Autumn-27
17c483dfa7
TestConnection 原本 MaxTokens=32：推理模型(deepseek-v4-pro)对一句 ping 也会先烧 ~2900 思考 token，永远在"思考阶段"就撞输出上限(finish=length)被截断——连接虽算通 但显示成"已中断/length/resume"一团糟。抬到 8192 让它把 OK 干净吐完(finish=stop)； 提示词也明确要求别思考。推理耗时不变(思考本就会发生),仅放行最终答案。
218 lines
7.3 KiB
Go
218 lines
7.3 KiB
Go
// Package agent wires real LLM-driven planner and work agents (on top of the
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// agent-core SDK) to the dual SQLite graph. See docs/ARTEX-架构设计.md
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// §4.3 (planner) and §4.4 (work agent).
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//
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// Provider configuration is read from the environment so the system runs with
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// any Anthropic- or OpenAI-format endpoint. If no key is configured, FromEnv
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// returns ok=false and the exploration engine stays idle (an LLM is required).
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package agent
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import (
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"context"
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"os"
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"strings"
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"time"
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"github.com/Autumn-27/norma/agentcore"
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"github.com/Autumn-27/norma/compaction"
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"github.com/Autumn-27/norma/llm"
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acperm "github.com/Autumn-27/norma/permission"
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)
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// Config describes the LLM backend resolved from the environment.
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type Config struct {
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Format llm.Format
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BaseURL string
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APIKey string
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Model string
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// Proxy routes all LLM requests through the given proxy URL (http/https/socks5).
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// Empty falls back to the standard *_PROXY environment variables.
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Proxy string
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// RatePerSecond / RatePerMinute cap the shared request rate across ALL agents
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// using the provider (0 = that window unlimited).
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RatePerSecond float64
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RatePerMinute float64
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// ContextWindowK is the model's context window in K tokens (user-configured),
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// used to size compaction thresholds. 0 = default; see CompactionWindow.
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ContextWindowK int
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// ReasoningEffort selects the thinking mode: "" = 默认(不发送思考参数);
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// "off" = 关闭(thinking.type=disabled); "low"/"medium"/"high"/"max" = 开启并设强度.
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// NewProvider derives the provider-specific request fields from it.
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ReasoningEffort string
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}
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// compaction window resolution bounds (in K tokens). Below the floor the
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// threshold math (window − summary reserve − buffer) would go non-positive and
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// compaction would fire every turn; above the cap it would never fire.
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const (
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defaultWindowK = 200 // unset → assume a 200K window (Claude default)
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minWindowK = 32 // floor so effectiveWindow stays comfortably positive
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maxWindowK = 1000 // cap at 1M tokens (user request)
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)
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// CompactionWindow returns the model context window in TOKENS for compaction
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// thresholds, resolved from the user-configured size (ContextWindowK). 0/unset →
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// a 200K default; otherwise clamped to [32K, 1M] so compaction stays effective.
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func (c Config) CompactionWindow() int {
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k := c.ContextWindowK
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if k <= 0 {
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k = defaultWindowK
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}
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if k < minWindowK {
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k = minWindowK
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}
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if k > maxWindowK {
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k = maxWindowK
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}
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return k * 1000
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}
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// compactionConfig builds the agent-core compaction config for a context window
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// in tokens. agentcore.NewSession wires the summarizer (same provider) when this
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// is set on Options.Compaction.
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func compactionConfig(windowTokens int) *compaction.Config {
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if windowTokens <= 0 {
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windowTokens = defaultWindowK * 1000
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}
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return &compaction.Config{ContextWindow: windowTokens}
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}
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// FromEnv resolves the LLM provider config:
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//
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// ARTEX_LLM_PROVIDER = anthropic|openai (default: inferred from keys)
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// ARTEX_LLM_MODEL = model id (default: per provider)
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// ARTEX_LLM_BASE_URL = endpoint (optional)
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// ARTEX_LLM_PROXY = proxy URL (optional; http/https/socks5)
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// ANTHROPIC_API_KEY / OPENAI_API_KEY = credentials
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func FromEnv() (Config, bool) {
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prov := os.Getenv("ARTEX_LLM_PROVIDER")
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anthKey := os.Getenv("ANTHROPIC_API_KEY")
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oaiKey := os.Getenv("OPENAI_API_KEY")
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if prov == "" {
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switch {
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case anthKey != "":
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prov = "anthropic"
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case oaiKey != "":
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prov = "openai"
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default:
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return Config{}, false
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}
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}
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c := Config{
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BaseURL: os.Getenv("ARTEX_LLM_BASE_URL"),
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Model: os.Getenv("ARTEX_LLM_MODEL"),
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Proxy: strings.TrimSpace(os.Getenv("ARTEX_LLM_PROXY")),
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}
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switch prov {
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case "openai":
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c.Format = llm.FormatOpenAI
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c.APIKey = oaiKey
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if c.Model == "" {
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c.Model = "gpt-4o"
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}
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default:
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c.Format = llm.FormatAnthropic
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c.APIKey = anthKey
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if c.Model == "" {
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c.Model = "claude-opus-4-8"
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}
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}
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if c.APIKey == "" {
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return Config{}, false
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}
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return c, true
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}
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// ConfigFrom builds a Config from UI-provided strings (provider defaults to
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// anthropic; model defaults per provider). Inputs are trimmed and the base URL
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// is normalized to the API base the provider expects (the provider appends the
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// endpoint path itself), so a full endpoint URL is tolerated.
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func ConfigFrom(provider, model, baseURL, apiKey, proxy string) Config {
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c := Config{
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Model: strings.TrimSpace(model),
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BaseURL: strings.TrimRight(strings.TrimSpace(baseURL), "/"),
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APIKey: strings.TrimSpace(apiKey),
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Proxy: strings.TrimSpace(proxy),
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}
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switch strings.TrimSpace(provider) {
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case "openai":
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c.Format = llm.FormatOpenAI
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// provider appends "/chat/completions"; tolerate a full endpoint URL.
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c.BaseURL = strings.TrimRight(strings.TrimSuffix(c.BaseURL, "/chat/completions"), "/")
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if c.Model == "" {
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c.Model = "gpt-4o"
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}
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default:
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c.Format = llm.FormatAnthropic
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// provider appends "/v1/messages".
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c.BaseURL = strings.TrimRight(strings.TrimSuffix(c.BaseURL, "/v1/messages"), "/")
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if c.Model == "" {
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c.Model = "claude-opus-4-8"
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}
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}
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return c
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}
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// Provider returns the short provider name ("anthropic"/"openai").
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func (c Config) Provider() string {
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if c.Format == llm.FormatOpenAI {
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return "openai"
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}
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return "anthropic"
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}
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// NewProvider builds an llm.Provider from the config. When a rate is set, the
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// limiter lives on the single provider instance — so planner + all workers +
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// main agent (which share this provider) are bounded by one shared rate limit.
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func (c Config) NewProvider() (llm.Provider, error) {
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lc := llm.Config{
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Format: c.Format,
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BaseURL: c.BaseURL,
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APIKey: c.APIKey,
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Model: c.Model,
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Proxy: c.Proxy,
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}
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// Derive the provider thinking params from the single UI selector:
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// "" → omit both (provider default); "off" → disable; else → enable + effort.
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switch c.ReasoningEffort {
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case "":
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// leave both empty → omitted from the request
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case "off":
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lc.ThinkingType = "disabled"
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default:
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lc.ThinkingType = "enabled"
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lc.ReasoningEffort = c.ReasoningEffort
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}
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if c.RatePerSecond > 0 || c.RatePerMinute > 0 {
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lc.RateLimit = &llm.RateLimit{PerSecond: c.RatePerSecond, PerMinute: c.RatePerMinute}
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}
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return llm.NewProvider(lc)
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}
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// TestConnection makes a minimal real completion to verify the provider/model/
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// endpoint/key actually work. Returns the round-trip latency.
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func TestConnection(ctx context.Context, c Config) (time.Duration, error) {
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prov, err := c.NewProvider()
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if err != nil {
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return 0, err
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}
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ctx, cancel := context.WithTimeout(ctx, 30*time.Second)
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defer cancel()
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start := time.Now()
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// MaxTokens 要给足：推理模型(如 deepseek-v4-pro)在给出答案前会先产出一大段
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// 思考(实测对一句 "ping" 也能烧 ~2900 token)。若只给 32,模型会一直卡在"思考阶段"
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// 就撞到输出上限(finish=length)、被截断,连接测试虽仍算通(err=nil)但显示成
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// "已中断/length/resume" 一团糟。给足预算让它把 OK 干净吐完(finish=stop)。
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// EscalateMaxTokens 保持 false:不因截断而抬额重试,避免 resume 循环空烧。
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_, err = agentcore.Run(ctx, agentcore.Options{
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Provider: prov,
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SystemPrompt: []string{"你是连接测试。直接输出两个字符 OK 即可，不要思考、不要解释、不要别的。"},
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PermissionMode: acperm.ModeBypass,
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MaxTurns: 1,
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MaxTokens: 8192,
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}, "ping")
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return time.Since(start), err
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}
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