anything-llm/server/utils/AiProviders/openRouter/index.js

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const { NativeEmbedder } = require("../../EmbeddingEngines/native");
const { v4: uuidv4 } = require("uuid");
const {
writeResponseChunk,
clientAbortedHandler,
} = require("../../helpers/chat/responses");
const fs = require("fs");
const path = require("path");
const { safeJsonParse } = require("../../http");
const cacheFolder = path.resolve(
process.env.STORAGE_DIR
? path.resolve(process.env.STORAGE_DIR, "models", "openrouter")
: path.resolve(__dirname, `../../../storage/models/openrouter`)
);
class OpenRouterLLM {
constructor(embedder = null, modelPreference = null) {
if (!process.env.OPENROUTER_API_KEY)
throw new Error("No OpenRouter API key was set.");
const { OpenAI: OpenAIApi } = require("openai");
this.basePath = "https://openrouter.ai/api/v1";
this.openai = new OpenAIApi({
baseURL: this.basePath,
apiKey: process.env.OPENROUTER_API_KEY ?? null,
defaultHeaders: {
"HTTP-Referer": "https://useanything.com",
"X-Title": "AnythingLLM",
},
});
this.model =
modelPreference || process.env.OPENROUTER_MODEL_PREF || "openrouter/auto";
this.limits = {
history: this.promptWindowLimit() * 0.15,
system: this.promptWindowLimit() * 0.15,
user: this.promptWindowLimit() * 0.7,
};
this.embedder = embedder ?? new NativeEmbedder();
this.defaultTemp = 0.7;
if (!fs.existsSync(cacheFolder))
fs.mkdirSync(cacheFolder, { recursive: true });
this.cacheModelPath = path.resolve(cacheFolder, "models.json");
this.cacheAtPath = path.resolve(cacheFolder, ".cached_at");
}
log(text, ...args) {
console.log(`\x1b[36m[${this.constructor.name}]\x1b[0m ${text}`, ...args);
}
// This checks if the .cached_at file has a timestamp that is more than 1Week (in millis)
// from the current date. If it is, then we will refetch the API so that all the models are up
// to date.
#cacheIsStale() {
const MAX_STALE = 6.048e8; // 1 Week in MS
if (!fs.existsSync(this.cacheAtPath)) return true;
const now = Number(new Date());
const timestampMs = Number(fs.readFileSync(this.cacheAtPath));
return now - timestampMs > MAX_STALE;
}
// The OpenRouter model API has a lot of models, so we cache this locally in the directory
// as if the cache directory JSON file is stale or does not exist we will fetch from API and store it.
// This might slow down the first request, but we need the proper token context window
// for each model and this is a constructor property - so we can really only get it if this cache exists.
// We used to have this as a chore, but given there is an API to get the info - this makes little sense.
async #syncModels() {
if (fs.existsSync(this.cacheModelPath) && !this.#cacheIsStale())
return false;
this.log(
"Model cache is not present or stale. Fetching from OpenRouter API."
);
await fetchOpenRouterModels();
return;
}
#appendContext(contextTexts = []) {
if (!contextTexts || !contextTexts.length) return "";
return (
"\nContext:\n" +
contextTexts
.map((text, i) => {
return `[CONTEXT ${i}]:\n${text}\n[END CONTEXT ${i}]\n\n`;
})
.join("")
);
}
models() {
if (!fs.existsSync(this.cacheModelPath)) return {};
return safeJsonParse(
fs.readFileSync(this.cacheModelPath, { encoding: "utf-8" }),
{}
);
}
streamingEnabled() {
return "streamGetChatCompletion" in this;
}
promptWindowLimit() {
const availableModels = this.models();
return availableModels[this.model]?.maxLength || 4096;
}
async isValidChatCompletionModel(model = "") {
await this.#syncModels();
const availableModels = this.models();
return availableModels.hasOwnProperty(model);
}
constructPrompt({
systemPrompt = "",
contextTexts = [],
chatHistory = [],
userPrompt = "",
}) {
const prompt = {
role: "system",
content: `${systemPrompt}${this.#appendContext(contextTexts)}`,
};
return [prompt, ...chatHistory, { role: "user", content: userPrompt }];
}
async isSafe(_input = "") {
// Not implemented so must be stubbed
return { safe: true, reasons: [] };
}
async getChatCompletion(messages = null, { temperature = 0.7 }) {
if (!(await this.isValidChatCompletionModel(this.model)))
throw new Error(
`OpenRouter chat: ${this.model} is not valid for chat completion!`
);
const result = await this.openai.chat.completions
.create({
model: this.model,
messages,
temperature,
})
.catch((e) => {
throw new Error(e.response.data.error.message);
});
if (!result.hasOwnProperty("choices") || result.choices.length === 0)
return null;
return result.choices[0].message.content;
}
async streamGetChatCompletion(messages = null, { temperature = 0.7 }) {
if (!(await this.isValidChatCompletionModel(this.model)))
throw new Error(
`OpenRouter chat: ${this.model} is not valid for chat completion!`
);
const streamRequest = await this.openai.chat.completions.create({
model: this.model,
stream: true,
messages,
temperature,
});
return streamRequest;
}
handleStream(response, stream, responseProps) {
const timeoutThresholdMs = 500;
const { uuid = uuidv4(), sources = [] } = responseProps;
return new Promise(async (resolve) => {
let fullText = "";
let lastChunkTime = null; // null when first token is still not received.
// Establish listener to early-abort a streaming response
// in case things go sideways or the user does not like the response.
// We preserve the generated text but continue as if chat was completed
// to preserve previously generated content.
const handleAbort = () => clientAbortedHandler(resolve, fullText);
response.on("close", handleAbort);
// NOTICE: Not all OpenRouter models will return a stop reason
// which keeps the connection open and so the model never finalizes the stream
// like the traditional OpenAI response schema does. So in the case the response stream
// never reaches a formal close state we maintain an interval timer that if we go >=timeoutThresholdMs with
// no new chunks then we kill the stream and assume it to be complete. OpenRouter is quite fast
// so this threshold should permit most responses, but we can adjust `timeoutThresholdMs` if
// we find it is too aggressive.
const timeoutCheck = setInterval(() => {
if (lastChunkTime === null) return;
const now = Number(new Date());
const diffMs = now - lastChunkTime;
if (diffMs >= timeoutThresholdMs) {
console.log(
`OpenRouter stream did not self-close and has been stale for >${timeoutThresholdMs}ms. Closing response stream.`
);
writeResponseChunk(response, {
uuid,
sources,
type: "textResponseChunk",
textResponse: "",
close: true,
error: false,
});
clearInterval(timeoutCheck);
response.removeListener("close", handleAbort);
resolve(fullText);
}
}, 500);
for await (const chunk of stream) {
const message = chunk?.choices?.[0];
const token = message?.delta?.content;
lastChunkTime = Number(new Date());
if (token) {
fullText += token;
writeResponseChunk(response, {
uuid,
sources: [],
type: "textResponseChunk",
textResponse: token,
close: false,
error: false,
});
}
if (message.finish_reason !== null) {
writeResponseChunk(response, {
uuid,
sources,
type: "textResponseChunk",
textResponse: "",
close: true,
error: false,
});
response.removeListener("close", handleAbort);
resolve(fullText);
}
}
});
}
// Simple wrapper for dynamic embedder & normalize interface for all LLM implementations
async embedTextInput(textInput) {
return await this.embedder.embedTextInput(textInput);
}
async embedChunks(textChunks = []) {
return await this.embedder.embedChunks(textChunks);
}
async compressMessages(promptArgs = {}, rawHistory = []) {
const { messageArrayCompressor } = require("../../helpers/chat");
const messageArray = this.constructPrompt(promptArgs);
return await messageArrayCompressor(this, messageArray, rawHistory);
}
}
async function fetchOpenRouterModels() {
return await fetch(`https://openrouter.ai/api/v1/models`, {
method: "GET",
headers: {
"Content-Type": "application/json",
},
})
.then((res) => res.json())
.then(({ data = [] }) => {
const models = {};
data.forEach((model) => {
models[model.id] = {
id: model.id,
name: model.name,
organization:
model.id.split("/")[0].charAt(0).toUpperCase() +
model.id.split("/")[0].slice(1),
maxLength: model.context_length,
};
});
// Cache all response information
if (!fs.existsSync(cacheFolder))
fs.mkdirSync(cacheFolder, { recursive: true });
fs.writeFileSync(
path.resolve(cacheFolder, "models.json"),
JSON.stringify(models),
{
encoding: "utf-8",
}
);
fs.writeFileSync(
path.resolve(cacheFolder, ".cached_at"),
String(Number(new Date())),
{
encoding: "utf-8",
}
);
return models;
})
.catch((e) => {
console.error(e);
return {};
});
}
module.exports = {
OpenRouterLLM,
fetchOpenRouterModels,
};