Add Hugging Face inference operator

### Feature Summary

Add a Hugging Face operator to Texera so users can run pretrained models from the Hugging Face Hub directly inside workflows. This feature makes model inference a first-class workflow step, so users can apply text, image, video and audio models without writing code.

The operator would let users:

- Pick a Hugging Face task such as text generation, summarization, image classification, ASR, or VQA
- Browse/search available models for that task
- Provide the right input column or upload media when the task requires it via property panel
- Configure model-specific parameters like prompt, temperature, token limits, and output column name
- Produce a workflow output that can be chained into downstream operators

### Proposed Solution or Design

The operator should work as a guided, task-aware inference component rather than a generic API wrapper. The user picks a task first, then the UI only shows the fields that matter for that task.

A simple flow would look like this:

This is a screenshot of a selected text-generation task where the user asks a question via the input operator and the selected Hugging Face model based on the models list produces the answer as workflow output.

This is a screenshot of a selected image-classification task where the user provides an image in the property panel and the chosen model outputs JSON predictions (predicted breeds with confidence).

Here are some examples of task-based flows:
- Text generation: select a prompt column, choose a model, set max tokens and temperature, get generated text in a result column
- Summarization: select a text column, choose a summarization model, emit the summary
- Image classification: upload or reference an image, choose an image model, output labels or captions

A task-aware configuration layout could be:
1. Task
2. Model
3. Input source
4. Task-specific options
5. Result column

The design should include a few key behaviors:

- Model discovery and search from the Hugging Face Hub
- Backend proxying for Hugging Face API calls so the UI does not talk to Hugging Face directly
- API token support, with token fallback from environment or deployment config
- Caching of model and task metadata to reduce repeated remote calls
- Task-based validation so invalid combinations are rejected early, for example requiring an image upload for image-only tasks

### Affected Area

Workflow Engine (Amber), Workflow UI, Storage / Metadata, Deployment / Infrastructure

Start by mapping the Workflow Engine (Amber), Workflow UI, Storage / Metadata, and Deployment / Infrastructure areas named in the issue. Identify the existing operator, property-panel, metadata, and remote-service entry points before proposing a design. Done means a task-aware Hugging Face operator supports model discovery, validation, configuration, and chained workflow output across the requested task types.

Written by the indexing model from the issue text.