canopy
starlette
canopy | starlette | |
---|---|---|
14 | 55 | |
883 | 9,541 | |
6.0% | 2.1% | |
9.8 | 9.2 | |
6 days ago | 2 days ago | |
Python | Python | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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.
canopy
- FLaNK AI Weekly for 29 April 2024
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How to choose the right type of database
Pinecone: A scalable vector database service that facilitates efficient similarity search in high-dimensional spaces. Ideal for building real-time applications in AI, such as personalized recommendation engines and content-based retrieval systems.
- Show HN: R2R – Open-source framework for production-grade RAG
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Using Stripe Docs in your RAG pipeline with LlamaIndex
In this post we’ll build a Python script that uses StripeDocs Reader, a loader on LlamaIndex, that creates vector embeddings of Stripe's documentation in Pinecone. This allows a user to ask questions about Stripe Docs to an LLM, in this case OpenAI, and receive a generated response.
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7 Vector Databases Every Developer Should Know!
Pinecone is a managed vector database service that simplifies the process of building and scaling vector search applications. It offers a simple API for embedding vector search into applications, providing accurate, scalable similarity search with minimal setup and maintenance.
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Using Vector Embeddings to Overengineer 404 pages
In case of AIMD, I am doing this all in-memory, but you could also do this in a database (e.g. Pinecone). It all depends on how much data you have and how much compute you have available.
- Pinecone: Build Knowledgeable AI
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How Modern SQL Databases Are Changing Web Development - #4 Into the AI Era
A RAG implementation's quality and performance highly depend on the similarity-based search of embeddings. The challenge arises from the fact that embeddings are usually high-dimensional vectors, and the knowledge base may have many documents. It's not surprising that the popularity of LLM catalyzed the development of specialized vector databases like Pinecone and Weaviate. However, SQL databases are also evolving to meet the new challenge.
- FLaNK Stack Weekly 11 Dec 2023
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Embracing Modern Python for Web Development
In the dynamic world of web development, Python has emerged as a dominant force, especially in backend development – the primary focus of this blog post. Although it's worth mentioning that there are ongoing efforts to use Python for the frontend as well, like Reflex (previously known as Pynecone, they presumably had to change their name because of Pinecone vector database), which even garnered support from Y Combinator. Samuel Colvin (creator of Pydantic) is also working on FastUI (he literally just released the first version in December 2023).
starlette
- Ask HN: What is your go-to stack for the web?
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Building Fast APIs with FastAPI: A Comprehensive Guide
Fast Execution: FastAPI is built on top of Starlette and Pydantic, making it one of the fastest Python frameworks for building APIs.
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Embracing Modern Python for Web Development
The framework's efficiency comes from its use of Starlette for building asynchronous web services and Pydantic for robust data validation and serialization, powered by Python's type hints. Pydantic has recently announced the official release of Pydantic V2 (June 2023), which is a ground-up rewrite that offers many new features and performance improvements, so make sure to be using that instead of V1.
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FastHttp for Python (64k requests/s)
Uvicorn + Starlette 8k requests/s
- Microdot "The impossibly small web framework for Python and MicroPython"
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An Introduction to ⚡FastAPI
Starlette documentation
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Writing a chat application in Django 4.2 using async StreamingHttpResponse
Same here, but without these weird utils it doesn't get any better.
I have 7 YoE with Django. Its great at so many things. You see some code, like middlewares, and immediately understand what's going on.
Now, we also have Starlette. The base of all new, fancy asgi libraries. Here's the base middleware class.
https://github.com/encode/starlette/blob/8d7a1cacfb3e1a30cbb...
In the last couple of years I heard 'we're running fastapi on production. Wanna join us?' so many times... but the reality is that it's still not suitable for prod. Who wants to work with a code like that if you have a readable, stable Django? I'm clueless.
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Deploying an ML model to Paperspace and creating an API
Set up Starlette, a tool we'll use to make async requests
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FastAPI middleware doesn't run while making request to websocket endpoint
I never used websockets in FastAPI so I wouldn't know how to guide you more, but Middleware in Websockets are 100% supported by Starlette : https://github.com/encode/starlette/issues/641
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Chat implementation
Websockets are the way but I would not recommend django as it's still not fully async. I would go for other tools.
What are some alternatives?
ragna - RAG orchestration framework ⛵️
Flask - The Python micro framework for building web applications.
tiger - Open Source LLM toolkit to build trustworthy LLM applications. TigerArmor (AI safety), TigerRAG (embedding, RAG), TigerTune (fine-tuning)
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
simple-pgvector-python - An Abstraction Using a similar API to Pinecone but implemented with pgvector python
uvicorn - An ASGI web server, for Python. 🦄
deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
mlx-examples - Examples in the MLX framework
starlite - Light, Flexible and Extensible ASGI API framework | Effortlessly Build Performant APIs [Moved to: https://github.com/litestar-org/litestar]
tonic_validate - Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.
quart - An async Python micro framework for building web applications.