feat(wasip2/llm): add support for llm

Signed-off-by: Rajat Jindal <[email protected]>

Author: rajatjindal

v2/examples/llm/.gitignore

@@ -0,0 +1,2 @@
+main.wasm
+.spin/

v2/examples/llm/go.mod

@@ -0,0 +1,12 @@
+module github.com/spinframework/spin-go-sdk/v2/examples/llm
+
+go 1.24.1
+
+require github.com/spinframework/spin-go-sdk/v2 v2.0.0
+
+require (
+	github.com/julienschmidt/httprouter v1.3.0 // indirect
+	go.bytecodealliance.org/cm v0.2.2 // indirect
+)
+
+replace github.com/spinframework/spin-go-sdk/v2 => ../../

v2/examples/llm/go.sum

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+github.com/julienschmidt/httprouter v1.3.0 h1:U0609e9tgbseu3rBINet9P48AI/D3oJs4dN7jwJOQ1U=
+github.com/julienschmidt/httprouter v1.3.0/go.mod h1:JR6WtHb+2LUe8TCKY3cZOxFyyO8IZAc4RVcycCCAKdM=
+go.bytecodealliance.org/cm v0.2.2 h1:M9iHS6qs884mbQbIjtLX1OifgyPG9DuMs2iwz8G4WQA=
+go.bytecodealliance.org/cm v0.2.2/go.mod h1:JD5vtVNZv7sBoQQkvBvAAVKJPhR/bqBH7yYXTItMfZI=

v2/examples/llm/main.go

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+package main
+
+import (
+	"fmt"
+	"net/http"
+
+	spinhttp "github.com/spinframework/spin-go-sdk/v2/http"
+	"github.com/spinframework/spin-go-sdk/v2/llm"
+)
+
+func init() {
+	spinhttp.Handle(func(w http.ResponseWriter, r *http.Request) {
+		result, err := llm.Infer("llama2-chat", "Tell me a joke", nil)
+		if err != nil {
+			http.Error(w, err.Error(), http.StatusInternalServerError)
+			return
+		}
+		fmt.Printf("Prompt tokens:    %d\n", result.Usage.PromptTokenCount)
+		fmt.Printf("Generated tokens: %d\n", result.Usage.GeneratedTokenCount)
+		fmt.Fprint(w, result.Text)
+		fmt.Fprintf(w, "\n\n")
+
+		embeddings, err := llm.GenerateEmbeddings("all-minilm-l6-v2", []string{"Hello world"})
+		if err != nil {
+			http.Error(w, err.Error(), http.StatusInternalServerError)
+			return
+		}
+		fmt.Printf("%d\n", len(embeddings.Embeddings[0]))
+		fmt.Printf("Prompt Tokens: %d\n", embeddings.Usage.PromptTokenCount)
+
+	})
+}
+
+func main() {}

v2/examples/llm/spin.toml

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+spin_manifest_version = 2
+
+[application]
+authors = ["Fermyon Engineering <[email protected]>"]
+description = "Simple example using the llm sdk."
+name = "llm-example"
+version = "0.1.0"
+
+[[trigger.http]]
+route = "/..."
+component = "llm"
+
+[component.llm]
+source = "main.wasm"
+allowed_outbound_hosts = []
+ai_models = ["llama2-chat", "all-minilm-l6-v2"]
+[component.llm.build]
+command = "tinygo build -target=wasip2 --wit-package $(go list -mod=readonly -m -f '{{.Dir}}' github.com/spinframework/spin-go-sdk/v2)/wit --wit-world http-trigger -gc=leaking -no-debug -o main.wasm main.go"
+watch = ["**/*.go", "go.mod"]

v2/llm/llm.go

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+package llm
+
+import (
+	"fmt"
+
+	"github.com/spinframework/spin-go-sdk/v2/internal/fermyon/spin/v2.0.0/llm"
+	"go.bytecodealliance.org/cm"
+)
+
+// The model use for inferencing
+const (
+	Llama2Chat        InferencingModel = "llama2-chat"
+	CodellamaInstruct InferencingModel = "codellama-instruct"
+)
+
+type InferencingParams struct {
+	// The maximum tokens that should be inferred.
+	//
+	// Note: the backing implementation may return less tokens.
+	MaxTokens uint32 `json:"max-tokens"`
+
+	// The amount the model should avoid repeating tokens.
+	RepeatPenalty float32 `json:"repeat-penalty"`
+
+	// The number of tokens the model should apply the repeat penalty to.
+	RepeatPenaltyLastNTokenCount uint32 `json:"repeat-penalty-last-n-token-count"`
+
+	// The randomness with which the next token is selected.
+	Temperature float32 `json:"temperature"`
+
+	// The number of possible next tokens the model will choose from.
+	TopK uint32 `json:"top-k"`
+
+	// The probability total of next tokens the model will choose from.
+	TopP float32 `json:"top-p"`
+}
+
+type InferencingResult struct {
+	// The text generated by the model
+	// TODO: this should be a stream
+	Text string `json:"text"`
+
+	// Usage information about the inferencing request
+	Usage InferencingUsage `json:"usage"`
+}
+
+// Usage information related to the inferencing result
+type InferencingUsage struct {
+	_ cm.HostLayout `json:"-"`
+	// Number of tokens in the prompt
+	PromptTokenCount uint32 `json:"prompt-token-count"`
+
+	// Number of tokens generated by the inferencing operation
+	GeneratedTokenCount uint32 `json:"generated-token-count"`
+}
+
+// A Large Language Model.
+type InferencingModel string
+
+// The model used for generating embeddings
+type EmbeddingModel string
+
+type EmbeddingsResult struct {
+	// Embeddings are the embeddings generated by the request.
+	Embeddings [][]float32
+	// Usage is usage related to an embeddings generation request.
+	Usage *EmbeddingsUsage
+}
+
+type EmbeddingsUsage struct {
+	// PromptTokenCount is number of tokens in the prompt.
+	PromptTokenCount int
+}
+
+// Infer performs inferencing using the provided model and prompt with the
+// given optional parameters.
+func Infer(model string, prompt string, params *InferencingParams) (InferencingResult, error) {
+	iparams := cm.None[llm.InferencingParams]()
+	if params != nil {
+		iparams = cm.Some(llm.InferencingParams{
+			MaxTokens:                    params.MaxTokens,
+			RepeatPenalty:                params.RepeatPenalty,
+			RepeatPenaltyLastNTokenCount: params.RepeatPenaltyLastNTokenCount,
+			Temperature:                  params.Temperature,
+			TopK:                         params.TopK,
+			TopP:                         params.TopP,
+		})
+	}
+
+	result := llm.Infer(llm.InferencingModel(model), prompt, iparams)
+	if result.IsErr() {
+		return InferencingResult{}, errorVariantToError(*result.Err())
+	}
+
+	return InferencingResult{
+		Text: result.OK().Text,
+		Usage: InferencingUsage{
+			PromptTokenCount:    result.OK().Usage.PromptTokenCount,
+			GeneratedTokenCount: result.OK().Usage.GeneratedTokenCount,
+		},
+	}, nil
+}
+
+// GenerateEmbeddings generates the embeddings for the supplied list of text.
+func GenerateEmbeddings(model EmbeddingModel, text []string) (*EmbeddingsResult, error) {
+	result := llm.GenerateEmbeddings(llm.EmbeddingModel(model), cm.ToList(text))
+	if result.IsErr() {
+		return &EmbeddingsResult{}, errorVariantToError(*result.Err())
+	}
+
+	embeddings := [][]float32{}
+	for _, l := range result.OK().Embeddings.Slice() {
+		embeddings = append(embeddings, l.Slice())
+	}
+
+	return &EmbeddingsResult{
+		Embeddings: embeddings,
+		Usage: &EmbeddingsUsage{
+			PromptTokenCount: int(result.OK().Usage.PromptTokenCount),
+		},
+	}, nil
+}
+
+func errorVariantToError(err llm.Error) error {
+	switch {
+	case llm.ErrorModelNotSupported() == err:
+		return fmt.Errorf("model not supported")
+	case err.RuntimeError() != nil:
+		return fmt.Errorf("runtime error %s", *err.RuntimeError())
+	case err.InvalidInput() != nil:
+		return fmt.Errorf("invalid input %s", *err.InvalidInput())
+	default:
+		return fmt.Errorf("no error provided by host implementation")
+	}
+}