Package cloud.google.com/go/vertexai/genai (v0.13.3)

func Ptr(t T) *T

func WithClientInfo(key, value string) option.ClientOption

func WithREST() option.ClientOption

type Blob struct {
	// Required. The IANA standard MIME type of the source data.
	MIMEType string
	// Required. Raw bytes.
	Data []byte
}

func ImageData(format string, data []byte) Blob

type BlockedError struct {
	// If non-nil, the model's response was blocked.
	// Consult the Candidate and SafetyRatings fields for details.
	Candidate *Candidate

	// If non-nil, there was a problem with the prompt.
	PromptFeedback *PromptFeedback
}

func (e *BlockedError) Error() string

type BlockedReason int32

const (
	// BlockedReasonUnspecified means unspecified blocked reason.
	BlockedReasonUnspecified BlockedReason = 0
	// BlockedReasonSafety means candidates blocked due to safety.
	BlockedReasonSafety BlockedReason = 1
	// BlockedReasonOther means candidates blocked due to other reason.
	BlockedReasonOther BlockedReason = 2
	// BlockedReasonBlocklist means candidates blocked due to the terms which are included from the
	// terminology blocklist.
	BlockedReasonBlocklist BlockedReason = 3
	// BlockedReasonProhibitedContent means candidates blocked due to prohibited content.
	BlockedReasonProhibitedContent BlockedReason = 4
)

func (v BlockedReason) String() string

type CachedContent struct {
	// Expiration time of the cached content.
	//
	// Types that are assignable to Expiration:
	//
	//	*CachedContent_ExpireTime
	//	*CachedContent_Ttl
	Expiration ExpireTimeOrTTL
	// Immutable. Identifier. The server-generated resource name of the cached
	// content Format:
	// projects/{project}/locations/{location}/cachedContents/{cached_content}
	Name string
	// Immutable. The name of the publisher model to use for cached content.
	// Format:
	// projects/{project}/locations/{location}/publishers/{publisher}/models/{model}
	Model string
	// Optional. Input only. Immutable. Developer set system instruction.
	// Currently, text only
	SystemInstruction *Content
	// Optional. Input only. Immutable. The content to cache
	Contents []*Content
	// Optional. Input only. Immutable. A list of `Tools` the model may use to
	// generate the next response
	Tools []*Tool
	// Optional. Input only. Immutable. Tool config. This config is shared for all
	// tools
	ToolConfig *ToolConfig
	// Output only. Creatation time of the cache entry.
	CreateTime time.Time
	// Output only. When the cache entry was last updated in UTC time.
	UpdateTime time.Time
}

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

func (it *CachedContentIterator) Next() (*CachedContent, error)

func (it *CachedContentIterator) PageInfo() *iterator.PageInfo

type CachedContentToUpdate struct {
	// If non-nil, update the expire time or TTL.
	Expiration *ExpireTimeOrTTL
}

type Candidate struct {
	// Output only. Index of the candidate.
	Index int32
	// Output only. Content parts of the candidate.
	Content *Content
	// Output only. The reason why the model stopped generating tokens.
	// If empty, the model has not stopped generating the tokens.
	FinishReason FinishReason
	// Output only. List of ratings for the safety of a response candidate.
	//
	// There is at most one rating per category.
	SafetyRatings []*SafetyRating
	// Output only. Describes the reason the mode stopped generating tokens in
	// more detail. This is only filled when `finish_reason` is set.
	FinishMessage string
	// Output only. Source attribution of the generated content.
	CitationMetadata *CitationMetadata
}

func (c *Candidate) FunctionCalls() []FunctionCall

type ChatSession struct {
	History []*Content
	// contains filtered or unexported fields
}

package main

import (
	"context"
	"fmt"
	"log"

	"cloud.google.com/go/vertexai/genai"

	"google.golang.org/api/iterator"
)

// Your GCP project
const projectID = "your-project"

// A GCP location like "us-central1"; if you're using standard Google-published
// models (like untuned Gemini models), you can keep location blank ("").
const location = "some-gcp-location"

// A model name like "gemini-1.0-pro"
// For custom models from different publishers, prepent the full publisher
// prefix for the model, e.g.:
//
//	modelName = publishers/some-publisher/models/some-model-name
const modelName = "some-model"

func main() {
	ctx := context.Background()
	client, err := genai.NewClient(ctx, projectID, location)
	if err != nil {
		log.Fatal(err)
	}
	defer client.Close()
	model := client.GenerativeModel(modelName)
	cs := model.StartChat()

	send := func(msg string) *genai.GenerateContentResponse {
		fmt.Printf("== Me: %s\n== Model:\n", msg)
		res, err := cs.SendMessage(ctx, genai.Text(msg))
		if err != nil {
			log.Fatal(err)
		}
		return res
	}

	res := send("Can you name some brands of air fryer?")
	printResponse(res)
	iter := cs.SendMessageStream(ctx, genai.Text("Which one of those do you recommend?"))
	for {
		res, err := iter.Next()
		if err == iterator.Done {
			break
		}
		if err != nil {
			log.Fatal(err)
		}
		printResponse(res)
	}

	for i, c := range cs.History {
		log.Printf("    %d: %+v", i, c)
	}
	res = send("Why do you like the Philips?")
	if err != nil {
		log.Fatal(err)
	}
	printResponse(res)
}

func printResponse(resp *genai.GenerateContentResponse) {
	for _, cand := range resp.Candidates {
		for _, part := range cand.Content.Parts {
			fmt.Println(part)
		}
	}
	fmt.Println("---")
}

func (cs *ChatSession) SendMessage(ctx context.Context, parts ...Part) (*GenerateContentResponse, error)

func (cs *ChatSession) SendMessageStream(ctx context.Context, parts ...Part) *GenerateContentResponseIterator

type Citation struct {
	// Output only. Start index into the content.
	StartIndex int32
	// Output only. End index into the content.
	EndIndex int32
	// Output only. Url reference of the attribution.
	URI string
	// Output only. Title of the attribution.
	Title string
	// Output only. License of the attribution.
	License string
	// Output only. Publication date of the attribution.
	PublicationDate civil.Date
}

type CitationMetadata struct {
	// Output only. List of citations.
	Citations []*Citation
}

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

package main

import (
	"context"
	"log"
	"os"

	"cloud.google.com/go/vertexai/genai"
)

// Your GCP project
const projectID = "your-project"

// A GCP location like "us-central1"; if you're using standard Google-published
// models (like untuned Gemini models), you can keep location blank ("").
const location = "some-gcp-location"

// A model name like "gemini-1.0-pro"
// For custom models from different publishers, prepent the full publisher
// prefix for the model, e.g.:
//
//	modelName = publishers/some-publisher/models/some-model-name
const modelName = "some-model"

func main() {
	ctx := context.Background()
	client, err := genai.NewClient(ctx, projectID, location)
	if err != nil {
		log.Fatal(err)
	}
	defer client.Close()
	file := genai.FileData{MIMEType: "application/pdf", FileURI: "gs://my-bucket/my-doc.pdf"}
	cc, err := client.CreateCachedContent(ctx, &genai.CachedContent{
		Model:    modelName,
		Contents: []*genai.Content{genai.NewUserContent(file)},
	})
	model := client.GenerativeModelFromCachedContent(cc)
	// Work with the model as usual in this program.
	_ = model

	// Store the CachedContent name for later use.
	if err := os.WriteFile("my-cached-content-name", []byte(cc.Name), 0o644); err != nil {
		log.Fatal(err)
	}

	///////////////////////////////
	// Later, in another process...

	bytes, err := os.ReadFile("my-cached-content-name")
	if err != nil {
		log.Fatal(err)
	}
	ccName := string(bytes)

	// No need to call [Client.GetCachedContent]; the name is sufficient.
	model = client.GenerativeModel(modelName)
	model.CachedContentName = ccName
	// Proceed as usual.
}

func NewClient(ctx context.Context, projectID, location string, opts ...option.ClientOption) (*Client, error)

func (c *Client) Close() error

func (c *Client) CreateCachedContent(ctx context.Context, cc *CachedContent) (*CachedContent, error)

func (c *Client) DeleteCachedContent(ctx context.Context, name string) error

func (c *Client) GenerativeModel(name string) *GenerativeModel

func (c *Client) GenerativeModelFromCachedContent(cc *CachedContent) *GenerativeModel

func (c *Client) GetCachedContent(ctx context.Context, name string) (*CachedContent, error)

func (c *Client) ListCachedContents(ctx context.Context) *CachedContentIterator

func (c *Client) UpdateCachedContent(ctx context.Context, cc *CachedContent, ccu *CachedContentToUpdate) (*CachedContent, error)

type Content struct {
	// Optional. The producer of the content. Must be either 'user' or 'model'.
	//
	// Useful to set for multi-turn conversations, otherwise can be left blank
	// or unset.
	Role string
	// Required. Ordered `Parts` that constitute a single message. Parts may have
	// different IANA MIME types.
	Parts []Part
}

func NewUserContent(parts ...Part) *Content

type CountTokensResponse struct {
	// The total number of tokens counted across all instances from the request.
	TotalTokens int32
	// The total number of billable characters counted across all instances from
	// the request.
	TotalBillableCharacters int32
}

type ExpireTimeOrTTL struct {
	ExpireTime time.Time
	TTL        time.Duration
}

type FileData struct {
	// Required. The IANA standard MIME type of the source data.
	MIMEType string
	// Required. URI.
	FileURI string
}

type FinishReason int32

const (
	// FinishReasonUnspecified means the finish reason is unspecified.
	FinishReasonUnspecified FinishReason = 0
	// FinishReasonStop means natural stop point of the model or provided stop sequence.
	FinishReasonStop FinishReason = 1
	// FinishReasonMaxTokens means the maximum number of tokens as specified in the request was reached.
	FinishReasonMaxTokens FinishReason = 2
	// FinishReasonSafety means the token generation was stopped as the response was flagged for safety
	// reasons. NOTE: When streaming the Candidate.content will be empty if
	// content filters blocked the output.
	FinishReasonSafety FinishReason = 3
	// FinishReasonRecitation means the token generation was stopped as the response was flagged for
	// unauthorized citations.
	FinishReasonRecitation FinishReason = 4
	// FinishReasonOther means all other reasons that stopped the token generation
	FinishReasonOther FinishReason = 5
	// FinishReasonBlocklist means the token generation was stopped as the response was flagged for the
	// terms which are included from the terminology blocklist.
	FinishReasonBlocklist FinishReason = 6
	// FinishReasonProhibitedContent means the token generation was stopped as the response was flagged for
	// the prohibited contents.
	FinishReasonProhibitedContent FinishReason = 7
	// FinishReasonSpii means the token generation was stopped as the response was flagged for
	// Sensitive Personally Identifiable Information (SPII) contents.
	FinishReasonSpii FinishReason = 8
	// FinishReasonMalformedFunctionCall means the function call generated by the model is invalid.
	FinishReasonMalformedFunctionCall FinishReason = 9
)

func (v FinishReason) String() string

type FunctionCall struct {
	// Required. The name of the function to call.
	// Matches [FunctionDeclaration.name].
	Name string
	// Optional. Required. The function parameters and values in JSON object
	// format. See [FunctionDeclaration.parameters] for parameter details.
	Args map[string]any
}

type FunctionCallingConfig struct {
	// Optional. Function calling mode.
	Mode FunctionCallingMode
	// Optional. Function names to call. Only set when the Mode is ANY. Function
	// names should match [FunctionDeclaration.name]. With mode set to ANY, model
	// will predict a function call from the set of function names provided.
	AllowedFunctionNames []string
}

type FunctionCallingMode int32

const (
	// FunctionCallingUnspecified means unspecified function calling mode. This value should not be used.
	FunctionCallingUnspecified FunctionCallingMode = 0
	// FunctionCallingAuto means default model behavior, model decides to predict either a function call
	// or a natural language repspose.
	FunctionCallingAuto FunctionCallingMode = 1
	// FunctionCallingAny means model is constrained to always predicting a function call only.
	// If "allowed_function_names" are set, the predicted function call will be
	// limited to any one of "allowed_function_names", else the predicted
	// function call will be any one of the provided "function_declarations".
	FunctionCallingAny FunctionCallingMode = 2
	// FunctionCallingNone means model will not predict any function call. Model behavior is same as when
	// not passing any function declarations.
	FunctionCallingNone FunctionCallingMode = 3
)

func (v FunctionCallingMode) String() string

type FunctionDeclaration struct {
	// Required. The name of the function to call.
	// Must start with a letter or an underscore.
	// Must be a-z, A-Z, 0-9, or contain underscores, dots and dashes, with a
	// maximum length of 64.
	Name string
	// Optional. Description and purpose of the function.
	// Model uses it to decide how and whether to call the function.
	Description string
	// Optional. Describes the parameters to this function in JSON Schema Object
	// format. Reflects the Open API 3.03 Parameter Object. string Key: the name
	// of the parameter. Parameter names are case sensitive. Schema Value: the
	// Schema defining the type used for the parameter. For function with no
	// parameters, this can be left unset. Parameter names must start with a
	// letter or an underscore and must only contain chars a-z, A-Z, 0-9, or
	// underscores with a maximum length of 64. Example with 1 required and 1
	// optional parameter: type: OBJECT properties:
	//
	//	param1:
	//	  type: STRING
	//	param2:
	//	  type: INTEGER
	//
	// required:
	//   - param1
	Parameters *Schema
	// Optional. Describes the output from this function in JSON Schema format.
	// Reflects the Open API 3.03 Response Object. The Schema defines the type
	// used for the response value of the function.
	Response *Schema
}

type FunctionResponse struct {
	// Required. The name of the function to call.
	// Matches [FunctionDeclaration.name] and [FunctionCall.name].
	Name string
	// Required. The function response in JSON object format.
	Response map[string]any
}

type GenerateContentResponse struct {
	// Output only. Generated candidates.
	Candidates []*Candidate
	// Output only. Content filter results for a prompt sent in the request.
	// Note: Sent only in the first stream chunk.
	// Only happens when no candidates were generated due to content violations.
	PromptFeedback *PromptFeedback
	// Usage metadata about the response(s).
	UsageMetadata *UsageMetadata
}

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

func (iter *GenerateContentResponseIterator) MergedResponse() *GenerateContentResponse

func (iter *GenerateContentResponseIterator) Next() (*GenerateContentResponse, error)

type GenerationConfig struct {
	// Optional. Controls the randomness of predictions.
	Temperature *float32
	// Optional. If specified, nucleus sampling will be used.
	TopP *float32
	// Optional. If specified, top-k sampling will be used.
	TopK *int32
	// Optional. Number of candidates to generate.
	CandidateCount *int32
	// Optional. The maximum number of output tokens to generate per message.
	MaxOutputTokens *int32
	// Optional. Stop sequences.
	StopSequences []string
	// Optional. Positive penalties.
	PresencePenalty *float32
	// Optional. Frequency penalties.
	FrequencyPenalty *float32
	// Optional. Output response mimetype of the generated candidate text.
	// Supported mimetype:
	// - `text/plain`: (default) Text output.
	// - `application/json`: JSON response in the candidates.
	// The model needs to be prompted to output the appropriate response type,
	// otherwise the behavior is undefined.
	// This is a preview feature.
	ResponseMIMEType string
	// Optional. The `Schema` object allows the definition of input and output
	// data types. These types can be objects, but also primitives and arrays.
	// Represents a select subset of an [OpenAPI 3.0 schema
	// object](https://spec.openapis.org/oas/v3.0.3#schema).
	// If set, a compatible response_mime_type must also be set.
	// Compatible mimetypes:
	// `application/json`: Schema for JSON response.
	ResponseSchema *Schema
}

func (c *GenerationConfig) SetCandidateCount(x int32)

func (c *GenerationConfig) SetMaxOutputTokens(x int32)

func (c *GenerationConfig) SetTemperature(x float32)

func (c *GenerationConfig) SetTopK(x int32)

func (c *GenerationConfig) SetTopP(x float32)

type GenerativeModel struct {
	GenerationConfig
	SafetySettings    []*SafetySetting
	Tools             []*Tool
	ToolConfig        *ToolConfig // configuration for tools
	SystemInstruction *Content
	// The name of the CachedContent to use.
	// Must have already been created with [Client.CreateCachedContent].
	CachedContentName string
	// contains filtered or unexported fields
}

func (m *GenerativeModel) CountTokens(ctx context.Context, parts ...Part) (*CountTokensResponse, error)

package main

import (
	"context"
	"fmt"
	"log"

	"cloud.google.com/go/vertexai/genai"
)

// Your GCP project
const projectID = "your-project"

// A GCP location like "us-central1"; if you're using standard Google-published
// models (like untuned Gemini models), you can keep location blank ("").
const location = "some-gcp-location"

// A model name like "gemini-1.0-pro"
// For custom models from different publishers, prepent the full publisher
// prefix for the model, e.g.:
//
//	modelName = publishers/some-publisher/models/some-model-name
const modelName = "some-model"

func main() {
	ctx := context.Background()
	client, err := genai.NewClient(ctx, projectID, location)
	if err != nil {
		log.Fatal(err)
	}
	defer client.Close()

	model := client.GenerativeModel(modelName)

	resp, err := model.CountTokens(ctx, genai.Text("What kind of fish is this?"))
	if err != nil {
		log.Fatal(err)
	}

	fmt.Println("Num tokens:", resp.TotalTokens)
}

func (m *GenerativeModel) GenerateContent(ctx context.Context, parts ...Part) (*GenerateContentResponse, error)

package main

import (
	"context"
	"fmt"
	"log"

	"cloud.google.com/go/vertexai/genai"
)

// Your GCP project
const projectID = "your-project"

// A GCP location like "us-central1"; if you're using standard Google-published
// models (like untuned Gemini models), you can keep location blank ("").
const location = "some-gcp-location"

// A model name like "gemini-1.0-pro"
// For custom models from different publishers, prepent the full publisher
// prefix for the model, e.g.:
//
//	modelName = publishers/some-publisher/models/some-model-name
const modelName = "some-model"

func main() {
	ctx := context.Background()
	client, err := genai.NewClient(ctx, projectID, location)
	if err != nil {
		log.Fatal(err)
	}
	defer client.Close()

	model := client.GenerativeModel(modelName)
	model.SetTemperature(0.9)
	resp, err := model.GenerateContent(ctx, genai.Text("What is the average size of a swallow?"))
	if err != nil {
		log.Fatal(err)
	}

	printResponse(resp)
}

func printResponse(resp *genai.GenerateContentResponse) {
	for _, cand := range resp.Candidates {
		for _, part := range cand.Content.Parts {
			fmt.Println(part)
		}
	}
	fmt.Println("---")
}

package main

import (
	"context"
	"fmt"
	"log"

	"cloud.google.com/go/vertexai/genai"
)

func main() {
	ctx := context.Background()
	const projectID = "YOUR PROJECT ID"
	const location = "GCP LOCATION"
	client, err := genai.NewClient(ctx, projectID, location)
	if err != nil {
		log.Fatal(err)
	}
	defer client.Close()

	model := client.GenerativeModel("gemini-1.0-pro")
	model.SetTemperature(0.9)
	model.SetTopP(0.5)
	model.SetTopK(20)
	model.SetMaxOutputTokens(100)
	model.SystemInstruction = genai.NewUserContent(genai.Text("You are Yoda from Star Wars."))
	resp, err := model.GenerateContent(ctx, genai.Text("What is the average size of a swallow?"))
	if err != nil {
		log.Fatal(err)
	}
	printResponse(resp)
}

func printResponse(resp *genai.GenerateContentResponse) {
	for _, cand := range resp.Candidates {
		for _, part := range cand.Content.Parts {
			fmt.Println(part)
		}
	}
	fmt.Println("---")
}

package main

import (
	"context"
	"fmt"
	"log"

	"cloud.google.com/go/vertexai/genai"
)

func main() {
	ctx := context.Background()
	const projectID = "YOUR PROJECT ID"
	const location = "GCP LOCATION"
	client, err := genai.NewClient(ctx, projectID, location)
	if err != nil {
		log.Fatal(err)
	}
	defer client.Close()

	model := client.GenerativeModel("gemini-1.0-pro")

	queries := []string{"Hello, World!", "What's the weather today?"}
	resultChan := make(chan *genai.GenerateContentResponse, len(queries))

	worker := func(query string) {
		result, err := model.GenerateContent(ctx, genai.Text(query))
		if err != nil {
			log.Fatal(err)
		}
		resultChan <- result
	}
	// Send two requests concurrently
	for _, query := range queries {
		go worker(query)
	}

	// Wait for the responses
	for a := 0; a < len(queries); a++ {
		result := <-resultChan
		printResponse(result)
	}
	close(resultChan)
}

func printResponse(resp *genai.GenerateContentResponse) {
	for _, cand := range resp.Candidates {
		for _, part := range cand.Content.Parts {
			fmt.Println(part)
		}
	}
	fmt.Println("---")
}

func (m *GenerativeModel) GenerateContentStream(ctx context.Context, parts ...Part) *GenerateContentResponseIterator

package main

import (
	"context"
	"fmt"
	"log"

	"cloud.google.com/go/vertexai/genai"

	"google.golang.org/api/iterator"
)

// Your GCP project
const projectID = "your-project"

// A GCP location like "us-central1"; if you're using standard Google-published
// models (like untuned Gemini models), you can keep location blank ("").
const location = "some-gcp-location"

// A model name like "gemini-1.0-pro"
// For custom models from different publishers, prepent the full publisher
// prefix for the model, e.g.:
//
//	modelName = publishers/some-publisher/models/some-model-name
const modelName = "some-model"

func main() {
	ctx := context.Background()
	client, err := genai.NewClient(ctx, projectID, location)
	if err != nil {
		log.Fatal(err)
	}
	defer client.Close()

	model := client.GenerativeModel(modelName)

	iter := model.GenerateContentStream(ctx, genai.Text("Tell me a story about a lumberjack and his giant ox. Keep it very short."))
	for {
		resp, err := iter.Next()
		if err == iterator.Done {
			break
		}
		if err != nil {
			log.Fatal(err)
		}
		printResponse(resp)
	}
}

func printResponse(resp *genai.GenerateContentResponse) {
	for _, cand := range resp.Candidates {
		for _, part := range cand.Content.Parts {
			fmt.Println(part)
		}
	}
	fmt.Println("---")
}

func (m *GenerativeModel) Name() string

func (m *GenerativeModel) StartChat() *ChatSession

type HarmBlockMethod int32

const (
	// HarmBlockMethodUnspecified means the harm block method is unspecified.
	HarmBlockMethodUnspecified HarmBlockMethod = 0
	// HarmBlockMethodSeverity means the harm block method uses both probability and severity scores.
	HarmBlockMethodSeverity HarmBlockMethod = 1
	// HarmBlockMethodProbability means the harm block method uses the probability score.
	HarmBlockMethodProbability HarmBlockMethod = 2
)

func (v HarmBlockMethod) String() string

type HarmBlockThreshold int32

const (
	// HarmBlockUnspecified means unspecified harm block threshold.
	HarmBlockUnspecified HarmBlockThreshold = 0
	// HarmBlockLowAndAbove means block low threshold and above (i.e. block more).
	HarmBlockLowAndAbove HarmBlockThreshold = 1
	// HarmBlockMediumAndAbove means block medium threshold and above.
	HarmBlockMediumAndAbove HarmBlockThreshold = 2
	// HarmBlockOnlyHigh means block only high threshold (i.e. block less).
	HarmBlockOnlyHigh HarmBlockThreshold = 3
	// HarmBlockNone means block none.
	HarmBlockNone HarmBlockThreshold = 4
)

func (v HarmBlockThreshold) String() string

type HarmCategory int32

const (
	// HarmCategoryUnspecified means the harm category is unspecified.
	HarmCategoryUnspecified HarmCategory = 0
	// HarmCategoryHateSpeech means the harm category is hate speech.
	HarmCategoryHateSpeech HarmCategory = 1
	// HarmCategoryDangerousContent means the harm category is dangerous content.
	HarmCategoryDangerousContent HarmCategory = 2
	// HarmCategoryHarassment means the harm category is harassment.
	HarmCategoryHarassment HarmCategory = 3
	// HarmCategorySexuallyExplicit means the harm category is sexually explicit content.
	HarmCategorySexuallyExplicit HarmCategory = 4
)

func (v HarmCategory) String() string

type HarmProbability int32

const (
	// HarmProbabilityUnspecified means harm probability unspecified.
	HarmProbabilityUnspecified HarmProbability = 0
	// HarmProbabilityNegligible means negligible level of harm.
	HarmProbabilityNegligible HarmProbability = 1
	// HarmProbabilityLow means low level of harm.
	HarmProbabilityLow HarmProbability = 2
	// HarmProbabilityMedium means medium level of harm.
	HarmProbabilityMedium HarmProbability = 3
	// HarmProbabilityHigh means high level of harm.
	HarmProbabilityHigh HarmProbability = 4
)

func (v HarmProbability) String() string

type HarmSeverity int32

const (
	// HarmSeverityUnspecified means harm severity unspecified.
	HarmSeverityUnspecified HarmSeverity = 0
	// HarmSeverityNegligible means negligible level of harm severity.
	HarmSeverityNegligible HarmSeverity = 1
	// HarmSeverityLow means low level of harm severity.
	HarmSeverityLow HarmSeverity = 2
	// HarmSeverityMedium means medium level of harm severity.
	HarmSeverityMedium HarmSeverity = 3
	// HarmSeverityHigh means high level of harm severity.
	HarmSeverityHigh HarmSeverity = 4
)

func (v HarmSeverity) String() string

type Part interface {
	// contains filtered or unexported methods
}

type PromptFeedback struct {
	// Output only. Blocked reason.
	BlockReason BlockedReason
	// Output only. Safety ratings.
	SafetyRatings []*SafetyRating
	// Output only. A readable block reason message.
	BlockReasonMessage string
}

type SafetyRating struct {
	// Output only. Harm category.
	Category HarmCategory
	// Output only. Harm probability levels in the content.
	Probability HarmProbability
	// Output only. Harm probability score.
	ProbabilityScore float32
	// Output only. Harm severity levels in the content.
	Severity HarmSeverity
	// Output only. Harm severity score.
	SeverityScore float32
	// Output only. Indicates whether the content was filtered out because of this
	// rating.
	Blocked bool
}

type SafetySetting struct {
	// Required. Harm category.
	Category HarmCategory
	// Required. The harm block threshold.
	Threshold HarmBlockThreshold
	// Optional. Specify if the threshold is used for probability or severity
	// score. If not specified, the threshold is used for probability score.
	Method HarmBlockMethod
}

type Schema struct {
	// Optional. The type of the data.
	Type Type
	// Optional. The format of the data.
	// Supported formats:
	//
	//	for NUMBER type: "float", "double"
	//	for INTEGER type: "int32", "int64"
	//	for STRING type: "email", "byte", etc
	Format string
	// Optional. The title of the Schema.
	Title string
	// Optional. The description of the data.
	Description string
	// Optional. Indicates if the value may be null.
	Nullable bool
	// Optional. SCHEMA FIELDS FOR TYPE ARRAY
	// Schema of the elements of Type.ARRAY.
	Items *Schema
	// Optional. Minimum number of the elements for Type.ARRAY.
	MinItems int64
	// Optional. Maximum number of the elements for Type.ARRAY.
	MaxItems int64
	// Optional. Possible values of the element of Type.STRING with enum format.
	// For example we can define an Enum Direction as :
	// {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]}
	Enum []string
	// Optional. SCHEMA FIELDS FOR TYPE OBJECT
	// Properties of Type.OBJECT.
	Properties map[string]*Schema
	// Optional. Required properties of Type.OBJECT.
	Required []string
	// Optional. Minimum number of the properties for Type.OBJECT.
	MinProperties int64
	// Optional. Maximum number of the properties for Type.OBJECT.
	MaxProperties int64
	// Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER
	// Minimum value of the Type.INTEGER and Type.NUMBER
	Minimum float64
	// Optional. Maximum value of the Type.INTEGER and Type.NUMBER
	Maximum float64
	// Optional. SCHEMA FIELDS FOR TYPE STRING
	// Minimum length of the Type.STRING
	MinLength int64
	// Optional. Maximum length of the Type.STRING
	MaxLength int64
	// Optional. Pattern of the Type.STRING to restrict a string to a regular
	// expression.
	Pattern string
}

type Text string

type Tool struct {
	// Optional. Function tool type.
	// One or more function declarations to be passed to the model along with the
	// current user query. Model may decide to call a subset of these functions
	// by populating [FunctionCall][content.part.function_call] in the response.
	// User should provide a [FunctionResponse][content.part.function_response]
	// for each function call in the next turn. Based on the function responses,
	// Model will generate the final response back to the user.
	// Maximum 64 function declarations can be provided.
	FunctionDeclarations []*FunctionDeclaration
}

package main

import (
	"context"
	"fmt"
	"log"

	"cloud.google.com/go/vertexai/genai"
)

// Your GCP project
const projectID = "your-project"

// A GCP location like "us-central1"; if you're using standard Google-published
// models (like untuned Gemini models), you can keep location blank ("").
const location = "some-gcp-location"

func main() {
	ctx := context.Background()
	client, err := genai.NewClient(ctx, projectID, location)
	if err != nil {
		log.Fatal(err)
	}
	defer client.Close()

	currentWeather := func(city string) string {
		switch city {
		case "New York, NY":
			return "cold"
		case "Miami, FL":
			return "warm"
		default:
			return "unknown"
		}
	}

	// To use functions / tools, we have to first define a schema that describes
	// the function to the model. The schema is similar to OpenAPI 3.0.
	//
	// In this example, we create a single function that provides the model with
	// a weather forecast in a given location.
	schema := &genai.Schema{
		Type: genai.TypeObject,
		Properties: map[string]*genai.Schema{
			"location": {
				Type:        genai.TypeString,
				Description: "The city and state, e.g. San Francisco, CA",
			},
			"unit": {
				Type: genai.TypeString,
				Enum: []string{"celsius", "fahrenheit"},
			},
		},
		Required: []string{"location"},
	}

	weatherTool := &genai.Tool{
		FunctionDeclarations: []*genai.FunctionDeclaration{{
			Name:        "CurrentWeather",
			Description: "Get the current weather in a given location",
			Parameters:  schema,
		}},
	}

	model := client.GenerativeModel("gemini-1.0-pro")

	// Before initiating a conversation, we tell the model which tools it has
	// at its disposal.
	model.Tools = []*genai.Tool{weatherTool}

	// For using tools, the chat mode is useful because it provides the required
	// chat context. A model needs to have tools supplied to it in the chat
	// history so it can use them in subsequent conversations.
	//
	// The flow of message expected here is:
	//
	// 1. We send a question to the model
	// 2. The model recognizes that it needs to use a tool to answer the question,
	//    an returns a FunctionCall response asking to use the CurrentWeather
	//    tool.
	// 3. We send a FunctionResponse message, simulating the return value of
	//    CurrentWeather for the model's query.
	// 4. The model provides its text answer in response to this message.
	session := model.StartChat()

	res, err := session.SendMessage(ctx, genai.Text("What is the weather like in New York?"))
	if err != nil {
		log.Fatal(err)
	}

	part := res.Candidates[0].Content.Parts[0]
	funcall, ok := part.(genai.FunctionCall)
	if !ok {
		log.Fatalf("expected FunctionCall: %v", part)
	}

	if funcall.Name != "CurrentWeather" {
		log.Fatalf("expected CurrentWeather: %v", funcall.Name)
	}

	// Expect the model to pass a proper string "location" argument to the tool.
	locArg, ok := funcall.Args["location"].(string)
	if !ok {
		log.Fatalf("expected string: %v", funcall.Args["location"])
	}

	weatherData := currentWeather(locArg)
	res, err = session.SendMessage(ctx, genai.FunctionResponse{
		Name: weatherTool.FunctionDeclarations[0].Name,
		Response: map[string]any{
			"weather": weatherData,
		},
	})
	if err != nil {
		log.Fatal(err)
	}

	printResponse(res)
}

func printResponse(resp *genai.GenerateContentResponse) {
	for _, cand := range resp.Candidates {
		for _, part := range cand.Content.Parts {
			fmt.Println(part)
		}
	}
	fmt.Println("---")
}

type ToolConfig struct {
	// Optional. Function calling config.
	FunctionCallingConfig *FunctionCallingConfig
}

type Type int32

const (
	// TypeUnspecified means not specified, should not be used.
	TypeUnspecified Type = 0
	// TypeString means openAPI string type
	TypeString Type = 1
	// TypeNumber means openAPI number type
	TypeNumber Type = 2
	// TypeInteger means openAPI integer type
	TypeInteger Type = 3
	// TypeBoolean means openAPI boolean type
	TypeBoolean Type = 4
	// TypeArray means openAPI array type
	TypeArray Type = 5
	// TypeObject means openAPI object type
	TypeObject Type = 6
)

func (v Type) String() string

type UsageMetadata struct {
	// Number of tokens in the request.
	PromptTokenCount int32
	// Number of tokens in the response(s).
	CandidatesTokenCount int32
	TotalTokenCount      int32
}