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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,250 @@ | ||
| import React from "react"; | ||
| import LangchainBase from "./base"; | ||
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| import LLMProviderInterface, { LLMConfig } from "../interface"; | ||
| import { IconExternalLink } from "@tabler/icons-react"; | ||
| import { HeaderEditor, ModelsHandler } from "../utils"; | ||
| import debug from "debug"; | ||
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| import { AI_MODELS, Input, Message, SettingItem, useGlobal } from "../refs"; | ||
| import { OpenAIChatInput } from "@langchain/openai"; | ||
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| const logger = debug("textgenerator:llmProvider:openaiChat"); | ||
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| const default_values = { | ||
| basePath: "https://api.openai.com/v1", | ||
| model: "o1-mini", | ||
| }; | ||
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| export default class LangchainOpenAIChatProvider | ||
| extends LangchainBase | ||
| implements LLMProviderInterface { | ||
| /** for models to know what provider is that, for example if this class is being extended. and the id changes. */ | ||
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| static provider = "Langchain"; | ||
| static id = "OpenAI Agent (Langchain)" as const; | ||
| static slug = "openAIAgent" as const; | ||
| static displayName = "OpenAI Agent"; | ||
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| id = LangchainOpenAIChatProvider.id; | ||
| provider = LangchainOpenAIChatProvider.provider; | ||
| originalId = LangchainOpenAIChatProvider.id; | ||
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| async load() { | ||
| const { ChatOpenAI } = await import("@langchain/openai"); | ||
| this.llmClass = ChatOpenAI; | ||
| } | ||
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| getConfig(options: LLMConfig) { | ||
| return this.cleanConfig({ | ||
| openAIApiKey: options.api_key, | ||
|
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| // ------------Necessary stuff-------------- | ||
| modelKwargs: options.modelKwargs, | ||
| modelName: options.model, | ||
| // frequencyPenalty: +options.frequency_penalty || 0, | ||
| presencePenalty: +options.presence_penalty || 0, | ||
| n: options.n || 1, | ||
| stop: options.stop || undefined, | ||
| streaming: options.stream || false, | ||
| maxRetries: 3, | ||
| headers: options.headers || undefined, | ||
|
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| bodyParams: { | ||
| max_completion_tokens: +options.max_tokens, | ||
| }, | ||
| } as Partial<OpenAIChatInput>); | ||
| } | ||
|
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|
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| // getLLM(options: LLMConfig) { | ||
| // return new ChatOpenAI({ | ||
| // ...this.getConfig(options), | ||
| // }); | ||
| // } | ||
|
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| RenderSettings(props: Parameters<LLMProviderInterface["RenderSettings"]>[0]) { | ||
| const global = useGlobal(); | ||
|
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| const id = props.self.id; | ||
| const config = (global.plugin.settings.LLMProviderOptions[id] ??= { | ||
| ...default_values, | ||
| }); | ||
|
|
||
| return ( | ||
| <React.Fragment key={id}> | ||
| <SettingItem | ||
| name="API Key" | ||
| register={props.register} | ||
| sectionId={props.sectionId} | ||
| > | ||
| <Input | ||
| type="password" | ||
| value={config.api_key || ""} | ||
| setValue={async (value) => { | ||
| if (props.self.originalId == id) | ||
| global.plugin.settings.api_key = value; | ||
| config.api_key = value; | ||
|
|
||
| global.triggerReload(); | ||
| global.plugin.encryptAllKeys(); | ||
| // TODO: it could use a debounce here | ||
| await global.plugin.saveSettings(); | ||
| }} | ||
| /> | ||
| </SettingItem> | ||
| <SettingItem | ||
| name="Base Path" | ||
| description={`Make sure it supports CORS`} | ||
| register={props.register} | ||
| sectionId={props.sectionId} | ||
| > | ||
| <Input | ||
| value={config.basePath || default_values.basePath} | ||
| placeholder="Enter your API Base Path" | ||
| setValue={async (value) => { | ||
| config.basePath = value || default_values.basePath; | ||
| global.plugin.settings.endpoint = | ||
| value || default_values.basePath; | ||
| global.triggerReload(); | ||
| // TODO: it could use a debounce here | ||
| await global.plugin.saveSettings(); | ||
| }} | ||
| /> | ||
| </SettingItem> | ||
|
|
||
| <ModelsHandler | ||
| register={props.register} | ||
| sectionId={props.sectionId} | ||
| llmProviderId={props.self.originalId || id} | ||
| default_values={default_values} | ||
| config={config} | ||
| /> | ||
|
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||
| <HeaderEditor | ||
| enabled={!!config.headers} | ||
| setEnabled={async (value) => { | ||
| if (!value) config.headers = undefined; | ||
| else config.headers = "{}"; | ||
| global.triggerReload(); | ||
| await global.plugin.saveSettings(); | ||
| }} | ||
| headers={config.headers} | ||
| setHeaders={async (value) => { | ||
| config.headers = value; | ||
| global.triggerReload(); | ||
| await global.plugin.saveSettings(); | ||
| }} | ||
| /> | ||
|
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||
| <div className="plug-tg-flex plug-tg-flex-col plug-tg-gap-2"> | ||
| <div className="plug-tg-text-lg plug-tg-opacity-70">Useful links</div> | ||
| <a href="https://beta.openai.com/signup/"> | ||
| <SettingItem | ||
| name="Create account OpenAI" | ||
| className="plug-tg-text-xs plug-tg-opacity-50 hover:plug-tg-opacity-100" | ||
| register={props.register} | ||
| sectionId={props.sectionId} | ||
| > | ||
| <IconExternalLink /> | ||
| </SettingItem> | ||
| </a> | ||
| <a href="https://beta.openai.com/docs/api-reference/introduction"> | ||
| <SettingItem | ||
| name="API documentation" | ||
| className="plug-tg-text-xs plug-tg-opacity-50 hover:plug-tg-opacity-100" | ||
| register={props.register} | ||
| sectionId={props.sectionId} | ||
| > | ||
| <IconExternalLink /> | ||
| </SettingItem> | ||
| </a> | ||
| <a href="https://discord.com/channels/1083485983879741572/1159894948636799126"> | ||
| <SettingItem | ||
| name="You can use LM Studio" | ||
| className="plug-tg-text-xs plug-tg-opacity-50 hover:plug-tg-opacity-100" | ||
| register={props.register} | ||
| sectionId={props.sectionId} | ||
| > | ||
| <IconExternalLink /> | ||
| </SettingItem> | ||
| </a> | ||
| <a href="https://beta.openai.com/docs/models/overview"> | ||
| <SettingItem | ||
| name="more information" | ||
| className="plug-tg-text-xs plug-tg-opacity-50 hover:plug-tg-opacity-100" | ||
| register={props.register} | ||
| sectionId={props.sectionId} | ||
| > | ||
| <IconExternalLink /> | ||
| </SettingItem> | ||
| </a> | ||
| </div> | ||
| </React.Fragment> | ||
| ); | ||
| } | ||
|
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||
| async calcPrice( | ||
| tokens: number, | ||
| reqParams: Partial<LLMConfig> | ||
| ): Promise<number> { | ||
| const model = reqParams.model; | ||
| const modelInfo = | ||
| AI_MODELS[model as keyof typeof AI_MODELS] || AI_MODELS["gpt-3.5-turbo"]; | ||
|
|
||
| console.log(reqParams.max_tokens, modelInfo.prices.completion); | ||
| return ( | ||
| (tokens * modelInfo.prices.prompt + | ||
| (reqParams.max_tokens || 100) * modelInfo.prices.completion) / | ||
| 1000 | ||
| ); | ||
| } | ||
|
|
||
| async calcTokens( | ||
| messages: Message[], | ||
| reqParams: Partial<LLMConfig> | ||
| ): ReturnType<LLMProviderInterface["calcTokens"]> { | ||
| const model = reqParams.model; | ||
| const modelInfo = | ||
| AI_MODELS[model as keyof typeof AI_MODELS] || AI_MODELS["gpt-3.5-turbo"]; | ||
|
|
||
| if (!modelInfo) | ||
| return { | ||
| tokens: 0, | ||
| maxTokens: 0, | ||
| }; | ||
| const encoder = this.plugin.tokensScope.getEncoderFromEncoding( | ||
| modelInfo.encoding | ||
| ); | ||
|
|
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| let tokensPerMessage, tokensPerName; | ||
| if (model && ["gpt-3.5-turbo", "gpt-3.5-turbo-0301"].includes(model)) { | ||
| tokensPerMessage = 4; | ||
| tokensPerName = -1; | ||
| } else if (model && ["gpt-4", "gpt-4-0314"].includes(model)) { | ||
| tokensPerMessage = 3; | ||
| tokensPerName = 1; | ||
| } else { | ||
| tokensPerMessage = 3; | ||
| tokensPerName = 1; | ||
| } | ||
|
|
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| let numTokens = 0; | ||
| for (const message of messages) { | ||
| numTokens += tokensPerMessage; | ||
| for (const [key, value] of Object.entries(message)) { | ||
| numTokens += encoder.encode(value).length; | ||
| if (key === "name") { | ||
| numTokens += tokensPerName; | ||
| } | ||
| } | ||
| } | ||
|
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| numTokens += 3; // every reply is primed with assistant | ||
|
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| return { | ||
| tokens: numTokens, | ||
| maxTokens: modelInfo.maxTokens, | ||
| }; | ||
| } | ||
| } |