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feat: llm engine driver #411
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,3 @@ | ||
| package llm | ||
|
|
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| type Arg func(*Driver) error |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,266 @@ | ||
| package llm | ||
|
|
||
| import ( | ||
| "context" | ||
| "encoding/json" | ||
| "errors" | ||
| "fmt" | ||
| "net/http" | ||
| "strings" | ||
| "time" | ||
|
|
||
| openai "github.com/sashabaranov/go-openai" | ||
|
|
||
| apiconstraints "github.com/open-policy-agent/frameworks/constraint/pkg/apis/constraints" | ||
| "github.com/open-policy-agent/frameworks/constraint/pkg/client/drivers" | ||
| llmSchema "github.com/open-policy-agent/frameworks/constraint/pkg/client/drivers/llm/schema" | ||
| "github.com/open-policy-agent/frameworks/constraint/pkg/core/templates" | ||
| "github.com/open-policy-agent/frameworks/constraint/pkg/types" | ||
| "github.com/open-policy-agent/opa/storage" | ||
| "github.com/sethvargo/go-retry" | ||
| flag "github.com/spf13/pflag" | ||
| "github.com/walles/env" | ||
| admissionv1 "k8s.io/api/admission/v1" | ||
| "k8s.io/apimachinery/pkg/apis/meta/v1/unstructured" | ||
| ) | ||
|
|
||
| const ( | ||
| maxRetries = 10 | ||
| // need minimum of 2023-12-01-preview for JSON mode. | ||
| azureOpenAIAPIVersion = "2024-03-01-preview" | ||
| azureOpenAIURL = "openai.azure.com" | ||
| systemPrompt = "You are a policy engine for Kubernetes designed to output JSON. Input will be a policy definition, Kubernetes AdmissionRequest object, and parameters to apply to the policy if applicable. Output JSON should only have a 'decision' field with a boolean value and a 'reason' field with a string value explaining the decision, only if decision is false. Only output valid JSON." | ||
| ) | ||
|
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| var ( | ||
| openAIAPIURLv1 = "https://api.openai.com/v1" | ||
|
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| openAIDeploymentName = flag.String("openai-deployment-name", env.GetOr("OPENAI_DEPLOYMENT_NAME", env.String, "gpt-3.5-turbo-0301"), "The deployment name used for the model in OpenAI service.") | ||
| openAIAPIKey = flag.String("openai-api-key", env.GetOr("OPENAI_API_KEY", env.String, ""), "The API key for the OpenAI service. This is required.") | ||
| openAIEndpoint = flag.String("openai-endpoint", env.GetOr("OPENAI_ENDPOINT", env.String, openAIAPIURLv1), "The endpoint for OpenAI service. Defaults to"+openAIAPIURLv1+". Set this to Azure OpenAI Service or OpenAI compatible API endpoint, if needed.") | ||
| ) | ||
|
|
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| type Driver struct { | ||
| prompts map[string]string | ||
| } | ||
|
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| var _ drivers.Driver = &Driver{} | ||
|
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| type Decision struct { | ||
| Name string | ||
| Constraint *unstructured.Unstructured | ||
| Decision bool | ||
| Reason string | ||
| } | ||
|
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| type ARGetter interface { | ||
| GetAdmissionRequest() *admissionv1.AdmissionRequest | ||
| } | ||
|
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| // Name returns the name of the driver. | ||
| func (d *Driver) Name() string { | ||
| return llmSchema.Name | ||
| } | ||
|
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| func (d *Driver) AddTemplate(_ context.Context, ct *templates.ConstraintTemplate) error { | ||
| source, err := llmSchema.GetSourceFromTemplate(ct) | ||
| if err != nil { | ||
| return err | ||
| } | ||
|
|
||
| prompt, err := source.GetPrompt() | ||
| if err != nil { | ||
| return err | ||
| } | ||
| if prompt == "" { | ||
| return fmt.Errorf("prompt is empty for template: %q", ct.Name) | ||
| } | ||
|
|
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| d.prompts[ct.Name] = prompt | ||
| return nil | ||
| } | ||
|
|
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| func (d *Driver) RemoveTemplate(_ context.Context, ct *templates.ConstraintTemplate) error { | ||
| delete(d.prompts, ct.Name) | ||
|
|
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| return nil | ||
| } | ||
|
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| func (d *Driver) AddConstraint(_ context.Context, constraint *unstructured.Unstructured) error { | ||
| promptName := strings.ToLower(constraint.GetKind()) | ||
|
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| _, found := d.prompts[promptName] | ||
| if !found { | ||
| return fmt.Errorf("no promptName with name: %q", promptName) | ||
| } | ||
| return nil | ||
| } | ||
|
|
||
| func (d *Driver) RemoveConstraint(_ context.Context, _ *unstructured.Unstructured) error { | ||
| return nil | ||
| } | ||
|
|
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| func (d *Driver) AddData(_ context.Context, _ string, _ storage.Path, _ interface{}) error { | ||
| return nil | ||
| } | ||
|
|
||
| func (d *Driver) RemoveData(_ context.Context, _ string, _ storage.Path) error { | ||
| return nil | ||
| } | ||
|
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| func (d *Driver) Query(ctx context.Context, _ string, constraints []*unstructured.Unstructured, review interface{}, _ ...drivers.QueryOpt) (*drivers.QueryResponse, error) { | ||
| llmc, err := newLLMClients() | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
|
|
||
| arGetter, ok := review.(ARGetter) | ||
| if !ok { | ||
| return nil, errors.New("cannot convert review to ARGetter") | ||
| } | ||
| aRequest := arGetter.GetAdmissionRequest() | ||
|
|
||
| var allDecisions []*Decision | ||
| for _, constraint := range constraints { | ||
| promptName := strings.ToLower(constraint.GetKind()) | ||
| prompt, found := d.prompts[promptName] | ||
| if !found { | ||
| continue | ||
| } | ||
|
|
||
| paramsStruct, _, err := unstructured.NestedFieldNoCopy(constraint.Object, "spec", "parameters") | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
|
|
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| params, err := json.Marshal(paramsStruct) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
|
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| llmPrompt := fmt.Sprintf("policy: %s\nadmission request: %s\nparameters: %s", prompt, string(aRequest.Object.Raw), string(params)) | ||
|
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| var resp string | ||
| r := retry.WithMaxRetries(maxRetries, retry.NewExponential(1*time.Second)) | ||
| if err := retry.Do(ctx, r, func(ctx context.Context) error { | ||
| resp, err = llmc.openaiGptChatCompletion(ctx, llmPrompt) | ||
| requestErr := &openai.APIError{} | ||
| if errors.As(err, &requestErr) { | ||
| switch requestErr.HTTPStatusCode { | ||
| case http.StatusTooManyRequests, http.StatusRequestTimeout, http.StatusInternalServerError, http.StatusBadGateway, http.StatusServiceUnavailable, http.StatusGatewayTimeout: | ||
| return retry.RetryableError(err) | ||
| } | ||
| } | ||
| return nil | ||
| }); err != nil { | ||
| return nil, err | ||
| } | ||
|
|
||
| var decision Decision | ||
| err = json.Unmarshal([]byte(resp), &decision) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
|
|
||
| if !decision.Decision { | ||
| llmDecision := &Decision{ | ||
| Decision: decision.Decision, | ||
| Name: constraint.GetName(), | ||
| Constraint: constraint, | ||
| Reason: decision.Reason, | ||
| } | ||
| allDecisions = append(allDecisions, llmDecision) | ||
| } | ||
| } | ||
| if len(allDecisions) == 0 { | ||
| return nil, nil | ||
| } | ||
|
|
||
| results := make([]*types.Result, len(allDecisions)) | ||
| for i, llmDecision := range allDecisions { | ||
| enforcementAction, found, err := unstructured.NestedString(llmDecision.Constraint.Object, "spec", "enforcementAction") | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| if !found { | ||
| enforcementAction = apiconstraints.EnforcementActionDeny | ||
| } | ||
|
|
||
| results[i] = &types.Result{ | ||
| Metadata: map[string]interface{}{ | ||
| "name": llmDecision.Name, | ||
| }, | ||
| Constraint: llmDecision.Constraint, | ||
| Msg: llmDecision.Reason, | ||
| EnforcementAction: enforcementAction, | ||
| } | ||
| } | ||
| return &drivers.QueryResponse{Results: results}, nil | ||
| } | ||
|
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||
| func (d *Driver) Dump(_ context.Context) (string, error) { | ||
| panic("implement me") | ||
| } | ||
|
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| func (d *Driver) GetDescriptionForStat(_ string) (string, error) { | ||
| panic("implement me") | ||
| } | ||
|
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| type llmClients struct { | ||
| openAIClient openai.Client | ||
| } | ||
|
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| func newLLMClients() (llmClients, error) { | ||
| var config openai.ClientConfig | ||
| // default to OpenAI API | ||
| config = openai.DefaultConfig(*openAIAPIKey) | ||
|
|
||
| if openAIEndpoint != &openAIAPIURLv1 { | ||
| // Azure OpenAI | ||
| if strings.Contains(*openAIEndpoint, azureOpenAIURL) { | ||
| config = openai.DefaultAzureConfig(*openAIAPIKey, *openAIEndpoint) | ||
| } else { | ||
| // OpenAI API compatible endpoint or proxy | ||
| config.BaseURL = *openAIEndpoint | ||
| } | ||
| config.APIVersion = azureOpenAIAPIVersion | ||
| } | ||
|
|
||
| clients := llmClients{ | ||
| openAIClient: *openai.NewClientWithConfig(config), | ||
| } | ||
| return clients, nil | ||
| } | ||
|
|
||
| func (c *llmClients) openaiGptChatCompletion(ctx context.Context, prompt string) (string, error) { | ||
| req := openai.ChatCompletionRequest{ | ||
| Model: *openAIDeploymentName, | ||
| Messages: []openai.ChatCompletionMessage{ | ||
| { | ||
| Role: openai.ChatMessageRoleSystem, | ||
| Content: systemPrompt, | ||
| }, | ||
| { | ||
| Role: openai.ChatMessageRoleUser, | ||
| Content: prompt, | ||
| }, | ||
| }, | ||
| N: 1, // Number of completions to generate | ||
| Temperature: 0, // 0 is more deterministic | ||
| ResponseFormat: &openai.ChatCompletionResponseFormat{ | ||
| Type: openai.ChatCompletionResponseFormatTypeJSONObject, | ||
| }, | ||
| } | ||
|
|
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| resp, err := c.openAIClient.CreateChatCompletion(ctx, req) | ||
| if err != nil { | ||
| return "", err | ||
| } | ||
|
|
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| if len(resp.Choices) != 1 { | ||
| return "", fmt.Errorf("expected choices to be 1 but received: %d", len(resp.Choices)) | ||
| } | ||
|
|
||
| result := resp.Choices[0].Message.Content | ||
| return result, nil | ||
| } | ||
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,13 @@ | ||
| package llm | ||
|
|
||
| func New(args ...Arg) (*Driver, error) { | ||
| driver := &Driver{ | ||
| prompts: make(map[string]string), | ||
| } | ||
| for _, arg := range args { | ||
| if err := arg(driver); err != nil { | ||
| return nil, err | ||
| } | ||
| } | ||
| return driver, nil | ||
| } |
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other than empty string, are there other prompts that we may want to prevent? could any prompts be used to exploit or manipulate the system?