mirror of
https://github.com/Mintplex-Labs/anything-llm
synced 2026-04-25 17:15:37 +02:00
163 lines
6.4 KiB
JavaScript
163 lines
6.4 KiB
JavaScript
const { WorkspaceChats } = require("../../../../models/workspaceChats");
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/**
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* Plugin to save chat history to AnythingLLM DB.
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*/
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const chatHistory = {
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name: "chat-history",
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startupConfig: {
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params: {},
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},
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plugin: function () {
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return {
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name: this.name,
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setup: function (aibitat) {
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// If the agent is aborted (e.g. user sent /reset mid-response), skip
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// the pending save so a completing in-flight response doesn't reappear.
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aibitat.onAbort(() => {
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aibitat._aborted = true;
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});
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// pre-register a workspace chat ID to secure it in the DB
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aibitat.onMessage(async (message) => {
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if (message.from !== "USER") return;
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/**
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* If we don't have a tracked chat ID, we need to create a new one so we can upsert the response later.
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* Normally, if this was a totally fresh chat from the user, we can assume that the message from the socket is
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* the message we want to store for the prompt. However, if this is a regeneration of a previous message and that message
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* called tools the history could include intermediate messages so need to search backwards to find the most recent user message
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* as that is actually the prompt.
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*/
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if (!aibitat.trackedChatId) {
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let userMessage = message.content;
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if (userMessage.startsWith("@agent:")) {
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const lastUserMsgIndex = aibitat._chats.findLastIndex(
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(c) => c.from === "USER" && !c.content.startsWith("@agent:")
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);
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// When regenerating a message, we need to use the last user message as the prompt.
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// Also prune the chats array to only include the messages before target prompt to re-run
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// or else tool call results from the previous run will be included in the history and the model will not re-call tools
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// that previously worked for the to-be-regenerated prompt.
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if (lastUserMsgIndex !== -1) {
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userMessage = aibitat._chats[lastUserMsgIndex].content;
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aibitat._chats = aibitat._chats.slice(0, lastUserMsgIndex + 1);
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}
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}
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const { chat } = await WorkspaceChats.new({
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workspaceId: Number(aibitat.handlerProps.invocation.workspace_id),
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user: { id: aibitat.handlerProps.invocation.user_id || null },
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threadId: aibitat.handlerProps.invocation.thread_id || null,
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include: false,
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prompt: userMessage,
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response: {},
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});
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if (chat) aibitat.registerChatId(chat.id);
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}
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});
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aibitat.onMessage(async () => {
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try {
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if (aibitat._aborted) return;
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const lastResponses = aibitat.chats.slice(-2);
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if (lastResponses.length !== 2) return;
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const [prev, last] = lastResponses;
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// We need a full conversation reply with prev being from
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// the USER and the last being from anyone other than the user.
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if (prev.from !== "USER" || last.from === "USER") return;
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// Extract attachments from user message if present
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const attachments = prev.attachments || [];
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// If we have a post-reply flow we should save the chat using this special flow
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// so that post save cleanup and other unique properties can be run as opposed to regular chat.
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if (aibitat.hasOwnProperty("_replySpecialAttributes")) {
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await this._storeSpecial(aibitat, {
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prompt: prev.content,
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response: last.content,
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attachments,
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options: aibitat._replySpecialAttributes,
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});
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delete aibitat._replySpecialAttributes;
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return;
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}
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await this._store(aibitat, {
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prompt: prev.content,
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response: last.content,
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attachments,
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});
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} catch {}
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});
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},
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_store: async function (
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aibitat,
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{ prompt, response, attachments = [] } = {}
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) {
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const invocation = aibitat.handlerProps.invocation;
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const metrics = aibitat.provider?.getUsage?.() ?? {};
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const citations = aibitat._pendingCitations ?? [];
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const outputs = aibitat._pendingOutputs ?? [];
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await WorkspaceChats.upsert(aibitat.trackedChatId, {
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workspaceId: Number(invocation.workspace_id),
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prompt,
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response: {
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text: response,
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sources: citations,
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type: "chat",
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attachments,
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metrics,
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...(outputs.length > 0 ? { outputs } : {}),
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},
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user: { id: invocation?.user_id || null },
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threadId: invocation?.thread_id || null,
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include: true,
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});
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this._cleanup(aibitat);
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},
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_storeSpecial: async function (
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aibitat,
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{ prompt, response, attachments = [], options = {} } = {}
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) {
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const invocation = aibitat.handlerProps.invocation;
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const metrics = aibitat.provider?.getUsage?.() ?? {};
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const citations = aibitat._pendingCitations ?? [];
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const outputs = aibitat._pendingOutputs ?? [];
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const existingSources = options?.sources ?? [];
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await WorkspaceChats.upsert(aibitat.trackedChatId, {
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workspaceId: Number(invocation.workspace_id),
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prompt,
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response: {
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sources: [...existingSources, ...citations],
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// when we have a _storeSpecial called the options param can include a storedResponse() function
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// that will override the text property to store extra information in, depending on the special type of chat.
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text: options.hasOwnProperty("storedResponse")
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? options.storedResponse(response)
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: response,
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type: options?.saveAsType ?? "chat",
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attachments,
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metrics,
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...(outputs.length > 0 ? { outputs } : {}),
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},
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user: { id: invocation?.user_id || null },
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threadId: invocation?.thread_id || null,
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include: true,
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});
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options?.postSave();
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this._cleanup(aibitat);
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},
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_cleanup: function (aibitat) {
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aibitat.clearCitations?.();
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aibitat._pendingOutputs = [];
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aibitat.clearTrackedChatId();
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},
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};
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},
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};
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module.exports = { chatHistory };
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