multi-llm
Version:
A unified TypeScript/JavaScript package to use LLMs across ALL platforms with support for 17 major providers, streaming, MCP tools, and intelligent response parsing
122 lines • 5 kB
JavaScript
;
var __importDefault = (this && this.__importDefault) || function (mod) {
return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.CerebrasProvider = void 0;
const axios_1 = __importDefault(require("axios"));
const provider_1 = require("../provider");
const llm_1 = require("../llm");
const parser_1 = require("../utils/parser");
class CerebrasProvider extends provider_1.Provider {
constructor(apiKey, baseUrl) {
super(apiKey, baseUrl);
this.baseUrl = baseUrl || 'https://api.cerebras.ai/v1';
}
async getModels() {
// Cerebras doesn't have a models endpoint, so we return known models
return [
{
id: 'llama3.1-8b',
name: 'Llama 3.1 8B',
contextWindow: 128000,
maxOutputTokens: 8192,
pricing: { input: 0.00010, output: 0.00010, currency: 'USD' }
},
{
id: 'llama3.1-70b',
name: 'Llama 3.1 70B',
contextWindow: 128000,
maxOutputTokens: 8192,
pricing: { input: 0.00060, output: 0.00060, currency: 'USD' }
}
];
}
createLLM(modelId) {
return new llm_1.LLM(this, modelId);
}
async chat(modelId, messages, options, streamCallback) {
try {
const payload = {
model: modelId,
messages: messages.map(msg => ({ role: msg.role, content: msg.content })),
temperature: options.temperature,
max_tokens: options.maxTokens,
top_p: options.topP,
stream: !!streamCallback
};
if (streamCallback) {
return this.streamChat(payload, streamCallback);
}
else {
const response = await axios_1.default.post(`${this.baseUrl}/chat/completions`, payload, {
headers: {
'Authorization': `Bearer ${this.apiKey}`,
'Content-Type': 'application/json'
}
});
const content = response.data.choices[0].message.content;
const parsed = parser_1.ResponseParser.parseResponse(content);
return {
raw: response.data,
parsed,
usage: {
inputTokens: response.data.usage?.prompt_tokens || 0,
outputTokens: response.data.usage?.completion_tokens || 0,
totalTokens: response.data.usage?.total_tokens || 0
}
};
}
}
catch (error) {
throw new Error(`Cerebras chat failed: ${error}`);
}
}
async streamChat(payload, streamCallback) {
return new Promise((resolve, reject) => {
let fullContent = '';
let rawResponse = null;
const source = axios_1.default.post(`${this.baseUrl}/chat/completions`, payload, {
headers: {
'Authorization': `Bearer ${this.apiKey}`,
'Content-Type': 'application/json'
},
responseType: 'stream'
});
source.then(response => {
response.data.on('data', (chunk) => {
const lines = chunk.toString().split('\n');
for (const line of lines) {
if (line.startsWith('data: ')) {
const data = line.slice(6);
if (data === '[DONE]') {
const parsed = parser_1.ResponseParser.parseResponse(fullContent);
resolve({
raw: rawResponse,
parsed,
usage: undefined
});
return;
}
try {
const parsed = JSON.parse(data);
rawResponse = parsed;
const content = parsed.choices[0]?.delta?.content || '';
if (content) {
fullContent += content;
streamCallback(content);
}
}
catch (e) {
// Ignore parsing errors for partial chunks
}
}
}
});
response.data.on('error', reject);
}).catch(reject);
});
}
}
exports.CerebrasProvider = CerebrasProvider;
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