[feature request]support gpt-4vision models

[truebit]

DSPY currently only supports llm models, but openai library also supports vison language models. Could we also support gpt-4v requests?

[arnavsinghvi11]

Would be exciting! Feel free to add a custom client for it through following this documentation or mirroring existing LM client integrations.

The current integration of the OpenAI SDK in dsp/modules/databricks.py will be useful in adding the vision LM integration as well.

[truebit]

I have created a custom module, the sample code like below:

class GPT4V(dspy.Module):
    def __init__(self):
        super().__init__()
        self.generate_answer = dspy.ChainOfThought("question -> answer")

    def forward(self, question, *images):
        # context = self.retrieve(question).passages
        config = {'images': images}
        answer = self.generate_answer(question=question, config=config)
        return answer

Notice: We should use config to pass customized params to the custom model

[antoan]

@truebit

Hi, thanks for this.

I'm having trouble running this with:

import cv2
import numpy as np
import base64

#The current integration of the OpenAI SDK in dsp/modules/databricks.py will be useful in adding the vision LM integration as well.
#
# https://github.com/stanfordnlp/dspy/issues/459

def encode_image_to_string_from_path(image_path: str) -> str:
    import base64
    import cv2

    # Read the image from the given path
    image = cv2.imread(image_path)
    if image is None:
        raise ValueError("Image not found or the path is incorrect")

    # Encode the image to a JPEG format in memory
    _, buffer = cv2.imencode('.jpg', image)

    # Encode the buffer to a base64 string
    return base64.b64encode(buffer).decode("utf-8")

class GPT4V(dspy.Module):
    def __init__(self):
        super().__init__()
        self.generate_answer = dspy.ChainOfThought("question -> answer")

    def forward(self, question, *images):
        # context = self.retrieve(question).passages
        config = {'images': images}
        answer = self.generate_answer(question=question, config=config)
        return answer

# Set up the LM
gpt_vision = dspy.OpenAI(model='gpt-4-vision-preview', max_tokens=1800)
dspy.settings.configure(lm=gpt_vision)

# construct the module
gptv_mod = GPT4V()

# Call with input arguments.
img = encode_image_to_string_from_path("./chicken_cluster.jpg")

response = gptv_mod("What is the main subject of the image?", img)

response.completions.answer

With the following output:

Traceback (most recent call last):
  File "/home/antoan/dev/ai/dspy/main.py", line 47, in <module>
    response = gptv_mod("What is the main subject of the image?", img)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dspy/primitives/program.py", line 26, in __call__
    return self.forward(*args, **kwargs)
  File "/home/antoan/dev/ai/dspy/main.py", line 36, in forward
    answer = self.generate_answer(question=question, config=config)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dspy/predict/predict.py", line 49, in __call__
    return self.forward(**kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dspy/predict/chain_of_thought.py", line 59, in forward
    return super().forward(signature=signature, **kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dspy/predict/predict.py", line 91, in forward
    x, C = dsp.generate(template, **config)(x, stage=self.stage)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dsp/primitives/predict.py", line 77, in do_generate
    completions: list[dict[str, Any]] = generator(prompt, **kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dsp/modules/gpt3.py", line 184, in __call__
    response = self.request(prompt, **kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/backoff/_sync.py", line 105, in retry
    ret = target(*args, **kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dsp/modules/gpt3.py", line 150, in request
    return self.basic_request(prompt, **kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dsp/modules/gpt3.py", line 123, in basic_request
    response = chat_request(**kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dsp/modules/gpt3.py", line 271, in chat_request
    return v1_cached_gpt3_turbo_request_v2_wrapped(**kwargs).model_dump()
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dsp/modules/cache_utils.py", line 16, in wrapper
    return func(*args, **kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dsp/modules/gpt3.py", line 264, in v1_cached_gpt3_turbo_request_v2_wrapped
    return v1_cached_gpt3_turbo_request_v2(**kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/joblib/memory.py", line 655, in __call__
    return self._cached_call(args, kwargs)[0]
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/joblib/memory.py", line 598, in _cached_call
    out, metadata = self.call(*args, **kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/joblib/memory.py", line 856, in call
    output = self.func(*args, **kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/dsp/modules/gpt3.py", line 258, in v1_cached_gpt3_turbo_request_v2
    return openai.chat.completions.create(**kwargs)
  File "/home/antoan/dev/ai/dspy/.venv/lib/python3.10/site-packages/openai/_utils/_utils.py", line 275, in wrapper
    return func(*args, **kwargs)
TypeError: Completions.create() got an unexpected keyword argument 'images'

Would this not require creating a client wrapper to give it the input images, similar to the databricks integration as mentioned earlier here?

[jmanhype]

its because you have to make a change here https://github.com/stanfordnlp/dspy/pull/675

[rawwerks]

https://github.com/stanfordnlp/dspy/blob/56a0949ad285e0a3dd5649de58a6f5fb6f734a60/dsp/modules/gpt4vision.py#L106C1-L147C20 contains a potential solution