libsql VS litellm

> PS: I've got nothing against Turso, or libSQL. In fact I spent the last year perusing their virtual WAL API. The problem is that I found no documentation, nor any useful open source implementations of it. If there any I'd be very interested. So, thus far, I also don't have anything that drives towards libSQL.

Hey, this is v and I am an engineer at Turso. We do have some documentation and an example implementation of Virtual WAL

docs: https://github.com/tursodatabase/libsql/blob/ef44612/libsql-...

example: https://github.com/tursodatabase/libsql/blob/ef44612/libsql-...

for an open source implementation, you may check how Bottomless works. Bottomless is another project which does back up like litestream and it internally implements a Virtual WAL.

Bottomless - https://github.com/tursodatabase/libsql/tree/main/bottomless

I am sure we can improve our docs, make it more discover-able and easy to find. I am open to feedback and suggestions!

Astro DB is powered by LibSQL, an open source fork of SQLite that was created by Turso. You can use Astro DB's drop-in database to build features like blogs, comment functionality, forums, feedback systems, and user authentication.

sqlite already had an active community fork started by Turso called libsql. They are fixing longstanding API gaps the upstream team isn’t interested in supporting. For example, they added a native write-ahead log API, so you can plug directly into the WAL for streaming replication. This is possible-ish with upstream sqlite + LiteFs but litefs has to implement a whole FUSE file system and can’t run on Mac for that reason.

It’s more risky to run libsql because new features mean new bugs, but it seems worth it to me.

Libsql: https://github.com/tursodatabase/libsql

A bit of a tangent but for those who’d like to use SQLite for a backend, running it as a separate daemon could be an interesting choice, which would also remove there need of Cgo for the build and maybe make things like separate background job processes easier to accomplish. See [1], [2].

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1: https://github.com/tursodatabase/libsql/tree/main/libsql-ser...

2: https://news.ycombinator.com/item?id=38602175

https://www.sqlite.org/copyright.html

To summarize, instead of using one of the OSS licenses, the copyright holders simply declare the source to be in the public domain. In order to preserve that status they don't accept patches unless you submit some signed document that you agree with that.

To make things more complicated, they also use their a relatively niche version management system instead of git. Which would complicate making contributions (if they accepted them).

There's a popular fork that fixes all of these issues: https://github.com/libsql/libsql It is MIT licensed, on Github, and open for contributions.

Kind of a weird legal situation for a popular project like this that so many people depend on to have. Not judging; but it is odd. Seems like a lot of wasted efforts between users, would be contributors, and the people that forked this thing to address all that.

You could try making feature requests for https://github.com/libsql/libsql , which is a community fork of SQLite that aims to speed-up the development of long-wanted features.

For a comprehensive view, check out the issues list for libSQL core and sqld. But mostly, I want libSQL to be a home for all builders who believe there is room to take a lean, mean, and SQLite-compatible embedded database to new heights. I’d love to see your contribution!

There are a few libs that already abstract this away, for example:

- https://github.com/BerriAI/litellm

- https://jxnl.github.io/instructor/

- langchain

It's not hard for me to imagine a future where there is something like the CNCF for AI models, tools, and infra.

Hey, are you just looking for litellm - https://github.com/BerriAI/litellm

context - i'm the repo maintainer

It should be possible using LiteLLM and a patch or a proxy.

https://github.com/BerriAI/litellm

This article will demonstrate how txtai can integrate with llama.cpp, LiteLLM and custom generation methods. For custom generation, we'll show how to run inference with a Mamba model.

I use this with ollama and works perfectly https://github.com/BerriAI/litellm

Another abstraction layer library is: https://github.com/BerriAI/litellm

For me the killer feature of a library like this would be if it implemented function calling. Even if it was for a very restricted grammar - like the traditional ReAct prompt:

  Solve a question answering task with interleaving Thought, Action, Observation   usteps. Thought can reason about the current situation, and Action can be three types:

Welcome to Open Interpreter. ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── ▌ OpenAI API key not found To use GPT-4 (recommended) please provide an OpenAI API key. To use Code-Llama (free but less capable) press enter. ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── OpenAI API key: [the API Key I inputed] Tip: To save this key for later, run export OPENAI_API_KEY=your_api_key on Mac/Linux or setx OPENAI_API_KEY your_api_key on Windows. ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── ▌ Model set to GPT-4 Open Interpreter will require approval before running code. Use interpreter -y to bypass this. Press CTRL-C to exit. > export OPENAI_API_KEY=your_api_key Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True'. Traceback (most recent call last): File "/Library/Frameworks/Python.framework/Versions/3.12/bin/interpreter", line 8, in sys.exit(cli()) ^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/core.py", line 22, in cli cli(self) File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/cli/cli.py", line 254, in cli interpreter.chat() File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/core.py", line 76, in chat for _ in self._streaming_chat(message=message, display=display): File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/core.py", line 97, in _streaming_chat yield from terminal_interface(self, message) File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/terminal_interface/terminal_interface.py", line 62, in terminal_interface for chunk in interpreter.chat(message, display=False, stream=True): File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/core.py", line 105, in _streaming_chat yield from self._respond() File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/core.py", line 131, in _respond yield from respond(self) File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/respond.py", line 61, in respond for chunk in interpreter._llm(messages_for_llm): File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/llm/setup_openai_coding_llm.py", line 94, in coding_llm response = litellm.completion(**params) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/utils.py", line 792, in wrapper raise e File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/utils.py", line 751, in wrapper result = original_function(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/timeout.py", line 53, in wrapper result = future.result(timeout=local_timeout_duration) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 456, in result return self.__get_result() ^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result raise self._exception File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/timeout.py", line 42, in async_func return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/main.py", line 1183, in completion raise exception_type( ^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/utils.py", line 2959, in exception_type raise e File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/utils.py", line 2355, in exception_type raise original_exception File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/main.py", line 441, in completion raise e File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/main.py", line 423, in completion response = openai.ChatCompletion.create( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/openai/api_resources/chat_completion.py", line 25, in create return super().create(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/openai/api_resources/abstract/engine_api_resource.py", line 155, in create response, _, api_key = requestor.request( ^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/openai/api_requestor.py", line 299, in request resp, got_stream = self._interpret_response(result, stream) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/openai/api_requestor.py", line 710, in _interpret_response self._interpret_response_line( File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/openai/api_requestor.py", line 775, in _interpret_response_line raise self.handle_error_response( openai.error.InvalidRequestError: The model `gpt-4` does not exist or you do not have access to it. Learn more: https://help.openai.com/en/articles/7102672-how-can-i-access-gpt-4.