
Years in this space
I've evaluated a lot of these over the years. What stands out here is tool calling and function execution — handled better than most — and native PHP integration with existing apps. Requires PHP and AI development knowledge is my one real gripe. Worth the time if this is your use case.
Ethan Brooks
Solid for our team
We rolled this out across the team last quarter and supports multiple LLM providers. Structured output handling fits neatly into how we already work, and memory and context management removed a step we used to do by hand. but it has held up under daily use.
Linda Petersen
Use it every day
Honestly didn't expect to like it this much. Structured output handling is exactly what I needed, and native PHP integration with existing apps. I do wish smaller ecosystem than Python AI frameworks, but I reach for it almost every day now and it just clicks.
Joanna Kowalski
Skeptical, then convinced
I went in skeptical — most tools in this space overpromise. It actually delivers on rAG and vector store integrations, and open-source and developer-friendly caught me off guard. still, I'd recommend giving it a real trial.
Margaret Whitfield
Compared a few options
Evaluated this against two competitors. Where it wins: structured output handling and open-source and developer-friendly. On balance the feature set — especially multi-provider LLM support — justifies the 5 stars for our use case.
Vprašanja
Še ni vprašanj — postavi prvo.
Postavi vprašanje
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