[Feature] Add multi-turn chat for Gemma 3, Mantis, and Pixtral

[reacher-z]

Summary

• add chat_inner for Gemma 3 while preserving complete user/assistant history and images in both Transformers and vLLM backends
• add chat_inner for Mantis using its native conversation template, with a separate Idefics chat-template path
• add chat_inner for Pixtral using native Mistral UserMessage, AssistantMessage, and SystemMessage requests
• keep each model's existing single-turn generate_inner path working through shared generation helpers
• reject images in assistant turns instead of silently constructing unsupported histories

This addresses another group of three models requested in #323. Their upstream documentation confirms the required capabilities:

• Gemma's official Transformers guide documents multimodal multi-turn prompt templates: https://ai.google.dev/gemma/docs/core/huggingface_inference#use_a_prompt_template_2
• Mantis's official model card includes a history-based multi-turn example: https://huggingface.co/TIGER-Lab/Mantis-8B-siglip-llama3
• Pixtral's official model card explicitly supports multi-turn conversations and multiple images: https://huggingface.co/mistralai/Pixtral-12B-2409

Validation

• python -m unittest -v tests/test_vlm_chat_inner_gemma_mantis_pixtral.py (8 tests passed)
• python -m py_compile vlmeval/vlm/gemma.py vlmeval/vlm/mantis.py vlmeval/vlm/pixtral.py tests/test_vlm_chat_inner_gemma_mantis_pixtral.py
• pre-commit run --files vlmeval/vlm/gemma.py vlmeval/vlm/mantis.py vlmeval/vlm/pixtral.py tests/test_vlm_chat_inner_gemma_mantis_pixtral.py

The tests exercise Gemma's Transformers and vLLM paths, Mantis's native and Idefics paths, Pixtral's Mistral request construction, image ordering, role preservation, and single-turn regression behavior without downloading model weights.

AI assistance

OpenAI Codex assisted with implementation and testing. I reviewed the model capability sources, code paths, and test outputs before submission.