LibreChat/packages/data-provider/src/parsers.ts
Danny Avila 0e50c07e3f
🤖 feat: Model Specs & Save Tools per Convo/Preset (#2578)
* WIP: first pass ModelSpecs

* refactor(onSelectEndpoint): use `getConvoSwitchLogic`

* feat: introduce iconURL, greeting, frontend fields for conversations/presets/messages

* feat: conversation.iconURL & greeting in Landing

* feat: conversation.iconURL & greeting in New Chat button

* feat: message.iconURL

* refactor: ConversationIcon -> ConvoIconURL

* WIP: add spec as a conversation field

* refactor: useAppStartup, set spec on initial load for new chat, allow undefined spec, add localStorage keys enum, additional type fields for spec

* feat: handle `showIconInMenu`, `showIconInHeader`, undefined `iconURL` and no specs on initial load

* chore: handle undefined or empty modelSpecs

* WIP: first pass, modelSpec schema for custom config

* refactor: move default filtered tools definition to ToolService

* feat: pass modelSpecs from backend via startupConfig

* refactor: modelSpecs config, return and define list

* fix: react error and include iconURL in responseMessage

* refactor: add iconURL to responseMessage only

* refactor: getIconEndpoint

* refactor: pass TSpecsConfig

* fix(assistants): differentiate compactAssistantSchema, correctly resets shared conversation state with other endpoints

* refactor: assistant id prefix localStorage key

* refactor: add more LocalStorageKeys and replace hardcoded values

* feat: prioritize spec on new chat behavior: last selected modelSpec behavior (localStorage)

* feat: first pass, interface config

* chore: WIP, todo: add warnings based on config.modelSpecs settings.

* feat: enforce modelSpecs if configured

* feat: show config file yaml errors

* chore: delete unused legacy Plugins component

* refactor: set tools to localStorage from recoil store

* chore: add stable recoil setter to useEffect deps

* refactor: save tools to conversation documents

* style(MultiSelectPop): dynamic height, remove unused import

* refactor(react-query): use localstorage keys and pass config to useAvailablePluginsQuery

* feat(utils): add mapPlugins

* refactor(Convo): use conversation.tools if defined, lastSelectedTools if not

* refactor: remove unused legacy code using `useSetOptions`, remove conditional flag `isMultiChat` for using legacy settings

* refactor(PluginStoreDialog): add exhaustive-deps which are stable react state setters

* fix(HeaderOptions): pass `popover` as true

* refactor(useSetStorage): use project enums

* refactor: use LocalStorageKeys enum

* fix: prevent setConversation from setting falsy values in lastSelectedTools

* refactor: use map for availableTools state and available Plugins query

* refactor(updateLastSelectedModel): organize logic better and add note on purpose

* fix(setAgentOption): prevent reseting last model to secondary model for gptPlugins

* refactor(buildDefaultConvo): use enum

* refactor: remove `useSetStorage` and consolidate areas where conversation state is saved to localStorage

* fix: conversations retain tools on refresh

* fix(gptPlugins): prevent nullish tools from being saved

* chore: delete useServerStream

* refactor: move initial plugins logic to useAppStartup

* refactor(MultiSelectDropDown): add more pass-in className props

* feat: use tools in presets

* chore: delete unused usePresetOptions

* refactor: new agentOptions default handling

* chore: note

* feat: add label and custom instructions to agents

* chore: remove 'disabled with tools' message

* style: move plugins to 2nd column in parameters

* fix: TPreset type for agentOptions

* fix: interface controls

* refactor: add interfaceConfig, use Separator within Switcher

* refactor: hide Assistants panel if interface.parameters are disabled

* fix(Header): only modelSpecs if list is greater than 0

* refactor: separate MessageIcon logic from useMessageHelpers for better react rule-following

* fix(AppService): don't use reserved keyword 'interface'

* feat: set existing Icon for custom endpoints through iconURL

* fix(ci): tests passing for App Service

* docs: refactor custom_config.md for readability and better organization, also include missing values

* docs: interface section and re-organize docs

* docs: update modelSpecs info

* chore: remove unused files

* chore: remove unused files

* chore: move useSetIndexOptions

* chore: remove unused file

* chore: move useConversation(s)

* chore: move useDefaultConvo

* chore: move useNavigateToConvo

* refactor: use plugin install hook so it can be used elsewhere

* chore: import order

* update docs

* refactor(OpenAI/Plugins): allow modelLabel as an initial value for chatGptLabel

* chore: remove unused EndpointOptionsPopover and hide 'Save as Preset' button if preset UI visibility disabled

* feat(loadDefaultInterface): issue warnings based on values

* feat: changelog for custom config file

* docs: add additional changelog note

* fix: prevent unavailable tool selection from preset and update availableTools on Plugin installations

* feat: add `filteredTools` option in custom config

* chore: changelog

* fix(MessageIcon): always overwrite conversation.iconURL in messageSettings

* fix(ModelSpecsMenu): icon edge cases

* fix(NewChat): dynamic icon

* fix(PluginsClient): always include endpoint in responseMessage

* fix: always include endpoint and iconURL in responseMessage across different response methods

* feat: interchangeable keys for modelSpec enforcing
2024-04-30 22:11:48 -04:00

322 lines
9.1 KiB
TypeScript

import type { ZodIssue } from 'zod';
import type { TConversation, TPreset } from './schemas';
import type { TConfig, TEndpointOption, TEndpointsConfig } from './types';
import {
EModelEndpoint,
openAISchema,
googleSchema,
bingAISchema,
anthropicSchema,
chatGPTBrowserSchema,
gptPluginsSchema,
assistantSchema,
compactOpenAISchema,
compactGoogleSchema,
compactAnthropicSchema,
compactChatGPTSchema,
compactPluginsSchema,
compactAssistantSchema,
} from './schemas';
import { alternateName } from './config';
type EndpointSchema =
| typeof openAISchema
| typeof googleSchema
| typeof bingAISchema
| typeof anthropicSchema
| typeof chatGPTBrowserSchema
| typeof gptPluginsSchema
| typeof assistantSchema;
const endpointSchemas: Record<EModelEndpoint, EndpointSchema> = {
[EModelEndpoint.openAI]: openAISchema,
[EModelEndpoint.azureOpenAI]: openAISchema,
[EModelEndpoint.custom]: openAISchema,
[EModelEndpoint.google]: googleSchema,
[EModelEndpoint.bingAI]: bingAISchema,
[EModelEndpoint.anthropic]: anthropicSchema,
[EModelEndpoint.chatGPTBrowser]: chatGPTBrowserSchema,
[EModelEndpoint.gptPlugins]: gptPluginsSchema,
[EModelEndpoint.assistants]: assistantSchema,
};
// const schemaCreators: Record<EModelEndpoint, (customSchema: DefaultSchemaValues) => EndpointSchema> = {
// [EModelEndpoint.google]: createGoogleSchema,
// };
/** Get the enabled endpoints from the `ENDPOINTS` environment variable */
export function getEnabledEndpoints() {
const defaultEndpoints: string[] = [
EModelEndpoint.openAI,
EModelEndpoint.assistants,
EModelEndpoint.azureOpenAI,
EModelEndpoint.google,
EModelEndpoint.bingAI,
EModelEndpoint.chatGPTBrowser,
EModelEndpoint.gptPlugins,
EModelEndpoint.anthropic,
];
const endpointsEnv = process.env.ENDPOINTS || '';
let enabledEndpoints = defaultEndpoints;
if (endpointsEnv) {
enabledEndpoints = endpointsEnv
.split(',')
.filter((endpoint) => endpoint?.trim())
.map((endpoint) => endpoint.trim());
}
return enabledEndpoints;
}
/** Orders an existing EndpointsConfig object based on enabled endpoint/custom ordering */
export function orderEndpointsConfig(endpointsConfig: TEndpointsConfig) {
if (!endpointsConfig) {
return {};
}
const enabledEndpoints = getEnabledEndpoints();
const endpointKeys = Object.keys(endpointsConfig);
const defaultCustomIndex = enabledEndpoints.indexOf(EModelEndpoint.custom);
return endpointKeys.reduce(
(accumulatedConfig: Record<string, TConfig | null | undefined>, currentEndpointKey) => {
const isCustom = !(currentEndpointKey in EModelEndpoint);
const isEnabled = enabledEndpoints.includes(currentEndpointKey);
if (!isEnabled && !isCustom) {
return accumulatedConfig;
}
const index = enabledEndpoints.indexOf(currentEndpointKey);
if (isCustom) {
accumulatedConfig[currentEndpointKey] = {
order: defaultCustomIndex >= 0 ? defaultCustomIndex : 9999,
...(endpointsConfig[currentEndpointKey] as Omit<TConfig, 'order'> & { order?: number }),
};
} else if (endpointsConfig[currentEndpointKey]) {
accumulatedConfig[currentEndpointKey] = {
...endpointsConfig[currentEndpointKey],
order: index,
};
}
return accumulatedConfig;
},
{},
);
}
/** Converts an array of Zod issues into a string. */
export function errorsToString(errors: ZodIssue[]) {
return errors
.map((error) => {
const field = error.path.join('.');
const message = error.message;
return `${field}: ${message}`;
})
.join(' ');
}
export const envVarRegex = /^\${(.+)}$/;
/** Extracts the value of an environment variable from a string. */
export function extractEnvVariable(value: string) {
const envVarMatch = value.match(envVarRegex);
if (envVarMatch) {
return process.env[envVarMatch[1]] || value;
}
return value;
}
/** Resolves header values to env variables if detected */
export function resolveHeaders(headers: Record<string, string> | undefined) {
const resolvedHeaders = { ...(headers ?? {}) };
if (headers && typeof headers === 'object' && !Array.isArray(headers)) {
Object.keys(headers).forEach((key) => {
resolvedHeaders[key] = extractEnvVariable(headers[key]);
});
}
return resolvedHeaders;
}
export function getFirstDefinedValue(possibleValues: string[]) {
let returnValue;
for (const value of possibleValues) {
if (value) {
returnValue = value;
break;
}
}
return returnValue;
}
export type TPossibleValues = {
models: string[];
secondaryModels?: string[];
};
export const parseConvo = ({
endpoint,
endpointType,
conversation,
possibleValues,
}: {
endpoint: EModelEndpoint;
endpointType?: EModelEndpoint;
conversation: Partial<TConversation | TPreset>;
possibleValues?: TPossibleValues;
// TODO: POC for default schema
// defaultSchema?: Partial<EndpointSchema>,
}) => {
let schema = endpointSchemas[endpoint];
if (!schema && !endpointType) {
throw new Error(`Unknown endpoint: ${endpoint}`);
} else if (!schema && endpointType) {
schema = endpointSchemas[endpointType];
}
// if (defaultSchema && schemaCreators[endpoint]) {
// schema = schemaCreators[endpoint](defaultSchema);
// }
const convo = schema.parse(conversation) as TConversation;
const { models, secondaryModels } = possibleValues ?? {};
if (models && convo) {
convo.model = getFirstDefinedValue(models) ?? convo.model;
}
if (secondaryModels && convo.agentOptions) {
convo.agentOptions.model = getFirstDefinedValue(secondaryModels) ?? convo.agentOptions.model;
}
return convo;
};
export const getResponseSender = (endpointOption: TEndpointOption): string => {
const { model, endpoint, endpointType, modelDisplayLabel, chatGptLabel, modelLabel, jailbreak } =
endpointOption;
if (
[
EModelEndpoint.openAI,
EModelEndpoint.azureOpenAI,
EModelEndpoint.gptPlugins,
EModelEndpoint.chatGPTBrowser,
].includes(endpoint)
) {
if (chatGptLabel) {
return chatGptLabel;
} else if (model && model.includes('gpt-3')) {
return 'GPT-3.5';
} else if (model && model.includes('gpt-4')) {
return 'GPT-4';
} else if (model && model.includes('mistral')) {
return 'Mistral';
}
return alternateName[endpoint] ?? 'ChatGPT';
}
if (endpoint === EModelEndpoint.bingAI) {
return jailbreak ? 'Sydney' : 'BingAI';
}
if (endpoint === EModelEndpoint.anthropic) {
return modelLabel ?? 'Claude';
}
if (endpoint === EModelEndpoint.google) {
if (modelLabel) {
return modelLabel;
} else if (model && model.includes('gemini')) {
return 'Gemini';
} else if (model && model.includes('code')) {
return 'Codey';
}
return 'PaLM2';
}
if (endpoint === EModelEndpoint.custom || endpointType === EModelEndpoint.custom) {
if (modelLabel) {
return modelLabel;
} else if (chatGptLabel) {
return chatGptLabel;
} else if (model && model.includes('mistral')) {
return 'Mistral';
} else if (model && model.includes('gpt-3')) {
return 'GPT-3.5';
} else if (model && model.includes('gpt-4')) {
return 'GPT-4';
} else if (modelDisplayLabel) {
return modelDisplayLabel;
}
return 'AI';
}
return '';
};
type CompactEndpointSchema =
| typeof compactOpenAISchema
| typeof compactAssistantSchema
| typeof compactGoogleSchema
| typeof bingAISchema
| typeof compactAnthropicSchema
| typeof compactChatGPTSchema
| typeof compactPluginsSchema;
const compactEndpointSchemas: Record<string, CompactEndpointSchema> = {
[EModelEndpoint.openAI]: compactOpenAISchema,
[EModelEndpoint.azureOpenAI]: compactOpenAISchema,
[EModelEndpoint.custom]: compactOpenAISchema,
[EModelEndpoint.assistants]: compactAssistantSchema,
[EModelEndpoint.google]: compactGoogleSchema,
/* BingAI needs all fields */
[EModelEndpoint.bingAI]: bingAISchema,
[EModelEndpoint.anthropic]: compactAnthropicSchema,
[EModelEndpoint.chatGPTBrowser]: compactChatGPTSchema,
[EModelEndpoint.gptPlugins]: compactPluginsSchema,
};
export const parseCompactConvo = ({
endpoint,
endpointType,
conversation,
possibleValues,
}: {
endpoint?: EModelEndpoint;
endpointType?: EModelEndpoint;
conversation: Partial<TConversation | TPreset>;
possibleValues?: TPossibleValues;
// TODO: POC for default schema
// defaultSchema?: Partial<EndpointSchema>,
}) => {
if (!endpoint) {
throw new Error(`undefined endpoint: ${endpoint}`);
}
let schema = compactEndpointSchemas[endpoint];
if (!schema && !endpointType) {
throw new Error(`Unknown endpoint: ${endpoint}`);
} else if (!schema && endpointType) {
schema = compactEndpointSchemas[endpointType];
}
const convo = schema.parse(conversation) as TConversation;
// const { models, secondaryModels } = possibleValues ?? {};
const { models } = possibleValues ?? {};
if (models && convo) {
convo.model = getFirstDefinedValue(models) ?? convo.model;
}
// if (secondaryModels && convo.agentOptions) {
// convo.agentOptionmodel = getFirstDefinedValue(secondaryModels) ?? convo.agentOptionmodel;
// }
return convo;
};