mirror of
https://github.com/dogkeeper886/ollama37.git
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ef14fb5b26
This commit represents a complete rework after pulling the latest changes from official ollama/ollama repository and re-applying Tesla K80 compatibility patches. ## Key Changes ### CUDA Compute Capability 3.7 Support (Tesla K80) - Added sm_37 (compute 3.7) to CMAKE_CUDA_ARCHITECTURES in CMakeLists.txt - Updated CMakePresets.json to include compute 3.7 in "CUDA 11" preset - Using 37-virtual (PTX with JIT compilation) for maximum compatibility ### Legacy Toolchain Compatibility - **NVIDIA Driver**: 470.256.02 (last version supporting Kepler/K80) - **CUDA Version**: 11.4.4 (last CUDA 11.x supporting compute 3.7) - **GCC Version**: 10.5.0 (required by CUDA 11.4 host_config.h) ### CPU Architecture Trade-offs Due to GCC 10.5 limitation, sacrificed newer CPU optimizations: - Alderlake CPU variant enabled WITHOUT AVX_VNNI (requires GCC 11+) - Still supports: SSE4.2, AVX, F16C, AVX2, BMI2, FMA - Performance impact: ~3-7% on newer CPUs (acceptable for K80 compatibility) ### Build System Updates - Modified ml/backend/ggml/ggml/src/ggml-cuda/CMakeLists.txt for compute 3.7 - Added -Wno-deprecated-gpu-targets flag to suppress warnings - Updated ml/backend/ggml/ggml/src/CMakeLists.txt for Alderlake without AVX_VNNI ### Upstream Sync Merged latest llama.cpp changes including: - Enhanced KV cache management with ISWA and hybrid memory support - Improved multi-modal support (mtmd framework) - New model architectures (Gemma3, Llama4, Qwen3, etc.) - GPU backend improvements for CUDA, Metal, and ROCm - Updated quantization support and GGUF format handling ### Documentation - Updated CLAUDE.md with comprehensive build instructions - Documented toolchain constraints and CPU architecture trade-offs - Removed outdated CI/CD workflows (tesla-k80-*.yml) - Cleaned up temporary development artifacts ## Rationale This fork maintains Tesla K80 GPU support (compute 3.7) which was dropped in official Ollama due to legacy driver/CUDA requirements. The toolchain constraint creates a deadlock: - K80 → Driver 470 → CUDA 11.4 → GCC 10 → No AVX_VNNI We accept the loss of cutting-edge CPU optimizations to enable running modern LLMs on legacy but still capable Tesla K80 hardware (12GB VRAM per GPU). 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
77 lines
2.0 KiB
Go
77 lines
2.0 KiB
Go
package parsers
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import (
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"github.com/ollama/ollama/api"
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"github.com/ollama/ollama/harmony"
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)
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type Parser interface {
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// Init initializes the parser with tools and optional last message for chat prefill
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// Returns processed tools if the parser needs to modify them (e.g., harmony renames them)
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Init(tools []api.Tool, lastMessage *api.Message) []api.Tool
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// Add processes streamed content and returns parsed content, thinking, and tool calls
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// The done flag indicates if this is the last chunk (used for draining accumulators)
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Add(s string, done bool) (content string, thinking string, calls []api.ToolCall, err error)
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HasToolSupport() bool
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HasThinkingSupport() bool
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}
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type ParserConstructor func() Parser
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type ParserRegistry struct {
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constructors map[string]ParserConstructor
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}
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func (r *ParserRegistry) Register(name string, constructor ParserConstructor) {
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r.constructors[name] = constructor
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}
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var registry = ParserRegistry{
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constructors: make(map[string]ParserConstructor),
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}
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func Register(name string, constructor ParserConstructor) {
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registry.Register(name, constructor)
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}
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func ParserForName(name string) Parser {
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if parser, ok := registry.constructors[name]; ok {
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return parser()
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}
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switch name {
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case "qwen3-coder":
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parser := &Qwen3CoderParser{}
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return parser
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case "qwen3-vl-instruct":
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parser := &Qwen3VLParser{hasThinkingSupport: false}
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return parser
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case "qwen3-vl-thinking":
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parser := &Qwen3VLParser{hasThinkingSupport: true}
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return parser
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case "passthrough":
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return &PassthroughParser{}
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case "harmony":
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return harmony.NewHarmonyMessageHandler()
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default:
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return nil
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}
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}
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type PassthroughParser struct{}
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func (p *PassthroughParser) Init(tools []api.Tool, lastMessage *api.Message) []api.Tool {
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return tools // passthrough doesn't modify tools
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}
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func (p *PassthroughParser) Add(s string, done bool) (content string, thinking string, calls []api.ToolCall, err error) {
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return s, "", nil, nil
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}
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func (p *PassthroughParser) HasToolSupport() bool {
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return false
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}
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func (p *PassthroughParser) HasThinkingSupport() bool {
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return false
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}
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