promptr

README

promptr

Typed prompts for Go. promptr makes a language model's output typed and reliable — the way BAML does, but as idiomatic, dependency-free Go.

Declare your prompts and their input/output types in a small .promptr schema; promptr compiles it to ordinary Go functions you call. Each generated function renders the prompt, calls a model through a tiny Provider interface you wire up (no vendor SDK in the core), and turns the loose reply into your typed value — retrying with the parse error fed back if the first attempt won't fit.

Its core is schema-aligned parsing: instead of forcing a model into a rigid JSON mode (which empirically degrades answer quality), you let it write naturally and a tolerant, schema-driven parser coerces the result into your Go types — recovering from prose preambles, Markdown fences, trailing commas, single quotes, fuzzy enum spellings, and truncated objects that real model output is full of.

.promptr schema ──promptr generate──▶ typed Go function
                                            │ renders prompt (schema baked in)
                                            ▼
                                    your Provider (any model)
                                            │ loose text reply
                                            ▼
                            coerce ──▶ typed value  (retry on misfit)

The pipeline in one example

// ticket.promptr
enum Severity { LOW HIGH CRITICAL }

class Ticket {
  title    string
  severity Severity
  tags     string[]
  due_days int?
}

client GPT4o { provider "openai" model "gpt-4o" }

function ExtractTicket(text: string) -> Ticket {
  client GPT4o
  prompt #"
    Extract a support ticket from the message.
    {{ ctx.output_schema }}      // compiler injects a schema description of Ticket
    Message: {{ text }}
  "#
}

promptr generate ./...     # -> ticket.promptr.go

ticket, err := ExtractTicket(ctx, provider, "my server is down!!")
// ticket.Severity == SeverityCRITICAL, even if the model wrote "critical priority"

The generated function bakes a human-readable schema of Ticket into the prompt (BAML's "show the model the shape you want" trick), then coerces the reply and re-asks on a parse miss — all in a few lines you can read.

coerce — the schema-aligned parser (usable on its own)

Don't want the DSL? Use the kernel directly on the structs you already have:

import "github.com/zkrebbekx/promptr/coerce"

ticket, err := coerce.Into[Ticket](modelText) // modelText: fences, prose and all

coerce.Into[T] digests input that encoding/json would reject outright:

the model emitted	encoding/json	coerce
```json { ... } ``` wrapped in prose	✗	✓ extracts the payload
{ title: 'x', tags: [1,2,], } (unquoted key, single quotes, trailing comma)	✗	✓
{"due_days": "7"} into an int field	✗	✓ coerces "7" → 7
{"amount": "$1,200.50"} into a float64	✗	✓ → 1200.5
{"severity": "high priority"} into an enum	✗	✓ fuzzy-matches → HIGH
{"title": "x", "tags": ["a", (truncated)	✗	✓ recovers what parsed

Nested structs, *T optionals, maps, snake/camel/case-insensitive keys, and a single value where a list was expected are all handled. Bare prose where a struct was expected returns a *coerce.Error — the signal the runtime retries on.

Discriminated unions

u := coerce.NewUnion(Search{}, Escalate{})
act, err := coerce.ResolveInto[Action](modelText, u) // best-fit by shape or "type" discriminator

Streaming

for p := range coerce.Stream[Ticket](tokenChan) {
    render(p.Value)        // a progressively-completed Ticket
    if p.Complete { break }
}

Type system

Beyond classes and enums, the schema language expresses the shapes real LLM tasks need — and each maps to idiomatic Go the coerce kernel already parses.

Unions — classify output into one of several typed shapes. Compiles to a sealed interface (sumx-style) plus a coerce resolver that picks the best-fit variant (by shape, or an explicit type/kind discriminator):

class Search   { query string }
class Escalate { reason string }
union Action = Search | Escalate          // or inline:  -> Search | Escalate

function Route(message: string) -> Action {
  client Default
  prompt #"Search or escalate? {{ ctx.output_schema }} Message: {{ message }}"#
}

act, err := Route(ctx, p, "I want a refund NOW")
switch a := act.(type) {            // exhaustive, type-safe
case Escalate: alertHuman(a.Reason)
case Search:   run(a.Query)
}

Maps — map<string, int> → map[string]int.

Field attributes tune the schema shown to the model (better prompt ⇒ better parse), the BAML "symbol tuning" idea:

class Profile {
  name  string @description("the person's full legal name") @alias("full_name")
  score int
}

@description annotates the field in the baked schema; @alias renames it on the wire — the model is shown full_name, and coerce binds that back to Name. (@assert/@check validation via valx is planned for a later release.)

Prompt templates

Prompts are more than string interpolation — the template engine supports control flow over your runtime values, so one function adapts its prompt to the input:

prompt #"
  Extract a support ticket.
  {{ if examples }}Here are examples of good tickets:
  {{ for e in examples }}- {{ e }}
  {{ end }}{{ end }}
  {{ ctx.output_schema }}
  Message: {{ text }}
"#

Supported inside {{ }}: {{ var }} (with dotted paths {{ user.name }}), {{ if cond }}…{{ else }}…{{ end }} (truthiness, not, and == "lit" / != "lit"), {{ for x in items }}…{{ end }}, and the compiler-injected {{ ctx.output_schema }}. Unknown names render empty rather than erroring, so a prompt never panics on real model context. The engine (promptr.Render) is usable directly, too.

Streaming & multimodal

Mark a function -> stream T and the generated function returns a channel of progressively-completed T values — the schema-aligned parser coerces each growing prefix, so you can render a partial object while tokens are still arriving:

function SummarizeArticle(article: string) -> stream Summary {
  client Default
  prompt #"Summarize it. {{ ctx.output_schema }} Article: {{ article }}"#
}

ch, err := SummarizeArticle(ctx, provider, text)
for part := range ch {           // promptr.Partial[Summary]
    if part.Err != nil { break }
    render(part.Value)           // headline fills in before the bullets do
    if part.Complete { break }
}

Any provider implementing the optional StreamProvider (openai, anthropic, fake) streams real tokens via SSE; others transparently fall back to a single complete value. promptr.ExtractStream[T] is usable directly, too.

Multimodal inputs. Give a parameter the type image, audio, pdf or file and it becomes a promptr.Part attached to the user message (not templated into the prompt text):

function CaptionImage(photo: image, hint: string) -> Summary { … }

cap, err := CaptionImage(ctx, provider, promptr.ImagePart("image/png", bytes), "be terse")

Providers map parts to their native content arrays (OpenAI image_url, Anthropic image blocks; inline bytes are base64 data-URLs, or pass a URL with promptr.ImageURL). See examples/stream.

Tool-calling & agents

Declare tools and hand them to a function with tools [...]. promptr runs the bounded model → tool → model loop for you and still returns a typed Go value at the end — single-shot extraction becomes a typed agent without giving up type safety:

tool GetWeather(city: string) -> Weather {
  description "Look up the current weather for a city."
}
tool SearchFlights(from: string, to: string) -> Flight[] {
  description "Find available flights between two cities."
}

function PlanTrip(goal: string) -> Itinerary {
  client Smart
  tools [GetWeather, SearchFlights]
  prompt #"Plan a trip for this goal. {{ ctx.output_schema }} Goal: {{ goal }}"#
}

The generated function takes a typed handlers struct — one func per tool, its argument a generated <Tool>Args struct coerced from the model's JSON:

itin, err := PlanTrip(ctx, provider, "see the northern lights", PlanTripTools{
    GetWeather: func(ctx context.Context, a GetWeatherArgs) (Weather, error) {
        return lookupWeather(a.City)
    },
    SearchFlights: func(ctx context.Context, a SearchFlightsArgs) ([]Flight, error) {
        return searchFlights(a.From, a.To)
    },
})

The loop dispatches each requested tool, feeds the result back, and repeats up to Options.MaxSteps (default 8) until the model answers — coerced into Itinerary. Unknown-tool and handler-error turns are fed back as text so the model can recover rather than aborting. promptr.RunTools[T] is usable directly, too. Works on providers implementing the optional ToolProvider interface (openai, anthropic, fake); others return a clear "does not support tool calls" error. See examples/agent.

Providers

The core imports no LLM SDK. A Provider is one method:

type Provider interface {
    Complete(ctx context.Context, messages []Message) (string, error)
}

Package	Backend
providers/openai	OpenAI Chat Completions — and anything compatible: Azure OpenAI, Groq, Together, OpenRouter, llama.cpp/vLLM/LM Studio (just set BaseURL)
providers/anthropic	Anthropic Messages API
providers/gemini	Google Gemini (Generative Language API)
providers/ollama	Local models via Ollama
providers/fake	Deterministic scripted replies for tests and the playground
providers/recorded	Replays hand-authored JSON cassettes — a VCR for deterministic, offline tests

Each is net/http only — import just the one you use. Wiring any other model is a dozen lines.

Client reliability policies

Declare retry/fallback/round-robin in the DSL; the compiler generates registry-resolving constructors that wrap your wired providers:

client Fast  { provider "openai"    model "gpt-4o-mini" }
client Smart { provider "anthropic" model "claude-opus-4-8" }
client Reliable {
  fallback [Smart, Fast]   // try Smart, fall over to Fast
  retry 3                  // each up to 3 times on transient error
}

reg := promptr.Registry{"Smart": anthropicClient, "Fast": openaiClient}
provider := ClientReliable(reg) // promptr.Retry(promptr.Fallback(...), 3, 0)
ticket, err := ExtractTicket(ctx, provider, msg)

promptr.Retry, promptr.Fallback, and promptr.RoundRobin are also usable directly — each is just a Provider that wraps other Providers.

Observability

A Middleware is just a Provider-to-Provider function, so you can wrap any provider without touching generated code. The built-in Collector records latency and token usage per call (exact when a provider implements UsageReporter, otherwise a chars/4 estimate):

col := &promptr.Collector{}
p := promptr.Chain(openaiClient, col.Collect) // outermost-first
_, _ = ExtractTicket(ctx, p, msg)

s := col.Stats()
log.Printf("%d calls, %d tokens, %s avg", s.Calls, s.TotalTokens(), s.AvgLatency())

Chain composes middlewares; the OpenTelemetry exporter is left to a future opt-in subpackage so the core stays dependency-free — Middleware is the seam it plugs into.

Tooling & editor support

promptr generate ./...   # compile .promptr -> Go (run under //go:generate)
promptr check ./...       # parse + validate without writing Go (CI-friendly)

promptr check reports unresolved types/clients, malformed unions and test blocks whose args don't match their function — the same checks the language server surfaces in your editor. Install cmd/promptr-lsp for live diagnostics and see editor/ for the tree-sitter grammar and editor wiring.

Deferred for a focused follow-up: promptr fmt (a canonical formatter needs the lexer to retain comments, currently dropped as trivia) and a live-execution test runner with typed assertions (best done by emitting Go tests from test blocks, which deserves its own provider-wiring design). providers/recorded is the deterministic substrate both will build on.

Install

# library
go get github.com/zkrebbekx/promptr

# CLI compiler
go install github.com/zkrebbekx/promptr/cmd/promptr@latest

Also published as a container image (ghcr.io/zkrebbekx/promptr) and a Homebrew cask.

Playground

A WebAssembly playground (DSL → Go, and paste-messy-output → repaired value) runs entirely client-side: playground/, deployed to GitHub Pages.

Develop

make test     # go test ./...
make race     # -race
make fuzz     # fuzz the tolerant parser
make lint
go generate ./...   # regenerate examples

License

MIT

Documentation

Overview

Package promptr is the runtime that generated .promptr code calls into: a minimal, provider-agnostic Provider interface plus the parse-with-repair loop that turns a model's loose reply into a typed Go value via the coerce kernel.

The compiler (cmd/promptr) turns each `function` in a .promptr file into a Go function whose body is a single call to Extract — so the generated code stays thin and readable, and all the retry/coercion logic lives here, tested once.

Index

• func Extract[T any](ctx context.Context, p Provider, prompt string, opts Options) (T, error)
• func ExtractStream[T any](ctx context.Context, p Provider, prompt string, opts Options) (<-chan Partial[T], error)
• func ExtractUnion[I any](ctx context.Context, p Provider, prompt string, opts Options, u *Union) (I, error)
• func Render(tmpl string, ctx map[string]any) (string, error)
• func RunTools[T any](ctx context.Context, p Provider, prompt string, tools []Tool, opts Options) (T, error)
• type Call
• type Collector
  • func (c *Collector) Calls() []Call
  • func (c *Collector) Collect(p Provider) Provider
  • func (c *Collector) CollectTools(p ToolProvider) Provider
  • func (c *Collector) Reset()
  • func (c *Collector) Stats() Stats
• type Message
• type Middleware
• type Options
• type Part
  • func AudioPart(mime string, data []byte) Part
  • func FilePart(mime string, data []byte) Part
  • func ImagePart(mime string, data []byte) Part
  • func ImageURL(url string) Part
  • func TextPart(s string) Part
• type PartKind
• type Partial
• type Provider
  • func Chain(p Provider, mws ...Middleware) Provider
  • func Fallback(providers ...Provider) Provider
  • func Retry(p Provider, attempts int, backoff time.Duration) Provider
  • func RoundRobin(providers ...Provider) Provider
• type Registry
  • func (r Registry) Get(name string) Provider
• type Reply
• type Stats
  • func (s Stats) AvgLatency() time.Duration
  • func (s Stats) TotalTokens() int
• type StreamProvider
• type TemplateError
  • func (e *TemplateError) Error() string
• type Tool
• type ToolCall
• type ToolDef
• type ToolProvider
• type Union
  • func NewUnion(samples ...any) *Union
• type UsageReporter

Functions

func Extract

func Extract[T any](ctx context.Context, p Provider, prompt string, opts Options) (T, error)

Extract runs prompt against the provider and coerces the reply into T. If the reply will not coerce, it re-asks — appending the unparseable reply and the parse error so the model can correct itself — up to Options.Attempts times.

This is the function every generated .promptr function calls.

func ExtractStream

func ExtractStream[T any](ctx context.Context, p Provider, prompt string, opts Options) (<-chan Partial[T], error)

ExtractStream runs prompt against the provider and emits a progressively completed T after each chunk, coercing the accumulated text with the tolerant kernel so callers can render partial state. If the provider implements StreamProvider the reply streams token-by-token; otherwise a single Complete call yields one final Partial. The returned channel closes when the model is done.

This is what a generated `-> stream T` function calls.

func ExtractUnion

func ExtractUnion[I any](ctx context.Context, p Provider, prompt string, opts Options, u *Union) (I, error)

ExtractUnion runs prompt against the provider and classifies the reply into one of the union's variants, returned as the sealed interface I. Like Extract it re-asks on a parse miss, feeding the error back, up to Options.Attempts.

This is what a generated function with a union return type calls.

func Render

func Render(tmpl string, ctx map[string]any) (string, error)

Render expands a prompt template against a context map and returns the finished prompt. It is the small, dependency-free template engine the compiler targets: generated functions call Render with the call's parameters (plus a "ctx" entry carrying the baked output-schema) so prompts can use control flow over runtime values.

Supported syntax (all inside {{ }}):

{{ name }}              value lookup, with dotted paths: {{ user.name }}
{{ ctx.output_schema }} the compiler-injected schema description
{{ if cond }}…{{ end }} conditional, with optional {{ else }}
{{ for x in items }}…{{ end }}   iterate a slice, binding x in the body

A condition is a path (truthy test), `not <path>`, or `<path> == "lit"` / `<path> != "lit"`. Lookups miss softly: an unknown name renders as empty rather than erroring, so a template can never panic on real model context. Render only returns an error for a structurally broken template (an unterminated {{ if }}/{{ for }}).

func RunTools

func RunTools[T any](ctx context.Context, p Provider, prompt string, tools []Tool, opts Options) (T, error)

RunTools runs prompt against a tool-capable provider, executing the Go tools the model asks for and feeding their results back, until the model returns a final answer that coerces into T. The loop is bounded by Options.MaxSteps (default 8).

An unknown tool name or a handler error is fed back to the model as a tool result so it can recover, rather than aborting the run. If the model's final answer will not coerce into T, the parse error is fed back for one repair re-ask (within the step budget), mirroring Extract.

This is what a generated tool-using function calls. The provider must implement ToolProvider; otherwise RunTools returns an error.

Types

type Call

type Call struct {
	Start    time.Time
	Duration time.Duration
	// PromptTokens / ReplyTokens are exact when the provider reports usage (see
	// UsageReporter); otherwise they are a chars/4 estimate.
	PromptTokens int
	ReplyTokens  int
	Estimated    bool // true when token counts are estimated, not reported
	Err          error
}

Call is one observed Provider.Complete invocation.

type Collector

type Collector struct {
	// contains filtered or unexported fields
}

Collector aggregates per-call latency and token usage across every Complete it wraps. It is safe for concurrent use. Wire it as middleware with Collect.

func (*Collector) Calls

func (c *Collector) Calls() []Call

Calls returns a snapshot copy of every recorded call.

func (*Collector) Collect

func (c *Collector) Collect(p Provider) Provider

Collect returns a Middleware that records every Complete into c.

func (*Collector) CollectTools

func (c *Collector) CollectTools(p ToolProvider) Provider

CollectTools wraps a ToolProvider so each CompleteTools call is recorded into c on the same latency/usage path as Collect. The returned Provider also implements ToolProvider, so it can be passed straight to RunTools while staying observable.

func (*Collector) Reset

func (c *Collector) Reset()

Reset clears all recorded calls.

func (*Collector) Stats

func (c *Collector) Stats() Stats

Stats rolls up the recorded calls into totals.

type Message

type Message struct {
	Role    string
	Content string
	// Parts, when non-empty, carries a multimodal message (text + images/etc).
	// Providers that support multimodal input map Parts to their content array;
	// otherwise Content is used. Text-only callers leave Parts nil.
	Parts []Part
	// ToolCalls, on an "assistant" turn, are the tool invocations the model
	// requested (see ToolProvider). ToolCallID, on a "tool" turn, correlates a
	// tool result back to the call that produced it. Both are zero for ordinary
	// text turns, so non-tool callers are unaffected.
	ToolCalls  []ToolCall
	ToolCallID string
}

Message is one turn in a chat-style exchange. Roles follow the usual "system" / "user" / "assistant" convention; a Provider maps them to whatever its backend expects.

type Middleware

type Middleware func(Provider) Provider

Middleware wraps a Provider to add cross-cutting behaviour — logging, metrics, caching, rate limiting — without touching the generated code. A Middleware is just a Provider-to-Provider function, so they compose by nesting and a wrapped provider is still a plain Provider the runtime can call.

type Options

type Options struct {
	// Attempts is the maximum number of model calls (default 2): the first
	// try plus repair re-asks when the reply will not coerce into T.
	Attempts int
	// System, when non-empty, is prepended as a system message.
	System string
	// UserParts, when non-empty, makes the user turn multimodal: the rendered
	// prompt becomes the leading text Part, followed by these (images, files…).
	UserParts []Part
	// MaxSteps bounds the tool-calling agent loop (default 8): the most
	// model⇄tool round-trips RunTools will take before giving up. Ignored by the
	// non-tool Extract paths.
	MaxSteps int
}

Options tunes an Extract call.

type Part

type Part struct {
	Kind PartKind
	Text string // PartText
	MIME string // media: e.g. "image/png", "application/pdf"
	Data []byte // inline media bytes (base64-encoded by the provider)
	URL  string // or a reference to remote media (used when Data is empty)
}

Part is one piece of a multimodal message: text, an image, audio, or a file. A media Part carries either inline Data (+MIME) or a URL reference. Providers map Parts to their own content-array formats; a provider that does not support a Part kind may ignore or reject it.

func AudioPart

func AudioPart(mime string, data []byte) Part

AudioPart builds an inline audio Part from bytes and a MIME type.

func FilePart

func FilePart(mime string, data []byte) Part

FilePart builds an inline document Part (e.g. a PDF) from bytes and a MIME.

func ImagePart

func ImagePart(mime string, data []byte) Part

ImagePart builds an inline image Part from raw bytes and a MIME type.

func ImageURL

func ImageURL(url string) Part

ImageURL builds an image Part that references a remote URL.

func TextPart

func TextPart(s string) Part

TextPart builds a text Part.

type PartKind

type PartKind uint8

PartKind tags a multimodal message Part.

const (
	// PartText is a plain-text span.
	PartText PartKind = iota
	// PartImage is an image (PNG/JPEG/…), by inline bytes or URL.
	PartImage
	// PartAudio is an audio clip.
	PartAudio
	// PartFile is a document (e.g. a PDF), by inline bytes or URL.
	PartFile
)

type Partial

type Partial[T any] struct {
	Value    T
	Complete bool
	Err      error
}

Partial carries a best-effort value parsed from an as-yet-incomplete stream. Complete flips to true once the payload parses cleanly. It mirrors coerce.Partial so generated code only imports promptr.

type Provider

type Provider interface {
	Complete(ctx context.Context, messages []Message) (string, error)
}

Provider is the single seam between promptr and a language model. Implement it with net/http against any chat API — the core imports no vendor SDK. A deterministic fake lives in providers/fake for tests and the playground.

func Chain

func Chain(p Provider, mws ...Middleware) Provider

Chain applies middlewares to p, outermost first: Chain(p, a, b) yields a(b(p)), so a sees each call before b does.

func Fallback

func Fallback(providers ...Provider) Provider

Fallback wraps providers so Complete tries each in order, returning the first success; if all fail, the last error is returned. Use it to fail over from a primary model to a backup.

func Retry

func Retry(p Provider, attempts int, backoff time.Duration) Provider

Retry wraps p so that Complete is retried up to attempts times on error, sleeping backoff between tries (respecting context cancellation). attempts < 1 is treated as 1. This is reliability against transient failures, distinct from Extract's parse-repair loop (which re-asks on unparseable but successful replies).

func RoundRobin

func RoundRobin(providers ...Provider) Provider

RoundRobin wraps providers so each Complete call goes to the next provider in rotation — load-spreading across keys or endpoints. It is safe for concurrent use.

type Registry

type Registry map[string]Provider

Registry maps the client names declared in a .promptr file to live Providers the caller has wired up. Generated client constructors resolve their provider references through a Registry, so the DSL stays free of credentials.

func (Registry) Get

func (r Registry) Get(name string) Provider

Get returns the Provider registered under name, or an error Provider that fails every call — so a missing wiring surfaces at call time with a clear message rather than a nil-pointer panic.

type Reply

type Reply struct {
	Text  string
	Calls []ToolCall
}

Reply is one turn from a ToolProvider: either a final answer in Text, or one or more tool Calls the model wants run before it can answer. When Calls is non-empty the loop dispatches them and asks again; otherwise Text is final.

type Stats

type Stats struct {
	Calls        int
	Errors       int
	PromptTokens int
	ReplyTokens  int
	TotalLatency time.Duration
}

Stats is a rollup of a Collector's recorded calls.

func (Stats) AvgLatency

func (s Stats) AvgLatency() time.Duration

AvgLatency is the mean Complete duration, or zero when no calls were recorded.

func (Stats) TotalTokens

func (s Stats) TotalTokens() int

TotalTokens is the sum of prompt and reply tokens across all calls.

type StreamProvider

type StreamProvider interface {
	Stream(ctx context.Context, messages []Message) (<-chan string, error)
}

StreamProvider is an optional capability a Provider may implement to deliver a reply incrementally. Stream returns a channel of text chunks (e.g. server-sent token deltas); the channel closes when the model is done. A Provider that does not implement this is still usable for streaming extraction — ExtractStream falls back to a single Complete call.

type TemplateError

type TemplateError struct{ Msg string }

TemplateError reports a structurally invalid template.

func (*TemplateError) Error

func (e *TemplateError) Error() string

type Tool

type Tool struct {
	Def    ToolDef
	Invoke func(ctx context.Context, argsJSON string) (resultJSON string, err error)
}

Tool binds a ToolDef to its Go implementation. Invoke receives the model's raw JSON arguments and returns the result as JSON to feed back into the conversation. Generated code builds these by wrapping a typed handler (decode args → call handler → marshal result); you can also construct them by hand.

type ToolCall

type ToolCall struct {
	ID        string
	Name      string
	Arguments string
}

ToolCall is the model's request to invoke a tool: an opaque ID the provider uses to correlate the result, the tool Name, and the raw JSON Arguments. The agent loop decodes Arguments tolerantly via the coerce kernel.

type ToolDef

type ToolDef struct {
	Name        string
	Description string
	Params      string // schema description of the JSON argument object
}

ToolDef describes a tool offered to the model: its name, a one-line description, and a human-readable schema of its argument object (built the same way output schemas are, so the model sees one consistent style). A ToolProvider marshals these into whatever its backend's tool/function-calling API expects.

type ToolProvider

type ToolProvider interface {
	CompleteTools(ctx context.Context, messages []Message, tools []ToolDef) (Reply, error)
}

ToolProvider is an optional capability a Provider may implement to support tool/function-calling. CompleteTools sends the conversation along with the available tool definitions and returns either the model's final text or the tool calls it wants executed. A Provider that does not implement this cannot run tool functions — RunTools returns a clear error.

type Union

type Union = coerce.Union

Union is a resolver over several candidate variant types — the building block generated code uses for a function that returns a union. It is an alias for coerce.Union so generated code only needs to import promptr.

func NewUnion

func NewUnion(samples ...any) *Union

NewUnion builds a Union resolver from zero values of each variant type.

type UsageReporter

type UsageReporter interface {
	LastUsage() (prompt, reply int)
}

UsageReporter is an optional interface a Provider may implement to expose the exact token counts of its most recent Complete call. The Collector uses it when present and falls back to a chars/4 estimate otherwise. It is consulted immediately after Complete returns, so an implementation should report the usage of that call.