diff --git a/CopilotKit/.changeset/khaki-spoons-relate.md b/CopilotKit/.changeset/khaki-spoons-relate.md new file mode 100644 index 0000000000..f04496b6cc --- /dev/null +++ b/CopilotKit/.changeset/khaki-spoons-relate.md @@ -0,0 +1,7 @@ +--- +"@copilotkit/runtime": patch +--- + +- Added RemoteAgentAdapter and implemented CopilotKit (protocol & events). +- Integrated CrewAI (with a prototype, HITL, event system, and chat/demo tweaks). +- Updated docs and cleaned up code (fixing stdout issues, restricting Python version, and streamlining demos). diff --git a/CopilotKit/.changeset/slow-buckets-own.md b/CopilotKit/.changeset/slow-buckets-own.md new file mode 100644 index 0000000000..3436077f68 --- /dev/null +++ b/CopilotKit/.changeset/slow-buckets-own.md @@ -0,0 +1,5 @@ +--- +"@copilotkit/runtime": minor +--- + +- CrewAI support diff --git a/CopilotKit/.vscode/cspell.json b/CopilotKit/.vscode/cspell.json index 6bf20366ff..da7bd2ecb8 100644 --- a/CopilotKit/.vscode/cspell.json +++ b/CopilotKit/.vscode/cspell.json @@ -17,6 +17,7 @@ "pino", "langsmith", "readables", - "uuidv4" + "uuidv4", + "crewai" ] } diff --git a/CopilotKit/packages/runtime/src/graphql/resolvers/copilot.resolver.ts b/CopilotKit/packages/runtime/src/graphql/resolvers/copilot.resolver.ts index b82dbb32a7..82ab696f69 100644 --- a/CopilotKit/packages/runtime/src/graphql/resolvers/copilot.resolver.ts +++ b/CopilotKit/packages/runtime/src/graphql/resolvers/copilot.resolver.ts @@ -196,6 +196,10 @@ export class CopilotResolver { rejectOutputMessagesPromise = reject; }); + if (copilotCloudPublicApiKey) { + ctx.properties["copilotCloudPublicApiKey"] = copilotCloudPublicApiKey; + } + logger.debug("Processing"); const { eventSource, diff --git a/CopilotKit/packages/runtime/src/lib/runtime/__tests__/remote-action-constructors.test.ts b/CopilotKit/packages/runtime/src/lib/runtime/__tests__/remote-action-constructors.test.ts index 7ae716d345..bfe6c5c53c 100644 --- a/CopilotKit/packages/runtime/src/lib/runtime/__tests__/remote-action-constructors.test.ts +++ b/CopilotKit/packages/runtime/src/lib/runtime/__tests__/remote-action-constructors.test.ts @@ -1,3 +1,4 @@ +import "reflect-metadata"; import { TextEncoder } from "util"; import { RemoteLangGraphEventSource } from "../../../agents/langgraph/event-source"; import telemetry from "../../telemetry-client"; @@ -7,6 +8,7 @@ import { createHeaders, } from "../remote-action-constructors"; import { execute } from "../remote-lg-action"; +import { ReplaySubject } from "rxjs"; // Mock external dependencies jest.mock("../remote-lg-action", () => ({ @@ -49,7 +51,7 @@ beforeEach(() => { describe("remote action constructors", () => { describe("constructLGCRemoteAction", () => { - it("should create an agent with langGraphAgentHandler that processes events", async () => { + it("should create an agent with remoteAgentHandler that processes events", async () => { // Arrange: simulate execute returning a dummy ReadableStream const dummyEncodedEvent = new TextEncoder().encode(JSON.stringify({ event: "test" }) + "\n"); const readerMock = { @@ -72,7 +74,7 @@ describe("remote action constructors", () => { processLangGraphEvents: processLangGraphEventsMock, })); - // Act: build the action and call langGraphAgentHandler + // Act: build the action and call remoteAgentHandler const actions = constructLGCRemoteAction({ endpoint, graphqlContext, @@ -84,7 +86,7 @@ describe("remote action constructors", () => { const action = actions[0]; expect(action.name).toEqual(dummyAgent.name); - const result = await action.langGraphAgentHandler({ + const result = await action.remoteAgentHandler({ name: dummyAgent.name, actionInputsWithoutAgents: [], threadId: "thread1", @@ -160,26 +162,46 @@ describe("remote action constructors", () => { }); it("should create remote agent handler that processes events", async () => { - // Arrange: mock fetch for agent handler to return a dummy stream - const dummyEncodedAgentEvent = new TextEncoder().encode('{"event":"data"}\n'); - const agentReaderMock = { - read: jest - .fn() - .mockResolvedValueOnce({ done: false, value: dummyEncodedAgentEvent }) - .mockResolvedValueOnce({ done: true, value: new Uint8Array() }), + const json = { + agents: [ + { + name: "agent2", + description: "agent desc", + type: "langgraph", // Add type to match RemoteAgentType.LangGraph + }, + ], + actions: [ + { + name: "action1", + description: "action desc", + parameters: { param: "value" }, + }, + ], }; - const dummyStreamResponse = { - getReader: () => agentReaderMock, - }; - global.fetch = jest.fn().mockResolvedValue({ - ok: true, - text: jest.fn().mockResolvedValue("ok"), - body: dummyStreamResponse, - }); - const processLangGraphEventsMock = jest.fn(() => "agent events processed"); + const dummyEncodedAgentEvent = new TextEncoder().encode('{"type":"data","content":"test"}\n'); + + const mockResponse = new Response( + new ReadableStream({ + start(controller) { + controller.enqueue(dummyEncodedAgentEvent); + controller.close(); + }, + }), + { + status: 200, + statusText: "OK", + headers: new Headers({ + "content-type": "application/json", + }), + }, + ); + + global.fetch = jest.fn().mockResolvedValue(mockResponse); + + const processLangGraphEventsMock = jest.fn().mockResolvedValue("agent events processed"); (RemoteLangGraphEventSource as jest.Mock).mockImplementation(() => ({ - eventStream$: { next: jest.fn(), complete: jest.fn(), error: jest.fn() }, + eventStream$: new ReplaySubject(), processLangGraphEvents: processLangGraphEventsMock, })); @@ -192,29 +214,17 @@ describe("remote action constructors", () => { messages: [], agentStates, }); - // The remote agent is the second item in the array - expect(actionsArray).toHaveLength(2); - const remoteAgentHandler = (actionsArray[1] as any).langGraphAgentHandler; + + const remoteAgentHandler = (actionsArray[1] as any).remoteAgentHandler; const result = await remoteAgentHandler({ name: "agent2", actionInputsWithoutAgents: [], threadId: "thread2", nodeName: "node2", - additionalMessages: [], - metaEvents: [], }); + expect(processLangGraphEventsMock).toHaveBeenCalled(); expect(result).toBe("agent events processed"); - - // Check telemetry.capture for agent execution - expect(telemetry.capture).toHaveBeenCalledWith( - "oss.runtime.remote_action_executed", - expect.objectContaining({ - agentExecution: true, - type: "self-hosted", - agentsAmount: 1, - }), - ); }); }); diff --git a/CopilotKit/packages/runtime/src/lib/runtime/copilot-runtime.ts b/CopilotKit/packages/runtime/src/lib/runtime/copilot-runtime.ts index ce6518630f..450be13e17 100644 --- a/CopilotKit/packages/runtime/src/lib/runtime/copilot-runtime.ts +++ b/CopilotKit/packages/runtime/src/lib/runtime/copilot-runtime.ts @@ -39,8 +39,8 @@ import { Message } from "../../graphql/types/converted"; import { ForwardedParametersInput } from "../../graphql/inputs/forwarded-parameters.input"; import { - isLangGraphAgentAction, - LangGraphAgentAction, + isRemoteAgentAction, + RemoteAgentAction, EndpointType, setupRemoteActions, EndpointDefinition, @@ -305,7 +305,7 @@ please use an LLM adapter instead.`, (action) => // TODO-AGENTS: do not exclude ALL server side actions !serverSideActions.find((serverSideAction) => serverSideAction.name == action.name), - // !isLangGraphAgentAction( + // !isRemoteAgentAction( // serverSideActions.find((serverSideAction) => serverSideAction.name == action.name), // ), ), @@ -322,7 +322,6 @@ please use an LLM adapter instead.`, } async discoverAgentsFromEndpoints(graphqlContext: GraphQLContext): Promise { - const headers = createHeaders(null, graphqlContext); const agents = this.remoteEndpointDefinitions.reduce( async (acc: Promise, endpoint) => { const agents = await acc; @@ -355,12 +354,12 @@ please use an LLM adapter instead.`, description: string; }>; } - - const fetchUrl = `${(endpoint as CopilotKitEndpoint).url}/info`; + const cpkEndpoint = endpoint as CopilotKitEndpoint; + const fetchUrl = `${endpoint.url}/info`; try { const response = await fetch(fetchUrl, { method: "POST", - headers, + headers: createHeaders(cpkEndpoint.onBeforeRequest, graphqlContext), body: JSON.stringify({ properties: graphqlContext.properties }), }); if (!response.ok) { @@ -444,11 +443,12 @@ please use an LLM adapter instead.`, agentWithEndpoint.endpoint.type === EndpointType.CopilotKit || !("type" in agentWithEndpoint.endpoint) ) { - const fetchUrl = `${(agentWithEndpoint.endpoint as CopilotKitEndpoint).url}/agents/state`; + const cpkEndpoint = agentWithEndpoint.endpoint as CopilotKitEndpoint; + const fetchUrl = `${cpkEndpoint.url}/agents/state`; try { const response = await fetch(fetchUrl, { method: "POST", - headers, + headers: createHeaders(cpkEndpoint.onBeforeRequest, graphqlContext), body: JSON.stringify({ properties: graphqlContext.properties, threadId, @@ -505,8 +505,8 @@ please use an LLM adapter instead.`, const messages = convertGqlInputToMessages(rawMessages); const currentAgent = serverSideActions.find( - (action) => action.name === agentName && isLangGraphAgentAction(action), - ) as LangGraphAgentAction; + (action) => action.name === agentName && isRemoteAgentAction(action), + ) as RemoteAgentAction; if (!currentAgent) { throw new CopilotKitAgentDiscoveryError({ agentName }); @@ -519,9 +519,9 @@ please use an LLM adapter instead.`, .filter( (action) => // Case 1: Keep all regular (non-agent) actions - !isLangGraphAgentAction(action) || + !isRemoteAgentAction(action) || // Case 2: For agent actions, keep all except self (prevent infinite loops) - (isLangGraphAgentAction(action) && action.name !== agentName) /* prevent self-calls */, + (isRemoteAgentAction(action) && action.name !== agentName) /* prevent self-calls */, ) .map((action) => ({ name: action.name, @@ -542,7 +542,7 @@ please use an LLM adapter instead.`, }); try { const eventSource = new RuntimeEventSource(); - const stream = await currentAgent.langGraphAgentHandler({ + const stream = await currentAgent.remoteAgentHandler({ name: agentName, threadId, nodeName, diff --git a/CopilotKit/packages/runtime/src/lib/runtime/remote-action-constructors.ts b/CopilotKit/packages/runtime/src/lib/runtime/remote-action-constructors.ts index aae7876051..7e34b89bdc 100644 --- a/CopilotKit/packages/runtime/src/lib/runtime/remote-action-constructors.ts +++ b/CopilotKit/packages/runtime/src/lib/runtime/remote-action-constructors.ts @@ -1,7 +1,7 @@ import { createHash } from "node:crypto"; import { CopilotKitEndpoint, - LangGraphAgentHandlerParams, + RemoteAgentHandlerParams, RemoteActionInfoResponse, LangGraphPlatformEndpoint, } from "./remote-actions"; @@ -10,13 +10,18 @@ import { Logger } from "pino"; import { Message } from "../../graphql/types/converted"; import { AgentStateInput } from "../../graphql/inputs/agent-state.input"; import { Observable, ReplaySubject } from "rxjs"; -import { RuntimeEvent } from "../../service-adapters/events"; +import { + RuntimeEvent, + RuntimeEventSource, + RuntimeEventSubject, +} from "../../service-adapters/events"; import telemetry from "../telemetry-client"; import { RemoteLangGraphEventSource } from "../../agents/langgraph/event-source"; import { Action } from "@copilotkit/shared"; import { LangGraphEvent } from "../../agents/langgraph/events"; import { execute } from "./remote-lg-action"; import { CopilotKitError, CopilotKitLowLevelError } from "@copilotkit/shared"; +import { writeJsonLineResponseToEventStream } from "../streaming"; import { CopilotKitApiDiscoveryError, ResolvedCopilotKitError } from "@copilotkit/shared"; import { parseJson, tryMap } from "@copilotkit/shared"; import { ActionInput } from "../../graphql/inputs/action.input"; @@ -39,14 +44,14 @@ export function constructLGCRemoteAction({ description: agent.description, parameters: [], handler: async (_args: any) => {}, - langGraphAgentHandler: async ({ + remoteAgentHandler: async ({ name, actionInputsWithoutAgents, threadId, nodeName, additionalMessages = [], metaEvents, - }: LangGraphAgentHandlerParams): Promise> => { + }: RemoteAgentHandlerParams): Promise> => { logger.debug({ actionName: agent.name }, "Executing LangGraph Platform agent"); telemetry.capture("oss.runtime.remote_action_executed", { @@ -87,7 +92,7 @@ export function constructLGCRemoteAction({ }); const eventSource = new RemoteLangGraphEventSource(); - streamResponse(response, eventSource.eventStream$); + writeJsonLineResponseToEventStream(response, eventSource.eventStream$); return eventSource.processLangGraphEvents(); } catch (error) { logger.error( @@ -102,6 +107,11 @@ export function constructLGCRemoteAction({ return [...agents]; } +export enum RemoteAgentType { + LangGraph = "langgraph", + CrewAI = "crewai", +} + export function constructRemoteActions({ json, url, @@ -183,14 +193,14 @@ export function constructRemoteActions({ parameters: [], handler: async (_args: any) => {}, - langGraphAgentHandler: async ({ + remoteAgentHandler: async ({ name, actionInputsWithoutAgents, threadId, nodeName, additionalMessages = [], metaEvents, - }: LangGraphAgentHandlerParams): Promise> => { + }: RemoteAgentHandlerParams): Promise> => { logger.debug({ actionName: agent.name }, "Executing remote agent"); const headers = createHeaders(onBeforeRequest, graphqlContext); @@ -247,9 +257,17 @@ export function constructRemoteActions({ }); } - const eventSource = new RemoteLangGraphEventSource(); - streamResponse(response.body!, eventSource.eventStream$); - return eventSource.processLangGraphEvents(); + if (agent.type === RemoteAgentType.LangGraph) { + const eventSource = new RemoteLangGraphEventSource(); + writeJsonLineResponseToEventStream(response.body!, eventSource.eventStream$); + return eventSource.processLangGraphEvents(); + } else if (agent.type === RemoteAgentType.CrewAI) { + const eventStream$ = new RuntimeEventSubject(); + writeJsonLineResponseToEventStream(response.body!, eventStream$); + return eventStream$; + } else { + throw new Error("Unsupported agent type"); + } } catch (error) { if (error instanceof CopilotKitError) { throw error; @@ -263,64 +281,6 @@ export function constructRemoteActions({ return [...actions, ...agents]; } -async function streamResponse( - response: ReadableStream, - eventStream$: ReplaySubject, -) { - const reader = response.getReader(); - const decoder = new TextDecoder(); - let buffer = []; - - function flushBuffer() { - const currentBuffer = buffer.join(""); - if (currentBuffer.trim().length === 0) { - return; - } - const parts = currentBuffer.split("\n"); - if (parts.length === 0) { - return; - } - - const lastPartIsComplete = currentBuffer.endsWith("\n"); - - // truncate buffer - buffer = []; - - if (!lastPartIsComplete) { - // put back the last part - buffer.push(parts.pop()); - } - - parts - .map((part) => part.trim()) - .filter((part) => part != "") - .forEach((part) => { - eventStream$.next(JSON.parse(part)); - }); - } - - try { - while (true) { - const { done, value } = await reader.read(); - - if (!done) { - buffer.push(decoder.decode(value, { stream: true })); - } - - flushBuffer(); - - if (done) { - break; - } - } - } catch (error) { - console.error("Error in stream", error); - eventStream$.error(error); - return; - } - eventStream$.complete(); -} - export function createHeaders( onBeforeRequest: CopilotKitEndpoint["onBeforeRequest"], graphqlContext: GraphQLContext, diff --git a/CopilotKit/packages/runtime/src/lib/runtime/remote-actions.ts b/CopilotKit/packages/runtime/src/lib/runtime/remote-actions.ts index 24a5b538d6..3973cb0f73 100644 --- a/CopilotKit/packages/runtime/src/lib/runtime/remote-actions.ts +++ b/CopilotKit/packages/runtime/src/lib/runtime/remote-actions.ts @@ -54,7 +54,7 @@ export type RemoteActionInfoResponse = { agents: any[]; }; -export type LangGraphAgentHandlerParams = { +export type RemoteAgentHandlerParams = { name: string; actionInputsWithoutAgents: ActionInput[]; threadId?: string; @@ -63,15 +63,15 @@ export type LangGraphAgentHandlerParams = { metaEvents?: MetaEventInput[]; }; -export type LangGraphAgentAction = Action & { - langGraphAgentHandler: (params: LangGraphAgentHandlerParams) => Promise>; +export type RemoteAgentAction = Action & { + remoteAgentHandler: (params: RemoteAgentHandlerParams) => Promise>; }; -export function isLangGraphAgentAction(action: Action): action is LangGraphAgentAction { +export function isRemoteAgentAction(action: Action): action is RemoteAgentAction { if (!action) { return false; } - return typeof (action as LangGraphAgentAction).langGraphAgentHandler === "function"; + return typeof (action as RemoteAgentAction).remoteAgentHandler === "function"; } async function fetchRemoteInfo({ diff --git a/CopilotKit/packages/runtime/src/lib/streaming.ts b/CopilotKit/packages/runtime/src/lib/streaming.ts new file mode 100644 index 0000000000..15d576ef3d --- /dev/null +++ b/CopilotKit/packages/runtime/src/lib/streaming.ts @@ -0,0 +1,59 @@ +import { ReplaySubject } from "rxjs"; + +export async function writeJsonLineResponseToEventStream( + response: ReadableStream, + eventStream$: ReplaySubject, +) { + const reader = response.getReader(); + const decoder = new TextDecoder(); + let buffer = []; + + function flushBuffer() { + const currentBuffer = buffer.join(""); + if (currentBuffer.trim().length === 0) { + return; + } + const parts = currentBuffer.split("\n"); + if (parts.length === 0) { + return; + } + + const lastPartIsComplete = currentBuffer.endsWith("\n"); + + // truncate buffer + buffer = []; + + if (!lastPartIsComplete) { + // put back the last part + buffer.push(parts.pop()); + } + + parts + .map((part) => part.trim()) + .filter((part) => part != "") + .forEach((part) => { + eventStream$.next(JSON.parse(part)); + }); + } + + try { + while (true) { + const { done, value } = await reader.read(); + + if (!done) { + buffer.push(decoder.decode(value, { stream: true })); + } + + flushBuffer(); + + if (done) { + break; + } + } + } catch (error) { + console.error("Error in stream", error); + eventStream$.error(error); + return; + } + eventStream$.complete(); +} diff --git a/CopilotKit/packages/runtime/src/service-adapters/events.ts b/CopilotKit/packages/runtime/src/service-adapters/events.ts index b12c3f91de..d9864082ba 100644 --- a/CopilotKit/packages/runtime/src/service-adapters/events.ts +++ b/CopilotKit/packages/runtime/src/service-adapters/events.ts @@ -14,7 +14,7 @@ import { import { streamLangChainResponse } from "./langchain/utils"; import { GuardrailsResult } from "../graphql/types/guardrails-result.type"; import telemetry from "../lib/telemetry-client"; -import { isLangGraphAgentAction } from "../lib/runtime/remote-actions"; +import { isRemoteAgentAction } from "../lib/runtime/remote-actions"; import { ActionInput } from "../graphql/inputs/action.input"; import { ActionExecutionMessage, ResultMessage, TextMessage } from "../graphql/types/converted"; import { plainToInstance } from "class-transformer"; @@ -372,7 +372,7 @@ async function executeAction( } // handle LangGraph agents - if (isLangGraphAgentAction(action)) { + if (isRemoteAgentAction(action)) { const result = `${action.name} agent started`; const agentExecution = plainToInstance(ActionExecutionMessage, { @@ -397,7 +397,7 @@ async function executeAction( result, }); - const stream = await action.langGraphAgentHandler({ + const stream = await action.remoteAgentHandler({ name: action.name, threadId, actionInputsWithoutAgents, diff --git a/CopilotKit/scripts/develop/example.sh b/CopilotKit/scripts/develop/example.sh index d235dfd4c8..737dd16238 100755 --- a/CopilotKit/scripts/develop/example.sh +++ b/CopilotKit/scripts/develop/example.sh @@ -37,7 +37,9 @@ example_dir="${1:-coagents-research-canvas}" if [[ "$example_dir" == "coagents-starter" || \ "$example_dir" == "langgraph-tutorial-customer-support" || \ - "$example_dir" == "langgraph-tutorial-quickstart" ]]; then + "$example_dir" == "langgraph-tutorial-quickstart" || \ + "$example_dir" == "coagents-starter-crewai-flows" || \ + "$example_dir" == "coagents-starter-crewai-crews" ]]; then agent_dir="agent-py" else agent_dir="agent" @@ -137,3 +139,4 @@ parallel --ungroup ::: \ "cd $root_dir && exec > >(sed 's/^/$copilotkit_prompt /') 2>&1 && turbo run dev" \ "cd $root_dir/../examples/$example_dir/$agent_dir && exec > >(sed 's/^/$agent_prompt /') 2>&1 && $agent_command" \ "cd $root_dir/../examples/$example_dir/ui && exec > >(sed 's/^/$frontend_prompt /') 2>&1 && pnpm dev" + diff --git a/CopilotKit/scripts/docs/lib/files.ts b/CopilotKit/scripts/docs/lib/files.ts index 4ecd8ef8bf..36054f7ab6 100644 --- a/CopilotKit/scripts/docs/lib/files.ts +++ b/CopilotKit/scripts/docs/lib/files.ts @@ -129,6 +129,7 @@ export const REFERENCE_DOCS: ReferenceDocConfiguration[] = [ "The useCopilotAdditionalInstructions hook allows you to provide additional instructions to the agent.", }, /* SDKs */ + { sourcePath: "../sdk-python/copilotkit/langgraph.py", destinationPath: "docs/content/docs/reference/sdk/python/LangGraph.mdx", @@ -143,6 +144,22 @@ export const REFERENCE_DOCS: ReferenceDocConfiguration[] = [ "copilotkit_emit_tool_call", ], }, + { + sourcePath: "../sdk-python/copilotkit/crewai.py", + destinationPath: "docs/content/docs/reference/sdk/python/CrewAI.mdx", + title: "CrewAI SDK", + description: + "The CopilotKit CrewAI SDK for Python allows you to build and run CrewAI agents with CopilotKit.", + pythonSymbols: [ + "copilotkit_emit_state", + "copilotkit_predict_state", + "copilotkit_exit", + "copilotkit_emit_message", + "copilotkit_emit_tool_call", + ], + }, + + /* Agents */ { sourcePath: "../sdk-python/copilotkit/langgraph_agent.py", destinationPath: "docs/content/docs/reference/sdk/python/LangGraphAgent.mdx", @@ -150,6 +167,13 @@ export const REFERENCE_DOCS: ReferenceDocConfiguration[] = [ description: "LangGraphAgent lets you define your agent for use with CopilotKit.", pythonSymbols: ["LangGraphAgent", "CopilotKitConfig"], }, + { + sourcePath: "../sdk-python/copilotkit/crewai_agent.py", + destinationPath: "docs/content/docs/reference/sdk/python/CrewAIAgent.mdx", + title: "CrewAIAgent", + description: "CrewAIAgent lets you define your agent for use with CopilotKit.", + pythonSymbols: ["CrewAIAgent", "CopilotKitConfig"], + }, { sourcePath: "../sdk-python/copilotkit/sdk.py", destinationPath: "docs/content/docs/reference/sdk/python/RemoteEndpoints.mdx", diff --git a/docs/app/(home)/layout.tsx b/docs/app/(home)/layout.tsx index 559ebaa3ad..26e92c6b71 100644 --- a/docs/app/(home)/layout.tsx +++ b/docs/app/(home)/layout.tsx @@ -4,8 +4,10 @@ import { baseOptions } from "../layout.config"; import { source } from "@/app/source"; import { SubdocsMenu } from "@/components/react/subdocs-menu"; import { TerminalIcon, RocketIcon } from "lucide-react"; -import { PiGraph, PiGraduationCap} from "react-icons/pi"; +import { PiGraph, PiGraduationCap } from "react-icons/pi"; +import { SiCrewai } from "@icons-pack/react-simple-icons"; import { TopBar } from "@/components/layout/top-bar"; +import { SiLangchain } from "react-icons/si"; export default function Layout({ children }: { children: ReactNode }) { return ( @@ -28,14 +30,40 @@ export default function Layout({ children }: { children: ReactNode }) { "bg-gradient-to-b from-indigo-700 to-indigo-400 text-indigo-100", selectedStyle: "ring-indigo-500/70 ring-2 rounded-sm", }, + { - title: "CoAgents (LangGraph)", - description: "Documentation for CoAgents with LangGraph", - url: "/coagents", - icon: , - bgGradient: - "bg-gradient-to-b from-purple-700 to-purple-400 text-purple-100", - selectedStyle: "ring-purple-500/70 ring-2 rounded-sm", + title: "CoAgents", + options: [ + { + title: "CoAgents (LangGraph)", + description: "Documentation for CoAgents with LangGraph", + url: "/coagents", + icon: , + bgGradient: + "bg-gradient-to-b from-purple-700 to-purple-400 text-purple-100", + selectedStyle: "ring-purple-500/70 ring-2 rounded-sm", + }, + { + title: "CoAgents (CrewAI Flows)", + description: + "Documentation for CoAgents with CrewAI Flows", + url: "/crewai-flows", + icon: , + bgGradient: + "bg-gradient-to-b from-[#FA694C] to-[#FE8A71] text-white", + selectedStyle: "ring-[#FA694C]/70 ring-2 rounded-sm", + }, + { + title: "CoAgents (CrewAI Crews)", + description: + "Documentation for CoAgents with CrewAI Crews", + url: "/crewai-crews", + icon: , + bgGradient: + "bg-gradient-to-b from-[#FA694C] to-[#FE8A71] text-white", + selectedStyle: "ring-[#FA694C]/70 ring-2 rounded-sm", + }, + ], }, { title: "API Reference", @@ -46,6 +74,7 @@ export default function Layout({ children }: { children: ReactNode }) { "bg-gradient-to-b from-teal-700 to-teal-400 text-teal-100", selectedStyle: "ring-teal-500/70 ring-2 rounded-sm", }, + // { // title: "Chat with our docs", // description: "Chat with our docs", diff --git a/docs/components/react/subdocs-menu.tsx b/docs/components/react/subdocs-menu.tsx index ab1d05c392..e19ac9f55b 100644 --- a/docs/components/react/subdocs-menu.tsx +++ b/docs/components/react/subdocs-menu.tsx @@ -5,13 +5,22 @@ import { type ReactNode, useCallback, useMemo, + useRef, useState, } from "react"; import Link from "next/link"; -import { usePathname } from "next/navigation"; +import { usePathname, useRouter } from "next/navigation"; import { cn } from "@/lib/utils"; import { useSidebar } from "fumadocs-ui/provider"; import { SearchToggle } from "../layout/top-bar"; +import { + Select, + SelectContent, + SelectItem, + SelectTrigger, + SelectValue, +} from "@/components/ui/select"; +import { PiGraph } from "react-icons/pi"; export function isActive( url: string, @@ -38,27 +47,54 @@ export interface Option { props?: HTMLAttributes; } +export interface OptionDropdown { + title: ReactNode; + options: Option[]; +} + +function isOptionDropdown( + item: Option | OptionDropdown +): item is OptionDropdown { + return "options" in item; +} + +function isOption(item: Option | OptionDropdown): item is Option { + return !isOptionDropdown(item); +} + export function SubdocsMenu({ options, ...props }: { - options: Option[]; + options: (Option | OptionDropdown)[]; } & HTMLAttributes): React.ReactElement { const { closeOnRedirect } = useSidebar(); const pathname = usePathname(); - const selected = useMemo(() => { + const selected: Option | undefined = useMemo(() => { // First, try all non-root options - const nonRootOptions = options.filter((item) => item.url !== "/"); - const activeNonRootOption = nonRootOptions.find((item) => - isActive(item.url, pathname, true) + let nonRootOptions = options.filter( + (item) => isOption(item) && item.url !== "/" + ); + + const dropDowns = options.filter((item) => isOptionDropdown(item)); + + if (dropDowns.length > 0) { + const dropDown = dropDowns[0]; + nonRootOptions = nonRootOptions.concat(dropDown.options); + } + + const activeNonRootOption = nonRootOptions.find( + (item) => isOption(item) && isActive(item.url, pathname, true) ); if (activeNonRootOption) { - return activeNonRootOption; + return activeNonRootOption as Option; } // If no non-root options are active, try the root options ("/*") - return options.find((item) => isActive(item.url, pathname, true, true)); + return options.find( + (item) => isOption(item) && isActive(item.url, pathname, true, true) + ) as Option | undefined; }, [options, pathname]); const onClick = useCallback(() => { @@ -68,29 +104,182 @@ export function SubdocsMenu({ return (
{options.map((item) => ( - -
- {item.icon} -
-
{item.title}
- + /> ))}
); } + +function SubdocsMenuItem({ + item, + selected, + onClick, +}: { + item: Option | OptionDropdown; + selected?: Option; + onClick?: () => void; +}) { + if (isOption(item)) { + return ( + +
+ {item.icon} +
+
{item.title}
+ + ); + } else if (isOptionDropdown(item)) { + return ( + + ); + } +} + +function SubdocsMenuItemAgentFramework({ + item, + selected, + onClick, +}: { + item: OptionDropdown; + selected?: Option; + onClick?: () => void; +}) { + const defaultOption = item.options.find( + (option) => option.url === "/coagents" + )!; + + const isSelected = item.options.find( + (option) => option.url === selected?.url + ); + + const showOption = + item.options.find((option) => option.url === selected?.url) || + defaultOption; + + return ( + +
+ {showOption.icon} +
+
{showOption.title}
+ + ); +} + +function SubdocsMenuItemDropdown({ + item, + selected, + onClick, +}: { + item: OptionDropdown; + selected?: Option; + onClick?: () => void; +}) { + const router = useRouter(); + const selectRef = useRef(null); + + const selectedOption = item.options.find( + (option) => option.url === selected?.url + ); + + const isSelected = selectedOption !== undefined; + + return ( + + ); +} diff --git a/docs/components/ui/select.tsx b/docs/components/ui/select.tsx index ed621d2611..0072139c7f 100644 --- a/docs/components/ui/select.tsx +++ b/docs/components/ui/select.tsx @@ -1,15 +1,19 @@ -"use client" +"use client"; -import * as React from "react" -import * as SelectPrimitive from "@radix-ui/react-select" -import { cn } from "@/lib/utils" -import { CheckIcon, ChevronDownIcon, ChevronUpIcon } from "@radix-ui/react-icons" +import * as React from "react"; +import * as SelectPrimitive from "@radix-ui/react-select"; +import { cn } from "@/lib/utils"; +import { + CheckIcon, + ChevronDownIcon, + ChevronUpIcon, +} from "@radix-ui/react-icons"; -const Select = SelectPrimitive.Root +const Select = SelectPrimitive.Root; -const SelectGroup = SelectPrimitive.Group +const SelectGroup = SelectPrimitive.Group; -const SelectValue = SelectPrimitive.Value +const SelectValue = SelectPrimitive.Value; const SelectTrigger = React.forwardRef< React.ElementRef, @@ -28,8 +32,8 @@ const SelectTrigger = React.forwardRef< -)) -SelectTrigger.displayName = SelectPrimitive.Trigger.displayName +)); +SelectTrigger.displayName = SelectPrimitive.Trigger.displayName; const SelectScrollUpButton = React.forwardRef< React.ElementRef, @@ -45,8 +49,8 @@ const SelectScrollUpButton = React.forwardRef< > -)) -SelectScrollUpButton.displayName = SelectPrimitive.ScrollUpButton.displayName +)); +SelectScrollUpButton.displayName = SelectPrimitive.ScrollUpButton.displayName; const SelectScrollDownButton = React.forwardRef< React.ElementRef, @@ -62,9 +66,9 @@ const SelectScrollDownButton = React.forwardRef< > -)) +)); SelectScrollDownButton.displayName = - SelectPrimitive.ScrollDownButton.displayName + SelectPrimitive.ScrollDownButton.displayName; const SelectContent = React.forwardRef< React.ElementRef, @@ -95,8 +99,8 @@ const SelectContent = React.forwardRef< -)) -SelectContent.displayName = SelectPrimitive.Content.displayName +)); +SelectContent.displayName = SelectPrimitive.Content.displayName; const SelectLabel = React.forwardRef< React.ElementRef, @@ -107,8 +111,8 @@ const SelectLabel = React.forwardRef< className={cn("px-2 py-1.5 text-sm font-semibold", className)} {...props} /> -)) -SelectLabel.displayName = SelectPrimitive.Label.displayName +)); +SelectLabel.displayName = SelectPrimitive.Label.displayName; const SelectItem = React.forwardRef< React.ElementRef, @@ -129,8 +133,8 @@ const SelectItem = React.forwardRef< {children} -)) -SelectItem.displayName = SelectPrimitive.Item.displayName +)); +SelectItem.displayName = SelectPrimitive.Item.displayName; const SelectSeparator = React.forwardRef< React.ElementRef, @@ -141,8 +145,8 @@ const SelectSeparator = React.forwardRef< className={cn("-mx-1 my-1 h-px bg-muted", className)} {...props} /> -)) -SelectSeparator.displayName = SelectPrimitive.Separator.displayName +)); +SelectSeparator.displayName = SelectPrimitive.Separator.displayName; export { Select, @@ -155,4 +159,4 @@ export { SelectSeparator, SelectScrollUpButton, SelectScrollDownButton, -} +}; diff --git a/docs/content/docs/coagents/index.mdx b/docs/content/docs/coagents/index.mdx index 994335800f..787e1921f7 100644 --- a/docs/content/docs/coagents/index.mdx +++ b/docs/content/docs/coagents/index.mdx @@ -55,22 +55,19 @@ Everything you need to build Agent-Native Applications (ANAs), right out of the { icon: LuMessageSquare, title: "Agentic Chat UI", - description: - "In-app chat powered by your agent.", + description: "In-app chat powered by your agent.", href: "/coagents/agentic-chat-ui", }, { icon: FaSync, title: "Shared State", - description: - "Your agent can see everything in your app, and vice versa.", + description: "Your agent can see everything in your app, and vice versa.", href: "/coagents/shared-state", }, { icon: LuLayoutTemplate, title: "Generative UI", - description: - "UI that updates in real-time based on your agent's state.", + description: "UI that updates in real-time based on your agent's state.", href: "/coagents/generative-ui", }, { @@ -90,8 +87,7 @@ Everything you need to build Agent-Native Applications (ANAs), right out of the { icon: LuUserCog, title: "Human-in-the-Loop", - description: - "Set smart checkpoints where humans can guide your agents.", + description: "Set smart checkpoints where humans can guide your agents.", href: "/coagents/human-in-the-loop", }, ]} @@ -155,10 +151,9 @@ Yes, check out our [Guide on Threads](/coagents/persistence/loading-message-hist -Currently we only support LangGraph for CoAgents. We will be adding support for more agent frameworks very soon. +CopilotKit is a complete framework for building AI-powered applications and can be used standalone. -However, if you are not looking to work with agents, CopilotKit is a complete framework for building AI-powered applications. LangGraph is just one tool of many that we integrate with to provide -rich AI experiences. +If you want to integrate with an agent framework, we currently support [LangGraph](/coagents/quickstart/langgraph) and [CrewAI](/crewai-flows/quickstart/crewai). Checkout our [CopilotKit Overview](/) for more information! diff --git a/docs/content/docs/crewai-crews/advanced/exit-agent.mdx b/docs/content/docs/crewai-crews/advanced/exit-agent.mdx new file mode 100644 index 0000000000..1fbe6614bd --- /dev/null +++ b/docs/content/docs/crewai-crews/advanced/exit-agent.mdx @@ -0,0 +1,17 @@ +--- +title: "Exiting the agent loop" +icon: "lucide/DoorOpen" +--- +import InstallSDKSnippet from "@/snippets/install-sdk.mdx" + + + +After your agent has finished running a crew, it will automatically exit the agent loop + +Exiting the agent has different effects depending on mode: + +- **Router Mode**: Exiting the agent hands responsibility for handling input back to the router, which can initiate chat, call actions, other agents, etc. The router can return to this agent later (starting a new loop) to satisfy a user request. + +- **Agent Lock Mode**: Exiting the agent restarts the workflow loop for the current agent. + + diff --git a/docs/content/docs/crewai-crews/advanced/meta.json b/docs/content/docs/crewai-crews/advanced/meta.json new file mode 100644 index 0000000000..b541e1e459 --- /dev/null +++ b/docs/content/docs/crewai-crews/advanced/meta.json @@ -0,0 +1,4 @@ +{ + "title": "Advanced", + "icon": "lucide/Cog" +} \ No newline at end of file diff --git a/docs/content/docs/crewai-crews/agentic-chat-ui.mdx b/docs/content/docs/crewai-crews/agentic-chat-ui.mdx new file mode 100644 index 0000000000..a0507d95b2 --- /dev/null +++ b/docs/content/docs/crewai-crews/agentic-chat-ui.mdx @@ -0,0 +1,46 @@ +--- +title: Chat with an Agent +icon: "lucide/SendHorizontal" +description: Chat with an agent using CopilotKit's UI components. +--- + +import ConnectCopilotUI from "@/snippets/copilot-ui.mdx"; +import SelfHostingCopilotRuntimeCreateEndpoint from "@/snippets/self-hosting-copilot-runtime-create-endpoint.mdx"; +import SelfHostingCopilotRuntimeConfigureCopilotKitProvider from "@/snippets/self-hosting-copilot-runtime-configure-copilotkit-provider.mdx"; +import CopilotCloudConfigureCopilotKitProvider from "@/snippets/cloud/cloud-copilotkit-provider.mdx"; +import ComponentExamples from "@/snippets/component-examples.mdx"; +import { UserIcon, PaintbrushIcon, WrenchIcon, RepeatIcon } from "lucide-react"; + + + + diff --git a/docs/content/docs/crewai-crews/concepts/agentic-copilots.mdx b/docs/content/docs/crewai-crews/concepts/agentic-copilots.mdx new file mode 100644 index 0000000000..d7719ee71f --- /dev/null +++ b/docs/content/docs/crewai-crews/concepts/agentic-copilots.mdx @@ -0,0 +1,163 @@ +--- +title: Agentic Copilots +description: Agentic copilots provide you with advanced control and orchestration over your agents. +icon: lucide/Bot +--- + +import { TailoredContent, TailoredContentOption } from "@/components/react/tailored-content"; +import { BsFillCloudHaze2Fill as CloudIcon } from "react-icons/bs"; +import { FaServer as SelfHostIcon } from "react-icons/fa6"; +import { SiLangchain } from "react-icons/si"; +import { LinkIcon } from "lucide-react"; +import { RocketIcon, GraduationCapIcon, CodeIcon, VideoIcon } from "lucide-react"; + + + +Before we dive into what agentic copilots are, help us help you by telling us your level of experience with CrewAI. We'll explain things in a way that best suits your experience level. + + + } + > + + CoAgents Shared State + + + ### What are Agents? + AI agents are intelligent systems that interact with their environment to achieve specific goals. Think of them as 'virtual colleagues' that can handle tasks ranging from + simple queries like "find the cheapest flight to Paris" to complex challenges like "design a new product layout." + + As these AI-driven experiences (or 'Agentic Experiences') become more sophisticated, developers need finer control over how agents make decisions. This is where specialized + frameworks like CrewAI become essential. + + ### What is CrewAI? + CrewAI is a framework that gives you precise control over AI agents. CrewAI flows allow developers to combine and coordinate coding tasks and Crews efficiently, + providing a robust framework for building sophisticated AI automations. + + ### What are Agentic Copilots? + Agentic copilots are how CopilotKit brings CrewAI agents into your application. If you're familiar with CopilotKit, you know that copilots are AI assistants that + understand your app's context and can take actions within it. While CopilotKit's standard copilots use a simplified [ReAct pattern](https://www.perplexity.ai/search/what-s-a-react-agent-5hu7ZOaKSAuY7YdFjQLCNQ) + for quick implementation, Agentic copilots give you CrewAI's full orchestration capabilities when you need more control over your agent's behavior. + + ### What are CoAgents? + CoAgents are what we call CopilotKit's approach to building agentic experiences! They're interchangeable with agentic copilots being a more descriptive term for the overall concept. + + ### When should I use CopilotKit's CoAgents? + You should use CoAgents when you require tight control over the Agentic runloop, as facilitated by an Agentic Orchestration framework like [CrewAI](https://crewai.com/). + With CoAgents, you can carry all of your existing CopilotKit-enabled Copilot capabilities into a customized agentic runloop. + + We suggest beginning with a basic Copilot and gradually transitioning specific components to CoAgents. + + The need for CoAgents spans a broad spectrum across different applications. At one end, their advanced capabilities might not be required at all, or only for a minimal 10% of the application's + functionality. Progressing further, there are scenarios where they become increasingly vital, managing 60-70% of operations. Ultimately, in some cases, CoAgents are indispensable, orchestrating + up to 100% of the Copilot's tasks (see [agent-lock mode](/crewai-crews/multi-agent-flows) for the 100% case). + + ### Examples + An excellent example of the type of experiences you can accomplish with CoAgents applications can be found in our [Research Canvas](https://github.com/CopilotKit/CopilotKit/tree/main/examples/coagents-research-canvas). + + More specifically, it demonstrates how CoAgents allow for AI driven experiences with: + - Precise state management across agent interactions + - Sophisticated multi-step reasoning capabilities + - Seamless orchestration of multiple AI tools + - Interactive human-AI collaboration features + - Real-time state updates and progress streaming + + ## Next Steps + + Want to get started? You have some options! + + + } + /> + } + /> + } + /> + } + /> + + + } + > + + + CoAgents demonstration + + + CrewAI is a framework for building deeply customizable AI agents. + + CopilotKit's Agentic Copilots is infrastructure for in-app agent-user interaction, i.e. for transforming agents from autonomous processes to user-interactive 'virtual colleagues' that live inside applications. + + Any CrewAI-based agent can be transformed into an Agentic Copilot with a minimal amount + of effort to get industry leading agentic UX such as: + - Shared state between the agent and the application. + - Intermediate result and state progress streaming + - Human-in-the-loop collaboration + - Agentic generative UI + - And more! + + All of these features are essential to delight instead of frustrate your users with AI features. + + ### What are CoAgents? + CoAgents are what we call CopilotKit's approach to building agentic experiences! They're interchangeable with agentic copilots being a more descriptive term for the overall concept. + + ## Next Steps + Want to get started? You have some options! + + + } + /> + } + /> + } + /> + } + /> + + + + + diff --git a/docs/content/docs/crewai-crews/concepts/copilotkit-stream.mdx b/docs/content/docs/crewai-crews/concepts/copilotkit-stream.mdx new file mode 100644 index 0000000000..a0661739e4 --- /dev/null +++ b/docs/content/docs/crewai-crews/concepts/copilotkit-stream.mdx @@ -0,0 +1,33 @@ +--- +title: Streaming and Tool Calls +description: CoAgents support streaming your messages and tool calls to the frontend. +--- + + + +If you'd like to stream messages from your CrewAI agents you can utilize our Copilotkit SDK which provides a collection +of functions and utilities for interacting with the agent's state or behavior. This allows you to choose how messages and +tool calls are emitted and streamed to the frontend. + +## Message Streaming +If you just call the LiteLLM `completion` function from your CrewAI agent, messages will not be streamed by default. +To stream messages, wrap the `completion` function with the `copilotkit_stream` function. This will enable streaming +of both the messages and tool calls to the frontend. + +```python +response = copilotkit_stream( + completion( + model="openai/gpt-4o", + messages=[ + {"role": "system", "content": my_prompt}, + *self.state["messages"] + ], + stream=True + ) +) +``` + +For more information on how tool calls are utilized check out our [frontend actions](/crewai-crews/frontend-actions) +documentation. + + diff --git a/docs/content/docs/crewai-crews/concepts/crewai.mdx b/docs/content/docs/crewai-crews/concepts/crewai.mdx new file mode 100644 index 0000000000..71bdc5b3bf --- /dev/null +++ b/docs/content/docs/crewai-crews/concepts/crewai.mdx @@ -0,0 +1,56 @@ +--- +title: CrewAI +description: An agentic framework for building LLM applications that can be used with Copilotkit. +icon: custom/langchain +--- + + + + + CoAgents High Level Overview + + +CrewAI is an agentic framework for building LLM applications that can be used with Copilotkit. CrewAi Flows allow developers +to combine and coordinate coding tasks and Crews efficiently, providing a robust framework for building sophisticated AI automations. + +## CoAgents and CrewAI + +How do CoAgents extend CrewAI? Let's read the first sentence of their [page on Flows](https://docs.crewai.com/concepts/flows) to understand. + +> Flows allow you to create structured, event-driven workflows. They provide a seamless way to connect multiple tasks, manage state, and control the flow of execution in your AI applications. + +Let's break down some key terms and understand how they relate to and are implemented by CoAgents. + +- ** manage state**: CoAgents have bi-directional state sharing with the agent and UI. This allows for the agent to remember + information from previous messages and the UI to update the agent with new information. Read more about how state sharing works + [here](/crewai-crews/shared-state). +- **Multi-actor**: CoAgents allow for multiple agents to interact with each other. Copilotkit acts as the "ground-truth" + when transitioning between agents. Read more about how multi-actor workflows work [here](/crewai-crews/multi-agent-flows) + and how messages are managed [here](/crewai-crews/concepts/message-management). +- **LLMs**: CoAgents use large language models to generate responses. This is useful for building applications that need to + generate natural language responses. + +Some additional functionality not mentioned here is: +- **Human in the loop**: CoAgents enabled human review and approval of generated responses. Read more about how this works + [here](/crewai-crews/human-in-the-loop). +- **Tool calling**: Tool calling is a fundamental building block for agentic workflows. They allow for greater control over what + the agent can do and can be used to interact with external systems. CoAgents allow you to easily render in-progress + tool calls in the UI so your users know what's happening. Read more about streaming tool calls [here](/crewai-crews/shared-state/predictive-state-updates). + +## Building with Python + +You can build CrewAI applications using Python. Check out the [CrewAI docs](https://docs.crewai.com/introduction) for more information. + +## CrewAI Enterprise + +Turn any crew into an API within seconds +Connect to your apps using hooks, REST, gRPC and more +Get access to templates, custom tools and early UI +Get business support, SLA, private VPC + +CrewAI enterprise is a platform for deploying and monitoring CrewAI applications. Read more about it on the +[CrewAI website](https://www.crewai.com/enterprise). + +If you want to take the next step to deploy your CrewAI application as an CoAgent, check out our [quickstart guide](/crewai-crews/quickstart/crewai). + + diff --git a/docs/content/docs/crewai-crews/concepts/message-management.mdx b/docs/content/docs/crewai-crews/concepts/message-management.mdx new file mode 100644 index 0000000000..6bd40aacd4 --- /dev/null +++ b/docs/content/docs/crewai-crews/concepts/message-management.mdx @@ -0,0 +1,80 @@ +--- +title: Message flow +icon: lucide/MessageCircle +--- + + + +Message management in CoAgents operates with CopilotKit as the "ground truth" for the full chat session. +When an CoAgent session begins, it receives the existing CopilotKit chat history to maintain conversational +continuity across different agents. + + +While all of this information is great to know, in most cases you won't need to worry about these details to +build rich agentic applications. Use the information here as a reference when getting really deep into +the CoAgent internals. + + +### Can I modify the message history? + +You can modify the message history from CrewAI Flows by using the `"messages"` key in the state. For example to remove all messages from the chat history: + +```python + +def a_flow_function(): + # ... + self.state["messages"] = [] +``` + +### Can I persist chat history? + +Yes! There are a few ways to persist various portions of a chat's history: +- [Threads](/crewai-crews/persistence/threads) +- [Message Persistence](/crewai-crews/persistence/message-persistence) +- [Agent State](/crewai-crews/persistence/loading-agent-state) + +## Types of LLM Messages + +Modern LLM interactions produce two distinct types of messages: + +1. **Communication Messages**: Direct responses and interactions with users +2. **Internal Messages**: Agent "thoughts" and reasoning processes + +A well known example of this pattern is OpenAI's o1 model, which has sophisticated reasoning capabilities and thoughts. Its internal +thought processes are presented distinctly from 'communication messages' which are clearly visible to the end-user. + +CrewAI agents can operate similarly. An LLM call's output can be considered either a communication message, or an internal message. + +### Emitting Messages for long running tasks + +Sometimes you'll have a task that is running for a long time, and you want the user to be aware of what's happening. +CopilotKit allows you to accomplish this by using the `copilotkit_emit_message` function. + +```python +@listen("route_to_ask_name") +async def ask_name(): + """ + Ask the user for their name. + """ + + content = "Hey, what is your name? 🙂" + + await copilotkit_emit_message(content) + + # something long running here... + + self.state["messages"].append({"role": "assistant", "content": content, "id": str(uuid.uuid4())}) + +``` + +Want some more help managing messages in your CoAgent application? Check out our guide on [emitting messages](/crewai-crews/advanced/emit-messages). + +## Message Flow +Messages flow between CopilotKit and CrewAI in a specific way: + +- All messages from CrewAI are forwarded to CopilotKit +- On a fresh agent invocation, the full CopilotKit chat history is provided to the CrewAI agent as its pre-existing chat history. + +When a CoAgent completes its execution, its relevant messages become part of CopilotKit's persistent chat history. This allows for all future agent invocations to get context from the full chat history. + + \ No newline at end of file diff --git a/docs/content/docs/crewai-crews/concepts/meta.json b/docs/content/docs/crewai-crews/concepts/meta.json new file mode 100644 index 0000000000..548d0b3d37 --- /dev/null +++ b/docs/content/docs/crewai-crews/concepts/meta.json @@ -0,0 +1,5 @@ +{ + "title": "Concepts", + "root": true, + "pages": ["terminology", "agentic-copilots", "crewai", "message-management"] +} diff --git a/docs/content/docs/crewai-crews/concepts/state.mdx b/docs/content/docs/crewai-crews/concepts/state.mdx new file mode 100644 index 0000000000..dd59eb23fe --- /dev/null +++ b/docs/content/docs/crewai-crews/concepts/state.mdx @@ -0,0 +1,38 @@ +--- +title: Shared State +description: CoAgents maintain a shared state across your UI and agent execution. +--- + + + + + Agentic Copilot State Diagram + + +CoAgents maintain a shared state that seamlessly connects your UI with the agent's execution. This shared state system allows you to: +- Display the agent's current progress and intermediate results +- Update the agent's state through UI interactions +- React to state changes in real-time across your application + +The foundation of this system is built on CrewAI's stateful architecture. CrewAI Flow agents maintain their +internal state throughout execution, which you can access via the `useCoAgentState` hook. + +### Understanding Predicted State + +While your agent runs, you can emit state updates using CopilotKit's `emit_intermediate_state` function, ensuring your UI stays synchronized +with the agent's progress. The emitted state is called the **predicted state** and is used to provide immediate feedback about ongoing +operations. + +While the core shared state reflects the agent's current function in the flow, the predicted state provides immediate +feedback about ongoing operations. Accordingly, this creates a more fluid user experience by showing real-time progress before the agent +completes its current task. + +When the state is updated (when a function finishes executing), the predicted state is updated with the new state. + +For example, when your agent is processing a request, the predicted state might show a loading indicator or partial results, while the actual +shared state updates once the operation is complete. + +Want help implementing this into your CoAgent application? Check out our [intermediate state streaming](/crewai-crews/shared-state/predictive-state-updates) +documentation. + + \ No newline at end of file diff --git a/docs/content/docs/crewai-crews/concepts/terminology.mdx b/docs/content/docs/crewai-crews/concepts/terminology.mdx new file mode 100644 index 0000000000..343c22146d --- /dev/null +++ b/docs/content/docs/crewai-crews/concepts/terminology.mdx @@ -0,0 +1,26 @@ +--- +title: Terminology +icon: lucide/Book +--- + + + +Here are the key terms and concepts used throughout CoAgents: + +| Term | Definition | +|------|------------| +| Agentic Copilot | An AI agent designed to collaborate with users in Agent-Native applications, rather than operate autonomously. | +| CoAgent | Terminology referring to CopilotKit's suite of tools for building agentic applications. Typically interchangeable with agentic copilot. | +| Agent State | The current data and context maintained by a CrewAI agent during its execution, including both internal state and data that can be synchronized with the frontend UI. | +| Agentic Generative UI | UI components that are dynamically generated and updated based on the agent's current state, providing users with visibility into what the agent is doing and building trust through transparency. | +| Ground Truth | In CoAgents, CopilotKit serves as the "ground truth" for the full chat session, maintaining the persistent chat history and ensuring conversational continuity across different agents. | +| Human-in-the-Loop (HITL) | A workflow pattern where human input or validation is required during agent execution, enabling quality control and oversight at critical decision points. | +| Intermediate State | The updates to agent state that occur during function execution, rather than only at flow transitions, enabling real-time feedback about the agent's progress. | +| [CrewAI](https://crewai.com) | The agent framework integrated with CopilotKit that provides the orchestration layer for CoAgents, enabling sophisticated multi-step reasoning and state management. | +| Agent Lock Mode | A mode where CopilotKit is configured to work exclusively with a specific agent, ensuring all requests stay within a single workflow graph for precise control. | +| Router Mode | A mode where CopilotKit dynamically routes requests between different agents and tools based on context and user input, enabling flexible multi-agent workflows. | +| State Streaming | The real-time synchronization of agent state between the backend and frontend, enabling immediate updates to the UI as the agent performs tasks. | + +These terms are referenced throughout the documentation and are essential for understanding how CoAgents work and how to implement them effectively in your applications. + + diff --git a/docs/content/docs/crewai-crews/frontend-actions.mdx b/docs/content/docs/crewai-crews/frontend-actions.mdx new file mode 100644 index 0000000000..37e65d95f6 --- /dev/null +++ b/docs/content/docs/crewai-crews/frontend-actions.mdx @@ -0,0 +1,98 @@ +--- +title: Frontend Actions +icon: "lucide/Wrench" +description: Create frontend actions and use them within your agent. +--- + +import InstallSDKSnippet from "@/snippets/install-sdk.mdx"; + + + + diff --git a/docs/content/docs/crewai-crews/generative-ui/agentic.mdx b/docs/content/docs/crewai-crews/generative-ui/agentic.mdx new file mode 100644 index 0000000000..c96ba5465e --- /dev/null +++ b/docs/content/docs/crewai-crews/generative-ui/agentic.mdx @@ -0,0 +1,81 @@ +--- +title: Agentic Generative UI +icon: "lucide/Bot" +description: Render the state of your agent with custom UI components. +--- +import InstallSDKSnippet from "@/snippets/install-sdk.mdx" +import { Accordions, Accordion } from "fumadocs-ui/components/accordion"; + + + + diff --git a/docs/content/docs/crewai-crews/generative-ui/index.mdx b/docs/content/docs/crewai-crews/generative-ui/index.mdx new file mode 100644 index 0000000000..ada69a13f1 --- /dev/null +++ b/docs/content/docs/crewai-crews/generative-ui/index.mdx @@ -0,0 +1,55 @@ +--- +title: Generative UI +icon: "lucide/Paintbrush" +description: Render your agent's behavior with custom UI components. +--- +import {CTACards} from "@/components/react/cta-cards" +import { WrenchIcon, BotIcon } from "lucide-react" + + + + + Demo of Generative UI showing a meeting scheduling agent + + + + This example shows our [Research Canvas](/crewai-crews/videos/research-canvas) making use of Generative UI! + + +## What is Generative UI? + +Generative UI lets you render your agent's state, progress, outputs, and tool calls with custom UI components in real-time. It bridges the gap between AI +agents and user interfaces. As your agent processes information and makes decisions, you can render custom UI components that: + +- Show loading states and progress indicators +- Display structured data in tables, cards, or charts +- Create interactive elements for user input +- Animate transitions between different states + +## How can I use this? + +There are two main variants of Generative UI. + + + + diff --git a/docs/content/docs/crewai-crews/generative-ui/tool-based.mdx b/docs/content/docs/crewai-crews/generative-ui/tool-based.mdx new file mode 100644 index 0000000000..f2d8f70792 --- /dev/null +++ b/docs/content/docs/crewai-crews/generative-ui/tool-based.mdx @@ -0,0 +1,90 @@ +--- +title: Tool-based Generative UI +icon: "lucide/Wrench" +description: Render your agent's tool calls with custom UI components. +--- +import { Accordions, Accordion } from "fumadocs-ui/components/accordion"; +import RunAndConnectAgentSnippet from "@/snippets/coagents/run-and-connect-agent.mdx" + + + + diff --git a/docs/content/docs/crewai-crews/human-in-the-loop/flow.mdx b/docs/content/docs/crewai-crews/human-in-the-loop/flow.mdx new file mode 100644 index 0000000000..d0dd89b3ac --- /dev/null +++ b/docs/content/docs/crewai-crews/human-in-the-loop/flow.mdx @@ -0,0 +1,122 @@ +--- +title: CrewAI Crews +description: Learn how to implement Human-in-the-Loop (HITL) using CrewAI Crews. +icon: lucide/Share2 +--- +import RunAndConnectAgentSnippet from "@/snippets/coagents/run-and-connect-agent.mdx" +import InstallSDKSnippet from "@/snippets/install-sdk.mdx" + + + + diff --git a/docs/content/docs/crewai-crews/human-in-the-loop/index.mdx b/docs/content/docs/crewai-crews/human-in-the-loop/index.mdx new file mode 100644 index 0000000000..db2f1b35e5 --- /dev/null +++ b/docs/content/docs/crewai-crews/human-in-the-loop/index.mdx @@ -0,0 +1,51 @@ +--- +title: Human in the Loop (HITL) +icon: "lucide/User" +description: Allow your agent and users to collaborate on complex tasks. +--- +import { CTACards } from "@/components/react/cta-cards" +import { Pause, Share2 } from "lucide-react" + + + + diff --git a/docs/content/docs/crewai-crews/human-in-the-loop/meta.json b/docs/content/docs/crewai-crews/human-in-the-loop/meta.json new file mode 100644 index 0000000000..9aa2116b64 --- /dev/null +++ b/docs/content/docs/crewai-crews/human-in-the-loop/meta.json @@ -0,0 +1,3 @@ +{ + "pages": ["flow"] +} diff --git a/docs/content/docs/crewai-crews/index.mdx b/docs/content/docs/crewai-crews/index.mdx new file mode 100644 index 0000000000..4a18bbe57a --- /dev/null +++ b/docs/content/docs/crewai-crews/index.mdx @@ -0,0 +1,157 @@ +--- +title: Introduction +icon: "lucide/Sparkles" +description: Build Agent-Native Applications (ANAs) powered by CopilotKit and CrewAI Flows. +--- + +import { BiSolidMessage as TextIcon } from "react-icons/bi"; +import { VscJson as JsonIcon } from "react-icons/vsc"; +import { FaDiscord } from "react-icons/fa"; +import Link from "next/link"; +import { YouTubeVideo } from "@/components/react/youtube-video"; +import { CoAgentsEnterpriseCTA } from "@/components/react/coagents/coagents-enterprise-cta.tsx"; +import { + CoAgentsFeatureToggle, + CoAgentsFeatureRender, +} from "@/components/react/coagents/coagents-features.tsx"; +import { DynamicContentWrapper } from "@/components/react/dynamic-content-wrapper"; +import { ExamplesCarousel } from "@/components/react/examples-carousel"; +import { + LuPlane, + LuBookOpen, + LuLightbulb, + LuLayoutTemplate, + LuBrainCog, + LuUserCog, + LuWand2, + LuPlay, + LuMessageSquare, + LuWrench, +} from "react-icons/lu"; +import { CoAgentsExamples } from "@/components/react/examples-carousel"; +import { CTACards } from "@/components/react/cta-cards"; +import { FaSync } from "react-icons/fa"; +import { Socials } from "@/components/react/socials"; + + + +# Copilot Infrastructure for CrewAI Crews + +Full user-interaction infrastructure for your agents, to turn your agents into Copilot Agents (CoAgents). + +{/* TODO-DOCS-CREWAI-FLOWS: Add a GIF of this animation for CrewAI Flows */} +{/* + + CoAgents demonstration + */} + +## Building blocks of a CoAgent + +Everything you need to build Agent-Native Applications (ANAs), right out of the box. + + + +{/* TODO-DOCS-CREWAI-FLOWS: Add CoAgents in action section for CrewAI Flows */} + +{/* ## CoAgents in action + +See **CoAgents** in action with some videos and examples we've made to demonstrate their power. + + */} + +## Ready to get started? + +Get started with CoAgents in as little as 5 minutes with one of our guides or tutorials. + + +{/* TODO-DOCS-CREWAI-FLOWS: Add Travel Agent tutorial for CrewAI Flows */} +{/* { + icon: LuPlane, + title: "Travel Agent", + description: + "Learn how to build an agent-native travel app with CopilotKit & CrewAI.", + href: "/crewai-crews/tutorials/ai-travel-app", + }, + { + icon: LuBookOpen, + title: "Researcher Agent", + description: + "Learn how to build an agent-native researcher with CopilotKit & CrewAI.", + href: "/crewai-crews/videos/research-canvas", + }, */} + +## Common Questions + +Have a question about CoAgents? You're in the right place! + + + +Sure! CoAgents are what we call "agentic copilots". Well, what's an agentic copilot then? + +Think of a Copilot as a simple and fully LLM controlled assistant that has relatively limited capabilities. An Agentic Copilot then is a copilot +that has been enhanced with the ability to use CrewAI agents to perform more complex tasks. This is an extremely powerful way to build AI +powered applications because it gives you, the developer, the ability to control the agent's behavior in a deterministic way while still letting +the agent do its magic. + +For more on this topic, checkout our [agentic copilot](/crewai-crews/concepts/agentic-copilots) concept page. + + + + + diff --git a/docs/content/docs/crewai-crews/meta.json b/docs/content/docs/crewai-crews/meta.json new file mode 100644 index 0000000000..1a9794201e --- /dev/null +++ b/docs/content/docs/crewai-crews/meta.json @@ -0,0 +1,19 @@ +{ + "title": "Crews", + "root": true, + "pages": [ + "index", + "---Quickstart---", + "...quickstart", + "---Guides---", + "agentic-chat-ui", + "generative-ui", + "human-in-the-loop", + "shared-state", + "frontend-actions", + "multi-agent-flows", + "advanced", + "---Learn---", + "...concepts" + ] +} diff --git a/docs/content/docs/crewai-crews/multi-agent-flows.mdx b/docs/content/docs/crewai-crews/multi-agent-flows.mdx new file mode 100644 index 0000000000..0fde3513c9 --- /dev/null +++ b/docs/content/docs/crewai-crews/multi-agent-flows.mdx @@ -0,0 +1,61 @@ +--- +title: Multi-Agent Flows +description: Use multiple agents to orchestrate complex flows. +icon: "lucide/Users" +--- + + + + + Multi-Agent Flows + + +## What are Multi-Agent Flows? + +When building agentic applications, you often want to orchestrate complex flows together that require the coordination of multiple +agents. This is traditionally called multi-agent orchestration. + +## When should I use this? + +Multi-agent flows are useful when you want to orchestrate complex flows together that require the coordination of multiple agents. As +your agentic application grows, delegation of sub-tasks to other agents can help you scale key pieces of your application. + +- Divide context into smaller chunks +- Delegate sub-tasks to other agents +- Use a single agent to orchestrate the flow + +## How does CopilotKit support this? + +CopilotKit can be used in either of two distinct modes: **Router Mode**, or **Agent Lock**. By default, CopilotKit +will use Router Mode, leveraging your defined LLM to route requests between agents. + +### Router Mode (default) + +Router Mode is enabled by default when using CoAgents. To use it, specify a runtime URL prop in the `CopilotKit` provider component and omit the `agent` prop, like so: + +```tsx + + {/* Your application components */} + +``` + +In router mode, CopilotKit acts as a central hub, dynamically selecting and _routing_ requests between different agents or actions based on the user's input. This mode can be good for chat-first experiences where an LLM chatbot is the entry point for a range of interactions, which can stay in the chat UI or expand to include native React UI widgets. + +In this mode, CopilotKit will intelligently route requests to the most appropriate agent or action based on the context and user input. + +### Agent Lock Mode + +To use Agent Lock Mode, specify the agent name in the `CopilotKit` component with the `agent` prop: + +```tsx +// [!code word:agent] + + {/* Your application components */} + +``` + +In this mode, CopilotKit is configured to work exclusively with a specific agent. This mode is useful when you want to focus on a particular task or domain. Whereas in Router Mode the LLM and CopilotKit's router are free to switch between agents to handle user requests, in Agent Lock Mode all requests will stay within a single workflow graph, ensuring precise control over the workflow. + +Use whichever mode works best for your app experience! Also, note that while you cannot nest `CopilotKit` providers, you can use different agents or modes in different areas of your app — for example, you may want a chatbot in router mode that can call on any agent or tool, but may also want to integrate one specific agent elsewhere for a more focused workflow. + + diff --git a/docs/content/docs/crewai-crews/quickstart/crewai.mdx b/docs/content/docs/crewai-crews/quickstart/crewai.mdx new file mode 100644 index 0000000000..ba46115988 --- /dev/null +++ b/docs/content/docs/crewai-crews/quickstart/crewai.mdx @@ -0,0 +1,350 @@ +--- +title: Quickstart CrewAI Crews +description: Turn your CrewAI Crews into an agent-native application in 10 minutes. +icon: "custom/crewai" +--- + +import { + TailoredContent, + TailoredContentOption, +} from "@/components/react/tailored-content.tsx"; +import { CoAgentsEnterpriseCTA } from "@/components/react/coagents/coagents-enterprise-cta.tsx"; +import { CoAgentsDiagram } from "@/components/react/coagents/coagents-diagram.tsx"; +import { FaPython, FaJs, FaCloud } from "react-icons/fa"; +import SelfHostingCopilotRuntimeCreateEndpoint from "@/snippets/self-hosting-copilot-runtime-create-endpoint.mdx"; +import CopilotCloudConfigureRemoteEndpointLangGraph from "@/snippets/copilot-cloud-configure-remote-endpoint-langgraph.mdx"; +import CopilotKitCloudCopilotKitProvider from "@/snippets/copilot-cloud-configure-copilotkit-provider.mdx"; +import LangGraphPlatformDeploymentTabs from "@/snippets/langgraph-platform-deployment-tabs.mdx"; +import { Accordions, Accordion } from "fumadocs-ui/components/accordion"; +import FindYourCopilotRuntime from "@/snippets/find-your-copilot-runtime.mdx"; +import CloudCopilotKitProvider from "@/snippets/coagents/cloud-configure-copilotkit-provider.mdx"; +import SelfHostingCopilotRuntimeConfigureCopilotKitProvider from "@/snippets/coagents/self-host-configure-copilotkit-provider.mdx"; +import SelfHostingCopilotRuntimeLangGraphEndpoint from "@/snippets/self-hosting-copilot-runtime-langgraph-endpoint.mdx"; +import SelfHostingCopilotRuntimeStarter from "@/snippets/self-hosting-copilot-runtime-starter.mdx"; +import SelfHostingRemoteEndpoints from "@/snippets/self-hosting-remote-endpoints.mdx"; +import { UserIcon, PaintbrushIcon, WrenchIcon, RepeatIcon, ServerIcon } from "lucide-react"; +import { SiCrewai } from "@icons-pack/react-simple-icons"; +import CopilotUI from "@/snippets/copilot-ui.mdx"; + + + + diff --git a/docs/content/docs/crewai-crews/quickstart/meta.json b/docs/content/docs/crewai-crews/quickstart/meta.json new file mode 100644 index 0000000000..f82abd6328 --- /dev/null +++ b/docs/content/docs/crewai-crews/quickstart/meta.json @@ -0,0 +1,5 @@ +{ + "title": "Quickstart", + "icon": "lucide/Play" + } + \ No newline at end of file diff --git a/docs/content/docs/crewai-crews/shared-state/in-app-agent-read.mdx b/docs/content/docs/crewai-crews/shared-state/in-app-agent-read.mdx new file mode 100644 index 0000000000..39c2cb6ba0 --- /dev/null +++ b/docs/content/docs/crewai-crews/shared-state/in-app-agent-read.mdx @@ -0,0 +1,83 @@ +--- +title: Reading the outputs +icon: "lucide/ArrowLeft" +description: Read the agent state in your native application. +--- +import { ImageZoom } from 'fumadocs-ui/components/image-zoom'; + + + + + + + + + Pictured above is the [coagent starter](https://github.com/copilotkit/copilotkit/tree/main/examples/coagent-starter) with + the [implementation](#implementation) section applied! + + +## What is this? + +You can easily use the realtime agent state in the native application UX. + +## When should I use this? + +You can use this when you want to provide the user with a way to read the outputs of a CrewAI Crew from your application. + +## Implementation + + + + ### Run and Connect Your Agent to CopilotKit + + You'll need to run your agent and connect it to CopilotKit before proceeding. If you haven't done so already, + you can follow the instructions in the [Getting Started](/getting-started) guide. + + If you don't already have an agent, you can use the [coagent starter](https://github.com/copilotkit/copilotkit/tree/main/examples/coagent-starter-crewai-crews) as a starting point + as this guide uses it as a starting point. + + + ### Use the `useCoAgent` Hook + With your agent connected and running all that is left is to call the [useCoAgent](/reference/hooks/useCoAgent) hook, pass the agent's name, and + optionally provide an initial state. + + ```tsx title="ui/app/page.tsx" + import { useCoAgent } from "@copilotkit/react-core"; // [!code highlight] + + // Define the agent state type, should match the actual state of your agent + + + function YourMainContent() { + const { state } = useCoAgent({ + name: "research_crew", + initialState: { + inputs: { + topic: "", + current_year: "2025", + }, + outputs: "Report will appear here", + }, + }); + + // ... + + return ( + // style excluded for brevity +
+

Your report:

+

{state.outputs}

// [!code highlight] +
+ ); + } + ``` + + The `state` in `useCoAgent` is reactive and will automatically update when the agent's state changes. + +
+ + ### Give it a try! + As the agent state updates, your `state` variable will automatically update with it! In this case, you'll see the report update when the crew is done running. + +
+ +
diff --git a/docs/content/docs/crewai-crews/shared-state/in-app-agent-write.mdx b/docs/content/docs/crewai-crews/shared-state/in-app-agent-write.mdx new file mode 100644 index 0000000000..0f25c316db --- /dev/null +++ b/docs/content/docs/crewai-crews/shared-state/in-app-agent-write.mdx @@ -0,0 +1,98 @@ +--- +title: Setting the inputs +icon: "lucide/ArrowRight" +description: Write to the inputs of a CrewAI Crew from your application. +--- + + + + diff --git a/docs/content/docs/crewai-crews/shared-state/index.mdx b/docs/content/docs/crewai-crews/shared-state/index.mdx new file mode 100644 index 0000000000..dc52f47472 --- /dev/null +++ b/docs/content/docs/crewai-crews/shared-state/index.mdx @@ -0,0 +1,39 @@ +--- +title: Shared State +description: Create a two-way connection between your UI and agent state. +icon: "lucide/Repeat" +--- +import { ImageZoom } from "fumadocs-ui/components/image-zoom"; + + + + + + + This video demonstrates the [Research Canvas](/crewai-crews/examples/research-canvas) utilizing shared state. + + + +## What is shared state? + +CoAgents maintain a shared state that seamlessly connects your UI with the agent's execution. In the case of CrewAI Crews, the shared state system allows you to: +- Update and send the `inputs` of the crew to the agent +- Receive the `outputs` of the crew +- React to state changes in real-time across your application + + + Agentic Copilot State Diagram + + +## When should I use this? +Shared state is perfect when you want to facilitate collaboration between your agent and the user. Updates to the outputs will be automatically shared by the UI. Similarly, any `inputs` that the user updates in the UI will be automatically reflected in the crews execution. + +This allows for a consistent experience where both the agent and the user are on the same page. + + diff --git a/docs/content/docs/crewai-crews/shared-state/meta.json b/docs/content/docs/crewai-crews/shared-state/meta.json new file mode 100644 index 0000000000..645df8a3c5 --- /dev/null +++ b/docs/content/docs/crewai-crews/shared-state/meta.json @@ -0,0 +1,3 @@ +{ + "pages": ["in-app-agent-read", "in-app-agent-write"] +} diff --git a/docs/content/docs/crewai-flows/advanced/disabling-state-streaming.mdx b/docs/content/docs/crewai-flows/advanced/disabling-state-streaming.mdx new file mode 100644 index 0000000000..4b4868d33a --- /dev/null +++ b/docs/content/docs/crewai-flows/advanced/disabling-state-streaming.mdx @@ -0,0 +1,63 @@ +--- +title: "Disabling state streaming" +icon: "lucide/Cog" +description: "Granularly control what is streamed to the frontend." +--- + +import InstallSDKSnippet from "@/snippets/install-sdk.mdx"; + + + +## What is this? + +By default, CopilotKit will stream both your state and tool calls to the frontend. +You can disable this by using CopilotKit's custom `RunnableConfig`. + +## When should I use this? + +Occasionally, you'll want to disable streaming temporarily — for example, the LLM may be +doing something the current user should not see, like emitting tool calls or questions +pertaining to other employees in an HR system. + +## Implementation + +### Disable all streaming + +You can decide wether to stream messages or tool calls by selectively wrapping calls to `completion` +with `copilotkit_stream`. + + + + ```python + from copilotkit.crewai import copilotkit_stream + + @start() + async def start(self): + + # 1) Do not emit messages or tool calls, keeping the LLM call private. + response = completion( + model="openai/gpt-4o", + messages=[ + {"role": "system", "content": my_prompt}, + *self.state["messages"] + ], + ) + + # 2) Or wrap the LLM call with `copilotkit_stream` to stream messages tokens. + # Note that we pass `stream=True` to the inner `completion` call. + response = copilotkit_stream( + completion( + model="openai/gpt-4o", + messages=[ + {"role": "system", "content": my_prompt}, + *self.state["messages"] + ], + stream=True + ) + ) + ``` + + + + + diff --git a/docs/content/docs/crewai-flows/advanced/emit-messages.mdx b/docs/content/docs/crewai-flows/advanced/emit-messages.mdx new file mode 100644 index 0000000000..1fedf7cb80 --- /dev/null +++ b/docs/content/docs/crewai-flows/advanced/emit-messages.mdx @@ -0,0 +1,86 @@ +--- +title: "Manually emitting messages" +icon: "lucide/Radio" +--- + + + +import InstallSDKSnippet from "@/snippets/install-sdk.mdx" +import RunAndConnectSnippet from "@/snippets/coagents/run-and-connect-agent.mdx" + +While most agent interactions happen automatically through shared state updates as the agent runs, you can also **manually send messages from within your agent code** to provide immediate feedback to users. + + diff --git a/docs/content/docs/crewai-flows/advanced/exit-agent.mdx b/docs/content/docs/crewai-flows/advanced/exit-agent.mdx new file mode 100644 index 0000000000..8390544ece --- /dev/null +++ b/docs/content/docs/crewai-flows/advanced/exit-agent.mdx @@ -0,0 +1,56 @@ +--- +title: "Exiting the agent loop" +icon: "lucide/DoorOpen" +--- +import InstallSDKSnippet from "@/snippets/install-sdk.mdx" + + + +After your agent has finished a workflow, you'll usually want to explicitly end that loop by calling the `copilotkit_exit()` method in your Python code. + +Exiting the agent has different effects depending on mode: + +- **Router Mode**: Exiting the agent hands responsibility for handling input back to the router, which can initiate chat, call actions, other agents, etc. The router can return to this agent later (starting a new loop) to satisfy a user request. + +- **Agent Lock Mode**: Exiting the agent restarts the workflow loop for the current agent. + +In this example from [our email-sending app](https://github.com/copilotkit/copilotkit/tree/main/examples/coagents-qa), the `send_email` node explicitly exits, then manually sends a response back to the user as a `ToolMessage`: + + + + ### Install the CopilotKit SDK + + + + + ### Exit the agent loop + This will exit the agent session as soon as the current CrewAI run is finished, either by a breakpoint or by reaching the `END` node. + + + + ```python + import uuid + from litellm import completion + from crewai.flow.flow import start + from copilotkit.crewai import copilotkit_exit + # ... + @start() + async def send_email(self): + """Send an email.""" + + await copilotkit_exit() # [!code highlight] + + # get the last message and cast to ToolMessage + last_message = self.state["messages"][-1] + if last_message["content"] == "CANCEL": + text_message = "❌ Cancelled sending email." + else: + text_message = "✅ Sent email." + self.state["messages"].append({"role": "assistant", "content": text_message, "id": str(uuid.uuid4())}) + ``` + + + + + + diff --git a/docs/content/docs/crewai-flows/advanced/meta.json b/docs/content/docs/crewai-flows/advanced/meta.json new file mode 100644 index 0000000000..b541e1e459 --- /dev/null +++ b/docs/content/docs/crewai-flows/advanced/meta.json @@ -0,0 +1,4 @@ +{ + "title": "Advanced", + "icon": "lucide/Cog" +} \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/agentic-chat-ui.mdx b/docs/content/docs/crewai-flows/agentic-chat-ui.mdx new file mode 100644 index 0000000000..7e7acbc1ca --- /dev/null +++ b/docs/content/docs/crewai-flows/agentic-chat-ui.mdx @@ -0,0 +1,34 @@ +--- +title: Chat with an Agent +icon: "lucide/SendHorizontal" +description: Chat with an agent using CopilotKit's UI components. +--- +import ConnectCopilotUI from "@/snippets/copilot-ui.mdx"; +import SelfHostingCopilotRuntimeCreateEndpoint from "@/snippets/self-hosting-copilot-runtime-create-endpoint.mdx"; +import SelfHostingCopilotRuntimeConfigureCopilotKitProvider from "@/snippets/self-hosting-copilot-runtime-configure-copilotkit-provider.mdx"; +import CopilotCloudConfigureCopilotKitProvider from "@/snippets/cloud/cloud-copilotkit-provider.mdx"; +import ComponentExamples from "@/snippets/component-examples.mdx"; +import { UserIcon, PaintbrushIcon, WrenchIcon, RepeatIcon } from "lucide-react"; + + + + \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/concepts/agentic-copilots.mdx b/docs/content/docs/crewai-flows/concepts/agentic-copilots.mdx new file mode 100644 index 0000000000..76533af5d9 --- /dev/null +++ b/docs/content/docs/crewai-flows/concepts/agentic-copilots.mdx @@ -0,0 +1,163 @@ +--- +title: Agentic Copilots +description: Agentic copilots provide you with advanced control and orchestration over your agents. +icon: lucide/Bot +--- + +import { TailoredContent, TailoredContentOption } from "@/components/react/tailored-content"; +import { BsFillCloudHaze2Fill as CloudIcon } from "react-icons/bs"; +import { FaServer as SelfHostIcon } from "react-icons/fa6"; +import { SiLangchain } from "react-icons/si"; +import { LinkIcon } from "lucide-react"; +import { RocketIcon, GraduationCapIcon, CodeIcon, VideoIcon } from "lucide-react"; + + + +Before we dive into what agentic copilots are, help us help you by telling us your level of experience with CrewAI. We'll explain things in a way that best suits your experience level. + + + } + > + + CoAgents Shared State + + + ### What are Agents? + AI agents are intelligent systems that interact with their environment to achieve specific goals. Think of them as 'virtual colleagues' that can handle tasks ranging from + simple queries like "find the cheapest flight to Paris" to complex challenges like "design a new product layout." + + As these AI-driven experiences (or 'Agentic Experiences') become more sophisticated, developers need finer control over how agents make decisions. This is where specialized + frameworks like CrewAI become essential. + + ### What is CrewAI? + CrewAI is a framework that gives you precise control over AI agents. CrewAI flows allow developers to combine and coordinate coding tasks and Crews efficiently, + providing a robust framework for building sophisticated AI automations. + + ### What are Agentic Copilots? + Agentic copilots are how CopilotKit brings CrewAI agents into your application. If you're familiar with CopilotKit, you know that copilots are AI assistants that + understand your app's context and can take actions within it. While CopilotKit's standard copilots use a simplified [ReAct pattern](https://www.perplexity.ai/search/what-s-a-react-agent-5hu7ZOaKSAuY7YdFjQLCNQ) + for quick implementation, Agentic copilots give you CrewAI's full orchestration capabilities when you need more control over your agent's behavior. + + ### What are CoAgents? + CoAgents are what we call CopilotKit's approach to building agentic experiences! They're interchangeable with agentic copilots being a more descriptive term for the overall concept. + + ### When should I use CopilotKit's CoAgents? + You should use CoAgents when you require tight control over the Agentic runloop, as facilitated by an Agentic Orchestration framework like [CrewAI](https://crewai.com/). + With CoAgents, you can carry all of your existing CopilotKit-enabled Copilot capabilities into a customized agentic runloop. + + We suggest beginning with a basic Copilot and gradually transitioning specific components to CoAgents. + + The need for CoAgents spans a broad spectrum across different applications. At one end, their advanced capabilities might not be required at all, or only for a minimal 10% of the application's + functionality. Progressing further, there are scenarios where they become increasingly vital, managing 60-70% of operations. Ultimately, in some cases, CoAgents are indispensable, orchestrating + up to 100% of the Copilot's tasks (see [agent-lock mode](/crewai-flows/multi-agent-flows) for the 100% case). + + ### Examples + An excellent example of the type of experiences you can accomplish with CoAgents applications can be found in our [Research Canvas](https://github.com/CopilotKit/CopilotKit/tree/main/examples/coagents-research-canvas). + + More specifically, it demonstrates how CoAgents allow for AI driven experiences with: + - Precise state management across agent interactions + - Sophisticated multi-step reasoning capabilities + - Seamless orchestration of multiple AI tools + - Interactive human-AI collaboration features + - Real-time state updates and progress streaming + + ## Next Steps + + Want to get started? You have some options! + + + } + /> + } + /> + } + /> + } + /> + + + } + > + + + CoAgents demonstration + + + CrewAI is a framework for building deeply customizable AI agents. + + CopilotKit's Agentic Copilots is infrastructure for in-app agent-user interaction, i.e. for transforming agents from autonomous processes to user-interactive 'virtual colleagues' that live inside applications. + + Any CrewAI-based agent can be transformed into an Agentic Copilot with a minimal amount + of effort to get industry leading agentic UX such as: + - Shared state between the agent and the application. + - Intermediate result and state progress streaming + - Human-in-the-loop collaboration + - Agentic generative UI + - And more! + + All of these features are essential to delight instead of frustrate your users with AI features. + + ### What are CoAgents? + CoAgents are what we call CopilotKit's approach to building agentic experiences! They're interchangeable with agentic copilots being a more descriptive term for the overall concept. + + ## Next Steps + Want to get started? You have some options! + + + } + /> + } + /> + } + /> + } + /> + + + + + diff --git a/docs/content/docs/crewai-flows/concepts/copilotkit-stream.mdx b/docs/content/docs/crewai-flows/concepts/copilotkit-stream.mdx new file mode 100644 index 0000000000..1f3227bcd2 --- /dev/null +++ b/docs/content/docs/crewai-flows/concepts/copilotkit-stream.mdx @@ -0,0 +1,33 @@ +--- +title: Streaming and Tool Calls +description: CoAgents support streaming your messages and tool calls to the frontend. +--- + + + +If you'd like to stream messages from your CrewAI agents you can utilize our Copilotkit SDK which provides a collection +of functions and utilities for interacting with the agent's state or behavior. This allows you to choose how messages and +tool calls are emitted and streamed to the frontend. + +## Message Streaming +If you just call the LiteLLM `completion` function from your CrewAI agent, messages will not be streamed by default. +To stream messages, wrap the `completion` function with the `copilotkit_stream` function. This will enable streaming +of both the messages and tool calls to the frontend. + +```python +response = copilotkit_stream( + completion( + model="openai/gpt-4o", + messages=[ + {"role": "system", "content": my_prompt}, + *self.state["messages"] + ], + stream=True + ) +) +``` + +For more information on how tool calls are utilized check out our [frontend actions](/crewai-flows/frontend-actions) +documentation. + + diff --git a/docs/content/docs/crewai-flows/concepts/crewai.mdx b/docs/content/docs/crewai-flows/concepts/crewai.mdx new file mode 100644 index 0000000000..ed0ca16c0a --- /dev/null +++ b/docs/content/docs/crewai-flows/concepts/crewai.mdx @@ -0,0 +1,56 @@ +--- +title: CrewAI +description: An agentic framework for building LLM applications that can be used with Copilotkit. +icon: custom/langchain +--- + + + + + CoAgents High Level Overview + + +CrewAI is an agentic framework for building LLM applications that can be used with Copilotkit. CrewAi Flows allow developers +to combine and coordinate coding tasks and Crews efficiently, providing a robust framework for building sophisticated AI automations. + +## CoAgents and CrewAI + +How do CoAgents extend CrewAI? Let's read the first sentence of their [page on Flows](https://docs.crewai.com/concepts/flows) to understand. + +> Flows allow you to create structured, event-driven workflows. They provide a seamless way to connect multiple tasks, manage state, and control the flow of execution in your AI applications. + +Let's break down some key terms and understand how they relate to and are implemented by CoAgents. + +- ** manage state**: CoAgents have bi-directional state sharing with the agent and UI. This allows for the agent to remember + information from previous messages and the UI to update the agent with new information. Read more about how state sharing works + [here](/crewai-flows/shared-state). +- **Multi-actor**: CoAgents allow for multiple agents to interact with each other. Copilotkit acts as the "ground-truth" + when transitioning between agents. Read more about how multi-actor workflows work [here](/crewai-flows/multi-agent-flows) + and how messages are managed [here](/crewai-flows/concepts/message-management). +- **LLMs**: CoAgents use large language models to generate responses. This is useful for building applications that need to + generate natural language responses. + +Some additional functionality not mentioned here is: +- **Human in the loop**: CoAgents enabled human review and approval of generated responses. Read more about how this works + [here](/crewai-flows/human-in-the-loop). +- **Tool calling**: Tool calling is a fundamental building block for agentic workflows. They allow for greater control over what + the agent can do and can be used to interact with external systems. CoAgents allow you to easily render in-progress + tool calls in the UI so your users know what's happening. Read more about streaming tool calls [here](/crewai-flows/shared-state/predictive-state-updates). + +## Building with Python + +You can build CrewAI applications using Python. Check out the [CrewAI docs](https://docs.crewai.com/introduction) for more information. + +## CrewAI Enterprise + +Turn any crew into an API within seconds +Connect to your apps using hooks, REST, gRPC and more +Get access to templates, custom tools and early UI +Get business support, SLA, private VPC + +CrewAI enterprise is a platform for deploying and monitoring CrewAI applications. Read more about it on the +[CrewAI website](https://www.crewai.com/enterprise). + +If you want to take the next step to deploy your CrewAI application as an CoAgent, check out our [quickstart guide](/crewai-flows/quickstart/crewai). + + diff --git a/docs/content/docs/crewai-flows/concepts/message-management.mdx b/docs/content/docs/crewai-flows/concepts/message-management.mdx new file mode 100644 index 0000000000..10c574be41 --- /dev/null +++ b/docs/content/docs/crewai-flows/concepts/message-management.mdx @@ -0,0 +1,80 @@ +--- +title: Message flow +icon: lucide/MessageCircle +--- + + + +Message management in CoAgents operates with CopilotKit as the "ground truth" for the full chat session. +When an CoAgent session begins, it receives the existing CopilotKit chat history to maintain conversational +continuity across different agents. + + +While all of this information is great to know, in most cases you won't need to worry about these details to +build rich agentic applications. Use the information here as a reference when getting really deep into +the CoAgent internals. + + +### Can I modify the message history? + +You can modify the message history from CrewAI Flows by using the `"messages"` key in the state. For example to remove all messages from the chat history: + +```python + +def a_flow_function(): + # ... + self.state["messages"] = [] +``` + +### Can I persist chat history? + +Yes! There are a few ways to persist various portions of a chat's history: +- [Threads](/crewai-flows/persistence/threads) +- [Message Persistence](/crewai-flows/persistence/message-persistence) +- [Agent State](/crewai-flows/persistence/loading-agent-state) + +## Types of LLM Messages + +Modern LLM interactions produce two distinct types of messages: + +1. **Communication Messages**: Direct responses and interactions with users +2. **Internal Messages**: Agent "thoughts" and reasoning processes + +A well known example of this pattern is OpenAI's o1 model, which has sophisticated reasoning capabilities and thoughts. Its internal +thought processes are presented distinctly from 'communication messages' which are clearly visible to the end-user. + +CrewAI agents can operate similarly. An LLM call's output can be considered either a communication message, or an internal message. + +### Emitting Messages for long running tasks + +Sometimes you'll have a task that is running for a long time, and you want the user to be aware of what's happening. +CopilotKit allows you to accomplish this by using the `copilotkit_emit_message` function. + +```python +@listen("route_to_ask_name") +async def ask_name(): + """ + Ask the user for their name. + """ + + content = "Hey, what is your name? 🙂" + + await copilotkit_emit_message(content) + + # something long running here... + + self.state["messages"].append({"role": "assistant", "content": content, "id": str(uuid.uuid4())}) + +``` + +Want some more help managing messages in your CoAgent application? Check out our guide on [emitting messages](/crewai-flows/advanced/emit-messages). + +## Message Flow +Messages flow between CopilotKit and CrewAI in a specific way: + +- All messages from CrewAI are forwarded to CopilotKit +- On a fresh agent invocation, the full CopilotKit chat history is provided to the CrewAI agent as its pre-existing chat history. + +When a CoAgent completes its execution, its relevant messages become part of CopilotKit's persistent chat history. This allows for all future agent invocations to get context from the full chat history. + + diff --git a/docs/content/docs/crewai-flows/concepts/meta.json b/docs/content/docs/crewai-flows/concepts/meta.json new file mode 100644 index 0000000000..548d0b3d37 --- /dev/null +++ b/docs/content/docs/crewai-flows/concepts/meta.json @@ -0,0 +1,5 @@ +{ + "title": "Concepts", + "root": true, + "pages": ["terminology", "agentic-copilots", "crewai", "message-management"] +} diff --git a/docs/content/docs/crewai-flows/concepts/state.mdx b/docs/content/docs/crewai-flows/concepts/state.mdx new file mode 100644 index 0000000000..5c4207db25 --- /dev/null +++ b/docs/content/docs/crewai-flows/concepts/state.mdx @@ -0,0 +1,39 @@ +--- +title: Shared State +description: CoAgents maintain a shared state across your UI and agent execution. +--- + + + + + Agentic Copilot State Diagram + + +CoAgents maintain a shared state that seamlessly connects your UI with the agent's execution. This shared state system allows you to: +- Display the agent's current progress and intermediate results +- Update the agent's state through UI interactions +- React to state changes in real-time across your application + +The foundation of this system is built on CrewAI's stateful architecture. CrewAI Flow agents maintain their +internal state throughout execution, which you can access via the `useCoAgentState` hook. + +### Understanding Predicted State + +While your agent runs, you can emit state updates using CopilotKit's `emit_intermediate_state` function, ensuring your UI stays synchronized +with the agent's progress. The emitted state is called the **predicted state** and is used to provide immediate feedback about ongoing +operations. + +While the core shared state reflects the agent's current function in the flow, the predicted state provides immediate +feedback about ongoing operations. Accordingly, this creates a more fluid user experience by showing real-time progress before the agent +completes its current task. + +When the state is updated (when a function finishes executing), the predicted state is updated with the new state. + +For example, when your agent is processing a request, the predicted state might show a loading indicator or partial results, while the actual +shared state updates once the operation is complete. + +Want help implementing this into your CoAgent application? Check out our [intermediate state streaming](/crewai-flows/shared-state/predictive-state-updates) +documentation. + + + \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/concepts/terminology.mdx b/docs/content/docs/crewai-flows/concepts/terminology.mdx new file mode 100644 index 0000000000..343c22146d --- /dev/null +++ b/docs/content/docs/crewai-flows/concepts/terminology.mdx @@ -0,0 +1,26 @@ +--- +title: Terminology +icon: lucide/Book +--- + + + +Here are the key terms and concepts used throughout CoAgents: + +| Term | Definition | +|------|------------| +| Agentic Copilot | An AI agent designed to collaborate with users in Agent-Native applications, rather than operate autonomously. | +| CoAgent | Terminology referring to CopilotKit's suite of tools for building agentic applications. Typically interchangeable with agentic copilot. | +| Agent State | The current data and context maintained by a CrewAI agent during its execution, including both internal state and data that can be synchronized with the frontend UI. | +| Agentic Generative UI | UI components that are dynamically generated and updated based on the agent's current state, providing users with visibility into what the agent is doing and building trust through transparency. | +| Ground Truth | In CoAgents, CopilotKit serves as the "ground truth" for the full chat session, maintaining the persistent chat history and ensuring conversational continuity across different agents. | +| Human-in-the-Loop (HITL) | A workflow pattern where human input or validation is required during agent execution, enabling quality control and oversight at critical decision points. | +| Intermediate State | The updates to agent state that occur during function execution, rather than only at flow transitions, enabling real-time feedback about the agent's progress. | +| [CrewAI](https://crewai.com) | The agent framework integrated with CopilotKit that provides the orchestration layer for CoAgents, enabling sophisticated multi-step reasoning and state management. | +| Agent Lock Mode | A mode where CopilotKit is configured to work exclusively with a specific agent, ensuring all requests stay within a single workflow graph for precise control. | +| Router Mode | A mode where CopilotKit dynamically routes requests between different agents and tools based on context and user input, enabling flexible multi-agent workflows. | +| State Streaming | The real-time synchronization of agent state between the backend and frontend, enabling immediate updates to the UI as the agent performs tasks. | + +These terms are referenced throughout the documentation and are essential for understanding how CoAgents work and how to implement them effectively in your applications. + + diff --git a/docs/content/docs/crewai-flows/frontend-actions.mdx b/docs/content/docs/crewai-flows/frontend-actions.mdx new file mode 100644 index 0000000000..00b6f1305b --- /dev/null +++ b/docs/content/docs/crewai-flows/frontend-actions.mdx @@ -0,0 +1,140 @@ +--- +title: Frontend Actions +icon: "lucide/Wrench" +description: Create frontend actions and use them within your agent. +--- +import InstallSDKSnippet from "@/snippets/install-sdk.mdx" + + + + diff --git a/docs/content/docs/crewai-flows/generative-ui/agentic.mdx b/docs/content/docs/crewai-flows/generative-ui/agentic.mdx new file mode 100644 index 0000000000..7028d6e725 --- /dev/null +++ b/docs/content/docs/crewai-flows/generative-ui/agentic.mdx @@ -0,0 +1,198 @@ +--- +title: Agentic Generative UI +icon: "lucide/Bot" +description: Render the state of your agent with custom UI components. +--- +import InstallSDKSnippet from "@/snippets/install-sdk.mdx" +import { Accordions, Accordion } from "fumadocs-ui/components/accordion"; + + + + diff --git a/docs/content/docs/crewai-flows/generative-ui/index.mdx b/docs/content/docs/crewai-flows/generative-ui/index.mdx new file mode 100644 index 0000000000..e17dc98352 --- /dev/null +++ b/docs/content/docs/crewai-flows/generative-ui/index.mdx @@ -0,0 +1,55 @@ +--- +title: Generative UI +icon: "lucide/Paintbrush" +description: Render your agent's behavior with custom UI components. +--- +import {CTACards} from "@/components/react/cta-cards" +import { WrenchIcon, BotIcon } from "lucide-react" + + + + + Demo of Generative UI showing a meeting scheduling agent + + + + This example shows our [Research Canvas](/crewai-flows/videos/research-canvas) making use of Generative UI! + + +## What is Generative UI? + +Generative UI lets you render your agent's state, progress, outputs, and tool calls with custom UI components in real-time. It bridges the gap between AI +agents and user interfaces. As your agent processes information and makes decisions, you can render custom UI components that: + +- Show loading states and progress indicators +- Display structured data in tables, cards, or charts +- Create interactive elements for user input +- Animate transitions between different states + +## How can I use this? + +There are two main variants of Generative UI. + + + + diff --git a/docs/content/docs/crewai-flows/generative-ui/tool-based.mdx b/docs/content/docs/crewai-flows/generative-ui/tool-based.mdx new file mode 100644 index 0000000000..b1e66eca90 --- /dev/null +++ b/docs/content/docs/crewai-flows/generative-ui/tool-based.mdx @@ -0,0 +1,133 @@ +--- +title: Tool-based Generative UI +icon: "lucide/Wrench" +description: Render your agent's tool calls with custom UI components. +--- +import { Accordions, Accordion } from "fumadocs-ui/components/accordion"; +import RunAndConnectAgentSnippet from "@/snippets/coagents/run-and-connect-agent.mdx" + + + + diff --git a/docs/content/docs/crewai-flows/human-in-the-loop/flow.mdx b/docs/content/docs/crewai-flows/human-in-the-loop/flow.mdx new file mode 100644 index 0000000000..a6495a1ecc --- /dev/null +++ b/docs/content/docs/crewai-flows/human-in-the-loop/flow.mdx @@ -0,0 +1,188 @@ +--- +title: CrewAI Flows +description: Learn how to implement Human-in-the-Loop (HITL) using CrewAI Flows. +icon: lucide/Share2 +--- +import RunAndConnectAgentSnippet from "@/snippets/coagents/run-and-connect-agent.mdx" +import InstallSDKSnippet from "@/snippets/install-sdk.mdx" + + + + diff --git a/docs/content/docs/crewai-flows/human-in-the-loop/index.mdx b/docs/content/docs/crewai-flows/human-in-the-loop/index.mdx new file mode 100644 index 0000000000..202c7a9c06 --- /dev/null +++ b/docs/content/docs/crewai-flows/human-in-the-loop/index.mdx @@ -0,0 +1,51 @@ +--- +title: Human in the Loop (HITL) +icon: "lucide/User" +description: Allow your agent and users to collaborate on complex tasks. +--- +import { CTACards } from "@/components/react/cta-cards" +import { Pause, Share2 } from "lucide-react" + + + + diff --git a/docs/content/docs/crewai-flows/human-in-the-loop/meta.json b/docs/content/docs/crewai-flows/human-in-the-loop/meta.json new file mode 100644 index 0000000000..9aa2116b64 --- /dev/null +++ b/docs/content/docs/crewai-flows/human-in-the-loop/meta.json @@ -0,0 +1,3 @@ +{ + "pages": ["flow"] +} diff --git a/docs/content/docs/crewai-flows/index.mdx b/docs/content/docs/crewai-flows/index.mdx new file mode 100644 index 0000000000..77546f8c56 --- /dev/null +++ b/docs/content/docs/crewai-flows/index.mdx @@ -0,0 +1,167 @@ +--- +title: Introduction +icon: "lucide/Sparkles" +description: Build Agent-Native Applications (ANAs) powered by CopilotKit and CrewAI Flows. +--- + +import { BiSolidMessage as TextIcon } from "react-icons/bi"; +import { VscJson as JsonIcon } from "react-icons/vsc"; +import { FaDiscord } from "react-icons/fa"; +import Link from "next/link"; +import { YouTubeVideo } from "@/components/react/youtube-video"; +import { CoAgentsEnterpriseCTA } from "@/components/react/coagents/coagents-enterprise-cta.tsx"; +import { + CoAgentsFeatureToggle, + CoAgentsFeatureRender, +} from "@/components/react/coagents/coagents-features.tsx"; +import { DynamicContentWrapper } from "@/components/react/dynamic-content-wrapper"; +import { ExamplesCarousel } from "@/components/react/examples-carousel"; +import { + LuPlane, + LuBookOpen, + LuLightbulb, + LuLayoutTemplate, + LuBrainCog, + LuUserCog, + LuWand2, + LuPlay, + LuMessageSquare, + LuWrench, +} from "react-icons/lu"; +import { CoAgentsExamples } from "@/components/react/examples-carousel"; +import { CTACards } from "@/components/react/cta-cards"; +import { FaSync } from "react-icons/fa"; +import { Socials } from "@/components/react/socials"; + + + +# Copilot Infrastructure for CrewAI Flows + +Full user-interaction infrastructure for your agents, to turn your agents into Copilot Agents (CoAgents). + +{/* TODO-DOCS-CREWAI-FLOWS: Add a GIF of this animation for CrewAI Flows */} +{/* + CoAgents demonstration + */} + +## Building blocks of a CoAgent + +Everything you need to build Agent-Native Applications (ANAs), right out of the box. + + + +{/* TODO-DOCS-CREWAI-FLOWS: Add CoAgents in action section for CrewAI Flows */} + +{/* ## CoAgents in action + +See **CoAgents** in action with some videos and examples we've made to demonstrate their power. + + */} + +## Ready to get started? + +Get started with CoAgents in as little as 5 minutes with one of our guides or tutorials. + + + {/* TODO-DOCS-CREWAI-FLOWS: Add Travel Agent tutorial for CrewAI Flows */} + {/* { + icon: LuPlane, + title: "Travel Agent", + description: + "Learn how to build an agent-native travel app with CopilotKit & CrewAI.", + href: "/crewai-flows/tutorials/ai-travel-app", + }, + { + icon: LuBookOpen, + title: "Researcher Agent", + description: + "Learn how to build an agent-native researcher with CopilotKit & CrewAI.", + href: "/crewai-flows/videos/research-canvas", + }, */} + +## Common Questions + +Have a question about CoAgents? You're in the right place! + + + +Sure! CoAgents are what we call "agentic copilots". Well, what's an agentic copilot then? + +Think of a Copilot as a simple and fully LLM controlled assistant that has relatively limited capabilities. An Agentic Copilot then is a copilot +that has been enhanced with the ability to use CrewAI agents to perform more complex tasks. This is an extremely powerful way to build AI +powered applications because it gives you, the developer, the ability to control the agent's behavior in a deterministic way while still letting +the agent do its magic. + +For more on this topic, checkout our [agentic copilot](/crewai-flows/concepts/agentic-copilots) concept page. + + + +Development of CoAgents is ongoing. One part of this is the ability to attach to an existing thread which is a high priority on our roadmap. + +Stay tuned for updates! + + + + + diff --git a/docs/content/docs/crewai-flows/meta.json b/docs/content/docs/crewai-flows/meta.json new file mode 100644 index 0000000000..642b327d78 --- /dev/null +++ b/docs/content/docs/crewai-flows/meta.json @@ -0,0 +1,20 @@ +{ + "title": "CoAgents", + "root": true, + "pages": [ + "index", + "---Quickstart---", + "...quickstart", + "---Guides---", + "agentic-chat-ui", + "generative-ui", + "human-in-the-loop", + "shared-state", + "frontend-actions", + "multi-agent-flows", + "persistence", + "advanced", + "---Learn---", + "...concepts" + ] +} diff --git a/docs/content/docs/crewai-flows/multi-agent-flows.mdx b/docs/content/docs/crewai-flows/multi-agent-flows.mdx new file mode 100644 index 0000000000..d147c4d0fc --- /dev/null +++ b/docs/content/docs/crewai-flows/multi-agent-flows.mdx @@ -0,0 +1,52 @@ +--- +title: Multi-Agent Flows +description: Use multiple agents to orchestrate complex flows. +icon: "lucide/Users" +--- + + + Multi-Agent Flows + + +## What are Multi-Agent Flows? + +When building agentic applications, you often want to orchestrate complex flows together that require the coordination of multiple +agents. This is traditionally called multi-agent orchestration. + +## When should I use this? + +Multi-agent flows are useful when you want to orchestrate complex flows together that require the coordination of multiple agents. As +your agentic application grows, delegation of sub-tasks to other agents can help you scale key pieces of your application. +- Divide context into smaller chunks +- Delegate sub-tasks to other agents +- Use a single agent to orchestrate the flow + +## How does CopilotKit support this? + +CopilotKit can be used in either of two distinct modes: **Router Mode**, or **Agent Lock**. By default, CopilotKit +will use Router Mode, leveraging your defined LLM to route requests between agents. + +### Router Mode (default) +Router Mode is enabled by default when using CoAgents. To use it, specify a runtime URL prop in the `CopilotKit` provider component and omit the `agent` prop, like so: +```tsx + + {/* Your application components */} + +``` + +In router mode, CopilotKit acts as a central hub, dynamically selecting and _routing_ requests between different agents or actions based on the user's input. This mode can be good for chat-first experiences where an LLM chatbot is the entry point for a range of interactions, which can stay in the chat UI or expand to include native React UI widgets. + +In this mode, CopilotKit will intelligently route requests to the most appropriate agent or action based on the context and user input. + +### Agent Lock Mode +To use Agent Lock Mode, specify the agent name in the `CopilotKit` component with the `agent` prop: +```tsx +// [!code word:agent] + + {/* Your application components */} + +``` + +In this mode, CopilotKit is configured to work exclusively with a specific agent. This mode is useful when you want to focus on a particular task or domain. Whereas in Router Mode the LLM and CopilotKit's router are free to switch between agents to handle user requests, in Agent Lock Mode all requests will stay within a single workflow graph, ensuring precise control over the workflow. + +Use whichever mode works best for your app experience! Also, note that while you cannot nest `CopilotKit` providers, you can use different agents or modes in different areas of your app — for example, you may want a chatbot in router mode that can call on any agent or tool, but may also want to integrate one specific agent elsewhere for a more focused workflow. \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/persistence/loading-agent-state.mdx b/docs/content/docs/crewai-flows/persistence/loading-agent-state.mdx new file mode 100644 index 0000000000..79df2eafa9 --- /dev/null +++ b/docs/content/docs/crewai-flows/persistence/loading-agent-state.mdx @@ -0,0 +1,40 @@ +--- +title: Loading Agent State +description: Learn how threadId is used to load previous agent states. +icon: "lucide/ChartBar" +--- + + + +### Setting the threadId + +When setting the `threadId` property in CopilotKit, i.e: + +```tsx + + + +``` + +CopilotKit will restore the complete state of the thread, including the messages, from the database. +(See [Message Persistence](/crewai-flows/persistence/message-persistence) for more details.) + +### Loading Agent State + +This means that the state of any agent will also be restored. For example: + +```tsx +const { state } = useCoAgent({name: "research_agent"}); + +// state will now be the state of research_agent in the thread id given above +``` + +### Learn More + +To learn more about persistence and state in CopilotKit, see: + +- [Reading agent state](/crewai-flows/shared-state/in-app-agent-read) +- [Writing agent state](/crewai-flows/shared-state/in-app-agent-write) +- [Loading Message History](/crewai-flows/persistence/loading-message-history) + + diff --git a/docs/content/docs/crewai-flows/persistence/loading-message-history.mdx b/docs/content/docs/crewai-flows/persistence/loading-message-history.mdx new file mode 100644 index 0000000000..5e7e98a672 --- /dev/null +++ b/docs/content/docs/crewai-flows/persistence/loading-message-history.mdx @@ -0,0 +1,69 @@ +--- +title: Threads +description: Learn how to load chat messages and threads within the CopilotKit framework. +icon: "lucide/MessagesSquare" +--- + + + +CrewAI Flows supports threads, a way to group messages together and ultimately maintain a continuous chat history. CopilotKit +provides a few different ways to interact with this concept. + +This guide assumes you have already gone through the [quickstart](/quickstart) guide. + +## Loading an Existing Thread + +To load an existing thread in CopilotKit, you can simply set the `threadId` property on `` like so. + +```tsx +import { CopilotKit } from "@copilotkit/react-core"; + + // [!code highlight] + + +``` + +## Dynamically Switching Threads + +You can also make the `threadId` dynamic. Once it is set, CopilotKit will load the previous messages for that thread. + +```tsx +import { useState } from "react"; +import { CopilotKit } from "@copilotkit/react-core"; + +const Page = () => { + const [threadId, setThreadId] = useState("af2fa5a4-36bd-4e02-9b55-2580ab584f89"); // [!code highlight] + return ( + // [!code highlight] + // [!code highlight] + + ) +} + +const YourApp = () => { + return ( + + ) +} +``` + +## Using setThreadId + +CopilotKit will also return the current `threadId` and a `setThreadId` function from the `useCopilotContext` hook. You can use `setThreadId` to change the `threadId`. + +```tsx +import { useCopilotContext } from "@copilotkit/react-core"; + +const ChangeThreadButton = () => { + const { threadId, setThreadId } = useCopilotContext(); // [!code highlight] + return ( + + ) +} +``` + + \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/persistence/message-persistence.mdx b/docs/content/docs/crewai-flows/persistence/message-persistence.mdx new file mode 100644 index 0000000000..7676801029 --- /dev/null +++ b/docs/content/docs/crewai-flows/persistence/message-persistence.mdx @@ -0,0 +1,34 @@ +--- +title: "Message Persistence" +icon: "lucide/Database" +--- + + + + + To learn about how to load previous messages and agent states, check out the [Loading Message History](/crewai-flows/persistence/loading-message-history) and [Loading Agent State](/crewai-flows/persistence/loading-agent-state) pages. + + +To persist CrewAI Flow messages to a database, you can use the `@persist` decorator. + +```python +from crewai.flow.flow import Flow, start, listen, persist + +@persist # Using SQLiteFlowPersistence by default +class MyFlow(Flow[MyState]): + @start() + def initialize_flow(self): + # This method will automatically have its state persisted + self.state.counter = 1 + print("Initialized flow. State ID:", self.state.id) + + @listen(initialize_flow) + def next_step(self): + # The state (including self.state.id) is automatically reloaded + self.state.counter += 1 + print("Flow state is persisted. Counter:", self.state.counter) +``` + + Read more about persistence in the [CrewAI Flows documentation](https://docs.crewai.com/concepts/flows#class-level-persistence). + + \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/persistence/meta.json b/docs/content/docs/crewai-flows/persistence/meta.json new file mode 100644 index 0000000000..5c59b29b46 --- /dev/null +++ b/docs/content/docs/crewai-flows/persistence/meta.json @@ -0,0 +1,4 @@ +{ + "title": "Persistence", + "icon": "lucide/Database" +} \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/quickstart/crewai.mdx b/docs/content/docs/crewai-flows/quickstart/crewai.mdx new file mode 100644 index 0000000000..fda7126e64 --- /dev/null +++ b/docs/content/docs/crewai-flows/quickstart/crewai.mdx @@ -0,0 +1,349 @@ +--- +title: Quickstart CrewAI Flows +description: Turn your CrewAI Flows into an agent-native application in 10 minutes. +icon: "custom/crewai" +--- + +import { + TailoredContent, + TailoredContentOption, +} from "@/components/react/tailored-content.tsx"; +import { CoAgentsEnterpriseCTA } from "@/components/react/coagents/coagents-enterprise-cta.tsx"; +import { CoAgentsDiagram } from "@/components/react/coagents/coagents-diagram.tsx"; +import { FaPython, FaJs, FaCloud } from "react-icons/fa"; +import SelfHostingCopilotRuntimeCreateEndpoint from "@/snippets/self-hosting-copilot-runtime-create-endpoint.mdx"; +import CopilotCloudConfigureRemoteEndpointLangGraph from "@/snippets/copilot-cloud-configure-remote-endpoint-langgraph.mdx"; +import CopilotKitCloudCopilotKitProvider from "@/snippets/copilot-cloud-configure-copilotkit-provider.mdx"; +import LangGraphPlatformDeploymentTabs from "@/snippets/langgraph-platform-deployment-tabs.mdx"; +import { Accordions, Accordion } from "fumadocs-ui/components/accordion"; +import FindYourCopilotRuntime from "@/snippets/find-your-copilot-runtime.mdx"; +import CloudCopilotKitProvider from "@/snippets/coagents/cloud-configure-copilotkit-provider.mdx"; +import SelfHostingCopilotRuntimeConfigureCopilotKitProvider from "@/snippets/coagents/self-host-configure-copilotkit-provider.mdx"; +import SelfHostingCopilotRuntimeLangGraphEndpoint from "@/snippets/self-hosting-copilot-runtime-langgraph-endpoint.mdx"; +import SelfHostingCopilotRuntimeStarter from "@/snippets/self-hosting-copilot-runtime-starter.mdx"; +import SelfHostingRemoteEndpoints from "@/snippets/self-hosting-remote-endpoints.mdx"; +import { UserIcon, PaintbrushIcon, WrenchIcon, RepeatIcon, ServerIcon } from "lucide-react"; +import { SiCrewai } from "@icons-pack/react-simple-icons"; +import CopilotUI from "@/snippets/copilot-ui.mdx"; + + + + \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/quickstart/meta.json b/docs/content/docs/crewai-flows/quickstart/meta.json new file mode 100644 index 0000000000..f82abd6328 --- /dev/null +++ b/docs/content/docs/crewai-flows/quickstart/meta.json @@ -0,0 +1,5 @@ +{ + "title": "Quickstart", + "icon": "lucide/Play" + } + \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/shared-state/in-app-agent-read.mdx b/docs/content/docs/crewai-flows/shared-state/in-app-agent-read.mdx new file mode 100644 index 0000000000..3ea1d1ca70 --- /dev/null +++ b/docs/content/docs/crewai-flows/shared-state/in-app-agent-read.mdx @@ -0,0 +1,137 @@ +--- +title: Reading agent state +icon: "lucide/ArrowLeft" +description: Read the realtime agent state in your native application. +--- +import { ImageZoom } from 'fumadocs-ui/components/image-zoom'; + + + + + + + + + Pictured above is the [coagent starter](https://github.com/copilotkit/copilotkit/tree/main/examples/coagent-starter) with + the [implementation](#implementation) section applied! + + +## What is this? + +You can easily use the realtime agent state not only in the chat UI, but also in the native application UX. + +## When should I use this? + +You can use this when you want to provide the user with feedback about what your agent's state. As your agent's +state update you can reflect these updates natively in your application. + +## Implementation + + + + ### Run and Connect Your Agent to CopilotKit + + You'll need to run your agent and connect it to CopilotKit before proceeding. If you haven't done so already, + you can follow the instructions in the [Getting Started](/getting-started) guide. + + If you don't already have an agent, you can use the [coagent starter](https://github.com/copilotkit/copilotkit/tree/main/examples/coagent-starter) as a starting point + as this guide uses it as a starting point. + + + ### Define the Agent State + CrewAI Flows are stateful. As you transition through the flow, that state is updated and available to the next function. For this example, + let's assume that our agent state looks something like this. + + + + ```python title="agent-py/sample_agent/agent.py" + from copilotkit.crewai import CopilotKitState + from typing import Literal + + class AgentState(CopilotKitState): + language: Literal["english", "spanish"] = "english" + ``` + + + + + ### Use the `useCoAgent` Hook + With your agent connected and running all that is left is to call the [useCoAgent](/reference/hooks/useCoAgent) hook, pass the agent's name, and + optionally provide an initial state. + + ```tsx title="ui/app/page.tsx" + import { useCoAgent } from "@copilotkit/react-core"; // [!code highlight] + + // Define the agent state type, should match the actual state of your agent + type AgentState = { + language: "english" | "spanish"; + } + + function YourMainContent() { + const { state } = useCoAgent({ // [!code highlight:4] + name: "sample_agent", + initialState: { language: "spanish" } // optionally provide an initial state + }); + + // ... + + return ( + // style excluded for brevity +
+

Your main content

+

Language: {state.language}

// [!code highlight] +
+ ); + } + ``` + + The `state` in `useCoAgent` is reactive and will automatically update when the agent's state changes. + +
+ + ### Give it a try! + As the agent state updates, your `state` variable will automatically update with it! In this case, you'll see the + language set to "spanish" as that's the initial state we set. + +
+ +## Rendering agent state in the chat + +You can also render the agent's state in the chat UI. This is useful for informing the user about the agent's state in a +more in-context way. To do this, you can use the [useCoAgentStateRender](/reference/hooks/useCoAgentStateRender) hook. + +```tsx title="ui/app/page.tsx" +import { useCoAgentStateRender } from "@copilotkit/react-core"; // [!code highlight] + +// Define the agent state type, should match the actual state of your agent +type AgentState = { + language: "english" | "spanish"; +} + +function YourMainContent() { + // ... + // [!code highlight:8] + useCoAgentStateRender({ + name: "sample_agent", + render: ({ state }) => { + if (!state.language) return null; + return
Language: {state.language}
; + }, + }); + // ... +} +``` + + + The `state` in `useCoAgentStateRender` is reactive and will automatically update when the agent's state changes. + + +## Intermediately Stream and Render Agent State +By default, the CrewAI Flow agent state will only update *between* CrewAI Flow node transitions -- +which means state updates will be discontinuous and delayed. + +You likely want to render the agent state as it updates **continuously.** + +See **[emit intermediate state](/crewai-flows/shared-state/predictive-state-updates).** + +
\ No newline at end of file diff --git a/docs/content/docs/crewai-flows/shared-state/in-app-agent-write.mdx b/docs/content/docs/crewai-flows/shared-state/in-app-agent-write.mdx new file mode 100644 index 0000000000..3b88f9ad79 --- /dev/null +++ b/docs/content/docs/crewai-flows/shared-state/in-app-agent-write.mdx @@ -0,0 +1,148 @@ +--- +title: Writing agent state +icon: "lucide/ArrowRight" +description: Write to agent's state from your application. +--- + + + + diff --git a/docs/content/docs/crewai-flows/shared-state/index.mdx b/docs/content/docs/crewai-flows/shared-state/index.mdx new file mode 100644 index 0000000000..b650c85fbf --- /dev/null +++ b/docs/content/docs/crewai-flows/shared-state/index.mdx @@ -0,0 +1,42 @@ +--- +title: Shared State +description: Create a two-way connection between your UI and agent state. +icon: "lucide/Repeat" +--- +import { ImageZoom } from "fumadocs-ui/components/image-zoom"; + + + + + + + This video demonstrates the [Research Canvas](/crewai-flows/examples/research-canvas) utilizing shared state. + + + +## What is shared state? + +CoAgents maintain a shared state that seamlessly connects your UI with the agent's execution. This shared state system allows you to: +- Display the agent's current progress and intermediate results +- Update the agent's state through UI interactions +- React to state changes in real-time across your application + + + Agentic Copilot State Diagram + + +The foundation of this system is built on CrewAI's stateful architecture. + +## When should I use this? +State streaming is perfect when you want to facilitate collaboration between your agent and the user. Any state that your CrewAI Flow +persists will be automatically shared by the UI. Similarly, any state that the user updates in the UI will be automatically reflected + +This allows for a consistent experience where both the agent and the user are on the same page. + + \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/shared-state/meta.json b/docs/content/docs/crewai-flows/shared-state/meta.json new file mode 100644 index 0000000000..139322c59b --- /dev/null +++ b/docs/content/docs/crewai-flows/shared-state/meta.json @@ -0,0 +1,7 @@ +{ + "pages": [ + "in-app-agent-read", + "in-app-agent-write", + "predictive-state-updates" + ] +} \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/shared-state/predictive-state-updates.mdx b/docs/content/docs/crewai-flows/shared-state/predictive-state-updates.mdx new file mode 100644 index 0000000000..eb9e6a2468 --- /dev/null +++ b/docs/content/docs/crewai-flows/shared-state/predictive-state-updates.mdx @@ -0,0 +1,239 @@ +--- +title: "Predictive state updates" +icon: "lucide/Podcast" +description: Stream in-progress agent state updates to the frontend. +--- +import { + TailoredContent, + TailoredContentOption, +} from "@/components/react/tailored-content.tsx"; +import { CoAgentsEnterpriseCTA } from "@/components/react/coagents/coagents-enterprise-cta.tsx"; +import InstallSDKSnippet from "@/snippets/install-sdk.mdx" +import { FaWrench } from "react-icons/fa"; +import { FaArrowUp } from "react-icons/fa"; + + + + \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/troubleshooting/common-issues.mdx b/docs/content/docs/crewai-flows/troubleshooting/common-issues.mdx new file mode 100644 index 0000000000..8f5765d7f3 --- /dev/null +++ b/docs/content/docs/crewai-flows/troubleshooting/common-issues.mdx @@ -0,0 +1,204 @@ +--- +title: Common Issues +description: Common issues you may encounter when using CoAgents. +--- + +import { Accordions, Accordion } from "fumadocs-ui/components/accordion"; + +Welcome to the CoAgents Troubleshooting Guide! If you're having trouble getting tool calls to work, you've come to the right place. + + + Have an issue not listed here? Open a ticket on [GitHub](https://github.com/CopilotKit/CopilotKit/issues) or reach out on [Discord](https://discord.com/invite/6dffbvGU3D) + and we'll be happy to help. + + We also highly encourage any open source contributors that want to add their own troubleshooting issues to [Github as a pull request](https://github.com/CopilotKit/CopilotKit/blob/main/CONTRIBUTING.md). + + + +## My tool calls are not being streamed + +This could be due to a few different reasons. + +First, we strongly recommend checking out our [Human In the Loop](/coagents/human-in-the-loop) guide to follow a more in depth example of how to stream tool calls +in your LangGraph agents. You can also check out our [travel tutorial](/coagents/tutorials/ai-travel-app/step-6-human-in-the-loop) which talks about how to stream +tool calls in a more complex example. + +If you have already done that, you can check the following: + + + + In your LangGraph agent, you have must specify which tool calls will be emitted to the CopilotKit runtime. By default, + only streamed messages are emitted. You can fix this by adding the following to the node making the tool call. + + ```python + from copilotkit.langgraph import copilotkit_customize_config, copilotkit_emit_message + from langgraph_core.runnables import RunnableConfig + from langchain.tools import tool + + @tool + def say_hello_to(name: str) -> str: + return f"Hello, {name}!" + + async def my_node(state: State, config: RunnableConfig) -> State: + # ... + config = copilotkit_customize_config(config, emit_tool_calls=["say_hello_to"]) # [code highlight] + # ... + return state + ``` + + +

+ When you invoke your LangGraph agent, you can invoke it synchronously or asynchronously. If you invoke it synchronously, + the tool calls will not be streamed progressively, only the final result will be streamed. If you invoke it asynchronously, + the tool calls will be streamed progressively. + + ```python + config = copilotkit_customize_config(config, emit_tool_calls=["say_hello_to"]) + response = await llm_with_tools.ainvoke( + [ SystemMessage(content=system_message), *state["messages"] ], + config=config + ) + ``` +

+
+ +
+ +## Error: `'AzureOpenAI' object has no attribute 'bind_tools'` + +This error is typically due to the use of an incorrect import from LangGraph. Instead of importing `AzureOpenAI` import `AzureChatOpenAI` and your +issue will be resolved. + +```python +from langchain_openai import AzureOpenAI # [!code --] +from langchain_openai import AzureChatOpenAI # [!code ++] +``` + +## I am getting "agent not found" error + +If you're seeing this error, it means CopilotKit couldn't find the LangGraph agent you're trying to use. Here's how to fix it: + + + + If you're using [agent lock mode](/coagents/multi-agent-flows), + check that the agent defined in `langgraph.json` matches what's defined in the CopilotKit provider: + + ```json title="langgraph.json" + { + "python_version": "3.12", + "dockerfile_lines": [], + "dependencies": ["."], + "graphs": { + "my_agent": "./src/agent.py:graph"// In this case, "my_agent" is the agent you're using // [!code highlight] + }, + "env": ".env" + } + ``` + + ```tsx title="layout.tsx" + // [!code highlight] + {/* Your application components */} + + ``` + + Common issues: + - Typos in agent names + - Case sensitivity mismatches + - Missing entries in `langgraph.json` + + + When using LangGraph Platform endpoint, make sure your agents are properly specified and are following the definition in your `langgraph.json`: + + ```json title="langgraph.json" + { + "python_version": "3.12", + "dockerfile_lines": [], + "dependencies": ["."], + "graphs": { + "my_agent": "./src/agent.py:graph"// In this case, "my_agent" is the agent you're using // [!code highlight] + }, + "env": ".env" + } + ``` + + ```typescript title="/copilotkit/api/route.ts" + langGraphPlatformEndpoint({ + deploymentUrl, + langsmithApiKey, + agents: [ + { + name: "my_agent", + description: "A helpful agent", + }, + ], + }) + ``` + + + Make sure the that the agent defined in `langgraph.json` matches what you use n `useCoAgent` hook: + + ```json title="langgraph.json" + { + "python_version": "3.12", + "dockerfile_lines": [], + "dependencies": ["."], + "graphs": { + "my_agent": "./src/agent.py:graph"// In this case, "my_agent" is the agent you're using // [!code highlight] + }, + "env": ".env" + } + ``` + + ```tsx title="MyComponent.tsx" + // Your React component + useCoAgent({ + name: "my_agent", // [!code focus] This must match exactly + }); + ``` + + + Make sure the that the agent defined in `langgraph.json` matches what you use n `useCoAgent` hook: + + ```json title="langgraph.json" + { + "python_version": "3.12", + "dockerfile_lines": [], + "dependencies": ["."], + "graphs": { + "my_agent": "./src/agent.py:graph"// In this case, "my_agent" is the agent you're using // [!code highlight] + }, + "env": ".env" + } + ``` + + ```tsx title="MyComponent.tsx" + // Your React component + useCoAgentStateRender({ + name: "my_agent", // [!code focus] This must match exactly + }); + ``` + + + + +## Connection issues with tunnel creation + +If you notice the tunnel creation process spinning indefinitely, your router or ISP might be blocking the connection to CopilotKit's tunnel service. + + + + To verify connectivity to the tunnel service, try these commands: + + ```bash + ping tunnels.devcopilotkit.com + curl -I https://tunnels.devcopilotkit.com + telnet tunnels.devcopilotkit.com 443 + ``` + + If these fail, your router's security features or ISP might be blocking the connection. Common solutions: + - Check router security settings + - Consider checking with your ISP about any connection restrictions + - Try using a mobile hotspot + + + diff --git a/docs/content/docs/crewai-flows/troubleshooting/migrate-from-v0.2-to-v0.3.mdx b/docs/content/docs/crewai-flows/troubleshooting/migrate-from-v0.2-to-v0.3.mdx new file mode 100644 index 0000000000..b84b51611d --- /dev/null +++ b/docs/content/docs/crewai-flows/troubleshooting/migrate-from-v0.2-to-v0.3.mdx @@ -0,0 +1,32 @@ +--- +title: Migrate from v0.2 to v0.3 +description: How to migrate from v0.2 to v0.3. +--- + +## What's new in v0.3? + +Starting with `v0.3`, we changed how messages are synced between the agent (LangGraph) and CopilotKit. Essentially, both will now share exactly the same message history. + +This means that you need to return the messages you want to appear in CopilotKit chat from your LangGraph nodes, for example: + +```python +def my_node(state: State, config: RunnableConfig) -> State: + response = # ... llm call ... + return { + "messages": response, + } +``` + +All tool messages are now emitted by default, so you don't need to manually call `copilotkit_customize_config` to configure tool call emissions. + + + + + +## How do I migrate? + +1. Make sure to return any messages (tool calls or text messages) you want to be part of the message history from your LangGraph nodes. + +2. Optionally, remove manual `copilotkit_customize_config` calls when you want to emit tool calls. + +3. If you want to hide tool calls or messages from the chat, use `copilotkit_customize_config` and set `emit_tool_calls` or `emit_messages` to `False`. Make sure to not return these messages in your nodes so they don't become part of the message history. diff --git a/docs/content/docs/crewai-flows/tutorials/ai-travel-app/index.mdx b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/index.mdx new file mode 100644 index 0000000000..355e9a4232 --- /dev/null +++ b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/index.mdx @@ -0,0 +1,56 @@ +--- +title: Overview +icon: "lucide/Plane" +--- +import { YouTubeVideo } from "@/components/react/youtube-video"; +import { FaGithub } from "react-icons/fa"; +import { PiMonitor } from "react-icons/pi"; +import { Button } from "@/components/ui/button"; +import Link from "next/link"; + +# AI Travel Agentic Copilot Tutorial + +
+
**Time to complete:** 20 minutes
+
**Difficulty:** Medium
+
+ +
+ + + +## What you'll learn + +In this tutorial, you will take a simple travel application and supercharge it with an agentic copilot. You will learn: + +- 💡 What an agentic copilot is and how it can be used to enhance your application +- 💡 How to use `useCoAgent` to allow for shared state between your UI and agent execution +- 💡 How to use `useCoAgentStateRender` to implement human-in-the-loop workflows +- 💡 How to render intermediate states of your agent's execution + + + + + +
+ + + +
+ + +In the next step, we'll checkout the repo, install dependencies, and start the project locally. \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/tutorials/ai-travel-app/meta.json b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/meta.json new file mode 100644 index 0000000000..0c0d54cebe --- /dev/null +++ b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/meta.json @@ -0,0 +1,12 @@ +{ + "title": "Tutorial: AI Travel App", + "pages": [ + "step-1-checkout-repo", + "step-2-langgraph-agent", + "step-3-setup-copilotkit", + "step-4-integrate-the-agent", + "step-5-stream-progress", + "step-6-human-in-the-loop", + "next-steps" + ] +} \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/tutorials/ai-travel-app/next-steps.mdx b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/next-steps.mdx new file mode 100644 index 0000000000..17c286d9b0 --- /dev/null +++ b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/next-steps.mdx @@ -0,0 +1,25 @@ +--- +title: "Next Steps" +--- + +This is the end of the tutorial. You can now start building your own CoAgents into your appications! + +## Source code + +You can find the source code and interactive sandboxes here: +- [Start app](https://github.com/CopilotKit/CopilotKit/tree/coagents-travel-tutorial-start/examples/coagents-travel) +- [Final app](https://github.com/CopilotKit/CopilotKit/tree/main/examples/coagents-travel) + +## What's next? + +For next steps, here are some ideas: + +- Add suggestions to your copilot, using the [`useCopilotChatSuggestions`](/reference/hooks/useCopilotChatSuggestions) hook. +- Implement a custom UI for your agent, using the [`useCopilotChat`](/reference/hooks/useCopilotChat) hook. +- Add human editing of tool call arguments to the human in the loop implementation. + +We have more tutorials coming soon. + +## Need help? + +If you have any questions, feel free to reach out to us on [Discord](https://discord.gg/6dffbvGU3D). diff --git a/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-1-checkout-repo.mdx b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-1-checkout-repo.mdx new file mode 100644 index 0000000000..c073a53c7d --- /dev/null +++ b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-1-checkout-repo.mdx @@ -0,0 +1,46 @@ +--- +title: "Step 1: Checkout the repo" +--- + + + +### Checkout the starting branch +We'll be working with the CopilotKit repository, specifically using a branch called `coagents-travel-tutorial-start`. This branch contains the starting code for our travel app tutorial. + +```shell +git clone -b coagents-travel-tutorial-start https://github.com/CopilotKit/CopilotKit.git +cd CopilotKit +``` + +The tutorial code is located in the `examples/coagents-travel` directory, which contains: +- `ui/`: A NextJS application where we'll integrate our LangGraph agent +- `agent/`: A Python-based LangGraph agent that we'll be enhancing + +Go ahead and navigate to the example directory: + +```shell +cd examples/coagents-travel +``` + + +### Install dependencies +First, let's set up the NextJS application. Navigate to the `ui` directory and install the dependencies: + +```shell +cd ui +pnpm install +``` + + +### Start the project +Launch the development server: + +```shell +pnpm run dev +``` + +Visit [http://localhost:3000](http://localhost:3000) to see the travel app in action. Take some time to explore the interface and familiarize yourself with its features. + + + +Next, let's understand the LangGraph agent and how it works. \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-2-langgraph-agent.mdx b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-2-langgraph-agent.mdx new file mode 100644 index 0000000000..8469c622bd --- /dev/null +++ b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-2-langgraph-agent.mdx @@ -0,0 +1,124 @@ +--- +title: "Step 2: LangGraph Agent" +--- + +Before we start integrating the LangGraph agent, let's understand how it works. + +For the sake of this tutorial we won't be building the LangGraph together from scratch. +Instead, we'll be using the LangGraph constructed in the `agent/` directory. + + +If you're interested in a step-by-step guide for building a LangGraph agent, you can checkout the +[LangGraph quickstart guide](https://langchain-ai.github.io/langgraph/tutorials/introduction/). + + +Let's walk through the LangGraph agent to understand how it works before we integrate it into the application. + + + +### Install LangGraph Studio + +LangGraph Studio is a tool for visualizing and debugging LangGraph workflows. It is not required for using CopilotKit but it is highly recommended +for understanding how LangGraph works. + +To install LangGraph Studio, checkout the [setup guide](https://studio.langchain.com/). + + + +### Retreive API keys + +For this application, we'll need two API keys: +- OpenAI API key: You can get an API key from the OpenAI console [here](https://platform.openai.com/api-keys). +- Google Maps API key: This can be retrieved from the Google Cloud Console [here](https://developers.google.com/maps/documentation/places/web-service/get-api-key#creating-api-keys). + + + +### Setup the .env file + +In a new terminal, navigate to the agent directory. + +```shell +cd examples/coagents-travel/agent +``` + +Now create a .env file there. + +```shell +touch .env +``` + +With that created, we'll want to add your OPENAI_API_KEY and GOOGLE_MAPS_API_KEY to the file. + +```txt title=".env" +OPENAI_API_KEY= +GOOGLE_MAPS_API_KEY= +``` + + + +### Visualizing the LangGraph Agent + +With LangGraph Studio installed, you can run and visualize the LangGraph agent by opening the `examples/coagents-travel/agent/` directory in the studio. + +The agent will take some time to load as things get setup but once finished it will look something like this. + +![LangGraph Studio](/images/coagents/tutorials/ai-travel-app/lgs-overview.png) + + + + + +### Understanding the LangGraph Agent + +As we're building this agent into an agentic experience, we'll want to understand how it works. The key concepts at play here are: + +- **State**: The state is the data that the agent is using to make and communicate its decisions. You can see all of the state variables in the bottom left of the screen. +- **Nodes**: Nodes are the building blocks of a LangGraph agent. They are the steps that the agent will take to complete a task. In this case, we have nodes for **chatting**, **searching** and **performing operations** on trips. +- **Edges**: Edges are the arrows that connect nodes together. They define the logic for how the agent will move from one node to the next. They are defined in code and conditional logic is handled with a `route` function. +- **Interrupts**: Interrupts are a way to allow for a user to work along side the agent and review its decisions. In this case, we have an **interrupt** before the **trips_node** which blocks the agent from proceeding until the user has approved the Agent's actions. + + + +### Testing the LangGraph Agent + +You can submit a message to the agent by adding a message to the `messages` state variable and then clicking "Submit". + +You'll see the agent respond in the chat and direct appropriately through the various nodes. In this case, you should notice that the +agent calls the `search_node` and, once it has received a response, will add a new trip based on its findings to the state via the +`trips_node`. + + + +### Understanding breakpoints +A very important concept for agentic copilots is [human-in-the-loop](/coagents/human-in-the-loop). This is the idea that the agent should be able to pause and wait for a human to review and approve its decisions. +LangGraph allows for this by using **breakpoints**. Let's take a look at what that looks like in action. + +First, click on the `trips_node` and select the `interrupt_after` option. + +Now, try to have the agent create a new trip again. You'll notice that it now asks for approval before proceeding via a `continue` button. + +![LangGraph Studio Progress](/images/coagents/tutorials/ai-travel-app/lgs-progress.png) + +Make sure to remove the `interrupt_after` option before proceeding, this will break things later if you don't. + + + +### Leave LangGraph Studio running + +In order to create an agentic copilot, you'll need to have your LangGraph agent running somewhere. In our case, LangGraph studio is +running this locally for us. We can see this by looking at the URL at the bottom left of the application. + +![LangGraph Studio URL](/images/coagents/tutorials/ai-travel-app/lgs-url.png) + +Later in this tutorial, we'll be using this URL to connect CopilotKit to the LangGraph agent. + + + +Here's what we did: +- Installed LangGraph Studio +- Setup the .env file +- Visualized the LangGraph agent +- Tested the LangGraph agent +- Left LangGraph Studio running + +In the next step, we'll be integrating the LangGraph agent into the application as an agentic copilot. \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-3-setup-copilotkit.mdx b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-3-setup-copilotkit.mdx new file mode 100644 index 0000000000..38c4964429 --- /dev/null +++ b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-3-setup-copilotkit.mdx @@ -0,0 +1,241 @@ +--- +title: "Step 2: Setup CopilotKit" +--- +import SelfHostingCopilotRuntimeCreateEndpoint from "@/snippets/self-hosting-copilot-runtime-create-endpoint.mdx"; +import { TailoredContent, TailoredContentOption } from "@/components/react/tailored-content.tsx"; +import { GoServer } from "react-icons/go"; +import { FaCloud } from "react-icons/fa"; + +Now that we have the application and agent running, we're ready to connect both via CopilotKit. For this tutorial, we will install the following dependencies: + +- `@copilotkit/react-core`: The core library for CopilotKit, which contains the CopilotKit provider and useful hooks. +- `@copilotkit/react-ui`: The UI library for CopilotKit, which contains the CopilotKit UI components such as the sidebar, chat popup, textarea and more. + +## Install Dependencies + +Navigate back to the `ui` directory and install the CopilotKit dependencies: + +```shell +pnpm add @copilotkit/react-core @copilotkit/react-ui +``` + +## Setup CopilotKit + +There are two ways of setting up CopilotKit, either by using Copilot Cloud or by self-hosting. Self-hosting will give you more control +over CopilotKit's runtime (our interface to the LLM) but will also require you to manage the extra complexity of running a server. Copilot Cloud +on the other hand is a fully managed service that you can get started with in just a few clicks. + +For this tutorial, you can select either option. + + +} + description="I want get started as fast as possible by using Copilot Cloud." +> +We're using CopiloKit cloud as a hosted version of the CopilotKit runtime. The runtime serves as an interface between the application and the LLM +(agentic or not). Copilot Cloud will manage all of the complexity for us but in return we need to provide a valid API key. + + +### Create an account on Copilot Cloud + +First, you'll need to create an account for Copilot Cloud [here](https://cloud.copilotkit.ai/sign-in). You can +use whatever authentication method you'd like. + + + +### Get a Copilot Cloud API Key + +Once logged in, you'll see some steps guiding you to getting our Copilot Cloud public API key. For this, you'll need an OpenAI API key since it's the only +provider currently supported (more providers coming soon!). + +Set your OpenAI API key, click the green checkmark and you'll see your API key created right below the input. + + +CopilotCloud API Key + + + + +### Setting up the environment variables + +First, create a `.env` file in the `ui` directory. + +```shell +touch ui/.env +``` + +Then, add your Copilot Cloud API key to the file like so: + +```txt title="ui/.env" +NEXT_PUBLIC_CPK_PUBLIC_API_KEY=... +``` + + + +### Configure the CopilotKit Provider + +Now we're ready to configure the CopilotKit provider in our application. + +```tsx title="ui/app/page.tsx" showLineNumbers +"use client"; + +import { CopilotKit } from "@copilotkit/react-core"; // [!code ++] + +export default function Home() { + // [!code ++:5] + return ( + + + +
+ +
+
+
+
// [!code ++] + ); +} +``` + + +### CopilotKit Chat Popup + +We provide several plug-and-play components for you to interact with your copilot. Some of these are ``, ``, and ``. You can of course use CopilotKit in headless mode and provide your own fully custom UI via [`useCopilotChat`](/reference/hooks/useCopilotChat). + +In this tutorial, we'll use the `` component to display the chat sidebar. + +```tsx title="ui/app/page.tsx" showLineNumbers {6-7,15} +"use client"; + +import { TasksList } from "@/components/TasksList"; +import { TasksProvider } from "@/lib/hooks/use-tasks"; +import { CopilotKit } from "@copilotkit/react-core"; +import { CopilotSidebar } from "@copilotkit/react-ui"; // [!code ++] +import "@copilotkit/react-ui/styles.css"; // [!code ++] + +export default function Home() { + return ( + + /* [!code ++:9] */ + + + +
+ +
+
+
+
+ ); +} +``` + +And we're done! Here's what we did: + +- We setup our Copilot cloud account and got an API key. +- We configured the CopilotKit provider in our application to use our API key. +- We added the CopilotSidebar to our application. +
+ +
+
+
+} + description="I want to learn how to self-host CopilotKit and will own the extra complexity." +> + + +### Set up Copilot Runtime Endpoint + + + + +### Configure the CopilotKit Provider +```tsx title="app/page.tsx" showLineNumbers +"use client"; + +import { TasksList } from "@/components/TasksList"; +import { TasksProvider } from "@/lib/hooks/use-tasks"; +import { CopilotKit } from "@copilotkit/react-core"; // [!code ++] + +export default function Home() { + return ( + // [!code ++] + + + + // [!code ++] + ); +} +``` + + + +### CopilotKit Chat Popup + +We provide several plug-and-play components for you to interact with your copilot. Some of these are ``, ``, and ``. You can of course use CopilotKit in headless mode and provide your own fully custom UI via [`useCopilotChat`](/reference/hooks/useCopilotChat). + +In this tutorial, we'll use the `` component to display the chat sidebar. + +```tsx title="ui/app/page.tsx" showLineNumbers {6-7,15} +"use client"; + +import { TasksList } from "@/components/TasksList"; +import { TasksProvider } from "@/lib/hooks/use-tasks"; +import { CopilotKit } from "@copilotkit/react-core"; +import { CopilotSidebar } from "@copilotkit/react-ui"; // [!code ++] +import "@copilotkit/react-ui/styles.css"; // [!code ++] + +export default function Home() { + return ( + + /* [!code ++:9] */ + + + +
+ +
+
+
+
+ ); +} +``` + +Here's what we did: + +- We imported the `` component from `@copilotkit/react-ui`. +- We wrapped the page with the `` provider. +- We imported the built-in styles from `@copilotkit/react-ui`. +
+
+ +Now, head back to the app and you'll find a chat sidebar on the left side of the page. At this point, you can start interacting with your copilot! 🎉 + +This is very exciting! In the next step we'll be making this copilot agentic through the use of LangGraph. \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-4-integrate-the-agent.mdx b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-4-integrate-the-agent.mdx new file mode 100644 index 0000000000..c59ae135df --- /dev/null +++ b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-4-integrate-the-agent.mdx @@ -0,0 +1,200 @@ +--- +title: "Step 4: Integrate the Agent" +--- +At this point, we have a LangGraph agent running in LangGraph Studioand have our own non-agentic copilot that we can interact with. Now, let's +combine the two together to make an agentic copilot! + +## The React State + +Let's quickly review how the app's state works. Open up the [`lib/hooks/use-trips.tsx`](https://github.com/CopilotKit/CopilotKit/blob/coagents-travel-tutorial-start/examples/coagents-travel/ui/lib/hooks/use-trips.tsx) file. + +At a glance, we can see that the file exposes a provider (`TripsProvider`), which defines a lot useful things. The main thing we care about is the `state` object which takes the shape of the `AgentState` type. This is consumable by a `useTrips` hook, which we use in the rest of the application (feel free to check out the `TripCard`, +`TripContent` and `TripSelect` components). + +This resembles the majority of React apps, where frontend state, either for a feature or the entire app, is managed by a context or state management library. + +## Integrate the Agent + +To integrate the agent into this state, we're going to need to setup a remote endpoint and then use the `useCoAgent` hook to connect the two. + + + +## Setup a remote endpoint + +Make sure you have the LangGraph Studio endpoint from the previous step! + + + +We're going to use the CopilotKit CLI to setup a tunnel between our locally running LangGraph agent and Copilot Cloud. You'll +need the port number of the LangGraph Studio endpoint we setup earlier. + + +It'll be on the bottom left of the LangGraph Studio interface like this. + + + LangGraph Studio Endpoint + + + + +To open a tunnel, run the following command. + +```bash +# replace with the port number of the LangGraph Studio endpoint +npx copilotkit@latest dev --port +``` + +It will guide you through the process of selecting a project and creating a tunnel. You should see output similar to the following. + +```bash +✔ Select a project Local (ID: ) +✅ LangGraph Platform endpoint detected +⠹ Creating tunnel... + +Tunnel Information: + +• Tunnel URL: https://.tunnels.devcopilotkit.com +• Endpoint Type: LangGraph Platform +• Project: projects/ + +Press Ctrl+C to stop the tunnel + +✔ 🚀 Local tunnel is live and linked to Copilot Cloud! +``` + + + + +In our previously setup `/api/copilotkit` route, we're going to add the following. + +```tsx title="ui/app/api/copilotkit/route.ts" +// ... + +import { langGraphPlatformEndpoint } from '@copilotkit/runtime'; // [!code ++] + +// ... + +const runtime = new CopilotRuntime();// [!code --] +// [!code ++:13] + const runtime = new CopilotRuntime({ + remoteEndpoints: [ + langGraphPlatformEndpoint({ + deploymentUrl: "http://localhost:", + langsmithApiKey: "your-langsmith-api-key", + agents: [{ + name: 'travel', + description: 'A travel assistant that can help with planning trips.' + }] + }), + ], +}); + +// ... +``` + + +The `deploymentUrl` is the URL from LangGraph Studio but it can also be a graph hosted in LangGraph Platform! + + + + +This allows CopilotKit to know where to send requests to when the agent is called. + + + +## Lock the agent + +By default, CopilotKit will intelligently route requests to the appropriate agent based on context. This allows +you to have multiple agents and actions and not have to worry about manually routing requests. + +In our case however, we only have a single agent and its ideal to lock all requests to that agent. We can do this +by updating the props of our `CopilotKit` provider. + + +Want to learn more about multi-agent routing? Checkout out the [multi-agent concept guide](/coagents/multi-agent-flows). + + +```tsx title="ui/app/page.tsx" +// ... + + {...} + +``` + +This will ensure that every request is sent to the `travel` agent. The `travel` name is defined in the [agents/langgraph.json](https://github.com/CopilotKit/CopilotKit/blob/main/examples/coagents-travel/agent/langgraph.json) +file. When we deploy our agent to Copilot Cloud this is automatically handled for us. When self-hosting, we need to specify the name of the agent in the `langGraphPlatformEndpoint` constructor. + + + +## The `useCoAgent` hook + +LangGraph agents are stateful, meaning that they can maintain their own state. We saw this earlier when we were using LangGraph Studio, in the bottom left. We +also have the application's state through React. + +Our current goal is to create a bidirectional connection between these two states. Luckily, the [`useCoAgent`](/reference/hooks/useCoAgent) hook makes this easy. + +```tsx title="ui/lib/hooks/use-trips.tsx" {3,8-11} +// ... +// [!code word:AgentState:1] +import { Trip, Place, AgentState, defaultTrips} from "@/lib/trips"; +import { useCoAgent } from "@copilotkit/react-core"; // [!code ++] + +export const TripsProvider = ({ children }: { children: ReactNode }) => { + // [!code --:5] + const [state, setState] = useState<{ trips: Trip[], selected_trip_id: string | null }>({ + trips: defaultTrips, + selected_trip_id: defaultTrips && defaultTrips[0] ? defaultTrips[0].id : null + }); + // [!code ++:9] + const { state, setState } = useCoAgent({ + name: "travel", + initialState: { + trips: defaultTrips, + selected_trip_id: defaultTrips[0].id, + }, + }); + + // ... +``` + + +The `useCoAgent` hook is generic. What this means is that we can specify a type for that represents the state of the LangGraph agent. +If you are going to specify a type, you should be very careful that the type has the same shape as the state of your LangGraph agent. + +It is not recommended, but you can ditch the type parameter and instead get an `any` type. + + +In this example, we use the `useCoAgent` hook to wire up the application's state to the LangGraph agent's state. +- For the generic type, we pass the `AgentState` type that was already defined for the application in `@/lib/types.ts`. +- For the `name` parameter, we pass the name of the graph as defined in `agent/langgraph.json`. +- For the `initialState` parameter, we pass the initial state of the LangGraph agent which is already defined in `@/lib/trips.ts`. + + + +## Try it out! + +Now, try it out! Ask the Copilot something about the state of your trips. For example: + +``` +What trips do I currently have? +``` + +The state is shared between the application and the agent, so you can edit a trip manually, ask the same question, +and the agent will know about it. + +``` +What trips do I have now? +``` + +In the same vein, you can ask the agent to update your trips and it will render in the UI. For example: + +``` +Add some hotels to my NYC trip +``` + +Its really that simple, you have now integrated a LangGraph agent into the application as an agentic copilot. In the following +steps, we'll be improving the user experience but the core agent is now accessible through the application's chat interface. + diff --git a/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-5-stream-progress.mdx b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-5-stream-progress.mdx new file mode 100644 index 0000000000..4026acfb18 --- /dev/null +++ b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-5-stream-progress.mdx @@ -0,0 +1,218 @@ +--- +title: "Step 5: Stream Progress" +--- + +Now that we have integrated the LangGraph agent into the application, we can start utilizing features that will enhance the +user agentic experience even further. For example, what if we could stream the progress of a search to the user? + +In this step, we'll be doing just that. To do so we'll be using the `copilotkit_emit_state` CopilotKit SDK function in the +`search_node` of our LangGraph agent. + +## Install the CopilotKit SDK + +CopilotKit comes ready with an SDK for building both Python and Typescript agents. In this case, the agent is written in Python +(manged with `poetry`), so we'll be installing the Python SDK. + + +Don't have poetry installed? [Install it here](https://python-poetry.org/docs/#installation). + + +```shell title="agent/" +poetry add copilotkit +``` + +Now we're ready to use the CopilotKit SDK in our agent! Since we're editing the `search_node` in agent, we'll be +editing the `search.py` file. + +## Manually emitting the agent's state + +With CoAgents, the LangGraph agent's state is only emitted when node change occurs (i.e, an edge is traversed). This means +that in-progress work is not emitted to the user by default. However, we can manually emit the state using the `copilotkit_emit_state` +function that we mentioned earlier. + + + +### Add the custom CopilotKit config to the `search_node` +First, we're going to add a custom copilotkit config to the `search_node` to describe what intermediate state +we'll be emitting. + +```python title="agent/travel/search.py" {3-5} +# ... +from copilotkit.langgraph import copilotkit_emit_state, copilotkit_customize_config # [!code ++] + +async def search_node(state: AgentState, config: RunnableConfig): + """ + The search node is responsible for searching the for places. + """ + ai_message = cast(AIMessage, state["messages"][-1]) + + # [!code ++:9] + config = copilotkit_customize_config( + config, + emit_intermediate_state=[{ + "state_key": "search_progress", + "tool": "search_for_places", + "tool_argument": "search_progress", + }], + ) + + # ... +``` + + +### Emit the intermediate state +Now we can call `copilotkit_emit_state` to emit the intermediate state wherever we want. In this case, we'll be emitting it +progress at the beginning of our search and as we receive results. + + +One piece of this that has already been setup for you is the `search_progress` state key. In order to emit progress, we add +an object to our state that we'll manually update with the results and progress of our search. Then we'll be calling `copilotkit_emit_state` +to manually emit that state. + + +```python title="agent/travel/search.py" +# ... +async def search_node(state: AgentState, config: RunnableConfig): + """ + The search node is responsible for searching the for places. + """ + ai_message = cast(AIMessage, state["messages"][-1]) + + config = copilotkit_customize_config( + config, + emit_intermediate_state=[{ + "state_key": "search_progress", + "tool": "search_for_places", + "tool_argument": "search_progress", + }], + ) + + # ^ Previous code + + state["search_progress"] = state.get("search_progress", []) + queries = ai_message.tool_calls[0]["args"]["queries"] + + for query in queries: + state["search_progress"].append({ + "query": query, + "results": [], + "done": False + }) + + await copilotkit_emit_state(config, state) # [!code ++] + + # ... +``` + +Now the state of our search will be emitted through the `search_progress` state key to CopilotKit! However, we still need to update this +state as we receive results from our search. + +```python title="agent/travel/search.py" +# ... +async def search_node(state: AgentState, config: RunnableConfig): + """ + The search node is responsible for searching the for places. + """ + ai_message = cast(AIMessage, state["messages"][-1]) + + config = copilotkit_customize_config( + config, + emit_intermediate_state=[{ + "state_key": "search_progress", + "tool": "search_for_places", + "tool_argument": "search_progress", + }], + ) + + state["search_progress"] = state.get("search_progress", []) + queries = ai_message.tool_calls[0]["args"]["queries"] + + for query in queries: + state["search_progress"].append({ + "query": query, + "results": [], + "done": False + }) + + await copilotkit_emit_state(config, state) + + # ^ Previous code + + places = [] + for i, query in enumerate(queries): + response = gmaps.places(query) + for result in response.get("results", []): + place = { + "id": result.get("place_id", f"{result.get('name', '')}-{i}"), + "name": result.get("name", ""), + "address": result.get("formatted_address", ""), + "latitude": result.get("geometry", {}).get("location", {}).get("lat", 0), + "longitude": result.get("geometry", {}).get("location", {}).get("lng", 0), + "rating": result.get("rating", 0), + } + places.append(place) + state["search_progress"][i]["done"] = True + await copilotkit_emit_state(config, state) # [!code ++] + + state["search_progress"] = [] + await copilotkit_emit_state(config, state) # [!code ++] + + # ... + +``` + + + +## Recieving and rendering the manaully emitted state + +Now that we are manually emitting the state of our search, we can recieve and render that state in the UI. To do this, +we'll be using the [useCoAgentStateRender](/reference/hooks/useCoAgentStateRender) function in our `use-trips.tsx` hook. + + +All we need to do is tell CopilotKit to conditionally render the `search_progress` state key through the `useCoAgentStateRender` hook. + +```tsx title="ui/lib/hooks/use-trips.tsx" +// ... +import { useCoAgent } from "@copilotkit/react-core"; // [!code --] +import { useCoAgent, useCoAgentStateRender } from "@copilotkit/react-core"; // [!code ++] +import { SearchProgress } from "@/components/SearchProgress"; // [!code ++] + +export const TripsProvider = ({ children }: { children: ReactNode }) => { + // ... + + const { state, setState } = useCoAgent({ + name: "travel", + initialState: { + trips: defaultTrips, + selected_trip_id: defaultTrips[0].id, + }, + }); + + // [!code ++:10] + useCoAgentStateRender({ + name: "travel", + render: ({ state }) => { + if (state.search_progress) { + return + } + return null; + }, + }); + + // ... +} + +``` + +The `` component is a custom component that was created for you ahead of time. If you'd like to +learn more about it feel free to check it out in `ui/components/SearchProgress.tsx`! + + +One other thing done for you ahead of time is that the `search_progress` key is already present in the `AgentState` type. You +can look at that type in `ui/lib/types.ts`. + + +Give it a try! Ask the agent to search for places and we'll see the progress of each search as it comes in. + +The final step is to add human in the loop to the application to allow the user to approve or reject mutative actions the +agent wants to perform. \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-6-human-in-the-loop.mdx b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-6-human-in-the-loop.mdx new file mode 100644 index 0000000000..72433b6a86 --- /dev/null +++ b/docs/content/docs/crewai-flows/tutorials/ai-travel-app/step-6-human-in-the-loop.mdx @@ -0,0 +1,300 @@ +--- +title: "Step 6: Human in the Loop" +--- + +Now its time to add human in the loop to the application. This will allow the user to approve, reject, or modify mutative actions the +agent wants to perform. For simplicity, we'll be only implementing approve and reject actions in this step. + +Our plan is to add a "breakpoint" to the application. This is a LangGraph concept that will force the agent to pause and wait for the +human approval before continuing execution. + + +You can learn more about breakpoints [here](https://langchain-ai.github.io/langgraph/how-tos/human_in_the_loop/breakpoints/?h=breakp). + + +The breakpoint will then be communicated to our front-end which we'll use to render and take the user's decision. Finally, the user's +decision will be communicated back to the agent and execution will continue. + +All together, this process will look like this: + + + Human in the loop + + +If you'd like to learn even more about human in the loop before proceeding, checkout our [Human in the Loop concept guide](/coagents/human-in-the-loop). + +Otherwise, let's get started! + + + +## Add the breakpoint to the `trips_node` + +The way that this LangGraph has been implemented allows for easy human in the loop integration. Essentially, we have a `trips_node` +that serves as a proxy to the `perform_trips_node`. This means that we can block entrance to the `perform_trips_node` by adding a breakpoint +to the `trips_node`. This will then force the agent to pause and wait for the human to approve the action before execution can continue. + +To add a breakpoint to the agent, we'll be editing the graph definition in the `agent/travel/agent.py` file. + +At the very bottom of the file, add the following line to the `compile` function: +```python title="agent/travel/agent.py" +# ... + +graph = graph_builder.compile( + checkpointer=MemorySaver(), + interrupt_after=["trips_node"], # [!code ++] +) +``` + +This will force the agent to pause execution at the `trips_node` and wait for the human to approve the action before continuing. + + +## Update the perform_trips_node node to properly handle the user's decision + +Prior to this step, entrance to the `perform_trips_node` was standard. We would recieve the requested tool call, call the appropriate +tool, edit the message state to reflect the tool call results, and then move on to the next node. + +However, this will no longer work since we've added a breakpoint to the `trips_node`. In a future step, we'll be utilizing this +breakpoint to render a UI to the user for approval or rejection. Their decision will be communicated back via the message state. + +In this step, we'll be retrieving that decison from the message state and acting accordingly. + +First, let's grab the tool call message and the tool call being requested. + +```python title="agent/travel/trips.py" +# ... + +async def perform_trips_node(state: AgentState, config: RunnableConfig): + """Execute trip operations""" + ai_message = state["messages"][-1] # [!code --] + ai_message = cast(AIMessage, state["messages"][-2]) # [!code ++] + tool_message = cast(ToolMessage, state["messages"][-1]) # [!code ++] + + # ... +``` + +Now, let's add a conditional that will check the user's decision and act accordingly. + +```python title="agent/travel/trips.py" +from copilotkit.langchain import copilotkit_emit_message # [!code ++] + +# ... +async def perform_trips_node(state: AgentState, config: RunnableConfig): + """Execute trip operations""" + ai_message = cast(AIMessage, state["messages"][-2]) + tool_message = cast(ToolMessage, state["messages"][-1]) + + # [!code ++:8] + if tool_message.content == "CANCEL": + await copilotkit_emit_message(config, "Cancelled operation of trip.") + return state + + # handle the edge case where the AI message is not an AIMessage or does not have tool calls, should never happen. + if not isinstance(ai_message, AIMessage) or not ai_message.tool_calls: + return state + + # ... +``` + +In this case, we are checking if the user decided to cancel the operation. If so, we emit a message to the UI and return the state. Any +other decision returned will result in the requested actions being performed. + + + +## Emitting the tool calls +In order for the front-end to recieve the breakpoint and take the user's decision, we'll need to emit the tool calls that the agent is requesting. +To do this, we'll be editing the `chat_node` in the `chat.py` file. +```python title="agent/travel/chat.py" +# ... +from copilotkit.langchain import copilotkit_customize_config # [!code ++] +async def chat_node(state: AgentState, config: RunnableConfig): + """Handle chat operations""" + # [!code ++:5] + config = copilotkit_customize_config( + config, + emit_tool_calls=["add_trips", "update_trips", "delete_trips"], + ) + # ... +``` + +We don't want to just set True here because doing so will emit all tool calls. By specifying these, we hand are handing off tool +handling to CopilotKit. If, for example, `search_for_places` was called here then it would break the state of tool calls. + +With that, our work on the agent is complete and we are ready to update the front-end to properly take and communicate the user's decision. + + + + +## Rendering the tool calls and taking the user's decision + +Now we need to update the front-end to render the tool calls and emit the user's decision back to the agent. To do this, +we'll be adding `useCopilotAction` hooks for each tool call with the `renderAndWait` option. + +```typescript title="ui/lib/hooks/use-trips.tsx" +// ... +import { AddTrips, EditTrips, DeleteTrips } from "@/components/humanInTheLoop"; // [!code ++] +import { useCoAgent, useCoAgentStateRender } from "@copilotkit/react-core"; // [!code --] +import { useCoAgent, useCoAgentStateRender, useCopilotAction } from "@copilotkit/react-core"; // [!code ++] +// ... + +export const TripsProvider = ({ children }: { children: ReactNode }) => { + // ... + + useCoAgentStateRender({ + name: "travel", + render: ({ state }) => { + return + }, + }); + + // [!code ++:42] + useCopilotAction({ + name: "add_trips", + description: "Add some trips", + parameters: [ + { + name: "trips", + type: "object[]", + description: "The trips to add", + required: true, + }, + ], + renderAndWait: AddTrips, + }); + + useCopilotAction({ + name: "update_trips", + description: "Update some trips", + parameters: [ + { + name: "trips", + type: "object[]", + description: "The trips to update", + required: true, + }, + ], + renderAndWait: EditTrips, + }); + + useCopilotAction({ + name: "delete_trips", + description: "Delete some trips", + parameters: [ + { + name: "trip_ids", + type: "string[]", + description: "The ids of the trips to delete", + required: true, + }, + ], + renderAndWait: (props) => DeleteTrips({ ...props, trips: state.trips }), + }); + + // ... +``` + +With that, our front-end is now ready to render the tool calls and take the user's decision. One thing we glossed over +are all of the imported `humanInTheLoop` components. They're provided for the convenience of this tutorial, but we should +note one very important thing - how they send the user's decision back to the agent. + + + +## (optional) Understanding the `humanInTheLoop` components + +Let's look at the `DeleteTrips` component as an example, but the same logic applies to the `AddTrips` and `EditTrips` components. + +```tsx title="ui/lib/components/humanInTheLoop/DeleteTrips.tsx" +import { Trip } from "@/lib/types"; +import { PlaceCard } from "@/components/PlaceCard"; +import { X, Trash } from "lucide-react"; +import { ActionButtons } from "./ActionButtons"; // [!code highlight] +import { RenderFunctionStatus } from "@copilotkit/react-core"; + +export type DeleteTripsProps = { + args: any; + status: RenderFunctionStatus; + handler: any; + trips: Trip[]; +}; + +export const DeleteTrips = ({ args, status, handler, trips }: DeleteTripsProps) => { + const tripsToDelete = trips.filter((trip: Trip) => args?.trip_ids?.includes(trip.id)); + + return ( +
+

The following trips will be deleted:

+ {status !== "complete" && tripsToDelete?.map((trip: Trip) => ( +
+ <> +
+
+

{trip.name}

+ {trip.places?.map((place) => ( + + ))} +
+ +
+ ))} + { status !== "complete" && ( + /* [!code highlight:7] */ + Delete} + reject={<> Cancel} + /> + )} +
+ ); +}; +``` + +As you can see, this is a fairly standard component that renders the trips that will be deleted. The important part is the `ActionButtons` +component. Let's take a look at it. + +```tsx title="ui/lib/components/humanInTheLoop/ActionButtons.tsx" +import { RenderFunctionStatus } from "@copilotkit/react-core"; +import { Button } from "../ui/button"; + +export type ActionButtonsProps = { + status: RenderFunctionStatus; + handler: any; + approve: React.ReactNode; + reject: React.ReactNode; +} + +export const ActionButtons = ({ status, handler, approve, reject }: ActionButtonsProps) => ( +
+ + +
+); +``` + +The important piece here is that the `onClick` handlers emit the user's decision back to the agent. If the user clicks the `Delete` button +then the `handler?.("SEND")` is called. If the user clicks the `Cancel` button then the `handler?.("CANCEL")` is called. This is how the +agent recieves the user's decision. + + +If you wanted to implement a more complex UI that allows for the human to edit the tool call arguments before sending them back to the agent, +you could do so by adding additional logic to the `onClick` handlers and the agent's handling of the tool call. + + +
+
+ +With that, we've now completed the human in the loop implementation! Try asking the agent to add, edit, or delete some trips and see it in +action. \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/tutorials/meta.json b/docs/content/docs/crewai-flows/tutorials/meta.json new file mode 100644 index 0000000000..fbcc8b84e0 --- /dev/null +++ b/docs/content/docs/crewai-flows/tutorials/meta.json @@ -0,0 +1,7 @@ +{ + "title": "coagents", + "root": true, + "pages": [ + "ai-travel-app" + ] + } \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/videos/meta.json b/docs/content/docs/crewai-flows/videos/meta.json new file mode 100644 index 0000000000..f3f20ea3a7 --- /dev/null +++ b/docs/content/docs/crewai-flows/videos/meta.json @@ -0,0 +1,7 @@ +{ + "title": "Videos", + "pages": [ + "research-canvas", + "perplexity-clone" + ] +} \ No newline at end of file diff --git a/docs/content/docs/crewai-flows/videos/perplexity-clone.mdx b/docs/content/docs/crewai-flows/videos/perplexity-clone.mdx new file mode 100644 index 0000000000..4504f59d8f --- /dev/null +++ b/docs/content/docs/crewai-flows/videos/perplexity-clone.mdx @@ -0,0 +1,19 @@ +--- +title: "Video: Perplexity Clone" +icon: "lucide/Search" +--- +import { YouTubeVideo } from "@/components/react/youtube-video"; + + + +This is a demo of a Perplexity-style search engine using **CopilotKit and LangGraph**. +Combining these technologies enables agentic copilots or, put short, **CoAgents**, which allow for the creation of human in the loop AI agents. +Instead of relying entirely on AI, CoAgents let users step in to guide or adjust the search as needed. + +In this demo, the CoAgent will come up with a list of topics to research, and combine the results +into a comprehensive answer, including references to the sources used. + +The agent state is streamed live to the frontend, so that the user can see the work progressing. + +Both the LangGraph and the CopilotKit specific code for this demo is [available +on GitHub](https://github.com/CopilotKit/CopilotKit/tree/main/examples/coagents-ai-researcher). diff --git a/docs/content/docs/crewai-flows/videos/research-canvas.mdx b/docs/content/docs/crewai-flows/videos/research-canvas.mdx new file mode 100644 index 0000000000..dff0a000bf --- /dev/null +++ b/docs/content/docs/crewai-flows/videos/research-canvas.mdx @@ -0,0 +1,14 @@ +--- +title: "Video: Research Canvas" +icon: "lucide/BookOpen" +--- +import { YouTubeVideo } from "@/components/react/youtube-video"; + + + +This is a step by step walkthrough of building an Agent-Native Research canvas using **CopilotKit and LangGraph**. + +You can run the app here: https://examples-coagents-research-canvas-ui.vercel.app/ + +The full source code is [available on GitHub](https://github.com/CopilotKit/CopilotKit/blob/main/examples/coagents-research-canvas/readme.md). + diff --git a/docs/content/docs/reference/sdk/python/CrewAI.mdx b/docs/content/docs/reference/sdk/python/CrewAI.mdx new file mode 100644 index 0000000000..490915d691 --- /dev/null +++ b/docs/content/docs/reference/sdk/python/CrewAI.mdx @@ -0,0 +1,102 @@ +--- +title: "CrewAI SDK" +description: "The CopilotKit CrewAI SDK for Python allows you to build and run CrewAI agents with CopilotKit." +--- + +{ + /* + * ATTENTION! DO NOT MODIFY THIS FILE! + * This page is auto-generated. If you want to make any changes to this page, changes must be made at: + * CopilotKit/../sdk-python/copilotkit/crewai.py + */ +} +## copilotkit_predict_state + +Stream tool calls as state to CopilotKit. + + To emit a tool call as streaming CrewAI state, pass the destination key in state, + the tool name and optionally the tool argument. (If you don't pass the argument name, + all arguments are emitted under the state key.) + + ```python + from copilotkit.crewai import copilotkit_predict_state + + await copilotkit_predict_state( + { + "steps": { + "tool_name": "SearchTool", + "tool_argument": "steps", + }, + } + ) + ``` + +### Parameters + + +The configuration to predict the state. + + +### Returns + + +Always return True. + + +## copilotkit_emit_message + +Manually emits a message to CopilotKit. Useful in longer running nodes to update the user. + Important: You still need to return the messages from the node. + + ### Examples + + ```python + from copilotkit.crewai import copilotkit_emit_message + + message = "Step 1 of 10 complete" + await copilotkit_emit_message(message) + + # Return the message from the node + return { + "messages": [AIMessage(content=message)] + } + ``` + +### Parameters + + +The message to emit. + + +### Returns + + +Always return True. + + +## copilotkit_emit_tool_call + +Manually emits a tool call to CopilotKit. + + ```python + from copilotkit.crewai import copilotkit_emit_tool_call + + await copilotkit_emit_tool_call(name="SearchTool", args={"steps": 10}) + ``` + +### Parameters + + +The name of the tool to emit. + + + +The arguments to emit. + + +### Returns + + +Always return True. + + diff --git a/docs/content/docs/reference/sdk/python/CrewAIAgent.mdx b/docs/content/docs/reference/sdk/python/CrewAIAgent.mdx new file mode 100644 index 0000000000..2d37e83206 --- /dev/null +++ b/docs/content/docs/reference/sdk/python/CrewAIAgent.mdx @@ -0,0 +1,108 @@ +--- +title: "CrewAIAgent" +description: "CrewAIAgent lets you define your agent for use with CopilotKit." +--- + +{ + /* + * ATTENTION! DO NOT MODIFY THIS FILE! + * This page is auto-generated. If you want to make any changes to this page, changes must be made at: + * CopilotKit/../sdk-python/copilotkit/crewai_agent.py + */ +} +## CrewAIAgent + +CrewAIAgent lets you define your agent for use with CopilotKit. + + To install, run: + + ```bash + pip install copilotkit + ``` + + Every agent must have the `name` and either `crew` or `flow` properties defined. An optional + `description` can also be provided. This is used when CopilotKit is dynamically routing requests + to the agent. + + ## Serving a Crew based agent + + To serve a Crew based agent, pass in a `Crew` object to the `crew` parameter. + + Note: + You need to make sure to have a `chat_llm` set on the `Crew` object. + See [the CrewAI docs](https://docs.crewai.com/concepts/cli#9-chat) for more information. + + ```python + from copilotkit import CrewAIAgent + + + CrewAIAgent( + name="email_agent_crew", + description="This crew based agent sends emails", + crew=SendEmailCrew(), + ) + ``` + + ## Serving a Flow based agent + + To serve a Flow based agent, pass in a `Flow` object to the `flow` parameter. + + ```python + CrewAIAgent( + name="email_agent_flow", + description="This flow based agent sends emails", + flow=SendEmailFlow(), + ) + ``` + + Note: + Either a `crew` or `flow` must be provided to CrewAIAgent. + +### Parameters + + +The name of the agent. + + + +When using a Crew based agent, pass in a `Crew` object to the `crew` parameter. + + + +When using a Flow based agent, pass in a `Flow` object to the `flow` parameter. + + + +The description of the agent. + + + +The CopilotKit config to use with the agent. + + +## CopilotKitConfig + +CopilotKit config for CrewAIAgent + + This is used for advanced cases where you want to customize how CopilotKit interacts with + CrewAI. + + ```python + # Function signatures: + def merge_state( + *, + state: dict, + messages: List[BaseMessage], + actions: List[Any], + agent_name: str + ): + # ...implementation... + + ``` + +### Parameters + + +This function lets you customize how CopilotKit merges the agent state. + + diff --git a/docs/content/docs/reference/sdk/python/LangGraph.mdx b/docs/content/docs/reference/sdk/python/LangGraph.mdx index f324b0b325..ed624e3559 100644 --- a/docs/content/docs/reference/sdk/python/LangGraph.mdx +++ b/docs/content/docs/reference/sdk/python/LangGraph.mdx @@ -14,7 +14,7 @@ description: "The CopilotKit LangGraph SDK for Python allows you to build and ru Customize the LangGraph configuration for use in CopilotKit. - To the CopilotKit SDK, run: + To install the CopilotKit SDK, run: ```bash pip install copilotkit diff --git a/docs/content/docs/reference/sdk/python/RemoteEndpoints.mdx b/docs/content/docs/reference/sdk/python/RemoteEndpoints.mdx index d5ce704c25..9e5dc9cee9 100644 --- a/docs/content/docs/reference/sdk/python/RemoteEndpoints.mdx +++ b/docs/content/docs/reference/sdk/python/RemoteEndpoints.mdx @@ -21,9 +21,10 @@ CopilotKitRemoteEndpoint lets you connect actions and agents written in Python t pip install copilotkit ``` - ### Examples + ## Adding actions + + In this example, we provide a simple action to the Copilot: - For example, to provide a simple action to the Copilot: ```python from copilotkit import CopilotKitRemoteEndpoint, Action @@ -46,7 +47,7 @@ CopilotKitRemoteEndpoint lets you connect actions and agents written in Python t ``` You can also dynamically build actions by providing a callable that returns a list of actions. - In this example, we use `"name"` from the `properties` object to parameterize the action handler. + In this example, we use "name" from the `properties` object to parameterize the action handler. ```python from copilotkit import CopilotKitRemoteEndpoint, Action @@ -74,7 +75,9 @@ CopilotKitRemoteEndpoint lets you connect actions and agents written in Python t ) ``` - Similarly, you can give a list of static or dynamic agents to the Copilot: + ## Adding agents + + Serving agents works in a similar way to serving actions: ```python from copilotkit import CopilotKitRemoteEndpoint, LangGraphAgent @@ -82,7 +85,7 @@ CopilotKitRemoteEndpoint lets you connect actions and agents written in Python t sdk = CopilotKitRemoteEndpoint( agents=[ - LangGraphAgent( + LangGraphAgent( name="email_agent", description="This agent sends emails", graph=graph, @@ -91,6 +94,41 @@ CopilotKitRemoteEndpoint lets you connect actions and agents written in Python t ) ``` + To dynamically build agents, provide a callable that returns a list of agents: + + ```python + from copilotkit import CopilotKitRemoteEndpoint, LangGraphAgent + from my_agent.agent import graph + + sdk = CopilotKitRemoteEndpoint( + agents=lambda context: [ + LangGraphAgent( + name="email_agent", + description="This agent sends emails", + graph=graph, + langgraph_config={ + "token": context["properties"]["token"] + } + ) + ] + ) + ``` + + To restrict the agents available to the Copilot, simply return a different list of agents based on the `context`: + + ```python + from copilotkit import CopilotKitRemoteEndpoint + from my_agents import agent_a, agent_b, is_admin + + sdk = CopilotKitRemoteEndpoint( + agents=lambda context: ( + [agent_a, agent_b] if is_admin(context["properties"]["token"]) else [agent_a] + ) + ) + ``` + + ## Serving the CopilotKit SDK + To serve the CopilotKit SDK, you can use the `add_fastapi_endpoint` function from the `copilotkit.integrations.fastapi` module: ```python @@ -135,3 +173,7 @@ The properties provided to the frontend via `` The current URL of the frontend + +The headers of the request + + diff --git a/docs/content/docs/reference/sdk/python/meta.json b/docs/content/docs/reference/sdk/python/meta.json index 77cccac20b..8a0dc62e3e 100644 --- a/docs/content/docs/reference/sdk/python/meta.json +++ b/docs/content/docs/reference/sdk/python/meta.json @@ -1,3 +1,9 @@ { - "pages": ["RemoteEndpoints", "LangGraphAgent", "LangGraph"] + "pages": [ + "RemoteEndpoints", + "LangGraphAgent", + "LangGraph", + "CrewAIAgent", + "CrewAI" + ] } diff --git a/docs/lib/icons/custom-icons.tsx b/docs/lib/icons/custom-icons.tsx index 3d6a821e05..44f360b011 100644 --- a/docs/lib/icons/custom-icons.tsx +++ b/docs/lib/icons/custom-icons.tsx @@ -4,6 +4,7 @@ import { LuBrush, LuZap, LuGlobe } from "react-icons/lu"; import { SiLangchain } from "react-icons/si"; import { TbBrandTypescript } from "react-icons/tb"; import { FaPython } from "react-icons/fa"; +import { SiCrewai } from "@icons-pack/react-simple-icons"; export const customIcons = { react: FaReact, @@ -14,4 +15,5 @@ export const customIcons = { langchain: SiLangchain, typescript: TbBrandTypescript, python: FaPython, -} \ No newline at end of file + crewai: SiCrewai, +}; diff --git a/docs/package.json b/docs/package.json index d8c2154f30..ae7d4345f7 100644 --- a/docs/package.json +++ b/docs/package.json @@ -12,6 +12,7 @@ "dependencies": { "@clerk/clerk-react": "^5.18.2", "@clerk/nextjs": "^6.7.1", + "@icons-pack/react-simple-icons": "^11.2.0", "@radix-ui/react-dialog": "^1.1.2", "@radix-ui/react-icons": "^1.3.0", "@radix-ui/react-scroll-area": "^1.2.2", diff --git a/docs/pnpm-lock.yaml b/docs/pnpm-lock.yaml index ba7bb2fb77..5b53c5be1d 100644 --- a/docs/pnpm-lock.yaml +++ b/docs/pnpm-lock.yaml @@ -14,6 +14,9 @@ importers: '@clerk/nextjs': specifier: ^6.7.1 version: 6.7.1(next@14.2.13(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react-dom@18.3.1(react@18.3.1))(react@18.3.1) + '@icons-pack/react-simple-icons': + specifier: ^11.2.0 + version: 11.2.0(react@18.3.1) '@radix-ui/react-dialog': specifier: ^1.1.2 version: 1.1.2(@types/react-dom@18.3.0)(@types/react@18.3.9)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) @@ -385,6 +388,11 @@ packages: '@iconify/utils@2.1.33': resolution: {integrity: sha512-jP9h6v/g0BIZx0p7XGJJVtkVnydtbgTgt9mVNcGDYwaa7UhdHdI9dvoq+gKj9sijMSJKxUPEG2JyjsgXjxL7Kw==} + '@icons-pack/react-simple-icons@11.2.0': + resolution: {integrity: sha512-jCJ+1Fe0yiBQGYSfhx8QGU/9o27t8J4Hw3mxHEI9vohRltLSi5CaPzO2fCQcMNeTrAUAm4j+yaDuAutskiKRjA==} + peerDependencies: + react: ^16.13 || ^17 || ^18 || ^19 + '@isaacs/cliui@8.0.2': resolution: {integrity: sha512-O8jcjabXaleOG9DQ0+ARXWZBTfnP4WNAqzuiJK7ll44AmxGKv/J2M4TPjxjY3znBCfvBXFzucm1twdyFybFqEA==} engines: {node: '>=12'} @@ -3007,6 +3015,10 @@ snapshots: transitivePeerDependencies: - supports-color + '@icons-pack/react-simple-icons@11.2.0(react@18.3.1)': + dependencies: + react: 18.3.1 + '@isaacs/cliui@8.0.2': dependencies: string-width: 5.1.2 diff --git a/docs/snippets/coagents/cloud-configure-copilotkit-provider.mdx b/docs/snippets/coagents/cloud-configure-copilotkit-provider.mdx index 6fd05f2f91..ca314b8e2f 100644 --- a/docs/snippets/coagents/cloud-configure-copilotkit-provider.mdx +++ b/docs/snippets/coagents/cloud-configure-copilotkit-provider.mdx @@ -10,7 +10,7 @@ export default function RootLayout({ children }: { children: ReactNode }) { {/* Use the public api key you got from Copilot Cloud */} // [!code highlight:5] {children} diff --git a/docs/snippets/coagents/self-host-configure-copilotkit-provider.mdx b/docs/snippets/coagents/self-host-configure-copilotkit-provider.mdx index 4137ba6b01..0f1c71a23c 100644 --- a/docs/snippets/coagents/self-host-configure-copilotkit-provider.mdx +++ b/docs/snippets/coagents/self-host-configure-copilotkit-provider.mdx @@ -10,7 +10,7 @@ export default function RootLayout({ children }: { children: ReactNode }) { {/* Use the public api key you got from Copilot Cloud */} // [!code highlight:5] {children} diff --git a/examples/coagents-qa-native/agent/email_agent/crewai/__init__.py b/examples/coagents-qa-native/agent/email_agent/crewai/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/examples/coagents-qa-native/agent/email_agent/crewai/agent.py b/examples/coagents-qa-native/agent/email_agent/crewai/agent.py new file mode 100644 index 0000000000..9bdee7118c --- /dev/null +++ b/examples/coagents-qa-native/agent/email_agent/crewai/agent.py @@ -0,0 +1,127 @@ +"""Email Agent CrewAI Flow""" + +import uuid +import json +from typing import Any, Dict, cast +from crewai.flow.flow import Flow, start, router, listen +from litellm import completion +from copilotkit.crewai import ( + copilotkit_exit, + copilotkit_emit_message, + copilotkit_stream, +) + +# Define a tool for composing emails – analogous to the "EmailTool" in LangGraph. +EMAIL_TOOL = { + "type": "function", + "function": { + "name": "EmailTool", + "description": "Compose an email based on instructions.", + "parameters": { + "type": "object", + "properties": { + "the_email": { + "type": "string", + "description": "The composed email." + } + }, + "required": ["the_email"] + } + } +} + + +class EmailAgentFlow(Flow[Dict[str, Any]]): + """ + CrewAI Flow for composing and sending emails. + """ + + @start() + async def start_flow(self): + """ + Start the flow. + """ + sender = self.state.get("sender") + if not sender: + sender = "Default Sender" + self.state["sender"] = sender + + sender_company = self.state.get("sender_company") + if not sender_company: + sender_company = "Default Company" + self.state["sender_company"] = sender_company + + @router(start_flow) + async def route_flow(self): + """ + Compose an email. + """ + messages = self.state.get("messages", []) + print(messages, flush=True) + + if (len(messages) > 0 and + messages[-1].get("role") == "tool" and + (messages[-1].get("content") == "CANCEL" or + messages[-1].get("content") == "SEND")): + return "route_send_email" + + return "route_create_email" + + @listen("route_create_email") + async def create_email(self): + """ + Compose an email. + """ + sender = self.state.get("sender") + sender_company = self.state.get("sender_company") + + # Build the instructions prompt. + prompt = ( + f"You write emails. The email is by the following sender: {sender}, " + f"working for: {sender_company}" + ) + + response = await copilotkit_stream( + completion( + model="openai/gpt-4o", + messages=[ + {"role": "system", "content": prompt}, + *self.state.get("messages", []) + ], + tools=[EMAIL_TOOL], + tool_choice="required", + stream=True + ) + ) + + # Extract the tool call from the response. + message = cast(Any, response).choices[0]["message"] + tool_calls = message.get("tool_calls", []) + if tool_calls: + email_text = json.loads(tool_calls[0]["function"]["arguments"]).get("the_email", "") + else: + email_text = "" + + # Update the state with the composed email and record the message. + self.state["email"] = email_text + self.state.setdefault("messages", []).append(message) + + + @listen("route_send_email") + async def send_email(self): + """ + Send the composed email. + """ + await copilotkit_exit() + + last_message = self.state.get("messages", [])[-1] + if last_message.get("content") == "CANCEL": + text_message = "❌ Cancelled sending email." + else: + text_message = "✅ Sent email." + + await copilotkit_emit_message(text_message) + self.state.setdefault("messages", []).append( + {"role": "assistant", "content": text_message, "id": str(uuid.uuid4())} + ) + return None diff --git a/examples/coagents-qa-native/agent/email_agent/demo.py b/examples/coagents-qa-native/agent/email_agent/demo.py index e89e4dc62f..054b759617 100644 --- a/examples/coagents-qa-native/agent/email_agent/demo.py +++ b/examples/coagents-qa-native/agent/email_agent/demo.py @@ -8,8 +8,9 @@ from fastapi import FastAPI import uvicorn from copilotkit.integrations.fastapi import add_fastapi_endpoint from copilotkit import CopilotKitRemoteEndpoint, LangGraphAgent -from email_agent.agent import graph - +from copilotkit.crewai import CrewAIAgent +from email_agent.langgraph.agent import graph +from email_agent.crewai.agent import EmailAgentFlow app = FastAPI() sdk = CopilotKitRemoteEndpoint( agents=[ @@ -17,7 +18,12 @@ sdk = CopilotKitRemoteEndpoint( name="email_agent", description="This agent sends emails", graph=graph, - ) + ), + CrewAIAgent( + name="email_agent_crewai", + description="This agent sends emails", + flow=EmailAgentFlow(), + ), ], ) diff --git a/examples/coagents-qa-native/agent/email_agent/langgraph/__init__.py b/examples/coagents-qa-native/agent/email_agent/langgraph/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/examples/coagents-qa-native/agent/email_agent/agent.py b/examples/coagents-qa-native/agent/email_agent/langgraph/agent.py similarity index 85% rename from examples/coagents-qa-native/agent/email_agent/agent.py rename to examples/coagents-qa-native/agent/email_agent/langgraph/agent.py index 95ca1c5838..701c3ccc58 100644 --- a/examples/coagents-qa-native/agent/email_agent/agent.py +++ b/examples/coagents-qa-native/agent/email_agent/langgraph/agent.py @@ -1,16 +1,17 @@ """Test Q&A Agent""" from typing import Any, cast -from langgraph.graph import StateGraph, END -from langgraph.checkpoint.memory import MemorySaver -from langchain_core.runnables import RunnableConfig + +from langgraph.graph import StateGraph, END # pylint: disable=no-name-in-module, import-error +from langgraph.checkpoint.memory import MemorySaver # pylint: disable=no-name-in-module, import-error +from langgraph.types import interrupt # pylint: disable=no-name-in-module, import-error +from langchain_core.runnables import RunnableConfig from langchain_core.messages import HumanMessage, ToolMessage, AIMessage from copilotkit.langgraph import ( copilotkit_customize_config, copilotkit_exit, copilotkit_emit_message, copilotkit_interrupt ) -from langgraph.types import interrupt -from email_agent.model import get_model -from email_agent.state import EmailAgentState +from email_agent.langgraph.model import get_model +from email_agent.langgraph.state import EmailAgentState async def email_node(state: EmailAgentState, config: RunnableConfig): diff --git a/examples/coagents-qa-native/agent/email_agent/model.py b/examples/coagents-qa-native/agent/email_agent/langgraph/model.py similarity index 89% rename from examples/coagents-qa-native/agent/email_agent/model.py rename to examples/coagents-qa-native/agent/email_agent/langgraph/model.py index ddf3269fe4..24ec12d6e6 100644 --- a/examples/coagents-qa-native/agent/email_agent/model.py +++ b/examples/coagents-qa-native/agent/email_agent/langgraph/model.py @@ -3,7 +3,7 @@ This module provides a function to get a model based on the configuration. """ import os from langchain_core.language_models.chat_models import BaseChatModel -from email_agent.state import EmailAgentState +from email_agent.langgraph.state import EmailAgentState def get_model(state: EmailAgentState) -> BaseChatModel: @@ -28,7 +28,7 @@ def get_model(state: EmailAgentState) -> BaseChatModel: stop=None ) if model == "google_genai": - from langchain_google_genai import ChatGoogleGenerativeAI # pylint: disable=import-outside-toplevel + from langchain_google_genai import ChatGoogleGenerativeAI # type: ignore pylint: disable=import-outside-toplevel, import-error return ChatGoogleGenerativeAI(temperature=0, model="gemini-1.5-pro") raise ValueError("Invalid model specified") diff --git a/examples/coagents-qa-native/agent/email_agent/state.py b/examples/coagents-qa-native/agent/email_agent/langgraph/state.py similarity index 100% rename from examples/coagents-qa-native/agent/email_agent/state.py rename to examples/coagents-qa-native/agent/email_agent/langgraph/state.py diff --git a/examples/coagents-qa-native/agent/langgraph.json b/examples/coagents-qa-native/agent/langgraph.json index bc49a6d971..44025d2106 100644 --- a/examples/coagents-qa-native/agent/langgraph.json +++ b/examples/coagents-qa-native/agent/langgraph.json @@ -3,7 +3,7 @@ "dockerfile_lines": [], "dependencies": ["."], "graphs": { - "email_agent": "./email_agent/agent.py:graph" + "email_agent": "./email_agent/langgraph/agent.py:graph" }, "env": ".env" } diff --git a/examples/coagents-qa-native/agent/poetry.lock b/examples/coagents-qa-native/agent/poetry.lock index 3e265a95aa..9533b2b15d 100644 --- a/examples/coagents-qa-native/agent/poetry.lock +++ b/examples/coagents-qa-native/agent/poetry.lock @@ -1,14 +1,14 @@ -# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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idna = ">=2.0" multidict = ">=4.0" propcache = ">=0.2.0" +[[package]] +name = "zipp" +version = "3.21.0" +description = "Backport of pathlib-compatible object wrapper for zip files" +optional = false +python-versions = ">=3.9" +files = [ + {file = "zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931"}, + {file = "zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4"}, +] + +[package.extras] +check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"] +cover = ["pytest-cov"] +doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] +enabler = ["pytest-enabler (>=2.2)"] +test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] +type = ["pytest-mypy"] + [metadata] lock-version = "2.0" -python-versions = "^3.12" -content-hash = "62e4afed7878dcb96435a9018869940b29de9ed0f66738da9adaf9ef1251d5ba" +python-versions = ">=3.12,<3.13" +content-hash = "17cfcecaa59c996f379262445a48ad163f9826ae24770a223ad9d07a919464ab" diff --git a/examples/coagents-qa-native/agent/pyproject.toml b/examples/coagents-qa-native/agent/pyproject.toml index 2236434422..785db4067b 100644 --- a/examples/coagents-qa-native/agent/pyproject.toml +++ b/examples/coagents-qa-native/agent/pyproject.toml @@ -24,7 +24,7 @@ requires = ["setuptools >= 61.0"] build-backend = "setuptools.build_meta" [tool.poetry.dependencies] -python = "^3.12" +python = ">=3.12,<3.13" langchain-openai = "0.2.3" langchain-anthropic = "0.2.3" langchain-google-genai = "2.0.0" @@ -37,6 +37,7 @@ uvicorn = "^0.31.0" python-dotenv = "^1.0.1" langchain-core = "^0.3.25" langgraph-cli = {extras = ["inmem"], version = "^0.1.64"} +crewai = {extras = ["tools"], version = "^0.102.0"} [tool.poetry.scripts] demo = "email_agent.demo:main" diff --git a/examples/coagents-qa-native/ui/app/Mailer.tsx b/examples/coagents-qa-native/ui/app/Mailer.tsx index 9ee2fd2d54..d2160a171d 100644 --- a/examples/coagents-qa-native/ui/app/Mailer.tsx +++ b/examples/coagents-qa-native/ui/app/Mailer.tsx @@ -7,12 +7,18 @@ import { useState } from "react"; import { useCopilotChatSuggestions } from "@copilotkit/react-ui"; import { useLangGraphInterrupt } from "@copilotkit/react-core"; -const InterruptForm = ({ event, resolve }: { event: { value: string }, resolve: (value: string) => void }) => { +const InterruptForm = ({ + event, + resolve, +}: { + event: { value: string }; + resolve: (value: string) => void; +}) => { const [name, setName] = useState(""); return (
{event.value}
- setName(e.target.value)} />
diff --git a/examples/coagents-routing/ui/src/app/page.tsx b/examples/coagents-routing/ui/src/app/page.tsx index 1a968ec8d2..8a8c103e6a 100644 --- a/examples/coagents-routing/ui/src/app/page.tsx +++ b/examples/coagents-routing/ui/src/app/page.tsx @@ -16,23 +16,41 @@ import { } from "./lib/model-selector-provider"; import { ModelSelector } from "./components/ModelSelector"; import { MessageRole, TextMessage } from "@copilotkit/runtime-client-gql"; +import { useSearchParams } from "next/navigation"; +import { Suspense } from "react"; export default function ModelSelectorWrapper() { return ( - + + + ); } function Home() { - const { lgcDeploymentUrl } = useModelSelectorContext(); + const { lgcDeploymentUrl, model } = useModelSelectorContext(); + + const searchParams = useSearchParams(); + + const runtimeUrl = searchParams.get("runtimeUrl") + ? (searchParams.get("runtimeUrl") as string) + : `/api/copilotkit?lgcDeploymentUrl=${lgcDeploymentUrl ?? ""}`; + + const publicApiKey = searchParams.get("publicApiKey"); + const copilotKitProps: Partial> = { + runtimeUrl, + publicApiKey: publicApiKey || undefined, + showDevConsole: false, + properties: { + model, + }, + }; return ( - +
diff --git a/examples/coagents-starter-crewai-crews/README.md b/examples/coagents-starter-crewai-crews/README.md new file mode 100644 index 0000000000..f61dbb0658 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/README.md @@ -0,0 +1,61 @@ +# CoAgents CrewAI + +This example contains a simple starter project. + +**These instructions assume you are in the `coagents-crewai/` directory** + +## Running the Agent + +First, install the dependencies: + +```sh +cd agent +poetry install +``` + +Then, create a `.env` file inside `./agent` with the following: + +``` +OPENAI_API_KEY=... +``` + +IMPORTANT: +Make sure the OpenAI API Key you provide, supports gpt-4o. + +Then, run the demo: + +```sh +poetry run demo +``` + +## Running the UI + +First, install the dependencies: + +```sh +cd ./ui +pnpm i +``` + +Then, create a `.env` file inside `./ui` with the following: + +``` +OPENAI_API_KEY=... +``` + +Then, run the Next.js project: + +```sh +pnpm run dev +``` + +## Usage + +Navigate to [http://localhost:3000](http://localhost:3000). + +# Troubleshooting + +A few things to try if you are running into trouble: + +1. Make sure there is no other local application server running on the 8000 port. +2. Under `/agent/greeter/demo.py`, change `0.0.0.0` to `127.0.0.1` or to `localhost` diff --git a/examples/coagents-starter-crewai-crews/agent-py/.gitignore b/examples/coagents-starter-crewai-crews/agent-py/.gitignore new file mode 100644 index 0000000000..f351710520 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/agent-py/.gitignore @@ -0,0 +1,5 @@ +venv/ +__pycache__/ +*.pyc +.env +.vercel diff --git a/examples/coagents-starter-crewai-crews/agent-py/.vscode/cspell.json b/examples/coagents-starter-crewai-crews/agent-py/.vscode/cspell.json new file mode 100644 index 0000000000..76135cf6f6 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/agent-py/.vscode/cspell.json @@ -0,0 +1,18 @@ +{ + "version": "0.2", + "language": "en", + "words": [ + "langgraph", + "langchain", + "perplexity", + "openai", + "ainvoke", + "pydantic", + "tavily", + "copilotkit", + "fastapi", + "uvicorn", + "checkpointer", + "dotenv" + ] +} diff --git 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a/examples/coagents-starter-crewai-crews/agent-py/pyproject.toml b/examples/coagents-starter-crewai-crews/agent-py/pyproject.toml new file mode 100644 index 0000000000..ff6aa68129 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/agent-py/pyproject.toml @@ -0,0 +1,25 @@ +[tool.poetry] +name = "research" +version = "0.1.0" +description = "Starter" +authors = ["Markus Ecker "] +license = "MIT" + +[project] +name = "greeter" +version = "0.0.1" + +[build-system] +requires = ["setuptools >= 61.0"] +build-backend = "setuptools.build_meta" + +[tool.poetry.dependencies] +python = ">=3.10,<3.13" +openai = "^1.51.0" +copilotkit = "0.1.39" +uvicorn = "^0.31.0" +python-dotenv = "^1.0.1" +crewai = {extras = ["tools"], version = "^0.102.0"} + +[tool.poetry.scripts] +demo = "research.demo:main" diff --git a/examples/coagents-starter-crewai-crews/agent-py/research/__init__.py b/examples/coagents-starter-crewai-crews/agent-py/research/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/examples/coagents-starter-crewai-crews/agent-py/research/config/agents.yaml b/examples/coagents-starter-crewai-crews/agent-py/research/config/agents.yaml new file mode 100644 index 0000000000..72ed6939e4 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/agent-py/research/config/agents.yaml @@ -0,0 +1,19 @@ +researcher: + role: > + {topic} Senior Data Researcher + goal: > + Uncover cutting-edge developments in {topic} + backstory: > + You're a seasoned researcher with a knack for uncovering the latest + developments in {topic}. Known for your ability to find the most relevant + information and present it in a clear and concise manner. + +reporting_analyst: + role: > + {topic} Reporting Analyst + goal: > + Create detailed reports based on {topic} data analysis and research findings + backstory: > + You're a meticulous analyst with a keen eye for detail. You're known for + your ability to turn complex data into clear and concise reports, making + it easy for others to understand and act on the information you provide. \ No newline at end of file diff --git a/examples/coagents-starter-crewai-crews/agent-py/research/config/tasks.yaml b/examples/coagents-starter-crewai-crews/agent-py/research/config/tasks.yaml new file mode 100644 index 0000000000..44bd898656 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/agent-py/research/config/tasks.yaml @@ -0,0 +1,17 @@ +research_task: + description: > + Conduct a thorough research about {topic} + Make sure you find any interesting and relevant information given + the current year is {current_year}. + expected_output: > + A list with 10 bullet points of the most relevant information about {topic} + agent: researcher + +reporting_task: + description: > + Review the context you got and expand each topic into a full section for a report. + Make sure the report is detailed and contains any and all relevant information. + expected_output: > + A fully fledged report with the main topics, each with a full section of information. + Formatted as markdown without '```' + agent: reporting_analyst diff --git a/examples/coagents-starter-crewai-crews/agent-py/research/crew.py b/examples/coagents-starter-crewai-crews/agent-py/research/crew.py new file mode 100644 index 0000000000..57a88d3e2e --- /dev/null +++ b/examples/coagents-starter-crewai-crews/agent-py/research/crew.py @@ -0,0 +1,67 @@ +from crewai import Agent, Crew, Process, Task +from crewai.project import CrewBase, agent, crew, task + +# If you want to run a snippet of code before or after the crew starts, +# you can use the @before_kickoff and @after_kickoff decorators +# https://docs.crewai.com/concepts/crews#example-crew-class-with-decorators + +@CrewBase +class ResearchCrew(): + """Research crew""" + + # Learn more about YAML configuration files here: + # Agents: https://docs.crewai.com/concepts/agents#yaml-configuration-recommended + # Tasks: https://docs.crewai.com/concepts/tasks#yaml-configuration-recommended + agents_config = 'config/agents.yaml' + tasks_config = 'config/tasks.yaml' + + # If you would like to add tools to your agents, you can learn more about it here: + # https://docs.crewai.com/concepts/agents#agent-tools + @agent + def researcher(self) -> Agent: + """Researcher agent""" + return Agent( + config=self.agents_config['researcher'], # pylint: disable=invalid-sequence-index + verbose=True + ) + + @agent + def reporting_analyst(self) -> Agent: + """Reporting analyst agent""" + return Agent( + config=self.agents_config['reporting_analyst'], # pylint: disable=invalid-sequence-index + verbose=True + ) + + # To learn more about structured task outputs, + # task dependencies, and task callbacks, check out the documentation: + # https://docs.crewai.com/concepts/tasks#overview-of-a-task + @task + def research_task(self) -> Task: + """Research task""" + return Task( + config=self.tasks_config['research_task'], # pylint: disable=invalid-sequence-index + ) + + @task + def reporting_task(self) -> Task: + """Reporting task""" + return Task( + config=self.tasks_config['reporting_task'], # pylint: disable=invalid-sequence-index + output_file='report.md' + ) + + @crew + def crew(self) -> Crew: + """Creates the LatestAiDevelopment crew""" + # To learn how to add knowledge sources to your crew, check out the documentation: + # https://docs.crewai.com/concepts/knowledge#what-is-knowledge + + return Crew( + agents=self.agents, # pylint: disable=no-member + tasks=self.tasks, # pylint: disable=no-member + process=Process.sequential, + verbose=True, + chat_llm="gpt-4o" + # process=Process.hierarchical, # In case you wanna use that instead https://docs.crewai.com/how-to/Hierarchical/ + ) diff --git a/examples/coagents-starter-crewai-crews/agent-py/research/demo.py b/examples/coagents-starter-crewai-crews/agent-py/research/demo.py new file mode 100644 index 0000000000..8660333d80 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/agent-py/research/demo.py @@ -0,0 +1,49 @@ +"""Demo""" + +import os +from dotenv import load_dotenv +load_dotenv() # pylint: disable=wrong-import-position + +from fastapi import FastAPI +import uvicorn +from copilotkit.integrations.fastapi import add_fastapi_endpoint +from copilotkit import CopilotKitRemoteEndpoint +from copilotkit.crewai import CrewAIAgent + +from research.crew import ResearchCrew + +app = FastAPI() +sdk = CopilotKitRemoteEndpoint( + agents=[ + CrewAIAgent( + name="research_crew", + description="Research agent", + crew=ResearchCrew(), + ), + ], +) + +add_fastapi_endpoint(app, sdk, "/copilotkit") + +# add new route for health check +@app.get("/health") +def health(): + """Health check.""" + return {"status": "ok"} + +def main(): + """Run the uvicorn server.""" + port = int(os.getenv("PORT", "8000")) + uvicorn.run( + "research.demo:app", + host="0.0.0.0", + port=port, + reload=True, + reload_dirs=( + ["."] + + (["../../../sdk-python/copilotkit"] + if os.path.exists("../../../sdk-python/copilotkit") + else [] + ) + ) + ) diff --git a/examples/coagents-starter-crewai-crews/agent-py/research/knowledge/user_preference.txt b/examples/coagents-starter-crewai-crews/agent-py/research/knowledge/user_preference.txt new file mode 100644 index 0000000000..dd63a17bf3 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/agent-py/research/knowledge/user_preference.txt @@ -0,0 +1,4 @@ +User name is John Doe. +User is an AI Engineer. +User is interested in AI Agents. +User is based in San Francisco, California. diff --git a/examples/coagents-starter-crewai-crews/agent-py/research/tools/__init__.py b/examples/coagents-starter-crewai-crews/agent-py/research/tools/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/examples/coagents-starter-crewai-crews/agent-py/research/tools/custom_tool.py b/examples/coagents-starter-crewai-crews/agent-py/research/tools/custom_tool.py new file mode 100644 index 0000000000..154beae8e0 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/agent-py/research/tools/custom_tool.py @@ -0,0 +1,19 @@ +from crewai.tools import BaseTool +from typing import Type +from pydantic import BaseModel, Field + + +class MyCustomToolInput(BaseModel): + """Input schema for MyCustomTool.""" + argument: str = Field(..., description="Description of the argument.") + +class MyCustomTool(BaseTool): + name: str = "Name of my tool" + description: str = ( + "Clear description for what this tool is useful for, your agent will need this information to use it." + ) + args_schema: Type[BaseModel] = MyCustomToolInput + + def _run(self, argument: str) -> str: + # Implementation goes here + return "this is an example of a tool output, ignore it and move along." diff --git a/examples/coagents-starter-crewai-crews/ui/.eslintrc.json b/examples/coagents-starter-crewai-crews/ui/.eslintrc.json new file mode 100644 index 0000000000..bffb357a71 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/ui/.eslintrc.json @@ -0,0 +1,3 @@ +{ + "extends": "next/core-web-vitals" +} diff --git a/examples/coagents-starter-crewai-crews/ui/.gitignore b/examples/coagents-starter-crewai-crews/ui/.gitignore new file mode 100644 index 0000000000..4b2412b333 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/ui/.gitignore @@ -0,0 +1,38 @@ +# See https://help.github.com/articles/ignoring-files/ for more about ignoring files. + +# dependencies +/node_modules +/.pnp +.pnp.js +.yarn/install-state.gz + +# testing +/coverage + +# next.js +/.next/ +/out/ + +# production +/build + +# misc +.DS_Store +*.pem + +# debug +npm-debug.log* +yarn-debug.log* +yarn-error.log* + +# local env files +.env*.local + +.env + +# vercel +.vercel + +# typescript +*.tsbuildinfo +next-env.d.ts diff --git a/examples/coagents-starter-crewai-crews/ui/README.md b/examples/coagents-starter-crewai-crews/ui/README.md new file mode 100644 index 0000000000..c4033664f8 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/ui/README.md @@ -0,0 +1,36 @@ +This is a [Next.js](https://nextjs.org/) project bootstrapped with [`create-next-app`](https://github.com/vercel/next.js/tree/canary/packages/create-next-app). + +## Getting Started + +First, run the development server: + +```bash +npm run dev +# or +yarn dev +# or +pnpm dev +# or +bun dev +``` + +Open [http://localhost:3000](http://localhost:3000) with your browser to see the result. + +You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file. + +This project uses [`next/font`](https://nextjs.org/docs/basic-features/font-optimization) to automatically optimize and load Inter, a custom Google Font. + +## Learn More + +To learn more about Next.js, take a look at the following resources: + +- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API. +- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial. + +You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js/) - your feedback and contributions are welcome! + +## Deploy on Vercel + +The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js. + +Check out our [Next.js deployment documentation](https://nextjs.org/docs/deployment) for more details. diff --git a/examples/coagents-starter-crewai-crews/ui/app/api/copilotkit/route.ts b/examples/coagents-starter-crewai-crews/ui/app/api/copilotkit/route.ts new file mode 100644 index 0000000000..891da98047 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/ui/app/api/copilotkit/route.ts @@ -0,0 +1,26 @@ +import { NextRequest } from "next/server"; +import { + CopilotRuntime, + OpenAIAdapter, + copilotRuntimeNextJSAppRouterEndpoint, +} from "@copilotkit/runtime"; + +const serviceAdapter = new OpenAIAdapter({}); + +const runtime = new CopilotRuntime({ + remoteEndpoints: [ + { + url: process.env.REMOTE_ACTION_URL || "http://localhost:8000/copilotkit", + }, + ], +}); + +export const POST = async (req: NextRequest) => { + const { handleRequest } = copilotRuntimeNextJSAppRouterEndpoint({ + runtime, + serviceAdapter, + endpoint: "/api/copilotkit", + }); + + return handleRequest(req); +}; diff --git a/examples/coagents-starter-crewai-crews/ui/app/favicon.ico b/examples/coagents-starter-crewai-crews/ui/app/favicon.ico new file mode 100644 index 0000000000..718d6fea48 Binary files /dev/null and b/examples/coagents-starter-crewai-crews/ui/app/favicon.ico differ diff --git a/examples/coagents-starter-crewai-crews/ui/app/globals.css b/examples/coagents-starter-crewai-crews/ui/app/globals.css new file mode 100644 index 0000000000..b5c61c9567 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/ui/app/globals.css @@ -0,0 +1,3 @@ +@tailwind base; +@tailwind components; +@tailwind utilities; diff --git a/examples/coagents-starter-crewai-crews/ui/app/layout.tsx b/examples/coagents-starter-crewai-crews/ui/app/layout.tsx new file mode 100644 index 0000000000..b1f523c237 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/ui/app/layout.tsx @@ -0,0 +1,23 @@ +import type { Metadata } from "next"; + +import { CopilotKit } from "@copilotkit/react-core"; + +import "@copilotkit/react-ui/styles.css"; +import "./globals.css"; + +export const metadata: Metadata = { + title: "CoAgents Starter", + description: "CoAgents Starter", +}; + +export default function RootLayout({ children }: { children: any }) { + return ( + + + + {children} + + + + ); +} diff --git a/examples/coagents-starter-crewai-crews/ui/app/page.tsx b/examples/coagents-starter-crewai-crews/ui/app/page.tsx new file mode 100644 index 0000000000..04a0036f64 --- /dev/null +++ b/examples/coagents-starter-crewai-crews/ui/app/page.tsx @@ -0,0 +1,181 @@ +"use client"; + +import { useCoAgent, useCopilotAction } from "@copilotkit/react-core"; +import { CopilotPopup } from "@copilotkit/react-ui"; +import ReactMarkdown from "react-markdown"; + +export default function Home() { + return ( + <> + + + + ); +} + +function MainContent() { + const { state, setState } = useCoAgent({ + name: "research_crew", + initialState: { + inputs: { + topic: "", + current_year: "2025", + }, + outputs: "Report will appear here", + }, + }); + + useCopilotAction({ + name: "research_crew", + parameters: [ + { + name: "topic", + }, + { + name: "current_year", + }, + ], + render({ args, status }) { + return ( +
+

+ Researching {args.topic} in {args.current_year}{" "} + {status == "complete" ? "✅" : "⏳"} +

+
+ ); + }, + }); + + return ( +
+
+
+ + + setState({ + ...state, + inputs: { ...state.inputs, current_year: e.target.value }, + }) + } + /> +
+
+ + + setState({ + ...state, + inputs: { ...state.inputs, topic: e.target.value }, + }) + } + /> +
+
+ +
+ +
+
+
+
+ ); +} + +interface MarkdownRendererProps { + content: string; +} + +const MarkdownRenderer: React.FC = ({ content }) => { + return ( + ( + // @ts-ignore +

+ ), + h2: ({ node, ...props }) => ( + // @ts-ignore +

+ ), + h3: ({ node, ...props }) => ( + // @ts-ignore +

+ ), + p: ({ node, ...props }) => ( + // @ts-ignore +

+ ), + ul: ({ node, ...props }) => ( + // @ts-ignore +