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import { AnthropicMessageRequest, AnthropicMessageResponse } from "./types.js";
import { ToolCall } from "../../chat/Tool.js";
import { Capabilities } from "./Capabilities.js";
import { handleAnthropicError } from "./Errors.js";
import { ModelRegistry } from "../../models/ModelRegistry.js";
import { logger } from "../../utils/logger.js";
import { fetchWithTimeout } from "../../utils/fetch.js";
import { formatSystemPrompt, formatMessages } from "./Utils.js";
export class AnthropicChat {
constructor(
private readonly baseUrl: string,
private readonly apiKey: string
) {}
async execute(request: ChatRequest): Promise<ChatResponse> {
const model = request.model;
const maxTokens = request.max_tokens || Capabilities.getMaxOutputTokens(model) || 4096;
const systemPrompt = formatSystemPrompt(request.messages);
const messages = formatMessages(request.messages);
let system = systemPrompt;
if (request.response_format) {
let schemaText = "";
Eif (
request.response_format.type === "json_schema" &&
request.response_format.json_schema?.schema
) {
schemaText =
"\nSchema:\n" + JSON.stringify(request.response_format.json_schema.schema, null, 2);
}
const instruction = `CRITICAL: Respond ONLY with a valid JSON object matching the requested schema.${schemaText}\n\nDo not include any other text or explanation.`;
system = system ? `${system}\n\n${instruction}` : instruction;
}
const {
model: _model,
messages: _messages,
tools: _tools,
temperature: _temp,
max_tokens: _max,
response_format: _format,
thinking: _thinking,
headers: _headers,
requestTimeout,
...rest
} = request;
const body: AnthropicMessageRequest = {
model: model,
messages: messages,
max_tokens: maxTokens,
system: system,
stream: false,
...rest
};
Iif (_thinking?.budget) {
body.thinking = {
type: "enabled",
budget_tokens: _thinking.budget
};
// Extended thinking models require a larger max_tokens
if (!request.max_tokens) {
body.max_tokens = Math.max(maxTokens, _thinking.budget + 1024);
}
}
Iif (request.temperature !== undefined) {
body.temperature = request.temperature;
}
// Map tools
if (request.tools && request.tools.length > 0) {
body.tools = request.tools.map((tool) => ({
name: tool.function.name,
description: tool.function.description,
input_schema: tool.function.parameters
}));
}
// Check if any message contains PDF content to add beta header
const hasPdf = messages.some(
(msg) => Array.isArray(msg.content) && msg.content.some((block) => block.type === "document")
);
const headers: Record<string, string> = {
"x-api-key": this.apiKey,
"anthropic-version": "2023-06-01",
"content-type": "application/json",
...request.headers
};
if (hasPdf) {
headers["anthropic-beta"] = "pdfs-2024-09-25";
}
const url = `${this.baseUrl}/messages`;
logger.logRequest("Anthropic", "POST", url, body);
const response = await fetchWithTimeout(
url,
{
method: "POST",
headers: headers,
body: JSON.stringify(body)
},
requestTimeout
);
if (!response.ok) {
await handleAnthropicError(response, model);
}
const json = (await response.json()) as AnthropicMessageResponse;
logger.logResponse("Anthropic", response.status, response.statusText, json);
const contentBlocks = json.content;
// Extract text content and tool calls
let content: string | null = null;
let thinkingResult: ThinkingResult | undefined = undefined;
const toolCalls: ToolCall[] = [];
for (const block of contentBlocks) {
if (block.type === "text") {
Eif (content === null) content = "";
content += block.text;
I} else if (block.type === "thinking") {
// Handle thinking block (Claude 3.7)
if (!thinkingResult) thinkingResult = { text: "" };
if (block.thinking) {
thinkingResult.text = (thinkingResult.text || "") + block.thinking;
}
if (block.signature) thinkingResult.signature = block.signature;
E} else if (block.type === "tool_use") {
toolCalls.push({
id: block.id!,
type: "function",
function: {
name: block.name!,
arguments: JSON.stringify(block.input)
}
});
}
}
const usage = json.usage
? {
input_tokens: json.usage.input_tokens,
output_tokens: json.usage.output_tokens,
total_tokens: json.usage.input_tokens + json.usage.output_tokens,
cached_tokens: json.usage.cache_read_input_tokens,
cache_creation_tokens: json.usage.cache_creation_input_tokens
}
: undefined;
const calculatedUsage = usage
? ModelRegistry.calculateCost(usage, model, "anthropic")
: undefined;
return {
content,
usage: calculatedUsage,
thinking: thinkingResult,
tool_calls: toolCalls.length > 0 ? toolCalls : undefined
};
}
}
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