docs VS pydantic

It's a DNS proxy, like pi-hole, but it seems a lot more powerful than Pi-hole that is basically just a configured dnsmasq server to be user-friendly.

https://docs.pi-hole.net/

I highly recommend the documentation or this video (which also has a blog) that I followed.

Protip: Setup a DNS Sinkhole on your network and you can easily block Vizio and other devices from calling home to update. https://docs.pi-hole.net/

version: "3" # More info at https://github.com/pi-hole/docker-pi-hole/ and https://docs.pi-hole.net/ networks: dns_net: driver: bridge ipam: config: - subnet: 10.2.0.0/24 services: pihole: depends_on: [unbound] container_name: pihole image: pihole/pihole:latest hostname: pihole networks: dns_net: ipv4_address: 10.2.0.100 ports: - "5335:53/tcp" - "5335:53/udp" - "7000:80/tcp" environment: TZ: ${TZ} WEBPASSWORD: ${PWD} FTLCONF_LOCAL_IPV4: ${HOST_IP} # Set to server's LAN IP, used by web block modes. PIHOLE_DNS_: 10.2.0.200 # Upstream DNS server(s) for Pi-hole to forward queries to, separated by a semicolon DNSMASQ_LISTENING: all # "Listen on all interfaces, permit all origins" # Volumes store your data between container upgrades volumes: - /var/lib/docker/volumes/pihole/etc-pihole:/etc/pihole - /var/lib/docker/volumes/pihole/etc-dnsmasq.d:/etc/dnsmasq.d healthcheck: disable: true restart: unless-stopped unbound: # https://github.com/MatthewVance/unbound-docker container_name: unbound image: mvance/unbound:latest hostname: unbound networks: dns_net: ipv4_address: 10.2.0.200 ports: - "${HOST_IP}:53:53/udp" - "${HOST_IP}:53:53/tcp" healthcheck: disable: true restart: unless-stopped

Absolutely. Check out the Pi-Hole documentation here: https://docs.pi-hole.net/

See https://docs.pi-hole.net/

First, note the method prefix_allowed_tokens_fn. This method applies a Pydantic model to constrain/guide how the LLM generates tokens. Next, see how that constrain can be applied to txtai's LLM pipeline.

utype is a concise alternative of pydantic with simplified parameters and usages, supporting both sync/async functions and generators parsing, and capable of using native logic operators to define logical types like AND/OR/NOT, also provides custom type parsing by register mechanism that supports libraries like pydantic, attrs and dataclasses

I like some of the changes from v1 to v2. But then you have something like this [0] removed from the library without proper documentation or replacement, resulting in ugly workarounds in the link that wont' work properly.

[0]: https://github.com/pydantic/pydantic/discussions/6337

The easiest implementation I found was to use a PyDantic class for my target schema — and use that as a parameter for the method call to “ChatCompletion.create()”. Here’s a fragment of the GinAI Python classes used.

Also, FastStream uses Pydantic to parse input JSON-encoded data into Python objects, making it easy to work with structured data in your applications, so you can serialize your input messages just using type annotations.

Pydantic Validation: Leverage Pydantic's validation capabilities to serialize and validate incoming messages

Not sure if it is exactly related, but there is an open issue on Github for that exact message.

Well the performance increase is so huge because pydantic1 is really really slow. And for using rust, I'd have expected more tbh…

I've been benchmarking pydantic v2 against typedload (which I write) and despite the rust, it still manages to be slower than pure python in some benchmarks.

The ones on the website are still about comparing to v1 because v2 was not out yet at the time of the last release.

pydantic's author will refuse to benchmark any library that is faster (https://github.com/pydantic/pydantic/pull/3264 https://github.com/pydantic/pydantic/pull/1525 https://github.com/pydantic/pydantic/pull/1810) and keep boasting about amazing performances.

On pypy, v2 beta was really really really slow.