From b990d3394cba71292ddbb1126aa3870e13a063e3 Mon Sep 17 00:00:00 2001 From: Alexis Deprez Date: Fri, 27 Sep 2024 11:19:59 +0200 Subject: [PATCH] chore: remove unused components --- extension_chrome/.eslintignore | 2 - extension_chrome/.eslintrc.js | 33 - extension_chrome/.prettierignore | 2 - extension_chrome/.prettierrc | 22 - extension_chrome/README.md | 108 - extension_chrome/jsconfig.json | 1 - extension_chrome/package-lock.json | 14774 ---------------- extension_chrome/package.json | 70 - extension_chrome/public/content.html | 11 - extension_chrome/public/images/lavague.png | Bin 54640 -> 0 bytes .../public/images/logo-128x128.png | Bin 17100 -> 0 bytes extension_chrome/public/images/logo-16x16.png | Bin 2625 -> 0 bytes .../public/images/logo-256x256.png | Bin 35258 -> 0 bytes extension_chrome/public/images/logo-48x48.png | Bin 6684 -> 0 bytes extension_chrome/public/manifest.json | 36 - extension_chrome/scss/content.scss | 86 - extension_chrome/src/actionSchemas.ts | 107 - extension_chrome/src/actions.ts | 98 - extension_chrome/src/app/App.tsx | 31 - .../src/app/component/Connection.tsx | 61 - extension_chrome/src/app/component/Debug.tsx | 277 - extension_chrome/src/app/component/Logs.tsx | 147 - .../src/app/component/MainLayout.tsx | 70 - extension_chrome/src/app/component/Prompt.tsx | 58 - .../src/app/context/AppContext.tsx | 40 - extension_chrome/src/app/util/theme.tsx | 20 - extension_chrome/src/background.ts | 101 - extension_chrome/src/connector.ts | 186 - extension_chrome/src/content.ts | 6 - extension_chrome/src/domactions.ts | 303 - extension_chrome/src/driver.ts | 308 - extension_chrome/src/inject_main.ts | 2 - extension_chrome/src/main.ts | 1 - extension_chrome/src/pages.ts | 160 - extension_chrome/src/parseactions.ts | 53 - extension_chrome/src/rpc.ts | 20 - extension_chrome/src/tools.ts | 184 - extension_chrome/tsconfig.json | 18 - extension_chrome/webpack.config.js | 88 - extension_chrome/yarn.lock | 8305 --------- lavague-integrations/contexts/__init__.py | 2 - .../lavague-contexts-anthropic/README.md | 1 - .../lavague/contexts/anthropic/__init__.py | 1 - .../lavague/contexts/anthropic/base.py | 35 - .../lavague-contexts-anthropic/poetry.lock | 3685 ---- .../lavague-contexts-anthropic/pyproject.toml | 30 - .../contexts/lavague-contexts-cache/README.md | 102 - .../lavague/contexts/cache/__init__.py | 4 - .../lavague/contexts/cache/base.py | 35 - .../lavague/contexts/cache/embedding_cache.py | 64 - .../lavague/contexts/cache/llm_cache.py | 36 - .../lavague/contexts/cache/mm_llm_cache.py | 100 - .../lavague/contexts/cache/prompts_store.py | 109 - .../lavague-contexts-cache/poetry.lock | 3467 ---- .../lavague-contexts-cache/pyproject.toml | 31 - .../lavague-contexts-fireworks/README.md | 1 - .../lavague/contexts/fireworks/__init__.py | 1 - .../lavague/contexts/fireworks/base.py | 35 - .../lavague-contexts-fireworks/poetry.lock | 3416 ---- .../lavague-contexts-fireworks/pyproject.toml | 31 - 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lavague-qa/lavague/qa/cli.py | 78 - lavague-qa/lavague/qa/generator.py | 295 - lavague-qa/lavague/qa/prompts.py | 296 - lavague-qa/lavague/qa/utils.py | 120 - lavague-qa/pyproject.toml | 36 - lavague-qa/qa_automation_rework.ipynb | 183 - lavague-server/README.md | 25 - lavague-server/lavague/server/__init__.py | 2 - lavague-server/lavague/server/base.py | 27 - lavague-server/lavague/server/channel.py | 183 - lavague-server/lavague/server/cli.py | 30 - lavague-server/lavague/server/driver.py | 366 - .../lavague/server/websocket_channel.py | 88 - lavague-server/pyproject.toml | 33 - lavague-tests/README.md | 138 - lavague-tests/contexts/__init__.py | 0 lavague-tests/contexts/anthropic_context.py | 8 - lavague-tests/contexts/custom_context.py | 21 - lavague-tests/contexts/default_context.py | 20 - lavague-tests/contexts/fireworks_context.py | 9 - lavague-tests/contexts/gemini_context.py | 10 - lavague-tests/contexts/readme.md | 62 - lavague-tests/lavague/tests/__init__.py | 0 lavague-tests/lavague/tests/cli.py | 104 - lavague-tests/lavague/tests/config.py | 71 - lavague-tests/lavague/tests/runner.py | 184 - lavague-tests/lavague/tests/setup.py | 58 - lavague-tests/lavague/tests/test.py | 61 - lavague-tests/poetry.lock | 3616 ---- lavague-tests/pyproject.toml | 37 - lavague-tests/sites/amazon.com/config.yml | 7 - lavague-tests/sites/examples/config.yml | 11 - lavague-tests/sites/examples/www/index.html | 18 - lavague-tests/sites/examples/www/menu.html | 15 - lavague-tests/sites/google.com/config.yml | 7 - lavague-tests/sites/huggingface.co/config.yml | 16 - lavague-tests/sites/iframe/config.yml | 11 - lavague-tests/sites/iframe/www/iframe.html | 18 - lavague-tests/sites/iframe/www/index.html | 19 - lavague-tests/sites/iframe/www/menu.html | 16 - lavague-tests/sites/iframe/www/nested.html | 18 - lavague-tests/sites/iframe/www/page2.html | 15 - lavague-tests/sites/iframe/www/sub_menu.html | 17 - lavague-tests/sites/jotform.com/config.yml | 8 - lavague-tests/sites/nytimes.com/config.yml | 7 - lavague-tests/sites/reddit.com/config.yml | 7 - lavague-tests/sites/weather.com/config.yml | 7 - lavague-tests/sites/wilkipedia.org/config.yml | 7 - lavague-tests/sites/youtube.com/config.yml | 7 - pyproject.toml | 5 +- python_engine_examples.txt | 28 - .../core/utilities/test_format_utils.py | 42 - 134 files changed, 1 insertion(+), 52886 deletions(-) delete mode 100644 extension_chrome/.eslintignore delete mode 100644 extension_chrome/.eslintrc.js delete mode 100644 extension_chrome/.prettierignore delete mode 100644 extension_chrome/.prettierrc delete mode 100644 extension_chrome/README.md delete mode 100644 extension_chrome/jsconfig.json delete mode 100644 extension_chrome/package-lock.json delete mode 100644 extension_chrome/package.json delete mode 100644 extension_chrome/public/content.html delete mode 100644 extension_chrome/public/images/lavague.png delete mode 100644 extension_chrome/public/images/logo-128x128.png delete mode 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a/extension_chrome/.eslintrc.js +++ /dev/null @@ -1,33 +0,0 @@ -module.exports = { - env: { - browser: true, - es2021: true, - node: true, - }, - extends: ['eslint:recommended', 'plugin:react/recommended', 'plugin:react-hooks/recommended', 'plugin:@typescript-eslint/recommended'], - parser: '@typescript-eslint/parser', - parserOptions: { - ecmaFeatures: { - jsx: true, - }, - ecmaVersion: 2020, - sourceType: 'module', - }, - plugins: ['react', 'react-hooks', 'prettier', '@typescript-eslint'], - rules: { - 'prettier/prettier': ['error', { endOfLine: 'auto' }], - 'react/react-in-jsx-scope': ['off'], - 'no-use-before-define': ['error', 'nofunc'], - '@typescript-eslint/no-use-before-define': ['error', 'nofunc'], - '@typescript-eslint/explicit-module-boundary-types': ['off'], - '@typescript-eslint/ban-ts-comment': 0, - '@typescript-eslint/no-var-requires': 0, - '@typescript-eslint/no-explicit-any': 0, - '@typescript-eslint/no-non-null-assertion': 0, - }, - settings: { - react: { - version: 'detect', - }, - }, -}; diff --git a/extension_chrome/.prettierignore b/extension_chrome/.prettierignore deleted file mode 100644 index b2d59d1f..00000000 --- a/extension_chrome/.prettierignore +++ /dev/null @@ -1,2 +0,0 @@ -/node_modules -/dist \ No newline at end of file diff --git a/extension_chrome/.prettierrc b/extension_chrome/.prettierrc deleted file mode 100644 index 09399c69..00000000 --- a/extension_chrome/.prettierrc +++ /dev/null @@ -1,22 +0,0 @@ -{ - "jsxSingleQuote": false, - "proseWrap": "always", - "quoteProps": "as-needed", - "printWidth": 150, - "singleQuote": true, - "trailingComma": "es5", - "tabWidth": 4, - "semi": true, - "arrowParens": "always", - "importOrderParserPlugins": [ - "typescript", - "decorators-legacy" - ], - "importOrder": [ - "^(react)", - "", - "^[./]" - ], - "importOrderSeparation": true, - "importOrderSortSpecifiers": true -} diff --git a/extension_chrome/README.md b/extension_chrome/README.md deleted file mode 100644 index d34f2a2a..00000000 --- a/extension_chrome/README.md +++ /dev/null @@ -1,108 +0,0 @@ -# LaVague Chrome Extension - -## Using the latest LaVague Chrome Extension release - -### Install necessary packages - -You will need to install the following lavague packages: - -```shell -pip install lavague-core lavague-server -``` - -You will also need to make sure your `OPENAI_API_KEY` is set in your current environment. - -### Running the LaVague Chrome Extension server - -Next, you will need to use LaVague to serve an instance of `AgentServer`. This allows the LaVague extension communicates with a Driver Server using Websockets. - -```python -from lavague.core import WorldModel, ActionEngine -from lavague.core.agents import WebAgent -from lavague.server.driver import DriverServer -from lavague.server import AgentServer, AgentSession - -def create_agent(session: AgentSession): - world_model = WorldModel() - driver = DriverServer(session) - action_engine = ActionEngine(driver) - return WebAgent(world_model, action_engine) - -server = AgentServer(create_agent) -server.serve() -``` - -You can see our latest example script [here](https://github.com/lavague-ai/LaVague/blob/main/examples/chrome_extension.py). - -### Using the extension - -Now you're ready to install and interact with with our LaVague browser extension directly in your Chrome navigator. - -You can install the extension [here](https://chromewebstore.google.com/detail/lavague/johbmggagpndaefakonkdfjpcfdmbfbm). - - - - - - -
Launch ExtensionExample Query Chrome
- -Launch Extension - - -## LaVague Chrome Extension from local - -To interact with a locally modified version of the extension, you'll need to take the following additional steps. - -### 1. Setup - -`yarn` or `npm install` - -### 2. Build or run - -You can build the project with: -`yarn build` or `npm run build` - -This will build the project as a minified production build. - -You can run the project with: -`yarn dev` or `npm run dev` - -This will allow the extension built files to be updated in real time when changes are made in the code using `watch mode`. - -### 3. Upload your local Chrome Extension - -Finally, you can upload and test your locally modified Chrome extension by doing the following: -- Go to the Extensions page [chrome://extensions/](chrome://extensions/) -- Click the `Load unpacked` button -- Select the `dist` directory - -Ta-da! The extension has been successfully installed. Every time you update the extension code, click the refresh button on the LaVague extension. - -### 4. Launch the LaVague Chrome Extension server - -Finally you will need to serve an instance of `AgentServer` by running the following code: - -```shell -pip install lavague-core lavague-server -``` - -```python -from lavague.core import WorldModel, ActionEngine -from lavague.core.agents import WebAgent -from lavague.server.driver import DriverServer -from lavague.server import AgentServer, AgentSession - -def create_agent(session: AgentSession): - world_model = WorldModel() - driver = DriverServer(session) - action_engine = ActionEngine(driver) - return WebAgent(world_model, action_engine) - -server = AgentServer(create_agent) -server.serve() -``` - -Note, you will need to set a valid `OPENAI_API_KEY` environment variable for this to work. - -You will now be able to interact with your LaVague extension in your Chrome navigator. \ No newline at end of file diff --git a/extension_chrome/jsconfig.json b/extension_chrome/jsconfig.json deleted file mode 100644 index 8ea258bf..00000000 --- a/extension_chrome/jsconfig.json +++ /dev/null @@ -1 +0,0 @@ -{"typeAcquisition": {"include": ["chrome"]}} \ No newline at end of file diff --git a/extension_chrome/package-lock.json b/extension_chrome/package-lock.json deleted file mode 100644 index 2ab8e35e..00000000 --- a/extension_chrome/package-lock.json +++ /dev/null @@ -1,14774 +0,0 @@ -{ - 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-} - -#app { - display: flex; - flex-direction: column; - gap: 8px; -} - -.logo { - height: 80px; - object-fit: contain; -} - -.chatbox { - display: flex; - height: calc(100vh - 168px); - flex-direction: column; - gap: 8px; - - .wmlogs { - flex: 1; - overflow-y: auto; - } -} - -.server { - display: flex; - align-items: center; - gap: 8px; -} - -.logs { - flex: 1; - overflow: auto; - display: flex; - flex-direction: column; - gap: 8px; - - .log_welcome { - font-size: 16px; - background: #ebebeb; - padding: 14px 18px; - border-radius: 16px; - white-space: pre-wrap; - width: fit-content; - max-width: 90%; - } - - .log { - font-size: 16px; - background: #ebebeb; - padding: 14px 18px; - border-radius: 16px; - white-space: pre-wrap; - width: fit-content; - max-width: 90%; - - &.error { - background: #ff9589; - } - - &.userprompt { - background: #268bdd; - color: white; - font-weight: 600; - align-self: flex-end; - } - - } -} - -.prompt { - position: relative; - - .button { - position: absolute; - bottom: -12px; - right: -12px; - border-radius: 50%; - width: 40px; - height: 40px; - } -} \ No newline at end of file diff --git a/extension_chrome/src/actionSchemas.ts b/extension_chrome/src/actionSchemas.ts deleted file mode 100644 index 51b575b9..00000000 --- a/extension_chrome/src/actionSchemas.ts +++ /dev/null @@ -1,107 +0,0 @@ -import { z } from 'zod'; - -export const clickSchema = z.object({ - name: z.literal('click'), - description: z.literal('Click on an element with the specified xpath').optional(), - args: z.object({ - xpath: z.string(), - value: z.string().optional(), - }), -}); - -export const enterSchema = z.object({ - name: z.literal('enter'), - description: z.literal('Press enter').optional(), - args: z.object({ - xpath: z.string(), - value: z.string().optional(), - }), -}); - -export const setValueSchema = z.object({ - name: z.literal('setValue'), - description: z.literal('Focus on and set the value of an input element with the specified xpath').optional(), - args: z.object({ - xpath: z.string(), - value: z.string(), - }), -}); - -export const setValueAndEnterSchema = z.object({ - name: z.literal('setValueAndEnter'), - description: z.literal('Like "setValue", but it press enters.').optional(), - args: z.object({ - xpath: z.string(), - value: z.string(), - }), -}); - -export const scrollSchema = z.object({ - name: z.literal('scroll'), - description: z - .literal( - 'Scroll the page to see the other parts. Use "up" or "down" to scroll 2/3 of height of the window. Use "top" or "bottom" to quickly scroll to the top or bottom of the page.' - ) - .optional(), - args: z.object({ - value: z.string(), - }), -}); - -export const waitSchema = z.object({ - name: z.literal('wait'), - description: z.literal('Wait for the amount of specified seconds before the next action.').optional(), - args: z.object({ - value: z.number(), - }), -}); - -export const failSchema = z.object({ - name: z.literal('fail'), - description: z.literal('Indicate that the task cannot be completed').optional(), - args: z.object({ - xpath: z.string().optional(), - value: z.string().optional(), - }), -}); - -export const toolSchemaUnion = z.discriminatedUnion('name', [ - clickSchema, - enterSchema, - setValueSchema, - setValueAndEnterSchema, - scrollSchema, - waitSchema, - failSchema, -]); -const allTools = toolSchemaUnion.options; -type ToolSchema = (typeof allTools)[number]; - -export type ToolOperation = z.infer; - -export function schemaToDescription(schema: ToolSchema): string { - let description = ''; - const shape = schema.shape; - const name = shape.name._def.value; - const descriptionText = shape.description.unwrap()._def.value; - description += `Name: ${name}\nDescription: ${descriptionText}\n`; - - const args = shape.args; - // If the tool has arguments, list them. If entire args is ZodOptional, there are no arguments. - if (args instanceof z.ZodObject && Object.keys(args.shape).length > 0) { - description += 'Arguments:\n'; - Object.entries(args.shape).forEach(([key, value]) => { - const argType = value instanceof z.ZodString ? 'string' : 'unknown'; - description += ` - ${key} (${argType})\n`; - }); - } else { - description += 'No arguments.\n'; - } - - return description; -} - -function getAllToolsDescriptions(): string { - return allTools.map(schemaToDescription).join('\n'); -} -export const allToolsDescriptions = getAllToolsDescriptions(); diff --git a/extension_chrome/src/actions.ts b/extension_chrome/src/actions.ts deleted file mode 100644 index bd38a186..00000000 --- a/extension_chrome/src/actions.ts +++ /dev/null @@ -1,98 +0,0 @@ -import { DomActions } from './domactions'; -import { sleep } from './tools'; -import { type ToolOperation } from './actionSchemas'; - -export async function clickWithXPath(domActions: DomActions, xpath: string): Promise { - console.log('clickWithXPath', xpath); - return await domActions.clickwithXPath(xpath); -} - -export async function setValueWithXPATH(domActions: DomActions, xpath: string, value: string): Promise { - console.log('setValueWithXPATH', xpath); - return await domActions.setValueWithXPATH({ - xpath, - value, - }); -} - -export async function pressEnter(domActions: DomActions, xpath: string): Promise { - console.log('pressEnter', xpath); - return await domActions.pressEnter({ - xpath, - }); -} - -export async function scroll(domActions: DomActions, value: string) { - switch (value) { - case 'up': - await domActions.scrollUp(); - break; - case 'down': - await domActions.scrollDown(); - break; - case 'top': - await domActions.scrollToTop(); - break; - case 'bottom': - await domActions.scrollToBottom(); - break; - default: - console.error('Invalid scroll value', value); - } -} - -function createOperateTool( - click: (domActions: DomActions, label: string) => Promise, - setValue: (domActions: DomActions, label: string, value: string) => Promise -): (tabId: number, action: ToolOperation) => Promise { - return async (tabId: number, action: ToolOperation) => { - const domActions = new DomActions(tabId); - console.log('operateTool', action); - switch (action.name) { - case 'scroll': - await scroll(domActions, action.args.value); - break; - case 'wait': - console.log('Wait...'); - await sleep(action.args.value * 1000); - console.log('Done waiting.'); - break; - case 'fail': - console.warn('Action failed.'); - break; - case 'click': { - const success = await click(domActions, action.args.xpath); - if (!success) { - console.error('Unable to find element with label: ', action.args.xpath); - } - break; - } - case 'setValue': { - const success = await setValue(domActions, action.args.xpath, action.args.value || ''); - if (!success) { - console.error('Unable to find element with xpath: ', action.args.xpath); - } - break; - } - case 'enter': { - const success = await pressEnter(domActions, action.args.xpath); - if (!success) { - console.error('Unable to find element with xpath: ', action.args.xpath); - } - break; - } - case 'setValueAndEnter': { - const success = await setValue(domActions, action.args.xpath, (action.args.value || '') + '\n'); - if (!success) { - console.error('Unable to find element with xpath: ', action.args.xpath); - } - break; - } - default: - console.log('Unknown action name', action); - } - }; -} - -// DOM agent currently use this (using xpath instead of label) -export const operateToolWithXPATH = createOperateTool(clickWithXPath, setValueWithXPATH); diff --git a/extension_chrome/src/app/App.tsx b/extension_chrome/src/app/App.tsx deleted file mode 100644 index 35b981d8..00000000 --- a/extension_chrome/src/app/App.tsx +++ /dev/null @@ -1,31 +0,0 @@ -import React, { useContext } from 'react'; -import { createRoot } from 'react-dom/client'; -import { AppContext, AppProvider } from './context/AppContext'; -import MainLayout from './component/MainLayout'; -import { ChakraProvider, Spinner, Box, Text } from '@chakra-ui/react'; -import theme from './util/theme'; -import { RunningAgentState } from '../connector'; - -export default function App({ port }: { port: chrome.runtime.Port }) { - return ( - - - - - - ); -} - -function MainContent() { - return ( - <> - {} - - - ); -} - -export function render(port: chrome.runtime.Port) { - const root = createRoot(document.getElementById('app')!); - root.render(); -} diff --git a/extension_chrome/src/app/component/Connection.tsx b/extension_chrome/src/app/component/Connection.tsx deleted file mode 100644 index 3900bcd3..00000000 --- a/extension_chrome/src/app/component/Connection.tsx +++ /dev/null @@ -1,61 +0,0 @@ -import React, { useContext, useEffect, useState } from 'react'; -import { AppContext } from '../context/AppContext'; -import { AgentServerState } from '../../connector'; -import { Button, FormControl, FormHelperText, FormLabel, Input, Text } from '@chakra-ui/react'; - -const LABELS: { [state in AgentServerState]: string } = { - [AgentServerState.CONNECTED]: 'Connected', - [AgentServerState.DISCONNECTED]: 'Disconnected', - [AgentServerState.CONNECTING]: 'Connecting...', -}; - -export default function Connection({ initialHost }: { initialHost: string }) { - const { serverState, connector } = useContext(AppContext); - const [host, setHost] = useState(initialHost); - const [error, setError] = useState(null); - - useEffect(() => { - connector.connect(initialHost); - }, [connector, initialHost]); - - const handleConnect = async () => { - setError(null); - try { - await connector.connect(host); - } catch (err: any) { - if (err instanceof Event && err.target instanceof WebSocket) { - setError( - 'Unable to connect. Please ensure that the host is valid and points to an active driver server / an instance of lavague-serve running. More instructions on https://docs.lavague.ai/.' - ); - } else { - setError((err.message ?? err) + ''); - } - } - }; - - return ( -

-
- - Agent server host - setHost(e.target.value)} required /> - {LABELS[serverState]} - - {serverState === AgentServerState.CONNECTED ? ( - - ) : ( - - )} -
- {error && ( - - {error} - - )} -
- ); -} diff --git a/extension_chrome/src/app/component/Debug.tsx b/extension_chrome/src/app/component/Debug.tsx deleted file mode 100644 index 29abdb65..00000000 --- a/extension_chrome/src/app/component/Debug.tsx +++ /dev/null @@ -1,277 +0,0 @@ -import React, { useContext, useState } from 'react'; -import { AppContext } from '../context/AppContext'; -import { - Accordion, - AccordionButton, - AccordionIcon, - AccordionItem, - AccordionPanel, - Box, - Button, - Checkbox, - FormControl, - FormLabel, - HStack, - IconButton, - Input, - Select, - Text, - Textarea, - VStack, -} from '@chakra-ui/react'; -import { AgentServerState, RunningAgentState } from '../../connector'; -import { ChatIcon } from '@chakra-ui/icons'; -import Logs from './Logs'; -import * as yaml from 'js-yaml'; - -export default function Debug({ requestConnection }: { requestConnection: () => void }) { - const { connector, runningAgentState, serverState } = useContext(AppContext); - const [highlightedElements, setHighlightedElements] = React.useState([]); - const [inViewport, setInViewport] = useState(true); - const [foregroundOnly, setForegroundOnly] = useState(true); - const [loadHighlight, setLoadHighlight] = useState(false); - const [prompt, setPrompt] = useState(''); - const [action, setAction] = useState('click'); - const [element, setElement] = useState(''); - const [value, setValue] = useState(''); - const [query, setQuery] = useState(''); - const [contextExpansionSize, setContextExpansionSize] = useState(750); - const [semanticTopK, setSemanticTopK] = useState(5); - const [isRetrieving, setIsRetrieving] = useState(false); - - const removeHighlight = async () => { - await Promise.all(highlightedElements.map((xpath) => connector.driver.remove_highlight(xpath))); - setHighlightedElements([]); - }; - - const handleRemoveHighlight = () => { - connector.driver.withConnection(async () => { - await removeHighlight(); - }); - }; - - const highlightElements = () => { - connector.driver.withConnection(async () => { - setLoadHighlight(true); - try { - await removeHighlight(); - const res = await connector.driver.get_possible_interactions(`{"in_viewport": ${inViewport}, "foreground_only": ${foregroundOnly}}`); - const interactions = JSON.parse(res); - const xpaths = Object.keys(interactions); - await Promise.all(xpaths.map((xpath) => connector.driver.highlight_elem(xpath))); - setHighlightedElements(xpaths); - } finally { - setLoadHighlight(false); - } - }); - }; - - const selectInViewport = (e: React.ChangeEvent) => { - setInViewport(e.target.checked); - if (highlightElements.length) { - highlightElements(); - } - }; - - const selectForegroundOnly = (e: React.ChangeEvent) => { - setForegroundOnly(e.target.checked); - if (highlightElements.length) { - highlightElements(); - } - }; - - const handleStart = () => { - if (!prompt && runningAgentState != RunningAgentState.RUNNING) { - return false; - } - if (serverState === AgentServerState.CONNECTED) { - if (runningAgentState === RunningAgentState.IDLE) { - connector.sendPrompt('navigate', prompt); - } - } else { - requestConnection(); - } - }; - - const handleKeyDownNav = (event: React.KeyboardEvent) => { - if (event.key === 'Enter' && !event.shiftKey) { - event.preventDefault(); - handleStart(); - } - }; - - const onRetrieve = async () => { - setIsRetrieving(true); - const unsubscribe = connector.on('inputMessage', async (msg) => { - if (msg.type === 'retrieved') { - try { - unsubscribe(); - await removeHighlight(); - const xpaths: string[] = msg.args; - await Promise.all(xpaths.map((xpath) => connector.driver.highlight_elem(xpath))); - setHighlightedElements(xpaths); - } finally { - setIsRetrieving(false); - } - } - }); - if (serverState !== AgentServerState.CONNECTED) { - requestConnection(); - } else { - connector.sendPrompt('retrieve', JSON.stringify({ query, contextExpansionSize, semanticTopK })); - } - }; - - const executeCommand = () => { - connector.driver.withConnection(async () => { - try { - await connector.driver.executeCode( - yaml.dump([ - { - actions: [ - { - action: { name: action, args: { xpath: element, value } }, - }, - ], - }, - ]) - ); - } catch (e: any) { - alert(e?.message ?? e + ''); - console.error(e); - } - }); - }; - - return ( - - -

- - - Interactive elements - - - -

- - - {highlightedElements.length && {highlightedElements.length} elements found} - - Foreground only - - - In viewport only - - - - - - - -
- -

- - - Navigation engine prompt - - - -

- -
- - } - onClick={handleStart} - zIndex={10} - isActive={!!prompt && serverState !== AgentServerState.CONNECTED && runningAgentState == RunningAgentState.IDLE} - > -
-
-
- -

- - - Retrieval - - - -

- - - Query - setQuery(e.target.value)} /> - - - Context expansion size - setContextExpansionSize(Number(e.target.value))} - /> - - - Semantic top k retrieval - setSemanticTopK(Number(e.target.value))} /> - - - -
- -

- - - Structured action - - - -

- - - setElement(e.target.value)} /> - {action.startsWith('setValue') && setValue(e.target.value)} />} - - -
- -

- - - Command logs - - - -

- - - -
-
- ); -} diff --git a/extension_chrome/src/app/component/Logs.tsx b/extension_chrome/src/app/component/Logs.tsx deleted file mode 100644 index c417ee72..00000000 --- a/extension_chrome/src/app/component/Logs.tsx +++ /dev/null @@ -1,147 +0,0 @@ -import React, { useCallback, useContext, useEffect, useRef, useState } from 'react'; -import { AppContext } from '../context/AppContext'; -import { Badge, Stack, Text } from '@chakra-ui/react'; -import { RunningAgentState } from '../../connector'; -import { extractNextEngine, extractWorldModelInstruction } from '../../tools'; - -export type LogType = 'network' | 'cmd' | 'userprompt' | 'agent_log'; - -interface Log { - type: LogType; - log: string; -} - -interface RepeatableLog extends Log { - count: number; -} - -const COMMAND_LABELS: { [key: string]: string } = { - get_url: 'Get URL', - get_html: 'Get HTML', - get: 'Navigate', - back: 'Go back', - get_screenshot: 'Take screenshot', - execute_script: 'Execute script', - exec_code: 'Execute code', - is_visible: 'Check visibility', - get_possible_interactions: 'Get possible interactions', -}; - -export default function Logs({ logTypes }: { logTypes: LogType[] }) { - const { connector, setRunningAgentState, runningAgentState } = useContext(AppContext); - const [logs, setLogs] = useState([]); - const bottomElementRef = useRef(null); - - const addLog = useCallback( - (log: Log) => { - if (logTypes.includes(log.type)) { - if (logs.length > 0 && logs[logs.length - 1].log === log.log) { - const newLogs = [...logs]; - newLogs[newLogs.length - 1].count++; - setLogs(newLogs); - } else { - if (log.type == 'agent_log') { - const index = logs.findIndex(log => log.type === 'agent_log' && log.log === ""); - const foundLog = index !== -1 ? logs[index] : undefined; - if (foundLog === undefined) { - setLogs([...logs, { ...log, count: 1 }]); - setTimeout(() => bottomElementRef.current?.scrollIntoView({ behavior: 'smooth' }), 500); - } - else { - const newLogs = [...logs]; - newLogs[index].log = log.log; - setLogs(newLogs); - } - } - else { - setLogs([...logs, { ...log, count: 1 }]); - setTimeout(() => bottomElementRef.current?.scrollIntoView({ behavior: 'smooth' }), 500); - } - } - } - }, - [logs, setLogs, bottomElementRef, logTypes] - ); - - useEffect(() => { - let check_last_entry = false - const destructors = [ - connector.onError((err: any) => { - if (err instanceof Event && err.target instanceof WebSocket) { - addLog({ log: 'Unable to connect. Please ensure that the host is valid and points to an active driver server', type: 'network' }); - } else { - console.error(err); - } - }), - connector.onInputMessage((message) => { - let log: string | null = null; - let type: LogType = 'cmd'; - if (message.command) { - log = COMMAND_LABELS[message.command]; - } else if (message.type === 'agent_log' && message.agent_log.world_model_output) { - const log_tmp = message.agent_log.world_model_output; - const engine = extractNextEngine(log_tmp); - if (engine === 'COMPLETE') { - const instruction = extractWorldModelInstruction(log_tmp); - log = instruction.indexOf('[NONE]') != -1 ? 'Objective reached' : 'Output:' + '\n' + instruction; - } else { - log = extractWorldModelInstruction(log_tmp); - } - type = 'agent_log'; - } else if (message.type === 'agent_log' && message.agent_log.current_state) { - log = "" - type = 'agent_log'; - check_last_entry = true - } - else if (message.type === 'start') { - setRunningAgentState(RunningAgentState.RUNNING); - } else if (message.type === 'stop') { - setRunningAgentState(RunningAgentState.IDLE); - for (let i = logs.length - 1; i >= 0; i--) { - if (logs[i].log === "") { - logs.splice(i, 1); - } - } - if (message.args == true) { - addLog({ log: 'The agent was interrupted.', type: 'agent_log' }); - } - } - if (log) { - addLog({ log, type }); - } - else if (check_last_entry) { - const curr_logs = [...logs] - if (curr_logs.length == 0 || curr_logs[curr_logs.length - 1].log != "") { - const lo: string = log! - addLog({ log: lo, type }); - } - check_last_entry = false - } - }), - connector.onOutputMessage((message) => addLog({ log: message.args, type: 'userprompt' })), - connector.onSystemMessage((message) => { - addLog({ log: message.args, type: 'agent_log' }); - }), - connector.onDisconnect(() => { - for (let i = logs.length - 1; i >= 0; i--) { - if (logs[i].log === "") { - logs.splice(i, 1); - } - } - }), - ]; - return () => destructors.forEach((d) => d()); - }, [connector, addLog, setLogs, setRunningAgentState]); - - return ( -
- {logs.map((log, index) => ( - - {log.log.length == 0 && log.type == "agent_log" ? " Thinking of next steps..." : log.log} - {log.count > 1 && {log.count}} - - ))} -
-
- ); -} diff --git a/extension_chrome/src/app/component/MainLayout.tsx b/extension_chrome/src/app/component/MainLayout.tsx deleted file mode 100644 index 291fb6d7..00000000 --- a/extension_chrome/src/app/component/MainLayout.tsx +++ /dev/null @@ -1,70 +0,0 @@ -import React, { useCallback, useContext, useEffect, useState } from 'react'; -import { Stack, Tab, TabList, TabPanel, TabPanels, Tabs, Text } from '@chakra-ui/react'; -import Prompt from './Prompt'; -import Logs from './Logs'; -import Debug from './Debug'; -import Connection from './Connection'; -import { AppContext } from '../context/AppContext'; -import { AgentServerState, RunningAgentState } from '../../connector'; - -export default function MainLayout() { - const { serverState, setRunningAgentState, connector } = useContext(AppContext); - const [tabIndex, setTabIndex] = useState(0); - const [firstConnection, setFirstConnection] = useState(false); - - const tabs: { header: React.JSX.Element; content: React.JSX.Element }[] = []; - - const requestConnection = useCallback(() => setTabIndex(1), []); - - useEffect(() => { - if (serverState === AgentServerState.CONNECTED) { - setTabIndex(0); - setFirstConnection(true); - } - if (serverState === AgentServerState.DISCONNECTED) { - if (firstConnection && !connector.forced_disconnection) { - requestConnection(); - } - setRunningAgentState(RunningAgentState.IDLE); - } - }, [serverState ,setTabIndex, setFirstConnection, setRunningAgentState, firstConnection, connector, requestConnection]); - - tabs.push({ - header: <>Agent, - content: ( -
-
-
- -
-
- -
- ), - }); - - tabs.push({ - header: <>Connection, - content: , - }); - - tabs.push({ - header: <>Dev tool, - content: , - }); - - return ( - - - {tabs.map((tab, index) => ( - {tab.header} - ))} - - - {tabs.map((tab, index) => ( - {tab.content} - ))} - - - ); -} diff --git a/extension_chrome/src/app/component/Prompt.tsx b/extension_chrome/src/app/component/Prompt.tsx deleted file mode 100644 index e8c9782f..00000000 --- a/extension_chrome/src/app/component/Prompt.tsx +++ /dev/null @@ -1,58 +0,0 @@ -import React, { useContext, useState } from 'react'; -import { AppContext } from '../context/AppContext'; -import { AgentServerState, RunningAgentState } from '../../connector'; -import { IconButton, Textarea } from '@chakra-ui/react'; -import { ChatIcon, CloseIcon } from '@chakra-ui/icons'; - -export default function Prompt({ requestConnection }: { requestConnection: () => void }) { - const { connector, serverState, runningAgentState } = useContext(AppContext); - const [prompt, setPrompt] = useState(''); - - const handleStart = () => { - if (!prompt && runningAgentState != RunningAgentState.RUNNING) { - return false; - } - if (serverState === AgentServerState.CONNECTED) { - if (runningAgentState === RunningAgentState.IDLE) { - connector.sendPrompt('run', prompt); - connector.sendSystemMessage("") - } else { - connector.disconnect(); - connector.sendSystemMessage('The agent is now interrupted.'); - connector.connect(connector.host); - } - setPrompt(''); - } else { - requestConnection(); - } - }; - - const handleKeyDown = (event: React.KeyboardEvent) => { - if (event.key === 'Enter' && !event.shiftKey) { - event.preventDefault(); - handleStart(); - } - }; - - return ( -
- - : } - onClick={handleStart} - zIndex={10} - isActive={!!prompt && serverState !== AgentServerState.CONNECTED} - > -
- ); -} diff --git a/extension_chrome/src/app/context/AppContext.tsx b/extension_chrome/src/app/context/AppContext.tsx deleted file mode 100644 index b058835d..00000000 --- a/extension_chrome/src/app/context/AppContext.tsx +++ /dev/null @@ -1,40 +0,0 @@ -import React, { createContext, useEffect, useMemo, useState } from 'react'; -import { AgentServerConnector, AgentServerState, RunningAgentState } from '../../connector'; - -export interface AppContextProps { - connector: AgentServerConnector; - serverState: AgentServerState; - runningAgentState: RunningAgentState; - setRunningAgentState: React.Dispatch>; -} - -export const AppContext = createContext({ - connector: new AgentServerConnector(), - serverState: AgentServerState.DISCONNECTED, - runningAgentState: RunningAgentState.IDLE, - setRunningAgentState: () => {}, -}); - -export const AppProvider = ({ children, port }: { children: React.ReactNode; port: chrome.runtime.Port }) => { - const [serverState, setServerState] = useState(AgentServerState.DISCONNECTED); - const [runningAgentState, setRunningAgentState] = useState(RunningAgentState.IDLE); - const connector = useMemo(() => new AgentServerConnector(), []); - - useEffect(() => { - connector.driver.onTabDebugged = (tabId) => port.postMessage({ type: 'tab_debug', tabId }); - return connector.onStateChange(setServerState); - }, [connector, port]); - - return ( - - {children} - - ); -}; diff --git a/extension_chrome/src/app/util/theme.tsx b/extension_chrome/src/app/util/theme.tsx deleted file mode 100644 index 12943f2a..00000000 --- a/extension_chrome/src/app/util/theme.tsx +++ /dev/null @@ -1,20 +0,0 @@ -import { theme as chakraTheme, extendBaseTheme } from '@chakra-ui/react'; - -const { Button, Input, Textarea, FormLabel, Tabs, Badge, List, Accordion, Checkbox, Select } = chakraTheme.components; - -const theme = extendBaseTheme({ - components: { - Button, - Input, - Textarea, - FormLabel, - Tabs, - Badge, - List, - Accordion, - Checkbox, - Select, - }, -}); - -export default theme; diff --git a/extension_chrome/src/background.ts b/extension_chrome/src/background.ts deleted file mode 100644 index db7dac0d..00000000 --- a/extension_chrome/src/background.ts +++ /dev/null @@ -1,101 +0,0 @@ -import { DomActions } from './domactions'; - -chrome.runtime.onInstalled.addListener(() => { - const sidePanel = (chrome as any).sidePanel; - sidePanel.setPanelBehavior({ openPanelOnActionClick: true }); - // Forcefully inject the RPC script on the open tabs, as chrome will usually only start to inject the code after the page is refreshed... - initRPCScript(); -}); - -function injectIntoTab(tab: any) { - const manifest = chrome.runtime.getManifest(); - const scripts = manifest.content_scripts![0].js; - const s = scripts!.length; - for (let i = 0; i < s; i++) { - chrome.scripting.executeScript({ - target: { tabId: tab.id }, - files: [scripts![i]], - }); - } -} - -function initRPCScript(): void { - chrome.windows.getAll({ populate: true }, (windows: chrome.windows.Window[]) => { - windows.forEach((currentWindow) => { - currentWindow.tabs?.forEach((currentTab) => { - if (currentTab.url && currentTab.url.match(/(file|http|https):\/\//gi)) { - injectIntoTab(currentTab); - } - }); - }); - }); -} - -chrome.runtime.onMessage.addListener((message, sender, sendResponse) => { - if (message.action === 'getEventListeners_all') { - const { xpath_list } = message; - const tabId = sender.tab?.id; - if (!tabId) { - console.error('No tabId found in the sender'); - sendResponse({ response: {} }); - } else { - const domAction = new DomActions(tabId!); - (async () => { - try { - const eventsXpath: { [key: string]: string[] } = {}; - await domAction.sendCommand('DOM.getDocument', { depth: -1 }); - const bodyId = await domAction.getObjectID('/html/body'); - const result_list: any = await domAction.sendCommand('DOMDebugger.getEventListeners', { objectId: bodyId, depth: -1 }); - const result: any[] = result_list.listeners; - await Promise.all( - xpath_list.map(async (xpath: string) => { - try { - const objectId = await domAction.getObjectID(xpath); - if (objectId != null) { - const nodeId_OBJ = await domAction.sendCommand('DOM.requestNode', { - objectId: objectId, - }); - const describedNode = await domAction.sendCommand('DOM.describeNode', { - nodeId: nodeId_OBJ.nodeId, - }); - for (const listener_obj of result) { - if (listener_obj.backendNodeId == describedNode.node.backendNodeId) { - if (!(xpath in eventsXpath)) { - eventsXpath[xpath] = [listener_obj.type]; - } else if (!eventsXpath[xpath].includes(listener_obj.type)) { - eventsXpath[xpath].push(listener_obj.type); - } - } - } - } - } catch (error) { - console.error(error); - } - }) - ); - sendResponse({ response: eventsXpath }); - } catch (error) { - console.error(error); - sendResponse({ response: {} }); - } - })(); - } - } - return true; -}); - -chrome.runtime.onConnect.addListener(function (port) { - if (port.name === 'content') { - let tabId: number | null = null; - port.onMessage.addListener((msg: any) => { - if (msg.type === 'tab_debug') { - tabId = msg.tabId; - } - }); - port.onDisconnect.addListener(() => { - if (tabId != null) { - chrome.debugger.detach({ tabId }); - } - }); - } -}); diff --git a/extension_chrome/src/connector.ts b/extension_chrome/src/connector.ts deleted file mode 100644 index fdea807d..00000000 --- a/extension_chrome/src/connector.ts +++ /dev/null @@ -1,186 +0,0 @@ -import { ChromeExtensionDriver } from './driver'; -import EventEmitter from 'eventemitter3'; - -export enum AgentServerState { - DISCONNECTED, - CONNECTING, - CONNECTED, -} - -export enum RunningAgentState { - IDLE, - RUNNING, -} - -export type EventType = 'init' | 'disconnect' | 'error' | 'stateChange' | 'runningStateChange' | 'inputMessage' | 'outputMessage' | 'systemMessage'; - -export class AgentServerConnector { - private webSocket: WebSocket | null = null; - private eventEmitter = new EventEmitter(); - readonly driver: ChromeExtensionDriver; - currentState: AgentServerState = AgentServerState.DISCONNECTED; - runningAgentState: RunningAgentState = RunningAgentState.IDLE; - public host = ''; - public forced_disconnection = false; - - constructor() { - this.driver = new ChromeExtensionDriver(); - this.emit('init', null); - } - - async connect(host: string) { - this.disconnect(); - this.updateState(AgentServerState.CONNECTING); - try { - const webSocket = new WebSocket('ws://' + host); - this.host = host; - this.forced_disconnection = false; - - webSocket.onmessage = async (event: { data: string }) => { - if (event.data === 'PONG') { - return; - } - const msg = JSON.parse(event.data); - this.emit('inputMessage', msg); - let ret = null; - try { - ret = await this.driver.handleMessage(msg); - } catch (error) { - console.error('Error processing request', error, event.data); - this.emit('error', error); - } - this.sendMessage( - { - id: msg.id, - ret, - method: msg.command, - }, - false - ); - }; - await new Promise((resolve, reject) => { - webSocket.onopen = () => { - this.updateState(AgentServerState.CONNECTED); - resolve(); - }; - webSocket.onerror = reject; - }); - webSocket.onerror = (error) => this.emit('error', error); - webSocket.onclose = () => { - this.updateState(AgentServerState.DISCONNECTED); - this.updateRunningState(RunningAgentState.IDLE); - this.emit('disconnect'); - }; - this.webSocket = webSocket; - this.keepAlive(); - await this.driver.start(); - } catch (e) { - this.updateState(AgentServerState.DISCONNECTED); - this.updateRunningState(RunningAgentState.IDLE); - this.emit('disconnect'); - throw e; - } - } - - sendMessage(message: any, emit = true) { - if (this.currentState !== AgentServerState.CONNECTED) { - return false; - } - this.webSocket?.send(JSON.stringify(message)); - if (emit) { - this.emit('outputMessage', message); - } - return true; - } - - async disconnect() { - if (this.webSocket) { - this.webSocket.close(); - this.webSocket = null; - this.updateState(AgentServerState.DISCONNECTED); - this.updateRunningState(RunningAgentState.IDLE); - this.emit('disconnect'); - } - await this.driver.stop(); - } - - sendSystemMessage(msg: string) { - this.emit('systemMessage', { - args: msg, - }); - } - - sendPrompt(type: 'run' | 'get' | 'run_step' | 'navigate' | 'prepare_run' | 'retrieve', args: string) { - this.sendMessage({ type, args }); - } - - runningStateChange(fn: (state: RunningAgentState) => void) { - return this.on('runningStateChange', fn); - } - - onStateChange(fn: (state: AgentServerState) => void) { - return this.on('stateChange', fn); - } - - onError(fn: (message: string) => void) { - return this.on('error', fn); - } - - onInit(fn: (ret: any) => void) { - return this.on('init', fn); - } - - onInputMessage(fn: (ret: any) => void) { - return this.on('inputMessage', fn); - } - - onDisconnect(fn: () => void) { - return this.on('disconnect', fn); - } - - onSystemMessage(fn: (message: any) => void) { - return this.on('systemMessage', fn); - } - - onOutputMessage(fn: (message: any) => void) { - return this.on('outputMessage', fn); - } - - on>(event: EventType, fn: F) { - this.eventEmitter.on(event, fn); - return () => { - this.eventEmitter.off(event, fn); - }; - } - - private emit(event: EventType, ...args: any[]) { - this.eventEmitter.emit(event, ...args); - } - - private updateRunningState(state: RunningAgentState) { - if (state !== this.runningAgentState) { - this.emit('runningStateChange', state); - this.runningAgentState = state; - } - } - - private updateState(state: AgentServerState) { - if (state !== this.currentState) { - this.emit('stateChange', state); - this.currentState = state; - } - } - - /** - * Keep alive interval shorter than 30s to avoid service worker becoming inactive - */ - private keepAlive() { - const keepAliveIntervalId = setInterval(() => { - if (this.webSocket && this.webSocket.readyState === this.webSocket.OPEN) { - this.webSocket.send('PING'); - } else { - clearInterval(keepAliveIntervalId); - } - }, 10_000); - } -} diff --git a/extension_chrome/src/content.ts b/extension_chrome/src/content.ts deleted file mode 100644 index 7cac756f..00000000 --- a/extension_chrome/src/content.ts +++ /dev/null @@ -1,6 +0,0 @@ -import '../scss/content.scss'; - -import { render } from './app/App'; - -const port = chrome.runtime.connect({ name: 'content' }); -render(port); diff --git a/extension_chrome/src/domactions.ts b/extension_chrome/src/domactions.ts deleted file mode 100644 index b5b14083..00000000 --- a/extension_chrome/src/domactions.ts +++ /dev/null @@ -1,303 +0,0 @@ -import { sleep, waitTillStable } from './tools'; - -const DEFAULT_INTERVAL = 500; -const DEFAULT_TIMEOUT = 10000; // 10 seconds - -export function getNodeFromXPATH(xpath: string): Node | null { - const result = document.evaluate(xpath, document, null, XPathResult.FIRST_ORDERED_NODE_TYPE, null); - const res2 = result.singleNodeValue; - return res2; -} - -export function clickElementByXPath(xpath: string): boolean { - const element = getNodeFromXPATH(xpath); - if (element && element instanceof HTMLElement) { - element.click(); - console.log('click', element.textContent); - return true; - } else { - console.log('failed to click!'); - return false; - } -} - -export class DomActions { - static delayBetweenClicks = 500; - static delayBetweenKeystrokes = 10; - - tabId: number; - - constructor(tabId: number) { - this.tabId = tabId; - } - - public async sendCommand(method: string, params?: any): Promise { - return chrome.debugger.sendCommand({ tabId: this.tabId }, method, params); - } - - public async execCode(code: string, returnByValue = false) { - return await this.sendCommand('Runtime.evaluate', { - expression: code, - returnByValue: returnByValue, - }); - } - - public async clickAtPosition(x: number, y: number, clickCount = 1): Promise { - await this.sendCommand('Input.dispatchMouseEvent', { - type: 'mousePressed', - x, - y, - button: 'left', - clickCount, - }); - await sleep(20); - await this.sendCommand('Input.dispatchMouseEvent', { - type: 'mouseReleased', - x, - y, - button: 'left', - clickCount, - }); - await sleep(DomActions.delayBetweenClicks); - } - - private async selectAllText() { - await this.sendCommand('Input.dispatchKeyEvent', { - type: 'keyDown', - commands: ['selectAll'], - }); - await sleep(200); - } - - public async getCoordinatesFromXPATH(xpath: string) { - const objectId = this.getObjectID(xpath); - const { model } = await this.sendCommand('DOM.getBoxModel', { - objectId, - }); - const [x1, y1, _x2, _y2, x3, y3] = model.border; - const centerX = (x1 + x3) / 2; - const centerY = (y1 + y3) / 2; - return { x: centerX, y: centerY }; - } - - private async typeText(text: string): Promise { - for (const char of text) { - if (char === '\n') { - this.enterButton(); - continue; - } - await this.sendCommand('Input.dispatchKeyEvent', { - type: 'keyDown', - text: char, - }); - await sleep(DomActions.delayBetweenKeystrokes); - await this.sendCommand('Input.dispatchKeyEvent', { - type: 'keyUp', - text: char, - }); - await sleep(DomActions.delayBetweenKeystrokes); - } - } - private async enterButton(): Promise { - await this.sendCommand('Input.dispatchKeyEvent', { - type: 'keyDown', - windowsVirtualKeyCode: 13, - key: 'Enter', - code: 'Enter', - text: '\r', - }); - await this.sendCommand('Input.dispatchKeyEvent', { - type: 'keyUp', - windowsVirtualKeyCode: 13, - key: 'Enter', - code: 'Enter', - text: '\r', - }); - } - - public async waitTillHTMLRendered(interval = DEFAULT_INTERVAL, timeout = DEFAULT_TIMEOUT): Promise { - return waitTillStable( - async () => { - const { result } = await this.sendCommand('Runtime.evaluate', { - expression: 'document.documentElement.innerHTML.length', - }); - return result.value; - }, - interval, - timeout - ); - } - - public async scrollUp() { - await this.sendCommand('Runtime.evaluate', { - expression: 'window.scrollBy(0, -window.innerHeight);', - }); - await sleep(300); - } - - public async scrollDown() { - await this.sendCommand('Runtime.evaluate', { - expression: 'window.scrollBy(0, window.innerHeight)', - }); - await sleep(300); - } - - public async scrollToTop() { - await this.sendCommand('Runtime.evaluate', { - expression: 'window.scroll({left: 0, top: 0})', - }); - await sleep(300); - } - - public async scrollToBottom() { - await this.sendCommand('Runtime.evaluate', { - expression: 'window.scroll({left: 0, top: document.body.offsetHeight})', - }); - await sleep(300); - } - - public async getObjectID(xpath: string) { - const code = ` - (function(xpath) { - ${getNodeFromXPATH.toString()} - res = getNodeFromXPATH(xpath); - return res - })(${JSON.stringify(xpath)});`; - const ret = await this.execCode(code); - return ret.result.objectId; - } - - public async remove_highlight(xpath: string) { - const code = ` - (function() { - const element = document.evaluate("${xpath}", document, null, XPathResult.FIRST_ORDERED_NODE_TYPE, null).singleNodeValue; - if (element) { - element.style.removeProperty('outline'); - } - })();`; - return this.execCode(code, true); - } - - public async highlight_elem(xpath: string) { - const code = ` - (function() { - const element = document.evaluate("${xpath}", document, null, XPathResult.FIRST_ORDERED_NODE_TYPE, null).singleNodeValue; - if (element) { - element.style.outline = '2px solid red'; - element.style['outline-offset'] = '-1px'; - const rect = element.getBoundingClientRect(); - return { - x: rect.x, - y: rect.y, - x2: rect.left + rect.width, - y2: rect.top + rect.height, - }; - } else { - return { - x: 0, - y: 0, - x2: 0, - y2: 0, - }; - } - })();`; - const ret = await this.execCode(code, true); - return ret; - } - - public async switchToTab(tabId: number) { - await chrome.tabs.update(tabId, { active: true }); - chrome.tabs.highlight({ tabs: tabId }, function () {}); - } - - public async getOpenTabs(): Promise { - const queryTabs = (queryInfo: chrome.tabs.QueryInfo): Promise => { - return new Promise((resolve, reject) => { - chrome.tabs.query(queryInfo, (result) => { - if (chrome.runtime.lastError) { - return reject(chrome.runtime.lastError); - } - resolve(result); - }); - }); - }; - - try { - // Query all tabs once - const tabs = await queryTabs({}); - - // Map the tab titles, marking the active tab - const tabTitles = tabs.map((t) => (t.id === this.tabId ? `${t.id} - [CURRENT] ${t.title}` : `${t.id} - ${t.title}`)); - console.log(tabTitles); - - return tabTitles; - } catch (error) { - console.error('Failed to get tabs:', error); - return []; - } - } - - public async setFocus(xpath: string) { - const code = ` - (function(xpath) { - ${getNodeFromXPATH.toString()} - res = getNodeFromXPATH(xpath); - return res - })(${JSON.stringify(xpath)});`; - const ret = await this.execCode(code); - console.log(ret); - - //Workaround so the nodeId can be retrieved. Might need some optimizations. - await this.sendCommand('DOM.getDocument', { depth: -1 }); - const nodeId = await this.sendCommand('DOM.requestNode', { - objectId: ret.result.objectId, - }); - console.log(nodeId); - await this.sendCommand('DOM.focus', { nodeId: nodeId.nodeId }); - } - - public async pressEnter(payload: { xpath: string }): Promise { - await this.setFocus(payload.xpath); - await sleep(300); - await this.enterButton(); - return true; - } - - public async setValueWithXPATH(payload: { xpath: string; value: string }): Promise { - await this.setFocus(payload.xpath); - await this.selectAllText(); - await this.typeText(payload.value); - return true; - } - - private async get_possible_interactions_dispatch(args: string) { - return new Promise((resolve, reject) => { - chrome.tabs.sendMessage(this.tabId, { method: 'get_possible_interactions', message: args }, (res) => { - const error = chrome.runtime.lastError?.message || res.error; - if (chrome.runtime.lastError || res.error) { - console.error('Error: ' + error); - reject(error); - } else { - resolve(res); - } - }); - }); - } - - public async get_possible_interactions(args: string) { - const res: any = await this.get_possible_interactions_dispatch(args); - return res.response; - } - - public async clickwithXPath(xpath: string) { - const code = ` - (function(xpath) { - ${getNodeFromXPATH.toString()} - ${clickElementByXPath.toString()} - res = getNodeFromXPATH(xpath); - clickElementByXPath(xpath); - })(${JSON.stringify(xpath)});`; - await this.execCode(code); - return true; - } -} diff --git a/extension_chrome/src/driver.ts b/extension_chrome/src/driver.ts deleted file mode 100644 index 01f030af..00000000 --- a/extension_chrome/src/driver.ts +++ /dev/null @@ -1,308 +0,0 @@ -import { operateToolWithXPATH } from './actions'; -import { DomActions } from './domactions'; -import { parseResponse } from './parseactions'; - -export interface DriverCommandHandler { - (message: any): Promise; -} - -export class ChromeExtensionDriver { - private currentTabId: number | null = null; - private started = false; - private readonly handlers: { [command: string]: DriverCommandHandler } = { - get_url: () => this.sendTabURL(), - get_html: () => this.sendHTML(), - get: (msg) => this.get(msg.args), - back: () => this.back(), - get_screenshot: () => this.takeScreenshot(), - execute_script: (msg) => this.executeScript(msg.args), - exec_code: (msg) => this.executeCode(msg.args), - highlight_elem: (msg) => this.highlight_elem(msg.args), - is_visible: (msg) => this.isVisible(msg.args), - get_possible_interactions: (msg) => this.get_possible_interactions(msg.args), - get_tabs: () => this.get_tabs(), - switch_tab: (msg) => this.switch_tab(msg.args), - }; - onTabDebugged?: (tabId: number) => void; - onCommand?: (command: string) => void; - - tabActivatedListener = async (activeInfo: chrome.tabs.TabActiveInfo) => { - chrome.tabs.query({ active: true, lastFocusedWindow: true }, (tabs) => { - if (tabs[0].url != undefined && !tabs[0].url.startsWith('chrome://')) { - const newTabId = activeInfo.tabId; - if (this.currentTabId !== newTabId) { - if (this.currentTabId != null) { - this.detachDebuggerFromTab(this.currentTabId); - } - this.currentTabId = newTabId; - this.attachDebuggerToTab(this.currentTabId); - } - } - }); - }; - - tabUpdatedListener = async (tabId: number, changeInfo: chrome.tabs.TabChangeInfo, tab: chrome.tabs.Tab) => { - if (tab.active && changeInfo.status === 'complete' && !tab.url!.startsWith('chrome://')) { - if (this.currentTabId !== tabId) { - if (this.currentTabId != null) { - this.detachDebuggerFromTab(this.currentTabId); - } - this.currentTabId = tabId; - this.attachDebuggerToTab(tabId); - } - } - }; - - attachDebuggerToTab(tabId: number | null) { - return new Promise((resolve, reject) => { - if (tabId == null) { - resolve(); - } else { - chrome.debugger.attach({ tabId }, '1.3', async () => { - if (chrome.runtime.lastError) { - reject(chrome.runtime.lastError.message); - } else { - resolve(); - this.onTabDebugged?.(tabId); - } - }); - } - }); - } - - detachDebuggerFromTab(tabId: number | null) { - return new Promise((resolve, reject) => { - if (tabId == null) { - resolve(); - } else { - chrome.debugger.detach({ tabId }, () => { - if (this.currentTabId === tabId) { - this.currentTabId = null; - } - if (chrome.runtime.lastError) { - reject(chrome.runtime.lastError.message); - } else { - resolve(); - } - }); - } - }); - } - - async start() { - chrome.tabs.onActivated.addListener(this.tabActivatedListener); - chrome.tabs.onUpdated.addListener(this.tabUpdatedListener); - await this.attachDebuggerToTab(await this.getTabId()); - this.started = true; - } - - async stop() { - this.started = false; - chrome.tabs.onActivated.removeListener(this.tabActivatedListener); - chrome.tabs.onUpdated.removeListener(this.tabUpdatedListener); - await this.detachDebuggerFromTab(await this.getTabId()); - } - - async withConnection(exe: () => Promise) { - const wasStarted = this.started; - if (!wasStarted) { - await this.start(); - } - try { - await exe(); - } finally { - if (!wasStarted) { - await this.stop(); - } - } - } - - async getTabId() { - return ( - this.currentTabId ?? - new Promise((resolve, reject) => { - chrome.tabs.query({ active: true, currentWindow: true }, (tabs) => { - const currentTab = tabs[0]; - if (currentTab.url!.startsWith('chrome://')) { - resolve(null); - } - const currentTabId = currentTab.id; - if (currentTabId) { - resolve(currentTabId); - } else { - reject('No active tab found'); - } - }); - }) - ); - } - - handleMessage(message: any) { - const handler = this.handlers[message.command]; - if (handler) { - this.onCommand?.(message.command); - return handler(message); - } - console.warn(`Unknown command ignored: ${message.command}`); - return null; - } - - sendTabURL() { - return new Promise((resolve) => { - chrome.tabs.query({ active: true, currentWindow: true }, (tabs) => { - resolve(tabs[0].url!); - }); - }); - } - - sendHTML() { - return new Promise((resolve, reject) => { - this.getTabId() - .then((tabId) => { - if (tabId == null) { - reject('No tab available'); - } else { - chrome.scripting - .executeScript({ - target: { tabId }, - func: () => document.documentElement.outerHTML, - }) - .then(([result]) => { - resolve(result.result); - }) - .catch(reject); - } - }) - .catch(reject); - }); - } - - async get(url: string) { - const tabId = await this.getTabId(); - if (tabId == null) { - throw new Error('No tab available'); - } - const res = await chrome.tabs.update(tabId, { url: url }); - const initialTabId = tabId; - - await new Promise((resolve) => { - chrome.tabs.onUpdated.addListener(function onUpdated(localTabId, info) { - if (localTabId === initialTabId && info.status === 'complete') { - chrome.tabs.onUpdated.removeListener(onUpdated); - resolve(); - } - }); - }); - return !!res; - } - - async back() { - const tabId = await this.getTabId(); - if (tabId == null) { - return false; - } - await chrome.tabs.goBack(tabId); - return true; - } - - async takeScreenshot() { - return chrome.tabs.captureVisibleTab({ format: 'png' }); - } - - async executeScript(code: string) { - const tabId = await this.getTabId(); - if (tabId == null) { - return false; - } - const dom = new DomActions(tabId); - const code_ex = `(function() { ${code} })()`; - const res = await dom.execCode(code_ex); - return res.result == undefined ? true : res.result; - } - - async executeCode(text: string) { - const tabId = await this.getTabId(); - if (tabId == null) { - return false; - } - const ret = parseResponse(text); - for (let i = 0; i < ret.length; i++) { - await operateToolWithXPATH(tabId, ret[i].operation); - } - return true; - } - - async get_possible_interactions(args: string) { - const tabId = await this.getTabId(); - if (tabId == null) { - return false; - } - const dom = new DomActions(tabId); - const res = await dom.get_possible_interactions(args); - return res; - } - - async highlight_elem(xpath: string) { - const tabId = await this.getTabId(); - if (tabId == null) { - return false; - } - const dom = new DomActions(tabId); - const res = await dom.highlight_elem(xpath); - const json_ret = JSON.stringify(res.result.value); - return json_ret; - } - - async remove_highlight(xpath: string) { - const tabId = await this.getTabId(); - if (tabId == null) { - return false; - } - const dom = new DomActions(tabId); - await dom.remove_highlight(xpath); - return true; - } - - async switch_tab(tab_id_str: string) { - console.log(tab_id_str); - const tab_id_num = Number(tab_id_str); - const tabId = await this.getTabId(); - if (tabId == null) { - return false; - } - const dom = new DomActions(tabId); - await dom.switchToTab(tab_id_num); - } - - async get_tabs() { - const tabId = await this.getTabId(); - if (tabId == null) { - return false; - } - const dom = new DomActions(tabId); - const res = await dom.getOpenTabs(); - const ret_json = JSON.stringify(res); - return ret_json; - } - - // left for compatibility reasons - async isVisible(xpath: string) { - const combinedExpression = ` - (function() { - const xpath = "${xpath}"; - const element = document.evaluate(xpath, document, null, XPathResult.FIRST_ORDERED_NODE_TYPE, null).singleNodeValue; - if (!element) return false; - const style = window.getComputedStyle(element); - return style.opacity !== "" && style.display !== "none" && style.visibility !== "hidden" && style.opacity !== "0" && element.getAttribute("aria-hidden") !== "true"; - })(); - `; - const tabId = await this.getTabId(); - if (tabId == null) { - return false; - } - const dom = new DomActions(tabId); - const res = await dom.execCode(combinedExpression); - const isVisible = res.result.value; - return isVisible; - } -} diff --git a/extension_chrome/src/inject_main.ts b/extension_chrome/src/inject_main.ts deleted file mode 100644 index 54b29c81..00000000 --- a/extension_chrome/src/inject_main.ts +++ /dev/null @@ -1,2 +0,0 @@ -import { initializeRPC } from './rpc'; -initializeRPC(); diff --git a/extension_chrome/src/main.ts b/extension_chrome/src/main.ts deleted file mode 100644 index d67cd4d5..00000000 --- a/extension_chrome/src/main.ts +++ /dev/null @@ -1 +0,0 @@ -import('./inject_main'); diff --git a/extension_chrome/src/pages.ts b/extension_chrome/src/pages.ts deleted file mode 100644 index 10ea6752..00000000 --- a/extension_chrome/src/pages.ts +++ /dev/null @@ -1,160 +0,0 @@ -function getInteractions(e: any, xpath: string, eventDict: any) { - if (e == null) { - return []; - } - const tag = e.tagName.toLowerCase(); - if ( - !e.checkVisibility() || - e.hasAttribute('disabled') || - e.hasAttribute('readonly') || - e.getAttribute('aria-hidden') === 'true' || - e.getAttribute('aria-disabled') === 'true' || - (tag === 'input' && e.getAttribute('type') === 'hidden') - ) { - return []; - } - const rect = e.getBoundingClientRect(); - if (rect.width + rect.height < 5) { - return []; - } - const style = getComputedStyle(e); - if (style.display === 'none' || style.visibility === 'hidden' || style.opacity === '0') { - return []; - } - const role = e.getAttribute('role'); - const clickableInputs = ['submit', 'checkbox', 'radio', 'color', 'file', 'image', 'reset']; - function hasEvent(n: any) { - const eventExistsInArray = xpath in eventDict && eventDict[xpath].includes(n); - const elementHasAttribute = e.hasAttribute('on' + n); - return eventExistsInArray || elementHasAttribute; - } - const evts = []; - if ( - hasEvent('keydown') || - hasEvent('keyup') || - hasEvent('keypress') || - hasEvent('keydown') || - hasEvent('input') || - e.isContentEditable || - ((tag === 'input' || tag === 'textarea' || role === 'searchbox' || role === 'input') && !clickableInputs.includes(e.getAttribute('type')!)) - ) { - evts.push('TYPE'); - } - if ( - tag === 'a' || - tag === 'button' || - role === 'button' || - role === 'checkbox' || - hasEvent('click') || - hasEvent('mousedown') || - hasEvent('mouseup') || - hasEvent('dblclick') || - style.cursor === 'pointer' || - (tag === 'input' && clickableInputs.includes(e.getAttribute('type'))) || - e.hasAttribute('aria-haspopup') || - tag === 'select' || - role === 'select' - ) { - evts.push('CLICK'); - } - return evts; -} - -function getInteractives(elements: any, foreground_only = false): Record { - const windowHeight = window.innerHeight || document.documentElement.clientHeight; - const windowWidth = window.innerWidth || document.documentElement.clientWidth; - - return Object.fromEntries( - Object.entries(elements).filter(([xpath]) => { - const element = document.evaluate(xpath, document, null, XPathResult.FIRST_ORDERED_NODE_TYPE, null).singleNodeValue as HTMLElement; - if (!element) return false; - - const rect = element.getBoundingClientRect(); - - const elemCenter = { - x: rect.left + rect.width / 2, - y: rect.top + rect.height / 2, - }; - - if (elemCenter.x < 0) return false; - if (elemCenter.x > windowWidth) return false; - if (elemCenter.y < 0) return false; - if (elemCenter.y > windowHeight) return false; - - if (!foreground_only) { - return true; - } - - try { - let pointContainer = document.elementFromPoint(elemCenter.x, elemCenter.y); - while (pointContainer) { - if (pointContainer === element) return true; - if (pointContainer == null) return true; - pointContainer = pointContainer.parentNode as HTMLElement | null; - } - } catch (e) { - console.error(e); - } - - return false; - }) - ); -} - -async function getEventListenersAll(xpath: string[]) { - const res = await chrome.runtime.sendMessage({ action: 'getEventListeners_all', xpath_list: xpath }); - return res.response; -} - -function traverse(node: any, xpath: string, results: any) { - if (node.nodeType === Node.ELEMENT_NODE) { - results.push(xpath); - } - const countByTag: { [key: string]: number } = {}; - for (let child = node.firstChild; child; child = child.nextSibling) { - let tag = child.nodeName.toLowerCase(); - if (tag.includes(':')) continue; //namespace - const isLocal = ['svg'].includes(tag); - if (isLocal) { - tag = `*[local-name() = '${tag}']`; - } - countByTag[tag] = (countByTag[tag] || 0) + 1; - let childXpath = xpath + '/' + tag; - if (countByTag[tag] > 1) { - childXpath += '[' + countByTag[tag] + ']'; - } - if (tag === 'iframe') { - try { - traverse(child.contentWindow!.document.body, childXpath + '/html/body', results); - } catch (e) { - // iframe access blocked - } - } else { - traverse(child, childXpath, results); - } - } - return results; -} - -function getElementByXpath(xpath: string) { - return document.evaluate(xpath, document, null, XPathResult.FIRST_ORDERED_NODE_TYPE, null).singleNodeValue; -} - -export async function getPossibleInteractions(args: string) { - let final_results: { [key: string]: string[] } = {}; - let xpath_list: string[] = []; - const args_parsed = JSON.parse(args); - xpath_list = traverse(document.body, '/html/body', xpath_list); - const results_events = await getEventListenersAll(xpath_list); - for (const xpath of xpath_list) { - const elem = getElementByXpath(xpath); - const interactions = getInteractions(elem, xpath, results_events); - if (interactions.length > 0) { - final_results[xpath] = interactions; - } - } - if (args_parsed['in_viewport'] == true) { - final_results = getInteractives(final_results, args_parsed['foreground_only']); - } - return JSON.stringify(final_results); -} diff --git a/extension_chrome/src/parseactions.ts b/extension_chrome/src/parseactions.ts deleted file mode 100644 index 9bef5c83..00000000 --- a/extension_chrome/src/parseactions.ts +++ /dev/null @@ -1,53 +0,0 @@ -import { fromError } from 'zod-validation-error'; -import { toolSchemaUnion } from './actionSchemas'; -import * as yaml from 'js-yaml'; - -// sometimes AI replies with a JSON wrapped in triple backticks -export function extractJsonFromMarkdown(input: string): string[] { - // Create a regular expression to capture code wrapped in triple backticks - const regex = /```(json)?\s*([\s\S]*?)\s*```/g; - - const results = []; - let match; - while ((match = regex.exec(input)) !== null) { - // If 'json' is specified, add the content to the results array - if (match[1] === 'json') { - results.push(match[2]); - } else if (match[2].startsWith('{')) { - results.push(match[2]); - } - } - return results; -} - -export function parseResponse(text: string) { - const action_list = []; - const action: any = yaml.load(text); - - for (let i = 0; i < action[0].actions.length; i++) { - const act = action[0].actions[i]; - console.log(act); - - if (act.action == null) { - throw new Error('Invalid response: Action is required'); - } - - let operation; - try { - operation = toolSchemaUnion.parse(act.action); - } catch (err) { - const validationError = fromError(err); - // user friendly error message - throw new Error(validationError.toString()); - } - - const res = { - thought: act.thought, - operation, - }; - - action_list.push(res); - } - - return action_list; -} diff --git a/extension_chrome/src/rpc.ts b/extension_chrome/src/rpc.ts deleted file mode 100644 index bcd1c384..00000000 --- a/extension_chrome/src/rpc.ts +++ /dev/null @@ -1,20 +0,0 @@ -// The content script runs inside each page this extension is enabled on -// Do NOT import from here from outside of content script (other than types). -import { getPossibleInteractions } from './pages'; - -export const initializeRPC = () => { - chrome.runtime.onMessage.addListener(function (request, sender, sendResponse) { - async function tryAndSend(fn: () => Promise) { - try { - sendResponse({ response: await fn() }); - } catch (error: any) { - console.error('Error:', error); - sendResponse({ error: error.toString() }); - } - } - if (request.method == 'get_possible_interactions') { - tryAndSend(() => getPossibleInteractions(request.message)); - } - return true; - }); -}; diff --git a/extension_chrome/src/tools.ts b/extension_chrome/src/tools.ts deleted file mode 100644 index 2f099eb9..00000000 --- a/extension_chrome/src/tools.ts +++ /dev/null @@ -1,184 +0,0 @@ -const DEFAULT_ENGINES: string[] = ['Navigation Controls', 'Python Engine', 'Navigation Engine', 'COMPLETE']; - -export async function copyToClipboard(text: string) { - await navigator.clipboard.writeText(text); -} - -export async function sleep(ms: number) { - return new Promise((resolve) => setTimeout(resolve, ms)); -} - -export function truthyFilter(value: T | null | undefined): value is T { - return Boolean(value); -} - -export function extractNextEngine(text: string, nextEngines: string[] = DEFAULT_ENGINES): string { - // Define the patterns to match "Next engine:" - const nextEnginePatterns: RegExp[] = [/Next engine:\s*(.*)/, /### Next Engine:\s*(.*)/]; - - for (const pattern of nextEnginePatterns) { - try { - const nextEngineMatch = text.match(pattern); - if (nextEngineMatch) { - const extractedText = nextEngineMatch[1].trim(); - // Check if the extracted text matches any of the provided engines - for (const engine of nextEngines) { - if (extractedText.toLowerCase().includes(engine.toLowerCase())) { - return engine; - } - } - } - } catch (e) {} - } - - throw new Error(`No next engine found in the text: ${text}`); -} - -export function extractWorldModelInstruction(text: string): string { - // Define the instruction patterns as an array of regular expressions - const instructionPatterns: RegExp[] = [ - /Instruction:\s*((?:- .*\n?)+)/, // For multi-line hyphenated instructions - /### Instruction:\s*((?:- .*\n?)+)/, // For multi-line hyphenated instructions with ### prefix - /Instruction:\s*((?:\d+\.\s.*\n?)+)/, // For multi-line numbered instructions - /### Instruction:\s*((?:\d+\.\s.*\n?)+)/, // For multi-line numbered instructions with ### prefix - /Instruction:\s*```([\s\S]*?)```/, // For block of text within triple backticks - /### Instruction:\s*```([\s\S]*?)```/, // For block of text within triple backticks with ### prefix - /Instruction:\s*(.*)/, // For single-line instructions - /### Instruction:\s*(.*)/, // For single-line instructions with ### prefix - ]; - - let longestInstruction = ''; - - for (const pattern of instructionPatterns) { - const matches = text.match(pattern); - if (matches && matches[1]) { - let instructionText = matches[1]; - // Check if the instruction is multi-line or single-line - if (instructionText.includes('\n')) { - // Remove newlines and extra spaces for multi-line instructions - instructionText = instructionText.split('\n').join(' ').trim(); - } - // Update longestInstruction if the current one is longer - if (instructionText.length > longestInstruction.length) { - longestInstruction = instructionText; - } - } - } - - if (longestInstruction) { - return longestInstruction; - } - - throw new Error('No instruction found in the text.'); -} - -export function ripple(x: number, y: number) { - const rippleRadius = 30; - const ripple = document.createElement('div'); - ripple.classList.add('web-agent-ripple'); - ripple.style.width = ripple.style.height = `${rippleRadius * 2}px`; - // Take scroll position into account - ripple.style.top = `${window.scrollY + y - rippleRadius}px`; - ripple.style.left = `${x - rippleRadius}px`; - - document.body.appendChild(ripple); - - // remove after the animation to finish - // but we don't need to `await` it - sleep(800).then(() => { - ripple.remove(); - }); -} - -export function xpathToCss(xpath: string) { - // Replace double slashes with spaces - const css = xpath - .replace(/\/\//g, ' ') - .replace(/\//g, ' > ') - .replace(/\[(\d+)\]/g, (match, p1) => `:nth-of-type(${p1})`) - .replace(/@/g, '') - .replace(/\[contains\((.*?),\s*'(.*?)'\)\]/g, (match, p1, p2) => `[${p1}*='${p2}']`) - .replace(/\[name\(\)='(.*?)'\]/g, '$1') - .replace(/\[(.*?)\]/g, '[$1]'); - - return css.trim(); -} - -export async function waitFor(predicate: () => Promise, interval: number, _maxChecks: number, rejectOnTimeout = true): Promise { - // special case for 0 maxChecks (wait forever) - const maxChecks = _maxChecks === 0 ? Infinity : _maxChecks; - let checkCount = 0; - return new Promise((resolve, reject) => { - const intervalId = setInterval(async () => { - if (await predicate()) { - clearInterval(intervalId); - resolve(); - } else { - checkCount++; - if (checkCount >= maxChecks) { - clearInterval(intervalId); - if (rejectOnTimeout) { - reject(new Error('Timed out waiting for condition')); - } else { - resolve(); - } - } - } - }, interval); - }); -} - -export async function waitTillStable( - getSize: () => Promise, - interval: number, - timeout: number, - rejectOnTimeout = false // default to assuming stable after timeout -): Promise { - let lastSize = 0; - let countStableSizeIterations = 0; - const minStableSizeIterations = 3; - - return waitFor( - async () => { - const currentSize = await getSize(); - - console.log('last: ', lastSize, ' <> curr: ', currentSize); - - if (lastSize != 0 && currentSize === lastSize) { - countStableSizeIterations++; - } else { - countStableSizeIterations = 0; //reset the counter - } - - if (countStableSizeIterations >= minStableSizeIterations) { - console.log('Size stable! Assume fully rendered..'); - return true; - } - - lastSize = currentSize; - return false; - }, - interval, - timeout / interval, - rejectOnTimeout - ); -} - -export function enumKeys(obj: O): K[] { - return Object.keys(obj) as K[]; -} - -export function enumValues(obj: O): O[keyof O][] { - return enumKeys(obj).map((key) => obj[key]); -} - -// TypeScript function -function scrollIntoViewFunction() { - // @ts-expect-error this is run in the browser context - this.scrollIntoView({ - block: 'center', - inline: 'center', - }); -} -// Convert the TypeScript function to a string -export const scrollScriptString = scrollIntoViewFunction.toString(); diff --git a/extension_chrome/tsconfig.json b/extension_chrome/tsconfig.json deleted file mode 100644 index 5b5a0f30..00000000 --- a/extension_chrome/tsconfig.json +++ /dev/null @@ -1,18 +0,0 @@ -{ - "compilerOptions": { - "strict": true, - "module": "commonjs", - "target": "es6", - "jsx": "react", - "esModuleInterop": true, - "sourceMap": true, - "rootDir": "src", - "outDir": "dist", - "noEmitOnError": true, - "moduleResolution": "node", - "typeRoots": [ - "node_modules/@types" - ] - }, - "typeAcquisition": {"include": ["chrome"]} -} \ No newline at end of file diff --git a/extension_chrome/webpack.config.js b/extension_chrome/webpack.config.js deleted file mode 100644 index 4df85e2b..00000000 --- a/extension_chrome/webpack.config.js +++ /dev/null @@ -1,88 +0,0 @@ -const CopyPlugin = require('copy-webpack-plugin'); -const MiniCssExtractPlugin = require('mini-css-extract-plugin'); -const Dotenv = require('dotenv-webpack'); -const TerserPlugin = require('terser-webpack-plugin'); -const path = require('path'); -const outputPath = 'dist'; - -module.exports = (env, { mode }) => { - const isProduction = mode === 'production'; - - return { - entry: { - main: [path.resolve(__dirname, 'src', 'main.ts')], - background: path.resolve(__dirname, 'src', 'background.ts'), - content: path.resolve(__dirname, 'src', 'content.ts'), - }, - output: { - path: path.join(__dirname, outputPath), - filename: '[name].js', - }, - resolve: { - extensions: ['.tsx', '.ts', '.js'], - alias: { - '@': path.resolve(__dirname, 'src/'), - }, - }, - module: { - rules: [ - { - test: /\.(ts|tsx)?$/, - use: 'ts-loader', - exclude: /node_modules/, - }, - { - test: /\.?(js|jsx)$/, - exclude: /node_modules/, - use: { - loader: 'babel-loader', - options: { - presets: ['@babel/preset-env', '@babel/preset-react', '@babel/preset-typescript'], - plugins: [ - [ - 'babel-plugin-styled-components', - { - minify: isProduction, - transpileTemplateLiterals: isProduction, - }, - ], - ], - }, - }, - }, - { - test: /\.s[ac]ss$/i, - use: ['style-loader', 'css-loader', 'sass-loader'], - }, - { - test: /\.(jpg|jpeg|png|gif|woff|woff2|eot|ttf|svg)$/i, - use: 'url-loader?limit=1024', - }, - ], - }, - plugins: [ - new CopyPlugin({ - patterns: [{ from: '.', to: '.', context: 'public' }], - }), - new MiniCssExtractPlugin({ - filename: '[name].css', - }), - new Dotenv(), - ], - optimization: { - minimize: isProduction, - mergeDuplicateChunks: true, - removeEmptyChunks: true, - sideEffects: false, - minimizer: [ - new TerserPlugin({ - terserOptions: { - keep_classnames: true, - keep_fnames: true, - }, - }), - ], - }, - devtool: isProduction ? 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- -class AnthropicContext(Context): - def __init__( - self, - api_key: Optional[str] = None, - openai_api_key: Optional[str] = None, - llm: str = "claude-3-5-sonnet-20240620", - mm_llm: str = "claude-3-5-sonnet-20240620", - embedding: str = "text-embedding-3-small", - ) -> Context: - if api_key is None: - api_key = os.getenv("ANTHROPIC_API_KEY") - if api_key is None: - raise ValueError("ANTHROPIC_API_KEY is not set") - if openai_api_key is None: - openai_api_key = os.getenv("OPENAI_API_KEY") - if openai_api_key == None: - raise ValueError("OPENAI_API_KEY is not set") - return super().__init__( - Anthropic( - api_key=api_key, - model=llm, - max_tokens=DEFAULT_MAX_TOKENS, - temperature=DEFAULT_TEMPERATURE, - ), - AnthropicMultiModal(api_key=api_key, model=mm_llm), - OpenAIEmbedding(api_key=openai_api_key, model=embedding), - ) diff --git a/lavague-integrations/contexts/lavague-contexts-anthropic/poetry.lock b/lavague-integrations/contexts/lavague-contexts-anthropic/poetry.lock deleted file mode 100644 index 17d1eede..00000000 --- a/lavague-integrations/contexts/lavague-contexts-anthropic/poetry.lock +++ /dev/null @@ -1,3685 +0,0 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. - 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"Development Status :: 3 - Alpha", - "Intended Audience :: Developers", - "Topic :: Scientific/Engineering :: Artificial Intelligence", - "Topic :: Software Development :: Libraries :: Application Frameworks", - "Topic :: Software Development :: Libraries :: Python Modules", - "License :: OSI Approved :: Apache Software License", -] -keywords = ["LAM", "action", "automation", "LLM", "NLP", "RAG", "selenium", "playwright"] -homepage = "https://lavague.ai" -repository = "https://github.com/lavague-ai/LaVague/" -documentation = "https://docs.lavague.ai/en/latest/" -packages = [{include = "lavague/"}] - -[tool.poetry.dependencies] -python = ">=3.10.0,<3.12" -lavague-core = "^0.2.26" -llama-index-llms-anthropic = "0.1.15" -llama-index-multi-modal-llms-anthropic = "^0.1.6" - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" diff --git a/lavague-integrations/contexts/lavague-contexts-cache/README.md b/lavague-integrations/contexts/lavague-contexts-cache/README.md deleted file mode 100644 index 6e75ccc3..00000000 --- a/lavague-integrations/contexts/lavague-contexts-cache/README.md +++ /dev/null @@ -1,102 +0,0 @@ -# Cache for LLM, Multimodal LLM and embeddings - - -## Overview - -LaVague Context Cache is a caching layer designed for Language Models, Multimodal Language Models and embeddings. -It ensures deterministic results, avoids unnecessary token consumption, and speeds up local development by caching responses and embeddings. - -This tool is ideal for: -- Developers seeking to streamline their workflow when working with models. -- Builders aiming to reduce model costs and enhance performance when agent objectives are stable. - -Key features: -- Guarantees consistent results in both automated and manual testing by caching previous responses -- Reduces API token consumption by reusing cached results, avoiding redundant API calls -- Speeds up local development by eliminating the need to repeatedly query the same results -- Cached scenario can be replayed offline - - -## Installation - -### From pypi - -```bash -pip install lavague-contexts-cache -``` - -### From the sources -```bash -pip install -e lavague-integrations/contexts/lavague-contexts-cache -``` - - -## Usage - -### Using wrappers - -```python -from lavague.contexts.cache import LLMCache -from llama_index.llms.openai import OpenAI - -llm = LLMCache(yml_prompts_file="llm.yml", fallback=OpenAI(model = "gpt-4o")) -``` - -```python -from lavague.contexts.cache import MultiModalLLMCache -from llama_index.multi_modal_llms.openai import OpenAIMultiModal - -mm_llm = MultiModalLLMCache(yml_prompts_file="mmllm.yml", fallback=OpenAIMultiModal(model = "gpt-4o")) -``` - -```python -from lavague.contexts.cache import EmbeddingCache -from llama_index.embeddings.openai import OpenAIEmbedding - -embedding = EmbeddingCache(yml_prompts_file="embeddings.yml", fallback=OpenAIEmbedding(model = "text-embedding-3-large")) -``` - -### Using LaVague context - -```python -from lavague.core import WorldModel, ActionEngine -from lavague.core.agents import WebAgent -from lavague.drivers.selenium import SeleniumDriver -from lavague.core.context import get_default_context -from lavague.contexts.cache import ContextCache - -driver = SeleniumDriver() -context = get_default_context() -cached_context = ContextCache.from_context(context) -world_model = WorldModel.from_context(cached_context) -action_engine = ActionEngine.from_context(cached_context, driver) -agent = WebAgent(world_model, action_engine) -``` - - -## Performance - -Cached values are stored in YAML files and loaded into memory by default. -While this approach works well for a few runs, it can consume excessive memory when applied to various websites. -For production use cases, we recommend using an optimized storage system (database, cache, ...). - -To do so, pass a `store` that implements abstract `PromptsStore` methods. - -```python -from lavague.contexts.cache import LLMCache -from lavague.contexts.cache.prompts_store import PromptsStore -from llama_index.llms.openai import OpenAI - -class MyDataBaseStore(PromptsStore[str]): - def _get_for_prompt(self, prompt: str) -> str: - # return from DB with prompt key - pass - - def _add_prompt(self, prompt: str, output: str): - # store in DB - pass - -my_database_store = MyDataBaseStore() - -llm = LLMCache(yml_prompts_file="llm.yml", fallback=OpenAI(model = "gpt-4o"), store=store) -``` \ No newline at end of file diff --git a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/__init__.py b/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/__init__.py deleted file mode 100644 index 8870f680..00000000 --- a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from lavague.contexts.cache.base import ContextCache -from lavague.contexts.cache.llm_cache import LLMCache -from lavague.contexts.cache.mm_llm_cache import MultiModalLLMCache -from lavague.contexts.cache.embedding_cache import EmbeddingCache diff --git a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/base.py b/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/base.py deleted file mode 100644 index a00db47a..00000000 --- a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/base.py +++ /dev/null @@ -1,35 +0,0 @@ -from lavague.core.context import Context -from llama_index.core.multi_modal_llms import MultiModalLLM -from typing import Optional -from llama_index.core.base.embeddings.base import BaseEmbedding -from llama_index.core.base.llms.base import BaseLLM -from lavague.contexts.cache.llm_cache import LLMCache -from lavague.contexts.cache.mm_llm_cache import MultiModalLLMCache -from lavague.contexts.cache.embedding_cache import EmbeddingCache -from lavague.core.context import get_default_context - - -class ContextCache(Context): - def __init__( - self, - llm_fallback: Optional[BaseLLM] = None, - mm_llm_fallback: Optional[MultiModalLLM] = None, - embedding_fallback: Optional[BaseEmbedding] = None, - ) -> Context: - return super().__init__( - LLMCache(fallback=llm_fallback), - MultiModalLLMCache(fallback=mm_llm_fallback), - EmbeddingCache(fallback=embedding_fallback), - ) - - @classmethod - def from_context(cls, context: Context) -> "ContextCache": - return cls( - llm_fallback=context.llm, - mm_llm_fallback=context.mm_llm, - embedding_fallback=context.embedding, - ) - - @classmethod - def default(cls) -> "ContextCache": - return cls.from_context(get_default_context()) diff --git a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/embedding_cache.py b/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/embedding_cache.py deleted file mode 100644 index f8863844..00000000 --- a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/embedding_cache.py +++ /dev/null @@ -1,64 +0,0 @@ -from llama_index.core.embeddings import ( - BaseEmbedding, - MockEmbedding as LlamaMockEmbedding, -) -from lavague.contexts.cache.prompts_store import PromptsStore, VectorStrPromptStore -from typing import List, Optional, Callable -import sys - - -class EmbeddingCache(LlamaMockEmbedding): - fallback: Optional[BaseEmbedding] - store: PromptsStore[List[float]] = None - max_dimensions: Optional[int] - - def __init__( - self, - fallback: Optional[BaseEmbedding] = None, - yml_prompts_file: Optional[str] = "embeddings.yml", - store: Optional[PromptsStore[List[float]]] = None, - max_dimensions: Optional[int] = 10, - ) -> None: - super().__init__(embed_dim=max_dimensions) - self.store = store or VectorStrPromptStore(yml_prompts_file=yml_prompts_file) - self.fallback = fallback - self.max_dimensions = max_dimensions - - def _reduce_dimension(self, value: List[float]): - """Linear dimension reduction compressing last features, single-vector but less accurate than PCA or t-SNE""" - while len(value) > self.max_dimensions: - last_value = value.pop() - value[-1] = value[-1] + last_value - if value[-1] == float("inf"): - value[-1] = sys.float_info.min + last_value - elif value[-1] == float("-inf"): - value[-1] = sys.float_info.max - last_value - - def get_embedding( - self, text: str, embedder: Callable[[str], List[float]] - ) -> List[float]: - value = self.store.get_for_prompt(text) - - if value is not None: - return value - - if self.fallback is None: - value = super()._get_vector() - else: - value = embedder(text) - self._reduce_dimension(value) - - self.store.add_prompt(text, value) - return value - - def get_text_embedding(self, text: str) -> List[float]: - return self.get_embedding(text, self.fallback.get_text_embedding) - - def get_query_embedding(self, query: str) -> List[float]: - return self.get_embedding(query, self.fallback.get_query_embedding) - - def _get_text_embeddings(self, texts: List[str]) -> List[List[float]]: - return [self.get_text_embedding(txt) for txt in texts] - - def _get_query_embeddings(self, queries: List[str]) -> List[List[float]]: - return [self.get_query_embedding(txt) for txt in queries] diff --git a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/llm_cache.py b/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/llm_cache.py deleted file mode 100644 index 43b871f9..00000000 --- a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/llm_cache.py +++ /dev/null @@ -1,36 +0,0 @@ -from llama_index.core.base.llms.base import BaseLLM -from llama_index.core.llms import MockLLM as LlamaMockLLM -from llama_index.core.base.llms.types import CompletionResponse -from typing import Any, Dict, Optional -from lavague.contexts.cache.prompts_store import PromptsStore, YamlPromptsStore - - -class LLMCache(LlamaMockLLM): - fallback: Optional[BaseLLM] - store: PromptsStore[str] = None - - def __init__( - self, - prompts: Dict[str, str] = None, - fallback: Optional[BaseLLM] = None, - store: Optional[PromptsStore[str]] = None, - yml_prompts_file: Optional[str] = "llm_prompts.yml", - ) -> None: - super().__init__() - self.store = store or YamlPromptsStore( - prompts=prompts, - yml_prompts_file=yml_prompts_file, - ) - self.fallback = fallback - - def complete( - self, prompt: str, formatted: bool = False, **kwargs: Any - ) -> CompletionResponse: - text = self.store.get_for_prompt(prompt) - if text is None: - if self.fallback is None: - text = "(!) Missing LLM answer" - else: - text = self.fallback.complete(prompt, formatted, **kwargs).text - self.store.add_prompt(prompt, text) - return CompletionResponse(text=text) diff --git a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/mm_llm_cache.py b/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/mm_llm_cache.py deleted file mode 100644 index e704eca4..00000000 --- a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/mm_llm_cache.py +++ /dev/null @@ -1,100 +0,0 @@ -from lavague.contexts.cache.prompts_store import PromptsStore, YamlPromptsStore -from llama_index.core.multi_modal_llms import MultiModalLLM, MultiModalLLMMetadata -from llama_index.core.schema import ImageDocument -from llama_index.core.base.llms.types import ( - CompletionResponse, - CompletionResponseGen, - ChatMessage, - ChatResponse, - ChatResponseGen, - CompletionResponseAsyncGen, - ChatResponseAsyncGen, -) -from typing import Optional, Dict, Sequence, Any -import imagehash -from PIL import Image - - -class MultiModalLLMCache(MultiModalLLM): - fallback: Optional[MultiModalLLM] - store: PromptsStore[str] = None - - def __init__( - self, - prompts: Dict[str, any] = None, - fallback: Optional[MultiModalLLM] = None, - store: Optional[PromptsStore[str]] = None, - yml_prompts_file: Optional[str] = "mm_llm_prompts.yml", - ): - super().__init__() - self.store = store or YamlPromptsStore( - prompts=prompts, - yml_prompts_file=yml_prompts_file, - ) - self.fallback = fallback - - def metadata(self) -> MultiModalLLMMetadata: - return MultiModalLLMMetadata() - - def get_image_hash(self, image: ImageDocument) -> str: - hash = imagehash.average_hash(Image.open(image.metadata["file_path"])) - return str(hash) - - def complete( - self, prompt: str, image_documents: Sequence[ImageDocument], **kwargs: Any - ) -> CompletionResponse: - hashes = list(map(self.get_image_hash, image_documents)) - full_prompt = " ".join([*hashes, prompt]) - text = self.store.get_for_prompt(full_prompt) - if text is None: - if self.fallback is None: - text = "(!) Missing Multimodal LLM answer" - else: - text = self.fallback.complete( - full_prompt, image_documents, **kwargs - ).text - self.store.add_prompt(full_prompt, text) - return CompletionResponse(text=text) - - def stream_complete( - self, prompt: str, image_documents: Sequence[ImageDocument], **kwargs: Any - ) -> CompletionResponseGen: - """Streaming completion endpoint for Multi-Modal LLM.""" - - def chat( - self, - messages: Sequence[ChatMessage], - **kwargs: Any, - ) -> ChatResponse: - """Chat endpoint for Multi-Modal LLM.""" - - def stream_chat( - self, - messages: Sequence[ChatMessage], - **kwargs: Any, - ) -> ChatResponseGen: - """Stream chat endpoint for Multi-Modal LLM.""" - - async def acomplete( - self, prompt: str, image_documents: Sequence[ImageDocument], **kwargs: Any - ) -> CompletionResponse: - """Async completion endpoint for Multi-Modal LLM.""" - - async def astream_complete( - self, prompt: str, image_documents: Sequence[ImageDocument], **kwargs: Any - ) -> CompletionResponseAsyncGen: - """Async streaming completion endpoint for Multi-Modal LLM.""" - - async def achat( - self, - messages: Sequence[ChatMessage], - **kwargs: Any, - ) -> ChatResponse: - """Async chat endpoint for Multi-Modal LLM.""" - - async def astream_chat( - self, - messages: Sequence[ChatMessage], - **kwargs: Any, - ) -> ChatResponseAsyncGen: - """Async streaming chat endpoint for Multi-Modal LLM.""" diff --git a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/prompts_store.py b/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/prompts_store.py deleted file mode 100644 index c6154010..00000000 --- a/lavague-integrations/contexts/lavague-contexts-cache/lavague/contexts/cache/prompts_store.py +++ /dev/null @@ -1,109 +0,0 @@ -from typing import Dict, Optional, List, TypeVar, Generic -from abc import ABC, abstractmethod -import yaml -import hashlib - -T = TypeVar("T") - - -class PromptsStore(ABC, Generic[T]): - """Utility class to map prompts with static outputs""" - - record_new_prompts: bool = True - is_cache_disabled = False - hash_prompt = True - - @abstractmethod - def _get_for_prompt(self, prompt: str) -> T: - pass - - @abstractmethod - def _add_prompt(self, prompt: str, output: T): - pass - - def get_for_prompt(self, prompt: str) -> T: - if self.is_cache_disabled: - return None - return self._get_for_prompt(self._to_prompt_key(prompt)) - - def add_prompt(self, prompt: str, output: T) -> bool: - if self.is_cache_disabled: - return False - - print("add prompt", prompt) - self._add_prompt(self._to_prompt_key(prompt), output) - return True - - def _to_prompt_key(self, prompt: str) -> str: - if self.hash_prompt: - return hashlib.sha256(str.encode(prompt)).hexdigest() - return prompt - - -class YamlPromptsStore(PromptsStore[str]): - prompts: Dict[str, str] = None - yml_prompts_file: Optional[str] - - def __init__( - self, - prompts: Optional[Dict[str, any]] = None, - yml_prompts_file: Optional[str] = None, - ) -> None: - self.prompts = prompts or {} - self.yml_prompts_file = yml_prompts_file - if yml_prompts_file is not None: - self.add_from_yml_file(yml_prompts_file) - super().__init__() - - def add_from_yml_file(self, file: str): - try: - with open(file) as stream: - prompts = yaml.safe_load(stream) - if prompts is not None: - self.add_from_yml(prompts) - except IOError: - pass - return self - - def add_from_yml(self, config_list: List[Dict[str, any]]): - for c in config_list: - self.prompts[c["prompt"]] = c["output"] - return self - - def _get_for_prompt(self, prompt: str) -> str: - return self.prompts.get(prompt) - - def _add_prompt(self, prompt: str, output: str): - self.prompts[prompt] = output - - if self.record_new_prompts and self.yml_prompts_file is not None: - with open(self.yml_prompts_file, "a") as outfile: - outfile.write("\n") - yaml.dump( - [{"prompt": prompt, "output": output}], outfile, sort_keys=False - ) - - -class VectorStrPromptStore(PromptsStore[List[float]]): - store: PromptsStore[str] - dim_separator: str - - def __init__( - self, - store: Optional[PromptsStore[str]] = None, - yml_prompts_file: Optional[str] = None, - dim_separator: str = " ", - ) -> None: - self.store = store or YamlPromptsStore(yml_prompts_file=yml_prompts_file) - self.dim_separator = dim_separator - - def _get_for_prompt(self, prompt: str) -> List[float]: - str_value = self.store.get_for_prompt(prompt) - if str_value is None: - return None - - return list(map(float, str_value.split(self.dim_separator))) - - def _add_prompt(self, prompt: str, output: List[float]): - str_value = self.dim_separator.join(list(map(str, output))) - self.store.add_prompt(prompt, str_value) diff --git a/lavague-integrations/contexts/lavague-contexts-cache/poetry.lock b/lavague-integrations/contexts/lavague-contexts-cache/poetry.lock deleted file mode 100644 index 8d9db17c..00000000 --- a/lavague-integrations/contexts/lavague-contexts-cache/poetry.lock +++ /dev/null @@ -1,3467 +0,0 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. - 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"Development Status :: 3 - Alpha", - "Intended Audience :: Developers", - "Topic :: Scientific/Engineering :: Artificial Intelligence", - "Topic :: Software Development :: Libraries :: Application Frameworks", - "Topic :: Software Development :: Libraries :: Python Modules", - "License :: OSI Approved :: Apache Software License", -] -keywords = ["LAM", "action", "automation", "LLM", "NLP", "RAG", "selenium", "playwright"] -homepage = "https://lavague.ai" -repository = "https://github.com/lavague-ai/LaVague/" -documentation = "https://docs.lavague.ai/en/latest/" -packages = [{include = "lavague/"}] - -[tool.poetry.dependencies] -python = "^3.10.0" -lavague-core = "^0.2.33" -pyyaml = "^6.0.1" -ImageHash = "^4.3.1" - - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" diff --git a/lavague-integrations/contexts/lavague-contexts-fireworks/README.md b/lavague-integrations/contexts/lavague-contexts-fireworks/README.md deleted file mode 100644 index 66c94761..00000000 --- a/lavague-integrations/contexts/lavague-contexts-fireworks/README.md +++ /dev/null @@ -1 +0,0 @@ -# Fireworks integration for lavague \ No newline at end of file diff --git a/lavague-integrations/contexts/lavague-contexts-fireworks/lavague/contexts/fireworks/__init__.py b/lavague-integrations/contexts/lavague-contexts-fireworks/lavague/contexts/fireworks/__init__.py deleted file mode 100644 index 6ee28259..00000000 --- a/lavague-integrations/contexts/lavague-contexts-fireworks/lavague/contexts/fireworks/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from lavague.contexts.fireworks.base import FireworksContext diff --git a/lavague-integrations/contexts/lavague-contexts-fireworks/lavague/contexts/fireworks/base.py b/lavague-integrations/contexts/lavague-contexts-fireworks/lavague/contexts/fireworks/base.py deleted file mode 100644 index 4daadc72..00000000 --- a/lavague-integrations/contexts/lavague-contexts-fireworks/lavague/contexts/fireworks/base.py +++ /dev/null @@ -1,35 +0,0 @@ -from typing import Optional -from llama_index.llms.fireworks import Fireworks -from llama_index.embeddings.fireworks import FireworksEmbedding -from llama_index.multi_modal_llms.openai import OpenAIMultiModal -import os -from lavague.core.context import Context, DEFAULT_MAX_TOKENS, DEFAULT_TEMPERATURE - 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"Development Status :: 3 - Alpha", - "Intended Audience :: Developers", - "Topic :: Scientific/Engineering :: Artificial Intelligence", - "Topic :: Software Development :: Libraries :: Application Frameworks", - "Topic :: Software Development :: Libraries :: Python Modules", - "License :: OSI Approved :: Apache Software License", -] -keywords = ["LAM", "action", "automation", "LLM", "NLP", "RAG", "selenium", "playwright"] -homepage = "https://lavague.ai" -repository = "https://github.com/lavague-ai/LaVague/" -documentation = "https://docs.lavague.ai/en/latest/" -packages = [{include = "lavague/"}] - -[tool.poetry.dependencies] -python = ">=3.10.0,<3.12" -lavague-core = "^0.2.26" -llama-index-llms-fireworks = "^0.1.6" -llama-index-embeddings-fireworks = "^0.1.2" -llama-index-multi-modal-llms-openai = "^0.1.6" - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" diff --git a/lavague-integrations/contexts/lavague-contexts-gemini/README.md b/lavague-integrations/contexts/lavague-contexts-gemini/README.md deleted file mode 100644 index 7920fc27..00000000 --- a/lavague-integrations/contexts/lavague-contexts-gemini/README.md +++ /dev/null @@ -1 +0,0 @@ -# Gemini integration for lavague \ No newline at end of file diff --git a/lavague-integrations/contexts/lavague-contexts-gemini/lavague/contexts/gemini/__init__.py b/lavague-integrations/contexts/lavague-contexts-gemini/lavague/contexts/gemini/__init__.py deleted file mode 100644 index 8113984a..00000000 --- a/lavague-integrations/contexts/lavague-contexts-gemini/lavague/contexts/gemini/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from lavague.contexts.gemini.base import GeminiContext diff --git a/lavague-integrations/contexts/lavague-contexts-gemini/lavague/contexts/gemini/base.py b/lavague-integrations/contexts/lavague-contexts-gemini/lavague/contexts/gemini/base.py deleted file mode 100644 index 8c52b0a5..00000000 --- a/lavague-integrations/contexts/lavague-contexts-gemini/lavague/contexts/gemini/base.py +++ /dev/null @@ -1,30 +0,0 @@ -from typing import Optional -from llama_index.llms.gemini import Gemini -from llama_index.embeddings.gemini import GeminiEmbedding -from llama_index.multi_modal_llms.gemini import GeminiMultiModal -import os -from lavague.core.context import Context, DEFAULT_MAX_TOKENS, DEFAULT_TEMPERATURE - 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-[package.dependencies] -idna = ">=2.0" -multidict = ">=4.0" - -[metadata] -lock-version = "2.0" -python-versions = "^3.10.0" -content-hash = "2e0271dd5c794ba084e842b55751706acb42757f00354d79e3e71484b2f6aee9" diff --git a/lavague-integrations/contexts/lavague-contexts-gemini/pyproject.toml b/lavague-integrations/contexts/lavague-contexts-gemini/pyproject.toml deleted file mode 100644 index 52e4ebea..00000000 --- a/lavague-integrations/contexts/lavague-contexts-gemini/pyproject.toml +++ /dev/null @@ -1,32 +0,0 @@ -[tool.poetry] -name = "lavague-contexts-gemini" -version = "0.2.1" -description = "gemini integration for lavague" -authors = ["lavague-ai"] -readme = "README.md" -license = "Apache-2.0" -classifiers = [ - "Development Status :: 3 - Alpha", - "Intended Audience :: Developers", - "Topic :: Scientific/Engineering :: Artificial Intelligence", - "Topic :: Software Development :: Libraries :: Application Frameworks", - "Topic :: Software Development :: Libraries :: Python Modules", - "License :: OSI Approved :: Apache Software License", -] -keywords = ["LAM", "action", "automation", "LLM", "NLP", "RAG", "selenium", "playwright"] -homepage = "https://lavague.ai" -repository = "https://github.com/lavague-ai/LaVague/" -documentation = "https://docs.lavague.ai/en/latest/" -packages = [{include = "lavague/"}] - -[tool.poetry.dependencies] -python = "^3.10.0" -lavague-core = "^0.2.28" -llama-index-llms-gemini = "^0.1.8" -llama-index-embeddings-gemini = "^0.1.6" -llama-index-multi-modal-llms-gemini = "^0.1.6" -google-generativeai = "^0.4.1" - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" diff --git a/lavague-integrations/contexts/lavague-contexts-openai/README.md b/lavague-integrations/contexts/lavague-contexts-openai/README.md deleted file mode 100644 index 06802296..00000000 --- a/lavague-integrations/contexts/lavague-contexts-openai/README.md +++ /dev/null @@ -1 +0,0 @@ -# Openai integration for lavague \ No newline at end of file diff --git a/lavague-integrations/contexts/lavague-contexts-openai/lavague/contexts/openai/__init__.py b/lavague-integrations/contexts/lavague-contexts-openai/lavague/contexts/openai/__init__.py deleted file mode 100644 index f55c06a2..00000000 --- a/lavague-integrations/contexts/lavague-contexts-openai/lavague/contexts/openai/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from lavague.contexts.openai.base import OpenaiContext, AzureOpenaiContext diff --git a/lavague-integrations/contexts/lavague-contexts-openai/lavague/contexts/openai/base.py b/lavague-integrations/contexts/lavague-contexts-openai/lavague/contexts/openai/base.py deleted file mode 100644 index 4ee270c7..00000000 --- a/lavague-integrations/contexts/lavague-contexts-openai/lavague/contexts/openai/base.py +++ /dev/null @@ -1,99 +0,0 @@ -from typing import Optional -from llama_index.llms.openai import OpenAI -from llama_index.llms.azure_openai import AzureOpenAI -from llama_index.embeddings.azure_openai import AzureOpenAIEmbedding -from llama_index.embeddings.openai import OpenAIEmbedding -from llama_index.multi_modal_llms.openai import OpenAIMultiModal -from llama_index.multi_modal_llms.azure_openai import AzureOpenAIMultiModal -import os -from lavague.core.context import Context, DEFAULT_MAX_TOKENS, DEFAULT_TEMPERATURE - - -class OpenaiContext(Context): - def __init__( - self, - api_key: Optional[str] = None, - llm: str = "gpt-4o", - mm_llm: str = "gpt-4o", - embedding: str = "text-embedding-3-large", - ) -> Context: - if api_key is None: - api_key = os.getenv("OPENAI_API_KEY") - if api_key is None: - raise ValueError("OPENAI_API_KEY is not set") - return super().__init__( - OpenAI( - api_key=api_key, - model=llm, - max_tokens=DEFAULT_MAX_TOKENS, - temperature=DEFAULT_TEMPERATURE, - ), - OpenAIMultiModal(api_key=api_key, model=mm_llm), - OpenAIEmbedding(api_key=api_key, model=embedding), - OpenAI( - api_key=api_key, - model=llm, - max_tokens=4096, - temperature=DEFAULT_TEMPERATURE, - ), - ) - - -class AzureOpenaiContext(Context): - def __init__( - self, - api_key: Optional[str] = None, - endpoint: Optional[str] = None, - deployment: Optional[str] = None, - llm: str = "got-4o", - mm_llm: str = "got-4o", - mm_llm_endpoint: Optional[str] = None, - mm_llm_deployment: Optional[str] = None, - embedding: str = "text-embedding-3-small", - embedding_deployment: Optional[str] = None, - embedding_endpoint: Optional[str] = None, - api_version: str = "2023-07-01-preview", - ): - if api_key is None: - api_key = os.getenv("AZURE_OPENAI_KEY") - if api_key is None: - raise ValueError("AZURE_OPENAI_API_KEY is not set") - if endpoint is None: - endpoint = os.getenv("AZURE_OPENAI_ENDPOINT") - if endpoint is None: - raise ValueError("AZURE_OPENAI_ENDPOINT is not set") - if deployment is None: - deployment = os.getenv("AZURE_OPENAI_DEPLOYMENT") - if deployment is None: - raise ValueError("AZURE_OPENAI_DEPLOYMENT is not set") - if embedding_deployment is None: - raise ValueError("No embedding_deployment argument passed") - if embedding_endpoint is None: - embedding_endpoint = endpoint - if mm_llm_deployment is None: - mm_llm_deployment = deployment - if mm_llm_endpoint is None: - mm_llm_endpoint = endpoint - return super().__init__( - AzureOpenAI( - api_key=api_key, - model=llm, - deployment_name=deployment, - azure_endpoint=endpoint, - api_version=api_version, - ), - AzureOpenAIMultiModal( - api_key=api_key, - model=mm_llm, - deployment_name=mm_llm_deployment, - azure_endpoint=mm_llm_endpoint, - api_version=api_version, - ), - AzureOpenAIEmbedding( - api_key=api_key, - model=embedding, - azure_endpoint=embedding_endpoint, - deployment_name=embedding_deployment, - api_version=api_version, - ), - ) diff --git a/lavague-integrations/contexts/lavague-contexts-openai/poetry.lock b/lavague-integrations/contexts/lavague-contexts-openai/poetry.lock deleted file mode 100644 index 64326f35..00000000 --- a/lavague-integrations/contexts/lavague-contexts-openai/poetry.lock +++ /dev/null @@ -1,3944 +0,0 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. - -[[package]] -name = "aiohttp" -version = "3.9.5" -description = "Async http client/server framework (asyncio)" -optional = false -python-versions = ">=3.8" -files = [ - {file = "aiohttp-3.9.5-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:fcde4c397f673fdec23e6b05ebf8d4751314fa7c24f93334bf1f1364c1c69ac7"}, - 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-[package.dependencies] -idna = ">=2.0" -multidict = ">=4.0" - -[metadata] -lock-version = "2.0" -python-versions = "^3.10.0" -content-hash = "5b21b2901b911eecefc83b5cc6928bdcee6a4734f05a8862c92cadad4b66c651" diff --git a/lavague-integrations/contexts/lavague-contexts-openai/pyproject.toml b/lavague-integrations/contexts/lavague-contexts-openai/pyproject.toml deleted file mode 100644 index 870e7998..00000000 --- a/lavague-integrations/contexts/lavague-contexts-openai/pyproject.toml +++ /dev/null @@ -1,34 +0,0 @@ -[tool.poetry] -name = "lavague-contexts-openai" -version = "0.2.4" -description = "Openai integration for lavague" -authors = ["lavague-ai"] -readme = "README.md" -license = "Apache-2.0" -classifiers = [ - "Development Status :: 3 - Alpha", - "Intended Audience :: Developers", - "Topic :: Scientific/Engineering :: Artificial Intelligence", - "Topic :: Software Development :: Libraries :: Application Frameworks", - "Topic :: Software Development :: Libraries :: Python Modules", - "License :: OSI Approved :: Apache Software License", -] -keywords = ["LAM", "action", "automation", "LLM", "NLP", "RAG", "selenium", "playwright"] -homepage = "https://lavague.ai" -repository = "https://github.com/lavague-ai/LaVague/" -documentation = "https://docs.lavague.ai/en/latest/" -packages = [{include = "lavague/"}] - -[tool.poetry.dependencies] -python = "^3.10.0" -lavague-core = "^0.2.0" -llama-index-llms-openai = "^0.1.9" -llama-index-embeddings-openai = "^0.1.9" -llama-index-llms-azure-openai = "0.1.10" -llama-index-multi-modal-llms-openai = "^0.1.6" -llama-index-multi-modal-llms-azure-openai = "0.1.4" -llama-index-embeddings-azure-openai = "0.1.11" - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" diff --git a/lavague-integrations/retrievers/lavague-retrievers-cohere/README.md b/lavague-integrations/retrievers/lavague-retrievers-cohere/README.md deleted file mode 100644 index ad90489c..00000000 --- a/lavague-integrations/retrievers/lavague-retrievers-cohere/README.md +++ /dev/null @@ -1 +0,0 @@ -# Cohere retriever for lavague \ No newline at end of file diff --git a/lavague-integrations/retrievers/lavague-retrievers-cohere/lavague/retrievers/cohere/__init__.py b/lavague-integrations/retrievers/lavague-retrievers-cohere/lavague/retrievers/cohere/__init__.py deleted file mode 100644 index 9a55b375..00000000 --- a/lavague-integrations/retrievers/lavague-retrievers-cohere/lavague/retrievers/cohere/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from lavague.retrievers.cohere.base import CohereRetriever diff --git a/lavague-integrations/retrievers/lavague-retrievers-cohere/lavague/retrievers/cohere/base.py b/lavague-integrations/retrievers/lavague-retrievers-cohere/lavague/retrievers/cohere/base.py deleted file mode 100644 index 30695d5a..00000000 --- a/lavague-integrations/retrievers/lavague-retrievers-cohere/lavague/retrievers/cohere/base.py +++ /dev/null @@ -1,44 +0,0 @@ -from typing import Optional -from lavague.core.retrievers import OpsmSplitRetriever -import cohere - - -class CohereRetriever(OpsmSplitRetriever): - """This retriever uses cohere as a backend, which means it will not use the provided embedding model (which can be None)""" - - def __init__( - self, - cohere_model: str = "rerank-english-v3.0", - cohere_api_key: Optional[str] = None, - top_k: int = 5, - rank_fields=["element", "placeholder", "text", "name"], - ): - self.cohere_model = cohere_model - self.cohere_session = cohere.Client(cohere_api_key) - super().__init__(top_k=top_k, rank_fields=rank_fields) - - def _get_results(self, _embedding, query, html): - attributes_list = self._create_nodes_dict(html) - l = len(attributes_list) - list_of_results = [] - for j in range(0, l, 1000): - attr = attributes_list[j : j + 1000] - results = self.cohere_session.rerank( - model=self.cohere_model, - query=query, - documents=attr, - top_n=self.top_k, - return_documents=True, - rank_fields=self.rank_fields, - ) - results = [r.dict() for r in results.results] - for r in results: - r["index"] += j - list_of_results += results - list_of_results = sorted( - list_of_results, key=lambda x: x["relevance_score"], reverse=True - ) - results = list_of_results[: self.top_k] - results_dict = [r["document"] for r in results] - score = [r["relevance_score"] for r in results] - return results_dict, score diff --git a/lavague-integrations/retrievers/lavague-retrievers-cohere/pyproject.toml b/lavague-integrations/retrievers/lavague-retrievers-cohere/pyproject.toml deleted file mode 100644 index 3a6eddff..00000000 --- a/lavague-integrations/retrievers/lavague-retrievers-cohere/pyproject.toml +++ /dev/null @@ -1,29 +0,0 @@ -[tool.poetry] -name = "lavague-retriever-cohere" -version = "0.2.0" -description = "Cohere retriever for lavague" -authors = ["lavague-ai"] -readme = "README.md" -license = "Apache-2.0" -classifiers = [ - "Development Status :: 3 - Alpha", - "Intended Audience :: Developers", - "Topic :: Scientific/Engineering :: Artificial Intelligence", - "Topic :: Software Development :: Libraries :: Application Frameworks", - "Topic :: Software Development :: Libraries :: Python Modules", - "License :: OSI Approved :: Apache Software License", -] -keywords = ["LAM", "action", "automation", "LLM", "NLP", "RAG", "selenium", "playwright"] -homepage = "https://lavague.ai" -repository = "https://github.com/lavague-ai/LaVague/" -documentation = "https://docs.lavague.ai/en/latest/" -packages = [{include = "lavague/"}] - -[tool.poetry.dependencies] -python = "^3.10.0" -lavague-core = "^0.2.0" -cohere = "^5.4.0" - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" diff --git a/lavague-qa/README.md b/lavague-qa/README.md deleted file mode 100644 index 86b95b03..00000000 --- a/lavague-qa/README.md +++ /dev/null @@ -1,32 +0,0 @@ -# Test runner for LaVague - -LaVague QA is a specialized tool to generate pytest files from Gherkin test descriptions. - -## Usage - -``` -Usage: lavague-qa [OPTIONS] - -Options: - -u, --url TEXT URL of the site to test - -f, --feature TEXT Path to the .feature file containing Gherkin - -l, --full-llm Enable full LLM pytest generation - -c, --context TEXT Path of python file containing an initialized context - and token_counter. Defaults to OpenAI GPT4o - -h, --headless Enable headless mode for the browser - -db, --log-to-db Enables logging to a SQLite database - --help Show this message and exit. -``` - - -Some examples are provided in `./features/`: - -```bash -lavague-qa --url https://amazon.fr/ --feature features/demo_amazon.feature -``` -Run `lavague-qa` to run a default example: Wikipedia login test - -## Learn more - -To learn more, please visit our LaVague QA documentation and join our [Discord](https://discord.gg/invite/SDxn9KpqX9) to reach our core team and get support! - diff --git a/lavague-qa/demo_lavague_QA.ipynb b/lavague-qa/demo_lavague_QA.ipynb deleted file mode 100644 index bd74893b..00000000 --- a/lavague-qa/demo_lavague_QA.ipynb +++ /dev/null @@ -1,748 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "le6eYfy0xVZF" - }, - "source": [ - "## Introduction\n", - "\n", - "LaVague QA is a command-line tool that turns Gherkin test specifications into ready-to-use Pytest code for web applications. Built on the LaVague open-source framework, it automates the creation and maintenance of automated tests.\n", - "\n", - "\n", - "### How it works\n", - "\n", - "1. Write test scenarios in natural language using Gherkin.\n", - "2. Run LaVague QA to automatically generate the corresponding Pytest code.\n", - "3. Execute tests or regenerate them as your website evolves." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "qVRXPVjkxVg2" - }, - "source": [ - "# Installation\n", - "\n", - "## Start by installing\n", - "- `lavague-qa`\n", - "- `pytest-bdd`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "8gp_X6hpfDPX", - "outputId": "4b8c2629-c505-4257-d735-b14fd9a7138d" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Collecting lavague-qa\n", - " Downloading lavague_qa-0.0.3-py3-none-any.whl.metadata (2.3 kB)\n", - "Collecting pytest-bdd\n", - " Downloading pytest_bdd-7.2.0-py3-none-any.whl.metadata (42 kB)\n", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m42.2/42.2 kB\u001b[0m \u001b[31m1.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", - "\u001b[?25hRequirement already satisfied: click<9.0.0,>=8.1.7 in /usr/local/lib/python3.10/dist-packages (from lavague-qa) (8.1.7)\n", - 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" Attempting uninstall: termcolor\n", - " Found existing installation: termcolor 2.4.0\n", - " Uninstalling termcolor-2.4.0:\n", - " Successfully uninstalled termcolor-2.4.0\n", - " Attempting uninstall: tenacity\n", - " Found existing installation: tenacity 9.0.0\n", - " Uninstalling tenacity-9.0.0:\n", - " Successfully uninstalled tenacity-9.0.0\n", - " Attempting uninstall: packaging\n", - " Found existing installation: packaging 24.1\n", - " Uninstalling packaging-24.1:\n", - " Successfully uninstalled packaging-24.1\n", - " Attempting uninstall: lxml\n", - " Found existing installation: lxml 4.9.4\n", - " Uninstalling lxml-4.9.4:\n", - " Successfully uninstalled lxml-4.9.4\n", - " Attempting uninstall: seaborn\n", - " Found existing installation: seaborn 0.13.1\n", - " Uninstalling seaborn-0.13.1:\n", - " Successfully uninstalled seaborn-0.13.1\n", - "Successfully installed Mako-1.3.5 courlan-1.3.0 dataclasses-json-0.6.7 dateparser-1.2.0 deprecated-1.2.14 dirtyjson-1.0.8 gherkin-official-28.0.0 h11-0.14.0 htmldate-1.8.1 httpcore-1.0.5 httpx-0.27.0 jedi-0.19.1 jsonpatch-1.33 jsonpointer-3.0.0 justext-3.0.1 langchain-0.1.20 langchain-community-0.0.38 langchain-core-0.1.52 langchain-text-splitters-0.0.2 langsmith-0.1.96 lavague-core-0.2.32 lavague-drivers-selenium-0.2.12 lavague-qa-0.0.3 lavague-tests-0.0.4 llama-cloud-0.0.11 llama-index-0.10.56 llama-index-agent-openai-0.2.9 llama-index-cli-0.1.13 llama-index-core-0.10.56 llama-index-embeddings-openai-0.1.11 llama-index-indices-managed-llama-cloud-0.2.7 llama-index-legacy-0.9.48 llama-index-llms-openai-0.1.26 llama-index-multi-modal-llms-openai-0.1.8 llama-index-program-openai-0.1.6 llama-index-question-gen-openai-0.1.3 llama-index-readers-file-0.1.32 llama-index-readers-llama-parse-0.1.6 llama-index-retrievers-bm25-0.1.5 llama-parse-0.4.9 lxml-5.2.2 lxml-html-clean-0.1.1 marshmallow-3.21.3 mypy-extensions-1.0.0 openai-1.38.0 orjson-3.10.6 outcome-1.3.0.post0 packaging-23.2 parse-1.20.2 parse-type-0.6.2 pypdf-4.3.1 pytest-bdd-7.2.0 rank-bm25-0.2.2 seaborn-0.13.2 selenium-4.23.1 striprtf-0.0.26 tenacity-8.3.0 termcolor-2.3.0 tiktoken-0.7.0 tld-0.13 trafilatura-1.12.0 trio-0.26.1 trio-websocket-0.11.1 typing-inspect-0.9.0 wsproto-1.2.0 yaspin-3.0.2\n" - ] - } - ], - "source": [ - "!pip install lavague-qa pytest-bdd" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IGyjrXB60H2K" - }, - "source": [ - "### Get the `OPENAI_API_KEY` from the environment.\n", - "\n", - "Add your key to the secrets tab if you're running in colab" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "izuMPtAgfV9z" - }, - "outputs": [], - "source": [ - "import os\n", - "\n", - "# Check if running in Google Colab\n", - "try:\n", - " from google.colab import userdata\n", - " IN_COLAB = True\n", - "except ImportError:\n", - " IN_COLAB = False\n", - "\n", - "if IN_COLAB:\n", - " os.environ[\"OPENAI_API_KEY\"] = userdata.get('OPENAI_API_KEY')\n", - "else:\n", - " os.environ[\"OPENAI_API_KEY\"] = os.getenv('OPENAI_API_KEY')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZlAiObzVxqb-" - }, - "source": [ - "# 1. Define test scenario\n", - "We fetch a `.feature` file from the LaVague repository and display it" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "9kf0Wa9PfFWW", - "outputId": "92ff7bf9-c5f3-41a4-80db-b275faf6b6f8" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--2024-08-05 07:11:30-- https://raw.githubusercontent.com/lavague-ai/LaVague/rework-qa-automation-example/lavague-qa/features/demo_wikipedia.feature\n", - "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n", - "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n", - "HTTP request sent, awaiting response... 200 OK\n", - "Length: 426 [text/plain]\n", - "Saving to: ‘demo_wikipedia.feature’\n", - "\n", - "\rdemo_wikipedia.feat 0%[ ] 0 --.-KB/s \rdemo_wikipedia.feat 100%[===================>] 426 --.-KB/s in 0s \n", - "\n", - "2024-08-05 07:11:30 (8.91 MB/s) - ‘demo_wikipedia.feature’ saved [426/426]\n", - "\n" - ] - } - ], - "source": [ - "!wget https://raw.githubusercontent.com/lavague-ai/LaVague/main/lavague-qa/features/demo_wikipedia.feature" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "j86Dxofyxzmx", - "outputId": "d50674e1-4230-4b74-e39f-dfe260dba89c" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Feature: Wikipedia Login\n", - "\n", - " Scenario: User logs in successfully\n", - " Given the user is on the Wikipedia homepage\n", - " When the user navigates to the login page\n", - " And the user enters Lavague-test in the username field\n", - " And the user enters lavaguetest123 in the password field\n", - " And the user clicks on login under the username and password field\n", - " Then the login is successful and the user is redirected to the main page\n" - ] - } - ], - "source": [ - "!cat demo_wikipedia.feature" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "UpQQiMJfxqWy" - }, - "source": [ - "# 2. Run LaVague QA\n", - "\n", - "LaVague QA is a CLI tool, as such, we run it with `!` in notebooks.\n", - "\n", - "We will run in `--headless` mode since colab cannot display a browser window. LaVague will run all steps defined in your tests and record actions and selectors. If you're running locally, you can remove this flag." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "-3PQURTSfT-A", - "outputId": "1c58d796-9fe9-406f-8ff6-39ce6ba7d8fc" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[nltk_data] Downloading package stopwords to\n", - "[nltk_data] /usr/local/lib/python3.10/dist-\n", - "[nltk_data] packages/llama_index/legacy/_static/nltk_cache...\n", - "[nltk_data] Unzipping corpora/stopwords.zip.\n", - "[nltk_data] Downloading package punkt to\n", - "[nltk_data] /usr/local/lib/python3.10/dist-\n", - "[nltk_data] packages/llama_index/legacy/_static/nltk_cache...\n", - "[nltk_data] Unzipping tokenizers/punkt.zip.\n", - "/usr/local/lib/python3.10/dist-packages/lavague/core/__init__.py:21: UserWarning: \u001b[93mTelemetry is turned on. To turn off telemetry, set your LAVAGUE_TELEMETRY to 'NONE'\u001b[0m\n", - " warnings.warn(warning_message, UserWarning)\n", - "Ready to generate tests on https://en.wikipedia.org/ for Feature: Wikipedia Login\n", - "\n", - " Scenario: User logs in successfully\n", - " Given the user is on the Wikipedia homepage\n", - " When the user navigates to the login page\n", - " And the user enters Lavague-test in the username field\n", - " And the user enters lavaguetest123 in the password field\n", - " And the user clicks on login under the username and password field\n", - " Then the login is successful and the user is redirected to the main page\n", - "\n", - "2024-08-05 07:11:55,274 - INFO - Screenshot folder cleared\n", - "2024-08-05 07:12:00,389 - INFO - Thoughts:\n", - "- The current screenshot shows the main page of Wikipedia.\n", - "- The objective is to navigate to the login page.\n", - "- Wikipedia typically has a 'Log in' link at the top right corner of the page.\n", - "- The next step should involve clicking on the 'Log in' link to navigate to the login page.\n", - "\n", - "Next engine: Navigation Engine\n", - "Instruction: Click on the 'Log in' link at the top right corner of the page.\n", - "2024-08-05 07:12:05,627 - ERROR - Navigation error: No element found.\n", - "2024-08-05 07:12:07,751 - ERROR - Navigation error: No element found.\n", - "2024-08-05 07:12:11,813 - ERROR - Navigation error: No element found.\n", - "2024-08-05 07:12:13,841 - ERROR - Navigation error: No element found.\n", - "2024-08-05 07:12:15,968 - ERROR - Navigation error: No element found.\n", - "2024-08-05 07:12:19,780 - INFO - Thoughts:\n", - "- The current screenshot shows the Wikipedia homepage with a pop-up about Wikipedia's new colors.\n", - "- The previous instruction to click on the 'Log in' link at the top right corner of the page failed.\n", - "- The pop-up might be obstructing the 'Log in' link, preventing the click action from succeeding.\n", - "- The next step should involve closing the pop-up to access the 'Log in' link.\n", - "\n", - "Next engine: Navigation Engine\n", - "Instruction: Click on the 'X' button to close the pop-up about Wikipedia's new colors.\n", - "2024-08-05 07:12:30,628 - INFO - Thoughts:\n", - "- The current screenshot shows the main page of Wikipedia.\n", - "- The previous step was to close the pop-up about Wikipedia's new colors, which has been successfully done.\n", - "- The objective is to enter 'lavaguetest123' in the password field.\n", - "- The next step is to navigate to the login page to find the password field.\n", - "\n", - "Next engine: Navigation Engine\n", - "Instruction: Click on the 'Log in' link at the top right corner of the page.\n", - "2024-08-05 07:12:40,619 - INFO - Thoughts:\n", - "- The current screenshot shows the login page of Wikipedia.\n", - "- The objective is to click on the 'Log in' button under the username and password fields.\n", - "- The 'Log in' button is clearly visible and can be interacted with.\n", - "\n", - "Next engine: Navigation Engine\n", - "Instruction: Click on the 'Log in' button under the username and password fields.\n", - "2024-08-05 07:12:51,043 - INFO - Thoughts:\n", - "- The current screenshot shows the login page of Wikipedia.\n", - "- The previous instruction to click on the 'Log in' button under the username and password fields was executed.\n", - "- The login attempt failed because the username and password fields were not filled out.\n", - "- To successfully log in, the username and password fields need to be filled with valid credentials before clicking the 'Log in' button again.\n", - "\n", - "Next engine: Navigation Engine\n", - "Instruction: Enter a valid username in the 'Username' field and a valid password in the 'Password' field, then click on the 'Log in' button.\n", - "Scenario might not be completed\n", - "◠\u001b[0m Generating pytest...Traceback (most recent call last):\n", - " File \"/usr/local/bin/lavague-qa\", line 8, in \n", - " sys.exit(cli())\n", - " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 1157, in __call__\n", - " return self.main(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 1078, in main\n", - " rv = self.invoke(ctx)\n", - " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 1434, in invoke\n", - " return ctx.invoke(self.callback, **ctx.params)\n", - " File \"/usr/local/lib/python3.10/dist-packages/click/core.py\", line 783, in invoke\n", - " return __callback(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/lavague/qa/cli.py\", line 78, in cli\n", - " pytest_generator.generate()\n", - " File \"/usr/local/lib/python3.10/dist-packages/lavague/qa/generator.py\", line 116, in generate\n", - " code = self._build_pytest_file(logs, assert_code)\n", - " File \"/usr/local/lib/python3.10/dist-packages/lavague/qa/generator.py\", line 196, in _build_pytest_file\n", - " pytest_code += self._generate_when_steps(logs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/lavague/qa/generator.py\", line 216, in _generate_when_steps\n", - " when_steps += self._get_pytest_when(\n", - " File \"/usr/local/lib/python3.10/dist-packages/lavague/qa/generator.py\", line 229, in _get_pytest_when\n", - " \"\\n\".join([INDENT + get_nav_action_code(a[\"action\"]) for a in actions])\n", - " File \"/usr/local/lib/python3.10/dist-packages/lavague/qa/generator.py\", line 229, in \n", - " \"\\n\".join([INDENT + get_nav_action_code(a[\"action\"]) for a in actions])\n", - " File \"/usr/local/lib/python3.10/dist-packages/lavague/qa/utils.py\", line 61, in get_nav_action_code\n", - " args = action[\"args\"]\n", - "KeyError: 'args'\n", - "◝\u001b[0m Generating pytest..." - ] - } - ], - "source": [ - "!lavague-qa --headless --url https://en.wikipedia.org/ --feature ./demo_wikipedia.feature" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-qiFeTZcxqZW" - }, - "source": [ - "We now display the pytest file generated." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "vJq8GqrWxyzz" - }, - "outputs": [], - "source": [ - "!cat generated_tests/demo_wikipedia.py" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4Q22_gCb0nyJ" - }, - "source": [ - "## Run the following cell if in colab, otherwise you can skip this cell.\n", - "\n", - "Since colab only allows headless browsers, we need to inject a `--headless` argument to our pytest fixture before we start the brower driver.\n", - "\n", - "This cell opens the file, replaces the code and writes the file back to disk." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "n9EVUcKJqiuo" - }, - "outputs": [], - "source": [ - "FILE_PATH = \"generated_tests/demo_wikipedia.py\"\n", - "\n", - "REPLACEMENT = (\n", - "\"\"\"from selenium.webdriver.chrome.options import Options\n", - " from selenium import webdriver\n", - " options = Options()\n", - " options.add_argument(\"--headless\")\n", - " options.add_argument(\"--no-sandbox\")\n", - " driver = webdriver.Chrome(options=options)\"\"\"\n", - ")\n", - "\n", - "\n", - "import os\n", - "\n", - "# read file\n", - "with open(FILE_PATH, 'r') as file:\n", - " content = file.read()\n", - "\n", - "modified_content = content.replace(\"driver = webdriver.Chrome()\", REPLACEMENT)\n", - "\n", - "# write file\n", - "with open(FILE_PATH, 'w') as file:\n", - " file.write(modified_content)\n", - "\n", - "print(f\"Updated file: {FILE_PATH}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "oG4Jfg4CxVoL" - }, - "source": [ - "Let's look at the file after injecting a new fixture." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "u1jnT_SPrvBO" - }, - "outputs": [], - "source": [ - "!cat generated_tests/demo_wikipedia.py" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "3TqmM0ot1f9G" - }, - "source": [ - "# Run the tests\n", - "\n", - "We can now run tests using `pytest`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "hfI9D57IgIvp" - }, - "outputs": [], - "source": [ - "!pytest generated_tests/demo_wikipedia.py" - ] - } - ], - "metadata": { - "colab": { - "provenance": [] - }, - "kernelspec": { - "display_name": "Python 3", - "name": "python3" - }, - "language_info": { - "name": "python" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} diff --git a/lavague-qa/features/demo_amazon.feature b/lavague-qa/features/demo_amazon.feature deleted file mode 100644 index 10cf2695..00000000 --- a/lavague-qa/features/demo_amazon.feature +++ /dev/null @@ -1,12 +0,0 @@ -Feature: Cart - - Scenario: Add and remove a single product from cart - Given the user is on the homepage - When the user clicks on "Accepter" to accept cookies - And the user enters "Zero to One" into the search bar and press Enter - And the user clicks on the first product in the search results - And the user clicks on the "Ajouter au panier" button - And the confirmation message is displayed - And the user clicks on "Aller au panier" under "Passer la commande" - And the user clicks on "Supprimer" from the cart page - Then the cart should be empty diff --git a/lavague-qa/features/demo_hsbc.feature b/lavague-qa/features/demo_hsbc.feature deleted file mode 100644 index e953124d..00000000 --- a/lavague-qa/features/demo_hsbc.feature +++ /dev/null @@ -1,11 +0,0 @@ -Feature: HSBC navigation - - Scenario: Multi tab navigation - Given the user is on the HSBC homepage - When the user clicks on "Tout accepter" to accept cookies - And the user clicks on "Global Banking and Markets" - And the user clicks on "Je comprends, continuons" - And the user navigates to the new tab opened - And the user clicks on "Accept all cookies" - And the user clicks on "About us" - Then the user should be on the "About us" page of the "Global Banking and Markets" services of HSBC diff --git a/lavague-qa/features/demo_laposte.feature b/lavague-qa/features/demo_laposte.feature deleted file mode 100644 index 46723320..00000000 --- a/lavague-qa/features/demo_laposte.feature +++ /dev/null @@ -1,11 +0,0 @@ -Feature: Shipping cost calculator - - Scenario: Estimate shipping costs for a large package - Given the user is on the homepage - When the user clicks on "J'accepte" to accept cookies - And the user clicks on "Envoyer un colis" - And the user clicks on the "Format du colis" dropdown under "Dimension" - And the user clicks on "Volumineux & tube" from the dropdown results - And the user enters 15 in the "Poids" field - And the user waist for the cost to update - Then the cost should be "34,70 €" diff --git a/lavague-qa/features/demo_wikipedia.feature b/lavague-qa/features/demo_wikipedia.feature deleted file mode 100644 index 7c44db75..00000000 --- a/lavague-qa/features/demo_wikipedia.feature +++ /dev/null @@ -1,9 +0,0 @@ -Feature: Wikipedia Login - - Scenario: User logs in successfully - Given the user is on the Wikipedia homepage - When the user navigates to the login page - And the user enters Lavague-test in the username field - And the user enters lavaguetest123 in the password field - And the user clicks on login under the username and password field - Then the login is successful and the user is redirected to the main page diff --git a/lavague-qa/gradio_demo.py b/lavague-qa/gradio_demo.py deleted file mode 100644 index 07a74098..00000000 --- a/lavague-qa/gradio_demo.py +++ /dev/null @@ -1,440 +0,0 @@ -from io import BytesIO -import os -from typing import List, Optional, Tuple -from lavague.contexts.openai.base import OpenaiContext -from lavague.core.agent import WebAgent -import gradio as gr -from lavague.core.memory import ShortTermMemory -from lavague.core.retrievers import SemanticRetriever -from lavague.core.world_model import WorldModel -from lavague.qa.generator import Scenario, TestGenerator -from lavague.drivers.selenium import SeleniumDriver, BrowserbaseRemoteConnection -from lavague.core.action_engine import ActionEngine -from PIL import Image -from gherkin.parser import Parser -from urllib.parse import urlparse - - -def uri_validator(x): - try: - result = urlparse(x) - return all([result.scheme, result.netloc]) - except AttributeError: - return False - - -class GradioQADemo: - """ - Launch an agent gradio demo of lavague-qa - - Args: - driver (`BaseDriver`): - The driver - context (`ActionContext`): - An action context - """ - - html = """ -
-
    -
-
- """ - - css = """ - .my-button { - height: 100px; /* Increase the height of the buttons */ - width: 100%; /* Make sure the button takes the full width */ - max-width: 300px; /* Optional: set a max width */ - max-height: 80px; - font-size: 1.1rem; /* Increase font size */ - } - .button-container { - display: flex; - justify-content: center; /* Center buttons horizontally */ - align-items: center; /* Center buttons vertically */ - height: 100%; /* Ensure it takes up the full height */ - width: 100%; /* Ensure it takes up the full width */ - } - """ - - title = """ -
-
- -
-
-

LaVague - QA

-
-
- """ - - title_history = """ -
-

Steps

-
- """ - - def __init__( - self, - objective: str, - instructions: Optional[List[str]], - agent: WebAgent = None, - user_data=None, - screenshot_ratio: float = 1, - use_browserbase=False, - ): - self.use_browserbase = use_browserbase - self.objective = objective - self.instructions = instructions - self.agent = agent - self.user_data = user_data - self.previous_val = None - self.screenshot_ratio = screenshot_ratio - self.api_key = "" - self.retriever = None - self.scenarios = None - self.feature_file_content = None - self.scenario = None - self.llm = None - self.code = "" - - @staticmethod - def _read_scenarios(gherkin: str) -> Tuple[List[Scenario], str]: - scenarios: List[Scenario] = [] - feature_file_content = gherkin - parser = Parser() - parsed_feature = parser.parse(feature_file_content) - parsed_scenarios = parsed_feature["feature"]["children"] - - for parsed_scenario in parsed_scenarios: - scenario = Scenario(parsed_scenario["scenario"]["name"]) - scenarios.append(scenario) - last_keyword: str = None - - for step in parsed_scenario["scenario"]["steps"]: - keyword = step["keywordType"] - if keyword == "Conjunction": - keyword = last_keyword - else: - last_keyword = keyword - - if keyword == "Context": - scenario.context.append(step["text"]) - elif keyword == "Action": - scenario.steps.append(step["text"]) - elif keyword == "Outcome": - scenario.expect.append(step["text"]) - else: - print("Parser missing", step) - - return scenarios, feature_file_content - - def _fill_example(self, file: str, url: str): - def fill_example_impl(): - file_str = open("features/" + file, "r") - objective = file_str.read() - url_input = url - return url_input, objective - - return fill_example_impl - - def _show_code(self): - def show_code_impl(browser: gr.Image, code: gr.Markdown): - browser = gr.Image( - label="Browser", interactive=False, height="100%", visible=False - ) - code = gr.Markdown(visible=True, value=self.code) - return browser, code - - return show_code_impl - - def _init_driver(self): - def init_driver_impl(url, img, api_key): - if len(api_key) == 0 and os.getenv("OPENAI_API_KEY") is None: - raise gr.Error("An OpenAI API Key is needed to run the agent.") - elif not uri_validator(url): - raise gr.Error("Please specify a valid URL.") - else: - if self.use_browserbase: - browserbase_connection = BrowserbaseRemoteConnection( - "http://connect.browserbase.com/webdriver", - api_key=os.environ["BROWSERBASE_API_KEY"], - project_id=os.environ["BROWSERBASE_PROJECT_ID"], - ) - selenium_driver = SeleniumDriver( - remote_connection=browserbase_connection - ) - if self.agent is None: - if self.use_browserbase == False: - selenium_driver = SeleniumDriver(headless=True) - openai_content = OpenaiContext( - api_key=api_key if len(api_key) > 0 else None - ) - openai_content.mm_llm.max_new_tokens = 2000 - self.llm = openai_content.llm - self.retriever = SemanticRetriever( - embedding=openai_content.embedding, xpathed_only=False - ) - action_engine = ActionEngine.from_context( - context=openai_content, driver=selenium_driver - ) - world_model = WorldModel.from_context(context=openai_content) - agent = WebAgent(world_model, action_engine) - agent.set_origin("lavague-qa-gradio-hf") - self.agent = agent - - if self.use_browserbase: - self.agent.driver = selenium_driver - - self.agent.get(url) - ret = self.agent.action_engine.driver.get_screenshot_as_png() - ret = BytesIO(ret) - ret = Image.open(ret) - img = ret - return url, img - - return init_driver_impl - - def _process_instructions(self): - def process_instructions_impl(objective, url_input, image_display, history): - original_url = url_input - self.scenarios, self.feature_file_content = self._read_scenarios(objective) - self.scenario = self.scenarios[0] - msg = gr.ChatMessage( - role="assistant", content="⏳ Thinking of next steps..." - ) - history.append(msg) - yield objective, url_input, image_display, history - self.agent.action_engine.set_gradio_mode_all( - True, objective, url_input, image_display, history - ) - self.agent.clean_screenshot_folder = False - self.agent.st_memory = ShortTermMemory() - self.agent.prepare_run() - nb_steps = 1 - for index, step in enumerate(self.scenario.steps): - yield from self.agent._run_step_gradio( - step, index, objective, url_input, image_display, history - ) - nb_steps = index - yield from self.agent._run_step_gradio( - " and ".join(self.scenario.expect), - nb_steps, - objective, - url_input, - image_display, - history, - ) - if self.agent.result: - history[-1] = gr.ChatMessage( - role="assistant", - content=f"{self.agent.result.output}", - metadata={"title": f"Scenario completed successfully"}, - ) - else: - history[-1] = gr.ChatMessage( - role="assistant", - content="", - metadata={"title": f"Scenario might not be completed"}, - ) - history.append( - gr.ChatMessage( - role="assistant", - content="The Pytest code is currently generated.", - metadata={"title": f"Generating Pytest..."}, - ) - ) - yield ( - objective, - url_input, - image_display, - history, - ) - logs = self.agent.logger.return_pandas() - html = self.agent.driver.get_html() - html_chunks = self.retriever.retrieve(self.scenario.expect[0], [html]) - assert_code = TestGenerator._generate_assert_code( - self.scenario.expect[0], html_chunks, self.llm - ) - code = TestGenerator._build_pytest_file( - logs, assert_code, self.scenario, original_url, "gradio.gherkin" - ) - self.code = "```python" + code + "```" - - history[-1] = gr.ChatMessage( - role="assistant", - content="The code is ready to use.", - metadata={"title": f"PyTest generated"}, - ) - yield ( - objective, - url_input, - image_display, - history, - ) - if self.use_browserbase: - self.agent.driver.destroy() - return objective, url_input, image_display, history - - return process_instructions_impl - - def __add_message(self): - def add_message(history, message, browser: gr.Image, code_display: gr.Markdown): - browser = gr.Image( - label="Browser", interactive=False, height="100%", visible=True - ) - code = gr.Markdown(visible=False, value="") - history.clear() - return history, browser, code - - return add_message - - def refresh_img_dislay(self, url, image_display): - img = self.agent.driver.get_screenshot_as_png() - img = BytesIO(img) - img = Image.open(img) - if self.screenshot_ratio != 1: - img = img.resize( - ( - int(img.width / self.screenshot_ratio), - int(img.height / self.screenshot_ratio), - ) - ) - image_display = img - return url, image_display - - def launch(self, server_port=7860, share=True, debug=True): - with gr.Blocks( - gr.themes.Default(primary_hue="blue", secondary_hue="neutral"), css=self.css - ) as demo: - with gr.Tab("Agent - QA"): - with gr.Row(): - gr.HTML(self.title) - - with gr.Row(variant="panel", equal_height=True): - with gr.Column(): - with gr.Row(): - with gr.Column(scale=8): - url_input = gr.Textbox( - scale=8, - type="text", - label="Enter URL and press 'Enter' to load the page.", - visible=True, - max_lines=1, - interactive=True, - ) - with gr.Row(): - txt = gr.Markdown("## Example scenarios: ") - with gr.Row(): - with gr.Blocks( - elem_id="button-container", fill_height=True - ): - ex1 = gr.Button( - "Wikipedia's login", - elem_classes="my-button", - ) - ex2 = gr.Button( - "Amazon cart feature", - elem_classes="my-button", - ) - ex3 = gr.Button( - "Navigation on HSBC", - elem_classes="my-button", - ) - ex1.click() - with gr.Column(scale=2): - objective_input = gr.Textbox( - value=self.objective, - scale=2, - type="text", - label="Enter here your Gherkin", - visible=True, - lines=5, - max_lines=5, - interactive=True, - ) - send_btn = gr.Button("Launch agent") - - with gr.Row(variant="panel", equal_height=True): - with gr.Column(scale=8): - image_display = gr.Image( - label="Browser", interactive=False, height="100%" - ) - code_display = gr.Markdown(visible=False) - with gr.Column(scale=2): - chatbot = gr.Chatbot( - [], - label="QA output", - elem_id="history", - type="messages", - bubble_full_width=False, - height="100%", - placeholder="QA output will be shown here\n", - layout="bubble", - ) - with gr.Tab("API keys"): - api_key = gr.Textbox( - value="", - type="text", - label="Please write your OpenAI API Key here", - visible=True, - max_lines=1, - interactive=True, - ) - - send_btn.click( - self.__add_message(), - inputs=[chatbot, objective_input, image_display, code_display], - outputs=[chatbot, image_display, code_display], - ).then( - self._init_driver(), - inputs=[url_input, image_display, api_key], - outputs=[url_input, image_display], - ).success( - self._process_instructions(), - inputs=[ - objective_input, - url_input, - image_display, - chatbot, - ], - outputs=[ - objective_input, - url_input, - image_display, - chatbot, - ], - ).then( - self._show_code(), - inputs=[image_display, code_display], - outputs=[image_display, code_display], - ) - url_input.submit( - self._init_driver(), - inputs=[url_input, image_display, api_key], - outputs=[url_input, image_display], - ) - ex1.click( - fn=self._fill_example( - "demo_wikipedia.feature", "https://en.wikipedia.org" - ), - inputs=[], - outputs=[url_input, objective_input], - ) - ex2.click( - fn=self._fill_example("demo_amazon.feature", "https://amazon.fr"), - inputs=[], - outputs=[url_input, objective_input], - ) - ex3.click( - fn=self._fill_example("demo_hsbc.feature", "https://www.hsbc.fr/"), - inputs=[], - outputs=[url_input, objective_input], - ) - - demo.launch(server_port=server_port, share=True, debug=True) - - -grad = GradioQADemo("", None, None) -grad.launch() diff --git a/lavague-qa/lavague/qa/__init__.py b/lavague-qa/lavague/qa/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/lavague-qa/lavague/qa/cli.py b/lavague-qa/lavague/qa/cli.py deleted file mode 100644 index 081f78b9..00000000 --- a/lavague-qa/lavague/qa/cli.py +++ /dev/null @@ -1,78 +0,0 @@ -import click -import os -from lavague.qa.generator import TestGenerator -from lavague.tests.cli import _load_context - -default_feature = None -default_url = None - -cwd = os.getcwd() -for path in ( - "/lavague-qa/features/demo_wikipedia.feature", - "/features/demo_wikipedia.feature", -): - if os.path.exists(cwd + path): - default_feature = cwd + path - default_url = "https://en.wikipedia.org/" - break - - -@click.command() -@click.option( - "--url", - "-u", - type=str, - default=default_url, - required=True, - help="URL of the site to test", -) -@click.option( - "--feature", - "-f", - default=default_feature, - type=str, - required=True, - help="Path to the .feature file containing Gherkin", -) -@click.option( - "--full-llm", - "-l", - is_flag=True, - required=False, - help="Enable full LLM pytest generation", -) -@click.option( - "--context", - "-c", - type=str, - default=None, - required=False, - help="Path of python file containing an initialized context and token_counter. Defaults to OpenAI GPT4o", -) -@click.option( - "--headless", - "-h", - is_flag=True, - required=False, - help="Enable headless mode for the browser", -) -@click.option( - "--log-to-db", - "-db", - is_flag=True, - required=False, - help="Enables logging to a SQLite database", -) -def cli( - url: str, - feature: str, - full_llm: bool, - context: str, - headless: bool, - log_to_db: bool, -) -> None: - context, token_counter = _load_context(context) - pytest_generator = TestGenerator( - context, url, feature, full_llm, token_counter, headless, log_to_db - ) - pytest_generator.generate() diff --git a/lavague-qa/lavague/qa/generator.py b/lavague-qa/lavague/qa/generator.py deleted file mode 100644 index 37c0dd29..00000000 --- a/lavague-qa/lavague/qa/generator.py +++ /dev/null @@ -1,295 +0,0 @@ -import os -from typing import List, Tuple -import yaml -import time -from yaspin import yaspin -from yaspin.spinners import Spinners -from gherkin.parser import Parser -from selenium.webdriver.chrome.webdriver import WebDriver - -from llama_index.llms.openai import OpenAI -from llama_index.multi_modal_llms.openai import OpenAIMultiModal -from llama_index.embeddings.openai import OpenAIEmbedding -from llama_index.legacy.readers.file.base import SimpleDirectoryReader -from lavague.core import WorldModel, ActionEngine -from lavague.core.agent import WebAgent -from lavague.core.context import Context -from lavague.core.token_counter import TokenCounter -from lavague.core.retrievers import SemanticRetriever -from lavague.drivers.selenium import SeleniumDriver -from lavague.qa.utils import ( - remove_comments, - clean_llm_output, - build_run_summary, - to_snake_case, - get_nav_action_code, - get_nav_control_code, - INDENT, - INDENT_PASS, -) -from lavague.qa.prompts import ( - FULL_PROMPT_TEMPLATE, - ASSERT_ONLY_PROMPT_TEMPLATE, - PYTEST_HEADER_TEMPLATE, - PYTEST_GIVEN_TEMPLATE, - PYTEST_WHEN_TEMPLATE, - PYTEST_THEN_TEMPLATE, -) - - -class Scenario: - def __init__(self, name: str): - self.name = name - self.context: List[str] = [] - self.steps: List[str] = [] - self.expect: List[str] = [] - - def __str__(self) -> str: - return f"Context: {self.context}\nSteps: {self.steps}\nExpect: {self.expect}" - - def __repr__(self) -> str: - return f"Scenario({str(self)})" - - -class TestGenerator: - def __init__( - self, - context: Context, - url: str, - feature_file_path: str, - full_llm: bool, - token_counter: TokenCounter, - headless: bool, - log_to_db: bool, - ): - self.context = context - self.url = url - self.feature_file_path = feature_file_path - self.full_llm = full_llm - self.token_counter = token_counter - self.headless = headless - self.log_to_db = log_to_db - - # parse feature - self.scenarios, self.feature_file_content = self._read_scenarios( - feature_file_path - ) - self.scenario = self.scenarios[0] - - # setup target directory and file paths - self.generated_dir = "./generated_tests" - self._setup_file_paths() - - # instantiate LLMs for Pytest generation from context - self.llm = self.context.llm - self.mm_llm = self.context.mm_llm - self.mm_llm.max_new_tokens = 2000 - self.retriever = SemanticRetriever( - embedding=self.context.embedding, xpathed_only=False - ) - print(f"Ready to generate tests on {self.url} for {self.feature_file_content}") - - def _setup_file_paths(self): - self.feature_file_name = os.path.basename(self.feature_file_path) - self.code_file_name = f"{self.feature_file_name.replace('.feature', '')}{'_llm' if self.full_llm else ''}.py" - self.final_pytest_path = os.path.join(self.generated_dir, self.code_file_name) - self.final_feature_path = os.path.join( - self.generated_dir, self.feature_file_name - ) - - def generate(self): - start_time = time.time() - logs, html = self._run_lavague_agent() - html_chunks = self.retriever.retrieve(self.scenario.expect[0], [html]) - - # start timer and spinner for pytest generation - spinner = yaspin(Spinners.arc, text="Generating pytest...") - spinner.start() - if self.full_llm: - actions, screenshot = self._process_logs(logs) - prompt = self._build_prompt(html_chunks, actions) - code = self._generate_pytest(prompt, screenshot) - else: - assert_code = TestGenerator._generate_assert_code( - self.scenario.expect[0], html_chunks, self.llm - ) - code = TestGenerator._build_pytest_file( - logs, assert_code, self.scenario, self.url, self.feature_file_name - ) - - self._write_files(code) - - # end timer and spinner - spinner.stop() - end_time = time.time() - execution_time = end_time - start_time - print( - build_run_summary( - logs, self.final_feature_path, self.final_pytest_path, execution_time - ) - ) - - def _run_lavague_agent(self): - from lavague.core.utilities.telemetry import send_telemetry - - selenium_driver = SeleniumDriver(headless=self.headless) - action_engine = ActionEngine.from_context( - context=self.context, driver=selenium_driver - ) - world_model = WorldModel.from_context(context=self.context) - agent = WebAgent(world_model, action_engine, token_counter=self.token_counter) - agent.set_origin("lavague-qa") - agent.get(self.url) - time.sleep(1) - - if self.full_llm: - objective = f"Run these scenarios step by step. Make sure you complete each step: {self.feature_file_content}" - agent.run(objective, log_to_db=self.log_to_db) - else: - agent.prepare_run() - for step in self.scenario.steps: - agent.run_step(step) - scenario_completion = agent.run_step(" and ".join(self.scenario.expect)) - send_telemetry(agent.logger.return_pandas(), origin="lavague-qa") - if scenario_completion: - print("Scenario completed successfully", scenario_completion.output) - else: - print("Scenario might not be completed") - - return agent.logger.return_pandas(), selenium_driver.get_html() - - def _process_logs(self, logs): - logs["action"] = logs["code"].dropna().apply(remove_comments) - cleaned_logs = logs[["instruction", "action"]].fillna("") - actions = "\n\n".join( - cleaned_logs["instruction"] + " " + cleaned_logs["action"] - ) - last_screenshot = SimpleDirectoryReader( - logs.iloc[-1]["screenshots_path"] - ).load_data() - return actions, last_screenshot - - def _build_prompt(self, nodes, actions): - return FULL_PROMPT_TEMPLATE.format( - feature_file_name=self.feature_file_name, - url=self.url, - feature_file_content=self.feature_file_content, - expect=self.scenario.expect[0], - nodes=nodes, - actions=actions, - ) - - def _generate_pytest(self, prompt, screenshot): - code = self.mm_llm.complete(prompt, image_documents=screenshot).text - return clean_llm_output(code) - - @staticmethod - def _generate_assert_code(expect: str, html_chunks: str, llm: any) -> str: - prompt = ASSERT_ONLY_PROMPT_TEMPLATE.format( - expect=expect, - html_chunks=html_chunks, - ) - code = llm.complete(prompt).text - code = code.replace("```python", "").replace("```", "") - code = code.replace("# assert code here", "") - return "\n".join([INDENT + l for l in code.splitlines()]) - - @staticmethod - def _build_pytest_file(logs, assert_code, scenario, url, feature_file_name): - pytest_code = PYTEST_HEADER_TEMPLATE.format( - url=url, feature_file_name=feature_file_name - ) - pytest_code += TestGenerator._generate_given_steps(scenario) - pytest_code += TestGenerator._generate_when_steps(logs, scenario) - pytest_code += TestGenerator._generate_then_step(assert_code, scenario) - return pytest_code - - @staticmethod - def _generate_given_steps(scenario): - given_steps = "" - for index, setup in enumerate(scenario.context): - step = setup.replace("'", "\\'") - method_name = to_snake_case(setup) - code = "browser.get(BASE_URL)" if index == 0 else "pass" - given_steps += PYTEST_GIVEN_TEMPLATE.format( - step=step, method_name=method_name, code=code - ) - return given_steps - - @staticmethod - def _generate_when_steps(logs, scenario): - when_steps = "" - for index, row in logs.iterrows(): - if index < len(scenario.steps): - gherkin_step = scenario.steps[index] - when_steps += TestGenerator._get_pytest_when( - gherkin_step, row["engine"], row["code"], row["instruction"] - ) - return when_steps - - @staticmethod - def _get_pytest_when( - gherkin_step: str, engine: str, engine_log: str, instruction: str - ) -> str: - step = gherkin_step.replace("'", "\\'") - method_name = to_snake_case(gherkin_step) - if engine == "Navigation Engine": - actions = yaml.safe_load(engine_log)[0]["actions"] - actions_code = ( - "\n".join([INDENT + get_nav_action_code(a["action"]) for a in actions]) - or INDENT_PASS - ) - elif engine == "Navigation Controls": - actions_code = INDENT + get_nav_control_code(instruction) - else: - actions_code = INDENT_PASS - return PYTEST_WHEN_TEMPLATE.format( - step=step, method_name=method_name, actions_code=actions_code - ) - - @staticmethod - def _generate_then_step(assert_code, scenario): - step = scenario.expect[0].replace("'", "\\'") - method_name = to_snake_case(scenario.expect[0]) - return PYTEST_THEN_TEMPLATE.format( - step=step, method_name=method_name, assert_code=assert_code - ) - - def _write_files(self, code): - os.makedirs(self.generated_dir, exist_ok=True) - with open(self.final_feature_path, "w") as file: - file.write(self.feature_file_content) - with open(self.final_pytest_path, "w") as file: - file.write(code) - - @staticmethod - def _read_scenarios(feature_file_path: str) -> Tuple[List[Scenario], str]: - scenarios: List[Scenario] = [] - with open(feature_file_path, "r", encoding="utf8") as file: - feature_file_content = file.read() - parser = Parser() - parsed_feature = parser.parse(feature_file_content) - parsed_scenarios = parsed_feature["feature"]["children"] - - for parsed_scenario in parsed_scenarios: - scenario = Scenario(parsed_scenario["scenario"]["name"]) - scenarios.append(scenario) - last_keyword: str = None - - for step in parsed_scenario["scenario"]["steps"]: - keyword = step["keywordType"] - if keyword == "Conjunction": - keyword = last_keyword - else: - last_keyword = keyword - - if keyword == "Context": - scenario.context.append(step["text"]) - elif keyword == "Action": - scenario.steps.append(step["text"]) - elif keyword == "Outcome": - scenario.expect.append(step["text"]) - else: - print("Parser missing", step) - - return scenarios, feature_file_content diff --git a/lavague-qa/lavague/qa/prompts.py b/lavague-qa/lavague/qa/prompts.py deleted file mode 100644 index 83421335..00000000 --- a/lavague-qa/lavague/qa/prompts.py +++ /dev/null @@ -1,296 +0,0 @@ -from llama_index.core import PromptTemplate - - -PYTEST_HEADER_TEMPLATE = PromptTemplate( - """ -import pytest -from pytest_bdd import scenarios, given, when, then -from selenium import webdriver -from selenium.webdriver.common.by import By -from selenium.webdriver.support.ui import WebDriverWait, Select -from selenium.webdriver.support import expected_conditions as EC - -# Constants -BASE_URL = '{url}' - -# Scenarios -scenarios('{feature_file_name}') - -# Fixtures -@pytest.fixture -def browser(): - driver = webdriver.Chrome() - driver.implicitly_wait(10) - yield driver - driver.quit() - -# Steps -""" -) - -PYTEST_GIVEN_TEMPLATE = PromptTemplate( - """@given('{step}') -def {method_name}(browser: webdriver.Chrome): - {code} -""" -) - -PYTEST_WHEN_TEMPLATE = PromptTemplate( - """@when('{step}') -def {method_name}(browser: webdriver.Chrome): -{actions_code} -""" -) - -PYTEST_THEN_TEMPLATE = PromptTemplate( - """@then('{step}') -def {method_name}(browser: webdriver.Chrome): -{assert_code} -""" -) - - -FULL_PROMPT_TEMPLATE = PromptTemplate( - """You are an expert in software testing frameworks and Python code generation. You answer in python markdown only and nothing else. -Your only goal is to generate pytest-bdd files based on the provided Gherkin feature, a collection of instructions and actions, and a specific assert statement to test. -You will use the provided information to generate a valid assert statement. -- Name the scenario appropriately. -- Always use time.sleep(3) if waiting is required. -- Include all necessary imports and fixtures. -- Use provided actions to find valid XPath selectors for the final pytest file. -- You answer in python code only and nothing else. - -I will provide an example below: ----------- -Feature file name: example.feature - -URL: https://www.example.com - -Gherkin of the feature to be tested: - -Feature: E-commerce Website Interaction - - Scenario: Browse products and checkout - Given I am on the example website - When I navigate to the product catalog - And I filter products by category - And I sort products by price - And I add a random product to the cart - And I proceed to checkout - Then the cart total should be correct - -Assert statement Then the cart total should be correct - -List of already executed instructions and actions: -- instruction: Navigate to the product catalog page - actions: - - action: - name: "click" - args: - xpath: "/html/body/div[1]/header/nav/ul/li[3]/a" - value: "" - -- instruction: Select a category from the dropdown filter - actions: - - action: - name: "click" - args: - xpath: "/html/body/div[2]/main/div/div[1]/aside/div[3]/select/option[3]" - value: "" - -- instruction: Sort products by price - actions: - - action: - name: "click" - args: - xpath: "/html/body/div[2]/main/div/div[2]/div[1]/div/button[2]" - value: "" - -- instruction: Add a random product to the cart - actions: - - action: - name: "click" - args: - xpath: "/html/body/div[2]/main/div/div[2]/ul/li[5]/div/button[@data-testid='add-to-cart']" - value: "" - -- instruction: Proceed to checkout - actions: - - action: - name: "click" - args: - xpath: "/html/body/div[1]/header/div[2]/div/div/a" - value: "" - - -Resulting pytest code: -import pytest -from pytest_bdd import scenarios, given, when, then, parsers -from selenium import webdriver -from selenium.webdriver.common.by import By -from selenium.webdriver.support.ui import WebDriverWait -from selenium.webdriver.support import expected_conditions as EC -from selenium.common.exceptions import ElementClickInterceptedException -import time -import random - -# Constants -BASE_URL = 'https://example.com' - -# Scenarios -scenarios('complex_example.feature') - -# Fixtures -@pytest.fixture -def browser(): - driver = webdriver.Chrome() - driver.implicitly_wait(10) - yield driver - driver.quit() - -# Steps -@given('I am on the example website') -def go_to_homepage(browser): - browser.get(BASE_URL) - -@when('I navigate to the product catalog') -def navigate_to_catalog(browser): - catalog_link = WebDriverWait(browser, 10).until( - EC.element_to_be_clickable((By.XPATH, "/html/body/div[1]/header/nav/ul/li[3]/a")) - ) - try: - browser.execute_script("arguments[0].click();", catalog_link) - except ElementClickInterceptedException: - pytest.fail("Failed to navigate to the product catalog") - -@when('I filter products by category') -def filter_products(browser): - category_dropdown = WebDriverWait(browser, 10).until( - EC.presence_of_element_located((By.XPATH, "/html/body/div[2]/main/div/div[1]/aside/div[3]/select")) - ) - options = category_dropdown.find_elements(By.TAG_NAME, "option") - random_option = random.choice(options[1:]) # Exclude the first option if it's a placeholder - random_option.click() - -@when('I sort products by price') -def sort_products(browser): - sort_button = WebDriverWait(browser, 10).until( - EC.element_to_be_clickable((By.XPATH, "/html/body/div[2]/main/div/div[2]/div[1]/div/button[2]")) - ) - try: - browser.execute_script("arguments[0].click();", sort_button) - except ElementClickInterceptedException: - pytest.fail("Failed to sort products") - -@when('I add a random product to the cart') -def add_to_cart(browser): - products = browser.find_elements(By.XPATH, "/html/body/div[2]/main/div/div[2]/ul/li") - random_product = random.choice(products) - add_to_cart_button = random_product.find_element(By.XPATH, ".//button[@data-testid='add-to-cart']") - try: - browser.execute_script("arguments[0].click();", add_to_cart_button) - except ElementClickInterceptedException: - pytest.fail("Failed to add product to cart") - -@when('I proceed to checkout') -def proceed_to_checkout(browser): - checkout_button = WebDriverWait(browser, 10).until( - EC.element_to_be_clickable((By.XPATH, "/html/body/div[1]/header/div[2]/div/div/a")) - ) - try: - browser.execute_script("arguments[0].click();", checkout_button) - except ElementClickInterceptedException: - pytest.fail("Failed to proceed to checkout") - -@then('I should see the checkout form') -def verify_checkout_form(browser): - try: - WebDriverWait(browser, 10).until( - EC.presence_of_element_located((By.ID, "checkout-form")) - ) - except Exception as e: - pytest.fail("Checkout form not found: " + str(e)) - -@then('the cart total should be correct') -def verify_cart_total(browser): - try: - total_element = WebDriverWait(browser, 10).until( - EC.presence_of_element_located((By.ID, "cart-total")) - ) - total_value = float(total_element.text.replace('$', '')) - assert total_value > 0, "Cart total should be greater than zero" - except Exception as e: - pytest.fail("Failed to verify cart total" + str(e)) - -@then('the product list should be visible') -def verify_product_list(browser): - try: - WebDriverWait(browser, 10).until( - EC.presence_of_element_located((By.CLASS_NAME, "product-list")) - ) - except Exception as e: - pytest.fail("Product list not found: " + str(e)) - -@then('the category filter should be available') -def verify_category_filter(browser): - try: - filter_element = WebDriverWait(browser, 10).until( - EC.presence_of_element_located((By.ID, "category-filter")) - ) - assert filter_element.is_enabled(), "Category filter should be enabled" - except Exception as e: - pytest.fail("Category filter not found or not enabled: " + str(e)) - -@then('the "Add to Cart" button should be present for each product') -def verify_add_to_cart_buttons(browser): - try: - add_to_cart_buttons = WebDriverWait(browser, 10).until( - EC.presence_of_all_elements_located((By.CSS_SELECTOR, "button[data-testid='add-to-cart']")) - ) - assert len(add_to_cart_buttons) > 0, "No 'Add to Cart' buttons found" - except Exception as e: - pytest.fail("Failed to verify 'Add to Cart' buttons: " + str(e)) - ----------- -Given this information, generate a valid pytest-bdd file with the following inputs: -Feature file name: {feature_file_name} -URL: {url} -Gherkin of the feature to be tested:{feature_file_content} -Assert statement: {expect}\n -Potentially relevant nodes that you may use to help you generate the assert code: {nodes}\n -List of already executed instructions and actions:\n -{actions}\n -""" -) - -ASSERT_ONLY_PROMPT_TEMPLATE = PromptTemplate( - """You are an expert in software testing frameworks and Python code generation. You answer in python markdown only and nothing else. -Your only goal is to use the provided Gherkin and HTML nodes to generate a valid pytest-bdd python assert statement. -- Include all necessary imports and fixtures. -- If element selection is needed, prefer XPath based on class or text content to fetch it. -- You answer in python code only and nothing else. -- You have access to a browser variable of type selenium.webdriver.chrome.webdriver.Chrome - -```python -browser: WebDriver -# assert code here -``` - -I will provide an example below: ----------- -Gherkin: Then the cost should be "34,70 €" -HTML:
Cost:34,70 €
- -Resulting pytest code: -cost_element = WebDriverWait(browser, 10).until( - EC.presence_of_element_located((By.XPATH, "//span[@class='calculator__cta__price']")) -) -actual_cost = cost_element.text.strip() -assert actual_cost == expected_cost - ----------- -Given this information, generate a valid pytest-bdd assert instruction with the following inputs: -Gherkin expect of the feature to be tested: Then {expect}\n -Potentially relevant HTML that you may use to help you generate the assert code: {html_chunks}\n -""" -) diff --git a/lavague-qa/lavague/qa/utils.py b/lavague-qa/lavague/qa/utils.py deleted file mode 100644 index 0de4237f..00000000 --- a/lavague-qa/lavague/qa/utils.py +++ /dev/null @@ -1,120 +0,0 @@ -import re -from lavague.core.utilities.pricing_util import build_summary_table - - -INDENT = " " -INDENT_PASS = INDENT + "pass" - - -def remove_comments(code): - return "\n".join( - [line for line in code.split("\n") if not line.strip().startswith("#")] - ) - - -def clean_llm_output(code: str) -> str: - return code.replace("```python", "").replace("```", "").replace("```\n", "") - - -def build_run_summary(logs, final_feature_path, final_pytest_path, execution_time): - token_summary = { - "world_model_input_tokens": 0, - "world_model_output_tokens": 0, - "action_engine_input_tokens": 0, - "action_engine_output_tokens": 0, - "total_world_model_tokens": 0, - "total_action_engine_tokens": 0, - "total_embedding_tokens": 0, - "total_world_model_cost": 0.0, - "total_action_engine_cost": 0.0, - "total_embedding_cost": 0.0, - "total_step_tokens": 0, - "total_step_cost": 0.0, - } - for key in token_summary.keys(): - if key in logs.columns: - token_summary[key] += logs[key].sum() - - summary = "" - summary += f"\nFinished generating tests in {execution_time:.1f}s\n\n" - summary += f" Feature file: {final_feature_path}\n" - summary += f" Pytest file: {final_pytest_path}\n" - # turn off TokenCounter output as it counts only the LaVague run and not the pytest generation - # summary += build_summary_table(token_summary, verbose=False) - - summary += f"\nRun the following command to execute your tests:\n\n pytest {final_pytest_path}\n" - - return summary - - -# all utils below are used for building the pytest file without LLMs -def to_snake_case(s: str): - s = s.lower() - s = re.sub(r"[^\w\s]", "_", s) - s = re.sub(r"\s+", "_", s) - s = re.sub(r"__+", "_", s) - return s.strip("_") - - -def get_nav_action_code(action): - action_name = action["name"] - args = action["args"] - xpath = None if args is None else args.get("xpath") - - if action_name == "click": - return get_click_action(xpath) - elif action_name == "setValue": - return get_set_value_action(xpath, args["value"]) - elif action_name == "setValueAndEnter": - return get_set_value_action(xpath, args["value"], True) - elif action_name == "dropdownSelect": - return get_select_action(xpath, args["value"]) - - return "pass" - - -def get_nav_control_code(instruction): - if "SCROLL_DOWN" in instruction: - return "browser.scroll_down()" - if "SCROLL_UP" in instruction: - return "browser.scroll_up()" - if "WAIT" in instruction: - return "import time\n time.sleep(5)" - if "BACK" in instruction: - return "browser.back()" - if "SCAN" in instruction: - return "pass" - if "MAXIMIZE_WINDOW" in instruction: - return "browser.maximize_window()" - if "SWITCH_TAB" in instruction: - tab_id = int(instruction.split(" ")[1]) - return f"browser.switch_tab(tab_id={tab_id})" - - -def get_click_action(xpath: str): - return f"""element = WebDriverWait(browser, 10).until( - EC.element_to_be_clickable((By.XPATH, '{xpath}')) - ) - browser.execute_script('arguments[0].click();', element) -""" - - -def get_select_action(xpath, value): - return f"""element = WebDriverWait(browser, 10).until( - EC.element_to_be_clickable((By.XPATH, '{xpath}')) - ) - select = Select(element) - try: - select.select_by_value('{value}') - except: - select.select_by_visible_text('{value}') -""" - - -def get_set_value_action(xpath, value, enter=False): - code = get_click_action(xpath) - code += INDENT + f"element.clear()" - code += "\n" + INDENT + f"element.send_keys('{value}')" - if enter: - code += "\n" + INDENT + f"element.send_keys('\ue007')" - return code diff --git a/lavague-qa/pyproject.toml b/lavague-qa/pyproject.toml deleted file mode 100644 index e41d95c2..00000000 --- a/lavague-qa/pyproject.toml +++ /dev/null @@ -1,36 +0,0 @@ -[tool.poetry] -name = "lavague-qa" -version = "0.0.6" -description = "QA Automation with LaVague" -authors = ["lavague-ai"] -readme = "README.md" -license = "Apache-2.0" -classifiers = [ - "Development Status :: 3 - Alpha", - "Intended Audience :: Developers", - "Topic :: Scientific/Engineering :: Artificial Intelligence", - "Topic :: Software Development :: Libraries :: Application Frameworks", - "Topic :: Software Development :: Libraries :: Python Modules", - "License :: OSI Approved :: Apache Software License", -] -keywords = ["QA", "testing", "automation", "cypress", "agents", "RAG", "selenium", "ai"] -homepage = "https://lavague.ai" -repository = "https://github.com/lavague-ai/LaVague/" -documentation = "https://docs.lavague.ai/en/latest/" -packages = [{include = "lavague/"}] - -[tool.poetry.dependencies] -python = "^3.10.0" -lavague-core = "^0.2.33" -lavague-tests = "^0.0.4" -lavague-drivers-selenium = "^0.2.6" -gherkin-official = "^28.0.0" -click = "^8.1.7" -yaspin = "^3.0.2" - -[tool.poetry.scripts] -lavague-qa = "lavague.qa.cli:cli" - -[build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" diff --git a/lavague-qa/qa_automation_rework.ipynb b/lavague-qa/qa_automation_rework.ipynb deleted file mode 100644 index 4c72f22c..00000000 --- a/lavague-qa/qa_automation_rework.ipynb +++ /dev/null @@ -1,183 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Using LaVague for QA Automation\n", - "\n", - "In this notebook, we'll show how LaVague can be used to automatically generate pytest files from a Gherkin test definition.\n", - "\n", - "We will use the `TestGenerator` class that powers the `lavague-qa` CLI you can use to generate your tests fast. \n", - "\n", - "We will use LaVague to autonomously run the test and record xpath and actions. We'll then use an LLM to generate assert statements and the final reusable test file. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from lavague.qa.generator import TestGenerator\n", - "import os\n", - "\n", - "example_features = {\n", - " \"demo_hsbc\": {\n", - " \"path\": \"./features/demo_hsbc.feature\",\n", - " \"url\": \"http://hsbc.fr/\"\n", - " },\n", - " \"demo_dev\": {\n", - " \"path\": \"./features/demo_dev.feature\",\n", - " \"url\": \"http://google.com/\"\n", - " },\n", - " \"demo_laposte\": {\n", - " \"path\": \"./features/demo_laposte.feature\",\n", - " \"url\": \"http://laposte.fr/\"\n", - " },\n", - " \"demo_amazon\": {\n", - " \"path\": \"./features/demo_amazon.feature\",\n", - " \"url\": \"http://amazon.com/\"\n", - " },\n", - " \"demo_wikipedia\": {\n", - " \"path\": \"./features/demo_wikipedia.feature\",\n", - " \"url\": \"http://en.wikipedia.org\"\n", - " }\n", - "}\n", - "\n", - "feature = example_features[\"demo_dev\"]\n", - "\n", - "generator = TestGenerator(feature[\"url\"], feature[\"path\"], headless=False, log_to_db=True)\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "logs, nodes = generator.run_lavague_agent()\n", - "logs.head()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "actions, screenshot = generator.process_logs(logs)\n", - "print(actions)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "prompt = generator.build_prompt(nodes, actions)\n", - "print(prompt)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "code = generator.generate_pytest(prompt, screenshot)\n", - "print(code)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "generator.write_files(code)\n", - "print(\n", - " f\"\\nTests successfully generated\\n - Run `pytest {generator.code_file_name}` to run the generated test.\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Run tests\n", - "\n", - "We can finally run our generated test to see it in action" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!pytest demo_amazon.py" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!pytest demo_laposte.py" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!pytest demo_wikipedia.py" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!pytest demo_hsbc.py" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!pytest demo_dev.py" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "lavague-Oj4z07SL-py3.11", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.2" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/lavague-server/README.md b/lavague-server/README.md deleted file mode 100644 index be1728e4..00000000 --- a/lavague-server/README.md +++ /dev/null @@ -1,25 +0,0 @@ -# Agent Server for lavague - -## Setup LaVague Driver Server - -Uses WebSockets to provide LaVague features to Agents. - -```shell -pip install lavague-core lavague-server -``` - -```python -from lavague.core import WorldModel, ActionEngine -from lavague.core.agents import WebAgent -from lavague.server.driver import DriverServer -from lavague.server import AgentServer, AgentSession - -def create_agent(session: AgentSession): - world_model = WorldModel() - driver = DriverServer(session) - action_engine = ActionEngine(driver) - return WebAgent(world_model, action_engine) - -server = AgentServer(create_agent) -server.serve() -``` \ No newline at end of file diff --git a/lavague-server/lavague/server/__init__.py b/lavague-server/lavague/server/__init__.py deleted file mode 100644 index 1e1a63c8..00000000 --- a/lavague-server/lavague/server/__init__.py +++ /dev/null @@ -1,2 +0,0 @@ -from lavague.server.base import AgentServer -from lavague.server.channel import AgentSession diff --git a/lavague-server/lavague/server/base.py b/lavague-server/lavague/server/base.py deleted file mode 100644 index 75cfb7ac..00000000 --- a/lavague-server/lavague/server/base.py +++ /dev/null @@ -1,27 +0,0 @@ -from typing import Callable -from lavague.core.agent import WebAgent -from lavague.server.websocket_channel import WebSocketHandler -from lavague.server.channel import CommunicationChannel - - -class AgentServer: - def __init__( - self, - agent_factory: Callable[[], WebAgent], - communication_channel: CommunicationChannel = None, - port: int = 8000, - ): - if communication_channel is None: - communication_channel = WebSocketHandler(port) - self.communication_channel = communication_channel - self.communication_channel.agent_factory = agent_factory - - def serve(self): - try: - self.communication_channel.start() - except KeyboardInterrupt: - print("The server was interrupted.") - pass - - def close(self): - self.communication_channel.close() diff --git a/lavague-server/lavague/server/channel.py b/lavague-server/lavague/server/channel.py deleted file mode 100644 index 96fd57f7..00000000 --- a/lavague-server/lavague/server/channel.py +++ /dev/null @@ -1,183 +0,0 @@ -from abc import ABC, abstractmethod -import asyncio -import json -import threading -from typing import Callable -import uuid -from lavague.core.agent import WebAgent -from lavague.core.extractors import YamlFromMarkdownExtractor -from llama_index.core import QueryBundle -from lavague.core.retrievers import ( - FromXPathNodesExpansionRetriever, - InteractiveXPathRetriever, - RetrieversPipeline, - SemanticRetriever, -) -import types -import copy -import re - - -class AgentSession(ABC): - agent: WebAgent - - def __init__(self): - self.uid = str(uuid.uuid4()) - self._task: threading.Thread = None - - @abstractmethod - async def send_message(self, message: str): - pass - - @abstractmethod - async def send_message_for_result(self, message: str, id: str) -> any: - pass - - def exe_start_stop(self, run: Callable): - asyncio.run(self.send_message(json.dumps({"type": "start"}))) - try: - run() - except Exception: - pass - finally: - try: - asyncio.run( - self.send_message( - json.dumps({"type": "stop", "args": self.agent.interrupted}) - ) - ) - except: - print("The stop signal could not be sent") - - def handle_prompt_agent_action(self, type: str, args: str, id: str): - match type: - case "run": - self.exe_start_stop(lambda: self.agent.run(args)) - - case "run_step": - self.exe_start_stop(lambda: self.agent.run_step(args)) - - case "get": - self.agent.get(args) - - case "prepare_run": - self.agent.prepare_run() - - case "navigate": - self.exe_start_stop( - lambda: self.agent.action_engine.navigation_engine.execute_instruction( - args - ) - ) - - case "nav_action": - self.exe_start_stop( - lambda: self.agent.action_engine.navigation_engine.execute_action( - args - ) - ) - - case "retrieve": - args_obj = json.loads(args) - retriever = RetrieversPipeline( - InteractiveXPathRetriever(self.agent.driver), - FromXPathNodesExpansionRetriever( - chunk_size=args_obj.get("contextExpansionSize", 750) - ), - SemanticRetriever( - embedding=None, top_k=args_obj.get("semanticTopK", 5) - ), - ) - html = retriever.retrieve( - QueryBundle(query_str=args_obj.get("query", "")), - [self.agent.driver.get_html()], - ) - xpaths = re.findall(r'xpath=["\'](.*?)["\']', "".join(html)) - asyncio.run( - self.send_message( - json.dumps({"type": "retrieved", "args": xpaths, "id": id}) - ) - ) - - def handle_agent_message(self, json_message): - if "type" in json_message: - - def exe_task(id): - self.handle_prompt_agent_action( - json_message["type"], json_message["args"], id - ) - - task_id = self.uid - self._task = threading.Thread(target=exe_task, args=(task_id,)) - self._task.start() - - def send_command_and_get_response_sync(self, command, args=""): - id = str(uuid.uuid4()) - event = threading.Event() - response_data = {} - - data = {"command": command, "args": args, "id": id} - - message = json.dumps(data) - - def send_command(): - response = asyncio.run(self.send_message_for_result(message, id)) - response_data["response"] = response - event.set() - - response_thread = threading.Thread(target=send_command) - response_thread.start() - - # Wait for the response - event.wait() - - ret = "" - if "response" in response_data: - try: - jso = response_data["response"] - if "ret" in jso: - ret = jso["ret"] - response_data.clear() - except Exception as e: - print("Failed to get response data", e) - pass - return ret - - -class CommunicationChannel(ABC): - sessions: list[AgentSession] = [] - agent_factory: Callable[[AgentSession], WebAgent] = None - - @abstractmethod - def start(self): - pass - - def stop(self): - for session in self.sessions: - session.stop() - - def add_session(self, session: AgentSession): - session.agent = self.agent_factory(session) - if session.agent is None: - raise Exception("Agent factory must provide an Agent") - self.setup_session_agent(session) - self.sessions.append(session) - - def setup_session_agent(self, session: AgentSession): - # override extractor for JSON format - session.agent.action_engine.navigation_engine.extractor = ( - YamlFromMarkdownExtractor() - ) - - # override logger method - add_log = session.agent.logger.add_log - - def send_log(self, message): - message_cp = copy.deepcopy(message) - add_log(message_cp) - if "screenshots" in message_cp: - del message_cp["screenshots"] - message_cp = {"type": "agent_log", "agent_log": message_cp} - asyncio.run(session.send_message(json.dumps(message_cp))) - - session.agent.logger.add_log = types.MethodType(send_log, session.agent.logger) diff --git a/lavague-server/lavague/server/cli.py b/lavague-server/lavague/server/cli.py deleted file mode 100644 index 0003f936..00000000 --- a/lavague-server/lavague/server/cli.py +++ /dev/null @@ -1,30 +0,0 @@ -import click -from lavague.server import AgentSession -from lavague.core import WorldModel, ActionEngine -from lavague.core.agent import WebAgent -from lavague.server.driver import DriverServer -from lavague.server.base import AgentServer - - -@click.command() -@click.option( - "--port", - "-p", - type=int, - required=False, - default=8000, - help="Server port", -) -def cli(port: int) -> None: - def create_agent(session: AgentSession): - world_model = WorldModel() - driver = DriverServer(session) - action_engine = ActionEngine(driver) - return WebAgent(world_model, action_engine) - - server = AgentServer(create_agent, port=port) - server.serve() - - -if __name__ == "__main__": - cli() diff --git a/lavague-server/lavague/server/driver.py b/lavague-server/lavague/server/driver.py deleted file mode 100644 index f1c072c6..00000000 --- a/lavague-server/lavague/server/driver.py +++ /dev/null @@ -1,366 +0,0 @@ -import base64 -import json -import logging -import time -from lavague.core.base_driver import ( - BaseDriver, - InteractionType, - PossibleInteractionsByXpath, -) -from typing import Any, Dict, List, Optional, Mapping - -import yaml -from lavague.server.channel import AgentSession - -logging_print = logging.getLogger(__name__) -logging_print.setLevel(logging.INFO) -format = logging.Formatter("%(asctime)s - %(levelname)s - %(message)s") -ch = logging.StreamHandler() -ch.setLevel(logging.INFO) -ch.setFormatter(format) -logging_print.addHandler(ch) -logging_print.propagate = False - - -class DriverServer(BaseDriver): - def __init__(self, session: AgentSession, url: Optional[str] = None): - self.session = session - super().__init__(url, None) - - def send_command_and_get_response_sync(self, command, args=""): - return self.session.send_command_and_get_response_sync(command, args) - - def default_init_code(self) -> Any: - return None - - def code_for_init(self) -> str: - return "" - - def get_html(self) -> str: - html = self.send_command_and_get_response_sync("get_html") - return html - - def get_driver(self) -> BaseDriver: - return self - - def resize_driver(self, width, height) -> None: - pass - - def code_for_resize(self, width, height) -> str: - "" - - def get_url(self) -> Optional[str]: - url = self.send_command_and_get_response_sync("get_url") - return url - - def code_for_get(self, url: str) -> str: - return "" - - def get(self, url: str) -> None: - self.send_command_and_get_response_sync("get", url) - - def back(self) -> None: - self.send_command_and_get_response_sync("back") - - def code_for_back(self) -> None: - return "" - - def get_screenshot_as_png(self) -> bytes: - scr = self.send_command_and_get_response_sync("get_screenshot") - scr_bytes = base64.b64decode(scr.split(",")[1]) - return scr_bytes - - def destroy(self) -> None: - pass - - def get_tabs(self) -> str: - tab_info = [] - try: - tab_list = self.send_command_and_get_response_sync("get_tabs") - tab_info = json.loads(tab_list) - except Exception as e: - logging_print.error( - f"JSON from the get_tabs method could not be deserialized. Reason: {e}" - ) - tab_info = "\n".join(tab_info) - tab_info = "Tabs opened:\n" + tab_info - - return tab_info - - def switch_tab(self, tab_id: int) -> None: - self.send_command_and_get_response_sync("switch_tab", str(tab_id)) - - def resolve_xpath(self, xpath: str): - pass - - def get_possible_interactions( - self, in_viewport=True, foreground_only=True - ) -> PossibleInteractionsByXpath: - exe: Dict[str, List[str]] = {} - try: - args: Dict[str, bool] = { - "in_viewport": in_viewport, - "foreground_only": foreground_only, - } - exe_json = self.send_command_and_get_response_sync( - "get_possible_interactions", json.dumps(args) - ) - exe = json.loads(exe_json) - except Exception as e: - logging_print.error( - f"JSON from the get_possible_interactions method could not be deserialized. Reason: {e}" - ) - res = dict() - for k, v in exe.items(): - res[k] = set(InteractionType[i] for i in v) - return res - - def get_highlighted_element(self, generated_code: str): - outputs = [] - - data = yaml.safe_load(generated_code) - if not isinstance(data, List): - data = [data] - for item in data: - for action in item["actions"]: - action_name = action["action"]["name"] - if action_name != "fail": - xpath = action["action"]["args"]["xpath"] - try: - bounding_box = {} - viewport_size = {} - - res_json = self.send_command_and_get_response_sync( - "highlight_elem", xpath - ) - res = json.loads(res_json) - - bounding_box["x1"] = res["x"] - bounding_box["y1"] = res["y"] - bounding_box["x2"] = res["x2"] - bounding_box["y2"] = res["y2"] - - viewport_size["width"] = self.execute_script( - "return window.innerWidth;" - ) - viewport_size["height"] = self.execute_script( - "return window.innerHeight;" - ) - output = { - "bounding_box": bounding_box, - "viewport_size": viewport_size, - } - outputs.append(output) - except Exception as e: - logging_print.error( - f"An error occured while rendering the highlighted element: {e}" - ) - return outputs - - def exec_code( - self, - code: str, - globals: dict[str, Any] = None, - locals: Mapping[str, object] = None, - ): - if code is not None and len(code.strip()) > 0: - url = self.send_command_and_get_response_sync("exec_code", code) - return url - else: - return "" - - def execute_script(self, js_code: str, *args) -> Any: - return self.send_command_and_get_response_sync("execute_script", js_code) - - def is_bottom_of_page(self) -> bool: - ret = super().is_bottom_of_page() - return ret["value"] - - def code_for_execute_script(self, js_code: str, *args) -> str: - return ( - f"driver.execute_script({js_code}, {', '.join(str(arg) for arg in args)})" - ) - - def get_screenshots_whole_page(self) -> list[str]: - """Take screenshots of the whole page""" - screenshot_paths = [] - - current_screenshot_folder = self.get_current_screenshot_folder() - - while True: - # Saves a screenshot - screenshot_path = self.save_screenshot(current_screenshot_folder) - screenshot_paths.append(screenshot_path) - self.execute_script("window.scrollBy(0, (window.innerHeight / 1.5));") - self.wait_for_idle() - # Necessary as doing screenshot too fast might hit Chrome internal limits - time.sleep(0.5) - - if self.is_bottom_of_page(): - break - - self.previously_scanned = True - return screenshot_paths - - def wait(self, time_between_actions): - json_str = f"""- actions: - - action: - args: - value: {time_between_actions} - name: "wait" -""" - self.exec_code(json_str) - pass - - def scroll_up(self): - json_str = f"""- actions: - - action: - args: - value: "up" - name: "scroll" -""" - self.exec_code(json_str) - pass - - def scroll_down(self): - json_str = f"""- actions: - - action: - args: - value: "down" - name: "scroll" -""" - self.exec_code(json_str) - pass - - def get_capability(self) -> str: - return REMOTE_PROMPT_TEMPLATE - - def maximize_window(self) -> None: - pass - - -REMOTE_PROMPT_TEMPLATE = """ -You are a chrome extension and your goal is to interact with web pages. You have been given a series of HTML snippets and queries. -Your goal is to return a list of actions that should be done in order to execute the actions. -Always target elements by XPATH. You can only use one of the Xpaths included in the HTML. Do not derive new Xpaths. - -Your response must always be in the YAML format with the yaml markdown indicator and must include the main item "actions" , which will contains the objects "action", which contains the string "name" of tool of choice, and necessary arguments ("args") if required by the tool. -There must be only ONE args sub-object, such as args (if the tool has multiple arguments). -You must always include the comments as well, describing your actions step by step, following strictly the format in the examples provided. - -Provide high level explanations about why you think this element is the right one. -Your answer must be short and concise. Always includes comments in the YAML before listing the actions. - -The actions available are: - -Name: click -Description: Click on an element with a specific xpath -Arguments: - - xpath (string) - -Name: setValue -Description: Focus on and set the value of an input element with a specific xpath -Arguments: - - xpath (string) - - value (string) - -Name: setValueAndEnter -Description: Like "setValue", except then it presses ENTER. Use this tool can submit the form when there's no "submit" button. -Arguments: - - xpath (string) - - value (string) - -Name: enter -Description: Press the enter button. Use this tool can submit the form when there's no "submit" button and when a textbox is already filled, or filled previously with setValue. -Arguments: - - xpath (string) - -Name: fail -Description: Indicate that you are unable to complete the task and explain why. -Arguments: - - xpath (string): Always set to an empty string - - value (string): Detailled explanation of why the task cannot be completed - - -Here are examples of previous answers: -HTML: -
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Privacy -Query: Click on the button labeled 'Alles accepteren' to accept all cookies. -Completion: -```yaml -# Let's think step by step -# First, we notice that the query asks us to click on the button labeled 'Alles accepteren' to accept all cookies. -# In the provided HTML, we can see several button elements. -# We need to identify the correct button labeled 'Alles accepteren'. -# Upon examining the HTML structure, we see that the button with the text 'Alles accepteren' is located within a specific hierarchy. -# We need to navigate through the hierarchy to accurately locate this button. -# The correct button is located within a div element with a specific class and role attribute, which helps us ensure that we are targeting the right element. -# Specifically, for 'Alles accepteren', there is a button element with a unique ID 'L2AGLb' which contains a div with the text 'Alles accepteren'. -# We observe that this button element has the following XPath: -# /html/body/div[2]/div[2]/div[3]/span/div/div/div/div[3]/div[1]/button[2] - -- actions: - - action: - # Thus, we believe this is the correct element to be interacted with: - args: - xpath: "/html/body/div[2]/div[2]/div[3]/span/div/div/div/div[3]/div[1]/button[2]" - value: "" - # Then we can click on the button - name: "click" -``` ------ -HTML: -
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