Detect chat template from model and use appropriate formatting - avoid Jinja errors by using manual formatting when template detection fails

Modify _try_load_model() to catch TypeError when quantization arguments
are not supported by the model class. When this happens, the method now:
1. Warns the user about unsupported quantization
2. Retries loading the model without quantization arguments
3. Returns the model successfully if loading works

This fixes issues with models like Qwen3.5 that don't support
bitsandbytes quantization.

- Wrap generate() with try-except to catch CUDA OOM errors
- On OOM: clear CUDA cache, retry with half tokens, return graceful error if still failing
- Wrap generate_stream() thread with error handling using shared variable
- Yield error messages to client instead of crashing the process
- Allows server to continue running after generation OOM

This new parameter allows users to specify the exact percentage of GPU VRAM
to use, overriding the offload-strategy. When specified, the model will:
1. Use up to max-gpu-percent of VRAM
2. Offload remaining weights to CPU RAM (--ram)
3. Overflow to disk (--offload-dir) if RAM exhausted
4. Automatically fallback in 5% steps if OOM occurs

Example usage for RTX 3090 with Qwen3.5-35B-A3B:
  coderai --model Qwen/Qwen3.5-35B-A3B --max-gpu-percent 50 --ram 64

This ensures MoE models with high VRAM requirements during generation
can run without OOM by using CPU RAM as the primary offload target.

Add session management, readline history, context compression, --ctx, --micro flags, and context counter in prompt

Fix streaming display in coder CLI - use iter_lines for immediate output, remove threading timer, simplify tool parsing