DAdanlenton·May 22, 2024
merged yesterday!
https://github.com/run-llama/llama_index/pull/12921
In Show HN: Route your prompts to the best LLMrun-llama
llama_index
Python2023–2024
run-llama / llama_index
llama_index
LlamaIndex is the document processing platform for AI
36Distinct people
44Mentions
0Explicit recommenders
52.9KGitHub stars
What to know before exploring
What it is
LlamaIndex is the document processing platform for AI
GitHub
Where it is used
No documented product use was verified in the last source check.
What people are saying
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Also in these discussions
- langchain-ai/langchain · linked in 6 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by month44 dated mentions
Observed mentions: 2023-01-08 10:29:26 UTC to 2024-05-22 22:27:49 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Jan 2023 | 2023-01-01 00:00:00 UTC | 2023-02-01 00:00:00 UTC | 16 | 5 | 11 |
| Feb 2023 | 2023-02-01 00:00:00 UTC | 2023-03-01 00:00:00 UTC | 2 | 0 | 2 |
| Mar 2023 | 2023-03-01 00:00:00 UTC | 2023-04-01 00:00:00 UTC | 6 | 0 | 6 |
| Apr 2023 | 2023-04-01 00:00:00 UTC | 2023-05-01 00:00:00 UTC | 4 | 2 | 2 |
| May 2023 | 2023-05-01 00:00:00 UTC | 2023-06-01 00:00:00 UTC | 3 | 1 | 2 |
| Jun 2023 | 2023-06-01 00:00:00 UTC | 2023-07-01 00:00:00 UTC | 1 | 0 | 1 |
| Jul 2023 | 2023-07-01 00:00:00 UTC | 2023-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2023 | 2023-08-01 00:00:00 UTC | 2023-09-01 00:00:00 UTC | 3 | 0 | 3 |
| Sep 2023 | 2023-09-01 00:00:00 UTC | 2023-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2023 | 2023-10-01 00:00:00 UTC | 2023-11-01 00:00:00 UTC | 1 | 1 | 0 |
| Nov 2023 | 2023-11-01 00:00:00 UTC | 2023-12-01 00:00:00 UTC | 1 | 0 | 1 |
| Dec 2023 | 2023-12-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 0 | 1 |
| Jan 2024 | 2024-01-01 00:00:00 UTC | 2024-02-01 00:00:00 UTC | 2 | 1 | 1 |
| Feb 2024 | 2024-02-01 00:00:00 UTC | 2024-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2024 | 2024-03-01 00:00:00 UTC | 2024-04-01 00:00:00 UTC | 1 | 1 | 0 |
| Apr 2024 | 2024-04-01 00:00:00 UTC | 2024-05-01 00:00:00 UTC | 2 | 1 | 1 |
| May 2024 | 2024-05-01 00:00:00 UTC | 2024-06-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
44 sourcesLlamaIndex: A data framework for your LLM applications
1 points · Open discussionFor anyone curious llamaindex's "prompt mixins", they're actually dead simple: https://github.com/run-llama/llama_index/blob/8a8324008764a7... - and maybe no longer supported.
I basically reinvented this wheel in ragdoll but made it more dynamic: https://github.com/bennyschmidt/ragdoll/blob/master/src/util...
In Show HN: Ragdoll Studio (fka Arthas.AI) is the FOSS alternative to character.aiLlamaIndex is a data framework for your LLM applications
3 points · Open discussionHow to verify that a snippet of Python code doesn't access protected members
2 points · Open discussionMistral Instruct does use a system prompt.
You can see the raw format here: https://www.promptingguide.ai/models/mistral-7b#chat-templat... and you can see how LllamaIndex uses it here (as an example): https://github.com/run-llama/llama_index/blob/1d861a9440cdc9...
In I made an app that runs Mistral 7B 0.2 LLM locally on iPhone ProsPartially agree.
Vector DBs are critical components in retrieval systems. What most applications need are retrieval systems, rather than building blocks of retrieval systems. That doesn't mean the building blocks are not important.
As someone working on vector DB, I find many users struggling in building their own retrieval systems with building blocks such as embedding service (openai,cohere), logic orchestration framework (langchain/llamaindex) and vector databases, some even with reranker models. Putting them together is not as easy as it looks. A fairly changeling system work. Letting alone quality tuning and devops.
The struggle is no surprise to me, as tech companies who are experts on this (google,meta) all have dedicated teams working on retrieval system alone, making tons of optimizations and develop a whole feedback loop of eval
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uating and improving the quality. Most developers don't get access to such resource.
No one size fits all. I think there shall exist a service that democratize AI-powered retrieval, in simple words the know-how of using embedding+vectordb and a bunch of tricks to achieve SOTA retrieval quality.
With this idea I built a Retrieval-as-a-service solution, and here is its demo:
https://github.com/milvus-io/bootcamp/blob/master/bootcamp/R...
Or using it in LlamaIndex:
https://github.com/run-llama/llama_index/blob/main/docs/exam...
Curious to learn your thoughts.
Dosu (https://dosu.dev) | Software Engineers | SF - Hybrid | Full Time
Maintaining you're code should be easier than writing it.
Checkout Dosu in action:
https://github.com/langchain-ai/langchain/issues/11371#issue...
https://github.com/run-llama/llama_index/issues/7684#issueco...
https://github.com/langchain-ai/langchain/issues/11359#issue...
jobs at dosu dot dev
In Ask HN: Who is hiring? (November 2023)Multi-Modal Retrieval: GPT text embedding and CLIP image embedding
2 points · Open discussionI'm sorry but from a _practical_ standpoint, it feels like mostly fluff. Someone was advertising today on a HN hiring post that they would create a basic chatbot for a specific set of documents for $15,000. This feels like the type of web page that person would use to confuse a client into thinking that was a fair price.
Practically speaking the starting point should be things like the APIs such as OpenAI or open source frameworks and software. For example, llama_index
https://github.com/jerryjliu/llama_index. You can use something like that or another GitHub repo built with it to create a customized chatbot application in a few minutes or a few days. (It should not take two weeks and $15,000).
It would be good to see something detailed that demonstrates an actual use case for fine tuning. Also, I don't believe that the academic tests ar
Read the rest
e appropriate in that case. If you really were dead set on avoiding a leading edge closed LLM, and doing actual fine-tuning, you would want a person to look at the outputs and judge them in their specific context such as handling customer support requests for that system.
For others in this thread, this algo is now publicly accessible in LlamaIndex at https://github.com/jerryjliu/llama_index/blob/e567e6a20cf89b...
In Chunking 2M files a day for code search using syntax treesUpdate: this algo is now publicly accessible in LlamaIndex at https://github.com/jerryjliu/llama_index/blob/e567e6a20cf89b...
In Chunking 2M files a day for code search using syntax treesGithub link https://github.com/jerryjliu/llama_index
In LlamaIndex raises $8.5M seed round, led by Greylock PartnersLlamaIndex (GPT Index): connect your LLM's with external data
2 points · Open discussionThere are a bunch of them now
https://github.com/jerryjliu/llama_index is one
In Train own custom dataset on GPT-4Showing the 15 most recent of 44 sources. Enable JavaScript to search and browse every indexed mention.