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I apologize, but the knowledge sources provided do not contain enough specific information to directly address your issue with ImageBlock and OpenAI in the latest version of LlamaIndex. However, I can provide some general information about using images with LlamaIndex that might be helpful:
LlamaIndex does support working with images in multi-modal contexts, particularly when using OpenAI's GPT-4 Vision model. The
OpenAI LLM abstraction in LlamaIndex can work with images, but the exact implementation might depend on the specific version and setup you're using.
For example, when using OpenAI's GPT-4 Vision model through LlamaIndex, you typically create a
ChatMessage object that includes both text and image blocks. Here's an example of how it's generally structured:
from llama_index.core.llms import (
ChatMessage,
ImageBlock,
TextBlock,
MessageRole,
)
msg = ChatMessage(
role=MessageRole.USER,
blocks=[
TextBlock(text="Describe the image"),
ImageBlock(url=image_url), # or ImageBlock(path=image_path)
],
)
response = openai_llm.chat(messages=[msg])If you're experiencing issues with the latest version, it might be worth checking the following:
- Ensure you're using the most up-to-date version of LlamaIndex and its dependencies.
- Verify that you're using the correct model that supports image inputs (e.g., "gpt-4-vision-preview").
- Check that your
OpenAI LLM instance is properly configured to handle multi-modal inputs.
If the problem persists, you might want to consult the
LlamaIndex documentation for the most current information or seek help in their community forums or GitHub issues page.
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Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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