Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Support for read/write prompts and/or responses to a file (+ OpenAI Batching Support?) #255

Open
aowen14 opened this issue May 17, 2024 · 3 comments
Labels
Feature Request New feature or request

Comments

@aowen14
Copy link

aowen14 commented May 17, 2024

Description

I would like to be able to load and write Mirascope objects directly to a file for analysis and processing in a very simple way. Here are a few reasons:

Inference optimizations:

OpenAI has a batch API for inference that is 50% cheaper for all of its models. vLLM and many other perform better throughput under higher load and have support for offline inference. While you can wrap Mirascope in asynch calls inside or outside of the library, you might not want the client to handle this in all use cases. The context in many cases for better performance is usually held at the inference server, not the client (current load, priority of other calls, GPU configuration, recommended simultaneous calls, etc.)

Prompt/Prefix caching can be further optimized Ahead-of-Time instead of Just-in-Time as well.

Timing:

I might want these calls to be a part of a chron job anyways

Compute Re-use:

I might want to re-evaluate the series of prompts on different models, or I might want to resume with a different model inside a chain of calls.

Analysis:

These files can be easily imported to other systems for analysis and processing without official integrations.

@aowen14 aowen14 added the Feature Request New feature or request label May 17, 2024
@willbakst
Copy link
Contributor

Would something like this work?

from mirascope.openai import OpenAICall


class MyCall(OpenAICall):
    prompt_template = "Template {var}"

    var: str = ""


my_call = MyCall()
values = ["one", "two", "three"]
for value in values:
    messages = my_call.messages()
    with open(f"filename_{value}", "w") as f:
        f.write(messages)

I know there's details here that are missing, but wondering if this is sufficient or if you want this baked directly into the class? Something like pass a list of tuples where each tuple contains all the template variables and then you can call something like my_call.output_batch(list_of_tuples)?

@aowen14
Copy link
Author

aowen14 commented May 17, 2024

I was thinking more of a way that was baked into the class. Or a way to take in a series of mirascope Call objects and turn them into a string representation that can be sent to a file. There might be multiple ways that someone would want a Call to be represented in text. But ideally, the code is 1 line to use.

@willbakst
Copy link
Contributor

So there's one path I think where we figure out how to specifically handle OpenAI batch functionality and add support to classes like OpenAIClass for outputting the correct file shape for that. I don't love this as it feels too specific and it sounds like there are other use-cases for which better generalizing this would be better.

The issue I see is that trying to better generalize this may result in not being able to make it a single line without overcomplicating that line.

Could you provide a minimal real example of an expected output you might expect? I'd love to better understand the use-case, particularly wrt. one vs. multiple calls and how those outputs are similar / differ.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Feature Request New feature or request
Projects
None yet
Development

No branches or pull requests

2 participants