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anthropicllm.go
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anthropicllm.go
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package anthropic
import (
"context"
"errors"
"fmt"
"net/http"
"os"
"github.com/tmc/langchaingo/callbacks"
"github.com/tmc/langchaingo/llms"
"github.com/tmc/langchaingo/llms/anthropic/internal/anthropicclient"
)
var (
ErrEmptyResponse = errors.New("no response")
ErrMissingToken = errors.New("missing the Anthropic API key, set it in the ANTHROPIC_API_KEY environment variable")
ErrUnexpectedResponseLength = errors.New("unexpected length of response")
)
const (
RoleUser = "user"
RoleAssistant = "assistant"
RoleSystem = "system"
)
type LLM struct {
CallbacksHandler callbacks.Handler
client *anthropicclient.Client
}
var _ llms.Model = (*LLM)(nil)
// New returns a new Anthropic LLM.
func New(opts ...Option) (*LLM, error) {
c, err := newClient(opts...)
return &LLM{
client: c,
}, err
}
func newClient(opts ...Option) (*anthropicclient.Client, error) {
options := &options{
token: os.Getenv(tokenEnvVarName),
baseURL: anthropicclient.DefaultBaseURL,
httpClient: http.DefaultClient,
}
for _, opt := range opts {
opt(options)
}
if len(options.token) == 0 {
return nil, ErrMissingToken
}
return anthropicclient.New(options.token, options.model, options.baseURL,
anthropicclient.WithHTTPClient(options.httpClient),
anthropicclient.WithLegacyTextCompletionsAPI(options.useLegacyTextCompletionsAPI),
)
}
// Call requests a completion for the given prompt.
func (o *LLM) Call(ctx context.Context, prompt string, options ...llms.CallOption) (string, error) {
return llms.GenerateFromSinglePrompt(ctx, o, prompt, options...)
}
// GenerateContent implements the Model interface.
func (o *LLM) GenerateContent(ctx context.Context, messages []llms.MessageContent, options ...llms.CallOption) (*llms.ContentResponse, error) {
if o.CallbacksHandler != nil {
o.CallbacksHandler.HandleLLMGenerateContentStart(ctx, messages)
}
opts := &llms.CallOptions{}
for _, opt := range options {
opt(opts)
}
if o.client.UseLegacyTextCompletionsAPI {
return generateCompletionsContent(ctx, o, messages, opts)
}
return generateMessagesContent(ctx, o, messages, opts)
}
func generateCompletionsContent(ctx context.Context, o *LLM, messages []llms.MessageContent, opts *llms.CallOptions) (*llms.ContentResponse, error) {
msg0 := messages[0]
part := msg0.Parts[0]
partText, ok := part.(llms.TextContent)
if !ok {
return nil, fmt.Errorf("unexpected message type: %T", part)
}
prompt := fmt.Sprintf("\n\nHuman: %s\n\nAssistant:", partText.Text)
result, err := o.client.CreateCompletion(ctx, &anthropicclient.CompletionRequest{
Model: opts.Model,
Prompt: prompt,
MaxTokens: opts.MaxTokens,
StopWords: opts.StopWords,
Temperature: opts.Temperature,
TopP: opts.TopP,
StreamingFunc: opts.StreamingFunc,
})
if err != nil {
if o.CallbacksHandler != nil {
o.CallbacksHandler.HandleLLMError(ctx, err)
}
return nil, err
}
resp := &llms.ContentResponse{
Choices: []*llms.ContentChoice{
{
Content: result.Text,
},
},
}
return resp, nil
}
func generateMessagesContent(ctx context.Context, o *LLM, messages []llms.MessageContent, opts *llms.CallOptions) (*llms.ContentResponse, error) {
chatMessages, systemPrompt, err := processMessages(messages)
if err != nil {
return nil, err
}
result, err := o.client.CreateMessage(ctx, &anthropicclient.MessageRequest{
Model: opts.Model,
Messages: chatMessages,
System: systemPrompt,
MaxTokens: opts.MaxTokens,
StopWords: opts.StopWords,
Temperature: opts.Temperature,
TopP: opts.TopP,
StreamingFunc: opts.StreamingFunc,
})
if err != nil {
if o.CallbacksHandler != nil {
o.CallbacksHandler.HandleLLMError(ctx, err)
}
return nil, err
}
choices := make([]*llms.ContentChoice, len(result.Content))
for i, content := range result.Content {
choices[i] = &llms.ContentChoice{
Content: content.Text,
StopReason: result.StopReason,
GenerationInfo: map[string]any{
"InputTokens": result.Usage.InputTokens,
"OutputTokens": result.Usage.OutputTokens,
},
}
}
resp := &llms.ContentResponse{
Choices: choices,
}
return resp, nil
}
func processMessages(messages []llms.MessageContent) ([]anthropicclient.ChatMessage, string, error) {
chatMessages := make([]anthropicclient.ChatMessage, 0, len(messages))
systemPrompt := ""
for _, msg := range messages {
switch msg.Role {
case llms.ChatMessageTypeSystem:
content, err := handleSystemMessage(msg)
if err != nil {
return nil, "", err
}
systemPrompt += content
case llms.ChatMessageTypeHuman:
chatMessage, err := handleHumanMessage(msg)
if err != nil {
return nil, "", err
}
chatMessages = append(chatMessages, chatMessage)
case llms.ChatMessageTypeAI:
chatMessage, err := handleAIMessage(msg)
if err != nil {
return nil, "", err
}
chatMessages = append(chatMessages, chatMessage)
case llms.ChatMessageTypeGeneric, llms.ChatMessageTypeFunction, llms.ChatMessageTypeTool:
return nil, "", fmt.Errorf("unsupported message type: %v", msg.Role)
default:
return nil, "", fmt.Errorf("unsupported message type: %v", msg.Role)
}
}
return chatMessages, systemPrompt, nil
}
func handleSystemMessage(msg llms.MessageContent) (string, error) {
if textContent, ok := msg.Parts[0].(llms.TextContent); ok {
return textContent.Text, nil
}
return "", errors.New("invalid content type for system message")
}
func handleHumanMessage(msg llms.MessageContent) (anthropicclient.ChatMessage, error) {
if textContent, ok := msg.Parts[0].(llms.TextContent); ok {
return anthropicclient.ChatMessage{
Role: RoleUser,
Content: textContent.Text,
}, nil
}
return anthropicclient.ChatMessage{}, errors.New("invalid content type for human message")
}
func handleAIMessage(msg llms.MessageContent) (anthropicclient.ChatMessage, error) {
if textContent, ok := msg.Parts[0].(llms.TextContent); ok {
return anthropicclient.ChatMessage{
Role: RoleAssistant,
Content: textContent.Text,
}, nil
}
return anthropicclient.ChatMessage{}, errors.New("invalid content type for AI message")
}