From 4a8346900d97f16938051f0666e7b1a9214b86c9 Mon Sep 17 00:00:00 2001
From: Huu Le <39040748+leehuwuj@users.noreply.github.com>
Date: Fri, 25 Oct 2024 16:44:56 +0700
Subject: [PATCH] feat: Add multi-agent financial report use case for TS (#394)
---
.changeset/little-jars-vanish.md | 5 +
helpers/typescript.ts | 28 ++-
questions/simple.ts | 30 ++--
.../typescript/blog}/agents.ts | 0
.../typescript/blog}/factory.ts | 0
.../typescript/blog}/tools.ts | 0
.../typescript/financial_report/agents.ts | 65 +++++++
.../typescript/financial_report/factory.ts | 159 ++++++++++++++++++
.../typescript/financial_report/tools.ts | 86 ++++++++++
.../typescript/workflow/single-agent.ts | 4 +-
.../types/streaming/express/package.json | 3 +-
templates/types/streaming/nextjs/package.json | 3 +-
12 files changed, 360 insertions(+), 23 deletions(-)
create mode 100644 .changeset/little-jars-vanish.md
rename templates/components/{multiagent/typescript/workflow => agents/typescript/blog}/agents.ts (100%)
rename templates/components/{multiagent/typescript/workflow => agents/typescript/blog}/factory.ts (100%)
rename templates/components/{multiagent/typescript/workflow => agents/typescript/blog}/tools.ts (100%)
create mode 100644 templates/components/agents/typescript/financial_report/agents.ts
create mode 100644 templates/components/agents/typescript/financial_report/factory.ts
create mode 100644 templates/components/agents/typescript/financial_report/tools.ts
diff --git a/.changeset/little-jars-vanish.md b/.changeset/little-jars-vanish.md
new file mode 100644
index 00000000..e9fe18ff
--- /dev/null
+++ b/.changeset/little-jars-vanish.md
@@ -0,0 +1,5 @@
+---
+"create-llama": patch
+---
+
+Add multi-agent financial report for Typescript (and update LITS to 0.7.10)
diff --git a/helpers/typescript.ts b/helpers/typescript.ts
index f4d42cf9..da6bd62c 100644
--- a/helpers/typescript.ts
+++ b/helpers/typescript.ts
@@ -1,7 +1,7 @@
import fs from "fs/promises";
import os from "os";
import path from "path";
-import { bold, cyan, yellow } from "picocolors";
+import { bold, cyan, red, yellow } from "picocolors";
import { assetRelocator, copy } from "../helpers/copy";
import { callPackageManager } from "../helpers/install";
import { templatesDir } from "./dir";
@@ -26,6 +26,7 @@ export const installTSTemplate = async ({
tools,
dataSources,
useLlamaParse,
+ agents,
}: InstallTemplateArgs & { backend: boolean }) => {
console.log(bold(`Using ${packageManager}.`));
@@ -132,6 +133,31 @@ export const installTSTemplate = async ({
cwd: path.join(multiagentPath, "workflow"),
});
+ // Copy agents use case code for multiagent template
+ if (agents) {
+ console.log("\nCopying agent:", agents, "\n");
+
+ const agentsCodePath = path.join(
+ compPath,
+ "agents",
+ "typescript",
+ agents,
+ );
+
+ await copy("**", path.join(root, relativeEngineDestPath, "workflow"), {
+ parents: true,
+ cwd: agentsCodePath,
+ rename: assetRelocator,
+ });
+ } else {
+ console.log(
+ red(
+ "There is no agent selected for multi-agent template. Please pick an agent to use via --agents flag.",
+ ),
+ );
+ process.exit(1);
+ }
+
if (framework === "nextjs") {
// patch route.ts file
await copy("**", path.join(root, relativeEngineDestPath), {
diff --git a/questions/simple.ts b/questions/simple.ts
index 195e30d8..4888c985 100644
--- a/questions/simple.ts
+++ b/questions/simple.ts
@@ -47,23 +47,19 @@ export const askSimpleQuestions = async (
let useLlamaCloud = false;
if (appType !== "extractor") {
- // Default financial report agent use case only supports Python
- // TODO: Add support for Typescript frameworks
- if (appType !== "financial_report_agent") {
- const { language: newLanguage } = await prompts(
- {
- type: "select",
- name: "language",
- message: "What language do you want to use?",
- choices: [
- { title: "Python (FastAPI)", value: "fastapi" },
- { title: "Typescript (NextJS)", value: "nextjs" },
- ],
- },
- questionHandlers,
- );
- language = newLanguage;
- }
+ const { language: newLanguage } = await prompts(
+ {
+ type: "select",
+ name: "language",
+ message: "What language do you want to use?",
+ choices: [
+ { title: "Python (FastAPI)", value: "fastapi" },
+ { title: "Typescript (NextJS)", value: "nextjs" },
+ ],
+ },
+ questionHandlers,
+ );
+ language = newLanguage;
const { useLlamaCloud: newUseLlamaCloud } = await prompts(
{
diff --git a/templates/components/multiagent/typescript/workflow/agents.ts b/templates/components/agents/typescript/blog/agents.ts
similarity index 100%
rename from templates/components/multiagent/typescript/workflow/agents.ts
rename to templates/components/agents/typescript/blog/agents.ts
diff --git a/templates/components/multiagent/typescript/workflow/factory.ts b/templates/components/agents/typescript/blog/factory.ts
similarity index 100%
rename from templates/components/multiagent/typescript/workflow/factory.ts
rename to templates/components/agents/typescript/blog/factory.ts
diff --git a/templates/components/multiagent/typescript/workflow/tools.ts b/templates/components/agents/typescript/blog/tools.ts
similarity index 100%
rename from templates/components/multiagent/typescript/workflow/tools.ts
rename to templates/components/agents/typescript/blog/tools.ts
diff --git a/templates/components/agents/typescript/financial_report/agents.ts b/templates/components/agents/typescript/financial_report/agents.ts
new file mode 100644
index 00000000..ca86aa5f
--- /dev/null
+++ b/templates/components/agents/typescript/financial_report/agents.ts
@@ -0,0 +1,65 @@
+import { ChatMessage } from "llamaindex";
+import { FunctionCallingAgent } from "./single-agent";
+import { getQueryEngineTools, lookupTools } from "./tools";
+
+export const createResearcher = async (
+ chatHistory: ChatMessage[],
+ params?: any,
+) => {
+ const queryEngineTools = await getQueryEngineTools(params);
+
+ if (!queryEngineTools) {
+ throw new Error("Query engine tool not found");
+ }
+
+ return new FunctionCallingAgent({
+ name: "researcher",
+ tools: queryEngineTools,
+ systemPrompt: `You are a researcher agent. You are responsible for retrieving information from the corpus.
+## Instructions:
++ Don't synthesize the information, just return the whole retrieved information.
++ Don't need to retrieve the information that is already provided in the chat history and respond with: "There is no new information, please reuse the information from the conversation."
+`,
+ chatHistory,
+ });
+};
+
+export const createAnalyst = async (chatHistory: ChatMessage[]) => {
+ let systemPrompt = `You are an expert in analyzing financial data.
+You are given a task and a set of financial data to analyze. Your task is to analyze the financial data and return a report.
+Your response should include a detailed analysis of the financial data, including any trends, patterns, or insights that you find.
+Construct the analysis in textual format; including tables would be great!
+Don't need to synthesize the data, just analyze and provide your findings.
+Always use the provided information, don't make up any information yourself.`;
+ const tools = await lookupTools(["interpreter"]);
+ if (tools.length > 0) {
+ systemPrompt = `${systemPrompt}
+You are able to visualize the financial data using code interpreter tool.
+It's very useful to create and include visualizations in the report. Never include any code in the report, just the visualization.`;
+ }
+ return new FunctionCallingAgent({
+ name: "analyst",
+ tools: tools,
+ chatHistory,
+ });
+};
+
+export const createReporter = async (chatHistory: ChatMessage[]) => {
+ const tools = await lookupTools(["document_generator"]);
+ let systemPrompt = `You are a report generation assistant tasked with producing a well-formatted report given parsed context.
+Given a comprehensive analysis of the user request, your task is to synthesize the information and return a well-formatted report.
+
+## Instructions
+You are responsible for representing the analysis in a well-formatted report. If tables or visualizations are provided, add them to the most relevant sections.
+Finally, the report should be presented in markdown format.`;
+ if (tools.length > 0) {
+ systemPrompt = `${systemPrompt}.
+You are also able to generate an HTML file of the report.`;
+ }
+ return new FunctionCallingAgent({
+ name: "reporter",
+ tools: tools,
+ systemPrompt: systemPrompt,
+ chatHistory,
+ });
+};
diff --git a/templates/components/agents/typescript/financial_report/factory.ts b/templates/components/agents/typescript/financial_report/factory.ts
new file mode 100644
index 00000000..ea530969
--- /dev/null
+++ b/templates/components/agents/typescript/financial_report/factory.ts
@@ -0,0 +1,159 @@
+import {
+ Context,
+ StartEvent,
+ StopEvent,
+ Workflow,
+ WorkflowEvent,
+} from "@llamaindex/core/workflow";
+import { Message } from "ai";
+import { ChatMessage, ChatResponseChunk, Settings } from "llamaindex";
+import { getAnnotations } from "../llamaindex/streaming/annotations";
+import { createAnalyst, createReporter, createResearcher } from "./agents";
+import { AgentInput, AgentRunEvent } from "./type";
+
+const TIMEOUT = 360 * 1000;
+const MAX_ATTEMPTS = 2;
+
+class ResearchEvent extends WorkflowEvent<{ input: string }> {}
+class AnalyzeEvent extends WorkflowEvent<{ input: string }> {}
+class ReportEvent extends WorkflowEvent<{ input: string }> {}
+
+const prepareChatHistory = (chatHistory: Message[]): ChatMessage[] => {
+ // By default, the chat history only contains the assistant and user messages
+ // all the agents messages are stored in annotation data which is not visible to the LLM
+
+ const MAX_AGENT_MESSAGES = 10;
+ const agentAnnotations = getAnnotations<{ agent: string; text: string }>(
+ chatHistory,
+ { role: "assistant", type: "agent" },
+ ).slice(-MAX_AGENT_MESSAGES);
+
+ const agentMessages = agentAnnotations
+ .map(
+ (annotation) =>
+ `\n<${annotation.data.agent}>\n${annotation.data.text}\n</${annotation.data.agent}>`,
+ )
+ .join("\n");
+
+ const agentContent = agentMessages
+ ? "Here is the previous conversation of agents:\n" + agentMessages
+ : "";
+
+ if (agentContent) {
+ const agentMessage: ChatMessage = {
+ role: "assistant",
+ content: agentContent,
+ };
+ return [
+ ...chatHistory.slice(0, -1),
+ agentMessage,
+ chatHistory.slice(-1)[0],
+ ] as ChatMessage[];
+ }
+ return chatHistory as ChatMessage[];
+};
+
+export const createWorkflow = (messages: Message[], params?: any) => {
+ const chatHistoryWithAgentMessages = prepareChatHistory(messages);
+ const runAgent = async (
+ context: Context,
+ agent: Workflow,
+ input: AgentInput,
+ ) => {
+ const run = agent.run(new StartEvent({ input }));
+ for await (const event of agent.streamEvents()) {
+ if (event.data instanceof AgentRunEvent) {
+ context.writeEventToStream(event.data);
+ }
+ }
+ return await run;
+ };
+
+ const start = async (context: Context, ev: StartEvent) => {
+ context.set("task", ev.data.input);
+
+ const chatHistoryStr = chatHistoryWithAgentMessages
+ .map((msg) => `${msg.role}: ${msg.content}`)
+ .join("\n");
+
+ // Decision-making process
+ const decision = await decideWorkflow(ev.data.input, chatHistoryStr);
+
+ if (decision !== "publish") {
+ return new ResearchEvent({
+ input: `Research for this task: ${ev.data.input}`,
+ });
+ } else {
+ return new ReportEvent({
+ input: `Publish content based on the chat history\n${chatHistoryStr}\n\n and task: ${ev.data.input}`,
+ });
+ }
+ };
+
+ const decideWorkflow = async (task: string, chatHistoryStr: string) => {
+ const llm = Settings.llm;
+
+ const prompt = `You are an expert in decision-making, helping people write and publish blog posts.
+If the user is asking for a file or to publish content, respond with 'publish'.
+If the user requests to write or update a blog post, respond with 'not_publish'.
+
+Here is the chat history:
+${chatHistoryStr}
+
+The current user request is:
+${task}
+
+Given the chat history and the new user request, decide whether to publish based on existing information.
+Decision (respond with either 'not_publish' or 'publish'):`;
+
+ const output = await llm.complete({ prompt: prompt });
+ const decision = output.text.trim().toLowerCase();
+ return decision === "publish" ? "publish" : "research";
+ };
+
+ const research = async (context: Context, ev: ResearchEvent) => {
+ const researcher = await createResearcher(
+ chatHistoryWithAgentMessages,
+ params,
+ );
+ const researchRes = await runAgent(context, researcher, {
+ message: ev.data.input,
+ });
+ const researchResult = researchRes.data.result;
+ return new AnalyzeEvent({
+ input: `Write a blog post given this task: ${context.get("task")} using this research content: ${researchResult}`,
+ });
+ };
+
+ const analyze = async (context: Context, ev: AnalyzeEvent) => {
+ const analyst = await createAnalyst(chatHistoryWithAgentMessages);
+ const analyzeRes = await runAgent(context, analyst, {
+ message: ev.data.input,
+ });
+ return new ReportEvent({
+ input: `Publish content based on the chat history\n${analyzeRes.data.result}\n\n and task: ${ev.data.input}`,
+ });
+ };
+
+ const report = async (context: Context, ev: ReportEvent) => {
+ const reporter = await createReporter(chatHistoryWithAgentMessages);
+
+ const reportResult = await runAgent(context, reporter, {
+ message: `${ev.data.input}`,
+ streaming: true,
+ });
+ return reportResult as unknown as StopEvent<
+ AsyncGenerator<ChatResponseChunk>
+ >;
+ };
+
+ const workflow = new Workflow({ timeout: TIMEOUT, validate: true });
+ workflow.addStep(StartEvent, start, {
+ outputs: [ResearchEvent, ReportEvent],
+ });
+ workflow.addStep(ResearchEvent, research, { outputs: AnalyzeEvent });
+ workflow.addStep(AnalyzeEvent, analyze, { outputs: ReportEvent });
+ workflow.addStep(ReportEvent, report, { outputs: StopEvent });
+
+ return workflow;
+};
diff --git a/templates/components/agents/typescript/financial_report/tools.ts b/templates/components/agents/typescript/financial_report/tools.ts
new file mode 100644
index 00000000..3d979a77
--- /dev/null
+++ b/templates/components/agents/typescript/financial_report/tools.ts
@@ -0,0 +1,86 @@
+import fs from "fs/promises";
+import { BaseToolWithCall, LlamaCloudIndex, QueryEngineTool } from "llamaindex";
+import path from "path";
+import { getDataSource } from "../engine";
+import { createTools } from "../engine/tools/index";
+
+export const getQueryEngineTools = async (
+ params?: any,
+): Promise<QueryEngineTool[] | null> => {
+ const topK = process.env.TOP_K ? parseInt(process.env.TOP_K) : undefined;
+
+ const index = await getDataSource(params);
+ if (!index) {
+ return null;
+ }
+ // index is LlamaCloudIndex use two query engine tools
+ if (index instanceof LlamaCloudIndex) {
+ return [
+ new QueryEngineTool({
+ queryEngine: index.asQueryEngine({
+ similarityTopK: topK,
+ retrieval_mode: "files_via_content",
+ }),
+ metadata: {
+ name: "document_retriever",
+ description: `Document retriever that retrieves entire documents from the corpus.
+ ONLY use for research questions that may require searching over entire research reports.
+ Will be slower and more expensive than chunk-level retrieval but may be necessary.`,
+ },
+ }),
+ new QueryEngineTool({
+ queryEngine: index.asQueryEngine({
+ similarityTopK: topK,
+ retrieval_mode: "chunks",
+ }),
+ metadata: {
+ name: "chunk_retriever",
+ description: `Retrieves a small set of relevant document chunks from the corpus.
+ Use for research questions that want to look up specific facts from the knowledge corpus,
+ and need entire documents.`,
+ },
+ }),
+ ];
+ } else {
+ return [
+ new QueryEngineTool({
+ queryEngine: (index as any).asQueryEngine({
+ similarityTopK: topK,
+ }),
+ metadata: {
+ name: "retriever",
+ description: `Use this tool to retrieve information about the text corpus from the index.`,
+ },
+ }),
+ ];
+ }
+};
+
+export const getAvailableTools = async () => {
+ const configFile = path.join("config", "tools.json");
+ let toolConfig: any;
+ const tools: BaseToolWithCall[] = [];
+ try {
+ toolConfig = JSON.parse(await fs.readFile(configFile, "utf8"));
+ } catch (e) {
+ console.info(`Could not read ${configFile} file. Using no tools.`);
+ }
+ if (toolConfig) {
+ tools.push(...(await createTools(toolConfig)));
+ }
+ const queryEngineTools = await getQueryEngineTools();
+ if (queryEngineTools) {
+ tools.push(...queryEngineTools);
+ }
+
+ return tools;
+};
+
+export const lookupTools = async (
+ toolNames: string[],
+): Promise<BaseToolWithCall[]> => {
+ const availableTools = await getAvailableTools();
+ return availableTools.filter((tool) =>
+ toolNames.includes(tool.metadata.name),
+ );
+};
diff --git a/templates/components/multiagent/typescript/workflow/single-agent.ts b/templates/components/multiagent/typescript/workflow/single-agent.ts
index 5344f108..c32ad82f 100644
--- a/templates/components/multiagent/typescript/workflow/single-agent.ts
+++ b/templates/components/multiagent/typescript/workflow/single-agent.ts
@@ -182,7 +182,9 @@ export class FunctionCallingAgent extends Workflow {
// TODO: make logger optional in callTool in framework
const toolOutput = await callTool(targetTool, call, {
log: () => {},
- error: console.error.bind(console),
+ error: (...args: unknown[]) => {
+ console.error(`[Tool ${call.name} Error]:`, ...args);
+ },
warn: () => {},
});
toolMsgs.push({
diff --git a/templates/types/streaming/express/package.json b/templates/types/streaming/express/package.json
index ef5ae0bd..8d59ae7a 100644
--- a/templates/types/streaming/express/package.json
+++ b/templates/types/streaming/express/package.json
@@ -15,13 +15,12 @@
"dev": "concurrently \"tsup index.ts --format esm --dts --watch\" \"nodemon --watch dist/index.js\""
},
"dependencies": {
- "@llamaindex/core": "^0.2.6",
"ai": "3.3.42",
"cors": "^2.8.5",
"dotenv": "^16.3.1",
"duck-duck-scrape": "^2.2.5",
"express": "^4.18.2",
- "llamaindex": "0.6.22",
+ "llamaindex": "0.7.10",
"pdf2json": "3.0.5",
"ajv": "^8.12.0",
"@e2b/code-interpreter": "0.0.9-beta.3",
diff --git a/templates/types/streaming/nextjs/package.json b/templates/types/streaming/nextjs/package.json
index 4153d741..090cfc31 100644
--- a/templates/types/streaming/nextjs/package.json
+++ b/templates/types/streaming/nextjs/package.json
@@ -12,7 +12,6 @@
"dependencies": {
"@apidevtools/swagger-parser": "^10.1.0",
"@e2b/code-interpreter": "0.0.9-beta.3",
- "@llamaindex/core": "^0.2.6",
"@llamaindex/pdf-viewer": "^1.1.3",
"@radix-ui/react-collapsible": "^1.0.3",
"@radix-ui/react-hover-card": "^1.0.7",
@@ -27,7 +26,7 @@
"duck-duck-scrape": "^2.2.5",
"formdata-node": "^6.0.3",
"got": "^14.4.1",
- "llamaindex": "0.6.22",
+ "llamaindex": "0.7.10",
"lucide-react": "^0.294.0",
"next": "^14.2.4",
"react": "^18.2.0",
--
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