localstack_ai
Containerized environment for experimenting with open source foundation models (by spara)
| localstack_ai | RAG_step-by-step | |
|---|---|---|
| 1 | 2 | |
| 6 | 4 | |
| - | - | |
| 7.3 | 6.8 | |
| about 2 months ago | 22 days ago | |
| Jupyter Notebook | Python | |
| MIT License | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
localstack_ai
Posts with mentions or reviews of localstack_ai.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-05.
-
RAG Step-by-Step: Open Source Edition
Instead of using OpenAI GPT3.5 and Pincone, I used the localstack_ai which is a containerized environment with Ollama, llama2, and PostgreSQL with pgvector.
RAG_step-by-step
Posts with mentions or reviews of RAG_step-by-step.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-05.
-
RAG with Web Search
Using web search with an LLM can help produce better search results and summaries. Be sure to check out the code long Github.
-
RAG Step-by-Step: Open Source Edition
Open-source foundation models are released literally every week. The barriers to running a model have decreased significantly, allowing you to play and learn about generative AI quickly and with minimal cost and effort. SaSS or open source, give RAG Step-by-Step a spin.