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smartai/ts/provider.anthropic.ts

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import * as plugins from './plugins.js';
import * as paths from './paths.js';
import { MultiModalModel } from './abstract.classes.multimodal.js';
import type {
ChatOptions,
ChatResponse,
ChatMessage,
ResearchOptions,
ResearchResponse,
ImageGenerateOptions,
ImageEditOptions,
ImageResponse
} from './abstract.classes.multimodal.js';
import type { ImageBlockParam, TextBlockParam } from '@anthropic-ai/sdk/resources/messages';
type ContentBlock = ImageBlockParam | TextBlockParam;
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export interface IAnthropicProviderOptions {
anthropicToken: string;
enableWebSearch?: boolean;
searchDomainAllowList?: string[];
searchDomainBlockList?: string[];
}
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export class AnthropicProvider extends MultiModalModel {
private options: IAnthropicProviderOptions;
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public anthropicApiClient: plugins.anthropic.default;
constructor(optionsArg: IAnthropicProviderOptions) {
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super();
this.options = optionsArg // Ensure the token is stored
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}
async start() {
await super.start();
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this.anthropicApiClient = new plugins.anthropic.default({
apiKey: this.options.anthropicToken,
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});
}
async stop() {
await super.stop();
}
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public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
// Create a TextDecoder to handle incoming chunks
const decoder = new TextDecoder();
let buffer = '';
let currentMessage: { role: string; content: string; } | null = null;
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// Create a TransformStream to process the input
const transform = new TransformStream<Uint8Array, string>({
async transform(chunk, controller) {
buffer += decoder.decode(chunk, { stream: true });
// Try to parse complete JSON messages from the buffer
while (true) {
const newlineIndex = buffer.indexOf('\n');
if (newlineIndex === -1) break;
const line = buffer.slice(0, newlineIndex);
buffer = buffer.slice(newlineIndex + 1);
if (line.trim()) {
try {
const message = JSON.parse(line);
currentMessage = {
role: message.role || 'user',
content: message.content || '',
};
} catch (e) {
console.error('Failed to parse message:', e);
}
}
}
// If we have a complete message, send it to Anthropic
if (currentMessage) {
const stream = await this.anthropicApiClient.messages.create({
model: 'claude-sonnet-4-5-20250929',
messages: [{ role: currentMessage.role, content: currentMessage.content }],
system: '',
stream: true,
max_tokens: 4000,
});
// Process each chunk from Anthropic
for await (const chunk of stream) {
const content = chunk.delta?.text;
if (content) {
controller.enqueue(content);
}
}
currentMessage = null;
}
},
flush(controller) {
if (buffer) {
try {
const message = JSON.parse(buffer);
controller.enqueue(message.content || '');
} catch (e) {
console.error('Failed to parse remaining buffer:', e);
}
}
}
});
// Connect the input to our transform stream
return input.pipeThrough(transform);
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}
// Implementing the synchronous chat interaction
public async chat(optionsArg: ChatOptions): Promise<ChatResponse> {
// Convert message history to Anthropic format
const messages = optionsArg.messageHistory.map(msg => ({
role: msg.role === 'assistant' ? 'assistant' as const : 'user' as const,
content: msg.content
}));
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const result = await this.anthropicApiClient.messages.create({
model: 'claude-sonnet-4-5-20250929',
system: optionsArg.systemMessage,
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messages: [
...messages,
{ role: 'user' as const, content: optionsArg.userMessage }
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],
max_tokens: 4000,
});
// Extract text content from the response
let message = '';
for (const block of result.content) {
if ('text' in block) {
message += block.text;
}
}
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return {
role: 'assistant' as const,
message,
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};
}
public async audio(optionsArg: { message: string }): Promise<NodeJS.ReadableStream> {
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// Anthropic does not provide an audio API, so this method is not implemented.
throw new Error('Audio generation is not yet supported by Anthropic.');
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}
public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
const base64Image = optionsArg.image.toString('base64');
const content: ContentBlock[] = [
{
type: 'text',
text: optionsArg.prompt
},
{
type: 'image',
source: {
type: 'base64',
media_type: 'image/jpeg',
data: base64Image
}
}
];
const result = await this.anthropicApiClient.messages.create({
model: 'claude-sonnet-4-5-20250929',
messages: [{
role: 'user',
content
}],
max_tokens: 1024
});
// Extract text content from the response
let message = '';
for (const block of result.content) {
if ('text' in block) {
message += block.text;
}
}
return message;
}
public async document(optionsArg: {
systemMessage: string;
userMessage: string;
pdfDocuments: Uint8Array[];
messageHistory: ChatMessage[];
}): Promise<{ message: any }> {
// Convert PDF documents to images using SmartPDF
let documentImageBytesArray: Uint8Array[] = [];
for (const pdfDocument of optionsArg.pdfDocuments) {
const documentImageArray = await this.smartpdfInstance.convertPDFToPngBytes(pdfDocument);
documentImageBytesArray = documentImageBytesArray.concat(documentImageArray);
}
// Convert message history to Anthropic format
const messages = optionsArg.messageHistory.map(msg => ({
role: msg.role === 'assistant' ? 'assistant' as const : 'user' as const,
content: msg.content
}));
// Create content array with text and images
const content: ContentBlock[] = [
{
type: 'text',
text: optionsArg.userMessage
}
];
// Add each document page as an image
for (const imageBytes of documentImageBytesArray) {
content.push({
type: 'image',
source: {
type: 'base64',
media_type: 'image/png',
data: Buffer.from(imageBytes).toString('base64')
}
});
}
const result = await this.anthropicApiClient.messages.create({
model: 'claude-sonnet-4-5-20250929',
system: optionsArg.systemMessage,
messages: [
...messages,
{ role: 'user', content }
],
max_tokens: 4096
});
// Extract text content from the response
let message = '';
for (const block of result.content) {
if ('text' in block) {
message += block.text;
}
}
return {
message: {
role: 'assistant',
content: message
}
};
}
public async research(optionsArg: ResearchOptions): Promise<ResearchResponse> {
// Prepare the messages for the research request
const systemMessage = `You are a research assistant with web search capabilities.
Provide comprehensive, well-researched answers with citations and sources.
When searching the web, be thorough and cite your sources accurately.`;
try {
// Build the tool configuration for web search
const tools: any[] = [];
if (this.options.enableWebSearch) {
const webSearchTool: any = {
type: 'web_search_20250305',
name: 'web_search'
};
// Add optional parameters
if (optionsArg.maxSources) {
webSearchTool.max_uses = optionsArg.maxSources;
}
if (this.options.searchDomainAllowList?.length) {
webSearchTool.allowed_domains = this.options.searchDomainAllowList;
} else if (this.options.searchDomainBlockList?.length) {
webSearchTool.blocked_domains = this.options.searchDomainBlockList;
}
tools.push(webSearchTool);
}
// Configure the request based on search depth
const maxTokens = optionsArg.searchDepth === 'deep' ? 8192 :
optionsArg.searchDepth === 'advanced' ? 6144 : 4096;
// Create the research request
const requestParams: any = {
model: 'claude-sonnet-4-5-20250929',
system: systemMessage,
messages: [
{
role: 'user' as const,
content: optionsArg.query
}
],
max_tokens: maxTokens,
temperature: 0.7
};
// Add tools if web search is enabled
if (tools.length > 0) {
requestParams.tools = tools;
}
// Execute the research request
const result = await this.anthropicApiClient.messages.create(requestParams);
// Extract the answer from content blocks
let answer = '';
const sources: Array<{ url: string; title: string; snippet: string }> = [];
const searchQueries: string[] = [];
// Process content blocks
for (const block of result.content) {
if ('text' in block) {
// Accumulate text content
answer += block.text;
// Extract citations if present
if ('citations' in block && Array.isArray(block.citations)) {
for (const citation of block.citations) {
if (citation.type === 'web_search_result_location') {
sources.push({
title: citation.title || '',
url: citation.url || '',
snippet: citation.cited_text || ''
});
}
}
}
} else if ('type' in block && block.type === 'server_tool_use') {
// Extract search queries from server tool use
if (block.name === 'web_search' && block.input && typeof block.input === 'object' && 'query' in block.input) {
searchQueries.push((block.input as any).query);
}
} else if ('type' in block && block.type === 'web_search_tool_result') {
// Extract sources from web search results
if (Array.isArray(block.content)) {
for (const result of block.content) {
if (result.type === 'web_search_result') {
// Only add if not already in sources (avoid duplicates from citations)
if (!sources.some(s => s.url === result.url)) {
sources.push({
title: result.title || '',
url: result.url || '',
snippet: '' // Search results don't include snippets, only citations do
});
}
}
}
}
}
}
// Fallback: Parse markdown-style links if no citations found
if (sources.length === 0) {
const urlRegex = /\[([^\]]+)\]\(([^)]+)\)/g;
let match: RegExpExecArray | null;
while ((match = urlRegex.exec(answer)) !== null) {
sources.push({
title: match[1],
url: match[2],
snippet: ''
});
}
}
// Check if web search was used based on usage info
const webSearchCount = result.usage?.server_tool_use?.web_search_requests || 0;
return {
answer,
sources,
searchQueries: searchQueries.length > 0 ? searchQueries : undefined,
metadata: {
model: 'claude-sonnet-4-5-20250929',
searchDepth: optionsArg.searchDepth || 'basic',
tokensUsed: result.usage?.output_tokens,
webSearchesPerformed: webSearchCount
}
};
} catch (error) {
console.error('Anthropic research error:', error);
throw new Error(`Failed to perform research: ${error.message}`);
}
}
/**
* Image generation is not supported by Anthropic
*/
public async imageGenerate(optionsArg: ImageGenerateOptions): Promise<ImageResponse> {
throw new Error('Image generation is not supported by Anthropic. Claude can only analyze images, not generate them. Please use OpenAI provider for image generation.');
}
/**
* Image editing is not supported by Anthropic
*/
public async imageEdit(optionsArg: ImageEditOptions): Promise<ImageResponse> {
throw new Error('Image editing is not supported by Anthropic. Claude can only analyze images, not edit them. Please use OpenAI provider for image editing.');
}
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}