RealtimeSTT
fastkafka
| RealtimeSTT | fastkafka | |
|---|---|---|
| 3 | 38 | |
| 1,105 | 38 | |
| - | - | |
| 8.0 | 8.7 | |
| 9 days ago | 6 months ago | |
| Python | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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.
RealtimeSTT
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Ask HN: Speech to text models, are they usable yet?
I have been using this with a lot of success for a while now: https://github.com/KoljaB/RealtimeSTT/tree/master , it works in real time, without any delays on an old Nvidia card.
I tried it with German & English without issues. It should also work for French but might need a bit of tweaking. The code is very straightforward, but depending on the context I'd recommend experimenting with the parameters that would suit you.
It's using a model called "Whisper" under the hood.
Have fun :)
- FLaNK Stack Weekly 16 October 2023
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Realtime Library for Python
Demo: Video Code: Github
fastkafka
- FLaNK Stack Weekly 16 October 2023
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FastStream: Python's framework for Efficient Message Queue Handling
Our journey with FastStream started when we needed to integrate our machine learning models into a customer's Apache Kafka environment. To streamline this process, we created FastKafka using AIOKafka, AsyncAPI, and asyncio. It was our first step in making message queue management easier.
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How we deprecated two successful projects and joined forces to create an even more successful one
After a short discussion, we concluded we were just too spoiled to use low-level libraries that were nothing more than just tiny wrappers around C++ libs and that we could just build our own. So, we shamelessly made one by reusing beloved paradigms from FastAPI and we shamelessly named it FastKafka. The point was to set the expectations right - you get pretty much what you would expect: function decorators for consumers and producers with type hints specifying Pydantic classes for JSON encoding/decoding, automatic message routing to Kafka brokers and documentation generation.
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Introducing FastStream: the easiest way to write microservices for Apache Kafka and RabbitMQ in Python
FastStream simplifies the process of writing producers and consumers for message queues, handling all the parsing, networking and documentation generation automatically. It is a new package based on the ideas and experiences gained from FastKafka and Propan. By joining our forces, we picked up the best from both packages and created a unified way to write services capable of processing streamed data regardless of the underlying protocol. We'll continue to maintain both packages, but new development will be in this project.
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FastStream: the easiest way to add Kafka and RabbitMQ support to FastAPI services
FastStream (https://github.com/airtai/faststream) is a new Python framework, born from Propan and FastKafka teams' collaboration (both are deprecated now). It extremely simplifies event-driven system development, handling all the parsing, networking, and documentation generation automatically. Now FastStream supports RabbitMQ and Kafka, but supported brokers are constantly growing (wait for NATS and Redis a bit). FastStream itself is a really great tool to build event-driven services. Also, it has a native FastAPI integration. Just create a StreamRouter (very close to APIRouter) and register event handlers the same with the regular HTTP-endpoints way:
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The new release of FastKafka supports Pydantic v2.0
Inspired by FastAPI, FastKafka uses the same paradigms for routing, validation, and documentation, making it easy to learn and integrate into your existing streaming data projects. Please check out the latest version adds supporting the newly released Pydantic v2.0, making it significantly faster. https://github.com/airtai/fastkafka
- Inspired by FastAPI, FastKafka uses the same paradigms for routing, validation, and documentation, making it easy to learn and integrate into your existing streaming data projects. The latest version adds support for newly released Pydantic v2.0, making it significantly faster.
- FastKafka – A Free Open-Source Python Library for Building Kafka-Based Services
What are some alternatives?
RealtimeTTS - Converts text to speech in realtime
cookiecutter-faststream - Cookiecutter template for FastStream apps
yolov7 - Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
inference - A fast, easy-to-use, production-ready inference server for computer vision supporting deployment of many popular model architectures and fine-tuned models.
datagen - Generate authentic looking mock data based on a SQL, JSON or Avro schema and produce to Kafka in JSON or Avro format.
JsonGenius - Get structured JSON data from any page.
aiokafka - asyncio client for kafka
Kouncil - Powerful dashboard for your Kafka. Monitor status, manage groups, topics, send messages and diagnose problems. All in one user friendly web dashboard.
Propan - Propan is a powerful and easy-to-use Python framework for building event-driven applications that interact with any MQ Broker
llmware - Unified framework for building enterprise RAG pipelines with small, specialized models
pythagora - Generate automated tests for your Node.js app via LLMs without developers having to write a single line of code.