Merge branch 'master' of github.com:khoj-ai/khoj into features/advanced-reasoning

This commit is contained in:
sabaimran 2024-10-23 19:15:51 -07:00
commit 30f9225021
85 changed files with 5132 additions and 3202 deletions

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@ -38,8 +38,8 @@
- Chat with any local or online LLM (e.g llama3, qwen, gemma, mistral, gpt, claude, gemini).
- Get answers from the internet and your docs (including image, pdf, markdown, org-mode, word, notion files).
- Access it from your Browser, Obsidian, Emacs, Desktop, Phone or Whatsapp.
- Build agents with custom knowledge bases and tools.
- Create automations to get personal newsletters and smart notifications.
- Create agents with custom knowledge, persona, chat model and tools to take on any role.
- Automate away repetitive research. Get personal newsletters and smart notifications delivered to your inbox.
- Find relevant docs quickly and easily using our advanced semantic search.
- Generate images, talk out loud, play your messages.
- Khoj is open-source, self-hostable. Always.

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@ -1,6 +1,8 @@
# Admin Panel
> Describes the Khoj settings configurable via the admin panel
By default, you admin panel is available at `http://localhost:42110/server/admin/`. You can access the admin panel by logging in with your admin credentials (this would be your `KHOJ_ADMIN_EMAIL` and `KHOJ_ADMIN_PASSWORD`). The admin panel allows you to configure various settings for your Khoj server.
## App Settings
### Agents
Add all the agents you want to use for your different use-cases like Writer, Researcher, Therapist etc.

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@ -12,7 +12,7 @@ Without any desktop clients, you can start chatting with Khoj on WhatsApp. Bear
In order to use Khoj on WhatsApp with your own data, you need to setup a Khoj Cloud account and connect your WhatsApp account to it. This is a one time setup and you can do it from the [Khoj Cloud config page](https://app.khoj.dev/settings).
If you hit usage limits for the WhatsApp bot, upgrade to [a paid plan](https://khoj.dev/pricing) on Khoj Cloud.
If you hit usage limits for the WhatsApp bot, upgrade to [a paid plan](https://khoj.dev/#pricing) on Khoj Cloud.
<img src="https://khoj-web-bucket.s3.amazonaws.com/khojwhatsapp.png" alt="WhatsApp QR Code" width="300" height="300" />

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@ -102,7 +102,19 @@ sudo -u postgres createdb khoj --password
</TabItem>
</Tabs>
#### 3. Run
#### 3. Build the front-end assets
```shell
cd src/interface/web/
yarn install
yarn export
```
You can optionally use `yarn dev` to start a development server for the front-end which will be available at http://localhost:3000. This is especially useful if you're making changes to the front-end code, but not necessary for running Khoj. Note that streaming does not work on the dev server due to how it is handled with SSR in Next.js.
Always run `yarn export` to test your front-end changes on http://localhost:42110 before creating a PR.
#### 4. Run
1. Start Khoj
```bash
khoj -vv

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@ -40,7 +40,7 @@ If you want to use the offline chat model and you have a GPU, you should use Ins
</TabItem>
<TabItem value="linux" label="Linux">
<h3>Prerequisites</h3>
Install [Docker Desktop](https://docs.docker.com/desktop/install/windows-install/).
Install [Docker Desktop](https://docs.docker.com/desktop/install/linux/).
You can also use your package manager to install Docker Engine & Docker Compose.
</TabItem>
</Tabs>
@ -240,7 +240,7 @@ Ensure you are using **localhost, not 127.0.0.1**, to access the admin panel to
:::info[DISALLOWED HOST or Bad Request (400) Error]
You may hit this if you try access Khoj exposed on a custom domain (e.g. 192.168.12.3 or example.com) or over HTTP.
Set the environment variables KHOJ_DOMAIN=your-domain and KHOJ_NO_HTTPS=false if required to avoid this error.
Set the environment variables KHOJ_DOMAIN=your-domain and KHOJ_NO_HTTPS=True if required to avoid this error.
:::
:::tip[Note]

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@ -1,7 +1,7 @@
{
"id": "khoj",
"name": "Khoj",
"version": "1.25.0",
"version": "1.26.4",
"minAppVersion": "0.15.0",
"description": "Your Second Brain",
"author": "Khoj Inc.",

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@ -62,8 +62,8 @@ dependencies = [
"requests >= 2.26.0",
"tenacity == 8.3.0",
"anyio == 3.7.1",
"pymupdf >= 1.23.5",
"django == 5.0.8",
"pymupdf == 1.24.11",
"django == 5.0.9",
"authlib == 1.2.1",
"llama-cpp-python == 0.2.88",
"itsdangerous == 2.1.2",

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@ -326,7 +326,7 @@
entries.forEach(entry => {
// If the element is in the viewport, fetch the remaining message and unobserve the element
if (entry.isIntersecting) {
fetchRemainingChatMessages(chatHistoryUrl, headers);
fetchRemainingChatMessages(chatHistoryUrl, headers, chatBody.dataset.conversation_id, hostURL);
observer.unobserve(entry.target);
}
});
@ -342,7 +342,11 @@
new Date(chat_log.created),
chat_log.onlineContext,
chat_log.intent?.type,
chat_log.intent?.["inferred-queries"]);
chat_log.intent?.["inferred-queries"],
chatBody.dataset.conversationId ?? "",
hostURL,
);
chatBody.appendChild(messageElement);
// When the 4th oldest message is within viewing distance (~60% scrolled up)
@ -421,7 +425,7 @@
}
}
function fetchRemainingChatMessages(chatHistoryUrl, headers) {
function fetchRemainingChatMessages(chatHistoryUrl, headers, conversationId, hostURL) {
// Create a new IntersectionObserver
let observer = new IntersectionObserver((entries, observer) => {
entries.forEach(entry => {
@ -435,7 +439,9 @@
new Date(chat_log.created),
chat_log.onlineContext,
chat_log.intent?.type,
chat_log.intent?.["inferred-queries"]
chat_log.intent?.["inferred-queries"],
chatBody.dataset.conversationId ?? "",
hostURL,
);
entry.target.replaceWith(messageElement);

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@ -189,11 +189,19 @@ function processOnlineReferences(referenceSection, onlineContext) { //same
return numOnlineReferences;
}
function renderMessageWithReference(message, by, context=null, dt=null, onlineContext=null, intentType=null, inferredQueries=null) { //same
function renderMessageWithReference(message, by, context=null, dt=null, onlineContext=null, intentType=null, inferredQueries=null, conversationId=null, hostURL=null) {
let chatEl;
if (intentType?.includes("text-to-image")) {
let imageMarkdown = generateImageMarkdown(message, intentType, inferredQueries);
chatEl = renderMessage(imageMarkdown, by, dt, null, false, "return");
} else if (intentType === "excalidraw") {
let domain = hostURL ?? "https://app.khoj.dev/";
if (!domain.endsWith("/")) domain += "/";
let excalidrawMessage = `Hey, I'm not ready to show you diagrams yet here. But you can view it in the web app at ${domain}chat?conversationId=${conversationId}`;
chatEl = renderMessage(excalidrawMessage, by, dt, null, false, "return");
} else {
chatEl = renderMessage(message, by, dt, null, false, "return");
}
@ -312,7 +320,6 @@ function formatHTMLMessage(message, raw=false, willReplace=true) { //same
}
function createReferenceSection(references, createLinkerSection=false) {
console.log("linker data: ", createLinkerSection);
let referenceSection = document.createElement('div');
referenceSection.classList.add("reference-section");
referenceSection.classList.add("collapsed");
@ -417,7 +424,11 @@ function handleImageResponse(imageJson, rawResponse) {
rawResponse += `![generated_image](${imageJson.image})`;
} else if (imageJson.intentType === "text-to-image-v3") {
rawResponse = `![](data:image/webp;base64,${imageJson.image})`;
} else if (imageJson.intentType === "excalidraw") {
const redirectMessage = `Hey, I'm not ready to show you diagrams yet here. But you can view it in the web app`;
rawResponse += redirectMessage;
}
if (inferredQuery) {
rawResponse += `\n\n**Inferred Query**:\n\n${inferredQuery}`;
}

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@ -19,7 +19,7 @@ const textFileTypes = [
'org', 'md', 'markdown', 'txt', 'html', 'xml',
// Other valid text file extensions from https://google.github.io/magika/model/config.json
'appleplist', 'asm', 'asp', 'batch', 'c', 'cs', 'css', 'csv', 'eml', 'go', 'html', 'ini', 'internetshortcut', 'java', 'javascript', 'json', 'latex', 'lisp', 'makefile', 'markdown', 'mht', 'mum', 'pem', 'perl', 'php', 'powershell', 'python', 'rdf', 'rst', 'rtf', 'ruby', 'rust', 'scala', 'shell', 'smali', 'sql', 'svg', 'symlinktext', 'txt', 'vba', 'winregistry', 'xml', 'yaml']
const binaryFileTypes = ['pdf', 'jpg', 'jpeg', 'png']
const binaryFileTypes = ['pdf', 'jpg', 'jpeg', 'png', 'webp']
const validFileTypes = textFileTypes.concat(binaryFileTypes);
const schema = {
@ -104,6 +104,8 @@ function filenameToMimeType (filename) {
case 'jpg':
case 'jpeg':
return 'image/jpeg';
case 'webp':
return 'image/webp';
case 'md':
case 'markdown':
return 'text/markdown';

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@ -1,6 +1,6 @@
{
"name": "Khoj",
"version": "1.25.0",
"version": "1.26.4",
"description": "Your Second Brain",
"author": "Khoj Inc. <team@khoj.dev>",
"license": "GPL-3.0-or-later",

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@ -6,7 +6,7 @@
;; Saba Imran <saba@khoj.dev>
;; Description: Your Second Brain
;; Keywords: search, chat, ai, org-mode, outlines, markdown, pdf, image
;; Version: 1.25.0
;; Version: 1.26.4
;; Package-Requires: ((emacs "27.1") (transient "0.3.0") (dash "2.19.1"))
;; URL: https://github.com/khoj-ai/khoj/tree/master/src/interface/emacs
@ -127,6 +127,11 @@
(const "image")
(const "pdf")))
(defcustom khoj-default-agent "khoj"
"The default agent to chat with. See https://app.khoj.dev/agents for available options."
:group 'khoj
:type 'string)
;; --------------------------
;; Khoj Dynamic Configuration
@ -144,6 +149,9 @@
(defconst khoj--chat-buffer-name "*🏮 Khoj Chat*"
"Name of chat buffer for Khoj.")
(defvar khoj--selected-agent khoj-default-agent
"Currently selected Khoj agent.")
(defvar khoj--content-type "org"
"The type of content to perform search on.")
@ -656,13 +664,15 @@ Simplified fork of `org-cycle-content' from Emacs 29.1 to work with >=27.1."
;; --------------
;; Query Khoj API
;; --------------
(defun khoj--call-api (path &optional method params callback &rest cbargs)
"Sync call API at PATH with METHOD and query PARAMS as kv assoc list.
(defun khoj--call-api (path &optional method params body callback &rest cbargs)
"Sync call API at PATH with METHOD, query PARAMS and BODY as kv assoc list.
Optionally apply CALLBACK with JSON parsed response and CBARGS."
(let* ((url-request-method (or method "GET"))
(url-request-extra-headers `(("Authorization" . ,(format "Bearer %s" khoj-api-key))))
(param-string (if params (url-build-query-string params) ""))
(query-url (format "%s%s?%s&client=emacs" khoj-server-url path param-string))
(url-request-extra-headers `(("Authorization" . ,(format "Bearer %s" khoj-api-key)) ("Content-Type" . "application/json")))
(url-request-data (if body (json-encode body) nil))
(param-string (url-build-query-string (append params '((client "emacs")))))
(query-url (format "%s%s?%s" khoj-server-url path param-string))
(cbargs (if (and (listp cbargs) (listp (car cbargs))) (car cbargs) cbargs))) ; normalize cbargs to (a b) from ((a b)) if required
(with-temp-buffer
(condition-case ex
@ -682,8 +692,8 @@ Optionally apply CALLBACK with JSON parsed response and CBARGS."
(url-request-extra-headers `(("Authorization" . ,(format "Bearer %s" khoj-api-key)) ("Content-Type" . "application/json")))
(url-request-data (if body (json-encode body) nil))
(param-string (url-build-query-string (append params '((client "emacs")))))
(cbargs (if (and (listp cbargs) (listp (car cbargs))) (car cbargs) cbargs)) ; normalize cbargs to (a b) from ((a b)) if required
(query-url (format "%s%s?%s" khoj-server-url path param-string)))
(query-url (format "%s%s?%s" khoj-server-url path param-string))
(cbargs (if (and (listp cbargs) (listp (car cbargs))) (car cbargs) cbargs))) ; normalize cbargs to (a b) from ((a b)) if required
(url-retrieve query-url
(lambda (status)
(if (plist-get status :error)
@ -699,7 +709,7 @@ Optionally apply CALLBACK with JSON parsed response and CBARGS."
(defun khoj--get-enabled-content-types ()
"Get content types enabled for search from API."
(khoj--call-api "/api/content/types" "GET" nil `(lambda (item) (mapcar #'intern item))))
(khoj--call-api "/api/content/types" "GET" nil nil `(lambda (item) (mapcar #'intern item))))
(defun khoj--query-search-api-and-render-results (query content-type buffer-name &optional rerank is-find-similar)
"Query Khoj Search API with QUERY, CONTENT-TYPE and RERANK as query params.
@ -913,14 +923,16 @@ Call CALLBACK func with response and CBARGS."
(let ((selected-session-id (khoj--select-conversation-session "Open")))
(khoj--load-chat-session khoj--chat-buffer-name selected-session-id)))
(defun khoj--create-chat-session ()
"Create new chat session."
(khoj--call-api "/api/chat/sessions" "POST"))
(defun khoj--create-chat-session (&optional agent)
"Create new chat session with AGENT."
(khoj--call-api "/api/chat/sessions"
"POST"
(when agent `(("agent_slug" ,agent)))))
(defun khoj--new-conversation-session ()
"Create new Khoj conversation session."
(defun khoj--new-conversation-session (&optional agent)
"Create new Khoj conversation session with AGENT."
(thread-last
(khoj--create-chat-session)
(khoj--create-chat-session agent)
(assoc 'conversation_id)
(cdr)
(khoj--chat)))
@ -935,6 +947,15 @@ Call CALLBACK func with response and CBARGS."
(khoj--select-conversation-session "Delete")
(khoj--delete-chat-session)))
(defun khoj--get-agents ()
"Get list of available Khoj agents."
(let* ((response (khoj--call-api "/api/agents" "GET"))
(agents (mapcar (lambda (agent)
(cons (cdr (assoc 'name agent))
(cdr (assoc 'slug agent))))
response)))
agents))
(defun khoj--render-chat-message (message sender &optional receive-date)
"Render chat messages as `org-mode' list item.
MESSAGE is the text of the chat message.
@ -1246,6 +1267,20 @@ Paragraph only starts at first text after blank line."
;; dynamically set choices to content types enabled on khoj backend
:choices (or (ignore-errors (mapcar #'symbol-name (khoj--get-enabled-content-types))) '("all" "org" "markdown" "pdf" "image")))
(transient-define-argument khoj--agent-switch ()
:class 'transient-switches
:argument-format "--agent=%s"
:argument-regexp ".+"
:init-value (lambda (obj)
(oset obj value (format "--agent=%s" khoj--selected-agent)))
:choices (or (ignore-errors (mapcar #'cdr (khoj--get-agents))) '("khoj"))
:reader (lambda (prompt initial-input history)
(let* ((agents (khoj--get-agents))
(selected (completing-read prompt agents nil t initial-input history))
(slug (cdr (assoc selected agents))))
(setq khoj--selected-agent slug)
slug)))
(transient-define-suffix khoj--search-command (&optional args)
(interactive (list (transient-args transient-current-command)))
(progn
@ -1287,10 +1322,11 @@ Paragraph only starts at first text after blank line."
(interactive (list (transient-args transient-current-command)))
(khoj--open-conversation-session))
(transient-define-suffix khoj--new-conversation-session-command (&optional _)
(transient-define-suffix khoj--new-conversation-session-command (&optional args)
"Command to select Khoj conversation sessions to open."
(interactive (list (transient-args transient-current-command)))
(khoj--new-conversation-session))
(let ((agent-slug (transient-arg-value "--agent=" args)))
(khoj--new-conversation-session agent-slug)))
(transient-define-suffix khoj--delete-conversation-session-command (&optional _)
"Command to select Khoj conversation sessions to delete."
@ -1298,14 +1334,15 @@ Paragraph only starts at first text after blank line."
(khoj--delete-conversation-session))
(transient-define-prefix khoj--chat-menu ()
"Open the Khoj chat menu."
["Act"
("c" "Chat" khoj--chat-command)
("o" "Open Conversation" khoj--open-conversation-session-command)
("n" "New Conversation" khoj--new-conversation-session-command)
("d" "Delete Conversation" khoj--delete-conversation-session-command)
("q" "Quit" transient-quit-one)
])
"Create the Khoj Chat Menu and Execute Commands."
[["Configure"
("a" "Select Agent" khoj--agent-switch)]]
[["Act"
("c" "Chat" khoj--chat-command)
("o" "Open Conversation" khoj--open-conversation-session-command)
("n" "New Conversation" khoj--new-conversation-session-command)
("d" "Delete Conversation" khoj--delete-conversation-session-command)
("q" "Quit" transient-quit-one)]])
(transient-define-prefix khoj--menu ()
"Create Khoj Menu to Configure and Execute Commands."

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@ -1,7 +1,7 @@
{
"id": "khoj",
"name": "Khoj",
"version": "1.25.0",
"version": "1.26.4",
"minAppVersion": "0.15.0",
"description": "Your Second Brain",
"author": "Khoj Inc.",

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@ -1,6 +1,6 @@
{
"name": "Khoj",
"version": "1.25.0",
"version": "1.26.4",
"description": "Your Second Brain",
"author": "Debanjum Singh Solanky, Saba Imran <team@khoj.dev>",
"license": "GPL-3.0-or-later",

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@ -484,12 +484,13 @@ export class KhojChatView extends KhojPaneView {
dt?: Date,
intentType?: string,
inferredQueries?: string[],
conversationId?: string,
) {
if (!message) return;
let chatMessageEl;
if (intentType?.includes("text-to-image")) {
let imageMarkdown = this.generateImageMarkdown(message, intentType, inferredQueries);
if (intentType?.includes("text-to-image") || intentType === "excalidraw") {
let imageMarkdown = this.generateImageMarkdown(message, intentType, inferredQueries, conversationId);
chatMessageEl = this.renderMessage(chatEl, imageMarkdown, sender, dt);
} else {
chatMessageEl = this.renderMessage(chatEl, message, sender, dt);
@ -509,7 +510,7 @@ export class KhojChatView extends KhojPaneView {
chatMessageBodyEl.appendChild(this.createReferenceSection(references));
}
generateImageMarkdown(message: string, intentType: string, inferredQueries?: string[]) {
generateImageMarkdown(message: string, intentType: string, inferredQueries?: string[], conversationId?: string): string {
let imageMarkdown = "";
if (intentType === "text-to-image") {
imageMarkdown = `![](data:image/png;base64,${message})`;
@ -517,6 +518,10 @@ export class KhojChatView extends KhojPaneView {
imageMarkdown = `![](${message})`;
} else if (intentType === "text-to-image-v3") {
imageMarkdown = `![](data:image/webp;base64,${message})`;
} else if (intentType === "excalidraw") {
const domain = this.setting.khojUrl.endsWith("/") ? this.setting.khojUrl : `${this.setting.khojUrl}/`;
const redirectMessage = `Hey, I'm not ready to show you diagrams yet here. But you can view it in ${domain}chat?conversationId=${conversationId}`;
imageMarkdown = redirectMessage;
}
if (inferredQueries) {
imageMarkdown += "\n\n**Inferred Query**:";
@ -884,6 +889,7 @@ export class KhojChatView extends KhojPaneView {
new Date(chatLog.created),
chatLog.intent?.type,
chatLog.intent?.["inferred-queries"],
chatBodyEl.dataset.conversationId ?? "",
);
// push the user messages to the chat history
if(chatLog.by === "you"){
@ -1354,6 +1360,10 @@ export class KhojChatView extends KhojPaneView {
rawResponse += `![generated_image](${imageJson.image})`;
} else if (imageJson.intentType === "text-to-image-v3") {
rawResponse = `![](data:image/webp;base64,${imageJson.image})`;
} else if (imageJson.intentType === "excalidraw") {
const domain = this.setting.khojUrl.endsWith("/") ? this.setting.khojUrl : `${this.setting.khojUrl}/`;
const redirectMessage = `Hey, I'm not ready to show you diagrams yet here. But you can view it in ${domain}`;
rawResponse += redirectMessage;
}
if (inferredQuery) {
rawResponse += `\n\n**Inferred Query**:\n\n${inferredQuery}`;

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@ -37,6 +37,8 @@ function filenameToMimeType (filename: TFile): string {
case 'jpg':
case 'jpeg':
return 'image/jpeg';
case 'webp':
return 'image/webp';
case 'md':
case 'markdown':
return 'text/markdown';
@ -50,7 +52,7 @@ function filenameToMimeType (filename: TFile): string {
export const fileTypeToExtension = {
'pdf': ['pdf'],
'image': ['png', 'jpg', 'jpeg'],
'image': ['png', 'jpg', 'jpeg', 'webp'],
'markdown': ['md', 'markdown'],
};
export const supportedImageFilesTypes = fileTypeToExtension.image;

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@ -77,5 +77,10 @@
"1.23.3": "0.15.0",
"1.24.0": "0.15.0",
"1.24.1": "0.15.0",
"1.25.0": "0.15.0"
"1.25.0": "0.15.0",
"1.26.0": "0.15.0",
"1.26.1": "0.15.0",
"1.26.2": "0.15.0",
"1.26.3": "0.15.0",
"1.26.4": "0.15.0"
}

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@ -79,7 +79,7 @@ div.titleBar {
div.chatBoxBody {
display: grid;
height: 100%;
width: 70%;
width: 95%;
margin: auto;
}

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@ -47,7 +47,14 @@ export default function RootLayout({
child-src 'none';
object-src 'none';"
></meta>
<body className={inter.className}>{children}</body>
<body className={inter.className}>
{children}
<script
dangerouslySetInnerHTML={{
__html: `window.EXCALIDRAW_ASSET_PATH = 'https://assets.khoj.dev/@excalidraw/excalidraw/dist/';`,
}}
/>
</body>
</html>
);
}

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@ -1,7 +1,7 @@
"use client";
import styles from "./chat.module.css";
import React, { Suspense, useEffect, useState } from "react";
import React, { Suspense, useEffect, useRef, useState } from "react";
import SidePanel, { ChatSessionActionMenu } from "../components/sidePanel/chatHistorySidePanel";
import ChatHistory from "../components/chatHistory/chatHistory";
@ -19,11 +19,9 @@ import {
StreamMessage,
} from "../components/chatMessage/chatMessage";
import { useIPLocationData, useIsMobileWidth, welcomeConsole } from "../common/utils";
import ChatInputArea, { ChatOptions } from "../components/chatInputArea/chatInputArea";
import { ChatInputArea, ChatOptions } from "../components/chatInputArea/chatInputArea";
import { useAuthenticatedData } from "../common/auth";
import { AgentData } from "../agents/page";
import { DotsThreeVertical } from "@phosphor-icons/react";
import { Button } from "@/components/ui/button";
interface ChatBodyDataProps {
chatOptionsData: ChatOptions | null;
@ -34,32 +32,38 @@ interface ChatBodyDataProps {
setUploadedFiles: (files: string[]) => void;
isMobileWidth?: boolean;
isLoggedIn: boolean;
setImage64: (image64: string) => void;
setImages: (images: string[]) => void;
}
function ChatBodyData(props: ChatBodyDataProps) {
const searchParams = useSearchParams();
const conversationId = searchParams.get("conversationId");
const [message, setMessage] = useState("");
const [image, setImage] = useState<string | null>(null);
const [images, setImages] = useState<string[]>([]);
const [processingMessage, setProcessingMessage] = useState(false);
const [agentMetadata, setAgentMetadata] = useState<AgentData | null>(null);
const chatInputRef = useRef<HTMLTextAreaElement>(null);
const setQueryToProcess = props.setQueryToProcess;
const onConversationIdChange = props.onConversationIdChange;
useEffect(() => {
if (image) {
props.setImage64(encodeURIComponent(image));
}
}, [image, props.setImage64]);
const chatHistoryCustomClassName = props.isMobileWidth ? "w-full" : "w-4/6";
useEffect(() => {
const storedImage = localStorage.getItem("image");
if (storedImage) {
setImage(storedImage);
props.setImage64(encodeURIComponent(storedImage));
localStorage.removeItem("image");
if (images.length > 0) {
const encodedImages = images.map((image) => encodeURIComponent(image));
props.setImages(encodedImages);
}
}, [images, props.setImages]);
useEffect(() => {
const storedImages = localStorage.getItem("images");
if (storedImages) {
const parsedImages: string[] = JSON.parse(storedImages);
setImages(parsedImages);
const encodedImages = parsedImages.map((img: string) => encodeURIComponent(img));
props.setImages(encodedImages);
localStorage.removeItem("images");
}
const storedMessage = localStorage.getItem("message");
@ -67,7 +71,7 @@ function ChatBodyData(props: ChatBodyDataProps) {
setProcessingMessage(true);
setQueryToProcess(storedMessage);
}
}, [setQueryToProcess]);
}, [setQueryToProcess, props.setImages]);
useEffect(() => {
if (message) {
@ -89,6 +93,7 @@ function ChatBodyData(props: ChatBodyDataProps) {
props.streamedMessages[props.streamedMessages.length - 1].completed
) {
setProcessingMessage(false);
setImages([]); // Reset images after processing
} else {
setMessage("");
}
@ -108,21 +113,23 @@ function ChatBodyData(props: ChatBodyDataProps) {
setAgent={setAgentMetadata}
pendingMessage={processingMessage ? message : ""}
incomingMessages={props.streamedMessages}
customClassName={chatHistoryCustomClassName}
/>
</div>
<div
className={`${styles.inputBox} p-1 md:px-2 shadow-md bg-background align-middle items-center justify-center dark:bg-neutral-700 dark:border-0 dark:shadow-sm rounded-t-2xl rounded-b-none md:rounded-xl h-fit`}
className={`${styles.inputBox} p-1 md:px-2 shadow-md bg-background align-middle items-center justify-center dark:bg-neutral-700 dark:border-0 dark:shadow-sm rounded-t-2xl rounded-b-none md:rounded-xl h-fit ${chatHistoryCustomClassName} mr-auto ml-auto`}
>
<ChatInputArea
agentColor={agentMetadata?.color}
isLoggedIn={props.isLoggedIn}
sendMessage={(message) => setMessage(message)}
sendImage={(image) => setImage(image)}
sendImage={(image) => setImages((prevImages) => [...prevImages, image])}
sendDisabled={processingMessage}
chatOptionsData={props.chatOptionsData}
conversationId={conversationId}
isMobileWidth={props.isMobileWidth}
setUploadedFiles={props.setUploadedFiles}
ref={chatInputRef}
/>
</div>
</>
@ -139,7 +146,7 @@ export default function Chat() {
const [queryToProcess, setQueryToProcess] = useState<string>("");
const [processQuerySignal, setProcessQuerySignal] = useState(false);
const [uploadedFiles, setUploadedFiles] = useState<string[]>([]);
const [image64, setImage64] = useState<string>("");
const [images, setImages] = useState<string[]>([]);
const locationData = useIPLocationData() || {
timezone: Intl.DateTimeFormat().resolvedOptions().timeZone,
@ -176,7 +183,7 @@ export default function Chat() {
completed: false,
timestamp: new Date().toISOString(),
rawQuery: queryToProcess || "",
uploadedImageData: decodeURIComponent(image64),
images: images,
};
setMessages((prevMessages) => [...prevMessages, newStreamMessage]);
setProcessQuerySignal(true);
@ -208,7 +215,7 @@ export default function Chat() {
if (done) {
setQueryToProcess("");
setProcessQuerySignal(false);
setImage64("");
setImages([]);
break;
}
@ -257,7 +264,7 @@ export default function Chat() {
country_code: locationData.countryCode,
timezone: locationData.timezone,
}),
...(image64 && { image: image64 }),
...(images.length > 0 && { images: images }),
};
const response = await fetch(chatAPI, {
@ -271,7 +278,8 @@ export default function Chat() {
try {
await readChatStream(response);
} catch (err) {
console.error(err);
const apiError = await response.json();
console.error(apiError);
// Retrieve latest message being processed
const currentMessage = messages.find((message) => !message.completed);
if (!currentMessage) return;
@ -280,7 +288,11 @@ export default function Chat() {
const errorMessage = (err as Error).message;
if (errorMessage.includes("Error in input stream"))
currentMessage.rawResponse = `Woops! The connection broke while I was writing my thoughts down. Maybe try again in a bit or dislike this message if the issue persists?`;
else
else if (response.status === 429) {
"detail" in apiError
? (currentMessage.rawResponse = `${apiError.detail}`)
: (currentMessage.rawResponse = `I'm a bit overwhelmed at the moment. Could you try again in a bit or dislike this message if the issue persists?`);
} else
currentMessage.rawResponse = `Umm, not sure what just happened. I see this error message: ${errorMessage}. Could you try again or dislike this message if the issue persists?`;
// Complete message streaming teardown properly
@ -339,7 +351,7 @@ export default function Chat() {
setUploadedFiles={setUploadedFiles}
isMobileWidth={isMobileWidth}
onConversationIdChange={handleConversationIdChange}
setImage64={setImage64}
setImages={setImages}
/>
</Suspense>
</div>

View file

@ -68,7 +68,8 @@ export interface UserConfig {
selected_voice_model_config: number;
// user billing info
subscription_state: SubscriptionStates;
subscription_renewal_date: string;
subscription_renewal_date: string | undefined;
subscription_enabled_trial_at: string | undefined;
// server settings
khoj_cloud_subscription_url: string | undefined;
billing_enabled: boolean;
@ -78,6 +79,7 @@ export interface UserConfig {
anonymous_mode: boolean;
notion_oauth_url: string;
detail: string;
length_of_free_trial: number;
}
export function useUserConfig(detailed: boolean = false) {
@ -93,3 +95,15 @@ export function useUserConfig(detailed: boolean = false) {
return { userConfig, isLoadingUserConfig };
}
export function isUserSubscribed(userConfig: UserConfig | null): boolean {
return (
(userConfig?.subscription_state &&
[
SubscriptionStates.SUBSCRIBED.valueOf(),
SubscriptionStates.TRIAL.valueOf(),
SubscriptionStates.UNSUBSCRIBED.valueOf(),
].includes(userConfig.subscription_state)) ||
false
);
}

View file

@ -11,11 +11,10 @@ export interface RawReferenceData {
codeContext?: CodeContext;
}
export interface ResponseWithReferences {
context?: Context[];
online?: OnlineContext;
codeContext?: CodeContext;
response?: string;
export interface ResponseWithIntent {
intentType: string;
response: string;
inferredQueries?: string[];
}
interface MessageChunk {
@ -56,10 +55,14 @@ export function convertMessageChunkToJson(chunk: string): MessageChunk {
function handleJsonResponse(chunkData: any) {
const jsonData = chunkData as any;
if (jsonData.image || jsonData.detail) {
let responseWithReference = handleImageResponse(chunkData, true);
if (responseWithReference.response) return responseWithReference.response;
let responseWithIntent = handleImageResponse(chunkData, true);
return responseWithIntent;
} else if (jsonData.response) {
return jsonData.response;
return {
response: jsonData.response,
intentType: "",
inferredQueries: [],
};
} else {
throw new Error("Invalid JSON response");
}
@ -89,8 +92,18 @@ export function processMessageChunk(
return { context, onlineContext, codeContext };
} else if (chunk.type === "message") {
const chunkData = chunk.data;
// Here, handle if the response is a JSON response with an image, but the intentType is excalidraw
if (chunkData !== null && typeof chunkData === "object") {
currentMessage.rawResponse += handleJsonResponse(chunkData);
let responseWithIntent = handleJsonResponse(chunkData);
if (responseWithIntent.intentType && responseWithIntent.intentType === "excalidraw") {
currentMessage.rawResponse = responseWithIntent.response;
} else {
currentMessage.rawResponse += responseWithIntent.response;
}
currentMessage.intentType = responseWithIntent.intentType;
currentMessage.inferredQueries = responseWithIntent.inferredQueries;
} else if (
typeof chunkData === "string" &&
chunkData.trim()?.startsWith("{") &&
@ -98,7 +111,10 @@ export function processMessageChunk(
) {
try {
const jsonData = JSON.parse(chunkData.trim());
currentMessage.rawResponse += handleJsonResponse(jsonData);
let responseWithIntent = handleJsonResponse(jsonData);
currentMessage.rawResponse += responseWithIntent.response;
currentMessage.intentType = responseWithIntent.intentType;
currentMessage.inferredQueries = responseWithIntent.inferredQueries;
} catch (e) {
currentMessage.rawResponse += JSON.stringify(chunkData);
}
@ -148,42 +164,26 @@ export function processMessageChunk(
return { context, onlineContext, codeContext };
}
export function handleImageResponse(imageJson: any, liveStream: boolean): ResponseWithReferences {
export function handleImageResponse(imageJson: any, liveStream: boolean): ResponseWithIntent {
let rawResponse = "";
if (imageJson.image) {
const inferredQuery = imageJson.inferredQueries?.[0] ?? "generated image";
// If response has image field, response is a generated image.
if (imageJson.intentType === "text-to-image") {
rawResponse += `![generated_image](data:image/png;base64,${imageJson.image})`;
} else if (imageJson.intentType === "text-to-image2") {
rawResponse += `![generated_image](${imageJson.image})`;
} else if (imageJson.intentType === "text-to-image-v3") {
rawResponse = `![](data:image/webp;base64,${imageJson.image})`;
}
if (inferredQuery && !liveStream) {
rawResponse += `\n\n${inferredQuery}`;
}
// If response has image field, response may be a generated image
rawResponse = imageJson.image;
}
let reference: ResponseWithReferences = {};
let responseWithIntent: ResponseWithIntent = {
intentType: imageJson.intentType,
response: rawResponse,
inferredQueries: imageJson.inferredQueries,
};
if (imageJson.context && imageJson.context.length > 0) {
const rawReferenceAsJson = imageJson.context;
if (rawReferenceAsJson instanceof Array) {
reference.context = rawReferenceAsJson;
} else if (typeof rawReferenceAsJson === "object" && rawReferenceAsJson !== null) {
reference.online = rawReferenceAsJson;
}
}
if (imageJson.detail) {
// The detail field contains the improved image prompt
rawResponse += imageJson.detail;
}
reference.response = rawResponse;
return reference;
return responseWithIntent;
}
export function renderCodeGenImageInline(message: string, codeContext: CodeContext) {
@ -228,7 +228,11 @@ export function modifyFileFilterForConversation(
},
body: JSON.stringify(body),
})
.then((response) => response.json())
.then((res) => {
if (!res.ok)
throw new Error(`Failed to call API at ${addUrl} with error ${res.statusText}`);
return res.json();
})
.then((data) => {
setAddedFiles(data);
})

View file

@ -48,6 +48,7 @@ import {
Oven,
Gavel,
Broadcast,
KeyReturn,
} from "@phosphor-icons/react";
import { Markdown, OrgMode, Pdf, Word } from "@/app/components/logo/fileLogo";
@ -193,6 +194,10 @@ export function getIconForSlashCommand(command: string, customClassName: string
}
if (command.includes("default")) {
return <KeyReturn className={className} />;
}
if (command.includes("diagram")) {
return <Shapes className={className} />;
}
@ -241,6 +246,7 @@ function getIconFromFilename(
case "jpg":
case "jpeg":
case "png":
case "webp":
return <Image className={className} weight="fill" />;
default:
return <File className={className} weight="fill" />;

View file

@ -70,3 +70,19 @@ export function useIsMobileWidth() {
return isMobileWidth;
}
export function useDebounce<T>(value: T, delay: number): T {
const [debouncedValue, setDebouncedValue] = useState<T>(value);
useEffect(() => {
const handler = setTimeout(() => {
setDebouncedValue(value);
}, delay);
return () => {
clearTimeout(handler);
};
}, [value, delay]);
return debouncedValue;
}

View file

@ -0,0 +1,20 @@
.agentPersonality p {
white-space: inherit;
overflow: hidden;
height: 77px;
line-height: 1.5;
}
div.agentPersonality {
text-align: left;
grid-column: span 3;
overflow: hidden;
}
button.infoButton {
border: none;
background-color: transparent !important;
text-align: left;
font-family: inherit;
font-size: medium;
}

File diff suppressed because it is too large Load diff

View file

@ -2,12 +2,7 @@ div.chatHistory {
display: flex;
flex-direction: column;
height: 100%;
}
div.chatLayout {
height: 80vh;
overflow-y: auto;
margin: 0 auto;
margin: auto;
}
div.agentIndicator a {

View file

@ -37,6 +37,7 @@ interface ChatHistoryProps {
pendingMessage?: string;
publicConversationSlug?: string;
setAgent: (agent: AgentData) => void;
customClassName?: string;
}
function constructTrainOfThought(
@ -255,7 +256,7 @@ export default function ChatHistory(props: ChatHistoryProps) {
return (
<ScrollArea className={`h-[80vh] relative`} ref={scrollAreaRef}>
<div>
<div className={styles.chatHistory}>
<div className={`${styles.chatHistory} ${props.customClassName}`}>
<div ref={sentinelRef} style={{ height: "1px" }}>
{fetchingData && (
<InlineLoading message="Loading Conversation" className="opacity-50" />
@ -299,7 +300,7 @@ export default function ChatHistory(props: ChatHistoryProps) {
created: message.timestamp,
by: "you",
automationId: "",
uploadedImageData: message.uploadedImageData,
images: message.images,
}}
customClassName="fullHistory"
borderLeftColor={`${data?.agent?.color}-500`}
@ -324,6 +325,12 @@ export default function ChatHistory(props: ChatHistoryProps) {
by: "khoj",
automationId: "",
rawQuery: message.rawQuery,
intent: {
type: message.intentType || "",
query: message.rawQuery,
"memory-type": "",
"inferred-queries": message.inferredQueries || [],
},
}}
customClassName="fullHistory"
borderLeftColor={`${data?.agent?.color}-500`}
@ -344,7 +351,6 @@ export default function ChatHistory(props: ChatHistoryProps) {
created: new Date().getTime().toString(),
by: "you",
automationId: "",
uploadedImageData: props.pendingMessage,
}}
customClassName="fullHistory"
borderLeftColor={`${data?.agent?.color}-500`}
@ -369,18 +375,20 @@ export default function ChatHistory(props: ChatHistoryProps) {
</div>
)}
</div>
{!isNearBottom && (
<button
title="Scroll to bottom"
className="absolute bottom-4 right-5 bg-white dark:bg-[hsl(var(--background))] text-neutral-500 dark:text-white p-2 rounded-full shadow-xl"
onClick={() => {
scrollToBottom();
setIsNearBottom(true);
}}
>
<ArrowDown size={24} />
</button>
)}
<div className={`${props.customClassName} fixed bottom-[15%] z-10`}>
{!isNearBottom && (
<button
title="Scroll to bottom"
className="absolute bottom-0 right-0 bg-white dark:bg-[hsl(var(--background))] text-neutral-500 dark:text-white p-2 rounded-full shadow-xl"
onClick={() => {
scrollToBottom();
setIsNearBottom(true);
}}
>
<ArrowDown size={24} />
</button>
)}
</div>
</div>
</ScrollArea>
);

View file

@ -1,25 +1,9 @@
import styles from "./chatInputArea.module.css";
import React, { useEffect, useRef, useState } from "react";
import React, { useEffect, useRef, useState, forwardRef } from "react";
import DOMPurify from "dompurify";
import "katex/dist/katex.min.css";
import {
ArrowRight,
ArrowUp,
Browser,
ChatsTeardrop,
GlobeSimple,
Gps,
Image,
Microphone,
Notebook,
Paperclip,
X,
Question,
Robot,
Shapes,
Stop,
} from "@phosphor-icons/react";
import { ArrowUp, Microphone, Paperclip, X, Stop } from "@phosphor-icons/react";
import {
Command,
@ -68,7 +52,7 @@ interface ChatInputProps {
agentColor?: string;
}
export default function ChatInputArea(props: ChatInputProps) {
export const ChatInputArea = forwardRef<HTMLTextAreaElement, ChatInputProps>((props, ref) => {
const [message, setMessage] = useState("");
const fileInputRef = useRef<HTMLInputElement>(null);
@ -78,15 +62,17 @@ export default function ChatInputArea(props: ChatInputProps) {
const [loginRedirectMessage, setLoginRedirectMessage] = useState<string | null>(null);
const [showLoginPrompt, setShowLoginPrompt] = useState(false);
const [recording, setRecording] = useState(false);
const [imageUploaded, setImageUploaded] = useState(false);
const [imagePath, setImagePath] = useState<string>("");
const [imageData, setImageData] = useState<string | null>(null);
const [imagePaths, setImagePaths] = useState<string[]>([]);
const [imageData, setImageData] = useState<string[]>([]);
const [recording, setRecording] = useState(false);
const [mediaRecorder, setMediaRecorder] = useState<MediaRecorder | null>(null);
const [progressValue, setProgressValue] = useState(0);
const [isDragAndDropping, setIsDragAndDropping] = useState(false);
const chatInputRef = ref as React.MutableRefObject<HTMLTextAreaElement>;
useEffect(() => {
if (!uploading) {
setProgressValue(0);
@ -106,27 +92,31 @@ export default function ChatInputArea(props: ChatInputProps) {
useEffect(() => {
async function fetchImageData() {
if (imagePath) {
const response = await fetch(imagePath);
const blob = await response.blob();
const reader = new FileReader();
reader.onload = function () {
const base64data = reader.result;
setImageData(base64data as string);
};
reader.readAsDataURL(blob);
if (imagePaths.length > 0) {
const newImageData = await Promise.all(
imagePaths.map(async (path) => {
const response = await fetch(path);
const blob = await response.blob();
return new Promise<string>((resolve) => {
const reader = new FileReader();
reader.onload = () => resolve(reader.result as string);
reader.readAsDataURL(blob);
});
}),
);
setImageData(newImageData);
}
setUploading(false);
}
setUploading(true);
fetchImageData();
}, [imagePath]);
}, [imagePaths]);
function onSendMessage() {
if (imageUploaded) {
setImageUploaded(false);
setImagePath("");
props.sendImage(imageData || "");
setImagePaths([]);
imageData.forEach((data) => props.sendImage(data));
}
if (!message.trim()) return;
@ -168,22 +158,29 @@ export default function ChatInputArea(props: ChatInputProps) {
function uploadFiles(files: FileList) {
if (!props.isLoggedIn) {
setLoginRedirectMessage("Whoa! You need to login to upload files");
setLoginRedirectMessage("Please login to chat with your files");
setShowLoginPrompt(true);
return;
}
// check for image file
const image_endings = ["jpg", "jpeg", "png"];
// check for image files
const image_endings = ["jpg", "jpeg", "png", "webp"];
const newImagePaths: string[] = [];
for (let i = 0; i < files.length; i++) {
const file = files[i];
const file_extension = file.name.split(".").pop();
if (image_endings.includes(file_extension || "")) {
setImageUploaded(true);
setImagePath(DOMPurify.sanitize(URL.createObjectURL(file)));
return;
newImagePaths.push(DOMPurify.sanitize(URL.createObjectURL(file)));
}
}
if (newImagePaths.length > 0) {
setImageUploaded(true);
setImagePaths((prevPaths) => [...prevPaths, ...newImagePaths]);
// Set focus to the input for user message after uploading files
chatInputRef?.current?.focus();
return;
}
uploadDataForIndexing(
files,
setWarning,
@ -192,6 +189,9 @@ export default function ChatInputArea(props: ChatInputProps) {
props.setUploadedFiles,
props.conversationId,
);
// Set focus to the input for user message after uploading files
chatInputRef?.current?.focus();
}
// Assuming this function is added within the same context as the provided excerpt
@ -270,9 +270,8 @@ export default function ChatInputArea(props: ChatInputProps) {
}
}, [recording, mediaRecorder]);
const chatInputRef = useRef<HTMLTextAreaElement>(null);
useEffect(() => {
if (!chatInputRef.current) return;
if (!chatInputRef?.current) return;
chatInputRef.current.style.height = "auto";
chatInputRef.current.style.height =
Math.max(chatInputRef.current.scrollHeight - 24, 64) + "px";
@ -288,9 +287,12 @@ export default function ChatInputArea(props: ChatInputProps) {
setIsDragAndDropping(false);
}
function removeImageUpload() {
setImageUploaded(false);
setImagePath("");
function removeImageUpload(index: number) {
setImagePaths((prevPaths) => prevPaths.filter((_, i) => i !== index));
setImageData((prevData) => prevData.filter((_, i) => i !== index));
if (imagePaths.length === 1) {
setImageUploaded(false);
}
}
return (
@ -407,24 +409,11 @@ export default function ChatInputArea(props: ChatInputProps) {
</div>
)}
<div
className={`${styles.actualInputArea} items-center justify-between dark:bg-neutral-700 relative ${isDragAndDropping && "animate-pulse"}`}
className={`${styles.actualInputArea} justify-between dark:bg-neutral-700 relative ${isDragAndDropping && "animate-pulse"}`}
onDragOver={handleDragOver}
onDragLeave={handleDragLeave}
onDrop={handleDragAndDropFiles}
>
{imageUploaded && (
<div className="absolute bottom-[80px] left-0 right-0 dark:bg-neutral-700 bg-white pt-5 pb-5 w-full rounded-lg border dark:border-none grid grid-cols-2">
<div className="pl-4 pr-4">
<img src={imagePath} alt="img" className="w-auto max-h-[100px]" />
</div>
<div className="pl-4 pr-4">
<X
className="w-6 h-6 float-right dark:hover:bg-[hsl(var(--background))] hover:bg-neutral-100 rounded-sm"
onClick={removeImageUpload}
/>
</div>
</div>
)}
<input
type="file"
multiple={true}
@ -432,15 +421,37 @@ export default function ChatInputArea(props: ChatInputProps) {
onChange={handleFileChange}
style={{ display: "none" }}
/>
<Button
variant={"ghost"}
className="!bg-none p-0 m-2 h-auto text-3xl rounded-full text-gray-300 hover:text-gray-500"
disabled={props.sendDisabled}
onClick={handleFileButtonClick}
>
<Paperclip className="w-8 h-8" />
</Button>
<div className="grid w-full gap-1.5 relative">
<div className="flex items-end pb-4">
<Button
variant={"ghost"}
className="!bg-none p-0 m-2 h-auto text-3xl rounded-full text-gray-300 hover:text-gray-500"
disabled={props.sendDisabled}
onClick={handleFileButtonClick}
>
<Paperclip className="w-8 h-8" />
</Button>
</div>
<div className="flex-grow flex flex-col w-full gap-1.5 relative pb-2">
<div className="flex items-center gap-2 overflow-x-auto">
{imageUploaded &&
imagePaths.map((path, index) => (
<div key={index} className="relative flex-shrink-0 pb-3 pt-2 group">
<img
src={path}
alt={`img-${index}`}
className="w-auto h-16 object-cover rounded-xl"
/>
<Button
variant="ghost"
size="icon"
className="absolute -top-0 -right-2 h-5 w-5 rounded-full bg-neutral-200 dark:bg-neutral-600 hover:bg-neutral-300 dark:hover:bg-neutral-500 opacity-0 group-hover:opacity-100 transition-opacity"
onClick={() => removeImageUpload(index)}
>
<X className="h-3 w-3" />
</Button>
</div>
))}
</div>
<Textarea
ref={chatInputRef}
className={`border-none w-full h-16 min-h-16 max-h-[128px] md:py-4 rounded-lg resize-none dark:bg-neutral-700 ${props.isMobileWidth ? "text-md" : "text-lg"}`}
@ -449,9 +460,9 @@ export default function ChatInputArea(props: ChatInputProps) {
autoFocus={true}
value={message}
onKeyDown={(e) => {
if (e.key === "Enter" && !e.shiftKey) {
if (e.key === "Enter" && !e.shiftKey && !props.isMobileWidth) {
setImageUploaded(false);
setImagePath("");
setImagePaths([]);
e.preventDefault();
onSendMessage();
}
@ -460,58 +471,62 @@ export default function ChatInputArea(props: ChatInputProps) {
disabled={props.sendDisabled || recording}
/>
</div>
{recording ? (
<TooltipProvider>
<Tooltip>
<TooltipTrigger asChild>
<Button
variant="default"
className={`${!recording && "hidden"} ${props.agentColor ? convertToBGClass(props.agentColor) : "bg-orange-300 hover:bg-orange-500"} rounded-full p-1 m-2 h-auto text-3xl transition transform md:hover:-translate-y-1`}
onClick={() => {
setRecording(!recording);
}}
disabled={props.sendDisabled}
>
<Stop weight="fill" className="w-6 h-6" />
</Button>
</TooltipTrigger>
<TooltipContent>
Click to stop recording and transcribe your voice.
</TooltipContent>
</Tooltip>
</TooltipProvider>
) : mediaRecorder ? (
<InlineLoading />
) : (
<TooltipProvider>
<Tooltip>
<TooltipTrigger asChild>
<Button
variant="default"
className={`${!message || recording || "hidden"} ${props.agentColor ? convertToBGClass(props.agentColor) : "bg-orange-300 hover:bg-orange-500"} rounded-full p-1 m-2 h-auto text-3xl transition transform md:hover:-translate-y-1`}
onClick={() => {
setMessage("Listening...");
setRecording(!recording);
}}
disabled={props.sendDisabled}
>
<Microphone weight="fill" className="w-6 h-6" />
</Button>
</TooltipTrigger>
<TooltipContent>
Click to transcribe your message with voice.
</TooltipContent>
</Tooltip>
</TooltipProvider>
)}
<Button
className={`${(!message || recording) && "hidden"} ${props.agentColor ? convertToBGClass(props.agentColor) : "bg-orange-300 hover:bg-orange-500"} rounded-full p-1 m-2 h-auto text-3xl transition transform md:hover:-translate-y-1`}
onClick={onSendMessage}
disabled={props.sendDisabled}
>
<ArrowUp className="w-6 h-6" weight="bold" />
</Button>
<div className="flex items-end pb-4">
{recording ? (
<TooltipProvider>
<Tooltip>
<TooltipTrigger asChild>
<Button
variant="default"
className={`${!recording && "hidden"} ${props.agentColor ? convertToBGClass(props.agentColor) : "bg-orange-300 hover:bg-orange-500"} rounded-full p-1 m-2 h-auto text-3xl transition transform md:hover:-translate-y-1`}
onClick={() => {
setRecording(!recording);
}}
disabled={props.sendDisabled}
>
<Stop weight="fill" className="w-6 h-6" />
</Button>
</TooltipTrigger>
<TooltipContent>
Click to stop recording and transcribe your voice.
</TooltipContent>
</Tooltip>
</TooltipProvider>
) : mediaRecorder ? (
<InlineLoading />
) : (
<TooltipProvider>
<Tooltip>
<TooltipTrigger asChild>
<Button
variant="default"
className={`${!message || recording || "hidden"} ${props.agentColor ? convertToBGClass(props.agentColor) : "bg-orange-300 hover:bg-orange-500"} rounded-full p-1 m-2 h-auto text-3xl transition transform md:hover:-translate-y-1`}
onClick={() => {
setMessage("Listening...");
setRecording(!recording);
}}
disabled={props.sendDisabled}
>
<Microphone weight="fill" className="w-6 h-6" />
</Button>
</TooltipTrigger>
<TooltipContent>
Click to transcribe your message with voice.
</TooltipContent>
</Tooltip>
</TooltipProvider>
)}
<Button
className={`${(!message || recording) && "hidden"} ${props.agentColor ? convertToBGClass(props.agentColor) : "bg-orange-300 hover:bg-orange-500"} rounded-full p-1 m-2 h-auto text-3xl transition transform md:hover:-translate-y-1`}
onClick={onSendMessage}
disabled={props.sendDisabled}
>
<ArrowUp className="w-6 h-6" weight="bold" />
</Button>
</div>
</div>
</>
);
}
});
ChatInputArea.displayName = "ChatInputArea";

View file

@ -57,7 +57,26 @@ div.emptyChatMessage {
display: none;
}
div.chatMessageContainer img {
div.imagesContainer {
display: flex;
overflow-x: auto;
padding-bottom: 8px;
margin-bottom: 8px;
}
div.imageWrapper {
flex: 0 0 auto;
margin-right: 8px;
}
div.imageWrapper img {
width: auto;
height: 128px;
object-fit: cover;
border-radius: 8px;
}
div.chatMessageContainer > img {
width: auto;
height: auto;
max-width: 100%;

View file

@ -28,6 +28,7 @@ import {
ClipboardText,
Check,
Code,
Shapes,
} from "@phosphor-icons/react";
import DOMPurify from "dompurify";
@ -37,6 +38,7 @@ import { AgentData } from "@/app/agents/page";
import renderMathInElement from "katex/contrib/auto-render";
import "katex/dist/katex.min.css";
import ExcalidrawComponent from "../excalidraw/excalidraw";
const md = new markdownIt({
html: true,
@ -137,7 +139,7 @@ export interface SingleChatMessage {
rawQuery?: string;
intent?: Intent;
agent?: AgentData;
uploadedImageData?: string;
images?: string[];
}
export interface StreamMessage {
@ -150,7 +152,9 @@ export interface StreamMessage {
rawQuery: string;
timestamp: string;
agent?: AgentData;
uploadedImageData?: string;
images?: string[];
intentType?: string;
inferredQueries?: string[];
}
export interface ChatHistoryData {
@ -232,7 +236,6 @@ interface ChatMessageProps {
borderLeftColor?: string;
isLastMessage?: boolean;
agent?: AgentData;
uploadedImageData?: string;
}
interface TrainOfThoughtProps {
@ -276,6 +279,10 @@ function chooseIconFromHeader(header: string, iconColor: string) {
return <Aperture className={`${classNames}`} />;
}
if (compareHeader.includes("diagram")) {
return <Shapes className={`${classNames}`} />;
}
if (compareHeader.includes("paint")) {
return <Palette className={`${classNames}`} />;
}
@ -311,6 +318,7 @@ const ChatMessage = forwardRef<HTMLDivElement, ChatMessageProps>((props, ref) =>
const [markdownRendered, setMarkdownRendered] = useState<string>("");
const [isPlaying, setIsPlaying] = useState<boolean>(false);
const [interrupted, setInterrupted] = useState<boolean>(false);
const [excalidrawData, setExcalidrawData] = useState<string>("");
const interruptedRef = useRef<boolean>(false);
const messageRef = useRef<HTMLDivElement>(null);
@ -347,8 +355,14 @@ const ChatMessage = forwardRef<HTMLDivElement, ChatMessageProps>((props, ref) =>
}, [messageRef.current]);
useEffect(() => {
// Prepare initial message for rendering
let message = props.chatMessage.message;
if (props.chatMessage.intent && props.chatMessage.intent.type == "excalidraw") {
message = props.chatMessage.intent["inferred-queries"][0];
setExcalidrawData(props.chatMessage.message);
}
// Replace LaTeX delimiters with placeholders
message = message
.replace(/\\\(/g, "LEFTPAREN")
@ -356,8 +370,50 @@ const ChatMessage = forwardRef<HTMLDivElement, ChatMessageProps>((props, ref) =>
.replace(/\\\[/g, "LEFTBRACKET")
.replace(/\\\]/g, "RIGHTBRACKET");
if (props.chatMessage.uploadedImageData) {
message = `![uploaded image](${props.chatMessage.uploadedImageData})\n\n${message}`;
const intentTypeHandlers = {
"text-to-image": (msg: string) => `![generated image](data:image/png;base64,${msg})`,
"text-to-image2": (msg: string) => `![generated image](${msg})`,
"text-to-image-v3": (msg: string) =>
`![generated image](data:image/webp;base64,${msg})`,
excalidraw: (msg: string) => msg,
};
// Handle intent-specific rendering
if (props.chatMessage.intent) {
const { type, "inferred-queries": inferredQueries } = props.chatMessage.intent;
console.log("intent type", type);
if (type in intentTypeHandlers) {
message = intentTypeHandlers[type as keyof typeof intentTypeHandlers](message);
}
if (type.includes("text-to-image") && inferredQueries?.length > 0) {
message += `\n\n${inferredQueries[0]}`;
}
}
// Handle user attached images rendering
let messageForClipboard = message;
let messageToRender = message;
if (props.chatMessage.images && props.chatMessage.images.length > 0) {
const sanitizedImages = props.chatMessage.images.map((image) => {
const decodedImage = image.startsWith("data%3Aimage")
? decodeURIComponent(image)
: image;
return DOMPurify.sanitize(decodedImage);
});
const imagesInMd = sanitizedImages
.map((sanitizedImage, index) => {
return `![uploaded image ${index + 1}](${sanitizedImage})`;
})
.join("\n");
const imagesInHtml = sanitizedImages
.map((sanitizedImage, index) => {
return `<div class="${styles.imageWrapper}"><img src="${sanitizedImage}" alt="uploaded image ${index + 1}" /></div>`;
})
.join("");
const userImagesInHtml = `<div class="${styles.imagesContainer}">${imagesInHtml}</div>`;
messageForClipboard = `${imagesInMd}\n\n${messageForClipboard}`;
messageToRender = `${userImagesInHtml}${messageToRender}`;
}
if (props.chatMessage.intent && props.chatMessage.intent.type == "text-to-image") {
@ -402,10 +458,11 @@ const ChatMessage = forwardRef<HTMLDivElement, ChatMessageProps>((props, ref) =>
});
}
setTextRendered(message);
// Set the message text
setTextRendered(messageForClipboard);
// Render the markdown
let markdownRendered = md.render(message);
let markdownRendered = md.render(messageToRender);
// Replace placeholders with LaTeX delimiters
markdownRendered = markdownRendered
@ -416,7 +473,7 @@ const ChatMessage = forwardRef<HTMLDivElement, ChatMessageProps>((props, ref) =>
// Sanitize and set the rendered markdown
setMarkdownRendered(DOMPurify.sanitize(markdownRendered));
}, [props.chatMessage.message, props.chatMessage.intent]);
}, [props.chatMessage.message, props.chatMessage.images, props.chatMessage.intent]);
useEffect(() => {
if (copySuccess) {
@ -607,6 +664,7 @@ const ChatMessage = forwardRef<HTMLDivElement, ChatMessageProps>((props, ref) =>
className={styles.chatMessage}
dangerouslySetInnerHTML={{ __html: markdownRendered }}
/>
{excalidrawData && <ExcalidrawComponent data={excalidrawData} />}
</div>
<div className={styles.teaserReferencesContainer}>
<TeaserReferencesSection

View file

@ -0,0 +1,24 @@
"use client";
import dynamic from "next/dynamic";
import { Suspense } from "react";
import Loading from "../../components/loading/loading";
// Since client components get prerenderd on server as well hence importing
// the excalidraw stuff dynamically with ssr false
const ExcalidrawWrapper = dynamic(() => import("./excalidrawWrapper").then((mod) => mod.default), {
ssr: false,
});
interface ExcalidrawComponentProps {
data: any;
}
export default function ExcalidrawComponent(props: ExcalidrawComponentProps) {
return (
<Suspense fallback={<Loading />}>
<ExcalidrawWrapper data={props.data} />
</Suspense>
);
}

View file

@ -0,0 +1,149 @@
"use client";
import { useState, useEffect } from "react";
import dynamic from "next/dynamic";
import { ExcalidrawProps } from "@excalidraw/excalidraw/types/types";
import { ExcalidrawElement } from "@excalidraw/excalidraw/types/element/types";
import { ExcalidrawElementSkeleton } from "@excalidraw/excalidraw/types/data/transform";
const Excalidraw = dynamic<ExcalidrawProps>(
async () => (await import("@excalidraw/excalidraw")).Excalidraw,
{
ssr: false,
},
);
import { convertToExcalidrawElements } from "@excalidraw/excalidraw";
import { Button } from "@/components/ui/button";
import { ArrowsInSimple, ArrowsOutSimple } from "@phosphor-icons/react";
interface ExcalidrawWrapperProps {
data: ExcalidrawElementSkeleton[];
}
export default function ExcalidrawWrapper(props: ExcalidrawWrapperProps) {
const [excalidrawElements, setExcalidrawElements] = useState<ExcalidrawElement[]>([]);
const [expanded, setExpanded] = useState<boolean>(false);
const isValidExcalidrawElement = (element: ExcalidrawElementSkeleton): boolean => {
return (
element.x !== undefined &&
element.y !== undefined &&
element.id !== undefined &&
element.type !== undefined
);
};
useEffect(() => {
if (expanded) {
onkeydown = (e) => {
if (e.key === "Escape") {
setExpanded(false);
// Trigger a resize event to make Excalidraw adjust its size
window.dispatchEvent(new Event("resize"));
}
};
} else {
onkeydown = null;
}
}, [expanded]);
useEffect(() => {
// Do some basic validation
const basicValidSkeletons: ExcalidrawElementSkeleton[] = [];
for (const element of props.data) {
if (isValidExcalidrawElement(element as ExcalidrawElementSkeleton)) {
basicValidSkeletons.push(element as ExcalidrawElementSkeleton);
}
}
const validSkeletons: ExcalidrawElementSkeleton[] = [];
for (const element of basicValidSkeletons) {
if (element.type === "frame") {
continue;
}
if (element.type === "arrow") {
const start = basicValidSkeletons.find((child) => child.id === element.start?.id);
const end = basicValidSkeletons.find((child) => child.id === element.end?.id);
if (start && end) {
validSkeletons.push(element);
}
} else {
validSkeletons.push(element);
}
}
for (const element of basicValidSkeletons) {
if (element.type === "frame") {
const children = element.children?.map((childId) => {
return validSkeletons.find((child) => child.id === childId);
});
// Get the valid children, filter out any undefined values
const validChildrenIds: readonly string[] = children
?.map((child) => child?.id)
.filter((id) => id !== undefined) as string[];
if (validChildrenIds === undefined || validChildrenIds.length === 0) {
continue;
}
validSkeletons.push({
...element,
children: validChildrenIds,
});
}
}
const elements = convertToExcalidrawElements(validSkeletons);
setExcalidrawElements(elements);
}, []);
return (
<div className="relative">
<div
className={`${expanded ? "fixed inset-0 bg-black bg-opacity-50 backdrop-blur-sm z-50 flex items-center justify-center" : ""}`}
>
<Button
onClick={() => {
setExpanded(!expanded);
// Trigger a resize event to make Excalidraw adjust its size
window.dispatchEvent(new Event("resize"));
}}
variant={"outline"}
className={`${expanded ? "absolute top-2 left-2 z-[60]" : ""}`}
>
{expanded ? (
<ArrowsInSimple className="h-4 w-4" />
) : (
<ArrowsOutSimple className="h-4 w-4" />
)}
</Button>
<div
className={`
${expanded ? "w-[80vw] h-[80vh]" : "w-full h-[500px]"}
bg-white overflow-hidden rounded-lg relative
`}
>
<Excalidraw
initialData={{
elements: excalidrawElements,
appState: { zenModeEnabled: true },
scrollToContent: true,
}}
// TODO - Create a common function to detect if the theme is dark?
theme={localStorage.getItem("theme") === "dark" ? "dark" : "light"}
validateEmbeddable={true}
renderTopRightUI={(isMobile, appState) => {
return <></>;
}}
/>
</div>
</div>
</div>
);
}

View file

@ -98,7 +98,11 @@ import { KhojLogoType } from "@/app/components/logo/khojLogo";
import NavMenu from "@/app/components/navMenu/navMenu";
// Define a fetcher function
const fetcher = (url: string) => fetch(url).then((res) => res.json());
const fetcher = (url: string) =>
fetch(url).then((res) => {
if (!res.ok) throw new Error(`Failed to call API at ${url} with error ${res.statusText}`);
return res.json();
});
interface GroupedChatHistory {
[key: string]: ChatHistory[];
@ -181,20 +185,15 @@ function FilesMenu(props: FilesMenuProps) {
useEffect(() => {
if (!files) return;
const uniqueFiles = Array.from(new Set(files));
let sortedUniqueFiles = Array.from(new Set(files)).sort();
// First, sort lexically
uniqueFiles.sort();
let sortedFiles = uniqueFiles;
if (addedFiles) {
sortedFiles = addedFiles.concat(
sortedFiles.filter((filename: string) => !addedFiles.includes(filename)),
if (Array.isArray(addedFiles)) {
sortedUniqueFiles = addedFiles.concat(
sortedUniqueFiles.filter((filename: string) => !addedFiles.includes(filename)),
);
}
setUnfilteredFiles(sortedFiles);
setUnfilteredFiles(sortedUniqueFiles);
}, [files, addedFiles]);
useEffect(() => {
@ -204,8 +203,10 @@ function FilesMenu(props: FilesMenuProps) {
}, [props.uploadedFiles]);
useEffect(() => {
if (selectedFiles) {
if (Array.isArray(selectedFiles)) {
setAddedFiles(selectedFiles);
} else {
setAddedFiles([]);
}
}, [selectedFiles]);
@ -269,7 +270,7 @@ function FilesMenu(props: FilesMenuProps) {
</CommandItem>
)}
{unfilteredFiles.map((filename: string) =>
addedFiles && addedFiles.includes(filename) ? (
Array.isArray(addedFiles) && addedFiles.includes(filename) ? (
<CommandItem
key={filename}
value={filename}

View file

@ -3,26 +3,33 @@ import "./globals.css";
import styles from "./page.module.css";
import "katex/dist/katex.min.css";
import React, { useEffect, useState } from "react";
import React, { useEffect, useRef, useState } from "react";
import useSWR from "swr";
import Image from "next/image";
import { ArrowCounterClockwise } from "@phosphor-icons/react";
import { Card, CardTitle } from "@/components/ui/card";
import SuggestionCard from "@/app/components/suggestions/suggestionCard";
import SidePanel from "@/app/components/sidePanel/chatHistorySidePanel";
import Loading from "@/app/components/loading/loading";
import ChatInputArea, { ChatOptions } from "@/app/components/chatInputArea/chatInputArea";
import { ChatInputArea, ChatOptions } from "@/app/components/chatInputArea/chatInputArea";
import { Suggestion, suggestionsData } from "@/app/components/suggestions/suggestionsData";
import LoginPrompt from "@/app/components/loginPrompt/loginPrompt";
import { useAuthenticatedData, UserConfig, useUserConfig } from "@/app/common/auth";
import {
isUserSubscribed,
useAuthenticatedData,
UserConfig,
useUserConfig,
} from "@/app/common/auth";
import { convertColorToBorderClass } from "@/app/common/colorUtils";
import { getIconFromIconName } from "@/app/common/iconUtils";
import { AgentData } from "@/app/agents/page";
import { createNewConversation } from "./common/chatFunctions";
import { useIsMobileWidth } from "./common/utils";
import { useSearchParams } from "next/navigation";
import { useDebounce, useIsMobileWidth } from "./common/utils";
import { useRouter, useSearchParams } from "next/navigation";
import { ScrollArea, ScrollBar } from "@/components/ui/scroll-area";
import { AgentCard } from "@/app/components/agentCard/agentCard";
import { Popover, PopoverContent, PopoverTrigger } from "@/components/ui/popover";
interface ChatBodyDataProps {
chatOptionsData: ChatOptions | null;
@ -44,14 +51,19 @@ function FisherYatesShuffle(array: any[]) {
function ChatBodyData(props: ChatBodyDataProps) {
const [message, setMessage] = useState("");
const [image, setImage] = useState<string | null>(null);
const [images, setImages] = useState<string[]>([]);
const [processingMessage, setProcessingMessage] = useState(false);
const [greeting, setGreeting] = useState("");
const [shuffledOptions, setShuffledOptions] = useState<Suggestion[]>([]);
const [hoveredAgent, setHoveredAgent] = useState<string | null>(null);
const debouncedHoveredAgent = useDebounce(hoveredAgent, 500);
const [isPopoverOpen, setIsPopoverOpen] = useState(false);
const [selectedAgent, setSelectedAgent] = useState<string | null>("khoj");
const [agentIcons, setAgentIcons] = useState<JSX.Element[]>([]);
const [agents, setAgents] = useState<AgentData[]>([]);
const chatInputRef = useRef<HTMLTextAreaElement>(null);
const [showLoginPrompt, setShowLoginPrompt] = useState(false);
const router = useRouter();
const searchParams = useSearchParams();
const queryParam = searchParams.get("q");
@ -61,6 +73,12 @@ function ChatBodyData(props: ChatBodyDataProps) {
}
}, [queryParam]);
useEffect(() => {
if (debouncedHoveredAgent) {
setIsPopoverOpen(true);
}
}, [debouncedHoveredAgent]);
const onConversationIdChange = props.onConversationIdChange;
const agentsFetcher = () =>
@ -72,6 +90,10 @@ function ChatBodyData(props: ChatBodyDataProps) {
revalidateOnFocus: false,
});
const openAgentEditCard = (agentSlug: string) => {
router.push(`/agents?agent=${agentSlug}`);
};
function shuffleAndSetOptions() {
const shuffled = FisherYatesShuffle(suggestionsData);
setShuffledOptions(shuffled.slice(0, 3));
@ -108,22 +130,13 @@ function ChatBodyData(props: ChatBodyDataProps) {
}, [props.chatOptionsData]);
useEffect(() => {
const nSlice = props.isMobileWidth ? 2 : 4;
const shuffledAgents = agentsData ? [...agentsData].sort(() => 0.5 - Math.random()) : [];
const agents = agentsData ? [agentsData[0]] : []; // Always add the first/default agent.
shuffledAgents.slice(0, nSlice - 1).forEach((agent) => {
if (!agents.find((a) => a.slug === agent.slug)) {
agents.push(agent);
}
});
const agents = (agentsData || []).filter((agent) => agent !== null && agent !== undefined);
setAgents(agents);
// set the first agent, which is always the default agent, as the default for chat
setSelectedAgent(agents.length > 1 ? agents[0].slug : "khoj");
//generate colored icons for the selected agents
const agentIcons = agents
.filter((agent) => agent !== null && agent !== undefined)
.map((agent) => getIconFromIconName(agent.icon, agent.color)!);
// generate colored icons for the available agents
const agentIcons = agents.map((agent) => getIconFromIconName(agent.icon, agent.color)!);
setAgentIcons(agentIcons);
}, [agentsData, props.isMobileWidth]);
@ -138,24 +151,39 @@ function ChatBodyData(props: ChatBodyDataProps) {
try {
const newConversationId = await createNewConversation(selectedAgent || "khoj");
onConversationIdChange?.(newConversationId);
window.location.href = `/chat?conversationId=${newConversationId}`;
localStorage.setItem("message", message);
if (image) {
localStorage.setItem("image", image);
if (images.length > 0) {
localStorage.setItem("images", JSON.stringify(images));
}
window.location.href = `/chat?conversationId=${newConversationId}`;
} catch (error) {
console.error("Error creating new conversation:", error);
setProcessingMessage(false);
}
setMessage("");
setImages([]);
}
};
processMessage();
if (message) {
if (message || images.length > 0) {
setProcessingMessage(true);
}
}, [selectedAgent, message, processingMessage, onConversationIdChange]);
// Close the agent detail hover card when scroll on agent pane
useEffect(() => {
const scrollAreaSelector = "[data-radix-scroll-area-viewport]";
const scrollAreaEl = document.querySelector<HTMLElement>(scrollAreaSelector);
const handleScroll = () => {
setHoveredAgent(null);
setIsPopoverOpen(false);
};
scrollAreaEl?.addEventListener("scroll", handleScroll);
return () => scrollAreaEl?.removeEventListener("scroll", handleScroll);
}, []);
function fillArea(link: string, type: string, prompt: string) {
if (!link) {
let message_str = "";
@ -194,37 +222,76 @@ function ChatBodyData(props: ChatBodyDataProps) {
</h1>
</div>
{!props.isMobileWidth && (
<div className="flex pb-6 gap-2 items-center justify-center">
{agentIcons.map((icon, index) => (
<Card
key={`${index}-${agents[index].slug}`}
className={`${
selectedAgent === agents[index].slug
? convertColorToBorderClass(agents[index].color)
: "border-stone-100 dark:border-neutral-700 text-muted-foreground"
}
hover:cursor-pointer rounded-lg px-2 py-2`}
>
<CardTitle
className="text-center text-md font-medium flex justify-center items-center"
onClick={() => setSelectedAgent(agents[index].slug)}
<ScrollArea className="w-full max-w-[600px] mx-auto">
<div className="flex pb-2 gap-2 items-center justify-center">
{agents.map((agent, index) => (
<Popover
key={`${index}-${agent.slug}`}
open={isPopoverOpen && debouncedHoveredAgent === agent.slug}
onOpenChange={(open) => {
if (!open) {
setHoveredAgent(null);
setIsPopoverOpen(false);
}
}}
>
{icon} {agents[index].name}
</CardTitle>
</Card>
))}
<Card
className="border-none shadow-none flex justify-center items-center hover:cursor-pointer"
onClick={() => (window.location.href = "/agents")}
>
<CardTitle className="text-center text-md font-normal flex justify-center items-center px-1.5 py-2">
See All
</CardTitle>
</Card>
</div>
<PopoverTrigger asChild>
<Card
className={`${
selectedAgent === agent.slug
? convertColorToBorderClass(agent.color)
: "border-stone-100 dark:border-neutral-700 text-muted-foreground"
}
hover:cursor-pointer rounded-lg px-2 py-2`}
onDoubleClick={() => openAgentEditCard(agent.slug)}
onClick={() => {
setSelectedAgent(agent.slug);
chatInputRef.current?.focus();
setHoveredAgent(null);
setIsPopoverOpen(false);
}}
onMouseEnter={() => setHoveredAgent(agent.slug)}
onMouseLeave={() => {
setHoveredAgent(null);
setIsPopoverOpen(false);
}}
>
<CardTitle className="text-center text-md font-medium flex justify-center items-center whitespace-nowrap">
{agentIcons[index]} {agent.name}
</CardTitle>
</Card>
</PopoverTrigger>
<PopoverContent
className="w-80 p-0 border-none bg-transparent shadow-none"
onMouseLeave={() => {
setHoveredAgent(null);
setIsPopoverOpen(false);
}}
>
<AgentCard
data={agent}
userProfile={null}
isMobileWidth={props.isMobileWidth || false}
showChatButton={false}
editCard={false}
filesOptions={[]}
selectedChatModelOption=""
agentSlug=""
isSubscribed={isUserSubscribed(props.userConfig)}
setAgentChangeTriggered={() => {}}
modelOptions={[]}
inputToolOptions={{}}
outputModeOptions={{}}
/>
</PopoverContent>
</Popover>
))}
</div>
<ScrollBar orientation="horizontal" />
</ScrollArea>
)}
</div>
<div className={`mx-auto ${props.isMobileWidth ? "w-full" : "w-fit"}`}>
<div className={`mx-auto ${props.isMobileWidth ? "w-full" : "w-fit max-w-screen-md"}`}>
{!props.isMobileWidth && (
<div
className={`w-full ${styles.inputBox} shadow-lg bg-background align-middle items-center justify-center px-3 py-1 dark:bg-neutral-700 border-stone-100 dark:border-none dark:shadow-none rounded-2xl`}
@ -232,12 +299,13 @@ function ChatBodyData(props: ChatBodyDataProps) {
<ChatInputArea
isLoggedIn={props.isLoggedIn}
sendMessage={(message) => setMessage(message)}
sendImage={(image) => setImage(image)}
sendImage={(image) => setImages((prevImages) => [...prevImages, image])}
sendDisabled={processingMessage}
chatOptionsData={props.chatOptionsData}
conversationId={null}
isMobileWidth={props.isMobileWidth}
setUploadedFiles={props.setUploadedFiles}
ref={chatInputRef}
/>
</div>
)}
@ -285,40 +353,40 @@ function ChatBodyData(props: ChatBodyDataProps) {
<div
className={`${styles.inputBox} pt-1 shadow-[0_-20px_25px_-5px_rgba(0,0,0,0.1)] dark:bg-neutral-700 bg-background align-middle items-center justify-center pb-3 mx-1 rounded-t-2xl rounded-b-none`}
>
<div className="flex gap-2 items-center justify-left pt-1 pb-2 px-12">
{agentIcons.map((icon, index) => (
<Card
key={`${index}-${agents[index].slug}`}
className={`${selectedAgent === agents[index].slug ? convertColorToBorderClass(agents[index].color) : "border-muted text-muted-foreground"} hover:cursor-pointer`}
>
<CardTitle
className="text-center text-xs font-medium flex justify-center items-center px-1.5 py-1"
onClick={() => setSelectedAgent(agents[index].slug)}
<ScrollArea className="w-full max-w-[85vw]">
<div className="flex gap-2 items-center justify-left pt-1 pb-2 px-12">
{agentIcons.map((icon, index) => (
<Card
key={`${index}-${agents[index].slug}`}
className={`${selectedAgent === agents[index].slug ? convertColorToBorderClass(agents[index].color) : "border-muted text-muted-foreground"} hover:cursor-pointer`}
>
{icon} {agents[index].name}
</CardTitle>
</Card>
))}
<Card
className="border-none shadow-none flex justify-center items-center hover:cursor-pointer"
onClick={() => (window.location.href = "/agents")}
>
<CardTitle
className={`text-center ${props.isMobileWidth ? "text-xs" : "text-md"} font-normal flex justify-center items-center px-1.5 py-2`}
>
See All
</CardTitle>
</Card>
</div>
<CardTitle
className="text-center text-xs font-medium flex justify-center items-center px-1.5 py-1"
onDoubleClick={() =>
openAgentEditCard(agents[index].slug)
}
onClick={() => {
setSelectedAgent(agents[index].slug);
chatInputRef.current?.focus();
}}
>
{icon} {agents[index].name}
</CardTitle>
</Card>
))}
</div>
<ScrollBar orientation="horizontal" />
</ScrollArea>
<ChatInputArea
isLoggedIn={props.isLoggedIn}
sendMessage={(message) => setMessage(message)}
sendImage={(image) => setImage(image)}
sendImage={(image) => setImages((prevImages) => [...prevImages, image])}
sendDisabled={processingMessage}
chatOptionsData={props.chatOptionsData}
conversationId={null}
isMobileWidth={props.isMobileWidth}
setUploadedFiles={props.setUploadedFiles}
ref={chatInputRef}
/>
</div>
</>

View file

@ -513,7 +513,7 @@ export default function SettingsView() {
const isMobileWidth = useIsMobileWidth();
const cardClassName =
"w-full lg:w-1/3 grid grid-flow-column border border-gray-300 shadow-md rounded-lg bg-gradient-to-b from-background to-gray-50 dark:to-gray-950";
"w-full lg:w-1/3 grid grid-flow-column border border-gray-300 shadow-md rounded-lg bg-gradient-to-b from-background to-gray-50 dark:to-gray-950 border border-opacity-50";
useEffect(() => {
setUserConfig(initialUserConfig);
@ -640,6 +640,51 @@ export default function SettingsView() {
}
};
const enableFreeTrial = async () => {
const formatDate = (dateString: Date) => {
const date = new Date(dateString);
return new Intl.DateTimeFormat("en-US", {
day: "2-digit",
month: "short",
year: "numeric",
}).format(date);
};
try {
const response = await fetch(`/api/subscription/trial`, {
method: "POST",
});
if (!response.ok) throw new Error("Failed to enable free trial");
const responseBody = await response.json();
// Set updated user settings
if (responseBody.trial_enabled && userConfig) {
let newUserConfig = userConfig;
newUserConfig.subscription_state = SubscriptionStates.TRIAL;
const renewalDate = new Date(
Date.now() + userConfig.length_of_free_trial * 24 * 60 * 60 * 1000,
);
newUserConfig.subscription_renewal_date = formatDate(renewalDate);
newUserConfig.subscription_enabled_trial_at = new Date().toISOString();
setUserConfig(newUserConfig);
// Notify user of free trial
toast({
title: "🎉 Trial Enabled",
description: `Your free trial will end on ${newUserConfig.subscription_renewal_date}`,
});
}
} catch (error) {
console.error("Error enabling free trial:", error);
toast({
title: "⚠️ Failed to Enable Free Trial",
description:
"Failed to enable free trial. Try again or contact us at team@khoj.dev",
});
}
};
const saveName = async () => {
if (!name) return;
try {
@ -673,7 +718,7 @@ export default function SettingsView() {
};
const updateModel = (name: string) => async (id: string) => {
if (!userConfig?.is_active && name !== "search") {
if (!userConfig?.is_active) {
toast({
title: `Model Update`,
description: `You need to be subscribed to update ${name} models`,
@ -866,10 +911,13 @@ export default function SettingsView() {
Futurist (Trial)
</p>
<p className="text-gray-400">
You are on a 14 day trial of the Khoj
Futurist plan. Check{" "}
You are on a{" "}
{userConfig.length_of_free_trial} day trial
of the Khoj Futurist plan. Your trial ends
on {userConfig.subscription_renewal_date}.
Check{" "}
<a
href="https://khoj.dev/pricing"
href="https://khoj.dev/#pricing"
target="_blank"
>
pricing page
@ -909,7 +957,7 @@ export default function SettingsView() {
)) ||
(userConfig.subscription_state === "expired" && (
<>
<p className="text-xl">Free Plan</p>
<p className="text-xl">Humanist</p>
{(userConfig.subscription_renewal_date && (
<p className="text-gray-400">
Subscription <b>expired</b> on{" "}
@ -923,7 +971,7 @@ export default function SettingsView() {
<p className="text-gray-400">
Check{" "}
<a
href="https://khoj.dev/pricing"
href="https://khoj.dev/#pricing"
target="_blank"
>
pricing page
@ -960,7 +1008,8 @@ export default function SettingsView() {
/>
Resubscribe
</Button>
)) || (
)) ||
(userConfig.subscription_enabled_trial_at && (
<Button
variant="outline"
className="text-primary/80 hover:text-primary"
@ -978,6 +1027,18 @@ export default function SettingsView() {
/>
Subscribe
</Button>
)) || (
<Button
variant="outline"
className="text-primary/80 hover:text-primary"
onClick={enableFreeTrial}
>
<ArrowCircleUp
weight="bold"
className="h-5 w-5 mr-2"
/>
Enable Trial
</Button>
)}
</CardFooter>
</Card>
@ -1172,27 +1233,6 @@ export default function SettingsView() {
</CardFooter>
</Card>
)}
{userConfig.search_model_options.length > 0 && (
<Card className={cardClassName}>
<CardHeader className="text-xl flex flex-row">
<FileMagnifyingGlass className="h-7 w-7 mr-2" />
Search
</CardHeader>
<CardContent className="overflow-hidden pb-12 grid gap-8 h-fit">
<p className="text-gray-400">
Pick the search model to find your documents
</p>
<DropdownComponent
items={userConfig.search_model_options}
selected={
userConfig.selected_search_model_config
}
callbackFunc={updateModel("search")}
/>
</CardContent>
<CardFooter className="flex flex-wrap gap-4"></CardFooter>
</Card>
)}
{userConfig.paint_model_options.length > 0 && (
<Card className={cardClassName}>
<CardHeader className="text-xl flex flex-row">

View file

@ -27,7 +27,14 @@ export default function RootLayout({
child-src 'none';
object-src 'none';"
></meta>
<body className={inter.className}>{children}</body>
<body className={inter.className}>
{children}
<script
dangerouslySetInnerHTML={{
__html: `window.EXCALIDRAW_ASSET_PATH = 'https://assets.khoj.dev/@excalidraw/excalidraw/dist/';`,
}}
/>
</body>
</html>
);
}

View file

@ -13,7 +13,7 @@ import "katex/dist/katex.min.css";
import { useIPLocationData, useIsMobileWidth, welcomeConsole } from "../../common/utils";
import { useAuthenticatedData } from "@/app/common/auth";
import ChatInputArea, { ChatOptions } from "@/app/components/chatInputArea/chatInputArea";
import { ChatInputArea, ChatOptions } from "@/app/components/chatInputArea/chatInputArea";
import { StreamMessage } from "@/app/components/chatMessage/chatMessage";
import { processMessageChunk } from "@/app/common/chatFunctions";
import { AgentData } from "@/app/agents/page";
@ -28,22 +28,44 @@ interface ChatBodyDataProps {
isLoggedIn: boolean;
conversationId?: string;
setQueryToProcess: (query: string) => void;
setImage64: (image64: string) => void;
setImages: (images: string[]) => void;
}
function ChatBodyData(props: ChatBodyDataProps) {
const [message, setMessage] = useState("");
const [image, setImage] = useState<string | null>(null);
const [images, setImages] = useState<string[]>([]);
const [processingMessage, setProcessingMessage] = useState(false);
const [agentMetadata, setAgentMetadata] = useState<AgentData | null>(null);
const chatInputRef = useRef<HTMLTextAreaElement>(null);
const setQueryToProcess = props.setQueryToProcess;
const streamedMessages = props.streamedMessages;
const chatHistoryCustomClassName = props.isMobileWidth ? "w-full" : "w-4/6";
useEffect(() => {
if (image) {
props.setImage64(encodeURIComponent(image));
if (images.length > 0) {
const encodedImages = images.map((image) => encodeURIComponent(image));
props.setImages(encodedImages);
}
}, [image, props.setImage64]);
}, [images, props.setImages]);
useEffect(() => {
const storedImages = localStorage.getItem("images");
if (storedImages) {
const parsedImages: string[] = JSON.parse(storedImages);
setImages(parsedImages);
const encodedImages = parsedImages.map((img: string) => encodeURIComponent(img));
props.setImages(encodedImages);
localStorage.removeItem("images");
}
const storedMessage = localStorage.getItem("message");
if (storedMessage) {
setProcessingMessage(true);
setQueryToProcess(storedMessage);
}
}, [setQueryToProcess, props.setImages]);
useEffect(() => {
if (message) {
@ -78,21 +100,23 @@ function ChatBodyData(props: ChatBodyDataProps) {
setTitle={props.setTitle}
pendingMessage={processingMessage ? message : ""}
incomingMessages={props.streamedMessages}
customClassName={chatHistoryCustomClassName}
/>
</div>
<div
className={`${styles.inputBox} p-1 md:px-2 shadow-md bg-background align-middle items-center justify-center dark:bg-neutral-700 dark:border-0 dark:shadow-sm rounded-t-2xl rounded-b-none md:rounded-xl`}
className={`${styles.inputBox} p-1 md:px-2 shadow-md bg-background align-middle items-center justify-center dark:bg-neutral-700 dark:border-0 dark:shadow-sm rounded-t-2xl rounded-b-none md:rounded-xl h-fit ${chatHistoryCustomClassName} mr-auto ml-auto`}
>
<ChatInputArea
isLoggedIn={props.isLoggedIn}
sendMessage={(message) => setMessage(message)}
sendImage={(image) => setImage(image)}
sendImage={(image) => setImages((prevImages) => [...prevImages, image])}
sendDisabled={processingMessage}
chatOptionsData={props.chatOptionsData}
conversationId={props.conversationId}
agentColor={agentMetadata?.color}
isMobileWidth={props.isMobileWidth}
setUploadedFiles={props.setUploadedFiles}
ref={chatInputRef}
/>
</div>
</>
@ -109,7 +133,7 @@ export default function SharedChat() {
const [processQuerySignal, setProcessQuerySignal] = useState(false);
const [uploadedFiles, setUploadedFiles] = useState<string[]>([]);
const [paramSlug, setParamSlug] = useState<string | undefined>(undefined);
const [image64, setImage64] = useState<string>("");
const [images, setImages] = useState<string[]>([]);
const locationData = useIPLocationData() || {
timezone: Intl.DateTimeFormat().resolvedOptions().timeZone,
@ -168,7 +192,7 @@ export default function SharedChat() {
completed: false,
timestamp: new Date().toISOString(),
rawQuery: queryToProcess || "",
uploadedImageData: decodeURIComponent(image64),
images: images,
};
setMessages((prevMessages) => [...prevMessages, newStreamMessage]);
setProcessQuerySignal(true);
@ -195,7 +219,7 @@ export default function SharedChat() {
if (done) {
setQueryToProcess("");
setProcessQuerySignal(false);
setImage64("");
setImages([]);
break;
}
@ -237,7 +261,7 @@ export default function SharedChat() {
country_code: locationData.countryCode,
timezone: locationData.timezone,
}),
...(image64 && { image: image64 }),
...(images.length > 0 && { image: images }),
};
const response = await fetch(chatAPI, {
@ -276,6 +300,19 @@ export default function SharedChat() {
<div className={styles.chatBox}>
<div className={styles.chatBoxBody}>
{!isMobileWidth && title && (
<div
className={`${styles.chatTitleWrapper} text-nowrap text-ellipsis overflow-hidden max-w-screen-md grid items-top font-bold mr-8 pt-6 col-auto h-fit`}
>
{title && (
<h2
className={`text-lg text-ellipsis whitespace-nowrap overflow-x-hidden`}
>
{title}
</h2>
)}
</div>
)}
<Suspense fallback={<Loading />}>
<ChatBodyData
conversationId={conversationId}
@ -287,7 +324,7 @@ export default function SharedChat() {
setTitle={setTitle}
setUploadedFiles={setUploadedFiles}
isMobileWidth={isMobileWidth}
setImage64={setImage64}
setImages={setImages}
/>
</Suspense>
</div>

View file

@ -75,7 +75,7 @@ div.titleBar {
div.chatBoxBody {
display: grid;
height: 100%;
width: 70%;
width: 95%;
margin: auto;
}

View file

@ -1,6 +1,6 @@
{
"name": "khoj-ai",
"version": "1.25.0",
"version": "1.26.4",
"private": true,
"scripts": {
"dev": "next dev",
@ -63,7 +63,8 @@
"swr": "^2.2.5",
"typescript": "^5",
"vaul": "^0.9.1",
"zod": "^3.23.8"
"zod": "^3.23.8",
"@excalidraw/excalidraw": "^0.17.6"
},
"devDependencies": {
"@types/dompurify": "^3.0.5",

View file

@ -286,6 +286,11 @@
resolved "https://registry.yarnpkg.com/@eslint/js/-/js-8.57.1.tgz#de633db3ec2ef6a3c89e2f19038063e8a122e2c2"
integrity sha512-d9zaMRSTIKDLhctzH12MtXvJKSSUhaHcjV+2Z+GK+EEY7XKpP5yR4x+N3TAcHTcu963nIr+TMcCb4DBCYX1z6Q==
"@excalidraw/excalidraw@^0.17.6":
version "0.17.6"
resolved "https://registry.yarnpkg.com/@excalidraw/excalidraw/-/excalidraw-0.17.6.tgz#5fd208ce69d33ca712d1804b50d7d06d5c46ac4d"
integrity sha512-fyCl+zG/Z5yhHDh5Fq2ZGmphcrALmuOdtITm8gN4d8w4ntnaopTXcTfnAAaU3VleDC6LhTkoLOTG6P5kgREiIg==
"@floating-ui/core@^1.6.0":
version "1.6.8"
resolved "https://registry.yarnpkg.com/@floating-ui/core/-/core-1.6.8.tgz#aa43561be075815879305965020f492cdb43da12"

View file

@ -108,7 +108,7 @@ class UserAuthenticationBackend(AuthenticationBackend):
password="default",
)
renewal_date = make_aware(datetime.strptime("2100-04-01", "%Y-%m-%d"))
Subscription.objects.create(user=default_user, type="standard", renewal_date=renewal_date)
Subscription.objects.create(user=default_user, type=Subscription.Type.STANDARD, renewal_date=renewal_date)
async def authenticate(self, request: HTTPConnection):
current_user = request.session.get("user")
@ -172,7 +172,7 @@ class UserAuthenticationBackend(AuthenticationBackend):
request=request,
telemetry_type="api",
api="create_user",
metadata={"user_id": str(user.uuid)},
metadata={"server_id": str(user.uuid)},
)
logger.log(logging.INFO, f"🥳 New User Created: {user.uuid}")
else:
@ -312,7 +312,7 @@ def configure_routes(app):
logger.info("🔑 Enabled Authentication")
if state.billing_enabled:
from khoj.routers.subscription import subscription_router
from khoj.routers.api_subscription import subscription_router
app.include_router(subscription_router, prefix="/api/subscription")
logger.info("💳 Enabled Billing")

View file

@ -1,6 +1,7 @@
import json
import logging
import math
import os
import random
import re
import secrets
@ -10,7 +11,6 @@ from enum import Enum
from typing import Callable, Iterable, List, Optional, Type
import cron_descriptor
import django
from apscheduler.job import Job
from asgiref.sync import sync_to_async
from django.contrib.sessions.backends.db import SessionStore
@ -52,6 +52,7 @@ from khoj.database.models import (
UserTextToImageModelConfig,
UserVoiceModelConfig,
VoiceModelOption,
WebScraper,
)
from khoj.processor.conversation import prompts
from khoj.search_filter.date_filter import DateFilter
@ -59,11 +60,19 @@ from khoj.search_filter.file_filter import FileFilter
from khoj.search_filter.word_filter import WordFilter
from khoj.utils import state
from khoj.utils.config import OfflineChatProcessorModel
from khoj.utils.helpers import generate_random_name, is_none_or_empty, timer
from khoj.utils.helpers import (
generate_random_name,
in_debug_mode,
is_none_or_empty,
timer,
)
logger = logging.getLogger(__name__)
LENGTH_OF_FREE_TRIAL = 7 #
class SubscriptionState(Enum):
TRIAL = "trial"
SUBSCRIBED = "subscribed"
@ -162,7 +171,7 @@ async def acreate_user_by_phone_number(phone_number: str) -> KhojUser:
)
await user.asave()
await Subscription.objects.acreate(user=user, type="trial")
await Subscription.objects.acreate(user=user, type=Subscription.Type.STANDARD)
return user
@ -179,11 +188,29 @@ async def aget_or_create_user_by_email(email: str) -> tuple[KhojUser, bool]:
user_subscription = await Subscription.objects.filter(user=user).afirst()
if not user_subscription:
await Subscription.objects.acreate(user=user, type="trial")
await Subscription.objects.acreate(user=user, type=Subscription.Type.STANDARD)
return user, is_new
async def astart_trial_subscription(user: KhojUser) -> Subscription:
subscription = await Subscription.objects.filter(user=user).afirst()
if not subscription:
raise HTTPException(status_code=400, detail="User does not have a subscription")
if subscription.type == Subscription.Type.TRIAL:
raise HTTPException(status_code=400, detail="User already has a trial subscription")
if subscription.enabled_trial_at:
raise HTTPException(status_code=400, detail="User already has a trial subscription")
subscription.type = Subscription.Type.TRIAL
subscription.enabled_trial_at = datetime.now(tz=timezone.utc)
subscription.renewal_date = datetime.now(tz=timezone.utc) + timedelta(days=LENGTH_OF_FREE_TRIAL)
await subscription.asave()
return subscription
async def aget_user_validated_by_email_verification_code(code: str) -> KhojUser:
user = await KhojUser.objects.filter(email_verification_code=code).afirst()
if not user:
@ -215,7 +242,7 @@ async def create_user_by_google_token(token: dict) -> KhojUser:
user=user,
)
await Subscription.objects.acreate(user=user, type="trial")
await Subscription.objects.acreate(user=user, type=Subscription.Type.STANDARD)
return user
@ -273,16 +300,15 @@ def subscription_to_state(subscription: Subscription) -> str:
if not subscription:
return SubscriptionState.INVALID.value
elif subscription.type == Subscription.Type.TRIAL:
# Trial subscription is valid for 7 days
if datetime.now(tz=timezone.utc) - subscription.created_at > timedelta(days=14):
# Check if the trial has expired
if datetime.now(tz=timezone.utc) > subscription.renewal_date:
return SubscriptionState.EXPIRED.value
return SubscriptionState.TRIAL.value
elif subscription.is_recurring and subscription.renewal_date >= datetime.now(tz=timezone.utc):
elif subscription.is_recurring and subscription.renewal_date > datetime.now(tz=timezone.utc):
return SubscriptionState.SUBSCRIBED.value
elif not subscription.is_recurring and subscription.renewal_date is None:
return SubscriptionState.EXPIRED.value
elif not subscription.is_recurring and subscription.renewal_date >= datetime.now(tz=timezone.utc):
elif not subscription.is_recurring and subscription.renewal_date > datetime.now(tz=timezone.utc):
return SubscriptionState.UNSUBSCRIBED.value
elif not subscription.is_recurring and subscription.renewal_date < datetime.now(tz=timezone.utc):
return SubscriptionState.EXPIRED.value
@ -440,18 +466,26 @@ async def set_user_github_config(user: KhojUser, pat_token: str, repos: list):
return config
def get_user_search_model_or_default(user=None):
if user and UserSearchModelConfig.objects.filter(user=user).exists():
return UserSearchModelConfig.objects.filter(user=user).first().setting
def get_default_search_model() -> SearchModelConfig:
default_search_model = SearchModelConfig.objects.filter(name="default").first()
if SearchModelConfig.objects.filter(name="default").exists():
return SearchModelConfig.objects.filter(name="default").first()
if default_search_model:
return default_search_model
else:
SearchModelConfig.objects.create()
return SearchModelConfig.objects.first()
def get_user_default_search_model(user: KhojUser = None) -> SearchModelConfig:
if user:
user_search_model = UserSearchModelConfig.objects.filter(user=user).first()
if user_search_model:
return user_search_model.setting
return get_default_search_model()
def get_or_create_search_models():
search_models = SearchModelConfig.objects.all()
if search_models.count() == 0:
@ -461,21 +495,6 @@ def get_or_create_search_models():
return search_models
async def aset_user_search_model(user: KhojUser, search_model_config_id: int):
config = await SearchModelConfig.objects.filter(id=search_model_config_id).afirst()
if not config:
return None
new_config, _ = await UserSearchModelConfig.objects.aupdate_or_create(user=user, defaults={"setting": config})
return new_config
async def aget_user_search_model(user: KhojUser):
config = await UserSearchModelConfig.objects.filter(user=user).prefetch_related("setting").afirst()
if not config:
return None
return config.setting
class ProcessLockAdapters:
@staticmethod
def get_process_lock(process_name: str):
@ -616,6 +635,8 @@ class AgentAdapters:
@staticmethod
def get_all_accessible_agents(user: KhojUser = None):
public_query = Q(privacy_level=Agent.PrivacyLevel.PUBLIC)
# TODO Update this to allow any public agent that's officially approved once that experience is launched
public_query &= Q(managed_by_admin=True)
if user:
return (
Agent.objects.filter(public_query | Q(creator=user))
@ -634,6 +655,16 @@ class AgentAdapters:
agents = await sync_to_async(AgentAdapters.get_all_accessible_agents)(user)
return await sync_to_async(list)(agents)
@staticmethod
async def ais_agent_accessible(agent: Agent, user: KhojUser) -> bool:
if agent.privacy_level == Agent.PrivacyLevel.PUBLIC:
return True
if agent.creator == user:
return True
if agent.privacy_level == Agent.PrivacyLevel.PROTECTED:
return True
return False
@staticmethod
def get_conversation_agent_by_id(agent_id: int):
agent = Agent.objects.filter(id=agent_id).first()
@ -1031,6 +1062,70 @@ class ConversationAdapters:
return server_chat_settings.chat_advanced
return await ConversationAdapters.aget_default_conversation_config(user)
@staticmethod
async def aget_server_webscraper():
server_chat_settings = await ServerChatSettings.objects.filter().prefetch_related("web_scraper").afirst()
if server_chat_settings is not None and server_chat_settings.web_scraper is not None:
return server_chat_settings.web_scraper
return None
@staticmethod
async def aget_enabled_webscrapers() -> list[WebScraper]:
enabled_scrapers: list[WebScraper] = []
server_webscraper = await ConversationAdapters.aget_server_webscraper()
if server_webscraper:
# Only use the webscraper set in the server chat settings
enabled_scrapers = [server_webscraper]
if not enabled_scrapers:
# Use the enabled web scrapers, ordered by priority, until get web page content
enabled_scrapers = [scraper async for scraper in WebScraper.objects.all().order_by("priority").aiterator()]
if not enabled_scrapers:
# Use scrapers enabled via environment variables
if os.getenv("FIRECRAWL_API_KEY"):
api_url = os.getenv("FIRECRAWL_API_URL", "https://api.firecrawl.dev")
enabled_scrapers.append(
WebScraper(
type=WebScraper.WebScraperType.FIRECRAWL,
name=WebScraper.WebScraperType.FIRECRAWL.capitalize(),
api_key=os.getenv("FIRECRAWL_API_KEY"),
api_url=api_url,
)
)
if os.getenv("OLOSTEP_API_KEY"):
api_url = os.getenv("OLOSTEP_API_URL", "https://agent.olostep.com/olostep-p2p-incomingAPI")
enabled_scrapers.append(
WebScraper(
type=WebScraper.WebScraperType.OLOSTEP,
name=WebScraper.WebScraperType.OLOSTEP.capitalize(),
api_key=os.getenv("OLOSTEP_API_KEY"),
api_url=api_url,
)
)
# Jina is the default fallback scrapers to use as it does not require an API key
api_url = os.getenv("JINA_READER_API_URL", "https://r.jina.ai/")
enabled_scrapers.append(
WebScraper(
type=WebScraper.WebScraperType.JINA,
name=WebScraper.WebScraperType.JINA.capitalize(),
api_key=os.getenv("JINA_API_KEY"),
api_url=api_url,
)
)
# Only enable the direct web page scraper by default in self-hosted single user setups.
# Useful for reading webpages on your intranet.
if state.anonymous_mode or in_debug_mode():
enabled_scrapers.append(
WebScraper(
type=WebScraper.WebScraperType.DIRECT,
name=WebScraper.WebScraperType.DIRECT.capitalize(),
api_key=None,
api_url=None,
)
)
return enabled_scrapers
@staticmethod
def create_conversation_from_public_conversation(
user: KhojUser, public_conversation: PublicConversation, client_app: ClientApplication
@ -1393,12 +1488,15 @@ class EntryAdapters:
file_filters = EntryAdapters.file_filter.get_filter_terms(query)
date_filters = EntryAdapters.date_filter.get_query_date_range(query)
user_or_agent = Q(user=user)
owner_filter = Q()
if user != None:
owner_filter = Q(user=user)
if agent != None:
user_or_agent |= Q(agent=agent)
owner_filter |= Q(agent=agent)
if len(word_filters) == 0 and len(file_filters) == 0 and len(date_filters) == 0:
return Entry.objects.filter(user_or_agent)
return Entry.objects.filter(owner_filter)
for term in word_filters:
if term.startswith("+"):
@ -1434,7 +1532,7 @@ class EntryAdapters:
formatted_max_date = date.fromtimestamp(max_date).strftime("%Y-%m-%d")
q_filter_terms &= Q(embeddings_dates__date__lte=formatted_max_date)
relevant_entries = Entry.objects.filter(user_or_agent).filter(q_filter_terms)
relevant_entries = Entry.objects.filter(owner_filter).filter(q_filter_terms)
if file_type_filter:
relevant_entries = relevant_entries.filter(file_type=file_type_filter)
return relevant_entries
@ -1449,13 +1547,18 @@ class EntryAdapters:
max_distance: float = math.inf,
agent: Agent = None,
):
user_or_agent = Q(user=user)
owner_filter = Q()
if user != None:
owner_filter = Q(user=user)
if agent != None:
user_or_agent |= Q(agent=agent)
owner_filter |= Q(agent=agent)
if owner_filter == Q():
return Entry.objects.none()
relevant_entries = EntryAdapters.apply_filters(user, raw_query, file_type_filter, agent)
relevant_entries = relevant_entries.filter(user_or_agent).annotate(
relevant_entries = relevant_entries.filter(owner_filter).annotate(
distance=CosineDistance("embeddings", embeddings)
)
relevant_entries = relevant_entries.filter(distance__lte=max_distance)

View file

@ -31,6 +31,7 @@ from khoj.database.models import (
UserSearchModelConfig,
UserVoiceModelConfig,
VoiceModelOption,
WebScraper,
)
from khoj.utils.helpers import ImageIntentType
@ -69,10 +70,11 @@ class KhojUserAdmin(UserAdmin):
"id",
"email",
"username",
"phone_number",
"is_active",
"uuid",
"is_staff",
"is_superuser",
"phone_number",
)
search_fields = ("email", "username", "phone_number", "uuid")
filter_horizontal = ("groups", "user_permissions")
@ -124,6 +126,7 @@ class EntryAdmin(admin.ModelAdmin):
"created_at",
"updated_at",
"user",
"agent",
"file_source",
"file_type",
"file_name",
@ -133,6 +136,7 @@ class EntryAdmin(admin.ModelAdmin):
list_filter = (
"file_type",
"user__email",
"search_model__name",
)
ordering = ("-created_at",)
@ -197,9 +201,24 @@ class ServerChatSettingsAdmin(admin.ModelAdmin):
list_display = (
"chat_default",
"chat_advanced",
"web_scraper",
)
@admin.register(WebScraper)
class WebScraperAdmin(admin.ModelAdmin):
list_display = (
"priority",
"name",
"type",
"api_key",
"api_url",
"created_at",
)
search_fields = ("name", "api_key", "api_url", "type")
ordering = ("priority",)
@admin.register(Conversation)
class ConversationAdmin(admin.ModelAdmin):
list_display = (

View file

@ -0,0 +1,182 @@
import logging
from typing import List
from django.core.management.base import BaseCommand
from django.db import transaction
from django.db.models import Count, Q
from tqdm import tqdm
from khoj.database.adapters import get_default_search_model
from khoj.database.models import (
Agent,
Entry,
KhojUser,
SearchModelConfig,
UserSearchModelConfig,
)
from khoj.processor.embeddings import EmbeddingsModel
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class Command(BaseCommand):
help = "Convert all existing Entry objects to use a new default Search model."
def add_arguments(self, parser):
# Pass default SearchModelConfig ID
parser.add_argument(
"--search_model_id",
action="store",
help="ID of the SearchModelConfig object to set as the default search model for all existing Entry objects and UserSearchModelConfig objects.",
required=True,
)
# Set the apply flag to apply the new default Search model to all existing Entry objects and UserSearchModelConfig objects.
parser.add_argument(
"--apply",
action="store_true",
help="Apply the new default Search model to all existing Entry objects and UserSearchModelConfig objects. Otherwise, only display the number of Entry objects and UserSearchModelConfig objects that will be affected.",
)
def handle(self, *args, **options):
@transaction.atomic
def regenerate_entries(entry_filter: Q, embeddings_model: EmbeddingsModel, search_model: SearchModelConfig):
entries = Entry.objects.filter(entry_filter).all()
compiled_entries = [entry.compiled for entry in entries]
updated_entries: List[Entry] = []
try:
embeddings = embeddings_model.embed_documents(compiled_entries)
except Exception as e:
logger.error(f"Error embedding documents: {e}")
return
for i, entry in enumerate(tqdm(entries)):
entry.embeddings = embeddings[i]
entry.search_model_id = search_model.id
updated_entries.append(entry)
Entry.objects.bulk_update(updated_entries, ["embeddings", "search_model_id", "file_path"])
search_model_config_id = options.get("search_model_id")
apply = options.get("apply")
logger.info(f"SearchModelConfig ID: {search_model_config_id}")
logger.info(f"Apply: {apply}")
embeddings_model = dict()
search_models = SearchModelConfig.objects.all()
for model in search_models:
embeddings_model.update(
{
model.name: EmbeddingsModel(
model.bi_encoder,
model.embeddings_inference_endpoint,
model.embeddings_inference_endpoint_api_key,
query_encode_kwargs=model.bi_encoder_query_encode_config,
docs_encode_kwargs=model.bi_encoder_docs_encode_config,
model_kwargs=model.bi_encoder_model_config,
)
}
)
new_default_search_model_config = SearchModelConfig.objects.get(id=search_model_config_id)
logger.info(f"New default Search model: {new_default_search_model_config}")
user_search_model_configs_to_update = UserSearchModelConfig.objects.exclude(
setting_id=search_model_config_id
).all()
logger.info(f"Number of UserSearchModelConfig objects to update: {user_search_model_configs_to_update.count()}")
for user_config in user_search_model_configs_to_update:
affected_user = user_config.user
entry_filter = Q(user=affected_user)
relevant_entries = Entry.objects.filter(entry_filter).all()
logger.info(f"Number of Entry objects to update for user {affected_user}: {relevant_entries.count()}")
if apply:
try:
regenerate_entries(
entry_filter,
embeddings_model[new_default_search_model_config.name],
new_default_search_model_config,
)
user_config.setting = new_default_search_model_config
user_config.save()
logger.info(
f"Updated UserSearchModelConfig object for user {affected_user} to use the new default Search model."
)
logger.info(
f"Updated {relevant_entries.count()} Entry objects for user {affected_user} to use the new default Search model."
)
except Exception as e:
logger.error(f"Error embedding documents: {e}")
logger.info("----")
# There are also plenty of users who have indexed documents without explicitly creating a UserSearchModelConfig object. You would have to migrate these users as well, if the default is different from search_model_config_id.
current_default = get_default_search_model()
if current_default.id != new_default_search_model_config.id:
users_without_user_search_model_config = KhojUser.objects.annotate(
user_search_model_config_count=Count("usersearchmodelconfig")
).filter(user_search_model_config_count=0)
logger.info(f"Number of User objects to update: {users_without_user_search_model_config.count()}")
for user in users_without_user_search_model_config:
entry_filter = Q(user=user)
relevant_entries = Entry.objects.filter(entry_filter).all()
logger.info(f"Number of Entry objects to update for user {user}: {relevant_entries.count()}")
if apply:
try:
regenerate_entries(
entry_filter,
embeddings_model[new_default_search_model_config.name],
new_default_search_model_config,
)
UserSearchModelConfig.objects.create(user=user, setting=new_default_search_model_config)
logger.info(
f"Created UserSearchModelConfig object for user {user} to use the new default Search model."
)
logger.info(
f"Updated {relevant_entries.count()} Entry objects for user {user} to use the new default Search model."
)
except Exception as e:
logger.error(f"Error embedding documents: {e}")
else:
logger.info("Default is the same as search_model_config_id.")
all_agents = Agent.objects.all()
logger.info(f"Number of Agent objects to update: {all_agents.count()}")
for agent in all_agents:
entry_filter = Q(agent=agent)
relevant_entries = Entry.objects.filter(entry_filter).all()
logger.info(f"Number of Entry objects to update for agent {agent}: {relevant_entries.count()}")
if apply:
try:
regenerate_entries(
entry_filter,
embeddings_model[new_default_search_model_config.name],
new_default_search_model_config,
)
logger.info(
f"Updated {relevant_entries.count()} Entry objects for agent {agent} to use the new default Search model."
)
except Exception as e:
logger.error(f"Error embedding documents: {e}")
if apply and current_default.id != new_default_search_model_config.id:
# Get the existing default SearchModelConfig object and update its name
current_default.name = f"prev_default_{current_default.id}"
current_default.save()
# Update the new default SearchModelConfig object's name
new_default_search_model_config.name = "default"
new_default_search_model_config.save()
if not apply:
logger.info("Run the command with the --apply flag to apply the new default Search model.")

View file

@ -0,0 +1,24 @@
# Generated by Django 5.0.8 on 2024-10-17 18:13
import django.contrib.postgres.fields
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("database", "0067_alter_agent_style_icon"),
]
operations = [
migrations.AlterField(
model_name="agent",
name="output_modes",
field=django.contrib.postgres.fields.ArrayField(
base_field=models.CharField(
choices=[("text", "Text"), ("image", "Image"), ("automation", "Automation")], max_length=200
),
default=list,
size=None,
),
),
]

View file

@ -0,0 +1,89 @@
# Generated by Django 5.0.8 on 2024-10-18 00:41
import django.db.models.deletion
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("database", "0068_alter_agent_output_modes"),
]
operations = [
migrations.CreateModel(
name="WebScraper",
fields=[
("id", models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name="ID")),
("created_at", models.DateTimeField(auto_now_add=True)),
("updated_at", models.DateTimeField(auto_now=True)),
(
"name",
models.CharField(
blank=True,
default=None,
help_text="Friendly name. If not set, it will be set to the type of the scraper.",
max_length=200,
null=True,
unique=True,
),
),
(
"type",
models.CharField(
choices=[
("Firecrawl", "Firecrawl"),
("Olostep", "Olostep"),
("Jina", "Jina"),
("Direct", "Direct"),
],
default="Jina",
max_length=20,
),
),
(
"api_key",
models.CharField(
blank=True,
default=None,
help_text="API key of the web scraper. Only set if scraper service requires an API key. Default is set from env var.",
max_length=200,
null=True,
),
),
(
"api_url",
models.URLField(
blank=True,
default=None,
help_text="API URL of the web scraper. Only set if scraper service on non-default URL.",
null=True,
),
),
(
"priority",
models.IntegerField(
blank=True,
default=None,
help_text="Priority of the web scraper. Lower numbers run first.",
null=True,
unique=True,
),
),
],
options={
"abstract": False,
},
),
migrations.AddField(
model_name="serverchatsettings",
name="web_scraper",
field=models.ForeignKey(
blank=True,
default=None,
null=True,
on_delete=django.db.models.deletion.CASCADE,
related_name="web_scraper",
to="database.webscraper",
),
),
]

View file

@ -0,0 +1,46 @@
# Generated by Django 5.0.8 on 2024-10-21 05:16
import django.contrib.postgres.fields
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("database", "0069_webscraper_serverchatsettings_web_scraper"),
]
operations = [
migrations.AlterField(
model_name="agent",
name="input_tools",
field=django.contrib.postgres.fields.ArrayField(
base_field=models.CharField(
choices=[
("general", "General"),
("online", "Online"),
("notes", "Notes"),
("summarize", "Summarize"),
("webpage", "Webpage"),
],
max_length=200,
),
blank=True,
default=list,
null=True,
size=None,
),
),
migrations.AlterField(
model_name="agent",
name="output_modes",
field=django.contrib.postgres.fields.ArrayField(
base_field=models.CharField(
choices=[("text", "Text"), ("image", "Image"), ("automation", "Automation")], max_length=200
),
blank=True,
default=list,
null=True,
size=None,
),
),
]

View file

@ -0,0 +1,32 @@
# Generated by Django 5.0.8 on 2024-10-20 19:24
from django.db import migrations, models
def set_enabled_trial_at(apps, schema_editor):
Subscription = apps.get_model("database", "Subscription")
for subscription in Subscription.objects.all():
subscription.enabled_trial_at = subscription.created_at
subscription.save()
class Migration(migrations.Migration):
dependencies = [
("database", "0070_alter_agent_input_tools_alter_agent_output_modes"),
]
operations = [
migrations.AddField(
model_name="subscription",
name="enabled_trial_at",
field=models.DateTimeField(blank=True, default=None, null=True),
),
migrations.AlterField(
model_name="subscription",
name="type",
field=models.CharField(
choices=[("trial", "Trial"), ("standard", "Standard")], default="standard", max_length=20
),
),
migrations.RunPython(set_enabled_trial_at),
]

View file

@ -0,0 +1,24 @@
# Generated by Django 5.0.8 on 2024-10-21 21:09
import django.db.models.deletion
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("database", "0071_subscription_enabled_trial_at_and_more"),
]
operations = [
migrations.AddField(
model_name="entry",
name="search_model",
field=models.ForeignKey(
blank=True,
default=None,
null=True,
on_delete=django.db.models.deletion.SET_NULL,
to="database.searchmodelconfig",
),
),
]

View file

@ -1,3 +1,4 @@
import os
import re
import uuid
from random import choice
@ -11,8 +12,6 @@ from django.dispatch import receiver
from pgvector.django import VectorField
from phonenumber_field.modelfields import PhoneNumberField
from khoj.utils.helpers import ConversationCommand
class BaseModel(models.Model):
created_at = models.DateTimeField(auto_now_add=True)
@ -74,9 +73,10 @@ class Subscription(BaseModel):
STANDARD = "standard"
user = models.OneToOneField(KhojUser, on_delete=models.CASCADE, related_name="subscription")
type = models.CharField(max_length=20, choices=Type.choices, default=Type.TRIAL)
type = models.CharField(max_length=20, choices=Type.choices, default=Type.STANDARD)
is_recurring = models.BooleanField(default=False)
renewal_date = models.DateTimeField(null=True, default=None, blank=True)
enabled_trial_at = models.DateTimeField(null=True, default=None, blank=True)
class OpenAIProcessorConversationConfig(BaseModel):
@ -174,14 +174,19 @@ class Agent(BaseModel):
# These map to various ConversationCommand types
TEXT = "text"
IMAGE = "image"
AUTOMATION = "automation"
creator = models.ForeignKey(
KhojUser, on_delete=models.CASCADE, default=None, null=True, blank=True
) # Creator will only be null when the agents are managed by admin
name = models.CharField(max_length=200)
personality = models.TextField()
input_tools = ArrayField(models.CharField(max_length=200, choices=InputToolOptions.choices), default=list)
output_modes = ArrayField(models.CharField(max_length=200, choices=OutputModeOptions.choices), default=list)
input_tools = ArrayField(
models.CharField(max_length=200, choices=InputToolOptions.choices), default=list, null=True, blank=True
)
output_modes = ArrayField(
models.CharField(max_length=200, choices=OutputModeOptions.choices), default=list, null=True, blank=True
)
managed_by_admin = models.BooleanField(default=False)
chat_model = models.ForeignKey(ChatModelOptions, on_delete=models.CASCADE)
slug = models.CharField(max_length=200, unique=True)
@ -243,6 +248,79 @@ class GithubRepoConfig(BaseModel):
github_config = models.ForeignKey(GithubConfig, on_delete=models.CASCADE, related_name="githubrepoconfig")
class WebScraper(BaseModel):
class WebScraperType(models.TextChoices):
FIRECRAWL = "Firecrawl"
OLOSTEP = "Olostep"
JINA = "Jina"
DIRECT = "Direct"
name = models.CharField(
max_length=200,
default=None,
null=True,
blank=True,
unique=True,
help_text="Friendly name. If not set, it will be set to the type of the scraper.",
)
type = models.CharField(max_length=20, choices=WebScraperType.choices, default=WebScraperType.JINA)
api_key = models.CharField(
max_length=200,
default=None,
null=True,
blank=True,
help_text="API key of the web scraper. Only set if scraper service requires an API key. Default is set from env var.",
)
api_url = models.URLField(
max_length=200,
default=None,
null=True,
blank=True,
help_text="API URL of the web scraper. Only set if scraper service on non-default URL.",
)
priority = models.IntegerField(
default=None,
null=True,
blank=True,
unique=True,
help_text="Priority of the web scraper. Lower numbers run first.",
)
def clean(self):
error = {}
if self.name is None:
self.name = self.type.capitalize()
if self.api_url is None:
if self.type == self.WebScraperType.FIRECRAWL:
self.api_url = os.getenv("FIRECRAWL_API_URL", "https://api.firecrawl.dev")
elif self.type == self.WebScraperType.OLOSTEP:
self.api_url = os.getenv("OLOSTEP_API_URL", "https://agent.olostep.com/olostep-p2p-incomingAPI")
elif self.type == self.WebScraperType.JINA:
self.api_url = os.getenv("JINA_READER_API_URL", "https://r.jina.ai/")
if self.api_key is None:
if self.type == self.WebScraperType.FIRECRAWL:
self.api_key = os.getenv("FIRECRAWL_API_KEY")
if not self.api_key and self.api_url == "https://api.firecrawl.dev":
error["api_key"] = "Set API key to use default Firecrawl. Get API key from https://firecrawl.dev."
elif self.type == self.WebScraperType.OLOSTEP:
self.api_key = os.getenv("OLOSTEP_API_KEY")
if self.api_key is None:
error["api_key"] = "Set API key to use Olostep. Get API key from https://olostep.com/."
elif self.type == self.WebScraperType.JINA:
self.api_key = os.getenv("JINA_API_KEY")
if error:
raise ValidationError(error)
def save(self, *args, **kwargs):
self.clean()
if self.priority is None:
max_priority = WebScraper.objects.aggregate(models.Max("priority"))["priority__max"]
self.priority = max_priority + 1 if max_priority else 1
super().save(*args, **kwargs)
class ServerChatSettings(BaseModel):
chat_default = models.ForeignKey(
ChatModelOptions, on_delete=models.CASCADE, default=None, null=True, blank=True, related_name="chat_default"
@ -250,6 +328,9 @@ class ServerChatSettings(BaseModel):
chat_advanced = models.ForeignKey(
ChatModelOptions, on_delete=models.CASCADE, default=None, null=True, blank=True, related_name="chat_advanced"
)
web_scraper = models.ForeignKey(
WebScraper, on_delete=models.CASCADE, default=None, null=True, blank=True, related_name="web_scraper"
)
class LocalOrgConfig(BaseModel):
@ -368,6 +449,7 @@ class UserVoiceModelConfig(BaseModel):
setting = models.ForeignKey(VoiceModelOption, on_delete=models.CASCADE, default=None, null=True, blank=True)
# TODO Delete this model once all users have been migrated to the server's default settings
class UserSearchModelConfig(BaseModel):
user = models.OneToOneField(KhojUser, on_delete=models.CASCADE)
setting = models.ForeignKey(SearchModelConfig, on_delete=models.CASCADE)
@ -454,6 +536,7 @@ class Entry(BaseModel):
url = models.URLField(max_length=400, default=None, null=True, blank=True)
hashed_value = models.CharField(max_length=100)
corpus_id = models.UUIDField(default=uuid.uuid4, editable=False)
search_model = models.ForeignKey(SearchModelConfig, on_delete=models.SET_NULL, default=None, null=True, blank=True)
def save(self, *args, **kwargs):
if self.user and self.agent:

View file

@ -14,5 +14,6 @@
clip-rule="evenodd"
fill-rule="evenodd"
fill="currentColor"
stroke="currentColor"
stroke-width="0.95844" />
</svg>

Before

Width:  |  Height:  |  Size: 2.5 KiB

After

Width:  |  Height:  |  Size: 2.5 KiB

View file

@ -12,6 +12,7 @@
fill-rule="evenodd"
clip-rule="evenodd"
fill-opacity="1"
stroke="currentColor"
stroke-width="1.16584"
stroke-dasharray="none"
/>

Before

Width:  |  Height:  |  Size: 1.5 KiB

After

Width:  |  Height:  |  Size: 1.5 KiB

View file

@ -0,0 +1,24 @@
<svg xmlns="http://www.w3.org/2000/svg"
width="800px"
height="800px"
viewBox="0 0 24 24"
fill="none"
version="1.1">
<path
d="m 14.024348,9.8497703 0.04627,1.9750167"
stroke="currentColor"
stroke-width="1.77073"
stroke-linecap="round" />
<path
d="m 9.6453624,9.7953624 0.046275,1.9750166"
stroke="currentColor"
stroke-width="1.77072"
stroke-linecap="round" />
<path
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After

Width:  |  Height:  |  Size: 2.4 KiB

View file

@ -46,33 +46,16 @@
<p>Transform the way you think, create, and remember</p>
<div class="features">
<div class="feature">
<svg viewBox="0 0 24 24" width="24" height="24" stroke="currentColor" stroke-width="2"
fill="none">
<path d="M14 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2V8z" />
<path d="M14 2v6h6" />
<path d="M16 13H8" />
<path d="M16 17H8" />
<path d="M10 9H8" />
</svg>
<img src="/static/assets/icons/chat.svg" alt="Chat" width="24" height="24">
<span>Get answers across your documents and the internet</span>
</div>
<div class="feature">
<svg viewBox="0 0 24 24" width="24" height="24" stroke="currentColor" stroke-width="2"
fill="none">
<path
d="M21 16V8a2 2 0 0 0-1-1.73l-7-4a2 2 0 0 0-2 0l-7 4A2 2 0 0 0 3 8v8a2 2 0 0 0 1 1.73l7 4a2 2 0 0 0 2 0l7-4A2 2 0 0 0 21 16z" />
<path d="M3.3 7l8.7 5 8.7-5" />
</svg>
<span>Go deeper in the topics personal to you</span>
<img src="/static/assets/icons/agents.svg" alt="Agents" width="24" height="24">
<span>Create agents with the knowledge and tools to take on any role</span>
</div>
<div class="feature">
<svg viewBox="0 0 24 24" width="24" height="24" stroke="currentColor" stroke-width="2"
fill="none">
<path d="M12 2L2 7l10 5 10-5-10-5z" />
<path d="M2 17l10 5 10-5" />
<path d="M2 12l10 5 10-5" />
</svg>
<span>Use specialized agents</span>
<img src="/static/assets/icons/automation.svg" alt="Automations" width="24" height="24">
<span>Automate away repetitive research</span>
</div>
</div>
</div>
@ -160,6 +143,12 @@
height: 24px;
stroke: white;
}
.feature img {
width: 24px;
height: 24px;
filter: invert(100%) sepia(0%) saturate(0%) hue-rotate(0deg) brightness(100%) contrast(100%);
stroke: white;
}
#login-modal {
display: grid;

View file

@ -64,6 +64,8 @@ class ImageToEntries(TextToEntries):
tmp_file = f"tmp_image_file_{timestamp_now}.png"
elif image_file.endswith(".jpg") or image_file.endswith(".jpeg"):
tmp_file = f"tmp_image_file_{timestamp_now}.jpg"
elif image_file.endswith(".webp"):
tmp_file = f"tmp_image_file_{timestamp_now}.webp"
with open(tmp_file, "wb") as f:
bytes = image_files[image_file]
f.write(bytes)

View file

@ -67,7 +67,7 @@ class PdfToEntries(TextToEntries):
bytes = pdf_files[pdf_file]
f.write(bytes)
try:
loader = PyMuPDFLoader(f"{tmp_file}", extract_images=True)
loader = PyMuPDFLoader(f"{tmp_file}", extract_images=False)
pdf_entries_per_file = [page.page_content for page in loader.load()]
except ImportError:
loader = PyMuPDFLoader(f"{tmp_file}")

View file

@ -12,7 +12,8 @@ from tqdm import tqdm
from khoj.database.adapters import (
EntryAdapters,
FileObjectAdapters,
get_user_search_model_or_default,
get_default_search_model,
get_user_default_search_model,
)
from khoj.database.models import Entry as DbEntry
from khoj.database.models import EntryDates, KhojUser
@ -148,10 +149,10 @@ class TextToEntries(ABC):
hashes_to_process |= hashes_for_file - existing_entry_hashes
embeddings = []
model = get_user_default_search_model(user=user)
with timer("Generated embeddings for entries to add to database in", logger):
entries_to_process = [hash_to_current_entries[hashed_val] for hashed_val in hashes_to_process]
data_to_embed = [getattr(entry, key) for entry in entries_to_process]
model = get_user_search_model_or_default(user)
embeddings += self.embeddings_model[model.name].embed_documents(data_to_embed)
added_entries: list[DbEntry] = []
@ -177,6 +178,7 @@ class TextToEntries(ABC):
file_type=file_type,
hashed_value=entry_hash,
corpus_id=entry.corpus_id,
search_model=model,
)
)
try:

View file

@ -6,14 +6,17 @@ from typing import Dict, Optional
from langchain.schema import ChatMessage
from khoj.database.models import Agent, KhojUser
from khoj.database.models import Agent, ChatModelOptions, KhojUser
from khoj.processor.conversation import prompts
from khoj.processor.conversation.google.utils import (
format_messages_for_gemini,
gemini_chat_completion_with_backoff,
gemini_completion_with_backoff,
)
from khoj.processor.conversation.utils import generate_chatml_messages_with_context
from khoj.processor.conversation.utils import (
construct_structured_message,
generate_chatml_messages_with_context,
)
from khoj.utils.helpers import ConversationCommand, is_none_or_empty
from khoj.utils.rawconfig import LocationData
@ -29,6 +32,8 @@ def extract_questions_gemini(
max_tokens=None,
location_data: LocationData = None,
user: KhojUser = None,
query_images: Optional[list[str]] = None,
vision_enabled: bool = False,
personality_context: Optional[str] = None,
):
"""
@ -70,17 +75,17 @@ def extract_questions_gemini(
text=text,
)
messages = [ChatMessage(content=prompt, role="user")]
prompt = construct_structured_message(
message=prompt,
images=query_images,
model_type=ChatModelOptions.ModelType.GOOGLE,
vision_enabled=vision_enabled,
)
model_kwargs = {"response_mime_type": "application/json"}
messages = [ChatMessage(content=prompt, role="user"), ChatMessage(content=system_prompt, role="system")]
response = gemini_completion_with_backoff(
messages=messages,
system_prompt=system_prompt,
model_name=model,
temperature=temperature,
api_key=api_key,
model_kwargs=model_kwargs,
response = gemini_send_message_to_model(
messages, api_key, model, response_type="json_object", temperature=temperature
)
# Extract, Clean Message from Gemini's Response
@ -102,7 +107,7 @@ def extract_questions_gemini(
return questions
def gemini_send_message_to_model(messages, api_key, model, response_type="text"):
def gemini_send_message_to_model(messages, api_key, model, response_type="text", temperature=0, model_kwargs=None):
"""
Send message to model
"""
@ -114,7 +119,12 @@ def gemini_send_message_to_model(messages, api_key, model, response_type="text")
# Get Response from Gemini
return gemini_completion_with_backoff(
messages=messages, system_prompt=system_prompt, model_name=model, api_key=api_key, model_kwargs=model_kwargs
messages=messages,
system_prompt=system_prompt,
model_name=model,
api_key=api_key,
temperature=temperature,
model_kwargs=model_kwargs,
)
@ -134,6 +144,8 @@ def converse_gemini(
location_data: LocationData = None,
user_name: str = None,
agent: Agent = None,
query_images: Optional[list[str]] = None,
vision_available: bool = False,
):
"""
Converse with user using Google's Gemini
@ -192,6 +204,9 @@ def converse_gemini(
model_name=model,
max_prompt_size=max_prompt_size,
tokenizer_name=tokenizer_name,
query_images=query_images,
vision_enabled=vision_available,
model_type=ChatModelOptions.ModelType.GOOGLE,
)
messages, system_prompt = format_messages_for_gemini(messages, system_prompt)

View file

@ -1,8 +1,11 @@
import logging
import random
from io import BytesIO
from threading import Thread
import google.generativeai as genai
import PIL.Image
import requests
from google.generativeai.types.answer_types import FinishReason
from google.generativeai.types.generation_types import StopCandidateException
from google.generativeai.types.safety_types import (
@ -53,14 +56,14 @@ def gemini_completion_with_backoff(
},
)
formatted_messages = [{"role": message.role, "parts": [message.content]} for message in messages]
formatted_messages = [{"role": message.role, "parts": message.content} for message in messages]
# Start chat session. All messages up to the last are considered to be part of the chat history
chat_session = model.start_chat(history=formatted_messages[0:-1])
try:
# Generate the response. The last message is considered to be the current prompt
aggregated_response = chat_session.send_message(formatted_messages[-1]["parts"][0])
aggregated_response = chat_session.send_message(formatted_messages[-1]["parts"])
return aggregated_response.text
except StopCandidateException as e:
response_message, _ = handle_gemini_response(e.args)
@ -117,11 +120,11 @@ def gemini_llm_thread(g, messages, system_prompt, model_name, temperature, api_k
},
)
formatted_messages = [{"role": message.role, "parts": [message.content]} for message in messages]
formatted_messages = [{"role": message.role, "parts": message.content} for message in messages]
# all messages up to the last are considered to be part of the chat history
chat_session = model.start_chat(history=formatted_messages[0:-1])
# the last message is considered to be the current prompt
for chunk in chat_session.send_message(formatted_messages[-1]["parts"][0], stream=True):
for chunk in chat_session.send_message(formatted_messages[-1]["parts"], stream=True):
message, stopped = handle_gemini_response(chunk.candidates, chunk.prompt_feedback)
message = message or chunk.text
g.send(message)
@ -148,6 +151,10 @@ def handle_gemini_response(candidates, prompt_feedback=None):
elif candidates[0].finish_reason == FinishReason.SAFETY:
message = generate_safety_response(candidates[0].safety_ratings)
stopped = True
# Check if finish reason is empty, therefore generation is in progress
elif not candidates[0].finish_reason:
message = None
stopped = False
# Check if the response was stopped due to reaching maximum token limit or other reasons
elif candidates[0].finish_reason != FinishReason.STOP:
message = f"\nI can't talk further about that because of **{candidates[0].finish_reason.name} issue.**"
@ -187,14 +194,6 @@ def generate_safety_response(safety_ratings):
def format_messages_for_gemini(messages: list[ChatMessage], system_prompt: str = None) -> tuple[list[str], str]:
if len(messages) == 1:
messages[0].role = "user"
return messages, system_prompt
for message in messages:
if message.role == "assistant":
message.role = "model"
# Extract system message
system_prompt = system_prompt or ""
for message in messages.copy():
@ -203,4 +202,31 @@ def format_messages_for_gemini(messages: list[ChatMessage], system_prompt: str =
messages.remove(message)
system_prompt = None if is_none_or_empty(system_prompt) else system_prompt
for message in messages:
# Convert message content to string list from chatml dictionary list
if isinstance(message.content, list):
# Convert image_urls to PIL.Image and place them at beginning of list (better for Gemini)
message.content = [
get_image_from_url(item["image_url"]["url"]) if item["type"] == "image_url" else item["text"]
for item in sorted(message.content, key=lambda x: 0 if x["type"] == "image_url" else 1)
]
elif isinstance(message.content, str):
message.content = [message.content]
if message.role == "assistant":
message.role = "model"
if len(messages) == 1:
messages[0].role = "user"
return messages, system_prompt
def get_image_from_url(image_url: str) -> PIL.Image:
try:
response = requests.get(image_url)
response.raise_for_status() # Check if the request was successful
return PIL.Image.open(BytesIO(response.content))
except requests.exceptions.RequestException as e:
logger.error(f"Failed to get image from URL {image_url}: {e}")
return None

View file

@ -1,127 +0,0 @@
from fastapi import HTTPException
from khoj.database.adapters import ConversationAdapters, ais_user_subscribed
from khoj.database.models import ChatModelOptions, KhojUser
from khoj.processor.conversation.anthropic.anthropic_chat import (
anthropic_send_message_to_model,
)
from khoj.processor.conversation.google.gemini_chat import gemini_send_message_to_model
from khoj.processor.conversation.offline.chat_model import send_message_to_model_offline
from khoj.processor.conversation.openai.gpt import send_message_to_model
from khoj.processor.conversation.utils import generate_chatml_messages_with_context
from khoj.utils import state
from khoj.utils.config import OfflineChatProcessorModel
async def send_message_to_model_wrapper(
message: str,
system_message: str = "",
response_type: str = "text",
chat_model_option: ChatModelOptions = None,
user: KhojUser = None,
uploaded_image_url: str = None,
):
conversation_config: ChatModelOptions = (
chat_model_option or await ConversationAdapters.aget_default_conversation_config(user)
)
vision_available = conversation_config.vision_enabled
if not vision_available and uploaded_image_url:
vision_enabled_config = await ConversationAdapters.aget_vision_enabled_config()
if vision_enabled_config:
conversation_config = vision_enabled_config
vision_available = True
subscribed = await ais_user_subscribed(user)
chat_model = conversation_config.chat_model
max_tokens = (
conversation_config.subscribed_max_prompt_size
if subscribed and conversation_config.subscribed_max_prompt_size
else conversation_config.max_prompt_size
)
tokenizer = conversation_config.tokenizer
model_type = conversation_config.model_type
vision_available = conversation_config.vision_enabled
if model_type == ChatModelOptions.ModelType.OFFLINE:
if state.offline_chat_processor_config is None or state.offline_chat_processor_config.loaded_model is None:
state.offline_chat_processor_config = OfflineChatProcessorModel(chat_model, max_tokens)
loaded_model = state.offline_chat_processor_config.loaded_model
truncated_messages = generate_chatml_messages_with_context(
user_message=message,
system_message=system_message,
model_name=chat_model,
loaded_model=loaded_model,
tokenizer_name=tokenizer,
max_prompt_size=max_tokens,
vision_enabled=vision_available,
model_type=conversation_config.model_type,
)
return send_message_to_model_offline(
messages=truncated_messages,
loaded_model=loaded_model,
model=chat_model,
max_prompt_size=max_tokens,
streaming=False,
response_type=response_type,
)
elif model_type == ChatModelOptions.ModelType.OPENAI:
openai_chat_config = conversation_config.openai_config
api_key = openai_chat_config.api_key
api_base_url = openai_chat_config.api_base_url
truncated_messages = generate_chatml_messages_with_context(
user_message=message,
system_message=system_message,
model_name=chat_model,
max_prompt_size=max_tokens,
tokenizer_name=tokenizer,
vision_enabled=vision_available,
uploaded_image_url=uploaded_image_url,
model_type=conversation_config.model_type,
)
return send_message_to_model(
messages=truncated_messages,
api_key=api_key,
model=chat_model,
response_type=response_type,
api_base_url=api_base_url,
)
elif model_type == ChatModelOptions.ModelType.ANTHROPIC:
api_key = conversation_config.openai_config.api_key
truncated_messages = generate_chatml_messages_with_context(
user_message=message,
system_message=system_message,
model_name=chat_model,
max_prompt_size=max_tokens,
tokenizer_name=tokenizer,
vision_enabled=vision_available,
uploaded_image_url=uploaded_image_url,
model_type=conversation_config.model_type,
)
return anthropic_send_message_to_model(
messages=truncated_messages,
api_key=api_key,
model=chat_model,
)
elif model_type == ChatModelOptions.ModelType.GOOGLE:
api_key = conversation_config.openai_config.api_key
truncated_messages = generate_chatml_messages_with_context(
user_message=message,
system_message=system_message,
model_name=chat_model,
max_prompt_size=max_tokens,
tokenizer_name=tokenizer,
vision_enabled=vision_available,
uploaded_image_url=uploaded_image_url,
)
return gemini_send_message_to_model(
messages=truncated_messages, api_key=api_key, model=chat_model, response_type=response_type
)
else:
raise HTTPException(status_code=500, detail="Invalid conversation config")

View file

@ -30,7 +30,7 @@ def extract_questions(
api_base_url=None,
location_data: LocationData = None,
user: KhojUser = None,
uploaded_image_url: Optional[str] = None,
query_images: Optional[list[str]] = None,
vision_enabled: bool = False,
personality_context: Optional[str] = None,
):
@ -74,7 +74,7 @@ def extract_questions(
prompt = construct_structured_message(
message=prompt,
image_url=uploaded_image_url,
images=query_images,
model_type=ChatModelOptions.ModelType.OPENAI,
vision_enabled=vision_enabled,
)
@ -136,7 +136,7 @@ def converse(
location_data: LocationData = None,
user_name: str = None,
agent: Agent = None,
image_url: Optional[str] = None,
query_images: Optional[list[str]] = None,
vision_available: bool = False,
):
"""
@ -196,7 +196,7 @@ def converse(
model_name=model,
max_prompt_size=max_prompt_size,
tokenizer_name=tokenizer_name,
uploaded_image_url=image_url,
query_images=query_images,
vision_enabled=vision_available,
model_type=ChatModelOptions.ModelType.OPENAI,
)

View file

@ -49,7 +49,7 @@ Instructions:\n{bio}
# Prompt forked from https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models
gemini_verbose_language_personality = """
All questions should be answered comprehensively with details, unless the user requests a concise response specifically.
Respond in the same language as the query.
Respond in the same language as the query. Use markdown to format your responses.
""".strip()
## General Conversation
@ -176,6 +176,150 @@ Improved Prompt:
""".strip()
)
## Diagram Generation
## --
improve_diagram_description_prompt = PromptTemplate.from_template(
"""
you are an architect working with a novice artist using a diagramming tool.
{personality_context}
you need to convert the user's query to a description format that the novice artist can use very well. you are allowed to use primitives like
- text
- rectangle
- diamond
- ellipse
- line
- arrow
- frame
use these primitives to describe what sort of diagram the drawer should create. the artist must recreate the diagram every time, so include all relevant prior information in your description.
use simple, concise language.
Today's Date: {current_date}
User's Location: {location}
User's Notes:
{references}
Online References:
{online_results}
Conversation Log:
{chat_history}
Query: {query}
""".strip()
)
excalidraw_diagram_generation_prompt = PromptTemplate.from_template(
"""
You are a program manager with the ability to describe diagrams to compose in professional, fine detail.
{personality_context}
You need to create a declarative description of the diagram and relevant components, using this base schema. Use the `label` property to specify the text to be rendered in the respective elements. Always use light colors for the `backgroundColor` property, like white, or light blue, green, red. "type", "x", "y", "id", are required properties for all elements.
{{
type: string,
x: number,
y: number,
strokeColor: string,
backgroundColor: string,
width: number,
height: number,
id: string,
label: {{
text: string,
}}
}}
Valid types:
- text
- rectangle
- diamond
- ellipse
- line
- arrow
For arrows and lines, you can use the `points` property to specify the start and end points of the arrow. You may also use the `label` property to specify the text to be rendered. You may use the `start` and `end` properties to connect the linear elements to other elements. The start and end point can either be the ID to map to an existing object, or the `type` to create a new object. Mapping to an existing object is useful if you want to connect it to multiple objects. Lines and arrows can only start and end at rectangle, text, diamond, or ellipse elements.
{{
type: "arrow",
id: string,
x: number,
y: number,
width: number,
height: number,
strokeColor: string,
start: {{
id: string,
type: string,
}},
end: {{
id: string,
type: string,
}},
label: {{
text: string,
}}
points: [
[number, number],
[number, number],
]
}}
For text, you must use the `text` property to specify the text to be rendered. You may also use `fontSize` property to specify the font size of the text. Only use the `text` element for titles, subtitles, and overviews. For labels, use the `label` property in the respective elements.
{{
type: "text",
id: string,
x: number,
y: number,
fontSize: number,
text: string,
}}
For frames, use the `children` property to specify the elements that are inside the frame by their ids.
{{
type: "frame",
id: string,
x: number,
y: number,
width: number,
height: number,
name: string,
children: [
string
]
}}
Here's an example of a valid diagram:
Design Description: Create a diagram describing a circular development process with 3 stages: design, implementation and feedback. The design stage is connected to the implementation stage and the implementation stage is connected to the feedback stage and the feedback stage is connected to the design stage. Each stage should be labeled with the stage name.
Response:
[
{{"type":"text","x":-150,"y":50,"width":300,"height":40,"id":"title_text","text":"Circular Development Process","fontSize":24}},
{{"type":"ellipse","x":-169,"y":113,"width":188,"height":202,"id":"design_ellipse", "label": {{"text": "Design"}}}},
{{"type":"ellipse","x":62,"y":394,"width":186,"height":188,"id":"implement_ellipse", "label": {{"text": "Implement"}}}},
{{"type":"ellipse","x":-348,"y":430,"width":184,"height":170,"id":"feedback_ellipse", "label": {{"text": "Feedback"}}}},
{{"type":"arrow","x":21,"y":273,"id":"design_to_implement_arrow","points":[[0,0],[86,105]],"start":{{"id":"design_ellipse"}}, "end":{{"id":"implement_ellipse"}}}},
{{"type":"arrow","x":50,"y":519,"id":"implement_to_feedback_arrow","points":[[0,0],[-198,-6]],"start":{{"id":"implement_ellipse"}}, "end":{{"id":"feedback_ellipse"}}}},
{{"type":"arrow","x":-228,"y":417,"id":"feedback_to_design_arrow","points":[[0,0],[85,-123]],"start":{{"id":"feedback_ellipse"}}, "end":{{"id":"design_ellipse"}}}},
]
Create a detailed diagram from the provided context and user prompt below. Return a valid JSON object:
Diagram Description: {query}
""".strip()
)
## Online Search Conversation
## --
online_search_conversation = PromptTemplate.from_template(

View file

@ -168,7 +168,7 @@ def save_to_conversation_log(
client_application: ClientApplication = None,
conversation_id: str = None,
automation_id: str = None,
uploaded_image_url: str = None,
query_images: List[str] = None,
):
user_message_time = user_message_time or datetime.now().strftime("%Y-%m-%d %H:%M:%S")
updated_conversation = message_to_log(
@ -176,7 +176,7 @@ def save_to_conversation_log(
chat_response=chat_response,
user_message_metadata={
"created": user_message_time,
"uploadedImageData": uploaded_image_url,
"images": query_images,
},
khoj_message_metadata={
"context": compiled_references,
@ -205,10 +205,18 @@ Khoj: "{inferred_queries if ("text-to-image" in intent_type) else chat_response}
)
# Format user and system messages to chatml format
def construct_structured_message(message, image_url, model_type, vision_enabled):
if image_url and vision_enabled and model_type == ChatModelOptions.ModelType.OPENAI:
return [{"type": "text", "text": message}, {"type": "image_url", "image_url": {"url": image_url}}]
def construct_structured_message(message: str, images: list[str], model_type: str, vision_enabled: bool):
"""
Format messages into appropriate multimedia format for supported chat model types
"""
if not images or not vision_enabled:
return message
if model_type in [ChatModelOptions.ModelType.OPENAI, ChatModelOptions.ModelType.GOOGLE]:
return [
{"type": "text", "text": message},
*[{"type": "image_url", "image_url": {"url": image}} for image in images],
]
return message
@ -220,7 +228,7 @@ def generate_chatml_messages_with_context(
loaded_model: Optional[Llama] = None,
max_prompt_size=None,
tokenizer_name=None,
uploaded_image_url=None,
query_images=None,
vision_enabled=False,
model_type="",
):
@ -241,11 +249,12 @@ def generate_chatml_messages_with_context(
message_notes = f'\n\n Notes:\n{chat.get("context")}' if chat.get("context") else "\n"
role = "user" if chat["by"] == "you" else "assistant"
message_content = chat["message"] + message_notes
if chat["by"] == "khoj" and "excalidraw" in chat["intent"].get("type"):
message_content = chat.get("intent").get("inferred-queries")[0] + message_notes
else:
message_content = chat["message"] + message_notes
message_content = construct_structured_message(
message_content, chat.get("uploadedImageData"), model_type, vision_enabled
)
message_content = construct_structured_message(message_content, chat.get("images"), model_type, vision_enabled)
reconstructed_message = ChatMessage(content=message_content, role=role)
@ -258,7 +267,7 @@ def generate_chatml_messages_with_context(
if not is_none_or_empty(user_message):
messages.append(
ChatMessage(
content=construct_structured_message(user_message, uploaded_image_url, model_type, vision_enabled),
content=construct_structured_message(user_message, query_images, model_type, vision_enabled),
role="user",
)
)
@ -282,7 +291,6 @@ def truncate_messages(
tokenizer_name=None,
) -> list[ChatMessage]:
"""Truncate messages to fit within max prompt size supported by model"""
default_tokenizer = "gpt-4o"
try:
@ -312,6 +320,7 @@ def truncate_messages(
system_message = messages.pop(idx)
break
# TODO: Handle truncation of multi-part message.content, i.e when message.content is a list[dict] rather than a string
system_message_tokens = (
len(encoder.encode(system_message.content)) if system_message and type(system_message.content) == str else 0
)

View file

@ -26,7 +26,7 @@ async def text_to_image(
references: List[Dict[str, Any]],
online_results: Dict[str, Any],
send_status_func: Optional[Callable] = None,
uploaded_image_url: Optional[str] = None,
query_images: Optional[List[str]] = None,
agent: Agent = None,
):
status_code = 200
@ -65,7 +65,7 @@ async def text_to_image(
note_references=references,
online_results=online_results,
model_type=text_to_image_config.model_type,
uploaded_image_url=uploaded_image_url,
query_images=query_images,
user=user,
agent=agent,
)
@ -87,18 +87,18 @@ async def text_to_image(
if "content_policy_violation" in e.message:
logger.error(f"Image Generation blocked by OpenAI: {e}")
status_code = e.status_code # type: ignore
message = f"Image generation blocked by OpenAI: {e.message}" # type: ignore
message = f"Image generation blocked by OpenAI due to policy violation" # type: ignore
yield image_url or image, status_code, message, intent_type.value
return
else:
logger.error(f"Image Generation failed with {e}", exc_info=True)
message = f"Image generation failed with OpenAI error: {e.message}" # type: ignore
message = f"Image generation failed using OpenAI" # type: ignore
status_code = e.status_code # type: ignore
yield image_url or image, status_code, message, intent_type.value
return
except requests.RequestException as e:
logger.error(f"Image Generation failed with {e}", exc_info=True)
message = f"Image generation using {text2image_model} via {text_to_image_config.model_type} failed with error: {e}"
message = f"Image generation using {text2image_model} via {text_to_image_config.model_type} failed due to a network error."
status_code = 502
yield image_url or image, status_code, message, intent_type.value
return

View file

@ -10,14 +10,22 @@ import aiohttp
from bs4 import BeautifulSoup
from markdownify import markdownify
from khoj.database.models import Agent, KhojUser
from khoj.database.adapters import ConversationAdapters
from khoj.database.models import Agent, KhojUser, WebScraper
from khoj.processor.conversation import prompts
from khoj.routers.helpers import (
ChatEvent,
extract_relevant_info,
generate_online_subqueries,
infer_webpage_urls,
)
from khoj.utils.helpers import is_internet_connected, is_none_or_empty, timer
from khoj.utils.helpers import (
is_env_var_true,
is_internal_url,
is_internet_connected,
is_none_or_empty,
timer,
)
from khoj.utils.rawconfig import LocationData
logger = logging.getLogger(__name__)
@ -25,12 +33,11 @@ logger = logging.getLogger(__name__)
SERPER_DEV_API_KEY = os.getenv("SERPER_DEV_API_KEY")
SERPER_DEV_URL = "https://google.serper.dev/search"
JINA_READER_API_URL = "https://r.jina.ai/"
JINA_SEARCH_API_URL = "https://s.jina.ai/"
JINA_API_KEY = os.getenv("JINA_API_KEY")
OLOSTEP_API_KEY = os.getenv("OLOSTEP_API_KEY")
OLOSTEP_API_URL = "https://agent.olostep.com/olostep-p2p-incomingAPI"
FIRECRAWL_USE_LLM_EXTRACT = is_env_var_true("FIRECRAWL_USE_LLM_EXTRACT")
OLOSTEP_QUERY_PARAMS = {
"timeout": 35, # seconds
"waitBeforeScraping": 1, # seconds
@ -54,11 +61,10 @@ async def search_online(
conversation_history: dict,
location: LocationData,
user: KhojUser,
subscribed: bool = False,
send_status_func: Optional[Callable] = None,
custom_filters: List[str] = [],
max_webpages_to_read: int = DEFAULT_MAX_WEBPAGES_TO_READ,
uploaded_image_url: str = None,
query_images: List[str] = None,
agent: Agent = None,
):
query += " ".join(custom_filters)
@ -69,7 +75,7 @@ async def search_online(
# Breakdown the query into subqueries to get the correct answer
subqueries = await generate_online_subqueries(
query, conversation_history, location, user, uploaded_image_url=uploaded_image_url, agent=agent
query, conversation_history, location, user, query_images=query_images, agent=agent
)
response_dict = {}
@ -86,33 +92,31 @@ async def search_online(
search_results = await asyncio.gather(*search_tasks)
response_dict = {subquery: search_result for subquery, search_result in search_results}
# Gather distinct web page data from organic results of each subquery without an instant answer.
# Gather distinct web pages from organic results for subqueries without an instant answer.
# Content of web pages is directly available when Jina is used for search.
webpages = {
(organic.get("link"), subquery, organic.get("content"))
for subquery in response_dict
for organic in response_dict[subquery].get("organic", [])[:max_webpages_to_read]
if "answerBox" not in response_dict[subquery]
}
webpages = set()
for subquery in response_dict:
for organic in response_dict[subquery].get("organic", [])[:max_webpages_to_read]:
if "answerBox" not in response_dict[subquery]:
webpages.add(organic.get("link"), {"queries": {subquery}, "content": organic.get("content")})
# Read, extract relevant info from the retrieved web pages
if webpages:
webpage_links = set([link for link, _, _ in webpages])
logger.info(f"Reading web pages at: {list(webpage_links)}")
logger.info(f"Reading web pages at: {webpages.keys()}")
if send_status_func:
webpage_links_str = "\n- " + "\n- ".join(list(webpage_links))
webpage_links_str = "\n- " + "\n- ".join(webpages.keys())
async for event in send_status_func(f"**Reading web pages**: {webpage_links_str}"):
yield {ChatEvent.STATUS: event}
tasks = [
read_webpage_and_extract_content(subquery, link, content, user=user, agent=agent)
for link, subquery, content in webpages
read_webpage_and_extract_content(data["queries"], link, data["content"], user=user, agent=agent)
for link, data in webpages.items()
]
results = await asyncio.gather(*tasks)
# Collect extracted info from the retrieved web pages
for subquery, webpage_extract, url in results:
for subqueries, url, webpage_extract in results:
if webpage_extract is not None:
response_dict[subquery]["webpages"] = {"link": url, "snippet": webpage_extract}
response_dict[subqueries.pop()]["webpages"] = {"link": url, "snippet": webpage_extract}
yield response_dict
@ -144,7 +148,7 @@ async def read_webpages(
location: LocationData,
user: KhojUser,
send_status_func: Optional[Callable] = None,
uploaded_image_url: str = None,
query_images: List[str] = None,
agent: Agent = None,
):
"Infer web pages to read from the query and extract relevant information from them"
@ -152,36 +156,73 @@ async def read_webpages(
if send_status_func:
async for event in send_status_func(f"**Inferring web pages to read**"):
yield {ChatEvent.STATUS: event}
urls = await infer_webpage_urls(query, conversation_history, location, user, uploaded_image_url)
urls = await infer_webpage_urls(query, conversation_history, location, user, query_images)
logger.info(f"Reading web pages at: {urls}")
if send_status_func:
webpage_links_str = "\n- " + "\n- ".join(list(urls))
async for event in send_status_func(f"**Reading web pages**: {webpage_links_str}"):
yield {ChatEvent.STATUS: event}
tasks = [read_webpage_and_extract_content(query, url, user=user, agent=agent) for url in urls]
tasks = [read_webpage_and_extract_content({query}, url, user=user, agent=agent) for url in urls]
results = await asyncio.gather(*tasks)
response: Dict[str, Dict] = defaultdict(dict)
response[query]["webpages"] = [
{"query": q, "link": url, "snippet": web_extract} for q, web_extract, url in results if web_extract is not None
{"query": qs.pop(), "link": url, "snippet": extract} for qs, url, extract in results if extract is not None
]
yield response
async def read_webpage(
url, scraper_type=None, api_key=None, api_url=None, subqueries=None, agent=None
) -> Tuple[str | None, str | None]:
if scraper_type == WebScraper.WebScraperType.FIRECRAWL and FIRECRAWL_USE_LLM_EXTRACT:
return None, await query_webpage_with_firecrawl(url, subqueries, api_key, api_url, agent)
elif scraper_type == WebScraper.WebScraperType.FIRECRAWL:
return await read_webpage_with_firecrawl(url, api_key, api_url), None
elif scraper_type == WebScraper.WebScraperType.OLOSTEP:
return await read_webpage_with_olostep(url, api_key, api_url), None
elif scraper_type == WebScraper.WebScraperType.JINA:
return await read_webpage_with_jina(url, api_key, api_url), None
else:
return await read_webpage_at_url(url), None
async def read_webpage_and_extract_content(
subquery: str, url: str, content: str = None, user: KhojUser = None, agent: Agent = None
) -> Tuple[str, Union[None, str], str]:
try:
if is_none_or_empty(content):
with timer(f"Reading web page at '{url}' took", logger):
content = await read_webpage_with_olostep(url) if OLOSTEP_API_KEY else await read_webpage_with_jina(url)
with timer(f"Extracting relevant information from web page at '{url}' took", logger):
extracted_info = await extract_relevant_info(subquery, content, user=user, agent=agent)
return subquery, extracted_info, url
except Exception as e:
logger.error(f"Failed to read web page at '{url}' with {e}")
return subquery, None, url
subqueries: set[str], url: str, content: str = None, user: KhojUser = None, agent: Agent = None
) -> Tuple[set[str], str, Union[None, str]]:
# Select the web scrapers to use for reading the web page
web_scrapers = await ConversationAdapters.aget_enabled_webscrapers()
# Only use the direct web scraper for internal URLs
if is_internal_url(url):
web_scrapers = [scraper for scraper in web_scrapers if scraper.type == WebScraper.WebScraperType.DIRECT]
# Fallback through enabled web scrapers until we successfully read the web page
extracted_info = None
for scraper in web_scrapers:
try:
# Read the web page
if is_none_or_empty(content):
with timer(f"Reading web page with {scraper.type} at '{url}' took", logger, log_level=logging.INFO):
content, extracted_info = await read_webpage(
url, scraper.type, scraper.api_key, scraper.api_url, subqueries, agent
)
# Extract relevant information from the web page
if is_none_or_empty(extracted_info):
with timer(f"Extracting relevant information from web page at '{url}' took", logger):
extracted_info = await extract_relevant_info(subqueries, content, user=user, agent=agent)
# If we successfully extracted information, break the loop
if not is_none_or_empty(extracted_info):
break
except Exception as e:
logger.warning(f"Failed to read web page with {scraper.type} at '{url}' with {e}")
# If this is the last web scraper in the list, log an error
if scraper.name == web_scrapers[-1].name:
logger.error(f"All web scrapers failed for '{url}'")
return subqueries, url, extracted_info
async def read_webpage_at_url(web_url: str) -> str:
@ -198,23 +239,23 @@ async def read_webpage_at_url(web_url: str) -> str:
return markdownify(body)
async def read_webpage_with_olostep(web_url: str) -> str:
headers = {"Authorization": f"Bearer {OLOSTEP_API_KEY}"}
async def read_webpage_with_olostep(web_url: str, api_key: str, api_url: str) -> str:
headers = {"Authorization": f"Bearer {api_key}"}
web_scraping_params: Dict[str, Union[str, int, bool]] = OLOSTEP_QUERY_PARAMS.copy() # type: ignore
web_scraping_params["url"] = web_url
async with aiohttp.ClientSession() as session:
async with session.get(OLOSTEP_API_URL, params=web_scraping_params, headers=headers) as response:
async with session.get(api_url, params=web_scraping_params, headers=headers) as response:
response.raise_for_status()
response_json = await response.json()
return response_json["markdown_content"]
async def read_webpage_with_jina(web_url: str) -> str:
jina_reader_api_url = f"{JINA_READER_API_URL}/{web_url}"
async def read_webpage_with_jina(web_url: str, api_key: str, api_url: str) -> str:
jina_reader_api_url = f"{api_url}/{web_url}"
headers = {"Accept": "application/json", "X-Timeout": "30"}
if JINA_API_KEY:
headers["Authorization"] = f"Bearer {JINA_API_KEY}"
if api_key:
headers["Authorization"] = f"Bearer {api_key}"
async with aiohttp.ClientSession() as session:
async with session.get(jina_reader_api_url, headers=headers) as response:
@ -223,6 +264,54 @@ async def read_webpage_with_jina(web_url: str) -> str:
return response_json["data"]["content"]
async def read_webpage_with_firecrawl(web_url: str, api_key: str, api_url: str) -> str:
firecrawl_api_url = f"{api_url}/v1/scrape"
headers = {"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"}
params = {"url": web_url, "formats": ["markdown"], "excludeTags": ["script", ".ad"]}
async with aiohttp.ClientSession() as session:
async with session.post(firecrawl_api_url, json=params, headers=headers) as response:
response.raise_for_status()
response_json = await response.json()
return response_json["data"]["markdown"]
async def query_webpage_with_firecrawl(
web_url: str, queries: set[str], api_key: str, api_url: str, agent: Agent = None
) -> str:
firecrawl_api_url = f"{api_url}/v1/scrape"
headers = {"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"}
schema = {
"type": "object",
"properties": {
"relevant_extract": {"type": "string"},
},
"required": [
"relevant_extract",
],
}
personality_context = (
prompts.personality_context.format(personality=agent.personality) if agent and agent.personality else ""
)
system_prompt = f"""
{prompts.system_prompt_extract_relevant_information}
{personality_context}
User Query: {", ".join(queries)}
Collate only relevant information from the website to answer the target query and in the provided JSON schema.
""".strip()
params = {"url": web_url, "formats": ["extract"], "extract": {"systemPrompt": system_prompt, "schema": schema}}
async with aiohttp.ClientSession() as session:
async with session.post(firecrawl_api_url, json=params, headers=headers) as response:
response.raise_for_status()
response_json = await response.json()
return response_json["data"]["extract"]["relevant_extract"]
async def search_with_jina(query: str, location: LocationData) -> Tuple[str, Dict[str, List[Dict]]]:
encoded_query = urllib.parse.quote(query)
jina_search_api_url = f"{JINA_SEARCH_API_URL}/{encoded_query}"

View file

@ -10,12 +10,12 @@ import aiohttp
from khoj.database.adapters import ais_user_subscribed
from khoj.database.models import Agent, KhojUser
from khoj.processor.conversation import prompts
from khoj.processor.conversation.helpers import send_message_to_model_wrapper
from khoj.processor.conversation.utils import (
ChatEvent,
construct_chat_history,
remove_json_codeblock,
)
from khoj.routers.helpers import send_message_to_model_wrapper
from khoj.utils.helpers import timer
from khoj.utils.rawconfig import LocationData
@ -32,7 +32,7 @@ async def run_code(
location_data: LocationData,
user: KhojUser,
send_status_func: Optional[Callable] = None,
uploaded_image_url: str = None,
query_images: List[str] = None,
agent: Agent = None,
sandbox_url: str = SANDBOX_URL,
):
@ -43,7 +43,7 @@ async def run_code(
try:
with timer("Chat actor: Generate programs to execute", logger):
codes = await generate_python_code(
query, conversation_history, previous_iterations_history, location_data, user, uploaded_image_url, agent
query, conversation_history, previous_iterations_history, location_data, user, query_images, agent
)
except Exception as e:
raise ValueError(f"Failed to generate code for {query} with error: {e}")
@ -70,7 +70,7 @@ async def generate_python_code(
previous_iterations_history: str,
location_data: LocationData,
user: KhojUser,
uploaded_image_url: str = None,
query_images: List[str] = None,
agent: Agent = None,
) -> List[str]:
location = f"{location_data}" if location_data else "Unknown"
@ -95,7 +95,7 @@ async def generate_python_code(
response = await send_message_to_model_wrapper(
code_generation_prompt,
uploaded_image_url=uploaded_image_url,
query_images=query_images,
response_type="json_object",
user=user,
)

View file

@ -21,11 +21,13 @@ from starlette.authentication import has_required_scope, requires
from khoj.configure import initialize_content
from khoj.database import adapters
from khoj.database.adapters import (
AgentAdapters,
AutomationAdapters,
ConversationAdapters,
EntryAdapters,
get_default_search_model,
get_user_default_search_model,
get_user_photo,
get_user_search_model_or_default,
)
from khoj.database.models import (
Agent,
@ -115,10 +117,16 @@ async def execute_search(
dedupe: Optional[bool] = True,
agent: Optional[Agent] = None,
):
start_time = time.time()
# Run validation checks
results: List[SearchResponse] = []
start_time = time.time()
# Ensure the agent, if present, is accessible by the user
if user and agent and not await AgentAdapters.ais_agent_accessible(agent, user):
logger.error(f"Agent {agent.slug} is not accessible by user {user}")
return results
if q is None or q == "":
logger.warning(f"No query param (q) passed in API call to initiate search")
return results
@ -143,7 +151,7 @@ async def execute_search(
encoded_asymmetric_query = None
if t != SearchType.Image:
with timer("Encoding query took", logger=logger):
search_model = await sync_to_async(get_user_search_model_or_default)(user)
search_model = await sync_to_async(get_user_default_search_model)(user)
encoded_asymmetric_query = state.embeddings_model[search_model.name].embed_query(defiltered_query)
with concurrent.futures.ThreadPoolExecutor() as executor:
@ -341,7 +349,7 @@ async def extract_references_and_questions(
conversation_commands: List[ConversationCommand] = [ConversationCommand.Default],
location_data: LocationData = None,
send_status_func: Optional[Callable] = None,
uploaded_image_url: Optional[str] = None,
query_images: Optional[List[str]] = None,
agent: Agent = None,
):
user = request.user.object if request.user.is_authenticated else None
@ -430,7 +438,7 @@ async def extract_references_and_questions(
conversation_log=meta_log,
location_data=location_data,
user=user,
uploaded_image_url=uploaded_image_url,
query_images=query_images,
vision_enabled=vision_enabled,
personality_context=personality_context,
)
@ -451,12 +459,14 @@ async def extract_references_and_questions(
chat_model = conversation_config.chat_model
inferred_queries = extract_questions_gemini(
defiltered_query,
query_images=query_images,
model=chat_model,
api_key=api_key,
conversation_log=meta_log,
location_data=location_data,
max_tokens=conversation_config.max_prompt_size,
user=user,
vision_enabled=vision_enabled,
personality_context=personality_context,
)

View file

@ -1,5 +1,7 @@
import json
import logging
import random
from datetime import datetime, timedelta, timezone
from typing import Dict, List, Optional
from asgiref.sync import sync_to_async
@ -9,8 +11,8 @@ from fastapi.responses import Response
from pydantic import BaseModel
from starlette.authentication import requires
from khoj.database.adapters import AgentAdapters
from khoj.database.models import Agent, KhojUser
from khoj.database.adapters import AgentAdapters, ConversationAdapters
from khoj.database.models import Agent, Conversation, KhojUser
from khoj.routers.helpers import CommonQueryParams, acheck_if_safe_prompt
from khoj.utils.helpers import (
ConversationCommand,
@ -45,30 +47,49 @@ async def all_agents(
) -> Response:
user: KhojUser = request.user.object if request.user.is_authenticated else None
agents = await AgentAdapters.aget_all_accessible_agents(user)
default_agent = await AgentAdapters.aget_default_agent()
default_agent_packet = None
agents_packet = list()
for agent in agents:
files = agent.fileobject_set.all()
file_names = [file.file_name for file in files]
agents_packet.append(
{
"slug": agent.slug,
"name": agent.name,
"persona": agent.personality,
"creator": agent.creator.username if agent.creator else None,
"managed_by_admin": agent.managed_by_admin,
"color": agent.style_color,
"icon": agent.style_icon,
"privacy_level": agent.privacy_level,
"chat_model": agent.chat_model.chat_model,
"files": file_names,
"input_tools": agent.input_tools,
"output_modes": agent.output_modes,
}
)
agent_packet = {
"slug": agent.slug,
"name": agent.name,
"persona": agent.personality,
"creator": agent.creator.username if agent.creator else None,
"managed_by_admin": agent.managed_by_admin,
"color": agent.style_color,
"icon": agent.style_icon,
"privacy_level": agent.privacy_level,
"chat_model": agent.chat_model.chat_model,
"files": file_names,
"input_tools": agent.input_tools,
"output_modes": agent.output_modes,
}
if agent.slug == default_agent.slug:
default_agent_packet = agent_packet
else:
agents_packet.append(agent_packet)
# Load recent conversation sessions
min_date = datetime.min.replace(tzinfo=timezone.utc)
two_weeks_ago = datetime.today() - timedelta(weeks=2)
conversations = []
if user:
conversations = await sync_to_async(list[Conversation])(
ConversationAdapters.get_conversation_sessions(user, request.user.client_app)
.filter(updated_at__gte=two_weeks_ago)
.order_by("-updated_at")[:50]
)
conversation_times = {conv.agent.slug: conv.updated_at for conv in conversations if conv.agent}
# Put default agent first, then sort by mru and finally shuffle unused randomly
random.shuffle(agents_packet)
agents_packet.sort(key=lambda x: conversation_times.get(x["slug"]) or min_date, reverse=True)
if default_agent_packet:
agents_packet.insert(0, default_agent_packet)
# Make sure that the agent named 'khoj' is first in the list. Everything else is sorted by name.
agents_packet.sort(key=lambda x: x["name"])
agents_packet.sort(key=lambda x: x["slug"] == "khoj", reverse=True)
return Response(content=json.dumps(agents_packet), media_type="application/json", status_code=200)

View file

@ -10,15 +10,15 @@ from urllib.parse import unquote
from asgiref.sync import sync_to_async
from fastapi import APIRouter, Depends, HTTPException, Request
from fastapi.requests import Request
from fastapi.responses import Response, StreamingResponse
from starlette.authentication import has_required_scope, requires
from starlette.authentication import requires
from khoj.app.settings import ALLOWED_HOSTS
from khoj.database.adapters import (
AgentAdapters,
ConversationAdapters,
EntryAdapters,
FileObjectAdapters,
PublicConversationAdapters,
aget_user_name,
)
@ -31,8 +31,10 @@ from khoj.processor.tools.online_search import read_webpages, search_online
from khoj.processor.tools.run_code import run_code
from khoj.routers.api import extract_references_and_questions
from khoj.routers.helpers import (
ApiImageRateLimiter,
ApiUserRateLimiter,
ChatEvent,
ChatRequestBody,
CommonQueryParams,
ConversationCommandRateLimiter,
agenerate_chat_response,
@ -41,6 +43,8 @@ from khoj.routers.helpers import (
construct_automation_created_message,
create_automation,
extract_relevant_info,
extract_relevant_summary,
generate_excalidraw_diagram,
generate_summary_from_files,
get_conversation_command,
is_query_empty,
@ -529,22 +533,6 @@ async def set_conversation_title(
)
class ChatRequestBody(BaseModel):
q: str
n: Optional[int] = 7
d: Optional[float] = None
stream: Optional[bool] = False
title: Optional[str] = None
conversation_id: Optional[str] = None
city: Optional[str] = None
region: Optional[str] = None
country: Optional[str] = None
country_code: Optional[str] = None
timezone: Optional[str] = None
image: Optional[str] = None
create_new: Optional[bool] = False
@api_chat.post("")
@requires(["authenticated"])
async def chat(
@ -557,6 +545,7 @@ async def chat(
rate_limiter_per_day=Depends(
ApiUserRateLimiter(requests=600, subscribed_requests=6000, window=60 * 60 * 24, slug="chat_day")
),
image_rate_limiter=Depends(ApiImageRateLimiter(max_images=10, max_combined_size_mb=20)),
):
# Access the parameters from the body
q = body.q
@ -570,29 +559,28 @@ async def chat(
country = body.country or get_country_name_from_timezone(body.timezone)
country_code = body.country_code or get_country_code_from_timezone(body.timezone)
timezone = body.timezone
image = body.image
raw_images = body.images
async def event_generator(q: str, image: str):
async def event_generator(q: str, images: list[str]):
start_time = time.perf_counter()
ttft = None
chat_metadata: dict = {}
connection_alive = True
user: KhojUser = request.user.object
subscribed: bool = has_required_scope(request, ["premium"])
event_delimiter = "␃🔚␗"
q = unquote(q)
nonlocal conversation_id
uploaded_image_url = None
if image:
decoded_string = unquote(image)
base64_data = decoded_string.split(",", 1)[1]
image_bytes = base64.b64decode(base64_data)
webp_image_bytes = convert_image_to_webp(image_bytes)
try:
uploaded_image_url = upload_image_to_bucket(webp_image_bytes, request.user.object.id)
except:
uploaded_image_url = None
uploaded_images: list[str] = []
if images:
for image in images:
decoded_string = unquote(image)
base64_data = decoded_string.split(",", 1)[1]
image_bytes = base64.b64decode(base64_data)
webp_image_bytes = convert_image_to_webp(image_bytes)
uploaded_image = upload_image_to_bucket(webp_image_bytes, request.user.object.id)
if uploaded_image:
uploaded_images.append(uploaded_image)
async def send_event(event_type: ChatEvent, data: str | dict):
nonlocal connection_alive, ttft
@ -645,7 +633,7 @@ async def chat(
request=request,
telemetry_type="api",
api="chat",
client=request.user.client_app,
client=common.client,
user_agent=request.headers.get("user-agent"),
host=request.headers.get("host"),
metadata=chat_metadata,
@ -706,11 +694,10 @@ async def chat(
async for research_result in execute_information_collection(
request=request,
user=user,
query=q,
query=defiltered_query,
conversation_id=conversation_id,
conversation_history=meta_log,
subscribed=subscribed,
uploaded_image_url=uploaded_image_url,
query_images=raw_images,
agent=agent,
send_status_func=partial(send_event, ChatEvent.STATUS),
user_name=user_name,
@ -743,11 +730,11 @@ async def chat(
meta_log,
is_automated_task,
user=user,
uploaded_image_url=uploaded_image_url,
query_images=uploaded_images,
agent=agent,
)
mode = await aget_relevant_output_modes(q, meta_log, is_automated_task, user, uploaded_image_url, agent)
mode = await aget_relevant_output_modes(q, meta_log, is_automated_task, user, uploaded_images, agent)
async for result in send_event(ChatEvent.STATUS, f"**Decided Response Mode:** {mode.value}"):
yield result
if mode not in conversation_commands:
@ -788,11 +775,15 @@ async def chat(
user=user,
file_filters=file_filters,
meta_log=meta_log,
subscribed=subscribed,
query_images=uploaded_images,
agent=agent,
send_status_func=partial(send_event, ChatEvent.STATUS),
send_response_func=partial(send_llm_response),
):
yield response
if isinstance(response, dict) and ChatEvent.STATUS in response:
yield result[ChatEvent.STATUS]
else:
response
await sync_to_async(save_to_conversation_log)(
q,
@ -803,7 +794,7 @@ async def chat(
intent_type="summarize",
client_application=request.user.client_app,
conversation_id=conversation_id,
uploaded_image_url=uploaded_image_url,
query_images=uploaded_images,
)
return
@ -846,189 +837,189 @@ async def chat(
conversation_id=conversation_id,
inferred_queries=[query_to_run],
automation_id=automation.id,
uploaded_image_url=uploaded_image_url,
query_images=uploaded_images,
)
async for result in send_llm_response(llm_response):
yield result
return
# # Gather Context
# # Extract Document References
# try:
# async for result in extract_references_and_questions(
# request,
# meta_log,
# q,
# (n or 7),
# d,
# conversation_id,
# conversation_commands,
# location,
# partial(send_event, ChatEvent.STATUS),
# uploaded_image_url=uploaded_image_url,
# agent=agent,
# ):
# if isinstance(result, dict) and ChatEvent.STATUS in result:
# yield result[ChatEvent.STATUS]
# else:
# compiled_references.extend(result[0])
# inferred_queries.extend(result[1])
# defiltered_query = result[2]
# except Exception as e:
# error_message = f"Error searching knowledge base: {e}. Attempting to respond without document references."
# logger.warning(error_message)
# async for result in send_event(
# ChatEvent.STATUS, "Document search failed. I'll try respond without document references"
# ):
# yield result
#
# # if not is_none_or_empty(compiled_references):
# try:
# headings = "\n- " + "\n- ".join(set([c.get("compiled", c).split("\n")[0] for c in compiled_references]))
# # Strip only leading # from headings
# headings = headings.replace("#", "")
# async for result in send_event(ChatEvent.STATUS, f"**Found Relevant Notes**: {headings}"):
# yield result
# except Exception as e:
# # TODO Get correct type for compiled across research notes extraction
# logger.error(f"Error extracting references: {e}", exc_info=True)
# Gather Context
## Extract Document References
if pending_research:
try:
async for result in extract_references_and_questions(
request,
meta_log,
q,
(n or 7),
d,
conversation_id,
conversation_commands,
location,
partial(send_event, ChatEvent.STATUS),
query_images=uploaded_images,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
yield result[ChatEvent.STATUS]
else:
compiled_references.extend(result[0])
inferred_queries.extend(result[1])
defiltered_query = result[2]
except Exception as e:
error_message = (
f"Error searching knowledge base: {e}. Attempting to respond without document references."
)
logger.error(error_message, exc_info=True)
async for result in send_event(
ChatEvent.STATUS, "Document search failed. I'll try respond without document references"
):
yield result
if conversation_commands == [ConversationCommand.Notes] and not await EntryAdapters.auser_has_entries(user):
async for result in send_llm_response(f"{no_entries_found.format()}"):
yield result
return
if not is_none_or_empty(compiled_references):
headings = "\n- " + "\n- ".join(set([c.get("compiled", c).split("\n")[0] for c in compiled_references]))
# Strip only leading # from headings
headings = headings.replace("#", "")
async for result in send_event(ChatEvent.STATUS, f"**Found Relevant Notes**: {headings}"):
yield result
if conversation_commands == [ConversationCommand.Notes] and not await EntryAdapters.auser_has_entries(user):
async for result in send_llm_response(f"{no_entries_found.format()}"):
yield result
return
if ConversationCommand.Notes in conversation_commands and is_none_or_empty(compiled_references):
conversation_commands.remove(ConversationCommand.Notes)
## Gather Online References
if ConversationCommand.Online in conversation_commands and pending_research:
try:
async for result in search_online(
defiltered_query,
meta_log,
location,
user,
subscribed,
partial(send_event, ChatEvent.STATUS),
custom_filters,
uploaded_image_url=uploaded_image_url,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
yield result[ChatEvent.STATUS]
else:
online_results = result
except Exception as e:
error_message = f"Error searching online: {e}. Attempting to respond without online results"
logger.warning(error_message)
async for result in send_event(
ChatEvent.STATUS, "Online search failed. I'll try respond without online references"
):
yield result
if pending_research:
## Gather Online References
if ConversationCommand.Online in conversation_commands:
try:
async for result in search_online(
defiltered_query,
meta_log,
location,
user,
partial(send_event, ChatEvent.STATUS),
custom_filters,
query_images=uploaded_images,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
yield result[ChatEvent.STATUS]
else:
online_results = result
except Exception as e:
error_message = f"Error searching online: {e}. Attempting to respond without online results"
logger.warning(error_message)
async for result in send_event(
ChatEvent.STATUS, "Online search failed. I'll try respond without online references"
):
yield result
## Gather Webpage References
if ConversationCommand.Webpage in conversation_commands and pending_research:
try:
async for result in read_webpages(
defiltered_query,
meta_log,
location,
user,
partial(send_event, ChatEvent.STATUS),
uploaded_image_url=uploaded_image_url,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
yield result[ChatEvent.STATUS]
else:
direct_web_pages = result
webpages = []
for query in direct_web_pages:
if online_results.get(query):
online_results[query]["webpages"] = direct_web_pages[query]["webpages"]
else:
online_results[query] = {"webpages": direct_web_pages[query]["webpages"]}
if pending_research:
## Gather Webpage References
if ConversationCommand.Webpage in conversation_commands:
try:
async for result in read_webpages(
defiltered_query,
meta_log,
location,
user,
partial(send_event, ChatEvent.STATUS),
query_images=uploaded_images,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
yield result[ChatEvent.STATUS]
else:
direct_web_pages = result
webpages = []
for query in direct_web_pages:
if online_results.get(query):
online_results[query]["webpages"] = direct_web_pages[query]["webpages"]
else:
online_results[query] = {"webpages": direct_web_pages[query]["webpages"]}
for webpage in direct_web_pages[query]["webpages"]:
webpages.append(webpage["link"])
async for result in send_event(ChatEvent.STATUS, f"**Read web pages**: {webpages}"):
yield result
except Exception as e:
logger.warning(
f"Error reading webpages: {e}. Attempting to respond without webpage results",
exc_info=True,
)
async for result in send_event(
ChatEvent.STATUS, "Webpage read failed. I'll try respond without webpage references"
):
yield result
for webpage in direct_web_pages[query]["webpages"]:
webpages.append(webpage["link"])
async for result in send_event(ChatEvent.STATUS, f"**Read web pages**: {webpages}"):
yield result
except Exception as e:
logger.warning(
f"Error reading webpages: {e}. Attempting to respond without webpage results",
exc_info=True,
)
async for result in send_event(
ChatEvent.STATUS, "Webpage read failed. I'll try respond without webpage references"
):
yield result
## Gather Code Results
if ConversationCommand.Code in conversation_commands and pending_research:
try:
previous_iteration_history = (
f"# Iteration 1:\n#---\nNotes:\n{compiled_references}\n\nOnline Results:{online_results}"
)
async for result in run_code(
defiltered_query,
meta_log,
previous_iteration_history,
location,
user,
partial(send_event, ChatEvent.STATUS),
uploaded_image_url=uploaded_image_url,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
yield result[ChatEvent.STATUS]
else:
code_results = result
async for result in send_event(ChatEvent.STATUS, f"**Ran code snippets**: {len(code_results)}"):
yield result
except ValueError as e:
logger.warning(
f"Failed to use code tool: {e}. Attempting to respond without code results",
exc_info=True,
)
## Send Gathered References
async for result in send_event(
ChatEvent.REFERENCES,
{
"inferredQueries": inferred_queries,
"context": compiled_references,
"onlineContext": online_results,
},
):
yield result
## Send Gathered References
async for result in send_event(
ChatEvent.REFERENCES,
{
"inferredQueries": inferred_queries,
"context": compiled_references,
"onlineContext": online_results,
"codeContext": code_results,
},
):
yield result
if pending_research:
## Gather Code Results
if ConversationCommand.Code in conversation_commands and pending_research:
try:
previous_iteration_history = (
f"# Iteration 1:\n#---\nNotes:\n{compiled_references}\n\nOnline Results:{online_results}"
)
async for result in run_code(
defiltered_query,
meta_log,
previous_iteration_history,
location,
user,
partial(send_event, ChatEvent.STATUS),
query_images=uploaded_images,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
yield result[ChatEvent.STATUS]
else:
code_results = result
async for result in send_event(ChatEvent.STATUS, f"**Ran code snippets**: {len(code_results)}"):
yield result
except ValueError as e:
logger.warning(
f"Failed to use code tool: {e}. Attempting to respond without code results",
exc_info=True,
)
# Generate Output
## Generate Image Output
if ConversationCommand.Image in conversation_commands and pending_research:
if ConversationCommand.Image in conversation_commands:
async for result in text_to_image(
q,
defiltered_query,
user,
meta_log,
location_data=location,
references=compiled_references,
online_results=online_results,
send_status_func=partial(send_event, ChatEvent.STATUS),
uploaded_image_url=uploaded_image_url,
query_images=uploaded_images,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
yield result[ChatEvent.STATUS]
else:
image, status_code, improved_image_prompt, intent_type = result
generated_image, status_code, improved_image_prompt, intent_type = result
if image is None or status_code != 200:
if generated_image is None or status_code != 200:
content_obj = {
"content-type": "application/json",
"intentType": intent_type,
"detail": improved_image_prompt,
"image": image,
"image": None,
}
async for result in send_llm_response(json.dumps(content_obj)):
yield result
@ -1036,7 +1027,7 @@ async def chat(
await sync_to_async(save_to_conversation_log)(
q,
image,
generated_image,
user,
meta_log,
user_message_time,
@ -1046,22 +1037,73 @@ async def chat(
conversation_id=conversation_id,
compiled_references=compiled_references,
online_results=online_results,
uploaded_image_url=uploaded_image_url,
query_images=uploaded_images,
)
content_obj = {
"intentType": intent_type,
"inferredQueries": [improved_image_prompt],
"image": image,
"image": generated_image,
}
async for result in send_llm_response(json.dumps(content_obj)):
yield result
return
if ConversationCommand.Diagram in conversation_commands:
async for result in send_event(ChatEvent.STATUS, f"Creating diagram"):
yield result
intent_type = "excalidraw"
inferred_queries = []
diagram_description = ""
async for result in generate_excalidraw_diagram(
q=defiltered_query,
conversation_history=meta_log,
location_data=location,
note_references=compiled_references,
online_results=online_results,
query_images=uploaded_images,
user=user,
agent=agent,
send_status_func=partial(send_event, ChatEvent.STATUS),
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
yield result[ChatEvent.STATUS]
else:
better_diagram_description_prompt, excalidraw_diagram_description = result
inferred_queries.append(better_diagram_description_prompt)
diagram_description = excalidraw_diagram_description
content_obj = {
"intentType": intent_type,
"inferredQueries": inferred_queries,
"image": diagram_description,
}
await sync_to_async(save_to_conversation_log)(
q,
excalidraw_diagram_description,
user,
meta_log,
user_message_time,
intent_type="excalidraw",
inferred_queries=[better_diagram_description_prompt],
client_application=request.user.client_app,
conversation_id=conversation_id,
compiled_references=compiled_references,
online_results=online_results,
query_images=uploaded_images,
)
async for result in send_llm_response(json.dumps(content_obj)):
yield result
return
## Generate Text Output
async for result in send_event(ChatEvent.STATUS, f"**Generating a well-informed response**"):
yield result
llm_response, chat_metadata = await agenerate_chat_response(
q,
defiltered_query,
meta_log,
conversation,
compiled_references,
@ -1074,8 +1116,8 @@ async def chat(
conversation_id,
location,
user_name,
uploaded_image_url,
researched_results,
uploaded_images,
)
# Send Response
@ -1101,9 +1143,9 @@ async def chat(
## Stream Text Response
if stream:
return StreamingResponse(event_generator(q, image=image), media_type="text/plain")
return StreamingResponse(event_generator(q, images=raw_images), media_type="text/plain")
## Non-Streaming Text Response
else:
response_iterator = event_generator(q, image=image)
response_iterator = event_generator(q, images=raw_images)
response_data = await read_chat_stream(response_iterator)
return Response(content=json.dumps(response_data), media_type="application/json", status_code=200)

View file

@ -94,39 +94,6 @@ async def update_voice_model(
return Response(status_code=202, content=json.dumps({"status": "ok"}))
@api_model.post("/search", status_code=200)
@requires(["authenticated"])
async def update_search_model(
request: Request,
id: str,
client: Optional[str] = None,
):
user = request.user.object
prev_config = await adapters.aget_user_search_model(user)
new_config = await adapters.aset_user_search_model(user, int(id))
if prev_config and int(id) != prev_config.id and new_config:
await EntryAdapters.adelete_all_entries(user)
if not prev_config:
# If the use was just using the default config, delete all the entries and set the new config.
await EntryAdapters.adelete_all_entries(user)
if new_config is None:
return {"status": "error", "message": "Model not found"}
else:
update_telemetry_state(
request=request,
telemetry_type="api",
api="set_search_model",
client=client,
metadata={"search_model": new_config.setting.name},
)
return {"status": "ok"}
@api_model.post("/paint", status_code=200)
@requires(["authenticated"])
async def update_paint_model(

View file

@ -1,12 +1,14 @@
import json
import logging
import os
from datetime import datetime, timezone
from asgiref.sync import sync_to_async
from fastapi import APIRouter, Request
from fastapi import APIRouter, Request, Response
from starlette.authentication import requires
from khoj.database import adapters
from khoj.database.models import KhojUser, Subscription
from khoj.routers.helpers import update_telemetry_state
from khoj.utils import state
@ -73,7 +75,7 @@ async def subscribe(request: Request):
elif event_type in {"customer.subscription.deleted"}:
# Reset the user to trial state
user, is_new = await adapters.set_user_subscription(
customer_email, is_recurring=False, renewal_date=False, type="trial"
customer_email, is_recurring=False, renewal_date=False, type=Subscription.Type.TRIAL
)
success = user is not None
@ -82,7 +84,7 @@ async def subscribe(request: Request):
request=request,
telemetry_type="api",
api="create_user",
metadata={"user_id": str(user.user.uuid)},
metadata={"server_id": str(user.user.uuid)},
)
logger.log(logging.INFO, f"🥳 New User Created: {user.user.uuid}")
@ -116,3 +118,19 @@ async def update_subscription(request: Request, email: str, operation: str):
return {"success": False, "message": "No subscription found that is set to cancel"}
return {"success": False, "message": "Invalid operation"}
@subscription_router.post("/trial", response_class=Response)
@requires(["authenticated"])
async def start_trial(request: Request) -> Response:
user: KhojUser = request.user.object
# Start a trial for the user
updated_subscription = await adapters.astart_trial_subscription(user)
# Return trial status as a JSON response
return Response(
content=json.dumps({"trial_enabled": updated_subscription is not None}),
media_type="application/json",
status_code=200,
)

View file

@ -90,7 +90,7 @@ async def login_magic_link(request: Request, form: MagicLinkForm):
request=request,
telemetry_type="api",
api="create_user",
metadata={"user_id": str(user.uuid)},
metadata={"server_id": str(user.uuid)},
)
logger.log(logging.INFO, f"🥳 New User Created: {user.uuid}")
@ -175,7 +175,7 @@ async def auth(request: Request):
request=request,
telemetry_type="api",
api="create_user",
metadata={"user_id": str(khoj_user.uuid)},
metadata={"server_id": str(khoj_user.uuid)},
)
logger.log(logging.INFO, f"🥳 New User Created: {khoj_user.uuid}")
return RedirectResponse(url=next_url, status_code=HTTP_302_FOUND)

View file

@ -1,4 +1,5 @@
import asyncio
import base64
import hashlib
import json
import logging
@ -22,7 +23,7 @@ from typing import (
Tuple,
Union,
)
from urllib.parse import parse_qs, quote, urljoin, urlparse
from urllib.parse import parse_qs, quote, unquote, urljoin, urlparse
import cron_descriptor
import pytz
@ -31,16 +32,19 @@ from apscheduler.job import Job
from apscheduler.triggers.cron import CronTrigger
from asgiref.sync import sync_to_async
from fastapi import Depends, Header, HTTPException, Request, UploadFile
from pydantic import BaseModel
from starlette.authentication import has_required_scope
from starlette.requests import URL
from khoj.database import adapters
from khoj.database.adapters import (
LENGTH_OF_FREE_TRIAL,
AgentAdapters,
AutomationAdapters,
ConversationAdapters,
EntryAdapters,
FileObjectAdapters,
ais_user_subscribed,
create_khoj_token,
get_khoj_tokens,
get_user_name,
@ -210,6 +214,21 @@ def get_next_url(request: Request) -> str:
return urljoin(str(request.base_url).rstrip("/"), next_path)
def construct_chat_history(conversation_history: dict, n: int = 4, agent_name="AI") -> str:
chat_history = ""
for chat in conversation_history.get("chat", [])[-n:]:
if chat["by"] == "khoj" and chat["intent"].get("type") in ["remember", "reminder", "summarize"]:
chat_history += f"User: {chat['intent']['query']}\n"
chat_history += f"{agent_name}: {chat['message']}\n"
elif chat["by"] == "khoj" and ("text-to-image" in chat["intent"].get("type")):
chat_history += f"User: {chat['intent']['query']}\n"
chat_history += f"{agent_name}: [generated image redacted for space]\n"
elif chat["by"] == "khoj" and ("excalidraw" in chat["intent"].get("type")):
chat_history += f"User: {chat['intent']['query']}\n"
chat_history += f"{agent_name}: {chat['intent']['inferred-queries'][0]}\n"
return chat_history
def get_conversation_command(query: str, any_references: bool = False) -> ConversationCommand:
if query.startswith("/notes"):
return ConversationCommand.Notes
@ -227,6 +246,8 @@ def get_conversation_command(query: str, any_references: bool = False) -> Conver
return ConversationCommand.AutomatedTask
elif query.startswith("/summarize"):
return ConversationCommand.Summarize
elif query.startswith("/diagram"):
return ConversationCommand.Diagram
# If no relevant notes found for the given query
elif not any_references:
return ConversationCommand.General
@ -282,7 +303,7 @@ async def aget_relevant_information_sources(
conversation_history: dict,
is_task: bool,
user: KhojUser,
uploaded_image_url: str = None,
query_images: List[str] = None,
agent: Agent = None,
):
"""
@ -301,8 +322,8 @@ async def aget_relevant_information_sources(
chat_history = construct_chat_history(conversation_history)
if uploaded_image_url:
query = f"[placeholder for user attached image]\n{query}"
if query_images:
query = f"[placeholder for {len(query_images)} user attached images]\n{query}"
personality_context = (
prompts.personality_context.format(personality=agent.personality) if agent and agent.personality else ""
@ -359,7 +380,7 @@ async def aget_relevant_output_modes(
conversation_history: dict,
is_task: bool = False,
user: KhojUser = None,
uploaded_image_url: str = None,
query_images: List[str] = None,
agent: Agent = None,
):
"""
@ -381,8 +402,8 @@ async def aget_relevant_output_modes(
chat_history = construct_chat_history(conversation_history)
if uploaded_image_url:
query = f"[placeholder for user attached image]\n{query}"
if query_images:
query = f"[placeholder for {len(query_images)} user attached images]\n{query}"
personality_context = (
prompts.personality_context.format(personality=agent.personality) if agent and agent.personality else ""
@ -425,7 +446,7 @@ async def infer_webpage_urls(
conversation_history: dict,
location_data: LocationData,
user: KhojUser,
uploaded_image_url: str = None,
query_images: List[str] = None,
agent: Agent = None,
) -> List[str]:
"""
@ -451,7 +472,7 @@ async def infer_webpage_urls(
with timer("Chat actor: Infer webpage urls to read", logger):
response = await send_message_to_model_wrapper(
online_queries_prompt, uploaded_image_url=uploaded_image_url, response_type="json_object", user=user
online_queries_prompt, query_images=query_images, response_type="json_object", user=user
)
# Validate that the response is a non-empty, JSON-serializable list of URLs
@ -472,7 +493,7 @@ async def generate_online_subqueries(
conversation_history: dict,
location_data: LocationData,
user: KhojUser,
uploaded_image_url: str = None,
query_images: List[str] = None,
agent: Agent = None,
) -> List[str]:
"""
@ -498,7 +519,7 @@ async def generate_online_subqueries(
with timer("Chat actor: Generate online search subqueries", logger):
response = await send_message_to_model_wrapper(
online_queries_prompt, uploaded_image_url=uploaded_image_url, response_type="json_object", user=user
online_queries_prompt, query_images=query_images, response_type="json_object", user=user
)
# Validate that the response is a non-empty, JSON-serializable list
@ -517,7 +538,7 @@ async def generate_online_subqueries(
async def schedule_query(
q: str, conversation_history: dict, user: KhojUser, uploaded_image_url: str = None
q: str, conversation_history: dict, user: KhojUser, query_images: List[str] = None
) -> Tuple[str, ...]:
"""
Schedule the date, time to run the query. Assume the server timezone is UTC.
@ -530,7 +551,7 @@ async def schedule_query(
)
raw_response = await send_message_to_model_wrapper(
crontime_prompt, uploaded_image_url=uploaded_image_url, response_type="json_object", user=user
crontime_prompt, query_images=query_images, response_type="json_object", user=user
)
# Validate that the response is a non-empty, JSON-serializable list
@ -544,12 +565,14 @@ async def schedule_query(
raise AssertionError(f"Invalid response for scheduling query: {raw_response}")
async def extract_relevant_info(q: str, corpus: str, user: KhojUser = None, agent: Agent = None) -> Union[str, None]:
async def extract_relevant_info(
qs: set[str], corpus: str, user: KhojUser = None, agent: Agent = None
) -> Union[str, None]:
"""
Extract relevant information for a given query from the target corpus
"""
if is_none_or_empty(corpus) or is_none_or_empty(q):
if is_none_or_empty(corpus) or is_none_or_empty(qs):
return None
personality_context = (
@ -557,17 +580,16 @@ async def extract_relevant_info(q: str, corpus: str, user: KhojUser = None, agen
)
extract_relevant_information = prompts.extract_relevant_information.format(
query=q,
query=", ".join(qs),
corpus=corpus.strip(),
personality_context=personality_context,
)
with timer("Chat actor: Extract relevant information from data", logger):
response = await send_message_to_model_wrapper(
extract_relevant_information,
prompts.system_prompt_extract_relevant_information,
user=user,
)
response = await send_message_to_model_wrapper(
extract_relevant_information,
prompts.system_prompt_extract_relevant_information,
user=user,
)
return response.strip()
@ -575,7 +597,7 @@ async def extract_relevant_summary(
q: str,
corpus: str,
conversation_history: dict,
uploaded_image_url: str = None,
query_images: List[str] = None,
user: KhojUser = None,
agent: Agent = None,
) -> Union[str, None]:
@ -604,7 +626,7 @@ async def extract_relevant_summary(
extract_relevant_information,
prompts.system_prompt_extract_relevant_summary,
user=user,
uploaded_image_url=uploaded_image_url,
query_images=query_images,
)
return response.strip()
@ -614,8 +636,7 @@ async def generate_summary_from_files(
user: KhojUser,
file_filters: List[str],
meta_log: dict,
subscribed: bool,
uploaded_image_url: str = None,
query_images: List[str] = None,
agent: Agent = None,
send_status_func: Optional[Callable] = None,
send_response_func: Optional[Callable] = None,
@ -647,7 +668,7 @@ async def generate_summary_from_files(
q,
contextual_data,
conversation_history=meta_log,
uploaded_image_url=uploaded_image_url,
query_images=query_images,
user=user,
agent=agent,
)
@ -661,6 +682,129 @@ async def generate_summary_from_files(
yield result
async def generate_excalidraw_diagram(
q: str,
conversation_history: Dict[str, Any],
location_data: LocationData,
note_references: List[Dict[str, Any]],
online_results: Optional[dict] = None,
query_images: List[str] = None,
user: KhojUser = None,
agent: Agent = None,
send_status_func: Optional[Callable] = None,
):
if send_status_func:
async for event in send_status_func("**Enhancing the Diagramming Prompt**"):
yield {ChatEvent.STATUS: event}
better_diagram_description_prompt = await generate_better_diagram_description(
q=q,
conversation_history=conversation_history,
location_data=location_data,
note_references=note_references,
online_results=online_results,
query_images=query_images,
user=user,
agent=agent,
)
if send_status_func:
async for event in send_status_func(f"**Diagram to Create:**:\n{better_diagram_description_prompt}"):
yield {ChatEvent.STATUS: event}
excalidraw_diagram_description = await generate_excalidraw_diagram_from_description(
q=better_diagram_description_prompt,
user=user,
agent=agent,
)
yield better_diagram_description_prompt, excalidraw_diagram_description
async def generate_better_diagram_description(
q: str,
conversation_history: Dict[str, Any],
location_data: LocationData,
note_references: List[Dict[str, Any]],
online_results: Optional[dict] = None,
query_images: List[str] = None,
user: KhojUser = None,
agent: Agent = None,
) -> str:
"""
Generate a diagram description from the given query and context
"""
today_date = datetime.now(tz=timezone.utc).strftime("%Y-%m-%d, %A")
personality_context = (
prompts.personality_context.format(personality=agent.personality) if agent and agent.personality else ""
)
if location_data:
location_prompt = prompts.user_location.format(location=f"{location_data}")
else:
location_prompt = "Unknown"
user_references = "\n\n".join([f"# {item['compiled']}" for item in note_references])
chat_history = construct_chat_history(conversation_history)
simplified_online_results = {}
if online_results:
for result in online_results:
if online_results[result].get("answerBox"):
simplified_online_results[result] = online_results[result]["answerBox"]
elif online_results[result].get("webpages"):
simplified_online_results[result] = online_results[result]["webpages"]
improve_diagram_description_prompt = prompts.improve_diagram_description_prompt.format(
query=q,
chat_history=chat_history,
location=location_prompt,
current_date=today_date,
references=user_references,
online_results=simplified_online_results,
personality_context=personality_context,
)
with timer("Chat actor: Generate better diagram description", logger):
response = await send_message_to_model_wrapper(
improve_diagram_description_prompt, query_images=query_images, user=user
)
response = response.strip()
if response.startswith(('"', "'")) and response.endswith(('"', "'")):
response = response[1:-1]
return response
async def generate_excalidraw_diagram_from_description(
q: str,
user: KhojUser = None,
agent: Agent = None,
) -> str:
personality_context = (
prompts.personality_context.format(personality=agent.personality) if agent and agent.personality else ""
)
excalidraw_diagram_generation = prompts.excalidraw_diagram_generation_prompt.format(
personality_context=personality_context,
query=q,
)
with timer("Chat actor: Generate excalidraw diagram", logger):
raw_response = await send_message_to_model_wrapper(message=excalidraw_diagram_generation, user=user)
raw_response = raw_response.strip()
raw_response = remove_json_codeblock(raw_response)
response: Dict[str, str] = json.loads(raw_response)
if not response or not isinstance(response, List) or not isinstance(response[0], Dict):
# TODO Some additional validation here that it's a valid Excalidraw diagram
raise AssertionError(f"Invalid response for improving diagram description: {response}")
return response
async def generate_better_image_prompt(
q: str,
conversation_history: str,
@ -668,7 +812,7 @@ async def generate_better_image_prompt(
note_references: List[Dict[str, Any]],
online_results: Optional[dict] = None,
model_type: Optional[str] = None,
uploaded_image_url: Optional[str] = None,
query_images: Optional[List[str]] = None,
user: KhojUser = None,
agent: Agent = None,
) -> str:
@ -720,7 +864,7 @@ async def generate_better_image_prompt(
)
with timer("Chat actor: Generate contextual image prompt", logger):
response = await send_message_to_model_wrapper(image_prompt, uploaded_image_url=uploaded_image_url, user=user)
response = await send_message_to_model_wrapper(image_prompt, query_images=query_images, user=user)
response = response.strip()
if response.startswith(('"', "'")) and response.endswith(('"', "'")):
response = response[1:-1]
@ -728,6 +872,117 @@ async def generate_better_image_prompt(
return response
async def send_message_to_model_wrapper(
message: str,
system_message: str = "",
response_type: str = "text",
user: KhojUser = None,
query_images: List[str] = None,
):
conversation_config: ChatModelOptions = await ConversationAdapters.aget_default_conversation_config(user)
vision_available = conversation_config.vision_enabled
if not vision_available and query_images:
vision_enabled_config = await ConversationAdapters.aget_vision_enabled_config()
if vision_enabled_config:
conversation_config = vision_enabled_config
vision_available = True
subscribed = await ais_user_subscribed(user)
chat_model = conversation_config.chat_model
max_tokens = (
conversation_config.subscribed_max_prompt_size
if subscribed and conversation_config.subscribed_max_prompt_size
else conversation_config.max_prompt_size
)
tokenizer = conversation_config.tokenizer
model_type = conversation_config.model_type
vision_available = conversation_config.vision_enabled
if model_type == ChatModelOptions.ModelType.OFFLINE:
if state.offline_chat_processor_config is None or state.offline_chat_processor_config.loaded_model is None:
state.offline_chat_processor_config = OfflineChatProcessorModel(chat_model, max_tokens)
loaded_model = state.offline_chat_processor_config.loaded_model
truncated_messages = generate_chatml_messages_with_context(
user_message=message,
system_message=system_message,
model_name=chat_model,
loaded_model=loaded_model,
tokenizer_name=tokenizer,
max_prompt_size=max_tokens,
vision_enabled=vision_available,
model_type=conversation_config.model_type,
)
return send_message_to_model_offline(
messages=truncated_messages,
loaded_model=loaded_model,
model=chat_model,
max_prompt_size=max_tokens,
streaming=False,
response_type=response_type,
)
elif model_type == ChatModelOptions.ModelType.OPENAI:
openai_chat_config = conversation_config.openai_config
api_key = openai_chat_config.api_key
api_base_url = openai_chat_config.api_base_url
truncated_messages = generate_chatml_messages_with_context(
user_message=message,
system_message=system_message,
model_name=chat_model,
max_prompt_size=max_tokens,
tokenizer_name=tokenizer,
vision_enabled=vision_available,
query_images=query_images,
model_type=conversation_config.model_type,
)
return send_message_to_model(
messages=truncated_messages,
api_key=api_key,
model=chat_model,
response_type=response_type,
api_base_url=api_base_url,
)
elif model_type == ChatModelOptions.ModelType.ANTHROPIC:
api_key = conversation_config.openai_config.api_key
truncated_messages = generate_chatml_messages_with_context(
user_message=message,
system_message=system_message,
model_name=chat_model,
max_prompt_size=max_tokens,
tokenizer_name=tokenizer,
vision_enabled=vision_available,
query_images=query_images,
model_type=conversation_config.model_type,
)
return anthropic_send_message_to_model(
messages=truncated_messages,
api_key=api_key,
model=chat_model,
)
elif model_type == ChatModelOptions.ModelType.GOOGLE:
api_key = conversation_config.openai_config.api_key
truncated_messages = generate_chatml_messages_with_context(
user_message=message,
system_message=system_message,
model_name=chat_model,
max_prompt_size=max_tokens,
tokenizer_name=tokenizer,
vision_enabled=vision_available,
query_images=query_images,
model_type=conversation_config.model_type,
)
return gemini_send_message_to_model(
messages=truncated_messages, api_key=api_key, model=chat_model, response_type=response_type
)
else:
raise HTTPException(status_code=500, detail="Invalid conversation config")
def send_message_to_model_wrapper_sync(
message: str,
system_message: str = "",
@ -809,12 +1064,14 @@ def send_message_to_model_wrapper_sync(
model_name=chat_model,
max_prompt_size=max_tokens,
vision_enabled=vision_available,
model_type=conversation_config.model_type,
)
return gemini_send_message_to_model(
messages=truncated_messages,
api_key=api_key,
model=chat_model,
response_type=response_type,
)
else:
raise HTTPException(status_code=500, detail="Invalid conversation config")
@ -834,8 +1091,8 @@ def generate_chat_response(
conversation_id: str = None,
location_data: LocationData = None,
user_name: Optional[str] = None,
uploaded_image_url: Optional[str] = None,
meta_research: str = "",
query_images: Optional[List[str]] = None,
) -> Tuple[Union[ThreadedGenerator, Iterator[str]], Dict[str, str]]:
# Initialize Variables
chat_response = None
@ -858,12 +1115,12 @@ def generate_chat_response(
inferred_queries=inferred_queries,
client_application=client_application,
conversation_id=conversation_id,
uploaded_image_url=uploaded_image_url,
query_images=query_images,
)
conversation_config = ConversationAdapters.get_valid_conversation_config(user, conversation)
vision_available = conversation_config.vision_enabled
if not vision_available and uploaded_image_url:
if not vision_available and query_images:
vision_enabled_config = ConversationAdapters.get_vision_enabled_config()
if vision_enabled_config:
conversation_config = vision_enabled_config
@ -894,7 +1151,8 @@ def generate_chat_response(
chat_response = converse(
compiled_references,
query_to_run,
image_url=uploaded_image_url,
q,
query_images=query_images,
online_results=online_results,
code_results=code_results,
conversation_log=meta_log,
@ -937,6 +1195,10 @@ def generate_chat_response(
online_results,
code_results,
meta_log,
q,
query_images=query_images,
online_results=online_results,
conversation_log=meta_log,
model=conversation_config.chat_model,
api_key=api_key,
completion_func=partial_completion,
@ -946,6 +1208,7 @@ def generate_chat_response(
location_data=location_data,
user_name=user_name,
agent=agent,
vision_available=vision_available,
)
metadata.update({"chat_model": conversation_config.chat_model})
@ -957,6 +1220,22 @@ def generate_chat_response(
return chat_response, metadata
class ChatRequestBody(BaseModel):
q: str
n: Optional[int] = 7
d: Optional[float] = None
stream: Optional[bool] = False
title: Optional[str] = None
conversation_id: Optional[str] = None
city: Optional[str] = None
region: Optional[str] = None
country: Optional[str] = None
country_code: Optional[str] = None
timezone: Optional[str] = None
images: Optional[list[str]] = None
create_new: Optional[bool] = False
class ApiUserRateLimiter:
def __init__(self, requests: int, subscribed_requests: int, window: int, slug: str):
self.requests = requests
@ -1002,13 +1281,58 @@ class ApiUserRateLimiter:
)
raise HTTPException(
status_code=429,
detail="We're glad you're enjoying Khoj! You've exceeded your usage limit for today. Come back tomorrow or subscribe to increase your usage limit via [your settings](https://app.khoj.dev/settings).",
detail="I'm glad you're enjoying interacting with me! But you've exceeded your usage limit for today. Come back tomorrow or subscribe to increase your usage limit via [your settings](https://app.khoj.dev/settings).",
)
# Add the current request to the cache
UserRequests.objects.create(user=user, slug=self.slug)
class ApiImageRateLimiter:
def __init__(self, max_images: int = 10, max_combined_size_mb: float = 10):
self.max_images = max_images
self.max_combined_size_mb = max_combined_size_mb
def __call__(self, request: Request, body: ChatRequestBody):
if state.billing_enabled is False:
return
# Rate limiting is disabled if user unauthenticated.
# Other systems handle authentication
if not request.user.is_authenticated:
return
if not body.images:
return
# Check number of images
if len(body.images) > self.max_images:
raise HTTPException(
status_code=429,
detail=f"Those are way too many images for me! I can handle up to {self.max_images} images per message.",
)
# Check total size of images
total_size_mb = 0.0
for image in body.images:
# Unquote the image in case it's URL encoded
image = unquote(image)
# Assuming the image is a base64 encoded string
# Remove the data:image/jpeg;base64, part if present
if "," in image:
image = image.split(",", 1)[1]
# Decode base64 to get the actual size
image_bytes = base64.b64decode(image)
total_size_mb += len(image_bytes) / (1024 * 1024) # Convert bytes to MB
if total_size_mb > self.max_combined_size_mb:
raise HTTPException(
status_code=429,
detail=f"Those images are way too large for me! I can handle up to {self.max_combined_size_mb}MB of images per message.",
)
class ConversationCommandRateLimiter:
def __init__(self, trial_rate_limit: int, subscribed_rate_limit: int, slug: str):
self.slug = slug
@ -1411,10 +1735,16 @@ def get_user_config(user: KhojUser, request: Request, is_detailed: bool = False)
user_subscription_state = get_user_subscription_state(user.email)
user_subscription = adapters.get_user_subscription(user.email)
subscription_renewal_date = (
user_subscription.renewal_date.strftime("%d %b %Y")
if user_subscription and user_subscription.renewal_date
else (user_subscription.created_at + timedelta(days=7)).strftime("%d %b %Y")
else None
)
subscription_enabled_trial_at = (
user_subscription.enabled_trial_at.strftime("%d %b %Y")
if user_subscription and user_subscription.enabled_trial_at
else None
)
given_name = get_user_name(user)
@ -1437,13 +1767,6 @@ def get_user_config(user: KhojUser, request: Request, is_detailed: bool = False)
for chat_model in chat_models:
chat_model_options.append({"name": chat_model.chat_model, "id": chat_model.id})
search_model_options = adapters.get_or_create_search_models().all()
all_search_model_options = list()
for search_model_option in search_model_options:
all_search_model_options.append({"name": search_model_option.name, "id": search_model_option.id})
current_search_model_option = adapters.get_user_search_model_or_default(user)
selected_paint_model_config = ConversationAdapters.get_user_text_to_image_model_config(user)
paint_model_options = ConversationAdapters.get_text_to_image_model_options().all()
all_paint_model_options = list()
@ -1476,8 +1799,6 @@ def get_user_config(user: KhojUser, request: Request, is_detailed: bool = False)
"has_documents": has_documents,
"notion_token": notion_token,
# user model settings
"search_model_options": all_search_model_options,
"selected_search_model_config": current_search_model_option.id,
"chat_model_options": chat_model_options,
"selected_chat_model_config": selected_chat_model_config.id if selected_chat_model_config else None,
"paint_model_options": all_paint_model_options,
@ -1487,6 +1808,7 @@ def get_user_config(user: KhojUser, request: Request, is_detailed: bool = False)
# user billing info
"subscription_state": user_subscription_state,
"subscription_renewal_date": subscription_renewal_date,
"subscription_enabled_trial_at": subscription_enabled_trial_at,
# server settings
"khoj_cloud_subscription_url": os.getenv("KHOJ_CLOUD_SUBSCRIPTION_URL"),
"billing_enabled": state.billing_enabled,
@ -1495,6 +1817,7 @@ def get_user_config(user: KhojUser, request: Request, is_detailed: bool = False)
"khoj_version": state.khoj_version,
"anonymous_mode": state.anonymous_mode,
"notion_oauth_url": notion_oauth_url,
"length_of_free_trial": LENGTH_OF_FREE_TRIAL,
}

View file

@ -38,7 +38,7 @@ async def apick_next_tool(
query: str,
conversation_history: dict,
user: KhojUser = None,
uploaded_image_url: str = None,
query_images: List[str] = [],
location: LocationData = None,
user_name: str = None,
agent: Agent = None,
@ -62,8 +62,8 @@ async def apick_next_tool(
chat_history = construct_chat_history(conversation_history, agent_name=agent.name if agent else "Khoj")
if uploaded_image_url:
query = f"[placeholder for user attached image]\n{query}"
if query_images:
query = f"[placeholder for user attached images]\n{query}"
personality_context = (
prompts.personality_context.format(personality=agent.personality) if agent and agent.personality else ""
@ -131,8 +131,7 @@ async def execute_information_collection(
query: str,
conversation_id: str,
conversation_history: dict,
subscribed: bool,
uploaded_image_url: str = None,
query_images: List[str],
agent: Agent = None,
send_status_func: Optional[Callable] = None,
user_name: str = None,
@ -154,7 +153,7 @@ async def execute_information_collection(
query,
conversation_history,
user,
uploaded_image_url,
query_images,
location,
user_name,
agent,
@ -180,7 +179,7 @@ async def execute_information_collection(
[ConversationCommand.Default],
location,
send_status_func,
uploaded_image_url=uploaded_image_url,
query_images,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
@ -208,11 +207,10 @@ async def execute_information_collection(
conversation_history,
location,
user,
subscribed,
send_status_func,
[],
max_webpages_to_read=0,
uploaded_image_url=uploaded_image_url,
query_images=query_images,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
@ -229,7 +227,7 @@ async def execute_information_collection(
location,
user,
send_status_func,
uploaded_image_url=uploaded_image_url,
query_images=query_images,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:
@ -259,7 +257,7 @@ async def execute_information_collection(
location,
user,
send_status_func,
uploaded_image_url=uploaded_image_url,
query_images=query_images,
agent=agent,
):
if isinstance(result, dict) and ChatEvent.STATUS in result:

View file

@ -51,17 +51,6 @@ def chat_page(request: Request):
)
@web_client.get("/experimental", response_class=FileResponse)
@requires(["authenticated"], redirect="login_page")
def experimental_page(request: Request):
return templates.TemplateResponse(
"index.html",
context={
"request": request,
},
)
@web_client.get("/factchecker", response_class=FileResponse)
def fact_checker_page(request: Request):
return templates.TemplateResponse(

View file

@ -8,7 +8,11 @@ import torch
from asgiref.sync import sync_to_async
from sentence_transformers import util
from khoj.database.adapters import EntryAdapters, get_user_search_model_or_default
from khoj.database.adapters import (
EntryAdapters,
get_default_search_model,
get_user_default_search_model,
)
from khoj.database.models import Agent
from khoj.database.models import Entry as DbEntry
from khoj.database.models import KhojUser
@ -110,7 +114,7 @@ async def query(
file_type = search_type_to_embeddings_type[type.value]
query = raw_query
search_model = await sync_to_async(get_user_search_model_or_default)(user)
search_model = await sync_to_async(get_user_default_search_model)(user)
if not max_distance:
if search_model.bi_encoder_confidence_threshold:
max_distance = search_model.bi_encoder_confidence_threshold

View file

@ -2,10 +2,12 @@ from __future__ import annotations # to avoid quoting type hints
import datetime
import io
import ipaddress
import logging
import os
import platform
import random
import urllib.parse
import uuid
from collections import OrderedDict
from enum import Enum
@ -125,6 +127,8 @@ def get_file_type(file_type: str, file_content: bytes) -> tuple[str, str]:
return "image", encoding
elif file_type in ["image/png"]:
return "image", encoding
elif file_type in ["image/webp"]:
return "image", encoding
elif content_group in ["code", "text"]:
return "plaintext", encoding
else:
@ -164,9 +168,9 @@ def get_class_by_name(name: str) -> object:
class timer:
"""Context manager to log time taken for a block of code to run"""
def __init__(self, message: str, logger: logging.Logger, device: torch.device = None):
def __init__(self, message: str, logger: logging.Logger, device: torch.device = None, log_level=logging.DEBUG):
self.message = message
self.logger = logger
self.logger = logger.debug if log_level == logging.DEBUG else logger.info
self.device = device
def __enter__(self):
@ -176,9 +180,9 @@ class timer:
def __exit__(self, *_):
elapsed = perf_counter() - self.start
if self.device is None:
self.logger.debug(f"{self.message}: {elapsed:.3f} seconds")
self.logger(f"{self.message}: {elapsed:.3f} seconds")
else:
self.logger.debug(f"{self.message}: {elapsed:.3f} seconds on device: {self.device}")
self.logger(f"{self.message}: {elapsed:.3f} seconds on device: {self.device}")
class LRU(OrderedDict):
@ -315,6 +319,7 @@ class ConversationCommand(str, Enum):
Automation = "automation"
AutomatedTask = "automated_task"
Summarize = "summarize"
Diagram = "diagram"
command_descriptions = {
@ -324,10 +329,11 @@ command_descriptions = {
ConversationCommand.Online: "Search for information on the internet.",
ConversationCommand.Webpage: "Get information from webpage suggested by you.",
ConversationCommand.Code: "Run Python code to parse information, run complex calculations, create documents and charts.",
ConversationCommand.Image: "Generate images by describing your imagination in words.",
ConversationCommand.Image: "Generate illustrative, creative images by describing your imagination in words.",
ConversationCommand.Automation: "Automatically run your query at a specified time or interval.",
ConversationCommand.Help: "Get help with how to use or setup Khoj from the documentation",
ConversationCommand.Summarize: "Get help with a question pertaining to an entire document.",
ConversationCommand.Diagram: "Draw a flowchart, diagram, or any other visual representation best expressed with primitives like lines, rectangles, and text.",
}
command_descriptions_for_agent = {
@ -359,11 +365,16 @@ mode_descriptions_for_llm = {
ConversationCommand.Image: "Use this if the user is requesting you to generate images based on their description. This does not support generating charts or graphs.",
ConversationCommand.Automation: "Use this if the user is requesting a response at a scheduled date or time.",
ConversationCommand.Text: "Use this if the other response modes don't seem to fit the query.",
ConversationCommand.Automation: "Use this if you are confident the user is requesting a response at a scheduled date, time and frequency",
ConversationCommand.Text: "Use this if a normal text response would be sufficient for accurately responding to the query.",
ConversationCommand.Diagram: "Use this if the user is requesting a visual representation that requires primitives like lines, rectangles, and text.",
}
mode_descriptions_for_agent = {
ConversationCommand.Image: "Agent can generate images in response. It cannot not use this to generate charts and graphs.",
ConversationCommand.Automation: "Agent can schedule a task to run at a scheduled date, time and frequency in response.",
ConversationCommand.Text: "Agent can generate text in response.",
ConversationCommand.Diagram: "Agent can generate a visual representation that requires primitives like lines, rectangles, and text.",
}
@ -445,6 +456,46 @@ def is_internet_connected():
return False
def is_internal_url(url: str) -> bool:
"""
Check if a URL is likely to be internal/non-public.
Args:
url (str): The URL to check.
Returns:
bool: True if the URL is likely internal, False otherwise.
"""
try:
parsed_url = urllib.parse.urlparse(url)
hostname = parsed_url.hostname
# Check for localhost
if hostname in ["localhost", "127.0.0.1", "::1"]:
return True
# Check for IP addresses in private ranges
try:
ip = ipaddress.ip_address(hostname)
return ip.is_private
except ValueError:
pass # Not an IP address, continue with other checks
# Check for common internal TLDs
internal_tlds = [".local", ".internal", ".private", ".corp", ".home", ".lan"]
if any(hostname.endswith(tld) for tld in internal_tlds):
return True
# Check for URLs without a TLD
if "." not in hostname:
return True
return False
except Exception:
# If we can't parse the URL or something else goes wrong, assume it's not internal
return False
def convert_image_to_webp(image_bytes):
"""Convert image bytes to webp format for faster loading"""
image_io = io.BytesIO(image_bytes)

View file

@ -178,6 +178,13 @@ def api_user4(default_user4):
)
@pytest.mark.django_db
@pytest.fixture
def default_openai_chat_model_option():
chat_model = ChatModelOptionsFactory(chat_model="gpt-4o-mini", model_type="openai")
return chat_model
@pytest.mark.django_db
@pytest.fixture
def offline_agent():

View file

@ -86,7 +86,7 @@ class SubscriptionFactory(factory.django.DjangoModelFactory):
model = Subscription
user = factory.SubFactory(UserFactory)
type = "standard"
type = Subscription.Type.STANDARD
is_recurring = False
renewal_date = make_aware(datetime.strptime("2100-04-01", "%Y-%m-%d"))

211
tests/test_agents.py Normal file
View file

@ -0,0 +1,211 @@
# tests/test_agents.py
import os
import pytest
from asgiref.sync import sync_to_async
from khoj.database.adapters import AgentAdapters
from khoj.database.models import Agent, ChatModelOptions, Entry, KhojUser
from khoj.routers.api import execute_search
from khoj.utils.helpers import get_absolute_path
from tests.helpers import ChatModelOptionsFactory
def test_create_default_agent(default_user: KhojUser):
ChatModelOptionsFactory()
agent = AgentAdapters.create_default_agent(default_user)
assert agent is not None
assert agent.input_tools == []
assert agent.output_modes == []
assert agent.privacy_level == Agent.PrivacyLevel.PUBLIC
assert agent.managed_by_admin == True
@pytest.mark.anyio
@pytest.mark.django_db(transaction=True)
async def test_create_or_update_agent(default_user: KhojUser, default_openai_chat_model_option: ChatModelOptions):
new_agent = await AgentAdapters.aupdate_agent(
default_user,
"Test Agent",
"Test Personality",
Agent.PrivacyLevel.PRIVATE,
"icon",
"color",
default_openai_chat_model_option.chat_model,
[],
[],
[],
)
assert new_agent is not None
assert new_agent.name == "Test Agent"
assert new_agent.privacy_level == Agent.PrivacyLevel.PRIVATE
assert new_agent.creator == default_user
@pytest.mark.anyio
@pytest.mark.django_db(transaction=True)
async def test_create_or_update_agent_with_knowledge_base(
default_user2: KhojUser, default_openai_chat_model_option: ChatModelOptions, chat_client
):
full_filename = get_absolute_path("tests/data/markdown/having_kids.markdown")
new_agent = await AgentAdapters.aupdate_agent(
default_user2,
"Test Agent",
"Test Personality",
Agent.PrivacyLevel.PRIVATE,
"icon",
"color",
default_openai_chat_model_option.chat_model,
[full_filename],
[],
[],
)
entries = await sync_to_async(list)(Entry.objects.filter(agent=new_agent))
file_names = set()
for entry in entries:
file_names.add(entry.file_path)
assert new_agent is not None
assert new_agent.name == "Test Agent"
assert new_agent.privacy_level == Agent.PrivacyLevel.PRIVATE
assert new_agent.creator == default_user2
assert len(entries) > 0
assert full_filename in file_names
assert len(file_names) == 1
@pytest.mark.anyio
@pytest.mark.django_db(transaction=True)
async def test_create_or_update_agent_with_knowledge_base_and_search(
default_user2: KhojUser, default_openai_chat_model_option: ChatModelOptions, chat_client
):
full_filename = get_absolute_path("tests/data/markdown/having_kids.markdown")
new_agent = await AgentAdapters.aupdate_agent(
default_user2,
"Test Agent",
"Test Personality",
Agent.PrivacyLevel.PRIVATE,
"icon",
"color",
default_openai_chat_model_option.chat_model,
[full_filename],
[],
[],
)
search_result = await execute_search(user=default_user2, q="having kids", agent=new_agent)
assert len(search_result) == 5
@pytest.mark.anyio
@pytest.mark.django_db(transaction=True)
async def test_agent_with_knowledge_base_and_search_not_creator(
default_user2: KhojUser, default_openai_chat_model_option: ChatModelOptions, chat_client, default_user3: KhojUser
):
full_filename = get_absolute_path("tests/data/markdown/having_kids.markdown")
new_agent = await AgentAdapters.aupdate_agent(
default_user2,
"Test Agent",
"Test Personality",
Agent.PrivacyLevel.PUBLIC,
"icon",
"color",
default_openai_chat_model_option.chat_model,
[full_filename],
[],
[],
)
search_result = await execute_search(user=default_user3, q="having kids", agent=new_agent)
assert len(search_result) == 5
@pytest.mark.anyio
@pytest.mark.django_db(transaction=True)
async def test_agent_with_knowledge_base_and_search_not_creator_and_private(
default_user2: KhojUser, default_openai_chat_model_option: ChatModelOptions, chat_client, default_user3: KhojUser
):
full_filename = get_absolute_path("tests/data/markdown/having_kids.markdown")
new_agent = await AgentAdapters.aupdate_agent(
default_user2,
"Test Agent",
"Test Personality",
Agent.PrivacyLevel.PRIVATE,
"icon",
"color",
default_openai_chat_model_option.chat_model,
[full_filename],
[],
[],
)
search_result = await execute_search(user=default_user3, q="having kids", agent=new_agent)
assert len(search_result) == 0
@pytest.mark.anyio
@pytest.mark.django_db(transaction=True)
async def test_agent_with_knowledge_base_and_search_not_creator_and_private_accessible_to_none(
default_user2: KhojUser, default_openai_chat_model_option: ChatModelOptions, chat_client
):
full_filename = get_absolute_path("tests/data/markdown/having_kids.markdown")
new_agent = await AgentAdapters.aupdate_agent(
default_user2,
"Test Agent",
"Test Personality",
Agent.PrivacyLevel.PRIVATE,
"icon",
"color",
default_openai_chat_model_option.chat_model,
[full_filename],
[],
[],
)
search_result = await execute_search(user=None, q="having kids", agent=new_agent)
assert len(search_result) == 5
@pytest.mark.anyio
@pytest.mark.django_db(transaction=True)
async def test_multiple_agents_with_knowledge_base_and_users(
default_user2: KhojUser, default_openai_chat_model_option: ChatModelOptions, chat_client, default_user3: KhojUser
):
full_filename = get_absolute_path("tests/data/markdown/having_kids.markdown")
new_agent = await AgentAdapters.aupdate_agent(
default_user2,
"Test Agent",
"Test Personality",
Agent.PrivacyLevel.PUBLIC,
"icon",
"color",
default_openai_chat_model_option.chat_model,
[full_filename],
[],
[],
)
full_filename2 = get_absolute_path("tests/data/markdown/Namita.markdown")
new_agent2 = await AgentAdapters.aupdate_agent(
default_user2,
"Test Agent 2",
"Test Personality",
Agent.PrivacyLevel.PUBLIC,
"icon",
"color",
default_openai_chat_model_option.chat_model,
[full_filename2],
[],
[],
)
search_result = await execute_search(user=default_user3, q="having kids", agent=new_agent2)
search_result2 = await execute_search(user=default_user3, q="Namita", agent=new_agent2)
assert len(search_result) == 0
assert len(search_result2) == 1

View file

@ -1,6 +1,8 @@
import os
import re
import pytest
from khoj.processor.content.pdf.pdf_to_entries import PdfToEntries
from khoj.utils.fs_syncer import get_pdf_files
from khoj.utils.rawconfig import TextContentConfig
@ -37,6 +39,7 @@ def test_multi_page_pdf_to_jsonl():
assert len(entries[1]) == 6
@pytest.mark.skip(reason="Temporarily disabled OCR due to performance issues")
def test_ocr_page_pdf_to_jsonl():
"Convert multiple pages from single PDF file to jsonl."
# Arrange

View file

@ -77,5 +77,10 @@
"1.23.3": "0.15.0",
"1.24.0": "0.15.0",
"1.24.1": "0.15.0",
"1.25.0": "0.15.0"
"1.25.0": "0.15.0",
"1.26.0": "0.15.0",
"1.26.1": "0.15.0",
"1.26.2": "0.15.0",
"1.26.3": "0.15.0",
"1.26.4": "0.15.0"
}