Hello, I'm the founder of Devv. Thank you for your feedback; however, I'm not acquainted with Zag, so I can't identify the incorrect syntax.

I utilized Agent Mode to rephrase the query, and here are the results: https://devv.ai/search?threadId=dl3rtxmcsruo

P.S. Agent Mode is a superior option to Fast Mode. It meticulously examines your questions and assigns an appropriate agent to provide answers, leveraging GPT-4 technology in its operations.

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> The syntax came from a language proposal in a github issue from 8 years ago, so I guess it's not fully hallucinated. But still not the best choice of what source to use.

Yes, if the source contains errors, the response may generate inaccurate information. We are continually refining our re-ranking algorithm within the Retrieval-Augmented Generation (RAG) system to select the most reliable sources.

I've noticed this w/ using LLMs for programming, esp while learning Zig.

Outside of popular languages it seems like they always hallucinate.

Both Bing Copilot and Perplexity Copilot uses GTP-4 under the hood. For more LLMs, check out https://labs.perplexity.ai

I pay for perplexity pro - absolutely love it.

I had an issue with shopify and was able to work through the fix using perplexity which I wasn't able to get with chatgpt on its own.

I love that you can change the models, I mostly use Claude opus though.

I do wish the image generator was better but they frame perplexity as a search engine rather than chat so I have firefly if I really need an image.

I just signed up for the PPLX API and it surprisingly doesn't do internet searches... It just has slightly more recent info than GPT-4.

Try searching for "Weather in [your city]" and compare it to Google or any weather app. It's consistently wrong.

I use perplexity because it's the best free GPT that is anonymous (no login required)

does the bing API have citations? both you.com and pplx have that feature which chatGPT doesn't, tho its still in closed beta release for pplx

That's kind of an interesting issue, I wonder if different tokenization would help. Like maybe putting a space between GTK and the number would put them in separate tokens and give better output.

More generally, do text AI's not support weighting terms like the image AI's do? Over in Stable Diffusion that sounds like something where I'd add a weight like "How do I create a <GTK3:1.2> interface in <PHP:1.1>?"

It is quite possible that the lack of actual intelligence in the LLM is the obstacle in this context.

I also just queried something with "perplexing" results in fact, but I tried the "generic" "knowledge" instead of the "specific" about coding: in the reply the engine included good pointers, but clearly without knowing why they were especially relevant - relevance which instead appeared in the linked references.

It is an LLM+RAG based search engine: the value is only partly in the summary, which could even be misleading - as expected from lack of actual intelligence -, the value is in the linked resources.

In other words, it "understands" your query better that a search engine of the past - and that is valuable. But for the actual solution you are querying for, the "summary" part could be good or could be defective: it is probably best to consult the linked material... Material that you could have not found immediately otherwise - it could have been tricky with past technology to express your need in a way that makes you obtain good search results.

Have you tried Agent Mode? It offers greater intelligence and accuracy compared to Fast Mode.

P.S. Agent Mode is a superior option to Fast Mode. It meticulously examines your questions and assigns an appropriate agent to provide answers, leveraging GPT-4 technology in its operations.

I use Agent Mode to rephrase the query, and it appears to have provided the correct answer.

The results: https://devv.ai/search?threadId=dl3vwbdu52ww

P.S. Agent Mode is a superior option to Fast Mode. It meticulously examines your questions and assigns an appropriate agent to provide answers, leveraging GPT-4 technology in its operations.

You can initiate a new search by using the URL `https://devv.ai/search/{query}`.

Currently, we display terms on Notion pages, which may not be viewable in your browser. We plan to transfer this content to our website shortly.

You can view the terms here: https://indexlabs.notion.site/Term-of-Service-6ca77cbc49504c...

Hi, Devv founder here.

Thank you for your valuable feedback; it's an excellent suggestion! In fact, we've already begun implementing this feature with our initial step being the introduction of GitHub Mode. This new functionality will enable seamless integration with your personal GitHub repositories. We've developed a bespoke indexer tailored to various programming languages to enhance this experience.

Furthermore, we can expand this capability to include documentation and other resources as well. The architecture is designed to be extensible, so all that's needed is the creation of additional indexers to support these materials.

I've previously given a talk on RAG and am eager to adapt it into an article in the future.

I would also love an API like this for integration with Plandex[1] (a terminal-based coding agent for complex tasks). Perplexity has an API but it only exposes various open source LLMs, not the search-enriched results from their main product.

It would be really cool if, when starting a coding task with Plandex, relevant docs/context from a web search could be automatically included in context via this kind of API. Currently urls can be loaded into context with `plandex load [url]` but you have to figure out which urls would be helpful to load yourself.

1 - https://github.com/plandex-ai/plandex

Hi, Devv founder here.

That sounds interesting. Could you provide further details? By the way, integrating an API is part of our future plans. We plan to enable Devv integration with Slack, Linear, and websites in the future.

Also, if you want to discuss more, feel free to email me at jiayuan@devv.ai

Hi, Devv founder here.

Yes, this is on our roadmap. We will launch "Devv for Teams" in the upcoming quarter. This new feature will enable seamless integration of internal team knowledge, including codebases, wikis, issue trackers, and logs.

I would install right away if this is the case.

I really distrust putting my API keys into brand new and unknown websites, just seems like credentials harvesting to me.

It won't be worth looking into, because there's nothing they (devv.ai) can do, short of trying some automated self-improvement loop a la devin where the AI writes code, evaluates the code, fixes issues as they arise... Still not worth, it's not their core business.

You're just hitting a limit of the LLMs, they won't give you bug-free code, specially not from the first time, specially not complex ones like galloping timsort.

Hi, Devv founder here. It works fine here, did you just click the "related questions"? This will generate a follow-up answer.

frontend: next.js + react + vercel

backend: go/rust/python + gin + mysql + pinecone + es + redis + aws

llm: openai/azure + aws gpu + aws bedrock

Creating a simple generative search engine is straightforward and can be accomplished over a weekend.

Essential components include: - A search engine API (such as Bing or Google's) - Integration of search engine results with a Large Language Model (LLM)

This framework, known as Retrieval-Augmented Generation (RAG), was the foundation for the initial version of Perplexity.

The challenging aspect lies in refining the generation outcomes, which involves more proprietary techniques.

This does not align with their vision.

Hi, Devv founder here.

I've outlined some initial ideas in this post and may develop a more detailed article later on. Stay tuned!