mirror of
https://github.com/ianarawjo/ChainForge.git
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Add stop button to cancel pending queries (#211)
* Add Stop button * Replaced QueryTracker stop checks in _prompt_llm in query.ts. Modified _prompt_llm and *gen_responses to take in node id for checking purposes. Added new css class for stopping status. * Used callback function instead of passing id to the backend, renamed QueryStopper and some of its functions, made custom error * Added semicolons and one more UserForcedPrematureExit check * Revise canceler to never clear id, and use unique id Date.now instead * Make cancel go into call_llm funcs * Cleanup console logs * Rebuild app and update package version --------- Co-authored-by: Kayla Zethelyn <kaylazethelyn@college.harvard.edu> Co-authored-by: Ian Arawjo <fatso784@gmail.com>
This commit is contained in:
Kayla Z
GitHub
parent
83c49ffe0b
commit
3d15bc9d17
@ -1,15 +1,15 @@
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{
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"files": {
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"main.css": "/static/css/main.d7b7e6a1.css",
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"main.js": "/static/js/main.16bd62df.js",
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"main.css": "/static/css/main.01603dff.css",
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"main.js": "/static/js/main.dd40466e.js",
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"static/js/787.4c72bb55.chunk.js": "/static/js/787.4c72bb55.chunk.js",
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"index.html": "/index.html",
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"main.d7b7e6a1.css.map": "/static/css/main.d7b7e6a1.css.map",
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"main.16bd62df.js.map": "/static/js/main.16bd62df.js.map",
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"main.01603dff.css.map": "/static/css/main.01603dff.css.map",
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"main.dd40466e.js.map": "/static/js/main.dd40466e.js.map",
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"787.4c72bb55.chunk.js.map": "/static/js/787.4c72bb55.chunk.js.map"
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},
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"entrypoints": [
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"static/css/main.d7b7e6a1.css",
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"static/js/main.16bd62df.js"
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"static/css/main.01603dff.css",
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"static/js/main.dd40466e.js"
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]
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}
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@ -1 +1 @@
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<!doctype html><html lang="en"><head><meta charset="utf-8"/><script async src="https://www.googletagmanager.com/gtag/js?id=G-RN3FDBLMCR"></script><script>function gtag(){dataLayer.push(arguments)}window.dataLayer=window.dataLayer||[],gtag("js",new Date),gtag("config","G-RN3FDBLMCR")</script><link rel="icon" href="/favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#000000"/><meta name="description" content="A visual programming environment for prompt engineering"/><link rel="apple-touch-icon" href="/logo192.png"/><link rel="manifest" href="/manifest.json"/><title>ChainForge</title><script defer="defer" src="/static/js/main.16bd62df.js"></script><link href="/static/css/main.d7b7e6a1.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
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<!doctype html><html lang="en"><head><meta charset="utf-8"/><script async src="https://www.googletagmanager.com/gtag/js?id=G-RN3FDBLMCR"></script><script>function gtag(){dataLayer.push(arguments)}window.dataLayer=window.dataLayer||[],gtag("js",new Date),gtag("config","G-RN3FDBLMCR")</script><link rel="icon" href="/favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#000000"/><meta name="description" content="A visual programming environment for prompt engineering"/><link rel="apple-touch-icon" href="/logo192.png"/><link rel="manifest" href="/manifest.json"/><title>ChainForge</title><script defer="defer" src="/static/js/main.dd40466e.js"></script><link href="/static/css/main.01603dff.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
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@ -1,4 +1,4 @@
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import { useRef } from 'react';
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import { useMemo, useRef } from 'react';
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import useStore from './store';
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import { EditText } from 'react-edit-text';
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import 'react-edit-text/dist/index.css';
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@ -10,8 +10,7 @@ import { Tooltip, Popover, Badge, Stack } from '@mantine/core';
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import { IconSparkles } from '@tabler/icons-react';
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export default function NodeLabel({ title, nodeId, icon, onEdit, onSave, editable, status, alertModal, customButtons, handleRunClick, handleRunHover, runButtonTooltip }) {
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const setDataPropsForNode = useStore((state) => state.setDataPropsForNode);
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export default function NodeLabel({ title, nodeId, icon, onEdit, onSave, editable, status, isRunning, alertModal, customButtons, handleRunClick, handleStopClick, handleRunHover, runButtonTooltip }) { const setDataPropsForNode = useStore((state) => state.setDataPropsForNode);
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const [statusIndicator, setStatusIndicator] = useState('none');
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const [runButton, setRunButton] = useState('none');
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const removeNode = useStore((state) => state.removeNode);
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@ -21,6 +20,11 @@ export default function NodeLabel({ title, nodeId, icon, onEdit, onSave, editabl
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const [deleteConfirmProps, setDeleteConfirmProps] = useState({
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title: 'Delete node', message: 'Are you sure?', onConfirm: () => {}
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});
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const stopButton = useMemo(() =>
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<button className="AmitSahoo45-button-3 nodrag" style={{padding: '0px 10px 0px 9px'}} onClick={() => handleStopClick(nodeId)}>
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◼
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</button>
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, [handleStopClick, nodeId]);
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const handleNodeLabelChange = (evt) => {
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const { value } = evt;
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@ -47,9 +51,8 @@ export default function NodeLabel({ title, nodeId, icon, onEdit, onSave, editabl
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if (runButtonTooltip)
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setRunButton(
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<Tooltip label={runButtonTooltip} withArrow arrowSize={6} arrowRadius={2} zIndex={1001} withinPortal={true} >
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{run_btn}
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</Tooltip>
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);
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{run_btn}
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</Tooltip>);
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else
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setRunButton(run_btn);
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}
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@ -58,6 +61,8 @@ export default function NodeLabel({ title, nodeId, icon, onEdit, onSave, editabl
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}
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}, [handleRunClick, runButtonTooltip]);
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useEffect(() => {}, [stopButton])
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const handleCloseButtonClick = useCallback(() => {
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setDeleteConfirmProps({
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title: 'Delete node',
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@ -86,7 +91,7 @@ export default function NodeLabel({ title, nodeId, icon, onEdit, onSave, editabl
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<AlertModal ref={alertModal} />
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<div className="node-header-btns-container">
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{customButtons ? customButtons : <></>}
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{runButton}
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{isRunning ? stopButton : runButton}
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<button className="close-button nodrag" onClick={handleCloseButtonClick}>✕</button>
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<br/>
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</div>
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174
chainforge/react-server/src/PromptNode.js
vendored
174
chainforge/react-server/src/PromptNode.js
vendored
@ -15,6 +15,8 @@ import ChatHistoryView from './ChatHistoryView';
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import InspectFooter from './InspectFooter';
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import { countNumLLMs, setsAreEqual, getLLMsInPulledInputData } from './backend/utils';
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import LLMResponseInspectorDrawer from './LLMResponseInspectorDrawer';
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import CancelTracker from './backend/canceler';
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import { UserForcedPrematureExit } from './backend/errors';
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const getUniqueLLMMetavarKey = (responses) => {
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const metakeys = new Set(responses.map(resp_obj => Object.keys(resp_obj.metavars)).flat());
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@ -125,6 +127,10 @@ const PromptNode = ({ data, id, type: node_type }) => {
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const [progressAnimated, setProgressAnimated] = useState(true);
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const [runTooltip, setRunTooltip] = useState(null);
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// Cancelation of pending queries
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const [cancelId, setCancelId] = useState(Date.now());
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const refreshCancelId = () => setCancelId(Date.now());
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// Debounce helpers
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const debounceTimeoutRef = useRef(null);
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const debounce = (func, delay) => {
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@ -223,9 +229,8 @@ const PromptNode = ({ data, id, type: node_type }) => {
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data['prompt'] = value;
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// Update status icon, if need be:
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if (promptTextOnLastRun !== null && status !== 'warning' && value !== promptTextOnLastRun) {
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if (promptTextOnLastRun !== null && status !== 'warning' && value !== promptTextOnLastRun)
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setStatus('warning');
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}
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refreshTemplateHooks(value);
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};
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@ -529,9 +534,14 @@ const PromptNode = ({ data, id, type: node_type }) => {
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setProgressAnimated(true);
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const rejected = (err) => {
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setStatus('error');
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setContChatToggleDisabled(false);
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triggerAlert(err.message || err);
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if (err instanceof UserForcedPrematureExit || CancelTracker.has(cancelId)) {
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// Handle a premature cancelation
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console.log("Canceled.");
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} else {
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setStatus('error');
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setContChatToggleDisabled(false);
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triggerAlert(err.message || err);
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}
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};
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// Fetch info about the number of queries we'll need to make
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@ -550,7 +560,7 @@ const PromptNode = ({ data, id, type: node_type }) => {
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const max_responses = Object.keys(total_num_responses).reduce((acc, llm) => acc + total_num_responses[llm], 0);
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onProgressChange = (progress_by_llm_key) => {
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if (!progress_by_llm_key) return;
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if (!progress_by_llm_key || CancelTracker.has(cancelId)) return;
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// Update individual progress bars
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const num_llms = _llmItemsCurrState.length;
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@ -584,7 +594,6 @@ const PromptNode = ({ data, id, type: node_type }) => {
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};
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};
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// Run all prompt permutations through the LLM to generate + cache responses:
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const query_llms = () => {
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return fetch_from_backend('queryllm', {
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@ -598,65 +607,23 @@ const PromptNode = ({ data, id, type: node_type }) => {
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no_cache: false,
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progress_listener: onProgressChange,
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cont_only_w_prior_llms: node_type !== 'chat' ? (showContToggle && contWithPriorLLMs) : undefined,
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cancel_id: cancelId,
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}, rejected).then(function(json) {
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if (!json) {
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rejected('Request was sent and received by backend server, but there was no response.');
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}
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else if (json.responses && json.errors) {
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// We have to early exit explicitly because we will still enter this function even if 'rejected' is called
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if (!json && CancelTracker.has(cancelId))
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return;
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// Remove progress bars
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setProgress(undefined);
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setProgressAnimated(false);
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debounce(() => {}, 1)(); // erase any pending debounces
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// Remove progress bars
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setProgress(undefined);
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setProgressAnimated(false);
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debounce(() => {}, 1)(); // erase any pending debounces
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// Store and log responses (if any)
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if (json.responses) {
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setJSONResponses(json.responses);
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// Store and log responses (if any)
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if (json?.responses) {
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setJSONResponses(json.responses);
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// Log responses for debugging:
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console.log(json.responses);
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}
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// If there was at least one error collecting a response...
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const llms_w_errors = Object.keys(json.errors);
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if (llms_w_errors.length > 0) {
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// Remove the total progress bar
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setProgress(undefined);
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// Ensure there's a sliver of error displayed in the progress bar
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// of every LLM item that has an error:
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llmListContainer?.current?.ensureLLMItemsErrorProgress(llms_w_errors);
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// Set error status
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setStatus('error');
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setContChatToggleDisabled(false);
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// Trigger alert and display one error message per LLM of all collected errors:
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let combined_err_msg = "";
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llms_w_errors.forEach(llm_key => {
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const item = _llmItemsCurrState.find((item) => item.key === llm_key);
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combined_err_msg += item?.name + ': ' + JSON.stringify(json.errors[llm_key][0]) + '\n';
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});
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// We trigger the alert directly (don't use triggerAlert) here because we want to keep the progress bar:
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alertModal?.current?.trigger('Errors collecting responses. Re-run prompt node to retry.\n\n'+combined_err_msg);
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return;
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}
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if (responsesWillChange && !showDrawer)
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setUninspectedResponses(true);
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setResponsesWillChange(false);
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// All responses collected! Change status to 'ready':
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setStatus('ready');
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setContChatToggleDisabled(false);
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// Remove individual progress rings
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llmListContainer?.current?.resetLLMItemsProgress();
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// Save prompt text so we remember what prompt we have responses cache'd for:
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setPromptTextOnLastRun(promptText);
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setNumGenerationsLastRun(numGenerations);
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// Log responses for debugging:
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console.log(json.responses);
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// Save response texts as 'fields' of data, for any prompt nodes pulling the outputs
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// We also need to store a unique metavar for the LLM *set* (set of LLM nicknames) that produced these responses,
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@ -668,9 +635,9 @@ const PromptNode = ({ data, id, type: node_type }) => {
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r => {
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// Carry over the response text, prompt, prompt fill history (vars), and llm nickname:
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let o = { text: escapeBraces(r),
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prompt: resp_obj['prompt'],
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fill_history: resp_obj['vars'],
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llm: _llmItemsCurrState.find((item) => item.name === resp_obj.llm) };
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prompt: resp_obj['prompt'],
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fill_history: resp_obj['vars'],
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llm: _llmItemsCurrState.find((item) => item.name === resp_obj.llm) };
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// Carry over any metavars
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o.metavars = resp_obj['metavars'] || {};
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@ -685,12 +652,58 @@ const PromptNode = ({ data, id, type: node_type }) => {
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}
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)).flat()
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});
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// Ping any inspect nodes attached to this node to refresh their contents:
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pingOutputNodes(id);
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} else {
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rejected(json.error || 'Unknown error when querying LLM');
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}
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// If there was at least one error collecting a response...
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const llms_w_errors = json?.errors ? Object.keys(json.errors) : [];
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if (llms_w_errors.length > 0) {
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// Remove the total progress bar
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setProgress(undefined);
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// Ensure there's a sliver of error displayed in the progress bar
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// of every LLM item that has an error:
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llmListContainer?.current?.ensureLLMItemsErrorProgress(llms_w_errors);
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// Set error status
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setStatus('error');
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setContChatToggleDisabled(false);
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// Trigger alert and display one error message per LLM of all collected errors:
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let combined_err_msg = "";
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llms_w_errors.forEach(llm_key => {
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const item = _llmItemsCurrState.find((item) => item.key === llm_key);
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combined_err_msg += item?.name + ': ' + JSON.stringify(json.errors[llm_key][0]) + '\n';
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});
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// We trigger the alert directly (don't use triggerAlert) here because we want to keep the progress bar:
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alertModal?.current?.trigger('Errors collecting responses. Re-run prompt node to retry.\n\n'+combined_err_msg);
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return;
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}
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if (responsesWillChange && !showDrawer)
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setUninspectedResponses(true);
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setResponsesWillChange(false);
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setContChatToggleDisabled(false);
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// Remove individual progress rings
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llmListContainer?.current?.resetLLMItemsProgress();
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if (json?.error || !json) {
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rejected(json?.error ?? 'Request was sent and received by backend server, but there was no response.');
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return;
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}
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// Save prompt text so we remember what prompt we have responses cache'd for:
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setPromptTextOnLastRun(promptText);
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setNumGenerationsLastRun(numGenerations);
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// All responses collected! Change status to 'ready':
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setStatus('ready');
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// Ping any inspect nodes attached to this node to refresh their contents:
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pingOutputNodes(id);
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}, rejected);
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};
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@ -701,6 +714,23 @@ const PromptNode = ({ data, id, type: node_type }) => {
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.catch(rejected);
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};
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const handleStopClick = useCallback(() => {
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CancelTracker.add(cancelId);
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refreshCancelId();
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// Update UI to seem like it's been immediately canceled, even
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// though we cannot fully cancel the queryLLMs Promise.
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// Remove progress bars
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setProgress(undefined);
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setProgressAnimated(false);
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debounce(() => {}, 1)(); // erase any pending debounces
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// Set error status
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setStatus('none');
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setContChatToggleDisabled(false);
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llmListContainer?.current?.resetLLMItemsProgress();
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}, [cancelId, refreshCancelId]);
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const handleNumGenChange = useCallback((event) => {
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let n = event.target.value;
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if (!isNaN(n) && n.length > 0 && /^\d+$/.test(n)) {
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@ -714,7 +744,7 @@ const PromptNode = ({ data, id, type: node_type }) => {
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}, [numGenerationsLastRun, status]);
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const hideStatusIndicator = () => {
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if (status !== 'none') { setStatus('none'); }
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if (status !== 'none') setStatus('none');
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};
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// Dynamically update the textareas and position of the template hooks
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@ -748,8 +778,10 @@ const PromptNode = ({ data, id, type: node_type }) => {
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onEdit={hideStatusIndicator}
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icon={node_icon}
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status={status}
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isRunning = {status === 'loading'}
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alertModal={alertModal}
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handleRunClick={handleRunClick}
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handleStopClick={handleStopClick}
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handleRunHover={handleRunHover}
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runButtonTooltip={runTooltip}
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customButtons={[
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1
chainforge/react-server/src/ScriptNode.js
vendored
1
chainforge/react-server/src/ScriptNode.js
vendored
@ -32,7 +32,6 @@ const ScriptNode = ({ data, id }) => {
|
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if (Object.keys(new_data.scriptFiles).length === 0) {
|
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new_data.scriptFiles[get_id()] = '';
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}
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console.log(new_data);
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setDataPropsForNode(id, new_data);
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}, [data, id, setDataPropsForNode]);
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@ -73,7 +73,7 @@ const TabularDataNode = ({ data, id }) => {
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}));
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return;
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||||
}
|
||||
console.log('handleSaveCell', rowIdx, columnKey, value);
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// console.log('handleSaveCell', rowIdx, columnKey, value);
|
||||
tableData[rowIdx][columnKey] = value;
|
||||
setTableData([...tableData]);
|
||||
}, [tableData, tableColumns, pingOutputNodes]);
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||||
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||||
@ -128,9 +128,7 @@ function decode(mdText: string): Row[] {
|
||||
export async function autofill(input: Row[], n: number, apiKeys?: Dict): Promise<Row[]> {
|
||||
// hash the arguments to get a unique id
|
||||
let id = JSON.stringify([input, n]);
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||||
|
||||
let encoded = encode(input);
|
||||
|
||||
let templateVariables = [...new Set(new StringTemplate(input.join('\n')).get_vars())];
|
||||
|
||||
console.log("System message: ", autofillSystemMessage(n, templateVariables));
|
||||
|
||||
@ -6,6 +6,8 @@ import { APP_IS_RUNNING_LOCALLY, set_api_keys, FLASK_BASE_URL, call_flask_backen
|
||||
import StorageCache from "./cache";
|
||||
import { PromptPipeline } from "./query";
|
||||
import { PromptPermutationGenerator, PromptTemplate } from "./template";
|
||||
import { UserForcedPrematureExit } from "./errors";
|
||||
import CancelTracker from "./canceler";
|
||||
|
||||
// """ =================
|
||||
// SETUP AND GLOBALS
|
||||
@ -547,6 +549,9 @@ export async function fetchEnvironAPIKeys(): Promise<Dict> {
|
||||
* @param chat_histories Either an array of `ChatHistory` (to use across all LLMs), or a dict indexed by LLM nicknames of `ChatHistory` arrays to use per LLM.
|
||||
* @param api_keys (optional) a dict of {api_name: api_key} pairs. Supported key names: OpenAI, Anthropic, Google
|
||||
* @param no_cache (optional) if true, deletes any cache'd responses for 'id' (always calls the LLMs fresh)
|
||||
* @param progress_listener (optional) a callback whenever an LLM response is collected, on the current progress
|
||||
* @param cont_only_w_prior_llms (optional) whether we are continuing using prior LLMs
|
||||
* @param cancel_id (optional) the id that would appear in CancelTracker if the user cancels the querying (NOT the same as 'id' --must be unique!)
|
||||
* @returns a dictionary in format `{responses: StandardizedLLMResponse[], errors: string[]}`
|
||||
*/
|
||||
export async function queryLLM(id: string,
|
||||
@ -558,7 +563,8 @@ export async function queryLLM(id: string,
|
||||
api_keys?: Dict,
|
||||
no_cache?: boolean,
|
||||
progress_listener?: (progress: {[key: symbol]: any}) => void,
|
||||
cont_only_w_prior_llms?: boolean): Promise<Dict> {
|
||||
cont_only_w_prior_llms?: boolean,
|
||||
cancel_id?: string): Promise<Dict> {
|
||||
// Verify the integrity of the params
|
||||
if (typeof id !== 'string' || id.trim().length === 0)
|
||||
return {'error': 'id is improper format (length 0 or not a string)'};
|
||||
@ -635,6 +641,9 @@ export async function queryLLM(id: string,
|
||||
}
|
||||
});
|
||||
|
||||
// Helper function to check whether this process has been canceled
|
||||
const should_cancel = () => CancelTracker.has(cancel_id);
|
||||
|
||||
// For each LLM, generate and cache responses:
|
||||
let responses: {[key: string]: Array<LLMResponseObject>} = {};
|
||||
let all_errors = {};
|
||||
@ -667,11 +676,12 @@ export async function queryLLM(id: string,
|
||||
let errors: Array<string> = [];
|
||||
let num_resps = 0;
|
||||
let num_errors = 0;
|
||||
|
||||
try {
|
||||
console.log(`Querying ${llm_str}...`)
|
||||
|
||||
// Yield responses for 'llm' for each prompt generated from the root template 'prompt' and template variables in 'properties':
|
||||
for await (const response of prompter.gen_responses(_vars, llm_str as LLM, num_generations, temperature, llm_params, chat_hists)) {
|
||||
for await (const response of prompter.gen_responses(_vars, llm_str as LLM, num_generations, temperature, llm_params, chat_hists, should_cancel)) {
|
||||
|
||||
// Check for selective failure
|
||||
if (response instanceof LLMResponseError) { // The request failed
|
||||
@ -694,8 +704,12 @@ export async function queryLLM(id: string,
|
||||
};
|
||||
}
|
||||
} catch (e) {
|
||||
console.error(`Error generating responses for ${llm_str}: ${e.message}`);
|
||||
throw e;
|
||||
if (e instanceof UserForcedPrematureExit) {
|
||||
throw e;
|
||||
} else {
|
||||
console.error(`Error generating responses for ${llm_str}: ${e.message}`);
|
||||
throw e;
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
@ -716,6 +730,7 @@ export async function queryLLM(id: string,
|
||||
all_errors[result.llm_key] = result.errors;
|
||||
});
|
||||
} catch (e) {
|
||||
if (e instanceof UserForcedPrematureExit) throw e;
|
||||
console.error(`Error requesting responses: ${e.message}`);
|
||||
return { error: e.message };
|
||||
}
|
||||
@ -758,6 +773,7 @@ export async function queryLLM(id: string,
|
||||
cache_files: cache_filenames,
|
||||
responses_last_run: res,
|
||||
});
|
||||
|
||||
// Return all responses for all LLMs
|
||||
return {
|
||||
responses: res,
|
||||
@ -1194,4 +1210,4 @@ export async function loadCachedCustomProviders(): Promise<Dict> {
|
||||
}).then(function(res) {
|
||||
return res.json();
|
||||
});
|
||||
}
|
||||
}
|
||||
57
chainforge/react-server/src/backend/canceler.ts
Normal file
57
chainforge/react-server/src/backend/canceler.ts
Normal file
@ -0,0 +1,57 @@
|
||||
import { UserForcedPrematureExit } from "./errors";
|
||||
|
||||
/**
|
||||
* A CancelTracker allows ids to be added, to signal
|
||||
* any associated processes should be 'canceled'. The tracker
|
||||
* operates as a global. It does not cancel anything itself,
|
||||
* but rather can be used to send a message to cancel a process
|
||||
* associated with 'id' (through .add(id)), which the process itself
|
||||
* checks (through .has(id)) and then performs the cancellation.
|
||||
*/
|
||||
export default class CancelTracker {
|
||||
private static instance: CancelTracker;
|
||||
private data: Set<string>;
|
||||
|
||||
private constructor() {
|
||||
this.data = new Set();
|
||||
}
|
||||
|
||||
// Get the canceler
|
||||
public static getInstance(): CancelTracker {
|
||||
if (!CancelTracker.instance)
|
||||
CancelTracker.instance = new CancelTracker();
|
||||
return CancelTracker.instance;
|
||||
}
|
||||
|
||||
// Add an id to trigger cancelation
|
||||
private addId(id: string): void {
|
||||
this.data.add(id);
|
||||
}
|
||||
public static add(id: string): void {
|
||||
CancelTracker.getInstance().addId(id);
|
||||
}
|
||||
|
||||
// Canceler has the given id
|
||||
private hasId(id: string): boolean {
|
||||
return this.data.has(id);
|
||||
}
|
||||
public static has(id: string): boolean {
|
||||
return CancelTracker.getInstance().hasId(id);
|
||||
}
|
||||
|
||||
// Clear id from the canceler
|
||||
private clearId(id: string): void {
|
||||
if (CancelTracker.has(id))
|
||||
this.data.delete(id);
|
||||
}
|
||||
public static clear(id: string): void {
|
||||
CancelTracker.getInstance().clearId(id);
|
||||
}
|
||||
private clearTracker(): void {
|
||||
this.data.clear();
|
||||
}
|
||||
public static clearAll(): void {
|
||||
CancelTracker.getInstance().clearTracker();
|
||||
}
|
||||
}
|
||||
|
||||
@ -6,4 +6,12 @@ export class DuplicateVariableNameError extends Error {
|
||||
this.name = "DuplicateVariableNameError";
|
||||
this.message = "You have multiple template variables with the same name, {" + variable + "}. Duplicate names in the same chain is not allowed. To fix, ensure that all template variable names are unique across a chain.";
|
||||
}
|
||||
}
|
||||
|
||||
export class UserForcedPrematureExit extends Error {
|
||||
constructor(id?: string) {
|
||||
super();
|
||||
this.name = "UserForcedPrematureExit";
|
||||
this.message = "You have forced the premature exit of the process" + (id !== undefined ? ` with id ${id}` : "");
|
||||
}
|
||||
}
|
||||
@ -3,6 +3,8 @@ import { LLM, NativeLLM, RATE_LIMITS } from './models';
|
||||
import { Dict, LLMResponseError, LLMResponseObject, isEqualChatHistory, ChatHistoryInfo } from "./typing";
|
||||
import { extract_responses, merge_response_objs, call_llm, mergeDicts } from "./utils";
|
||||
import StorageCache from "./cache";
|
||||
import CancelTracker from "./canceler";
|
||||
import { UserForcedPrematureExit } from "./errors";
|
||||
|
||||
const clone = (obj) => JSON.parse(JSON.stringify(obj));
|
||||
|
||||
@ -129,12 +131,13 @@ export class PromptPipeline {
|
||||
* and 3 different prior chat histories, it will send off 9 queries.
|
||||
* @yields Yields `LLMResponseObject` if API call succeeds, or `LLMResponseError` if API call fails, for all requests.
|
||||
*/
|
||||
async *gen_responses(vars: Dict,
|
||||
async *gen_responses( vars: Dict,
|
||||
llm: LLM,
|
||||
n: number = 1,
|
||||
temperature: number = 1.0,
|
||||
llm_params?: Dict,
|
||||
chat_histories?: ChatHistoryInfo[]): AsyncGenerator<LLMResponseObject | LLMResponseError, boolean, undefined> {
|
||||
n: number = 1,
|
||||
temperature: number = 1.0,
|
||||
llm_params?: Dict,
|
||||
chat_histories?: ChatHistoryInfo[],
|
||||
should_cancel?: ()=>boolean): AsyncGenerator<LLMResponseObject | LLMResponseError, boolean, undefined> {
|
||||
// Load any cache'd responses
|
||||
let responses = this._load_cached_responses();
|
||||
|
||||
@ -215,13 +218,15 @@ export class PromptPipeline {
|
||||
max_req,
|
||||
wait_secs,
|
||||
llm_params,
|
||||
chat_history));
|
||||
chat_history,
|
||||
should_cancel));
|
||||
} else {
|
||||
// Block. Await + yield a single LLM call.
|
||||
let result = await this._prompt_llm(llm, prompt, n, temperature,
|
||||
cached_resp, cached_resp_idx,
|
||||
undefined, undefined, undefined,
|
||||
llm_params, chat_history);
|
||||
llm_params, chat_history,
|
||||
should_cancel);
|
||||
yield this.collect_LLM_response(result, llm, responses);
|
||||
}
|
||||
}
|
||||
@ -263,7 +268,8 @@ export class PromptPipeline {
|
||||
rate_limit_batch_size?: number,
|
||||
rate_limit_wait_secs?: number,
|
||||
llm_params?: Dict,
|
||||
chat_history?: ChatHistoryInfo): Promise<_IntermediateLLMResponseType> {
|
||||
chat_history?: ChatHistoryInfo,
|
||||
should_cancel?: ()=>boolean): Promise<_IntermediateLLMResponseType> {
|
||||
// Detect how many responses we have already (from cache obj past_resp_obj)
|
||||
if (past_resp_obj) {
|
||||
// How many *new* queries we need to send:
|
||||
@ -283,7 +289,7 @@ export class PromptPipeline {
|
||||
await sleep(wait_secs);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
// Now try to call the API. If it fails for whatever reason, 'soft fail' by returning
|
||||
// an LLMResponseException object as the 'response'.
|
||||
let params = clone(llm_params);
|
||||
@ -291,15 +297,24 @@ export class PromptPipeline {
|
||||
let query: Dict | undefined;
|
||||
let response: Dict | LLMResponseError;
|
||||
try {
|
||||
[query, response] = await call_llm(llm, prompt.toString(), n, temperature, params);
|
||||
// When/if we emerge from sleep, check if this process has been canceled in the meantime:
|
||||
if (should_cancel && should_cancel()) throw new UserForcedPrematureExit();
|
||||
|
||||
// Call the LLM, returning when the Promise returns (if it does!)
|
||||
[query, response] = await call_llm(llm, prompt.toString(), n, temperature, params, should_cancel);
|
||||
|
||||
// When/if we emerge from getting a response, check if this process has been canceled in the meantime:
|
||||
if (should_cancel && should_cancel()) throw new UserForcedPrematureExit();
|
||||
} catch(err) {
|
||||
if (err instanceof UserForcedPrematureExit) throw err; // bubble cancels up
|
||||
|
||||
return { prompt: prompt,
|
||||
query: undefined,
|
||||
response: new LLMResponseError(err.message),
|
||||
past_resp_obj: undefined,
|
||||
past_resp_obj_cache_idx: -1 };
|
||||
}
|
||||
|
||||
|
||||
return { prompt,
|
||||
chat_history,
|
||||
query,
|
||||
|
||||
@ -100,7 +100,8 @@ export interface LLMAPICall {
|
||||
model: LLM,
|
||||
n: number,
|
||||
temperature: number,
|
||||
params?: Dict): Promise<[Dict, Dict]>
|
||||
params?: Dict,
|
||||
should_cancel?: (() => boolean)): Promise<[Dict, Dict]>,
|
||||
}
|
||||
|
||||
/** A standard response format expected by the front-end. */
|
||||
|
||||
@ -12,6 +12,7 @@ import { StringTemplate } from './template';
|
||||
import { Configuration as OpenAIConfig, OpenAIApi } from "openai";
|
||||
import { OpenAIClient as AzureOpenAIClient, AzureKeyCredential } from "@azure/openai";
|
||||
import { GoogleGenerativeAI } from "@google/generative-ai";
|
||||
import { UserForcedPrematureExit } from './errors';
|
||||
|
||||
const ANTHROPIC_HUMAN_PROMPT = "\n\nHuman:";
|
||||
const ANTHROPIC_AI_PROMPT = "\n\nAssistant:";
|
||||
@ -155,7 +156,7 @@ function construct_openai_chat_history(prompt: string, chat_history: ChatHistory
|
||||
* Calls OpenAI models via OpenAI's API.
|
||||
@returns raw query and response JSON dicts.
|
||||
*/
|
||||
export async function call_chatgpt(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict): Promise<[Dict, Dict]> {
|
||||
export async function call_chatgpt(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
if (!OPENAI_API_KEY)
|
||||
throw new Error("Could not find an OpenAI API key. Double-check that your API key is set in Settings or in your local environment.");
|
||||
|
||||
@ -233,7 +234,7 @@ export async function call_chatgpt(prompt: string, model: LLM, n: number = 1, te
|
||||
*
|
||||
* NOTE: It is recommended to set an environment variables AZURE_OPENAI_KEY and AZURE_OPENAI_ENDPOINT
|
||||
*/
|
||||
export async function call_azure_openai(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict): Promise<[Dict, Dict]> {
|
||||
export async function call_azure_openai(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
if (!AZURE_OPENAI_KEY)
|
||||
throw new Error("Could not find an Azure OpenAPI Key to use. Double-check that your key is set in Settings or in your local environment.");
|
||||
if (!AZURE_OPENAI_ENDPOINT)
|
||||
@ -306,7 +307,7 @@ export async function call_azure_openai(prompt: string, model: LLM, n: number =
|
||||
|
||||
NOTE: It is recommended to set an environment variable ANTHROPIC_API_KEY with your Anthropic API key
|
||||
*/
|
||||
export async function call_anthropic(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict): Promise<[Dict, Dict]> {
|
||||
export async function call_anthropic(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
if (!ANTHROPIC_API_KEY)
|
||||
throw new Error("Could not find an API key for Anthropic models. Double-check that your API key is set in Settings or in your local environment.");
|
||||
|
||||
@ -357,6 +358,8 @@ export async function call_anthropic(prompt: string, model: LLM, n: number = 1,
|
||||
// Repeat call n times, waiting for each response to come in:
|
||||
let responses: Array<Dict> = [];
|
||||
while (responses.length < n) {
|
||||
// Abort if canceled
|
||||
if (should_cancel && should_cancel()) throw new UserForcedPrematureExit();
|
||||
|
||||
if (APP_IS_RUNNING_LOCALLY()) {
|
||||
// If we're running locally, route the request through the Flask backend,
|
||||
@ -369,7 +372,6 @@ export async function call_anthropic(prompt: string, model: LLM, n: number = 1,
|
||||
'User-Agent': "Anthropic/JS 0.5.0",
|
||||
'X-Api-Key': ANTHROPIC_API_KEY,
|
||||
};
|
||||
console.log(query);
|
||||
const resp = await route_fetch(url, 'POST', headers, query);
|
||||
responses.push(resp);
|
||||
|
||||
@ -389,7 +391,6 @@ export async function call_anthropic(prompt: string, model: LLM, n: number = 1,
|
||||
throw new Error(`${resp.error.type}: ${resp.error.message}`);
|
||||
}
|
||||
|
||||
// console.log('Received Anthropic response from server proxy:', resp);
|
||||
responses.push(resp);
|
||||
}
|
||||
}
|
||||
@ -401,12 +402,12 @@ export async function call_anthropic(prompt: string, model: LLM, n: number = 1,
|
||||
* Calls a Google PaLM/Gemini model, based on the model selection from the user.
|
||||
* Returns raw query and response JSON dicts.
|
||||
*/
|
||||
export async function call_google_ai(prompt: string, model: LLM, n: number = 1, temperature: number = 0.7, params?: Dict): Promise<[Dict, Dict]> {
|
||||
export async function call_google_ai(prompt: string, model: LLM, n: number = 1, temperature: number = 0.7, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
switch(model) {
|
||||
case NativeLLM.GEMINI_PRO:
|
||||
return call_google_gemini(prompt, model, n, temperature, params);
|
||||
return call_google_gemini(prompt, model, n, temperature, params, should_cancel);
|
||||
default:
|
||||
return call_google_palm(prompt, model, n, temperature, params);
|
||||
return call_google_palm(prompt, model, n, temperature, params, should_cancel);
|
||||
}
|
||||
}
|
||||
|
||||
@ -414,7 +415,7 @@ export async function call_google_ai(prompt: string, model: LLM, n: number = 1,
|
||||
* Calls a Google PaLM model.
|
||||
* Returns raw query and response JSON dicts.
|
||||
*/
|
||||
export async function call_google_palm(prompt: string, model: LLM, n: number = 1, temperature: number = 0.7, params?: Dict): Promise<[Dict, Dict]> {
|
||||
export async function call_google_palm(prompt: string, model: LLM, n: number = 1, temperature: number = 0.7, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
if (!GOOGLE_PALM_API_KEY)
|
||||
throw new Error("Could not find an API key for Google PaLM models. Double-check that your API key is set in Settings or in your local environment.");
|
||||
const is_chat_model = model.toString().includes('chat');
|
||||
@ -523,7 +524,7 @@ export async function call_google_palm(prompt: string, model: LLM, n: number = 1
|
||||
return [query, completion];
|
||||
}
|
||||
|
||||
export async function call_google_gemini(prompt: string, model: LLM, n: number = 1, temperature: number = 0.7, params?: Dict): Promise<[Dict, Dict]> {
|
||||
export async function call_google_gemini(prompt: string, model: LLM, n: number = 1, temperature: number = 0.7, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
if (!GOOGLE_PALM_API_KEY)
|
||||
throw new Error("Could not find an API key for Google Gemini models. Double-check that your API key is set in Settings or in your local environment.");
|
||||
|
||||
@ -604,6 +605,8 @@ export async function call_google_gemini(prompt: string, model: LLM, n: number =
|
||||
let responses: Array<Dict> = [];
|
||||
|
||||
while(responses.length < n) {
|
||||
if (should_cancel && should_cancel()) throw new UserForcedPrematureExit();
|
||||
|
||||
const chat = gemini_model.startChat(
|
||||
{
|
||||
history: gemini_chat_context.history,
|
||||
@ -624,7 +627,7 @@ export async function call_google_gemini(prompt: string, model: LLM, n: number =
|
||||
return [query, responses];
|
||||
}
|
||||
|
||||
export async function call_dalai(prompt: string, model: LLM, n: number = 1, temperature: number = 0.7, params?: Dict): Promise<[Dict, Dict]> {
|
||||
export async function call_dalai(prompt: string, model: LLM, n: number = 1, temperature: number = 0.7, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
if (APP_IS_RUNNING_LOCALLY()) {
|
||||
// Try to call Dalai server, through Flask:
|
||||
let {query, response, error} = await call_flask_backend('callDalai', {
|
||||
@ -641,7 +644,7 @@ export async function call_dalai(prompt: string, model: LLM, n: number = 1, temp
|
||||
}
|
||||
|
||||
|
||||
export async function call_huggingface(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict): Promise<[Dict, Dict]> {
|
||||
export async function call_huggingface(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
// Whether we should notice a given param in 'params'
|
||||
const param_exists = (p: any) => (p !== undefined && !((typeof p === 'number' && p < 0) || (typeof p === 'string' && p.trim().length === 0)));
|
||||
const set_param_if_exists = (name: string, query: Dict) => {
|
||||
@ -710,7 +713,11 @@ export async function call_huggingface(prompt: string, model: LLM, n: number = 1
|
||||
let continued_response: Dict = { generated_text: "" };
|
||||
let curr_cont = 0;
|
||||
let curr_text = prompt;
|
||||
|
||||
while (curr_cont <= num_continuations) {
|
||||
// Abort if user canceled the query operation
|
||||
if (should_cancel && should_cancel()) throw new UserForcedPrematureExit();
|
||||
|
||||
const inputs = (model_type === 'chat')
|
||||
? ({ text: curr_text,
|
||||
past_user_inputs: hf_chat_hist.past_user_inputs,
|
||||
@ -749,7 +756,7 @@ export async function call_huggingface(prompt: string, model: LLM, n: number = 1
|
||||
}
|
||||
|
||||
|
||||
export async function call_alephalpha(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict): Promise<[Dict, Dict]> {
|
||||
export async function call_alephalpha(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
if (!ALEPH_ALPHA_API_KEY)
|
||||
throw Error("Could not find an API key for Aleph Alpha models. Double-check that your API key is set in Settings or in your local environment.");
|
||||
|
||||
@ -784,7 +791,7 @@ export async function call_alephalpha(prompt: string, model: LLM, n: number = 1,
|
||||
return [query, responses];
|
||||
}
|
||||
|
||||
export async function call_ollama_provider(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict): Promise<[Dict, Dict]> {
|
||||
export async function call_ollama_provider(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
let url: string = appendEndSlashIfMissing(params?.ollama_url);
|
||||
const ollama_model: string = params?.ollamaModel.toString();
|
||||
const model_type: string = params?.model_type ?? "text";
|
||||
@ -820,10 +827,15 @@ export async function call_ollama_provider(prompt: string, model: LLM, n: number
|
||||
// Call Ollama API
|
||||
let resps : Response[] = [];
|
||||
for (let i = 0; i < n; i++) {
|
||||
// Abort if the user canceled
|
||||
if (should_cancel && should_cancel()) throw new UserForcedPrematureExit();
|
||||
|
||||
// Query Ollama and collect the response
|
||||
const response = await fetch(url, {
|
||||
method: "POST",
|
||||
body: JSON.stringify(query),
|
||||
});
|
||||
|
||||
resps.push(response);
|
||||
}
|
||||
|
||||
@ -842,7 +854,7 @@ export async function call_ollama_provider(prompt: string, model: LLM, n: number
|
||||
return [query, responses];
|
||||
}
|
||||
|
||||
async function call_custom_provider(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict): Promise<[Dict, Dict]> {
|
||||
async function call_custom_provider(prompt: string, model: LLM, n: number = 1, temperature: number = 1.0, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
if (!APP_IS_RUNNING_LOCALLY())
|
||||
throw new Error("The ChainForge app does not appear to be running locally. You can only call custom model providers if you are running ChainForge on your local machine, from a Flask app.")
|
||||
|
||||
@ -859,6 +871,10 @@ async function call_custom_provider(prompt: string, model: LLM, n: number = 1, t
|
||||
|
||||
// Call the custom provider n times
|
||||
while (responses.length < n) {
|
||||
// Abort if the user canceled
|
||||
if (should_cancel && should_cancel()) throw new UserForcedPrematureExit();
|
||||
|
||||
// Collect response from the custom provider
|
||||
let {response, error} = await call_flask_backend('callCustomProvider',
|
||||
{ 'name': provider_name,
|
||||
'params': {
|
||||
@ -878,7 +894,7 @@ async function call_custom_provider(prompt: string, model: LLM, n: number = 1, t
|
||||
/**
|
||||
* Switcher that routes the request to the appropriate API call function. If call doesn't exist, throws error.
|
||||
*/
|
||||
export async function call_llm(llm: LLM, prompt: string, n: number, temperature: number, params?: Dict): Promise<[Dict, Dict]> {
|
||||
export async function call_llm(llm: LLM, prompt: string, n: number, temperature: number, params?: Dict, should_cancel?: (() => boolean)): Promise<[Dict, Dict]> {
|
||||
// Get the correct API call for the given LLM:
|
||||
let call_api: LLMAPICall | undefined;
|
||||
let llm_provider: LLMProvider = getProvider(llm);
|
||||
@ -905,7 +921,7 @@ export async function call_llm(llm: LLM, prompt: string, n: number, temperature:
|
||||
else if (llm_provider === LLMProvider.Custom)
|
||||
call_api = call_custom_provider;
|
||||
|
||||
return call_api(prompt, llm, n, temperature, params);
|
||||
return call_api(prompt, llm, n, temperature, params, should_cancel);
|
||||
}
|
||||
|
||||
|
||||
|
||||
@ -15,7 +15,7 @@ async function _route_to_js_backend(route, params) {
|
||||
case 'generatePrompts':
|
||||
return generatePrompts(params.prompt, clone(params.vars));
|
||||
case 'queryllm':
|
||||
return queryLLM(params.id, clone(params.llm), params.n, params.prompt, clone(params.vars), params.chat_histories, params.api_keys, params.no_cache, params.progress_listener, params.cont_only_w_prior_llms);
|
||||
return queryLLM(params.id, clone(params.llm), params.n, params.prompt, clone(params.vars), params.chat_histories, params.api_keys, params.no_cache, params.progress_listener, params.cont_only_w_prior_llms, params.cancel_id);
|
||||
case 'executejs':
|
||||
return executejs(params.id, params.code, params.responses, params.scope, params.process_type);
|
||||
case 'executepy':
|
||||
|
||||
@ -70,8 +70,8 @@
|
||||
display: inline-block;
|
||||
position: relative;
|
||||
margin-left: 4px;
|
||||
width: 18px;
|
||||
height: 18px;
|
||||
width: 16px;
|
||||
height: 16px;
|
||||
}
|
||||
.lds-ring div {
|
||||
box-sizing: border-box;
|
||||
@ -748,6 +748,7 @@
|
||||
.AmitSahoo45-button-3 {
|
||||
position: relative;
|
||||
padding: 2px 10px;
|
||||
height: 20px;
|
||||
margin-top: -5px;
|
||||
margin-right: 3px;
|
||||
border-radius: 5px;
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user