function-openai/fn.go at main · upbound/function-openai · GitHub

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Licensed under the Apache License, Version 2.0 (the "License");

you may not use this file except in compliance with the License.

You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software

distributed under the License is distributed on an "AS IS" BASIS,

WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

See the License for the specific language governing permissions and

limitations under the License.

package main

import (

"context"

"encoding/json"

"html/template"

"strings"

"github.com/tidwall/gjson"

"github.com/tidwall/sjson"

"github.com/tmc/langchaingo/agents"

"github.com/tmc/langchaingo/chains"

openaillm "github.com/tmc/langchaingo/llms/openai"

"github.com/tmc/langchaingo/tools"

"google.golang.org/protobuf/encoding/protojson"

"google.golang.org/protobuf/types/known/structpb"

"sigs.k8s.io/yaml"

"github.com/crossplane/function-sdk-go/errors"

"github.com/crossplane/function-sdk-go/logging"

fnv1 "github.com/crossplane/function-sdk-go/proto/v1"

"github.com/crossplane/function-sdk-go/request"

"github.com/crossplane/function-sdk-go/resource"

"github.com/crossplane/function-sdk-go/response"

"github.com/upbound/function-openai/input/v1alpha1"

"github.com/upbound/function-openai/internal/tool"

)

const (

credName = "gpt"

credKey = "OPENAI_API_KEY"

credBaseURLKey = "OPENAI_BASE_URL"

credModelKey = "OPENAI_MODEL"

defaultModel = "gpt-4"

)

// Variables used to form the prompt.

type Variables struct {

// Observed composite resource, as a YAML manifest.

Composite string

// Observed composed resources, as a stream of YAML manifests.

Composed string

}

// Function asks GPT to compose resources.

type Function struct {

fnv1.UnimplementedFunctionRunnerServiceServer

ai agentInvoker

log logging.Logger

}

// agentInvoker is a consumer interface for working with agents. Notably this

// is helpful for writing tests that mock the agent invocations.

type agentInvoker interface {

Invoke(ctx context.Context, key, system, prompt, baseURL, modelName string) (string, error)

}

// Option modifies the underlying Function.

type Option func(*Function)

// WithLogger overrides the default logger.

func WithLogger(log logging.Logger) Option {

return func(f *Function) {

f.log = log

}

// NewFunction creates a new function powered by GPT.

func NewFunction(opts ...Option) *Function {

f := &Function{

log: logging.NewNopLogger(),

}

for _, o := range opts {

o(f)

}

f.ai = &agent{

log: f.log,

res: tool.NewResolver(tool.WithLogger(f.log)),

}

return f

}

// RunFunction runs the Function.

func (f *Function) RunFunction(ctx context.Context, req *fnv1.RunFunctionRequest) (*fnv1.RunFunctionResponse, error) {

log := f.log.WithValues("tag", req.GetMeta().GetTag())

log.Info("Running function", "tag", req.GetMeta().GetTag())

rsp := response.To(req, response.DefaultTTL)

if f.shouldIgnore(req) {

response.ConditionTrue(rsp, "FunctionSuccess", "Success").TargetCompositeAndClaim()

response.Normal(rsp, "received an ignored resource, skipping")

return rsp, nil

}

in := &v1alpha1.Prompt{}

if err := request.GetInput(req, in); err != nil {

response.Fatal(rsp, errors.Wrapf(err, "cannot get Function input from %T", req))

return rsp, err

}

c, err := request.GetCredentials(req, credName)

if err != nil {

response.Fatal(rsp, errors.Wrapf(err, "cannot get OPENAI_API_KEY from credential %q", credName))

return rsp, err

}

if c.Type != resource.CredentialsTypeData {

response.Fatal(rsp, errors.Errorf("expected credential %q to be %q, got %q", credName, resource.CredentialsTypeData, c.Type))

return rsp, err

}

b, ok := c.Data[credKey]

if !ok {

response.Fatal(rsp, errors.Errorf("credential %q is missing required key %q", credName, credKey))

return rsp, err

}

// TODO(negz): Where the heck is the newline at the end of this key

// coming from? Bug in crossplane render?

key := strings.Trim(string(b), "\n")

// Extract optional base URL from credentials

var baseURL string

if baseURLBytes, ok := c.Data[credBaseURLKey]; ok {

baseURL = strings.Trim(string(baseURLBytes), "\n")

}

// Extract optional model from credentials, default to gpt-4

model := defaultModel

if modelBytes, ok := c.Data[credModelKey]; ok {

model = strings.Trim(string(modelBytes), "\n")

}

d := pipelineDetails{

req: req,

rsp: rsp,

in: in,

cred: key,

baseURL: baseURL,

model: model,

}

// If we're in a composition pipeline we want to do things with the

// composed resources.

if inCompositionPipeline(req) {

return f.compositionPipeline(ctx, log, d)

}

// Handle operation pipeline separately.

return f.operationPipeline(ctx, log, d)

}

// CompositeToYAML returns the XR as YAML.

func CompositeToYAML(xr *fnv1.Resource) (string, error) {

j, err := protojson.Marshal(xr.GetResource())

if err != nil {

return "", errors.Wrap(err, "cannot convert XR to JSON")

}

y, err := yaml.JSONToYAML(j)

return string(y), errors.Wrap(err, "cannot convert XR to YAML")

}

// ComposedToYAML returns the supplied composed resources as a YAML stream. The

// resources are annotated with their upbound.io/name annotations.

func ComposedToYAML(cds map[string]*fnv1.Resource) (string, error) {

composed := &strings.Builder{}

for name, ocd := range cds {

jocd, err := protojson.Marshal(ocd.GetResource())

if err != nil {

return "", errors.Wrap(err, "cannot convert composed resource to JSON")

}

jocd, err = sjson.SetBytes(jocd, "metadata.annotations.upbound\\.io/name", name)

if err != nil {

return "", errors.Wrapf(err, "cannot set upbound.io/name annotation")

}

yocd, err := yaml.JSONToYAML(jocd)

if err != nil {

return "", errors.Wrap(err, "cannot convert composed resource to YAML")

}

composed.WriteString("---\n")

composed.Write(yocd)

}

return composed.String(), nil

}

// ComposedFromYAML parses the supplied YAML stream as desired composed

// resources. The resource names are extracted from the upbound.io/name

// annotation.

func ComposedFromYAML(y string) (map[string]*fnv1.Resource, error) {

out := make(map[string]*fnv1.Resource)

for doc := range strings.SplitSeq(y, "---") {

if doc == "" {

continue

}

j, err := yaml.YAMLToJSON([]byte(doc))

if err != nil {

return nil, errors.Wrap(err, "cannot parse YAML")

}

s := &structpb.Struct{}

if err := protojson.Unmarshal(j, s); err != nil {

return nil, errors.Wrap(err, "cannot parse JSON")

}

name := gjson.GetBytes(j, "metadata.annotations.upbound\\.io/name").String()

if name == "" {

return nil, errors.New("missing 'upbound.io/name' annotation")

}

if _, seen := out[name]; seen {

return nil, errors.Errorf("'upbound.io/name' annotation %q must be unique within the YAML stream", name)

}

out[name] = &fnv1.Resource{Resource: s}

}

return out, nil

}

// removeYAMLMarkdown is a helper function for cleaning the output from GPT.

// The responses can be inconsitent with markdown being returned at times.

// This function takes a multi-line string containing YAML tags and cleans

// those for future processing of the YAML stream.

func removeYAMLMarkdown(in string) string {

wsRemoved := strings.TrimSpace(in)

yamlPrefix := strings.TrimPrefix(wsRemoved, "```yaml")

return strings.TrimSuffix(yamlPrefix, "```")

}

// resourceFrom produces a map of resource name to resources derived from the

// given string. If the string is neither JSON nor YAML, an error is returned.

func (f *Function) resourceFrom(i string) (map[string]*fnv1.Resource, error) {

out := make(map[string]*fnv1.Resource)

b := []byte(i)

// Is i YAML?

jb, err := yaml.YAMLToJSON(b)

if err != nil {

f.log.Debug("error seen while attempting to convert YAML to JSON", "error", err)

// i doesn't appear to be YAML, maybe it's JSON...

jb = b

}

s := &structpb.Struct{}

if err := protojson.Unmarshal(jb, s); err != nil {

return nil, errors.Wrap(err, "cannot parse JSON")

}

name := gjson.GetBytes(jb, "metadata.name").String()

out[name] = &fnv1.Resource{Resource: s}

return out, nil

}

// attempts to identify if the function is operating within a composition

// pipeline or not by looking to see if a composite was sent with the request.

func inCompositionPipeline(req *fnv1.RunFunctionRequest) bool {

return req.GetObserved().GetComposite() != nil

}

// pipelineDetails wraps the inputs and outputs for the given function run.

type pipelineDetails struct {

// FunctionRequest

req *fnv1.RunFunctionRequest

// FunctionResponse

rsp *fnv1.RunFunctionResponse

// marshalled input

in *v1alpha1.Prompt

// LLM API credential

cred string

// Optional base URL for OpenAI API

baseURL string

// Optional model name, defaults to gpt-4

model string

}

// compositionPipeline processes the given pipelineDetails with the assumption

// that the function is defined in a composition pipeline and will be working

// with composites and desired resources.

func (f *Function) compositionPipeline(ctx context.Context, log logging.Logger, d pipelineDetails) (*fnv1.RunFunctionResponse, error) {

userPrompt, err := template.New("prompt").Parse(d.in.UserPrompt)

if err != nil {

response.Fatal(d.rsp, errors.Wrap(err, "cannot parse userPrompt"))

return d.rsp, err

}

// TODO(ththornton): possibly switch to just JSON to remove the double encode.

xr, err := CompositeToYAML(d.req.GetObserved().GetComposite())

if err != nil {

response.Fatal(d.rsp, errors.Wrap(err, "cannot convert observed XR to YAML"))

return d.rsp, err

}

cds, err := ComposedToYAML(d.req.GetObserved().GetResources())

if err != nil {

response.Fatal(d.rsp, errors.Wrap(err, "cannot convert observed composed resources to YAML"))

return d.rsp, err

}

pb := &strings.Builder{}

if err := userPrompt.Execute(pb, &Variables{Composite: xr, Composed: cds}); err != nil {

response.Fatal(d.rsp, errors.Wrapf(err, "cannot build prompt from template"))

return d.rsp, err

}

log.Debug("Using prompt", "prompt", pb.String())

resp, err := f.ai.Invoke(ctx, d.cred, d.in.SystemPrompt, pb.String(), d.baseURL, d.model)

if err != nil {

response.Fatal(d.rsp, errors.Wrap(err, "failed to run chain"))

return d.rsp, err

}

result := ""

dcds, err := ComposedFromYAML(removeYAMLMarkdown(resp))

if err != nil {

result = err.Error()

log.Debug("Submitted YAML stream", "result", result, "isError", true)

response.Fatal(d.rsp, errors.Wrap(err, "did not receive a YAML stream from GPT"))

return d.rsp, err

}

log.Debug("Received YAML manifests from GPT", "resourceCount", len(dcds))

d.rsp.Desired.Resources = dcds

return d.rsp, nil

}

// OperationVariables used to form the prompt.

type OperationVariables struct {

Input string `json:"input"`

Resources string `json:"resources"`

}

// operationPipeline processes the given pipelineDetails with the assumption

// that the function is defined in an operations pipeline.

func (f *Function) operationPipeline(ctx context.Context, log logging.Logger, d pipelineDetails) (*fnv1.RunFunctionResponse, error) {

prompt, err := template.New("prompt").Parse(d.in.UserPrompt)

if err != nil {

response.Fatal(d.rsp, errors.New("failed to parse UserPrompt as a go-template"))

return d.rsp, err

}

rr, err := request.GetRequiredResources(d.req)

if err != nil {

response.Fatal(d.rsp, errors.Wrapf(err, "cannot get Function extra resources from %T", d.req))

return d.rsp, err

}

// TODO(tnthornton) reference const from c/c instead. Currently too many

// conflicting dependencies are pulled in when updating c/c in this repo.

rs, ok := rr["ops.crossplane.io/watched-resource"]

if !ok {

f.log.Debug("no resource to process")

response.ConditionTrue(d.rsp, "FunctionSuccess", "Success").TargetCompositeAndClaim()

return d.rsp, nil

}

if len(rs) != 1 {

response.Fatal(d.rsp, errors.New("too many resources sent to the function. expected 1"))

return d.rsp, err

}

rb, err := json.MarshalIndent(rs[0].Resource.UnstructuredContent(), "", " ")

if err != nil {

response.Fatal(d.rsp, errors.New("failed to unmarshal required resource"))

return d.rsp, err

}

vars := &strings.Builder{}

if err := prompt.Execute(vars, &OperationVariables{Input: d.in.UserPrompt, Resources: string(rb)}); err != nil {

response.Fatal(d.rsp, errors.Wrapf(err, "cannot build prompt from template"))

return d.rsp, err

}

log.Debug("Using prompt", "prompt", vars.String())

resp, err := f.ai.Invoke(ctx, d.cred, d.in.SystemPrompt, vars.String(), d.baseURL, d.model)

if err != nil {

response.Fatal(d.rsp, errors.Wrap(err, "failed to run chain"))

return d.rsp, err

}

desired, err := f.resourceFrom(resp)

if err != nil {

// we didn't get a JSON based response from GPT

log.Debug("failed to get a JSON response back, no desired resources will be sent back to crossplane")

}

response.ConditionTrue(d.rsp, "FunctionSuccess", "Success").TargetCompositeAndClaim()

response.Normal(d.rsp, resp)

d.rsp.Desired.Resources = desired

return d.rsp, nil

}

// shouldIgnore returns true if the caller has communicated that the resource

// is an ignored resource. False otherwise.

func (f *Function) shouldIgnore(req *fnv1.RunFunctionRequest) bool {

fctx := req.GetContext()

ignored, ok := fctx.AsMap()["ops.upbound.io/ignored-resource"]

if ok {

i, ok := ignored.(bool)

if ok && i {

return true

}

return false

}

type agent struct {

log logging.Logger

res *tool.Resolver

}

// Invoke makes an external call to the configured LLM with the supplied

// credential key, system and user prompts.

func (a *agent) Invoke(ctx context.Context, key, system, prompt, baseURL, modelName string) (string, error) {

opts := []openaillm.Option{

openaillm.WithToken(key),

openaillm.WithModel(modelName),

}

// Add custom base URL if provided

if baseURL != "" {

opts = append(opts, openaillm.WithBaseURL(baseURL))

}

model, err := openaillm.New(opts...)

if err != nil {

return "", errors.Wrap(err, "failed to build model")

}

agent := agents.NewOpenAIFunctionsAgent(

model,

a.tools(ctx),

agents.WithMaxIterations(20),

agents.NewOpenAIOption().WithSystemMessage(system),

)

return chains.Run(

ctx,

agents.NewExecutor(agent),

prompt,

chains.WithTemperature(float64(0)),

)

}

func (a *agent) tools(ctx context.Context) []tools.Tool {

cfgs := a.res.FromEnvVars()

if len(cfgs) == 0 {

a.log.Debug("no valid mcp server configurations found")

}

return a.res.Resolve(ctx, cfgs)

}

function-openai/fn.go at main · upbound/function-openai · GitHub

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