feat: 完整实现 NLP 三元组提取系统 + token budget 上下文分配

- 重写 extractor.go: 分句、17条 POS 模板、依存模板 + COO 链、ATT合并
- parser.go: 分句循环 + TransE 向量验证(h+r≈t)
- fallback.go: jieba POS 降级解析器
- bridge.go: nlp.Triple ↔ memory.Triple 转换
- pipeline.go: extractKeyTriples 改用 NLP 提取器, 删除5条旧前缀规则
- distill.go: docToTriples 改用 NLP 提取器
- reorgGraph: 语义相似度增强检测, 保持纯 LLM 决断
- Provider 接口加 MaxContextTokens() + 模型窗口映射表
- tokenbudget.go: 中文 token 估算器 + budget 分配(80%利用率)
- process.go/buildSystemPrompt: 按 token 预算截断 memory+timeline

internal/agent/api/provider.go

@@ -148,6 +148,47 @@ type Provider interface {
 	Name() string
 	Chat(ctx context.Context, req *CompletionRequest) (*CompletionResponse, error)
 	ChatStream(ctx context.Context, req *CompletionRequest) (<-chan StreamChunk, error)
+	MaxContextTokens() int
+}
+
+// ModelContextWindow 返回模型的最大上下文窗口（token 数）
+// 标称窗口 ≠ 有效窗口：接近满时注意力涣散，调用方应取 70-80% 为目标利用率
+func ModelContextWindow(model string) int {
+	model = strings.ToLower(model)
+	switch {
+	case strings.Contains(model, "deepseek-r1") || strings.Contains(model, "deepseek-chat"):
+		return 65536
+	case strings.Contains(model, "gpt-4") && (strings.Contains(model, "turbo") || strings.Contains(model, "mini") || strings.Contains(model, "omni")):
+		return 128000
+	case strings.Contains(model, "gpt-4"):
+		return 8192
+	case strings.Contains(model, "gpt-3.5"):
+		return 16384
+	case strings.Contains(model, "claude-3.5") || strings.Contains(model, "claude-3"):
+		return 200000
+	case strings.Contains(model, "claude"):
+		return 100000
+	case strings.Contains(model, "gemini-1.5") || strings.Contains(model, "gemini-2"):
+		return 1048576
+	case strings.Contains(model, "gemini"):
+		return 32768
+	case strings.Contains(model, "qwen"):
+		return 131072
+	case strings.Contains(model, "glm") || strings.Contains(model, "chatglm"):
+		return 131072
+	case strings.Contains(model, "llama-3"):
+		return 8192
+	case strings.Contains(model, "llama-2"):
+		return 4096
+	case strings.Contains(model, "mistral") || strings.Contains(model, "mixtral"):
+		return 32768
+	case strings.Contains(model, "yi-") || strings.Contains(model, "零一"):
+		return 200000
+	case strings.Contains(model, "moonshot") || strings.Contains(model, "kimi"):
+		return 131072
+	default:
+		return 32768
+	}
 }
 
 type BaseConfig struct {
@@ -409,6 +450,18 @@ func NewLuaAdaptedProvider(cfg BaseConfig, vm *luaVM.VM, adapter string) *LuaAda
 	}
 }
 
+func (p *OpenAIProvider) MaxContextTokens() int {
+	return ModelContextWindow(p.cfg.Model)
+}
+
+func (p *OllamaProvider) MaxContextTokens() int {
+	return ModelContextWindow(p.cfg.Model)
+}
+
+func (p *LuaAdaptedProvider) MaxContextTokens() int {
+	return ModelContextWindow(p.cfg.Model)
+}
+
 func (p *LuaAdaptedProvider) Name() string { return p.name }
 
 func (p *LuaAdaptedProvider) Chat(ctx context.Context, req *CompletionRequest) (*CompletionResponse, error) {