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Centralizes every LLM client build in chatd behind one resolver and makes all model calls behave the same, instead of preserving per-flow quirks. ## Why `chatd` built LLM clients in five places (standard turn, compaction override, quickgen, title override, advisor), each repeating config parsing, route resolution, client construction, and debug wrapping with slightly different behavior. An earlier iteration of this PR centralized construction but preserved every historical quirk behind purpose-specific spec constructors and policy flags. Review concluded the quirks themselves were the problem. ## What changed - `Server.resolveModelCall` (`modelcall.go`) is the single pipeline from a `modelCallSpec` to a ready client plus call metadata. Callers build spec literals inline; the only spec fields are data: model source (chat config, explicit config row, or fixed provider/model pair for computer use), requested reasoning effort, chatd-scoped routing, and build options. - Uniform behavior for every call: - Provider options are always derived. Whole-chat summaries, turn status labels, and chat-model compaction summaries previously sent none; they now follow the config like everything else. - `MaxOutputTokens` always defaults to 32k when the config leaves it unset. The compaction summary call nulls the cap after copying the template because it is non-streaming and the Anthropic SDK rejects non-streaming requests whose cap implies a completion over ten minutes. - Debug recording always wraps the client when chat debug is enabled, labeled with the resolved provider/model. The debug-rebuild paths (`manualTitleDebugSpec`, `quickgenDebugSpec`) are deleted; debug helpers now only create and finalize run records, since run association flows through the generate context, not the model. - Clients are always constructed with the configured model string and unmutated route, so AI Gateway validation sees the name exactly as configured. The resolved identity feeds metadata, logs, and debug labels only. - `resolvedModelCall.newCall` / `newObjectCall` are the only production constructors of `fantasy.Call` / `fantasy.ObjectCall`; object calls now carry the config's sampling parameters. - Net: -240 lines. ## Validation - Full `./coderd/x/chatd/...` suite green (PostgreSQL-backed). - Red-green toggles verified for the three key unifications (option derivation, token default, summary cap removal). - ARCHITECTURE.md: prose the refactor made stale is deleted; no new resolver documentation is added. > Mux acted on Mike's behalf for this PR.
171 lines
5.0 KiB
Go
171 lines
5.0 KiB
Go
package chatadvisor
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import (
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"context"
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"fmt"
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"strings"
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"time"
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"charm.land/fantasy"
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"golang.org/x/xerrors"
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stringutil "github.com/coder/coder/v2/coderd/util/strings"
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"github.com/coder/coder/v2/coderd/x/chatd/chatloop"
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"github.com/coder/coder/v2/coderd/x/chatd/chatretry"
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"github.com/coder/coder/v2/codersdk"
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)
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// RunAdvisorOptions carries optional streaming callbacks for a
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// single RunAdvisor invocation.
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type RunAdvisorOptions struct {
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OnAdviceDelta func(delta string)
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OnAdviceReset func()
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}
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// RunAdvisor executes a single, tool-less nested advisor call.
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func (rt *Runtime) RunAdvisor(
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ctx context.Context,
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question string,
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conversationSnapshot []fantasy.Message,
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opts *RunAdvisorOptions,
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) (AdvisorResult, error) {
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// Model, MaxUsesPerRun, and MaxOutputTokens are validated by NewRuntime.
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// Runtime fields are unexported so callers cannot bypass that.
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question = strings.TrimSpace(question)
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if question == "" {
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return AdvisorResult{}, xerrors.New("advisor question is required")
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}
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question = stringutil.Truncate(question, advisorQuestionMaxRunes)
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if !rt.tryAcquire() {
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return AdvisorResult{
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Type: ResultTypeLimitReached,
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Advice: LimitReachedAdvice,
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RemainingUses: 0,
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}, nil
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}
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// resetProviderOptionsForNestedCall mutates its argument; give it a
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// clone so the Runtime's stored options stay unchanged across calls.
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nestedCall := rt.cfg.CallTemplate
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nestedCall.ProviderOptions = cloneProviderOptions(rt.cfg.CallTemplate.ProviderOptions)
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resetProviderOptionsForNestedCall(nestedCall.ProviderOptions)
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assistantOpts := chatloop.GenerateAssistantOptions{
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Model: rt.cfg.Model,
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Messages: BuildAdvisorMessages(question, conversationSnapshot),
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CallTemplate: nestedCall,
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}
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if opts != nil && opts.OnAdviceDelta != nil {
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assistantOpts.PublishMessagePart = func(role codersdk.ChatMessageRole, part codersdk.ChatMessagePart) {
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if role != codersdk.ChatMessageRoleAssistant ||
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part.Type != codersdk.ChatMessagePartTypeText ||
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part.Text == "" {
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return
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}
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opts.OnAdviceDelta(part.Text)
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}
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}
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var outcome chatloop.AssistantOutcome
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if err := chatretry.Retry(ctx, func(retryCtx context.Context) error {
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var err error
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outcome, err = chatloop.GenerateAssistant(retryCtx, assistantOpts)
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return err
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}, func(int, error, chatretry.ClassifiedError, time.Duration) {
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if opts != nil && opts.OnAdviceReset != nil {
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opts.OnAdviceReset()
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}
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}); err != nil {
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// Refund the use so a transient provider failure does not
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// permanently exhaust the per-run advisor budget.
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rt.release()
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return AdvisorResult{
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Type: ResultTypeError,
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Error: err.Error(),
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RemainingUses: rt.RemainingUses(),
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}, nil
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}
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advice := extractAdvisorText(outcome.Step)
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if advice == "" {
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// Refund: the run did not produce advice, so the contract
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// "increments on every successful advisor call" treats this
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// as not consuming a use.
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rt.release()
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return AdvisorResult{
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Type: ResultTypeError,
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Error: fmt.Sprintf(
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"advisor produced no text output (%s)",
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describeTextlessOutcome(outcome),
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),
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RemainingUses: rt.RemainingUses(),
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}, nil
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}
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return AdvisorResult{
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Type: ResultTypeAdvice,
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Advice: advice,
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AdvisorModel: rt.cfg.Model.Provider() + "/" + rt.cfg.Model.Model(),
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RemainingUses: rt.RemainingUses(),
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}, nil
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}
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func extractAdvisorText(step chatloop.PersistedStep) string {
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parts := make([]string, 0, len(step.Content))
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for _, content := range step.Content {
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text, ok := fantasy.AsContentType[fantasy.TextContent](content)
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if !ok {
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continue
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}
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trimmed := strings.TrimSpace(text.Text)
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if trimmed == "" {
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continue
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}
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parts = append(parts, trimmed)
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}
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return strings.TrimSpace(strings.Join(parts, "\n\n"))
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}
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// describeTextlessOutcome summarizes a step that yielded no usable advice
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// text so the error pinpoints the failure mode. A reasoning-only step means
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// the model spent its turn deciding on an action (such as a tool call it
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// cannot perform in this tool-less run) without answering; a length finish
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// means the output was truncated before any text was produced.
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func describeTextlessOutcome(outcome chatloop.AssistantOutcome) string {
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var text, reasoning, toolCalls, other int
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for _, content := range outcome.Step.Content {
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switch content.(type) {
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case fantasy.TextContent:
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text++
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case fantasy.ReasoningContent:
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reasoning++
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case fantasy.ToolCallContent:
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toolCalls++
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default:
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other++
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}
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}
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if len(outcome.ToolCalls) > toolCalls {
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toolCalls = len(outcome.ToolCalls)
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}
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kinds := make([]string, 0, 4)
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appendKind := func(name string, count int) {
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if count > 0 {
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kinds = append(kinds, fmt.Sprintf("%s=%d", name, count))
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}
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}
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// Text parts can only reach here blank, so label them accordingly.
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appendKind("blank_text", text)
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appendKind("reasoning", reasoning)
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appendKind("tool_call", toolCalls)
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appendKind("other", other)
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summary := "none"
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if len(kinds) > 0 {
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summary = strings.Join(kinds, ", ")
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}
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return fmt.Sprintf("finish_reason=%s; parts: %s", outcome.FinishReason, summary)
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}
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