mirror of
https://github.com/Mintplex-Labs/anything-llm.git
synced 2024-11-14 02:20:12 +01:00
125 lines
3.6 KiB
JavaScript
125 lines
3.6 KiB
JavaScript
const OpenAI = require("openai");
|
|
const Provider = require("./ai-provider.js");
|
|
const InheritMultiple = require("./helpers/classes.js");
|
|
const UnTooled = require("./helpers/untooled.js");
|
|
const { toValidNumber } = require("../../../http/index.js");
|
|
|
|
/**
|
|
* The agent provider for the Generic OpenAI provider.
|
|
* Since we cannot promise the generic provider even supports tool calling
|
|
* which is nearly 100% likely it does not, we can just wrap it in untooled
|
|
* which often is far better anyway.
|
|
*/
|
|
class GenericOpenAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
|
model;
|
|
|
|
constructor(config = {}) {
|
|
super();
|
|
const { model = "gpt-3.5-turbo" } = config;
|
|
const client = new OpenAI({
|
|
baseURL: process.env.GENERIC_OPEN_AI_BASE_PATH,
|
|
apiKey: process.env.GENERIC_OPEN_AI_API_KEY ?? null,
|
|
maxRetries: 3,
|
|
});
|
|
|
|
this._client = client;
|
|
this.model = model;
|
|
this.verbose = true;
|
|
this.maxTokens = process.env.GENERIC_OPEN_AI_MAX_TOKENS
|
|
? toValidNumber(process.env.GENERIC_OPEN_AI_MAX_TOKENS, 1024)
|
|
: 1024;
|
|
}
|
|
|
|
get client() {
|
|
return this._client;
|
|
}
|
|
|
|
async #handleFunctionCallChat({ messages = [] }) {
|
|
return await this.client.chat.completions
|
|
.create({
|
|
model: this.model,
|
|
temperature: 0,
|
|
messages,
|
|
max_tokens: this.maxTokens,
|
|
})
|
|
.then((result) => {
|
|
if (!result.hasOwnProperty("choices"))
|
|
throw new Error("Generic OpenAI chat: No results!");
|
|
if (result.choices.length === 0)
|
|
throw new Error("Generic OpenAI chat: No results length!");
|
|
return result.choices[0].message.content;
|
|
})
|
|
.catch((_) => {
|
|
return null;
|
|
});
|
|
}
|
|
|
|
/**
|
|
* Create a completion based on the received messages.
|
|
*
|
|
* @param messages A list of messages to send to the API.
|
|
* @param functions
|
|
* @returns The completion.
|
|
*/
|
|
async complete(messages, functions = null) {
|
|
try {
|
|
let completion;
|
|
if (functions.length > 0) {
|
|
const { toolCall, text } = await this.functionCall(
|
|
messages,
|
|
functions,
|
|
this.#handleFunctionCallChat.bind(this)
|
|
);
|
|
|
|
if (toolCall !== null) {
|
|
this.providerLog(`Valid tool call found - running ${toolCall.name}.`);
|
|
this.deduplicator.trackRun(toolCall.name, toolCall.arguments);
|
|
return {
|
|
result: null,
|
|
functionCall: {
|
|
name: toolCall.name,
|
|
arguments: toolCall.arguments,
|
|
},
|
|
cost: 0,
|
|
};
|
|
}
|
|
completion = { content: text };
|
|
}
|
|
|
|
if (!completion?.content) {
|
|
this.providerLog(
|
|
"Will assume chat completion without tool call inputs."
|
|
);
|
|
const response = await this.client.chat.completions.create({
|
|
model: this.model,
|
|
messages: this.cleanMsgs(messages),
|
|
});
|
|
completion = response.choices[0].message;
|
|
}
|
|
|
|
// The UnTooled class inherited Deduplicator is mostly useful to prevent the agent
|
|
// from calling the exact same function over and over in a loop within a single chat exchange
|
|
// _but_ we should enable it to call previously used tools in a new chat interaction.
|
|
this.deduplicator.reset("runs");
|
|
return {
|
|
result: completion.content,
|
|
cost: 0,
|
|
};
|
|
} catch (error) {
|
|
throw error;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Get the cost of the completion.
|
|
*
|
|
* @param _usage The completion to get the cost for.
|
|
* @returns The cost of the completion.
|
|
*/
|
|
getCost(_usage) {
|
|
return 0;
|
|
}
|
|
}
|
|
|
|
module.exports = GenericOpenAiProvider;
|