- Add selectable parameters to format_for_raw_completion()
- inject_system: toggle agentic system prompt injection
- force_reasoning: toggle prompt seeding (thought tag)
- Update create_reasoning_prompt() convenience function

- Add REASONING_PREFIXES for Big 10 model families (Qwen, Llama3, DeepSeek, etc.)
- Add REASONING_STOP_TOKENS for stopping reasoning generation
- Add force_reasoning_prompt() to construct prompts ending with thought tags
- Add extract_reasoning() to parse reasoning from responses
- Add format_for_raw_completion() and create_reasoning_prompt() convenience functions
- This enables 'token hijacking' to force models to start with reasoning

- Enhanced flash attention status output in NvidiaBackend to always show availability
- Added debug output in chat completions endpoint for force-reasoning mode
- Shows CLI flag value, API param, reasoning action, and whether injection was done
- Displays the actual injected system prompt content when debug mode is enabled

Now accepts positional args: max_tokens, temperature, top_p, stop

Convert ChatMessage objects to dicts before applying chat template.

Now detects and uses the built-in chat template from GGUF files
loaded via llama-cpp-python before falling back to manual formatting.

Now detects GGUF model repos (e.g., unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF)
and lists available GGUF files before downloading.

Prefers Q4_K_M or Q4_K quantizations when available.

Fixed load_model and generate to be non-async methods (matching base class):
- load_model: changed from async def returning bool to def returning None
- generate: changed from async def to def (removed streaming support in sync version)
- Removed 'stream' parameter from generate since it's now sync
- chat: changed from async def to def
- generate_stream remains async def (correct for streaming)

Added:
- get_model_name()
- format_messages()
- cleanup()

These were required by the ModelBackend abstract base class.

Removed ~2050 lines of duplicate code:
- Pydantic models (ToolFunction, Tool, ChatMessage, etc.) - now from codai.pydantic
- ModelParserAdapter, ToolCallParser - now from codai.models
- NvidiaBackend, VulkanBackend - now from codai.backends
- All other duplicates removed

Now coderai properly imports all classes from codai modules.

Removed ~1500 lines of duplicate code that now exist in codai modules:
- ModelCapabilities, detect_model_capabilities (now in codai.models.capabilities)
- Cache functions (now in codai.models.cache)
- detect_available_backends, check_flash_attn_availability (now in codai.backends)
- ModelBackend abstract class (now in codai.backends.base)
- ModelManager, WhisperServerManager, MultiModelManager (now in codai.models.manager)
- QueueManager (now in codai.queue.manager)
- Utility functions (now in codai.models.utils)

The code now properly imports from codai modules instead of having inline duplicates.

- Added complete check_hf_chat_template with global_args support
- Added complete get_resolved_model_name
- Added complete get_model_family with more model families
- Added complete get_reasoning_stop_tokens for more model families
- Added complete get_reasoning_system_prompt
- Added set_global_args and get_global_args for configuration

- Move NvidiaBackend to codai/backends/cuda.py
- Move VulkanBackend to codai/backends/vulkan.py
- Move ModelManager, WhisperServerManager, MultiModelManager to codai/models/manager.py
- Move QueueManager to codai/queue/manager.py
- Add proper exports in codai/backends/__init__.py
- Update imports in coderai to use new modules
- Fix import paths for base class and cache functions

- Added --force-reasoning with choices: 'stop', 'inject', 'both' (default)
- Add model-family detection for reasoning stop tokens
- Get appropriate stop tokens for Qwen, DeepSeek, Llama3, Mistral, Gemma, Hermes/Yi
- Add system prompt injection for forcing reasoning on non-native models
- Add extract_reasoning_content() function to parsers for extracting thinking tags

- Added --force-reasoning argument to enable reasoning mode for models
  that support it (Qwen3, DeepSeek R1, etc.)
- Modified chat_completions endpoint to check both API parameter
  enable_thinking and CLI flag force_reasoning
- When either is true, injects agentic template to enable thinking

- Add enable_thinking parameter to ChatCompletionRequest
- When enable_thinking=True, inject agentic system prompt to force thinking/reasoning
- Uses AgenticTemplateManager to inject thought tags for supported models

- Add --force-reasoning CLI flag to force thinking mode for models like qwen3 coder
- Add check_force_reasoning() function to determine if reasoning should be forced
- Modify QwenParser to extract thinking/reasoning content instead of stripping it
- Add reasoning field to response message in non-streaming chat completions
- Prepend reasoning content to generated text in streaming responses
- Update OpenAIFormatter to include reasoning in response when available