# November 24: Support for direct LLM prompt, multi-turn image analysis, bug fixes

### New Features

* :bulb: Graphlit now supports multi-turn analysis of images with the `reviseImage` and `reviseEncodedImage` mutations.  You can provide an LLM prompt and either a URI or Base-64 encoded image and MIME type, along with an optional LLM specification.  This can be used for analyzing any image and having a multi-turn conversation with the LLM to revise the output from the LLM. ([Colab Notebook Example](https://colab.research.google.com/github/graphlit/graphlit-samples/blob/main/python/Notebook%20Examples/Graphlit_2024_11_24_Multi_turn_Analysis_of_Image.ipynb))
* :bulb: Graphlit now supports directly prompting an LLM with the `prompt` mutation, bypassing any RAG content retrieval, while providing an optional list of previous conversation messages.  This also accepts an optional LLM specification. ([Colab Notebook Example](https://colab.research.google.com/github/graphlit/graphlit-samples/blob/main/python/Notebook%20Examples/Graphlit_2024_11_24_Directly_Prompt_LLM_via_Conversation_Messages.ipynb))
* We have added support for the new Mistral Pixtral Large model, with `PIXTRAL_LARGE` model enum, which can be used with LLM completion or entity extraction LLM specifications.
* We have added support for the OpenAI 2024-11-20 version of GPT-4o, with `GPT4O_128K_20241120` model enum.
* :zap: We have added Microsoft Entra ID (fka Azure Active Directory) `clientId` and `clientSecret` properties to the `SharePointFeedPropertiesInput` type, which are now required when creating a SharePoint feed using user authentication with `refreshToken` property. ([Colab Notebook Example](https://colab.research.google.com/github/graphlit/graphlit-samples/blob/main/python/Notebook%20Examples/Graphlit_2024_11_25_SharePoint_to_RAG.ipynb))

### Bugs Fixed

* GPLA-3438: Not filtering on desktop presentation when scraping web pages
* GPLA-3340: Failed to parse invalid JSON from extracted PDF page
* GPLA-3427: Not formatting extracted tables properly from Sonnet 3.5


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://changelog.graphlit.dev/november-2024/november-24-support-for-direct-llm-prompt-multi-turn-image-analysis-bug-fixes.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
