f395083978
* Add automatic chat mode with native tool calling support
Introduces a new automatic chat mode (now the default) that automatically invokes tools when the provider supports native tool calling. Conditionally shows/hides the @agent command based on whether native tooling is available.
- Add supportsNativeToolCalling() to AI providers (OpenAI, Anthropic, Azure always support; others opt-in via ENV)
- Update all locale translations with new mode descriptions
- Enhance translator to preserve Trans component tags
- Remove deprecated ability tags UI
* rebase translations
* WIP on image attachments. Supports initial image attachment + subsequent attachments
* persist images
* Image attachments and updates for providers
* desktop pre-change
* always show command on failure
* add back gemini streaming detection
* move provider native tooling flag to Provider func
* whoops - forgot to delete
* strip "@agent" from prompts to prevent weird replies
* translations for automatic-mode (#5145)
* translations for automatic-mode
* rebase
* translations
* lint
* fix dead translations
* change default for now to chat mode just for rollout
* remove pfp for workspace
* passthrough workspace for showAgentCommand detection and rendering
* Agent API automatic mode support
* ephemeral attachments passthrough
* support reading of pinned documents in agent context
104 lines
3.6 KiB
JavaScript
104 lines
3.6 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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aibitat.onMessage(async () => {
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try {
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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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await WorkspaceChats.new({
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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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},
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user: { id: invocation?.user_id || null },
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threadId: invocation?.thread_id || null,
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});
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aibitat.clearCitations?.();
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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 existingSources = options?.sources ?? [];
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await WorkspaceChats.new({
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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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},
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user: { id: invocation?.user_id || null },
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threadId: invocation?.thread_id || null,
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});
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aibitat.clearCitations?.();
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options?.postSave();
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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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