Compare commits
4 Commits
abhi/folde
...
chore/remo
| Author | SHA1 | Date | |
|---|---|---|---|
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4b3611ca43 | ||
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cd6271b787 | ||
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223df9d3da | ||
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187ab04745 |
@@ -106,8 +106,6 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
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GPT41_MINI = "gpt-4.1-mini-2025-04-14"
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GPT4O_MINI = "gpt-4o-mini"
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GPT4O = "gpt-4o"
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GPT4_TURBO = "gpt-4-turbo"
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GPT3_5_TURBO = "gpt-3.5-turbo"
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# Anthropic models
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CLAUDE_4_1_OPUS = "claude-opus-4-1-20250805"
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CLAUDE_4_OPUS = "claude-opus-4-20250514"
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@@ -255,12 +253,6 @@ MODEL_METADATA = {
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LlmModel.GPT4O: ModelMetadata(
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"openai", 128000, 16384, "GPT-4o", "OpenAI", "OpenAI", 2
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), # gpt-4o-2024-08-06
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LlmModel.GPT4_TURBO: ModelMetadata(
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"openai", 128000, 4096, "GPT-4 Turbo", "OpenAI", "OpenAI", 3
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), # gpt-4-turbo-2024-04-09
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LlmModel.GPT3_5_TURBO: ModelMetadata(
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"openai", 16385, 4096, "GPT-3.5 Turbo", "OpenAI", "OpenAI", 1
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), # gpt-3.5-turbo-0125
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# https://docs.anthropic.com/en/docs/about-claude/models
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LlmModel.CLAUDE_4_1_OPUS: ModelMetadata(
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"anthropic", 200000, 32000, "Claude Opus 4.1", "Anthropic", "Anthropic", 3
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@@ -75,8 +75,6 @@ MODEL_COST: dict[LlmModel, int] = {
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LlmModel.GPT41_MINI: 1,
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LlmModel.GPT4O_MINI: 1,
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LlmModel.GPT4O: 3,
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LlmModel.GPT4_TURBO: 10,
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LlmModel.GPT3_5_TURBO: 1,
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LlmModel.CLAUDE_4_1_OPUS: 21,
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LlmModel.CLAUDE_4_OPUS: 21,
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LlmModel.CLAUDE_4_SONNET: 5,
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@@ -79,7 +79,7 @@ async def test_block_credit_usage(server: SpinTestServer):
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node_exec_id="test_node_exec",
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block_id=AITextGeneratorBlock().id,
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inputs={
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"model": "gpt-4-turbo",
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"model": "gpt-4o",
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"credentials": {
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"id": openai_credentials.id,
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"provider": openai_credentials.provider,
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@@ -100,7 +100,7 @@ async def test_block_credit_usage(server: SpinTestServer):
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graph_exec_id="test_graph_exec",
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node_exec_id="test_node_exec",
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block_id=AITextGeneratorBlock().id,
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inputs={"model": "gpt-4-turbo", "api_key": "owned_api_key"},
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inputs={"model": "gpt-4o", "api_key": "owned_api_key"},
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execution_context=ExecutionContext(user_timezone="UTC"),
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),
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)
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@@ -0,0 +1,42 @@
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-- Migrate deprecated OpenAI GPT-4-turbo and GPT-3.5-turbo models
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-- This updates all AgentNode blocks that use deprecated models
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-- OpenAI is retiring these models:
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-- - gpt-4-turbo: March 26, 2026 -> migrate to gpt-4o
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-- - gpt-3.5-turbo: September 28, 2026 -> migrate to gpt-4o-mini
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-- Update gpt-4-turbo to gpt-4o (staying in same capability tier)
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UPDATE "AgentNode"
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SET "constantInput" = JSONB_SET(
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"constantInput"::jsonb,
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'{model}',
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'"gpt-4o"'::jsonb
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)
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WHERE "constantInput"::jsonb->>'model' = 'gpt-4-turbo';
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-- Update gpt-3.5-turbo to gpt-4o-mini (appropriate replacement for lightweight model)
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UPDATE "AgentNode"
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SET "constantInput" = JSONB_SET(
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"constantInput"::jsonb,
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'{model}',
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'"gpt-4o-mini"'::jsonb
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)
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WHERE "constantInput"::jsonb->>'model' = 'gpt-3.5-turbo';
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-- Update AgentPreset input overrides (stored in AgentNodeExecutionInputOutput)
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UPDATE "AgentNodeExecutionInputOutput"
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SET "data" = JSONB_SET(
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"data"::jsonb,
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'{model}',
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'"gpt-4o"'::jsonb
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)
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WHERE "agentPresetId" IS NOT NULL
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AND "data"::jsonb->>'model' = 'gpt-4-turbo';
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UPDATE "AgentNodeExecutionInputOutput"
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SET "data" = JSONB_SET(
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"data"::jsonb,
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'{model}',
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'"gpt-4o-mini"'::jsonb
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)
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WHERE "agentPresetId" IS NOT NULL
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AND "data"::jsonb->>'model' = 'gpt-3.5-turbo';
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@@ -4,7 +4,7 @@ import {
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} from "@/app/api/__generated__/endpoints/graphs/graphs";
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import { useToast } from "@/components/molecules/Toast/use-toast";
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import { parseAsInteger, parseAsString, useQueryStates } from "nuqs";
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import { GraphExecutionMeta } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/use-agent-runs";
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import { GraphExecutionMeta } from "@/app/api/__generated__/models/graphExecutionMeta";
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import { useGraphStore } from "@/app/(platform)/build/stores/graphStore";
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import { useShallow } from "zustand/react/shallow";
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import { useEffect, useState } from "react";
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@@ -1,6 +1,6 @@
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import { useCallback } from "react";
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import { AgentRunDraftView } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view";
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import { AgentRunDraftView } from "@/app/(platform)/build/components/legacy-builder/agent-run-draft-view";
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import { Dialog } from "@/components/molecules/Dialog/Dialog";
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import type {
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CredentialsMetaInput,
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@@ -18,7 +18,7 @@ import {
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import { useToast } from "@/components/molecules/Toast/use-toast";
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import { useQueryClient } from "@tanstack/react-query";
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import { getGetV2ListMySubmissionsQueryKey } from "@/app/api/__generated__/endpoints/store/store";
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import { CronExpressionDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
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import { CronExpressionDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
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import { humanizeCronExpression } from "@/lib/cron-expression-utils";
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import { CalendarClockIcon } from "lucide-react";
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@@ -20,7 +20,7 @@ import {
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import { useBackendAPI } from "@/lib/autogpt-server-api/context";
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import { RunAgentInputs } from "@/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentInputs/RunAgentInputs";
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import { ScheduleTaskDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
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import { ScheduleTaskDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
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import ActionButtonGroup from "@/components/__legacy__/action-button-group";
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import type { ButtonAction } from "@/components/__legacy__/types";
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import {
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@@ -53,7 +53,10 @@ import { ClockIcon, CopyIcon, InfoIcon } from "@phosphor-icons/react";
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import { CalendarClockIcon, Trash2Icon } from "lucide-react";
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import { analytics } from "@/services/analytics";
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import { AgentStatus, AgentStatusChip } from "./agent-status-chip";
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import {
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AgentStatus,
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AgentStatusChip,
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} from "@/app/(platform)/build/components/legacy-builder/agent-status-chip";
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export function AgentRunDraftView({
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graph,
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@@ -4,11 +4,11 @@ import { Button } from "@/components/atoms/Button/Button";
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import { Text } from "@/components/atoms/Text/Text";
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import {
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BookOpenIcon,
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CheckFatIcon,
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PencilSimpleIcon,
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WarningDiamondIcon,
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} from "@phosphor-icons/react";
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import type { ToolUIPart } from "ai";
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import Image from "next/image";
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import NextLink from "next/link";
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import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
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import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
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@@ -24,6 +24,7 @@ import {
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ClarificationQuestionsCard,
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ClarifyingQuestion,
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} from "./components/ClarificationQuestionsCard";
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import sparklesImg from "./components/MiniGame/assets/sparkles.png";
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import { MiniGame } from "./components/MiniGame/MiniGame";
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import {
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AccordionIcon,
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@@ -83,7 +84,8 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
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) {
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return {
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icon,
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title: "Creating agent, this may take a few minutes. Sit back and relax.",
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title:
|
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"Creating agent, this may take a few minutes. Play while you wait.",
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expanded: true,
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};
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}
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@@ -167,16 +169,20 @@ export function CreateAgentTool({ part }: Props) {
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{isAgentSavedOutput(output) && (
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<div className="rounded-xl border border-border/60 bg-card p-4 shadow-sm">
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<div className="flex items-baseline gap-2">
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<CheckFatIcon
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size={18}
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weight="regular"
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className="relative top-1 text-green-500"
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<Image
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src={sparklesImg}
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alt="sparkles"
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width={24}
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height={24}
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className="relative top-1"
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||||
/>
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<Text
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variant="body-medium"
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className="text-blacks mb-2 text-[16px]"
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className="mb-2 text-[16px] text-black"
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>
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{output.message}
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Agent{" "}
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<span className="text-violet-600">{output.agent_name}</span>{" "}
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has been saved to your library!
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</Text>
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</div>
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<div className="mt-3 flex flex-wrap gap-4">
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@@ -2,20 +2,65 @@
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import { useMiniGame } from "./useMiniGame";
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function Key({ children }: { children: React.ReactNode }) {
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return <strong>[{children}]</strong>;
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}
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export function MiniGame() {
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const { canvasRef } = useMiniGame();
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const { canvasRef, activeMode, showOverlay, score, highScore, onContinue } =
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useMiniGame();
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const isRunActive =
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activeMode === "run" || activeMode === "idle" || activeMode === "over";
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let overlayText: string | undefined;
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let buttonLabel = "Continue";
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if (activeMode === "idle") {
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buttonLabel = "Start";
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} else if (activeMode === "boss-intro") {
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overlayText = "Face the bandit!";
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} else if (activeMode === "boss-defeated") {
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overlayText = "Great job, keep on going";
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} else if (activeMode === "over") {
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overlayText = `Score: ${score} / Record: ${highScore}`;
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buttonLabel = "Retry";
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}
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|
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return (
|
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<div
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className="w-full overflow-hidden rounded-md bg-background text-foreground"
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style={{ border: "1px solid #d17fff" }}
|
||||
>
|
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<canvas
|
||||
ref={canvasRef}
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tabIndex={0}
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className="block w-full outline-none"
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style={{ imageRendering: "pixelated" }}
|
||||
/>
|
||||
<div className="flex flex-col gap-2">
|
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<p className="text-sm font-medium text-purple-500">
|
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{isRunActive ? (
|
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<>
|
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Run mode: <Key>Space</Key> to jump
|
||||
</>
|
||||
) : (
|
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<>
|
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Duel mode: <Key>←→</Key> to move · <Key>Z</Key> to attack ·{" "}
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<Key>X</Key> to block · <Key>Space</Key> to jump
|
||||
</>
|
||||
)}
|
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</p>
|
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<div className="relative w-full overflow-hidden rounded-md border border-accent bg-background text-foreground">
|
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<canvas
|
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ref={canvasRef}
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tabIndex={0}
|
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className="block w-full outline-none"
|
||||
/>
|
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{showOverlay && (
|
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<div className="absolute inset-0 flex flex-col items-center justify-center gap-3 bg-black/40">
|
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{overlayText && (
|
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<p className="text-lg font-bold text-white">{overlayText}</p>
|
||||
)}
|
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<button
|
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type="button"
|
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onClick={onContinue}
|
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className="rounded-md bg-white px-4 py-2 text-sm font-semibold text-zinc-800 shadow-md transition-colors hover:bg-zinc-100"
|
||||
>
|
||||
{buttonLabel}
|
||||
</button>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
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|
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|
After Width: | Height: | Size: 5.2 KiB |
|
After Width: | Height: | Size: 4.9 KiB |
|
After Width: | Height: | Size: 12 KiB |
|
After Width: | Height: | Size: 8.0 KiB |
|
After Width: | Height: | Size: 7.3 KiB |
|
After Width: | Height: | Size: 9.6 KiB |
|
After Width: | Height: | Size: 9.5 KiB |
|
After Width: | Height: | Size: 8.0 KiB |
|
After Width: | Height: | Size: 16 KiB |
|
After Width: | Height: | Size: 14 KiB |
|
After Width: | Height: | Size: 10 KiB |
@@ -136,7 +136,7 @@ export function getAnimationText(part: {
|
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if (isOperationPendingOutput(output)) return "Agent creation in progress";
|
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if (isOperationInProgressOutput(output))
|
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return "Agent creation already in progress";
|
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if (isAgentSavedOutput(output)) return `Saved "${output.agent_name}"`;
|
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if (isAgentSavedOutput(output)) return `Saved ${output.agent_name}`;
|
||||
if (isAgentPreviewOutput(output)) return `Preview "${output.agent_name}"`;
|
||||
if (isClarificationNeededOutput(output)) return "Needs clarification";
|
||||
return "Error creating agent";
|
||||
|
||||
@@ -5,7 +5,6 @@ import type { ToolUIPart } from "ai";
|
||||
import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
|
||||
import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
|
||||
import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
|
||||
import { ProgressBar } from "../../components/ProgressBar/ProgressBar";
|
||||
import {
|
||||
ContentCardDescription,
|
||||
ContentCodeBlock,
|
||||
@@ -15,7 +14,7 @@ import {
|
||||
ContentMessage,
|
||||
} from "../../components/ToolAccordion/AccordionContent";
|
||||
import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
|
||||
import { useAsymptoticProgress } from "../../hooks/useAsymptoticProgress";
|
||||
import { MiniGame } from "../CreateAgent/components/MiniGame/MiniGame";
|
||||
import {
|
||||
ClarificationQuestionsCard,
|
||||
ClarifyingQuestion,
|
||||
@@ -54,6 +53,7 @@ function getAccordionMeta(output: EditAgentToolOutput): {
|
||||
title: string;
|
||||
titleClassName?: string;
|
||||
description?: string;
|
||||
expanded?: boolean;
|
||||
} {
|
||||
const icon = <AccordionIcon />;
|
||||
|
||||
@@ -80,7 +80,11 @@ function getAccordionMeta(output: EditAgentToolOutput): {
|
||||
isOperationPendingOutput(output) ||
|
||||
isOperationInProgressOutput(output)
|
||||
) {
|
||||
return { icon: <OrbitLoader size={32} />, title: "Editing agent" };
|
||||
return {
|
||||
icon: <OrbitLoader size={32} />,
|
||||
title: "Editing agent, this may take a few minutes. Play while you wait.",
|
||||
expanded: true,
|
||||
};
|
||||
}
|
||||
return {
|
||||
icon: (
|
||||
@@ -105,7 +109,6 @@ export function EditAgentTool({ part }: Props) {
|
||||
(isOperationStartedOutput(output) ||
|
||||
isOperationPendingOutput(output) ||
|
||||
isOperationInProgressOutput(output));
|
||||
const progress = useAsymptoticProgress(isOperating);
|
||||
const hasExpandableContent =
|
||||
part.state === "output-available" &&
|
||||
!!output &&
|
||||
@@ -149,9 +152,9 @@ export function EditAgentTool({ part }: Props) {
|
||||
<ToolAccordion {...getAccordionMeta(output)}>
|
||||
{isOperating && (
|
||||
<ContentGrid>
|
||||
<ProgressBar value={progress} className="max-w-[280px]" />
|
||||
<MiniGame />
|
||||
<ContentHint>
|
||||
This could take a few minutes, grab a coffee ☕
|
||||
This could take a few minutes — play while you wait!
|
||||
</ContentHint>
|
||||
</ContentGrid>
|
||||
)}
|
||||
|
||||
@@ -2,8 +2,14 @@
|
||||
|
||||
import type { ToolUIPart } from "ai";
|
||||
import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
|
||||
import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
|
||||
import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
|
||||
import { ContentMessage } from "../../components/ToolAccordion/AccordionContent";
|
||||
import {
|
||||
ContentGrid,
|
||||
ContentHint,
|
||||
ContentMessage,
|
||||
} from "../../components/ToolAccordion/AccordionContent";
|
||||
import { MiniGame } from "../CreateAgent/components/MiniGame/MiniGame";
|
||||
import {
|
||||
getAccordionMeta,
|
||||
getAnimationText,
|
||||
@@ -60,6 +66,21 @@ export function RunAgentTool({ part }: Props) {
|
||||
/>
|
||||
</div>
|
||||
|
||||
{isStreaming && !output && (
|
||||
<ToolAccordion
|
||||
icon={<OrbitLoader size={32} />}
|
||||
title="Running agent, this may take a few minutes. Play while you wait."
|
||||
expanded={true}
|
||||
>
|
||||
<ContentGrid>
|
||||
<MiniGame />
|
||||
<ContentHint>
|
||||
This could take a few minutes — play while you wait!
|
||||
</ContentHint>
|
||||
</ContentGrid>
|
||||
</ToolAccordion>
|
||||
)}
|
||||
|
||||
{hasExpandableContent && output && (
|
||||
<ToolAccordion {...getAccordionMeta(output)}>
|
||||
{isRunAgentExecutionStartedOutput(output) && (
|
||||
|
||||
@@ -1,631 +0,0 @@
|
||||
"use client";
|
||||
import { useParams, useRouter } from "next/navigation";
|
||||
import { useQueryState } from "nuqs";
|
||||
import React, {
|
||||
useCallback,
|
||||
useEffect,
|
||||
useMemo,
|
||||
useRef,
|
||||
useState,
|
||||
} from "react";
|
||||
|
||||
import {
|
||||
Graph,
|
||||
GraphExecution,
|
||||
GraphExecutionID,
|
||||
GraphExecutionMeta,
|
||||
GraphID,
|
||||
LibraryAgent,
|
||||
LibraryAgentID,
|
||||
LibraryAgentPreset,
|
||||
LibraryAgentPresetID,
|
||||
Schedule,
|
||||
ScheduleID,
|
||||
} from "@/lib/autogpt-server-api";
|
||||
import { useBackendAPI } from "@/lib/autogpt-server-api/context";
|
||||
import { exportAsJSONFile } from "@/lib/utils";
|
||||
|
||||
import DeleteConfirmDialog from "@/components/__legacy__/delete-confirm-dialog";
|
||||
import type { ButtonAction } from "@/components/__legacy__/types";
|
||||
import { Button } from "@/components/__legacy__/ui/button";
|
||||
import {
|
||||
Dialog,
|
||||
DialogContent,
|
||||
DialogDescription,
|
||||
DialogFooter,
|
||||
DialogHeader,
|
||||
DialogTitle,
|
||||
} from "@/components/__legacy__/ui/dialog";
|
||||
import LoadingBox, { LoadingSpinner } from "@/components/__legacy__/ui/loading";
|
||||
import {
|
||||
useToast,
|
||||
useToastOnFail,
|
||||
} from "@/components/molecules/Toast/use-toast";
|
||||
import { AgentRunDetailsView } from "./components/agent-run-details-view";
|
||||
import { AgentRunDraftView } from "./components/agent-run-draft-view";
|
||||
import { CreatePresetDialog } from "./components/create-preset-dialog";
|
||||
import { useAgentRunsInfinite } from "./use-agent-runs";
|
||||
import { AgentRunsSelectorList } from "./components/agent-runs-selector-list";
|
||||
import { AgentScheduleDetailsView } from "./components/agent-schedule-details-view";
|
||||
|
||||
export function OldAgentLibraryView() {
|
||||
const { id: agentID }: { id: LibraryAgentID } = useParams();
|
||||
const [executionId, setExecutionId] = useQueryState("executionId");
|
||||
const toastOnFail = useToastOnFail();
|
||||
const { toast } = useToast();
|
||||
const router = useRouter();
|
||||
const api = useBackendAPI();
|
||||
|
||||
// ============================ STATE =============================
|
||||
|
||||
const [graph, setGraph] = useState<Graph | null>(null); // Graph version corresponding to LibraryAgent
|
||||
const [agent, setAgent] = useState<LibraryAgent | null>(null);
|
||||
const agentRunsQuery = useAgentRunsInfinite(graph?.id); // only runs once graph.id is known
|
||||
const agentRuns = agentRunsQuery.agentRuns;
|
||||
const [agentPresets, setAgentPresets] = useState<LibraryAgentPreset[]>([]);
|
||||
const [schedules, setSchedules] = useState<Schedule[]>([]);
|
||||
const [selectedView, selectView] = useState<
|
||||
| { type: "run"; id?: GraphExecutionID }
|
||||
| { type: "preset"; id: LibraryAgentPresetID }
|
||||
| { type: "schedule"; id: ScheduleID }
|
||||
>({ type: "run" });
|
||||
const [selectedRun, setSelectedRun] = useState<
|
||||
GraphExecution | GraphExecutionMeta | null
|
||||
>(null);
|
||||
const selectedSchedule =
|
||||
selectedView.type == "schedule"
|
||||
? schedules.find((s) => s.id == selectedView.id)
|
||||
: null;
|
||||
const [isFirstLoad, setIsFirstLoad] = useState<boolean>(true);
|
||||
const [agentDeleteDialogOpen, setAgentDeleteDialogOpen] =
|
||||
useState<boolean>(false);
|
||||
const [confirmingDeleteAgentRun, setConfirmingDeleteAgentRun] =
|
||||
useState<GraphExecutionMeta | null>(null);
|
||||
const [confirmingDeleteAgentPreset, setConfirmingDeleteAgentPreset] =
|
||||
useState<LibraryAgentPresetID | null>(null);
|
||||
const [copyAgentDialogOpen, setCopyAgentDialogOpen] = useState(false);
|
||||
const [creatingPresetFromExecutionID, setCreatingPresetFromExecutionID] =
|
||||
useState<GraphExecutionID | null>(null);
|
||||
|
||||
// Set page title with agent name
|
||||
useEffect(() => {
|
||||
if (agent) {
|
||||
document.title = `${agent.name} - Library - AutoGPT Platform`;
|
||||
}
|
||||
}, [agent]);
|
||||
|
||||
const openRunDraftView = useCallback(() => {
|
||||
selectView({ type: "run" });
|
||||
}, []);
|
||||
|
||||
const selectRun = useCallback((id: GraphExecutionID) => {
|
||||
selectView({ type: "run", id });
|
||||
}, []);
|
||||
|
||||
const selectPreset = useCallback((id: LibraryAgentPresetID) => {
|
||||
selectView({ type: "preset", id });
|
||||
}, []);
|
||||
|
||||
const selectSchedule = useCallback((id: ScheduleID) => {
|
||||
selectView({ type: "schedule", id });
|
||||
}, []);
|
||||
|
||||
const graphVersions = useRef<Record<number, Graph>>({});
|
||||
const loadingGraphVersions = useRef<Record<number, Promise<Graph>>>({});
|
||||
const getGraphVersion = useCallback(
|
||||
async (graphID: GraphID, version: number) => {
|
||||
if (version in graphVersions.current)
|
||||
return graphVersions.current[version];
|
||||
if (version in loadingGraphVersions.current)
|
||||
return loadingGraphVersions.current[version];
|
||||
|
||||
const pendingGraph = api.getGraph(graphID, version).then((graph) => {
|
||||
graphVersions.current[version] = graph;
|
||||
return graph;
|
||||
});
|
||||
// Cache promise as well to avoid duplicate requests
|
||||
loadingGraphVersions.current[version] = pendingGraph;
|
||||
return pendingGraph;
|
||||
},
|
||||
[api, graphVersions, loadingGraphVersions],
|
||||
);
|
||||
|
||||
const lastRefresh = useRef<number>(0);
|
||||
const refreshPageData = useCallback(() => {
|
||||
if (Date.now() - lastRefresh.current < 2e3) return; // 2 second debounce
|
||||
lastRefresh.current = Date.now();
|
||||
|
||||
api.getLibraryAgent(agentID).then((agent) => {
|
||||
setAgent(agent);
|
||||
|
||||
getGraphVersion(agent.graph_id, agent.graph_version).then(
|
||||
(_graph) =>
|
||||
(graph && graph.version == _graph.version) || setGraph(_graph),
|
||||
);
|
||||
Promise.all([
|
||||
agentRunsQuery.refetchRuns(),
|
||||
api.listLibraryAgentPresets({
|
||||
graph_id: agent.graph_id,
|
||||
page_size: 100,
|
||||
}),
|
||||
]).then(([runsQueryResult, presets]) => {
|
||||
setAgentPresets(presets.presets);
|
||||
|
||||
const newestAgentRunsResponse = runsQueryResult.data?.pages[0];
|
||||
if (!newestAgentRunsResponse || newestAgentRunsResponse.status != 200)
|
||||
return;
|
||||
const newestAgentRuns = newestAgentRunsResponse.data.executions;
|
||||
// Preload the corresponding graph versions for the latest 10 runs
|
||||
new Set(
|
||||
newestAgentRuns.slice(0, 10).map((run) => run.graph_version),
|
||||
).forEach((version) => getGraphVersion(agent.graph_id, version));
|
||||
});
|
||||
});
|
||||
}, [api, agentID, getGraphVersion, graph]);
|
||||
|
||||
// On first load: select the latest run
|
||||
useEffect(() => {
|
||||
// Only for first load or first execution
|
||||
if (selectedView.id || !isFirstLoad) return;
|
||||
if (agentRuns.length == 0 && agentPresets.length == 0) return;
|
||||
|
||||
setIsFirstLoad(false);
|
||||
if (agentRuns.length > 0) {
|
||||
// select latest run
|
||||
const latestRun = agentRuns.reduce((latest, current) => {
|
||||
if (!latest.started_at && !current.started_at) return latest;
|
||||
if (!latest.started_at) return current;
|
||||
if (!current.started_at) return latest;
|
||||
return latest.started_at > current.started_at ? latest : current;
|
||||
}, agentRuns[0]);
|
||||
selectRun(latestRun.id as GraphExecutionID);
|
||||
} else {
|
||||
// select top preset
|
||||
const latestPreset = agentPresets.toSorted(
|
||||
(a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
|
||||
)[0];
|
||||
selectPreset(latestPreset.id);
|
||||
}
|
||||
}, [
|
||||
isFirstLoad,
|
||||
selectedView.id,
|
||||
agentRuns,
|
||||
agentPresets,
|
||||
selectRun,
|
||||
selectPreset,
|
||||
]);
|
||||
|
||||
useEffect(() => {
|
||||
if (executionId) {
|
||||
selectRun(executionId as GraphExecutionID);
|
||||
setExecutionId(null);
|
||||
}
|
||||
}, [executionId, selectRun, setExecutionId]);
|
||||
|
||||
// Initial load
|
||||
useEffect(() => {
|
||||
refreshPageData();
|
||||
|
||||
// Show a toast when the WebSocket connection disconnects
|
||||
let connectionToast: ReturnType<typeof toast> | null = null;
|
||||
const cancelDisconnectHandler = api.onWebSocketDisconnect(() => {
|
||||
connectionToast ??= toast({
|
||||
title: "Connection to server was lost",
|
||||
variant: "destructive",
|
||||
description: (
|
||||
<div className="flex items-center">
|
||||
Trying to reconnect...
|
||||
<LoadingSpinner className="ml-1.5 size-3.5" />
|
||||
</div>
|
||||
),
|
||||
duration: Infinity,
|
||||
dismissable: true,
|
||||
});
|
||||
});
|
||||
const cancelConnectHandler = api.onWebSocketConnect(() => {
|
||||
if (connectionToast)
|
||||
connectionToast.update({
|
||||
id: connectionToast.id,
|
||||
title: "✅ Connection re-established",
|
||||
variant: "default",
|
||||
description: (
|
||||
<div className="flex items-center">
|
||||
Refreshing data...
|
||||
<LoadingSpinner className="ml-1.5 size-3.5" />
|
||||
</div>
|
||||
),
|
||||
duration: 2000,
|
||||
dismissable: true,
|
||||
});
|
||||
connectionToast = null;
|
||||
});
|
||||
return () => {
|
||||
cancelDisconnectHandler();
|
||||
cancelConnectHandler();
|
||||
};
|
||||
}, []);
|
||||
|
||||
// Subscribe to WebSocket updates for agent runs
|
||||
useEffect(() => {
|
||||
if (!agent?.graph_id) return;
|
||||
|
||||
return api.onWebSocketConnect(() => {
|
||||
refreshPageData(); // Sync up on (re)connect
|
||||
|
||||
// Subscribe to all executions for this agent
|
||||
api.subscribeToGraphExecutions(agent.graph_id);
|
||||
});
|
||||
}, [api, agent?.graph_id, refreshPageData]);
|
||||
|
||||
// Handle execution updates
|
||||
useEffect(() => {
|
||||
const detachExecUpdateHandler = api.onWebSocketMessage(
|
||||
"graph_execution_event",
|
||||
(data) => {
|
||||
if (data.graph_id != agent?.graph_id) return;
|
||||
|
||||
agentRunsQuery.upsertAgentRun(data);
|
||||
if (data.id === selectedView.id) {
|
||||
// Update currently viewed run
|
||||
setSelectedRun(data);
|
||||
}
|
||||
},
|
||||
);
|
||||
|
||||
return () => {
|
||||
detachExecUpdateHandler();
|
||||
};
|
||||
}, [api, agent?.graph_id, selectedView.id]);
|
||||
|
||||
// Pre-load selectedRun based on selectedView
|
||||
useEffect(() => {
|
||||
if (selectedView.type != "run" || !selectedView.id) return;
|
||||
|
||||
const newSelectedRun = agentRuns.find((run) => run.id == selectedView.id);
|
||||
if (selectedView.id !== selectedRun?.id) {
|
||||
// Pull partial data from "cache" while waiting for the rest to load
|
||||
setSelectedRun((newSelectedRun as GraphExecutionMeta) ?? null);
|
||||
}
|
||||
}, [api, selectedView, agentRuns, selectedRun?.id]);
|
||||
|
||||
// Load selectedRun based on selectedView; refresh on agent refresh
|
||||
useEffect(() => {
|
||||
if (selectedView.type != "run" || !selectedView.id || !agent) return;
|
||||
|
||||
api
|
||||
.getGraphExecutionInfo(agent.graph_id, selectedView.id)
|
||||
.then(async (run) => {
|
||||
// Ensure corresponding graph version is available before rendering I/O
|
||||
await getGraphVersion(run.graph_id, run.graph_version);
|
||||
setSelectedRun(run);
|
||||
});
|
||||
}, [api, selectedView, agent, getGraphVersion]);
|
||||
|
||||
const fetchSchedules = useCallback(async () => {
|
||||
if (!agent) return;
|
||||
|
||||
setSchedules(await api.listGraphExecutionSchedules(agent.graph_id));
|
||||
}, [api, agent?.graph_id]);
|
||||
|
||||
useEffect(() => {
|
||||
fetchSchedules();
|
||||
}, [fetchSchedules]);
|
||||
|
||||
// =========================== ACTIONS ============================
|
||||
|
||||
const deleteRun = useCallback(
|
||||
async (run: GraphExecutionMeta) => {
|
||||
if (run.status == "RUNNING" || run.status == "QUEUED") {
|
||||
await api.stopGraphExecution(run.graph_id, run.id);
|
||||
}
|
||||
await api.deleteGraphExecution(run.id);
|
||||
|
||||
setConfirmingDeleteAgentRun(null);
|
||||
if (selectedView.type == "run" && selectedView.id == run.id) {
|
||||
openRunDraftView();
|
||||
}
|
||||
agentRunsQuery.removeAgentRun(run.id);
|
||||
},
|
||||
[api, selectedView, openRunDraftView],
|
||||
);
|
||||
|
||||
const deletePreset = useCallback(
|
||||
async (presetID: LibraryAgentPresetID) => {
|
||||
await api.deleteLibraryAgentPreset(presetID);
|
||||
|
||||
setConfirmingDeleteAgentPreset(null);
|
||||
if (selectedView.type == "preset" && selectedView.id == presetID) {
|
||||
openRunDraftView();
|
||||
}
|
||||
setAgentPresets((presets) => presets.filter((p) => p.id !== presetID));
|
||||
},
|
||||
[api, selectedView, openRunDraftView],
|
||||
);
|
||||
|
||||
const deleteSchedule = useCallback(
|
||||
async (scheduleID: ScheduleID) => {
|
||||
const removedSchedule =
|
||||
await api.deleteGraphExecutionSchedule(scheduleID);
|
||||
|
||||
setSchedules((schedules) => {
|
||||
const newSchedules = schedules.filter(
|
||||
(s) => s.id !== removedSchedule.id,
|
||||
);
|
||||
if (
|
||||
selectedView.type == "schedule" &&
|
||||
selectedView.id == removedSchedule.id
|
||||
) {
|
||||
if (newSchedules.length > 0) {
|
||||
// Select next schedule if available
|
||||
selectSchedule(newSchedules[0].id);
|
||||
} else {
|
||||
// Reset to draft view if current schedule was deleted
|
||||
openRunDraftView();
|
||||
}
|
||||
}
|
||||
return newSchedules;
|
||||
});
|
||||
openRunDraftView();
|
||||
},
|
||||
[schedules, api],
|
||||
);
|
||||
|
||||
const handleCreatePresetFromRun = useCallback(
|
||||
async (name: string, description: string) => {
|
||||
if (!creatingPresetFromExecutionID) return;
|
||||
|
||||
await api
|
||||
.createLibraryAgentPreset({
|
||||
name,
|
||||
description,
|
||||
graph_execution_id: creatingPresetFromExecutionID,
|
||||
})
|
||||
.then((preset) => {
|
||||
setAgentPresets((prev) => [...prev, preset]);
|
||||
selectPreset(preset.id);
|
||||
setCreatingPresetFromExecutionID(null);
|
||||
})
|
||||
.catch(toastOnFail("create a preset"));
|
||||
},
|
||||
[api, creatingPresetFromExecutionID, selectPreset, toast],
|
||||
);
|
||||
|
||||
const downloadGraph = useCallback(
|
||||
async () =>
|
||||
agent &&
|
||||
// Export sanitized graph from backend
|
||||
api
|
||||
.getGraph(agent.graph_id, agent.graph_version, true)
|
||||
.then((graph) =>
|
||||
exportAsJSONFile(graph, `${graph.name}_v${graph.version}.json`),
|
||||
),
|
||||
[api, agent],
|
||||
);
|
||||
|
||||
const copyAgent = useCallback(async () => {
|
||||
setCopyAgentDialogOpen(false);
|
||||
api
|
||||
.forkLibraryAgent(agentID)
|
||||
.then((newAgent) => {
|
||||
router.push(`/library/agents/${newAgent.id}`);
|
||||
})
|
||||
.catch((error) => {
|
||||
console.error("Error copying agent:", error);
|
||||
toast({
|
||||
title: "Error copying agent",
|
||||
description: `An error occurred while copying the agent: ${error.message}`,
|
||||
variant: "destructive",
|
||||
});
|
||||
});
|
||||
}, [agentID, api, router, toast]);
|
||||
|
||||
const agentActions: ButtonAction[] = useMemo(
|
||||
() => [
|
||||
{
|
||||
label: "Customize agent",
|
||||
href: `/build?flowID=${agent?.graph_id}&flowVersion=${agent?.graph_version}`,
|
||||
disabled: !agent?.can_access_graph,
|
||||
},
|
||||
{ label: "Export agent to file", callback: downloadGraph },
|
||||
...(!agent?.can_access_graph
|
||||
? [
|
||||
{
|
||||
label: "Edit a copy",
|
||||
callback: () => setCopyAgentDialogOpen(true),
|
||||
},
|
||||
]
|
||||
: []),
|
||||
{
|
||||
label: "Delete agent",
|
||||
callback: () => setAgentDeleteDialogOpen(true),
|
||||
},
|
||||
],
|
||||
[agent, downloadGraph],
|
||||
);
|
||||
|
||||
const runGraph =
|
||||
graphVersions.current[selectedRun?.graph_version ?? 0] ?? graph;
|
||||
|
||||
const onCreateSchedule = useCallback(
|
||||
(schedule: Schedule) => {
|
||||
setSchedules((prev) => [...prev, schedule]);
|
||||
selectSchedule(schedule.id);
|
||||
},
|
||||
[selectView],
|
||||
);
|
||||
|
||||
const onCreatePreset = useCallback(
|
||||
(preset: LibraryAgentPreset) => {
|
||||
setAgentPresets((prev) => [...prev, preset]);
|
||||
selectPreset(preset.id);
|
||||
},
|
||||
[selectPreset],
|
||||
);
|
||||
|
||||
const onUpdatePreset = useCallback(
|
||||
(updated: LibraryAgentPreset) => {
|
||||
setAgentPresets((prev) =>
|
||||
prev.map((p) => (p.id === updated.id ? updated : p)),
|
||||
);
|
||||
selectPreset(updated.id);
|
||||
},
|
||||
[selectPreset],
|
||||
);
|
||||
|
||||
if (!agent || !graph) {
|
||||
return <LoadingBox className="h-[90vh]" />;
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="container justify-stretch p-0 pt-16 lg:flex">
|
||||
{/* Sidebar w/ list of runs */}
|
||||
{/* TODO: render this below header in sm and md layouts */}
|
||||
<AgentRunsSelectorList
|
||||
className="agpt-div w-full border-b pb-2 lg:w-auto lg:border-b-0 lg:border-r lg:pb-0"
|
||||
agent={agent}
|
||||
agentRunsQuery={agentRunsQuery}
|
||||
agentPresets={agentPresets}
|
||||
schedules={schedules}
|
||||
selectedView={selectedView}
|
||||
onSelectRun={selectRun}
|
||||
onSelectPreset={selectPreset}
|
||||
onSelectSchedule={selectSchedule}
|
||||
onSelectDraftNewRun={openRunDraftView}
|
||||
doDeleteRun={setConfirmingDeleteAgentRun}
|
||||
doDeletePreset={setConfirmingDeleteAgentPreset}
|
||||
doDeleteSchedule={deleteSchedule}
|
||||
doCreatePresetFromRun={setCreatingPresetFromExecutionID}
|
||||
/>
|
||||
|
||||
<div className="flex-1">
|
||||
{/* Header */}
|
||||
<div className="agpt-div w-full border-b">
|
||||
<h1
|
||||
data-testid="agent-title"
|
||||
className="font-poppins text-3xl font-medium"
|
||||
>
|
||||
{
|
||||
agent.name /* TODO: use dynamic/custom run title - https://github.com/Significant-Gravitas/AutoGPT/issues/9184 */
|
||||
}
|
||||
</h1>
|
||||
</div>
|
||||
|
||||
{/* Run / Schedule views */}
|
||||
{(selectedView.type == "run" && selectedView.id ? (
|
||||
selectedRun && runGraph ? (
|
||||
<AgentRunDetailsView
|
||||
agent={agent}
|
||||
graph={runGraph}
|
||||
run={selectedRun}
|
||||
agentActions={agentActions}
|
||||
onRun={selectRun}
|
||||
doDeleteRun={() => setConfirmingDeleteAgentRun(selectedRun)}
|
||||
doCreatePresetFromRun={() =>
|
||||
setCreatingPresetFromExecutionID(selectedRun.id)
|
||||
}
|
||||
/>
|
||||
) : null
|
||||
) : selectedView.type == "run" ? (
|
||||
/* Draft new runs / Create new presets */
|
||||
<AgentRunDraftView
|
||||
graph={graph}
|
||||
onRun={selectRun}
|
||||
onCreateSchedule={onCreateSchedule}
|
||||
onCreatePreset={onCreatePreset}
|
||||
agentActions={agentActions}
|
||||
recommendedScheduleCron={agent?.recommended_schedule_cron || null}
|
||||
/>
|
||||
) : selectedView.type == "preset" ? (
|
||||
/* Edit & update presets */
|
||||
<AgentRunDraftView
|
||||
graph={graph}
|
||||
agentPreset={
|
||||
agentPresets.find((preset) => preset.id == selectedView.id)!
|
||||
}
|
||||
onRun={selectRun}
|
||||
recommendedScheduleCron={agent?.recommended_schedule_cron || null}
|
||||
onCreateSchedule={onCreateSchedule}
|
||||
onUpdatePreset={onUpdatePreset}
|
||||
doDeletePreset={setConfirmingDeleteAgentPreset}
|
||||
agentActions={agentActions}
|
||||
/>
|
||||
) : selectedView.type == "schedule" ? (
|
||||
selectedSchedule &&
|
||||
graph && (
|
||||
<AgentScheduleDetailsView
|
||||
graph={graph}
|
||||
schedule={selectedSchedule}
|
||||
// agent={agent}
|
||||
agentActions={agentActions}
|
||||
onForcedRun={selectRun}
|
||||
doDeleteSchedule={deleteSchedule}
|
||||
/>
|
||||
)
|
||||
) : null) || <LoadingBox className="h-[70vh]" />}
|
||||
|
||||
<DeleteConfirmDialog
|
||||
entityType="agent"
|
||||
open={agentDeleteDialogOpen}
|
||||
onOpenChange={setAgentDeleteDialogOpen}
|
||||
onDoDelete={() =>
|
||||
agent &&
|
||||
api.deleteLibraryAgent(agent.id).then(() => router.push("/library"))
|
||||
}
|
||||
/>
|
||||
|
||||
<DeleteConfirmDialog
|
||||
entityType="agent run"
|
||||
open={!!confirmingDeleteAgentRun}
|
||||
onOpenChange={(open) => !open && setConfirmingDeleteAgentRun(null)}
|
||||
onDoDelete={() =>
|
||||
confirmingDeleteAgentRun && deleteRun(confirmingDeleteAgentRun)
|
||||
}
|
||||
/>
|
||||
<DeleteConfirmDialog
|
||||
entityType={agent.has_external_trigger ? "trigger" : "agent preset"}
|
||||
open={!!confirmingDeleteAgentPreset}
|
||||
onOpenChange={(open) => !open && setConfirmingDeleteAgentPreset(null)}
|
||||
onDoDelete={() =>
|
||||
confirmingDeleteAgentPreset &&
|
||||
deletePreset(confirmingDeleteAgentPreset)
|
||||
}
|
||||
/>
|
||||
{/* Copy agent confirmation dialog */}
|
||||
<Dialog
|
||||
onOpenChange={setCopyAgentDialogOpen}
|
||||
open={copyAgentDialogOpen}
|
||||
>
|
||||
<DialogContent>
|
||||
<DialogHeader>
|
||||
<DialogTitle>You're making an editable copy</DialogTitle>
|
||||
<DialogDescription className="pt-2">
|
||||
The original Marketplace agent stays the same and cannot be
|
||||
edited. We'll save a new version of this agent to your
|
||||
Library. From there, you can customize it however you'd
|
||||
like by clicking "Customize agent" — this will open
|
||||
the builder where you can see and modify the inner workings.
|
||||
</DialogDescription>
|
||||
</DialogHeader>
|
||||
<DialogFooter className="justify-end">
|
||||
<Button
|
||||
type="button"
|
||||
variant="outline"
|
||||
onClick={() => setCopyAgentDialogOpen(false)}
|
||||
>
|
||||
Cancel
|
||||
</Button>
|
||||
<Button type="button" onClick={copyAgent}>
|
||||
Continue
|
||||
</Button>
|
||||
</DialogFooter>
|
||||
</DialogContent>
|
||||
</Dialog>
|
||||
<CreatePresetDialog
|
||||
open={!!creatingPresetFromExecutionID}
|
||||
onOpenChange={() => setCreatingPresetFromExecutionID(null)}
|
||||
onConfirm={handleCreatePresetFromRun}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -1,445 +0,0 @@
|
||||
"use client";
|
||||
import { format, formatDistanceToNow, formatDistanceStrict } from "date-fns";
|
||||
import React, { useCallback, useMemo, useEffect } from "react";
|
||||
|
||||
import {
|
||||
Graph,
|
||||
GraphExecution,
|
||||
GraphExecutionID,
|
||||
GraphExecutionMeta,
|
||||
LibraryAgent,
|
||||
} from "@/lib/autogpt-server-api";
|
||||
import { useBackendAPI } from "@/lib/autogpt-server-api/context";
|
||||
|
||||
import ActionButtonGroup from "@/components/__legacy__/action-button-group";
|
||||
import type { ButtonAction } from "@/components/__legacy__/types";
|
||||
import {
|
||||
Card,
|
||||
CardContent,
|
||||
CardHeader,
|
||||
CardTitle,
|
||||
} from "@/components/__legacy__/ui/card";
|
||||
import {
|
||||
IconRefresh,
|
||||
IconSquare,
|
||||
IconCircleAlert,
|
||||
} from "@/components/__legacy__/ui/icons";
|
||||
import { Input } from "@/components/__legacy__/ui/input";
|
||||
import LoadingBox from "@/components/__legacy__/ui/loading";
|
||||
import {
|
||||
Tooltip,
|
||||
TooltipContent,
|
||||
TooltipProvider,
|
||||
TooltipTrigger,
|
||||
} from "@/components/atoms/Tooltip/BaseTooltip";
|
||||
import { useToastOnFail } from "@/components/molecules/Toast/use-toast";
|
||||
|
||||
import { AgentRunStatus, agentRunStatusMap } from "./agent-run-status-chip";
|
||||
import useCredits from "@/hooks/useCredits";
|
||||
import { AgentRunOutputView } from "./agent-run-output-view";
|
||||
import { analytics } from "@/services/analytics";
|
||||
import { PendingReviewsList } from "@/components/organisms/PendingReviewsList/PendingReviewsList";
|
||||
import { usePendingReviewsForExecution } from "@/hooks/usePendingReviews";
|
||||
|
||||
export function AgentRunDetailsView({
|
||||
agent,
|
||||
graph,
|
||||
run,
|
||||
agentActions,
|
||||
onRun,
|
||||
doDeleteRun,
|
||||
doCreatePresetFromRun,
|
||||
}: {
|
||||
agent: LibraryAgent;
|
||||
graph: Graph;
|
||||
run: GraphExecution | GraphExecutionMeta;
|
||||
agentActions: ButtonAction[];
|
||||
onRun: (runID: GraphExecutionID) => void;
|
||||
doDeleteRun: () => void;
|
||||
doCreatePresetFromRun: () => void;
|
||||
}): React.ReactNode {
|
||||
const api = useBackendAPI();
|
||||
const { formatCredits } = useCredits();
|
||||
|
||||
const runStatus: AgentRunStatus = useMemo(
|
||||
() => agentRunStatusMap[run.status],
|
||||
[run],
|
||||
);
|
||||
|
||||
const {
|
||||
pendingReviews,
|
||||
isLoading: reviewsLoading,
|
||||
refetch: refetchReviews,
|
||||
} = usePendingReviewsForExecution(run.id);
|
||||
|
||||
const toastOnFail = useToastOnFail();
|
||||
|
||||
// Refetch pending reviews when execution status changes to REVIEW
|
||||
useEffect(() => {
|
||||
if (runStatus === "review" && run.id) {
|
||||
refetchReviews();
|
||||
}
|
||||
}, [runStatus, run.id, refetchReviews]);
|
||||
|
||||
const infoStats: { label: string; value: React.ReactNode }[] = useMemo(() => {
|
||||
if (!run) return [];
|
||||
return [
|
||||
{
|
||||
label: "Status",
|
||||
value: runStatus.charAt(0).toUpperCase() + runStatus.slice(1),
|
||||
},
|
||||
{
|
||||
label: "Started",
|
||||
value: run.started_at
|
||||
? `${formatDistanceToNow(run.started_at, { addSuffix: true })}, ${format(run.started_at, "HH:mm")}`
|
||||
: "—",
|
||||
},
|
||||
...(run.stats
|
||||
? [
|
||||
{
|
||||
label: "Duration",
|
||||
value: formatDistanceStrict(0, run.stats.duration * 1000),
|
||||
},
|
||||
{ label: "Steps", value: run.stats.node_exec_count },
|
||||
{ label: "Cost", value: formatCredits(run.stats.cost) },
|
||||
]
|
||||
: []),
|
||||
];
|
||||
}, [run, runStatus, formatCredits]);
|
||||
|
||||
const agentRunInputs:
|
||||
| Record<
|
||||
string,
|
||||
{
|
||||
title?: string;
|
||||
/* type: BlockIOSubType; */
|
||||
value: string | number | undefined;
|
||||
}
|
||||
>
|
||||
| undefined = useMemo(() => {
|
||||
if (!run.inputs) return undefined;
|
||||
// TODO: show (link to) preset - https://github.com/Significant-Gravitas/AutoGPT/issues/9168
|
||||
|
||||
// Add type info from agent input schema
|
||||
return Object.fromEntries(
|
||||
Object.entries(run.inputs).map(([k, v]) => [
|
||||
k,
|
||||
{
|
||||
title: graph.input_schema.properties[k]?.title,
|
||||
// type: graph.input_schema.properties[k].type, // TODO: implement typed graph inputs
|
||||
value: typeof v == "object" ? JSON.stringify(v, undefined, 2) : v,
|
||||
},
|
||||
]),
|
||||
);
|
||||
}, [graph, run]);
|
||||
|
||||
const runAgain = useCallback(() => {
|
||||
if (
|
||||
!run.inputs ||
|
||||
!(graph.credentials_input_schema?.required ?? []).every(
|
||||
(k) => k in (run.credential_inputs ?? {}),
|
||||
)
|
||||
)
|
||||
return;
|
||||
|
||||
if (run.preset_id) {
|
||||
return api
|
||||
.executeLibraryAgentPreset(
|
||||
run.preset_id,
|
||||
run.inputs!,
|
||||
run.credential_inputs!,
|
||||
)
|
||||
.then(({ id }) => {
|
||||
analytics.sendDatafastEvent("run_agent", {
|
||||
name: graph.name,
|
||||
id: graph.id,
|
||||
});
|
||||
onRun(id);
|
||||
})
|
||||
.catch(toastOnFail("execute agent preset"));
|
||||
}
|
||||
|
||||
return api
|
||||
.executeGraph(
|
||||
graph.id,
|
||||
graph.version,
|
||||
run.inputs!,
|
||||
run.credential_inputs!,
|
||||
"library",
|
||||
)
|
||||
.then(({ id }) => {
|
||||
analytics.sendDatafastEvent("run_agent", {
|
||||
name: graph.name,
|
||||
id: graph.id,
|
||||
});
|
||||
onRun(id);
|
||||
})
|
||||
.catch(toastOnFail("execute agent"));
|
||||
}, [api, graph, run, onRun, toastOnFail]);
|
||||
|
||||
const stopRun = useCallback(
|
||||
() => api.stopGraphExecution(graph.id, run.id),
|
||||
[api, graph.id, run.id],
|
||||
);
|
||||
|
||||
const agentRunOutputs:
|
||||
| Record<
|
||||
string,
|
||||
{
|
||||
title?: string;
|
||||
/* type: BlockIOSubType; */
|
||||
values: Array<React.ReactNode>;
|
||||
}
|
||||
>
|
||||
| null
|
||||
| undefined = useMemo(() => {
|
||||
if (!("outputs" in run)) return undefined;
|
||||
if (!["running", "success", "failed", "stopped"].includes(runStatus))
|
||||
return null;
|
||||
|
||||
// Add type info from agent input schema
|
||||
return Object.fromEntries(
|
||||
Object.entries(run.outputs).map(([k, vv]) => [
|
||||
k,
|
||||
{
|
||||
title: graph.output_schema.properties[k].title,
|
||||
/* type: agent.output_schema.properties[k].type */
|
||||
values: vv.map((v) =>
|
||||
typeof v == "object" ? JSON.stringify(v, undefined, 2) : v,
|
||||
),
|
||||
},
|
||||
]),
|
||||
);
|
||||
}, [graph, run, runStatus]);
|
||||
|
||||
const runActions: ButtonAction[] = useMemo(
|
||||
() => [
|
||||
...(["running", "queued"].includes(runStatus)
|
||||
? ([
|
||||
{
|
||||
label: (
|
||||
<>
|
||||
<IconSquare className="mr-2 size-4" />
|
||||
Stop run
|
||||
</>
|
||||
),
|
||||
variant: "secondary",
|
||||
callback: stopRun,
|
||||
},
|
||||
] satisfies ButtonAction[])
|
||||
: []),
|
||||
...(["success", "failed", "stopped"].includes(runStatus) &&
|
||||
!graph.has_external_trigger &&
|
||||
(graph.credentials_input_schema?.required ?? []).every(
|
||||
(k) => k in (run.credential_inputs ?? {}),
|
||||
)
|
||||
? [
|
||||
{
|
||||
label: (
|
||||
<>
|
||||
<IconRefresh className="mr-2 size-4" />
|
||||
Run again
|
||||
</>
|
||||
),
|
||||
callback: runAgain,
|
||||
dataTestId: "run-again-button",
|
||||
},
|
||||
]
|
||||
: []),
|
||||
...(agent.can_access_graph
|
||||
? [
|
||||
{
|
||||
label: "Open run in builder",
|
||||
href: `/build?flowID=${run.graph_id}&flowVersion=${run.graph_version}&flowExecutionID=${run.id}`,
|
||||
},
|
||||
]
|
||||
: []),
|
||||
{ label: "Create preset from run", callback: doCreatePresetFromRun },
|
||||
{ label: "Delete run", variant: "secondary", callback: doDeleteRun },
|
||||
],
|
||||
[
|
||||
runStatus,
|
||||
runAgain,
|
||||
stopRun,
|
||||
doDeleteRun,
|
||||
doCreatePresetFromRun,
|
||||
graph.has_external_trigger,
|
||||
graph.credentials_input_schema?.required,
|
||||
agent.can_access_graph,
|
||||
run.graph_id,
|
||||
run.graph_version,
|
||||
run.id,
|
||||
],
|
||||
);
|
||||
|
||||
return (
|
||||
<div className="agpt-div flex gap-6">
|
||||
<div className="flex flex-1 flex-col gap-4">
|
||||
<Card className="agpt-box">
|
||||
<CardHeader>
|
||||
<CardTitle className="font-poppins text-lg">Info</CardTitle>
|
||||
</CardHeader>
|
||||
|
||||
<CardContent>
|
||||
<div className="flex justify-stretch gap-4">
|
||||
{infoStats.map(({ label, value }) => (
|
||||
<div key={label} className="flex-1">
|
||||
<p className="text-sm font-medium text-black">{label}</p>
|
||||
<p className="text-sm text-neutral-600">{value}</p>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
{run.status === "FAILED" && (
|
||||
<div className="mt-4 rounded-md border border-red-200 bg-red-50 p-3 dark:border-red-800 dark:bg-red-900/20">
|
||||
<p className="text-sm text-red-800 dark:text-red-200">
|
||||
<strong>Error:</strong>{" "}
|
||||
{run.stats?.error ||
|
||||
"The execution failed due to an internal error. You can re-run the agent to retry."}
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
</CardContent>
|
||||
</Card>
|
||||
|
||||
{/* Smart Agent Execution Summary */}
|
||||
{run.stats?.activity_status && (
|
||||
<Card className="agpt-box">
|
||||
<CardHeader>
|
||||
<CardTitle className="flex items-center gap-2 font-poppins text-lg">
|
||||
Task Summary
|
||||
<TooltipProvider>
|
||||
<Tooltip>
|
||||
<TooltipTrigger asChild>
|
||||
<IconCircleAlert className="size-4 cursor-help text-neutral-500 hover:text-neutral-700" />
|
||||
</TooltipTrigger>
|
||||
<TooltipContent>
|
||||
<p className="max-w-xs">
|
||||
This AI-generated summary describes how the agent
|
||||
handled your task. It’s an experimental feature and may
|
||||
occasionally be inaccurate.
|
||||
</p>
|
||||
</TooltipContent>
|
||||
</Tooltip>
|
||||
</TooltipProvider>
|
||||
</CardTitle>
|
||||
</CardHeader>
|
||||
<CardContent className="space-y-4">
|
||||
<p className="text-sm leading-relaxed text-neutral-700">
|
||||
{run.stats.activity_status}
|
||||
</p>
|
||||
|
||||
{/* Correctness Score */}
|
||||
{typeof run.stats.correctness_score === "number" && (
|
||||
<div className="flex items-center gap-3 rounded-lg bg-neutral-50 p-3">
|
||||
<div className="flex items-center gap-2">
|
||||
<span className="text-sm font-medium text-neutral-600">
|
||||
Success Estimate:
|
||||
</span>
|
||||
<div className="flex items-center gap-2">
|
||||
<div className="relative h-2 w-16 overflow-hidden rounded-full bg-neutral-200">
|
||||
<div
|
||||
className={`h-full transition-all ${
|
||||
run.stats.correctness_score >= 0.8
|
||||
? "bg-green-500"
|
||||
: run.stats.correctness_score >= 0.6
|
||||
? "bg-yellow-500"
|
||||
: run.stats.correctness_score >= 0.4
|
||||
? "bg-orange-500"
|
||||
: "bg-red-500"
|
||||
}`}
|
||||
style={{
|
||||
width: `${Math.round(run.stats.correctness_score * 100)}%`,
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
<span className="text-sm font-medium">
|
||||
{Math.round(run.stats.correctness_score * 100)}%
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
<TooltipProvider>
|
||||
<Tooltip>
|
||||
<TooltipTrigger asChild>
|
||||
<IconCircleAlert className="size-4 cursor-help text-neutral-400 hover:text-neutral-600" />
|
||||
</TooltipTrigger>
|
||||
<TooltipContent>
|
||||
<p className="max-w-xs">
|
||||
AI-generated estimate of how well this execution
|
||||
achieved its intended purpose. This score indicates
|
||||
{run.stats.correctness_score >= 0.8
|
||||
? " the agent was highly successful."
|
||||
: run.stats.correctness_score >= 0.6
|
||||
? " the agent was mostly successful with minor issues."
|
||||
: run.stats.correctness_score >= 0.4
|
||||
? " the agent was partially successful with some gaps."
|
||||
: " the agent had limited success with significant issues."}
|
||||
</p>
|
||||
</TooltipContent>
|
||||
</Tooltip>
|
||||
</TooltipProvider>
|
||||
</div>
|
||||
)}
|
||||
</CardContent>
|
||||
</Card>
|
||||
)}
|
||||
|
||||
{agentRunOutputs !== null && (
|
||||
<AgentRunOutputView agentRunOutputs={agentRunOutputs} />
|
||||
)}
|
||||
|
||||
{/* Pending Reviews Section */}
|
||||
{runStatus === "review" && (
|
||||
<Card className="agpt-box">
|
||||
<CardHeader>
|
||||
<CardTitle className="font-poppins text-lg">
|
||||
Pending Reviews ({pendingReviews.length})
|
||||
</CardTitle>
|
||||
</CardHeader>
|
||||
<CardContent>
|
||||
{reviewsLoading ? (
|
||||
<LoadingBox spinnerSize={12} className="h-24" />
|
||||
) : pendingReviews.length > 0 ? (
|
||||
<PendingReviewsList
|
||||
reviews={pendingReviews}
|
||||
onReviewComplete={refetchReviews}
|
||||
emptyMessage="No pending reviews for this execution"
|
||||
/>
|
||||
) : (
|
||||
<div className="py-4 text-neutral-600">
|
||||
No pending reviews for this execution
|
||||
</div>
|
||||
)}
|
||||
</CardContent>
|
||||
</Card>
|
||||
)}
|
||||
|
||||
<Card className="agpt-box">
|
||||
<CardHeader>
|
||||
<CardTitle className="font-poppins text-lg">Input</CardTitle>
|
||||
</CardHeader>
|
||||
<CardContent className="flex flex-col gap-4">
|
||||
{agentRunInputs !== undefined ? (
|
||||
Object.entries(agentRunInputs).map(([key, { title, value }]) => (
|
||||
<div key={key} className="flex flex-col gap-1.5">
|
||||
<label className="text-sm font-medium">{title || key}</label>
|
||||
<Input value={value} className="rounded-full" disabled />
|
||||
</div>
|
||||
))
|
||||
) : (
|
||||
<LoadingBox spinnerSize={12} className="h-24" />
|
||||
)}
|
||||
</CardContent>
|
||||
</Card>
|
||||
</div>
|
||||
|
||||
{/* Run / Agent Actions */}
|
||||
<aside className="w-48 xl:w-56">
|
||||
<div className="flex flex-col gap-8">
|
||||
<ActionButtonGroup title="Run actions" actions={runActions} />
|
||||
|
||||
<ActionButtonGroup title="Agent actions" actions={agentActions} />
|
||||
</div>
|
||||
</aside>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -1,178 +0,0 @@
|
||||
"use client";
|
||||
|
||||
import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
|
||||
import React, { useMemo } from "react";
|
||||
|
||||
import {
|
||||
Card,
|
||||
CardContent,
|
||||
CardHeader,
|
||||
CardTitle,
|
||||
} from "@/components/__legacy__/ui/card";
|
||||
|
||||
import LoadingBox from "@/components/__legacy__/ui/loading";
|
||||
import type { OutputMetadata } from "../../../../../../../../components/contextual/OutputRenderers";
|
||||
import {
|
||||
globalRegistry,
|
||||
OutputActions,
|
||||
OutputItem,
|
||||
} from "../../../../../../../../components/contextual/OutputRenderers";
|
||||
|
||||
export function AgentRunOutputView({
|
||||
agentRunOutputs,
|
||||
}: {
|
||||
agentRunOutputs:
|
||||
| Record<
|
||||
string,
|
||||
{
|
||||
title?: string;
|
||||
/* type: BlockIOSubType; */
|
||||
values: Array<React.ReactNode>;
|
||||
}
|
||||
>
|
||||
| undefined;
|
||||
}) {
|
||||
const enableEnhancedOutputHandling = useGetFlag(
|
||||
Flag.ENABLE_ENHANCED_OUTPUT_HANDLING,
|
||||
);
|
||||
|
||||
// Prepare items for the renderer system
|
||||
const outputItems = useMemo(() => {
|
||||
if (!agentRunOutputs) return [];
|
||||
|
||||
const items: Array<{
|
||||
key: string;
|
||||
label: string;
|
||||
value: unknown;
|
||||
metadata?: OutputMetadata;
|
||||
renderer: any;
|
||||
}> = [];
|
||||
|
||||
Object.entries(agentRunOutputs).forEach(([key, { title, values }]) => {
|
||||
values.forEach((value, index) => {
|
||||
// Enhanced metadata extraction
|
||||
const metadata: OutputMetadata = {};
|
||||
|
||||
// Type guard to safely access properties
|
||||
if (
|
||||
typeof value === "object" &&
|
||||
value !== null &&
|
||||
!React.isValidElement(value)
|
||||
) {
|
||||
const objValue = value as any;
|
||||
if (objValue.type) metadata.type = objValue.type;
|
||||
if (objValue.mimeType) metadata.mimeType = objValue.mimeType;
|
||||
if (objValue.filename) metadata.filename = objValue.filename;
|
||||
}
|
||||
|
||||
const renderer = globalRegistry.getRenderer(value, metadata);
|
||||
if (renderer) {
|
||||
items.push({
|
||||
key: `${key}-${index}`,
|
||||
label: index === 0 ? title || key : "",
|
||||
value,
|
||||
metadata,
|
||||
renderer,
|
||||
});
|
||||
} else {
|
||||
const textRenderer = globalRegistry
|
||||
.getAllRenderers()
|
||||
.find((r) => r.name === "TextRenderer");
|
||||
if (textRenderer) {
|
||||
items.push({
|
||||
key: `${key}-${index}`,
|
||||
label: index === 0 ? title || key : "",
|
||||
value: JSON.stringify(value, null, 2),
|
||||
metadata,
|
||||
renderer: textRenderer,
|
||||
});
|
||||
}
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
return items;
|
||||
}, [agentRunOutputs]);
|
||||
|
||||
return (
|
||||
<>
|
||||
{enableEnhancedOutputHandling ? (
|
||||
<Card className="agpt-box" style={{ maxWidth: "950px" }}>
|
||||
<CardHeader>
|
||||
<div className="flex items-center justify-between">
|
||||
<CardTitle className="font-poppins text-lg">Output</CardTitle>
|
||||
{outputItems.length > 0 && (
|
||||
<OutputActions
|
||||
items={outputItems.map((item) => ({
|
||||
value: item.value,
|
||||
metadata: item.metadata,
|
||||
renderer: item.renderer,
|
||||
}))}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
</CardHeader>
|
||||
|
||||
<CardContent
|
||||
className="flex flex-col gap-4"
|
||||
style={{ maxWidth: "660px" }}
|
||||
>
|
||||
{agentRunOutputs !== undefined ? (
|
||||
outputItems.length > 0 ? (
|
||||
outputItems.map((item) => (
|
||||
<OutputItem
|
||||
key={item.key}
|
||||
value={item.value}
|
||||
metadata={item.metadata}
|
||||
renderer={item.renderer}
|
||||
label={item.label}
|
||||
/>
|
||||
))
|
||||
) : (
|
||||
<p className="text-sm text-muted-foreground">
|
||||
No outputs to display
|
||||
</p>
|
||||
)
|
||||
) : (
|
||||
<LoadingBox spinnerSize={12} className="h-24" />
|
||||
)}
|
||||
</CardContent>
|
||||
</Card>
|
||||
) : (
|
||||
<Card className="agpt-box" style={{ maxWidth: "950px" }}>
|
||||
<CardHeader>
|
||||
<CardTitle className="font-poppins text-lg">Output</CardTitle>
|
||||
</CardHeader>
|
||||
|
||||
<CardContent
|
||||
className="flex flex-col gap-4"
|
||||
style={{ maxWidth: "660px" }}
|
||||
>
|
||||
{agentRunOutputs !== undefined ? (
|
||||
Object.entries(agentRunOutputs).map(
|
||||
([key, { title, values }]) => (
|
||||
<div key={key} className="flex flex-col gap-1.5">
|
||||
<label className="text-sm font-medium">
|
||||
{title || key}
|
||||
</label>
|
||||
{values.map((value, i) => (
|
||||
<p
|
||||
className="resize-none overflow-x-auto whitespace-pre-wrap break-words border-none text-sm text-neutral-700 disabled:cursor-not-allowed"
|
||||
key={i}
|
||||
>
|
||||
{value}
|
||||
</p>
|
||||
))}
|
||||
{/* TODO: pretty type-dependent rendering */}
|
||||
</div>
|
||||
),
|
||||
)
|
||||
) : (
|
||||
<LoadingBox spinnerSize={12} className="h-24" />
|
||||
)}
|
||||
</CardContent>
|
||||
</Card>
|
||||
)}
|
||||
</>
|
||||
);
|
||||
}
|
||||
@@ -1,68 +0,0 @@
|
||||
import React from "react";
|
||||
|
||||
import { Badge } from "@/components/__legacy__/ui/badge";
|
||||
|
||||
import { GraphExecutionMeta } from "@/lib/autogpt-server-api/types";
|
||||
|
||||
export type AgentRunStatus =
|
||||
| "success"
|
||||
| "failed"
|
||||
| "queued"
|
||||
| "running"
|
||||
| "stopped"
|
||||
| "scheduled"
|
||||
| "draft"
|
||||
| "review";
|
||||
|
||||
export const agentRunStatusMap: Record<
|
||||
GraphExecutionMeta["status"],
|
||||
AgentRunStatus
|
||||
> = {
|
||||
INCOMPLETE: "draft",
|
||||
COMPLETED: "success",
|
||||
FAILED: "failed",
|
||||
QUEUED: "queued",
|
||||
RUNNING: "running",
|
||||
TERMINATED: "stopped",
|
||||
REVIEW: "review",
|
||||
};
|
||||
|
||||
const statusData: Record<
|
||||
AgentRunStatus,
|
||||
{ label: string; variant: keyof typeof statusStyles }
|
||||
> = {
|
||||
success: { label: "Success", variant: "success" },
|
||||
running: { label: "Running", variant: "info" },
|
||||
failed: { label: "Failed", variant: "destructive" },
|
||||
queued: { label: "Queued", variant: "warning" },
|
||||
draft: { label: "Draft", variant: "secondary" },
|
||||
stopped: { label: "Stopped", variant: "secondary" },
|
||||
scheduled: { label: "Scheduled", variant: "secondary" },
|
||||
review: { label: "In Review", variant: "warning" },
|
||||
};
|
||||
|
||||
const statusStyles = {
|
||||
success:
|
||||
"bg-green-100 text-green-800 hover:bg-green-100 hover:text-green-800",
|
||||
destructive: "bg-red-100 text-red-800 hover:bg-red-100 hover:text-red-800",
|
||||
warning:
|
||||
"bg-yellow-100 text-yellow-800 hover:bg-yellow-100 hover:text-yellow-800",
|
||||
info: "bg-blue-100 text-blue-800 hover:bg-blue-100 hover:text-blue-800",
|
||||
secondary:
|
||||
"bg-slate-100 text-slate-800 hover:bg-slate-100 hover:text-slate-800",
|
||||
};
|
||||
|
||||
export function AgentRunStatusChip({
|
||||
status,
|
||||
}: {
|
||||
status: AgentRunStatus;
|
||||
}): React.ReactElement {
|
||||
return (
|
||||
<Badge
|
||||
variant="secondary"
|
||||
className={`text-xs font-medium ${statusStyles[statusData[status]?.variant]} rounded-[45px] px-[9px] py-[3px]`}
|
||||
>
|
||||
{statusData[status]?.label}
|
||||
</Badge>
|
||||
);
|
||||
}
|
||||
@@ -1,130 +0,0 @@
|
||||
import React from "react";
|
||||
import { formatDistanceToNow, isPast } from "date-fns";
|
||||
|
||||
import { cn } from "@/lib/utils";
|
||||
|
||||
import { Link2Icon, Link2OffIcon, MoreVertical } from "lucide-react";
|
||||
import { Card, CardContent } from "@/components/__legacy__/ui/card";
|
||||
import { Button } from "@/components/__legacy__/ui/button";
|
||||
import {
|
||||
DropdownMenu,
|
||||
DropdownMenuContent,
|
||||
DropdownMenuItem,
|
||||
DropdownMenuTrigger,
|
||||
} from "@/components/__legacy__/ui/dropdown-menu";
|
||||
|
||||
import { AgentStatus, AgentStatusChip } from "./agent-status-chip";
|
||||
import { AgentRunStatus, AgentRunStatusChip } from "./agent-run-status-chip";
|
||||
import { PushPinSimpleIcon } from "@phosphor-icons/react";
|
||||
|
||||
export type AgentRunSummaryProps = (
|
||||
| {
|
||||
type: "run";
|
||||
status: AgentRunStatus;
|
||||
}
|
||||
| {
|
||||
type: "preset";
|
||||
status?: undefined;
|
||||
}
|
||||
| {
|
||||
type: "preset.triggered";
|
||||
status: AgentStatus;
|
||||
}
|
||||
| {
|
||||
type: "schedule";
|
||||
status: "scheduled";
|
||||
}
|
||||
) & {
|
||||
title: string;
|
||||
timestamp?: number | Date;
|
||||
selected?: boolean;
|
||||
onClick?: () => void;
|
||||
// onRename: () => void;
|
||||
onDelete: () => void;
|
||||
onPinAsPreset?: () => void;
|
||||
className?: string;
|
||||
};
|
||||
|
||||
export function AgentRunSummaryCard({
|
||||
type,
|
||||
status,
|
||||
title,
|
||||
timestamp,
|
||||
selected = false,
|
||||
onClick,
|
||||
// onRename,
|
||||
onDelete,
|
||||
onPinAsPreset,
|
||||
className,
|
||||
}: AgentRunSummaryProps): React.ReactElement {
|
||||
return (
|
||||
<Card
|
||||
className={cn(
|
||||
"agpt-rounded-card cursor-pointer border-zinc-300",
|
||||
selected ? "agpt-card-selected" : "",
|
||||
className,
|
||||
)}
|
||||
onClick={onClick}
|
||||
>
|
||||
<CardContent className="relative p-2.5 lg:p-4">
|
||||
{(type == "run" || type == "schedule") && (
|
||||
<AgentRunStatusChip status={status} />
|
||||
)}
|
||||
{type == "preset" && (
|
||||
<div className="flex items-center text-sm font-medium text-neutral-700">
|
||||
<PushPinSimpleIcon className="mr-1 size-4 text-foreground" /> Preset
|
||||
</div>
|
||||
)}
|
||||
{type == "preset.triggered" && (
|
||||
<div className="flex items-center justify-between">
|
||||
<AgentStatusChip status={status} />
|
||||
|
||||
<div className="flex items-center text-sm font-medium text-neutral-700">
|
||||
{status == "inactive" ? (
|
||||
<Link2OffIcon className="mr-1 size-4 text-foreground" />
|
||||
) : (
|
||||
<Link2Icon className="mr-1 size-4 text-foreground" />
|
||||
)}{" "}
|
||||
Trigger
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
<div className="mt-5 flex items-center justify-between">
|
||||
<h3 className="truncate pr-2 text-base font-medium text-neutral-900">
|
||||
{title}
|
||||
</h3>
|
||||
|
||||
<DropdownMenu>
|
||||
<DropdownMenuTrigger asChild>
|
||||
<Button variant="ghost" className="h-5 w-5 p-0">
|
||||
<MoreVertical className="h-5 w-5" />
|
||||
</Button>
|
||||
</DropdownMenuTrigger>
|
||||
<DropdownMenuContent>
|
||||
{onPinAsPreset && (
|
||||
<DropdownMenuItem onClick={onPinAsPreset}>
|
||||
Pin as a preset
|
||||
</DropdownMenuItem>
|
||||
)}
|
||||
|
||||
{/* <DropdownMenuItem onClick={onRename}>Rename</DropdownMenuItem> */}
|
||||
|
||||
<DropdownMenuItem onClick={onDelete}>Delete</DropdownMenuItem>
|
||||
</DropdownMenuContent>
|
||||
</DropdownMenu>
|
||||
</div>
|
||||
|
||||
{timestamp && (
|
||||
<p
|
||||
className="mt-1 text-sm font-normal text-neutral-500"
|
||||
title={new Date(timestamp).toString()}
|
||||
>
|
||||
{isPast(timestamp) ? "Ran" : "Runs in"}{" "}
|
||||
{formatDistanceToNow(timestamp, { addSuffix: true })}
|
||||
</p>
|
||||
)}
|
||||
</CardContent>
|
||||
</Card>
|
||||
);
|
||||
}
|
||||
@@ -1,237 +0,0 @@
|
||||
"use client";
|
||||
import { Plus } from "lucide-react";
|
||||
import React, { useEffect, useState } from "react";
|
||||
|
||||
import {
|
||||
GraphExecutionID,
|
||||
GraphExecutionMeta,
|
||||
LibraryAgent,
|
||||
LibraryAgentPreset,
|
||||
LibraryAgentPresetID,
|
||||
Schedule,
|
||||
ScheduleID,
|
||||
} from "@/lib/autogpt-server-api";
|
||||
import { cn } from "@/lib/utils";
|
||||
|
||||
import { Badge } from "@/components/__legacy__/ui/badge";
|
||||
import { Button } from "@/components/atoms/Button/Button";
|
||||
import LoadingBox, { LoadingSpinner } from "@/components/__legacy__/ui/loading";
|
||||
import { Separator } from "@/components/__legacy__/ui/separator";
|
||||
import { ScrollArea } from "@/components/__legacy__/ui/scroll-area";
|
||||
import { InfiniteScroll } from "@/components/contextual/InfiniteScroll/InfiniteScroll";
|
||||
import { AgentRunsQuery } from "../use-agent-runs";
|
||||
import { agentRunStatusMap } from "./agent-run-status-chip";
|
||||
import { AgentRunSummaryCard } from "./agent-run-summary-card";
|
||||
|
||||
interface AgentRunsSelectorListProps {
|
||||
agent: LibraryAgent;
|
||||
agentRunsQuery: AgentRunsQuery;
|
||||
agentPresets: LibraryAgentPreset[];
|
||||
schedules: Schedule[];
|
||||
selectedView: { type: "run" | "preset" | "schedule"; id?: string };
|
||||
allowDraftNewRun?: boolean;
|
||||
onSelectRun: (id: GraphExecutionID) => void;
|
||||
onSelectPreset: (preset: LibraryAgentPresetID) => void;
|
||||
onSelectSchedule: (id: ScheduleID) => void;
|
||||
onSelectDraftNewRun: () => void;
|
||||
doDeleteRun: (id: GraphExecutionMeta) => void;
|
||||
doDeletePreset: (id: LibraryAgentPresetID) => void;
|
||||
doDeleteSchedule: (id: ScheduleID) => void;
|
||||
doCreatePresetFromRun?: (id: GraphExecutionID) => void;
|
||||
className?: string;
|
||||
}
|
||||
|
||||
export function AgentRunsSelectorList({
|
||||
agent,
|
||||
agentRunsQuery: {
|
||||
agentRuns,
|
||||
agentRunCount,
|
||||
agentRunsLoading,
|
||||
hasMoreRuns,
|
||||
fetchMoreRuns,
|
||||
isFetchingMoreRuns,
|
||||
},
|
||||
agentPresets,
|
||||
schedules,
|
||||
selectedView,
|
||||
allowDraftNewRun = true,
|
||||
onSelectRun,
|
||||
onSelectPreset,
|
||||
onSelectSchedule,
|
||||
onSelectDraftNewRun,
|
||||
doDeleteRun,
|
||||
doDeletePreset,
|
||||
doDeleteSchedule,
|
||||
doCreatePresetFromRun,
|
||||
className,
|
||||
}: AgentRunsSelectorListProps): React.ReactElement {
|
||||
const [activeListTab, setActiveListTab] = useState<"runs" | "scheduled">(
|
||||
"runs",
|
||||
);
|
||||
|
||||
useEffect(() => {
|
||||
if (selectedView.type === "schedule") {
|
||||
setActiveListTab("scheduled");
|
||||
} else {
|
||||
setActiveListTab("runs");
|
||||
}
|
||||
}, [selectedView]);
|
||||
|
||||
const listItemClasses = "h-28 w-72 lg:w-full lg:h-32";
|
||||
|
||||
return (
|
||||
<aside className={cn("flex flex-col gap-4", className)}>
|
||||
{allowDraftNewRun ? (
|
||||
<Button
|
||||
className={"mb-4 hidden lg:flex"}
|
||||
onClick={onSelectDraftNewRun}
|
||||
leftIcon={<Plus className="h-6 w-6" />}
|
||||
>
|
||||
New {agent.has_external_trigger ? "trigger" : "run"}
|
||||
</Button>
|
||||
) : null}
|
||||
|
||||
<div className="flex gap-2">
|
||||
<Badge
|
||||
variant={activeListTab === "runs" ? "secondary" : "outline"}
|
||||
className="cursor-pointer gap-2 rounded-full text-base"
|
||||
onClick={() => setActiveListTab("runs")}
|
||||
>
|
||||
<span>Runs</span>
|
||||
<span className="text-neutral-600">
|
||||
{agentRunCount ?? <LoadingSpinner className="size-4" />}
|
||||
</span>
|
||||
</Badge>
|
||||
|
||||
<Badge
|
||||
variant={activeListTab === "scheduled" ? "secondary" : "outline"}
|
||||
className="cursor-pointer gap-2 rounded-full text-base"
|
||||
onClick={() => setActiveListTab("scheduled")}
|
||||
>
|
||||
<span>Scheduled</span>
|
||||
<span className="text-neutral-600">{schedules.length}</span>
|
||||
</Badge>
|
||||
</div>
|
||||
|
||||
{/* Runs / Schedules list */}
|
||||
{agentRunsLoading && activeListTab === "runs" ? (
|
||||
<LoadingBox className="h-28 w-full lg:h-[calc(100vh-300px)] lg:w-72 xl:w-80" />
|
||||
) : (
|
||||
<ScrollArea
|
||||
className="w-full lg:h-[calc(100vh-300px)] lg:w-72 xl:w-80"
|
||||
orientation={window.innerWidth >= 1024 ? "vertical" : "horizontal"}
|
||||
>
|
||||
<InfiniteScroll
|
||||
direction={window.innerWidth >= 1024 ? "vertical" : "horizontal"}
|
||||
hasNextPage={hasMoreRuns}
|
||||
fetchNextPage={fetchMoreRuns}
|
||||
isFetchingNextPage={isFetchingMoreRuns}
|
||||
>
|
||||
<div className="flex items-center gap-2 lg:flex-col">
|
||||
{/* New Run button - only in small layouts */}
|
||||
{allowDraftNewRun && (
|
||||
<Button
|
||||
size="large"
|
||||
className={
|
||||
"flex h-12 w-40 items-center gap-2 py-6 lg:hidden " +
|
||||
(selectedView.type == "run" && !selectedView.id
|
||||
? "agpt-card-selected text-accent"
|
||||
: "")
|
||||
}
|
||||
onClick={onSelectDraftNewRun}
|
||||
leftIcon={<Plus className="h-6 w-6" />}
|
||||
>
|
||||
New {agent.has_external_trigger ? "trigger" : "run"}
|
||||
</Button>
|
||||
)}
|
||||
|
||||
{activeListTab === "runs" ? (
|
||||
<>
|
||||
{agentPresets
|
||||
.filter((preset) => preset.webhook) // Triggers
|
||||
.toSorted(
|
||||
(a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
|
||||
)
|
||||
.map((preset) => (
|
||||
<AgentRunSummaryCard
|
||||
className={cn(listItemClasses, "lg:h-auto")}
|
||||
key={preset.id}
|
||||
type="preset.triggered"
|
||||
status={preset.is_active ? "active" : "inactive"}
|
||||
title={preset.name}
|
||||
// timestamp={preset.last_run_time} // TODO: implement this
|
||||
selected={selectedView.id === preset.id}
|
||||
onClick={() => onSelectPreset(preset.id)}
|
||||
onDelete={() => doDeletePreset(preset.id)}
|
||||
/>
|
||||
))}
|
||||
{agentPresets
|
||||
.filter((preset) => !preset.webhook) // Presets
|
||||
.toSorted(
|
||||
(a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
|
||||
)
|
||||
.map((preset) => (
|
||||
<AgentRunSummaryCard
|
||||
className={cn(listItemClasses, "lg:h-auto")}
|
||||
key={preset.id}
|
||||
type="preset"
|
||||
title={preset.name}
|
||||
// timestamp={preset.last_run_time} // TODO: implement this
|
||||
selected={selectedView.id === preset.id}
|
||||
onClick={() => onSelectPreset(preset.id)}
|
||||
onDelete={() => doDeletePreset(preset.id)}
|
||||
/>
|
||||
))}
|
||||
{agentPresets.length > 0 && <Separator className="my-1" />}
|
||||
{agentRuns
|
||||
.toSorted((a, b) => {
|
||||
const aTime = a.started_at?.getTime() ?? 0;
|
||||
const bTime = b.started_at?.getTime() ?? 0;
|
||||
return bTime - aTime;
|
||||
})
|
||||
.map((run) => (
|
||||
<AgentRunSummaryCard
|
||||
className={listItemClasses}
|
||||
key={run.id}
|
||||
type="run"
|
||||
status={agentRunStatusMap[run.status]}
|
||||
title={
|
||||
(run.preset_id
|
||||
? agentPresets.find((p) => p.id == run.preset_id)
|
||||
?.name
|
||||
: null) ?? agent.name
|
||||
}
|
||||
timestamp={run.started_at ?? undefined}
|
||||
selected={selectedView.id === run.id}
|
||||
onClick={() => onSelectRun(run.id)}
|
||||
onDelete={() => doDeleteRun(run as GraphExecutionMeta)}
|
||||
onPinAsPreset={
|
||||
doCreatePresetFromRun
|
||||
? () => doCreatePresetFromRun(run.id)
|
||||
: undefined
|
||||
}
|
||||
/>
|
||||
))}
|
||||
</>
|
||||
) : (
|
||||
schedules.map((schedule) => (
|
||||
<AgentRunSummaryCard
|
||||
className={listItemClasses}
|
||||
key={schedule.id}
|
||||
type="schedule"
|
||||
status="scheduled" // TODO: implement active/inactive status for schedules
|
||||
title={schedule.name}
|
||||
timestamp={schedule.next_run_time}
|
||||
selected={selectedView.id === schedule.id}
|
||||
onClick={() => onSelectSchedule(schedule.id)}
|
||||
onDelete={() => doDeleteSchedule(schedule.id)}
|
||||
/>
|
||||
))
|
||||
)}
|
||||
</div>
|
||||
</InfiniteScroll>
|
||||
</ScrollArea>
|
||||
)}
|
||||
</aside>
|
||||
);
|
||||
}
|
||||
@@ -1,180 +0,0 @@
|
||||
"use client";
|
||||
import React, { useCallback, useMemo } from "react";
|
||||
|
||||
import {
|
||||
Graph,
|
||||
GraphExecutionID,
|
||||
Schedule,
|
||||
ScheduleID,
|
||||
} from "@/lib/autogpt-server-api";
|
||||
import { useBackendAPI } from "@/lib/autogpt-server-api/context";
|
||||
|
||||
import ActionButtonGroup from "@/components/__legacy__/action-button-group";
|
||||
import type { ButtonAction } from "@/components/__legacy__/types";
|
||||
import {
|
||||
Card,
|
||||
CardContent,
|
||||
CardHeader,
|
||||
CardTitle,
|
||||
} from "@/components/__legacy__/ui/card";
|
||||
import { IconCross } from "@/components/__legacy__/ui/icons";
|
||||
import { Input } from "@/components/__legacy__/ui/input";
|
||||
import LoadingBox from "@/components/__legacy__/ui/loading";
|
||||
import { useToastOnFail } from "@/components/molecules/Toast/use-toast";
|
||||
import { humanizeCronExpression } from "@/lib/cron-expression-utils";
|
||||
import { formatScheduleTime } from "@/lib/timezone-utils";
|
||||
import { useUserTimezone } from "@/lib/hooks/useUserTimezone";
|
||||
import { PlayIcon } from "lucide-react";
|
||||
|
||||
import { AgentRunStatus } from "./agent-run-status-chip";
|
||||
|
||||
export function AgentScheduleDetailsView({
|
||||
graph,
|
||||
schedule,
|
||||
agentActions,
|
||||
onForcedRun,
|
||||
doDeleteSchedule,
|
||||
}: {
|
||||
graph: Graph;
|
||||
schedule: Schedule;
|
||||
agentActions: ButtonAction[];
|
||||
onForcedRun: (runID: GraphExecutionID) => void;
|
||||
doDeleteSchedule: (scheduleID: ScheduleID) => void;
|
||||
}): React.ReactNode {
|
||||
const api = useBackendAPI();
|
||||
|
||||
const selectedRunStatus: AgentRunStatus = "scheduled";
|
||||
|
||||
const toastOnFail = useToastOnFail();
|
||||
|
||||
// Get user's timezone for displaying schedule times
|
||||
const userTimezone = useUserTimezone();
|
||||
|
||||
const infoStats: { label: string; value: React.ReactNode }[] = useMemo(() => {
|
||||
return [
|
||||
{
|
||||
label: "Status",
|
||||
value:
|
||||
selectedRunStatus.charAt(0).toUpperCase() +
|
||||
selectedRunStatus.slice(1),
|
||||
},
|
||||
{
|
||||
label: "Schedule",
|
||||
value: humanizeCronExpression(schedule.cron),
|
||||
},
|
||||
{
|
||||
label: "Next run",
|
||||
value: formatScheduleTime(schedule.next_run_time, userTimezone),
|
||||
},
|
||||
];
|
||||
}, [schedule, selectedRunStatus, userTimezone]);
|
||||
|
||||
const agentRunInputs: Record<
|
||||
string,
|
||||
{ title?: string; /* type: BlockIOSubType; */ value: any }
|
||||
> = useMemo(() => {
|
||||
// TODO: show (link to) preset - https://github.com/Significant-Gravitas/AutoGPT/issues/9168
|
||||
|
||||
// Add type info from agent input schema
|
||||
return Object.fromEntries(
|
||||
Object.entries(schedule.input_data).map(([k, v]) => [
|
||||
k,
|
||||
{
|
||||
title: graph.input_schema.properties[k].title,
|
||||
/* TODO: type: agent.input_schema.properties[k].type */
|
||||
value: v,
|
||||
},
|
||||
]),
|
||||
);
|
||||
}, [graph, schedule]);
|
||||
|
||||
const runNow = useCallback(
|
||||
() =>
|
||||
api
|
||||
.executeGraph(
|
||||
graph.id,
|
||||
graph.version,
|
||||
schedule.input_data,
|
||||
schedule.input_credentials,
|
||||
"library",
|
||||
)
|
||||
.then((run) => onForcedRun(run.id))
|
||||
.catch(toastOnFail("execute agent")),
|
||||
[api, graph, schedule, onForcedRun, toastOnFail],
|
||||
);
|
||||
|
||||
const runActions: ButtonAction[] = useMemo(
|
||||
() => [
|
||||
{
|
||||
label: (
|
||||
<>
|
||||
<PlayIcon className="mr-2 size-4" />
|
||||
Run now
|
||||
</>
|
||||
),
|
||||
callback: runNow,
|
||||
},
|
||||
{
|
||||
label: (
|
||||
<>
|
||||
<IconCross className="mr-2 size-4 px-0.5" />
|
||||
Delete schedule
|
||||
</>
|
||||
),
|
||||
callback: () => doDeleteSchedule(schedule.id),
|
||||
variant: "destructive",
|
||||
},
|
||||
],
|
||||
[runNow],
|
||||
);
|
||||
|
||||
return (
|
||||
<div className="agpt-div flex gap-6">
|
||||
<div className="flex flex-1 flex-col gap-4">
|
||||
<Card className="agpt-box">
|
||||
<CardHeader>
|
||||
<CardTitle className="font-poppins text-lg">Info</CardTitle>
|
||||
</CardHeader>
|
||||
|
||||
<CardContent>
|
||||
<div className="flex justify-stretch gap-4">
|
||||
{infoStats.map(({ label, value }) => (
|
||||
<div key={label} className="flex-1">
|
||||
<p className="text-sm font-medium text-black">{label}</p>
|
||||
<p className="text-sm text-neutral-600">{value}</p>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</CardContent>
|
||||
</Card>
|
||||
|
||||
<Card className="agpt-box">
|
||||
<CardHeader>
|
||||
<CardTitle className="font-poppins text-lg">Input</CardTitle>
|
||||
</CardHeader>
|
||||
<CardContent className="flex flex-col gap-4">
|
||||
{agentRunInputs !== undefined ? (
|
||||
Object.entries(agentRunInputs).map(([key, { title, value }]) => (
|
||||
<div key={key} className="flex flex-col gap-1.5">
|
||||
<label className="text-sm font-medium">{title || key}</label>
|
||||
<Input value={value} className="rounded-full" disabled />
|
||||
</div>
|
||||
))
|
||||
) : (
|
||||
<LoadingBox spinnerSize={12} className="h-24" />
|
||||
)}
|
||||
</CardContent>
|
||||
</Card>
|
||||
</div>
|
||||
|
||||
{/* Run / Agent Actions */}
|
||||
<aside className="w-48 xl:w-56">
|
||||
<div className="flex flex-col gap-8">
|
||||
<ActionButtonGroup title="Run actions" actions={runActions} />
|
||||
|
||||
<ActionButtonGroup title="Agent actions" actions={agentActions} />
|
||||
</div>
|
||||
</aside>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -1,100 +0,0 @@
|
||||
"use client";
|
||||
|
||||
import React, { useState } from "react";
|
||||
import { Button } from "@/components/__legacy__/ui/button";
|
||||
import {
|
||||
Dialog,
|
||||
DialogContent,
|
||||
DialogDescription,
|
||||
DialogFooter,
|
||||
DialogHeader,
|
||||
DialogTitle,
|
||||
} from "@/components/__legacy__/ui/dialog";
|
||||
import { Input } from "@/components/__legacy__/ui/input";
|
||||
import { Textarea } from "@/components/__legacy__/ui/textarea";
|
||||
|
||||
interface CreatePresetDialogProps {
|
||||
open: boolean;
|
||||
onOpenChange: (open: boolean) => void;
|
||||
onConfirm: (name: string, description: string) => Promise<void> | void;
|
||||
}
|
||||
|
||||
export function CreatePresetDialog({
|
||||
open,
|
||||
onOpenChange,
|
||||
onConfirm,
|
||||
}: CreatePresetDialogProps) {
|
||||
const [name, setName] = useState("");
|
||||
const [description, setDescription] = useState("");
|
||||
|
||||
const handleSubmit = async () => {
|
||||
if (name.trim()) {
|
||||
await onConfirm(name.trim(), description.trim());
|
||||
setName("");
|
||||
setDescription("");
|
||||
onOpenChange(false);
|
||||
}
|
||||
};
|
||||
|
||||
const handleCancel = () => {
|
||||
setName("");
|
||||
setDescription("");
|
||||
onOpenChange(false);
|
||||
};
|
||||
|
||||
const handleKeyDown = (e: React.KeyboardEvent) => {
|
||||
if (e.key === "Enter" && (e.metaKey || e.ctrlKey)) {
|
||||
e.preventDefault();
|
||||
handleSubmit();
|
||||
}
|
||||
};
|
||||
|
||||
return (
|
||||
<Dialog open={open} onOpenChange={onOpenChange}>
|
||||
<DialogContent className="sm:max-w-[425px]">
|
||||
<DialogHeader>
|
||||
<DialogTitle>Create Preset</DialogTitle>
|
||||
<DialogDescription>
|
||||
Give your preset a name and description to help identify it later.
|
||||
</DialogDescription>
|
||||
</DialogHeader>
|
||||
<div className="grid gap-4 py-4">
|
||||
<div className="grid gap-2">
|
||||
<label htmlFor="preset-name" className="text-sm font-medium">
|
||||
Name *
|
||||
</label>
|
||||
<Input
|
||||
id="preset-name"
|
||||
placeholder="Enter preset name"
|
||||
value={name}
|
||||
onChange={(e) => setName(e.target.value)}
|
||||
onKeyDown={handleKeyDown}
|
||||
autoFocus
|
||||
/>
|
||||
</div>
|
||||
<div className="grid gap-2">
|
||||
<label htmlFor="preset-description" className="text-sm font-medium">
|
||||
Description
|
||||
</label>
|
||||
<Textarea
|
||||
id="preset-description"
|
||||
placeholder="Optional description"
|
||||
value={description}
|
||||
onChange={(e) => setDescription(e.target.value)}
|
||||
onKeyDown={handleKeyDown}
|
||||
rows={3}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
<DialogFooter>
|
||||
<Button variant="outline" onClick={handleCancel}>
|
||||
Cancel
|
||||
</Button>
|
||||
<Button onClick={handleSubmit} disabled={!name.trim()}>
|
||||
Create Preset
|
||||
</Button>
|
||||
</DialogFooter>
|
||||
</DialogContent>
|
||||
</Dialog>
|
||||
);
|
||||
}
|
||||
@@ -1,210 +0,0 @@
|
||||
import {
|
||||
GraphExecutionMeta as LegacyGraphExecutionMeta,
|
||||
GraphID,
|
||||
GraphExecutionID,
|
||||
} from "@/lib/autogpt-server-api";
|
||||
import { getQueryClient } from "@/lib/react-query/queryClient";
|
||||
import {
|
||||
getPaginatedTotalCount,
|
||||
getPaginationNextPageNumber,
|
||||
unpaginate,
|
||||
} from "@/app/api/helpers";
|
||||
import {
|
||||
getV1ListGraphExecutionsResponse,
|
||||
getV1ListGraphExecutionsResponse200,
|
||||
useGetV1ListGraphExecutionsInfinite,
|
||||
} from "@/app/api/__generated__/endpoints/graphs/graphs";
|
||||
import { GraphExecutionsPaginated } from "@/app/api/__generated__/models/graphExecutionsPaginated";
|
||||
import { GraphExecutionMeta as RawGraphExecutionMeta } from "@/app/api/__generated__/models/graphExecutionMeta";
|
||||
|
||||
export type GraphExecutionMeta = Omit<
|
||||
RawGraphExecutionMeta,
|
||||
"id" | "user_id" | "graph_id" | "preset_id" | "stats"
|
||||
> &
|
||||
Pick<
|
||||
LegacyGraphExecutionMeta,
|
||||
"id" | "user_id" | "graph_id" | "preset_id" | "stats"
|
||||
>;
|
||||
|
||||
/** Hook to fetch runs for a specific graph, with support for infinite scroll.
|
||||
*
|
||||
* @param graphID - The ID of the graph to fetch agent runs for. This parameter is
|
||||
* optional in the sense that the hook doesn't run unless it is passed.
|
||||
* This way, it can be used in components where the graph ID is not
|
||||
* immediately available.
|
||||
*/
|
||||
export const useAgentRunsInfinite = (graphID?: GraphID) => {
|
||||
const queryClient = getQueryClient();
|
||||
const {
|
||||
data: queryResults,
|
||||
refetch: refetchRuns,
|
||||
isPending: agentRunsLoading,
|
||||
isRefetching: agentRunsReloading,
|
||||
hasNextPage: hasMoreRuns,
|
||||
fetchNextPage: fetchMoreRuns,
|
||||
isFetchingNextPage: isFetchingMoreRuns,
|
||||
queryKey,
|
||||
} = useGetV1ListGraphExecutionsInfinite(
|
||||
graphID!,
|
||||
{ page: 1, page_size: 20 },
|
||||
{
|
||||
query: {
|
||||
getNextPageParam: getPaginationNextPageNumber,
|
||||
|
||||
// Prevent query from running if graphID is not available (yet)
|
||||
...(!graphID
|
||||
? {
|
||||
enabled: false,
|
||||
queryFn: () =>
|
||||
// Fake empty response if graphID is not available (yet)
|
||||
Promise.resolve({
|
||||
status: 200,
|
||||
data: {
|
||||
executions: [],
|
||||
pagination: {
|
||||
current_page: 1,
|
||||
page_size: 20,
|
||||
total_items: 0,
|
||||
total_pages: 0,
|
||||
},
|
||||
},
|
||||
headers: new Headers(),
|
||||
} satisfies getV1ListGraphExecutionsResponse),
|
||||
}
|
||||
: {}),
|
||||
},
|
||||
},
|
||||
queryClient,
|
||||
);
|
||||
|
||||
const agentRuns = queryResults ? unpaginate(queryResults, "executions") : [];
|
||||
const agentRunCount = getPaginatedTotalCount(queryResults);
|
||||
|
||||
const upsertAgentRun = (newAgentRun: GraphExecutionMeta) => {
|
||||
queryClient.setQueryData(
|
||||
queryKey,
|
||||
(currentQueryData: typeof queryResults) => {
|
||||
if (!currentQueryData?.pages || agentRunCount === undefined)
|
||||
return currentQueryData;
|
||||
|
||||
const exists = currentQueryData.pages.some((page) => {
|
||||
if (page.status !== 200) return false;
|
||||
|
||||
const response = page.data;
|
||||
return response.executions.some((run) => run.id === newAgentRun.id);
|
||||
});
|
||||
if (exists) {
|
||||
// If the run already exists, we update it
|
||||
return {
|
||||
...currentQueryData,
|
||||
pages: currentQueryData.pages.map((page) => {
|
||||
if (page.status !== 200) return page;
|
||||
const response = page.data;
|
||||
const executions = response.executions;
|
||||
|
||||
const index = executions.findIndex(
|
||||
(run) => run.id === newAgentRun.id,
|
||||
);
|
||||
if (index === -1) return page;
|
||||
|
||||
const newExecutions = [...executions];
|
||||
newExecutions[index] = newAgentRun;
|
||||
|
||||
return {
|
||||
...page,
|
||||
data: {
|
||||
...response,
|
||||
executions: newExecutions,
|
||||
},
|
||||
} satisfies getV1ListGraphExecutionsResponse;
|
||||
}),
|
||||
};
|
||||
}
|
||||
|
||||
// If the run does not exist, we add it to the first page
|
||||
const page = currentQueryData
|
||||
.pages[0] as getV1ListGraphExecutionsResponse200 & {
|
||||
headers: Headers;
|
||||
};
|
||||
const updatedExecutions = [newAgentRun, ...page.data.executions];
|
||||
const updatedPage = {
|
||||
...page,
|
||||
data: {
|
||||
...page.data,
|
||||
executions: updatedExecutions,
|
||||
},
|
||||
} satisfies getV1ListGraphExecutionsResponse;
|
||||
const updatedPages = [updatedPage, ...currentQueryData.pages.slice(1)];
|
||||
return {
|
||||
...currentQueryData,
|
||||
pages: updatedPages.map(
|
||||
// Increment the total runs count in the pagination info of all pages
|
||||
(page) =>
|
||||
page.status === 200
|
||||
? {
|
||||
...page,
|
||||
data: {
|
||||
...page.data,
|
||||
pagination: {
|
||||
...page.data.pagination,
|
||||
total_items: agentRunCount + 1,
|
||||
},
|
||||
},
|
||||
}
|
||||
: page,
|
||||
),
|
||||
};
|
||||
},
|
||||
);
|
||||
};
|
||||
|
||||
const removeAgentRun = (runID: GraphExecutionID) => {
|
||||
queryClient.setQueryData(
|
||||
[queryKey, { page: 1, page_size: 20 }],
|
||||
(currentQueryData: typeof queryResults) => {
|
||||
if (!currentQueryData?.pages) return currentQueryData;
|
||||
|
||||
let found = false;
|
||||
return {
|
||||
...currentQueryData,
|
||||
pages: currentQueryData.pages.map((page) => {
|
||||
const response = page.data as GraphExecutionsPaginated;
|
||||
const filteredExecutions = response.executions.filter(
|
||||
(run) => run.id !== runID,
|
||||
);
|
||||
if (filteredExecutions.length < response.executions.length) {
|
||||
found = true;
|
||||
}
|
||||
|
||||
return {
|
||||
...page,
|
||||
data: {
|
||||
...response,
|
||||
executions: filteredExecutions,
|
||||
pagination: {
|
||||
...response.pagination,
|
||||
total_items:
|
||||
response.pagination.total_items - (found ? 1 : 0),
|
||||
},
|
||||
},
|
||||
};
|
||||
}),
|
||||
};
|
||||
},
|
||||
);
|
||||
};
|
||||
|
||||
return {
|
||||
agentRuns: agentRuns as GraphExecutionMeta[],
|
||||
refetchRuns,
|
||||
agentRunCount,
|
||||
agentRunsLoading: agentRunsLoading || agentRunsReloading,
|
||||
hasMoreRuns,
|
||||
fetchMoreRuns,
|
||||
isFetchingMoreRuns,
|
||||
upsertAgentRun,
|
||||
removeAgentRun,
|
||||
};
|
||||
};
|
||||
|
||||
export type AgentRunsQuery = ReturnType<typeof useAgentRunsInfinite>;
|
||||
@@ -1,7 +0,0 @@
|
||||
"use client";
|
||||
|
||||
import { OldAgentLibraryView } from "../../agents/[id]/components/OldAgentLibraryView/OldAgentLibraryView";
|
||||
|
||||
export default function OldAgentLibraryPage() {
|
||||
return <OldAgentLibraryView />;
|
||||
}
|
||||
@@ -2,7 +2,7 @@ import { useEffect, useState } from "react";
|
||||
import { Input } from "@/components/__legacy__/ui/input";
|
||||
import { Button } from "@/components/__legacy__/ui/button";
|
||||
import { useToast } from "@/components/molecules/Toast/use-toast";
|
||||
import { CronScheduler } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler";
|
||||
import { CronScheduler } from "@/components/contextual/CronScheduler/cron-scheduler";
|
||||
import { Dialog } from "@/components/molecules/Dialog/Dialog";
|
||||
import { getTimezoneDisplayName } from "@/lib/timezone-utils";
|
||||
import { useUserTimezone } from "@/lib/hooks/useUserTimezone";
|
||||
@@ -1,6 +1,6 @@
|
||||
"use client";
|
||||
|
||||
import { CronExpressionDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
|
||||
import { CronExpressionDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
|
||||
import { Form, FormField } from "@/components/__legacy__/ui/form";
|
||||
import { Button } from "@/components/atoms/Button/Button";
|
||||
import { Input } from "@/components/atoms/Input/Input";
|
||||
|
||||
@@ -7,7 +7,6 @@ import { useFlags } from "launchdarkly-react-client-sdk";
|
||||
export enum Flag {
|
||||
BETA_BLOCKS = "beta-blocks",
|
||||
NEW_BLOCK_MENU = "new-block-menu",
|
||||
NEW_AGENT_RUNS = "new-agent-runs",
|
||||
GRAPH_SEARCH = "graph-search",
|
||||
ENABLE_ENHANCED_OUTPUT_HANDLING = "enable-enhanced-output-handling",
|
||||
SHARE_EXECUTION_RESULTS = "share-execution-results",
|
||||
@@ -22,7 +21,6 @@ const isPwMockEnabled = process.env.NEXT_PUBLIC_PW_TEST === "true";
|
||||
const defaultFlags = {
|
||||
[Flag.BETA_BLOCKS]: [],
|
||||
[Flag.NEW_BLOCK_MENU]: false,
|
||||
[Flag.NEW_AGENT_RUNS]: false,
|
||||
[Flag.GRAPH_SEARCH]: false,
|
||||
[Flag.ENABLE_ENHANCED_OUTPUT_HANDLING]: false,
|
||||
[Flag.SHARE_EXECUTION_RESULTS]: false,
|
||||
|
||||
4
autogpt_platform/frontend/src/types/images.d.ts
vendored
Normal file
@@ -0,0 +1,4 @@
|
||||
declare module "*.png" {
|
||||
const content: import("next/image").StaticImageData;
|
||||
export default content;
|
||||
}
|
||||
@@ -65,7 +65,7 @@ The result routes data to yes_output or no_output, enabling intelligent branchin
|
||||
| condition | A plaintext English description of the condition to evaluate | str | Yes |
|
||||
| yes_value | (Optional) Value to output if the condition is true. If not provided, input_value will be used. | Yes Value | No |
|
||||
| no_value | (Optional) Value to output if the condition is false. If not provided, input_value will be used. | No Value | No |
|
||||
| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
|
||||
### Outputs
|
||||
|
||||
@@ -103,7 +103,7 @@ The block sends the entire conversation history to the chosen LLM, including sys
|
||||
|-------|-------------|------|----------|
|
||||
| prompt | The prompt to send to the language model. | str | No |
|
||||
| messages | List of messages in the conversation. | List[Any] | Yes |
|
||||
| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
|
||||
| ollama_host | Ollama host for local models | str | No |
|
||||
|
||||
@@ -257,7 +257,7 @@ The block formulates a prompt based on the given focus or source data, sends it
|
||||
|-------|-------------|------|----------|
|
||||
| focus | The focus of the list to generate. | str | No |
|
||||
| source_data | The data to generate the list from. | str | No |
|
||||
| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| max_retries | Maximum number of retries for generating a valid list. | int | No |
|
||||
| force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
|
||||
| max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
|
||||
@@ -424,7 +424,7 @@ The block sends the input prompt to a chosen LLM, along with any system prompts
|
||||
| prompt | The prompt to send to the language model. | str | Yes |
|
||||
| expected_format | Expected format of the response. If provided, the response will be validated against this format. The keys should be the expected fields in the response, and the values should be the description of the field. | Dict[str, str] | Yes |
|
||||
| list_result | Whether the response should be a list of objects in the expected format. | bool | No |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
|
||||
| sys_prompt | The system prompt to provide additional context to the model. | str | No |
|
||||
| conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |
|
||||
@@ -464,7 +464,7 @@ The block sends the input prompt to a chosen LLM, processes the response, and re
|
||||
| Input | Description | Type | Required |
|
||||
|-------|-------------|------|----------|
|
||||
| prompt | The prompt to send to the language model. You can use any of the {keys} from Prompt Values to fill in the prompt with values from the prompt values dictionary by putting them in curly braces. | str | Yes |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| sys_prompt | The system prompt to provide additional context to the model. | str | No |
|
||||
| retry | Number of times to retry the LLM call if the response does not match the expected format. | int | No |
|
||||
| prompt_values | Values used to fill in the prompt. The values can be used in the prompt by putting them in a double curly braces, e.g. {{variable_name}}. | Dict[str, str] | No |
|
||||
@@ -501,7 +501,7 @@ The block splits the input text into smaller chunks, sends each chunk to an LLM
|
||||
| Input | Description | Type | Required |
|
||||
|-------|-------------|------|----------|
|
||||
| text | The text to summarize. | str | Yes |
|
||||
| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| focus | The topic to focus on in the summary | str | No |
|
||||
| style | The style of the summary to generate. | "concise" \| "detailed" \| "bullet points" \| "numbered list" | No |
|
||||
| max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
|
||||
@@ -763,7 +763,7 @@ Configure agent_mode_max_iterations to control loop behavior: 0 for single decis
|
||||
| Input | Description | Type | Required |
|
||||
|-------|-------------|------|----------|
|
||||
| prompt | The prompt to send to the language model. | str | Yes |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
|
||||
| multiple_tool_calls | Whether to allow multiple tool calls in a single response. | bool | No |
|
||||
| sys_prompt | The system prompt to provide additional context to the model. | str | No |
|
||||
| conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |
|
||||
|
||||