Add support for Google's Gemini and Anthropic's Claude models

Description

Currently, markitdown only supports OpenAI models for image captioning and content extraction. It would be valuable to add support for other leading multimodal LLMs, specifically:

1. Google's Gemini models (Pro and Ultra)
2. Anthropic's Claude models (Opus, Sonnet, and Haiku)

This would provide us with more flexibility and choice based on their preferences, API access, pricing, or specific model strengths.

Motivation

• Different users have access to different AI provider APIs
• Some users may prefer the strengths of a particular model family
• Pricing and rate limits vary between providers
• Organizations may have existing enterprise agreements with Google or Anthropic

Current implementation

Currently, _image_converter.py has hardcoded OpenAI-specific client API calls:

# Prepare the OpenAI API request
messages = [
    {
        "role": "user",
        "content": [
            {"type": "text", "text": prompt},
            {
                "type": "image_url",
                "image_url": {
                    "url": data_uri,
                },
            },
        ],
    }
]

# Call the OpenAI API
response = client.chat.completions.create(model=model, messages=messages)
return response.choices[0].message.content

Proposed solution

Create an abstraction layer for LLM providers that would:

1. Detect the client type (OpenAI, Google, or Anthropic)
2. Use the appropriate API format for each provider
3. Extract the response content consistently

This could be implemented either:

• As provider-specific adapter classes
• Through a simple detection mechanism based on client type
• Or potentially by leveraging [Semantic Kernel](https://github.com/microsoft/markitdown/issues/232) as suggested in a related issue

Related issues

• [Issue #232: Suggestion to use Semantic Kernel for different LLM providers](https://github.com/microsoft/markitdown/issues/232)
• [Issue #12: LLM Integration for image understanding](https://github.com/microsoft/markitdown/issues/12)

Start with _image_converter.py and trace the current OpenAI-specific image captioning and content-extraction flow. Review related issues #232 and #12 before choosing between provider adapters, client detection, or Semantic Kernel. Done means Gemini and Claude models are supported alongside OpenAI with consistent response extraction.