diff --git a/.changeset/spicy-apricots-double.md b/.changeset/spicy-apricots-double.md
new file mode 100644
index 0000000000000000000000000000000000000000..24b490816383f871198b1d05f84a6fd0ee2ecbd3
--- /dev/null
+++ b/.changeset/spicy-apricots-double.md
@@ -0,0 +1,5 @@
+---
+"create-llama": patch
+---
+
+Add financial report as the default use case in the multi-agent template (Python).
diff --git a/create-app.ts b/create-app.ts
index 7e00e0bab268af6ce9e3a8a268fda80f01a6bb3d..144fdc7e207f90b6d5d2bc289d4698eb5470196e 100644
--- a/create-app.ts
+++ b/create-app.ts
@@ -41,6 +41,7 @@ export async function createApp({
tools,
useLlamaParse,
observability,
+ agents,
}: InstallAppArgs): Promise<void> {
const root = path.resolve(appPath);
@@ -86,6 +87,7 @@ export async function createApp({
tools,
useLlamaParse,
observability,
+ agents,
};
if (frontend) {
diff --git a/e2e/shared/multiagent_template.spec.ts b/e2e/shared/multiagent_template.spec.ts
index c330b2c95ebd2f1509121dffbb840fbc344547f5..f470b34925f674686aec2979b783e06d1e2d6a79 100644
--- a/e2e/shared/multiagent_template.spec.ts
+++ b/e2e/shared/multiagent_template.spec.ts
@@ -18,68 +18,72 @@ const templateUI: TemplateUI = "shadcn";
const templatePostInstallAction: TemplatePostInstallAction = "runApp";
const appType: AppType = templateFramework === "nextjs" ? "" : "--frontend";
const userMessage = "Write a blog post about physical standards for letters";
+const templateAgents = ["financial_report", "blog"];
-test.describe(`Test multiagent template ${templateFramework} ${dataSource} ${templateUI} ${appType} ${templatePostInstallAction}`, async () => {
- test.skip(
- process.platform !== "linux" || process.env.DATASOURCE === "--no-files",
- "The multiagent template currently only works with files. We also only run on Linux to speed up tests.",
- );
- let port: number;
- let externalPort: number;
- let cwd: string;
- let name: string;
- let appProcess: ChildProcess;
- // Only test without using vector db for now
- const vectorDb = "none";
+for (const agents of templateAgents) {
+ test.describe(`Test multiagent template ${agents} ${templateFramework} ${dataSource} ${templateUI} ${appType} ${templatePostInstallAction}`, async () => {
+ test.skip(
+ process.platform !== "linux" || process.env.DATASOURCE === "--no-files",
+ "The multiagent template currently only works with files. We also only run on Linux to speed up tests.",
+ );
+ let port: number;
+ let externalPort: number;
+ let cwd: string;
+ let name: string;
+ let appProcess: ChildProcess;
+ // Only test without using vector db for now
+ const vectorDb = "none";
- test.beforeAll(async () => {
- port = Math.floor(Math.random() * 10000) + 10000;
- externalPort = port + 1;
- cwd = await createTestDir();
- const result = await runCreateLlama({
- cwd,
- templateType: "multiagent",
- templateFramework,
- dataSource,
- vectorDb,
- port,
- externalPort,
- postInstallAction: templatePostInstallAction,
- templateUI,
- appType,
+ test.beforeAll(async () => {
+ port = Math.floor(Math.random() * 10000) + 10000;
+ externalPort = port + 1;
+ cwd = await createTestDir();
+ const result = await runCreateLlama({
+ cwd,
+ templateType: "multiagent",
+ templateFramework,
+ dataSource,
+ vectorDb,
+ port,
+ externalPort,
+ postInstallAction: templatePostInstallAction,
+ templateUI,
+ appType,
+ agents,
+ });
+ name = result.projectName;
+ appProcess = result.appProcess;
});
- name = result.projectName;
- appProcess = result.appProcess;
- });
- test("App folder should exist", async () => {
- const dirExists = fs.existsSync(path.join(cwd, name));
- expect(dirExists).toBeTruthy();
- });
+ test("App folder should exist", async () => {
+ const dirExists = fs.existsSync(path.join(cwd, name));
+ expect(dirExists).toBeTruthy();
+ });
- test("Frontend should have a title", async ({ page }) => {
- await page.goto(`http://localhost:${port}`);
- await expect(page.getByText("Built by LlamaIndex")).toBeVisible();
- });
+ test("Frontend should have a title", async ({ page }) => {
+ await page.goto(`http://localhost:${port}`);
+ await expect(page.getByText("Built by LlamaIndex")).toBeVisible();
+ });
- test("Frontend should be able to submit a message and receive the start of a streamed response", async ({
- page,
- }) => {
- await page.goto(`http://localhost:${port}`);
- await page.fill("form textarea", userMessage);
+ test("Frontend should be able to submit a message and receive the start of a streamed response", async ({
+ page,
+ }) => {
+ await page.goto(`http://localhost:${port}`);
+ await page.fill("form textarea", userMessage);
- const responsePromise = page.waitForResponse((res) =>
- res.url().includes("/api/chat"),
- );
+ const responsePromise = page.waitForResponse((res) =>
+ res.url().includes("/api/chat"),
+ );
- await page.click("form button[type=submit]");
+ await page.click("form button[type=submit]");
- const response = await responsePromise;
- expect(response.ok()).toBeTruthy();
- });
+ const response = await responsePromise;
+ expect(response.ok()).toBeTruthy();
+ });
- // clean processes
- test.afterAll(async () => {
- appProcess?.kill();
+ // clean processes
+ test.afterAll(async () => {
+ appProcess?.kill();
+ });
});
-});
+}
diff --git a/e2e/utils.ts b/e2e/utils.ts
index 44a40d11ad99a1412d5a78c25ebe7b23bf3b3b2c..a835f0f20f8699791b07f186f5f8229ed1fb2da1 100644
--- a/e2e/utils.ts
+++ b/e2e/utils.ts
@@ -34,6 +34,7 @@ export type RunCreateLlamaOptions = {
tools?: string;
useLlamaParse?: boolean;
observability?: string;
+ agents?: string;
};
export async function runCreateLlama({
@@ -52,6 +53,7 @@ export async function runCreateLlama({
tools,
useLlamaParse,
observability,
+ agents,
}: RunCreateLlamaOptions): Promise<CreateLlamaResult> {
if (!process.env.OPENAI_API_KEY || !process.env.LLAMA_CLOUD_API_KEY) {
throw new Error(
@@ -119,6 +121,9 @@ export async function runCreateLlama({
if (observability) {
commandArgs.push("--observability", observability);
}
+ if (templateType === "multiagent" && agents) {
+ commandArgs.push("--agents", agents);
+ }
const command = commandArgs.join(" ");
console.log(`running command '${command}' in ${cwd}`);
diff --git a/helpers/datasources.ts b/helpers/datasources.ts
index dc80207e43bf6061f97f4ac40d27734cba6d6b1b..80b936b0db3cb914bcff2709cadefce3626c7ed8 100644
--- a/helpers/datasources.ts
+++ b/helpers/datasources.ts
@@ -11,6 +11,25 @@ export const EXAMPLE_FILE: TemplateDataSource = {
},
};
+export const EXAMPLE_10K_SEC_FILES: TemplateDataSource[] = [
+ {
+ type: "file",
+ config: {
+ url: new URL(
+ "https://s2.q4cdn.com/470004039/files/doc_earnings/2023/q4/filing/_10-K-Q4-2023-As-Filed.pdf",
+ ),
+ },
+ },
+ {
+ type: "file",
+ config: {
+ url: new URL(
+ "https://ir.tesla.com/_flysystem/s3/sec/000162828024002390/tsla-20231231-gen.pdf",
+ ),
+ },
+ },
+];
+
export function getDataSources(
files?: string,
exampleFile?: boolean,
diff --git a/helpers/index.ts b/helpers/index.ts
index 56d07808f92480d2fe771429af73521eac52d05f..8525455d444503432babdde672a5df644073e9cd 100644
--- a/helpers/index.ts
+++ b/helpers/index.ts
@@ -96,6 +96,12 @@ async function generateContextData(
}
}
+const downloadFile = async (url: string, destPath: string) => {
+ const response = await fetch(url);
+ const fileBuffer = await response.arrayBuffer();
+ await fsExtra.writeFile(destPath, Buffer.from(fileBuffer));
+};
+
const prepareContextData = async (
root: string,
dataSources: TemplateDataSource[],
@@ -103,12 +109,28 @@ const prepareContextData = async (
await makeDir(path.join(root, "data"));
for (const dataSource of dataSources) {
const dataSourceConfig = dataSource?.config as FileSourceConfig;
- // Copy local data
- const dataPath = dataSourceConfig.path;
-
- const destPath = path.join(root, "data", path.basename(dataPath));
- console.log("Copying data from path:", dataPath);
- await fsExtra.copy(dataPath, destPath);
+ // If the path is URLs, download the data and save it to the data directory
+ if ("url" in dataSourceConfig) {
+ console.log(
+ "Downloading file from URL:",
+ dataSourceConfig.url.toString(),
+ );
+ const destPath = path.join(
+ root,
+ "data",
+ path.basename(dataSourceConfig.url.toString()),
+ );
+ await downloadFile(dataSourceConfig.url.toString(), destPath);
+ } else {
+ // Copy local data
+ console.log("Copying data from path:", dataSourceConfig.path);
+ const destPath = path.join(
+ root,
+ "data",
+ path.basename(dataSourceConfig.path),
+ );
+ await fsExtra.copy(dataSourceConfig.path, destPath);
+ }
}
};
diff --git a/helpers/python.ts b/helpers/python.ts
index 58908276bdc6ebed5355606234a1931c94364a4f..6305739a21804703baee60358b03e720ecaeebda 100644
--- a/helpers/python.ts
+++ b/helpers/python.ts
@@ -362,6 +362,7 @@ export const installPythonTemplate = async ({
postInstallAction,
observability,
modelConfig,
+ agents,
}: Pick<
InstallTemplateArgs,
| "root"
@@ -373,6 +374,7 @@ export const installPythonTemplate = async ({
| "postInstallAction"
| "observability"
| "modelConfig"
+ | "agents"
>) => {
console.log("\nInitializing Python project with template:", template, "\n");
let templatePath;
@@ -443,6 +445,24 @@ export const installPythonTemplate = async ({
cwd: path.join(compPath, "engines", "python", engine),
});
+ // Copy agent code
+ if (template === "multiagent") {
+ if (agents) {
+ await copy("**", path.join(root), {
+ parents: true,
+ cwd: path.join(compPath, "agents", "python", agents),
+ 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);
+ }
+ }
+
// Copy router code
await copyRouterCode(root, tools ?? []);
}
diff --git a/helpers/types.ts b/helpers/types.ts
index 89dd96644349b5fff06494babe5699e98d2c55fd..30a2ab357601d654f4848e8c736439f6bced6c71 100644
--- a/helpers/types.ts
+++ b/helpers/types.ts
@@ -48,10 +48,15 @@ export type TemplateDataSource = {
};
export type TemplateDataSourceType = "file" | "web" | "db";
export type TemplateObservability = "none" | "traceloop" | "llamatrace";
+export type TemplateAgents = "financial_report" | "blog";
// Config for both file and folder
-export type FileSourceConfig = {
- path: string;
-};
+export type FileSourceConfig =
+ | {
+ path: string;
+ }
+ | {
+ url: URL;
+ };
export type WebSourceConfig = {
baseUrl?: string;
prefix?: string;
@@ -94,4 +99,5 @@ export interface InstallTemplateArgs {
postInstallAction?: TemplatePostInstallAction;
tools?: Tool[];
observability?: TemplateObservability;
+ agents?: TemplateAgents;
}
diff --git a/index.ts b/index.ts
index 6ee0edeb13fa3403c4f7eaf369f83e322bca6146..de7f5b6492b8d3ee39dae666e8ad760fc9db8a08 100644
--- a/index.ts
+++ b/index.ts
@@ -208,6 +208,13 @@ const program = new Command(packageJson.name)
`,
false,
)
+ .option(
+ "--agents <agents>",
+ `
+
+ Select which agents to use for the multi-agent template (e.g: financial_report, blog).
+`,
+ )
.allowUnknownOption()
.parse(process.argv);
diff --git a/questions/simple.ts b/questions/simple.ts
index 29930c1aefb244bd773c843eed7a73891558213c..195e30d8c18141e6e6085b26f3003bca30429361 100644
--- a/questions/simple.ts
+++ b/questions/simple.ts
@@ -1,5 +1,5 @@
import prompts from "prompts";
-import { EXAMPLE_FILE } from "../helpers/datasources";
+import { EXAMPLE_10K_SEC_FILES, EXAMPLE_FILE } from "../helpers/datasources";
import { askModelConfig } from "../helpers/providers";
import { getTools } from "../helpers/tools";
import { ModelConfig, TemplateFramework } from "../helpers/types";
@@ -9,7 +9,7 @@ import { askPostInstallAction, questionHandlers } from "./utils";
type AppType =
| "rag"
| "code_artifact"
- | "multiagent"
+ | "financial_report_agent"
| "extractor"
| "data_scientist";
@@ -31,8 +31,11 @@ export const askSimpleQuestions = async (
choices: [
{ title: "Agentic RAG", value: "rag" },
{ title: "Data Scientist", value: "data_scientist" },
+ {
+ title: "Financial Report Generator (using Workflows)",
+ value: "financial_report_agent",
+ },
{ title: "Code Artifact Agent", value: "code_artifact" },
- { title: "Multi-Agent Report Gen", value: "multiagent" },
{ title: "Structured extraction", value: "extractor" },
],
},
@@ -42,20 +45,25 @@ export const askSimpleQuestions = async (
let language: TemplateFramework = "fastapi";
let llamaCloudKey = args.llamaCloudKey;
let useLlamaCloud = false;
+
if (appType !== "extractor") {
- 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;
+ // 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 { useLlamaCloud: newUseLlamaCloud } = await prompts(
{
@@ -113,7 +121,10 @@ const convertAnswers = async (
};
const lookup: Record<
AppType,
- Pick<QuestionResults, "template" | "tools" | "frontend" | "dataSources"> & {
+ Pick<
+ QuestionResults,
+ "template" | "tools" | "frontend" | "dataSources" | "agents"
+ > & {
modelConfig?: ModelConfig;
}
> = {
@@ -137,16 +148,13 @@ const convertAnswers = async (
dataSources: [],
modelConfig: MODEL_GPT4o,
},
- multiagent: {
+ financial_report_agent: {
template: "multiagent",
- tools: getTools([
- "document_generator",
- "wikipedia.WikipediaToolSpec",
- "duckduckgo",
- "img_gen",
- ]),
+ agents: "financial_report",
+ tools: getTools(["document_generator", "interpreter"]),
+ dataSources: EXAMPLE_10K_SEC_FILES,
frontend: true,
- dataSources: [EXAMPLE_FILE],
+ modelConfig: MODEL_GPT4o,
},
extractor: {
template: "extractor",
diff --git a/templates/components/multiagent/python/README-template.md b/templates/components/agents/python/blog/README-template.md
similarity index 89%
rename from templates/components/multiagent/python/README-template.md
rename to templates/components/agents/python/blog/README-template.md
index 761f19a4ddc2bf620c7180e8efedf9b26d53626c..162de0c8a3a2e75dfe72eb67b679965cdf45f874 100644
--- a/templates/components/multiagent/python/README-template.md
+++ b/templates/components/agents/python/blog/README-template.md
@@ -1,5 +1,3 @@
-This is a [LlamaIndex](https://www.llamaindex.ai/) multi-agents project using [Workflows](https://docs.llamaindex.ai/en/stable/understanding/workflows/).
-
## Overview
This example is using three agents to generate a blog post:
@@ -25,7 +23,6 @@ poetry install
```
Then check the parameters that have been pre-configured in the `.env` file in this directory. (E.g. you might need to configure an `OPENAI_API_KEY` if you're using OpenAI as model provider).
-
Second, generate the embeddings of the documents in the `./data` directory:
```shell
@@ -39,7 +36,6 @@ poetry run python main.py
```
Per default, the example is using the explicit workflow. You can change the example by setting the `EXAMPLE_TYPE` environment variable to `choreography` or `orchestrator`.
-
The example provides one streaming API endpoint `/api/chat`.
You can test the endpoint with the following curl request:
@@ -65,5 +61,4 @@ To learn more about LlamaIndex, take a look at the following resources:
- [LlamaIndex Documentation](https://docs.llamaindex.ai) - learn about LlamaIndex.
- [Workflows Introduction](https://docs.llamaindex.ai/en/stable/understanding/workflows/) - learn about LlamaIndex workflows.
-
-You can check out [the LlamaIndex GitHub repository](https://github.com/run-llama/llama_index) - your feedback and contributions are welcome!
+ You can check out [the LlamaIndex GitHub repository](https://github.com/run-llama/llama_index) - your feedback and contributions are welcome!
diff --git a/templates/components/multiagent/python/app/examples/choreography.py b/templates/components/agents/python/blog/app/agents/choreography.py
similarity index 90%
rename from templates/components/multiagent/python/app/examples/choreography.py
rename to templates/components/agents/python/blog/app/agents/choreography.py
index b194c20b73b47703c0aacde618e413fa5325cb6e..ce43388e071330678946fbf9c16363b9df616db7 100644
--- a/templates/components/multiagent/python/app/examples/choreography.py
+++ b/templates/components/agents/python/blog/app/agents/choreography.py
@@ -1,10 +1,10 @@
from textwrap import dedent
from typing import List, Optional
-from app.agents.multi import AgentCallingAgent
-from app.agents.single import FunctionCallingAgent
-from app.examples.publisher import create_publisher
-from app.examples.researcher import create_researcher
+from app.agents.publisher import create_publisher
+from app.agents.researcher import create_researcher
+from app.workflows.multi import AgentCallingAgent
+from app.workflows.single import FunctionCallingAgent
from llama_index.core.chat_engine.types import ChatMessage
diff --git a/templates/components/multiagent/python/app/examples/orchestrator.py b/templates/components/agents/python/blog/app/agents/orchestrator.py
similarity index 90%
rename from templates/components/multiagent/python/app/examples/orchestrator.py
rename to templates/components/agents/python/blog/app/agents/orchestrator.py
index 7cf74c0cb1e1209c8dfd40286f19857dc8fdeb66..c4593ea44243df83f04fea6f6cb4fc32acd60b7f 100644
--- a/templates/components/multiagent/python/app/examples/orchestrator.py
+++ b/templates/components/agents/python/blog/app/agents/orchestrator.py
@@ -1,10 +1,10 @@
from textwrap import dedent
from typing import List, Optional
-from app.agents.multi import AgentOrchestrator
-from app.agents.single import FunctionCallingAgent
-from app.examples.publisher import create_publisher
-from app.examples.researcher import create_researcher
+from app.agents.publisher import create_publisher
+from app.agents.researcher import create_researcher
+from app.workflows.multi import AgentOrchestrator
+from app.workflows.single import FunctionCallingAgent
from llama_index.core.chat_engine.types import ChatMessage
diff --git a/templates/components/multiagent/python/app/examples/publisher.py b/templates/components/agents/python/blog/app/agents/publisher.py
similarity index 96%
rename from templates/components/multiagent/python/app/examples/publisher.py
rename to templates/components/agents/python/blog/app/agents/publisher.py
index 2a170d88680d01b18523a5804ca78a24199fa244..5dfc6c7781d777c39181c405c98d165819baf4a1 100644
--- a/templates/components/multiagent/python/app/examples/publisher.py
+++ b/templates/components/agents/python/blog/app/agents/publisher.py
@@ -1,8 +1,8 @@
from textwrap import dedent
from typing import List, Tuple
-from app.agents.single import FunctionCallingAgent
from app.engine.tools import ToolFactory
+from app.workflows.single import FunctionCallingAgent
from llama_index.core.chat_engine.types import ChatMessage
from llama_index.core.tools import FunctionTool
diff --git a/templates/components/multiagent/python/app/examples/researcher.py b/templates/components/agents/python/blog/app/agents/researcher.py
similarity index 98%
rename from templates/components/multiagent/python/app/examples/researcher.py
rename to templates/components/agents/python/blog/app/agents/researcher.py
index abcc2da385f19c793265780ae1480d8b1700b911..3b9ba5ed6665ff34de7a7efb109e7a12acc510a5 100644
--- a/templates/components/multiagent/python/app/examples/researcher.py
+++ b/templates/components/agents/python/blog/app/agents/researcher.py
@@ -2,9 +2,9 @@ import os
from textwrap import dedent
from typing import List
-from app.agents.single import FunctionCallingAgent
from app.engine.index import IndexConfig, get_index
from app.engine.tools import ToolFactory
+from app.workflows.single import FunctionCallingAgent
from llama_index.core.chat_engine.types import ChatMessage
from llama_index.core.tools import QueryEngineTool, ToolMetadata
diff --git a/templates/components/multiagent/python/app/examples/workflow.py b/templates/components/agents/python/blog/app/agents/workflow.py
similarity index 98%
rename from templates/components/multiagent/python/app/examples/workflow.py
rename to templates/components/agents/python/blog/app/agents/workflow.py
index 89bd6dbafd5e2f7749b0e5cf2ef06b77898fe86c..c7bfbe51e6370b0c1405afd4713ec5dfdfe8c275 100644
--- a/templates/components/multiagent/python/app/examples/workflow.py
+++ b/templates/components/agents/python/blog/app/agents/workflow.py
@@ -1,9 +1,9 @@
from textwrap import dedent
from typing import AsyncGenerator, List, Optional
-from app.agents.single import AgentRunEvent, AgentRunResult, FunctionCallingAgent
-from app.examples.publisher import create_publisher
-from app.examples.researcher import create_researcher
+from app.agents.publisher import create_publisher
+from app.agents.researcher import create_researcher
+from app.workflows.single import AgentRunEvent, AgentRunResult, FunctionCallingAgent
from llama_index.core.chat_engine.types import ChatMessage
from llama_index.core.prompts import PromptTemplate
from llama_index.core.settings import Settings
diff --git a/templates/components/multiagent/python/app/engine/engine.py b/templates/components/agents/python/blog/app/engine/engine.py
similarity index 82%
rename from templates/components/multiagent/python/app/engine/engine.py
rename to templates/components/agents/python/blog/app/engine/engine.py
index 506179a02cf1d596d98a08e6175a28487620da70..78a79c4593494c8cb4382d2760d3962234b825f4 100644
--- a/templates/components/multiagent/python/app/engine/engine.py
+++ b/templates/components/agents/python/blog/app/engine/engine.py
@@ -2,9 +2,9 @@ import logging
import os
from typing import List, Optional
-from app.examples.choreography import create_choreography
-from app.examples.orchestrator import create_orchestrator
-from app.examples.workflow import create_workflow
+from app.agents.choreography import create_choreography
+from app.agents.orchestrator import create_orchestrator
+from app.agents.workflow import create_workflow
from llama_index.core.chat_engine.types import ChatMessage
from llama_index.core.workflow import Workflow
diff --git a/templates/components/agents/python/financial_report/README-template.md b/templates/components/agents/python/financial_report/README-template.md
new file mode 100644
index 0000000000000000000000000000000000000000..ba6d24fba8d3ae42637a680222dff0bba91060c4
--- /dev/null
+++ b/templates/components/agents/python/financial_report/README-template.md
@@ -0,0 +1,53 @@
+This is a [LlamaIndex](https://www.llamaindex.ai/) multi-agents project using [Workflows](https://docs.llamaindex.ai/en/stable/understanding/workflows/).
+
+## Getting Started
+
+First, setup the environment with poetry:
+
+> **_Note:_** This step is not needed if you are using the dev-container.
+
+```shell
+poetry install
+```
+
+Then check the parameters that have been pre-configured in the `.env` file in this directory. (E.g. you might need to configure an `OPENAI_API_KEY` if you're using OpenAI as model provider and `E2B_API_KEY` for the [E2B's code interpreter tool](https://e2b.dev/docs)).
+
+Second, generate the embeddings of the documents in the `./data` directory:
+
+```shell
+poetry run generate
+```
+
+Third, run the development server:
+
+```shell
+poetry run python main.py
+```
+
+The example provides one streaming API endpoint `/api/chat`.
+You can test the endpoint with the following curl request:
+
+```
+curl --location 'localhost:8000/api/chat' \
+--header 'Content-Type: application/json' \
+--data '{ "messages": [{ "role": "user", "content": "Create a report comparing the finances of Apple and Tesla" }] }'
+```
+
+You can start editing the API by modifying `app/api/routers/chat.py` or `app/financial_report/workflow.py`. The API auto-updates as you save the files.
+
+Open [http://localhost:8000/docs](http://localhost:8000/docs) with your browser to see the Swagger UI of the API.
+
+The API allows CORS for all origins to simplify development. You can change this behavior by setting the `ENVIRONMENT` environment variable to `prod`:
+
+```
+ENVIRONMENT=prod poetry run python main.py
+```
+
+## Learn More
+
+To learn more about LlamaIndex, take a look at the following resources:
+
+- [LlamaIndex Documentation](https://docs.llamaindex.ai) - learn about LlamaIndex.
+- [Workflows Introduction](https://docs.llamaindex.ai/en/stable/understanding/workflows/) - learn about LlamaIndex workflows.
+
+You can check out [the LlamaIndex GitHub repository](https://github.com/run-llama/llama_index) - your feedback and contributions are welcome!
diff --git a/templates/components/agents/python/financial_report/app/agents/analyst.py b/templates/components/agents/python/financial_report/app/agents/analyst.py
new file mode 100644
index 0000000000000000000000000000000000000000..f86b10d92af12d06eb8a62221659de31262e7766
--- /dev/null
+++ b/templates/components/agents/python/financial_report/app/agents/analyst.py
@@ -0,0 +1,47 @@
+from textwrap import dedent
+from typing import List, Tuple
+
+from app.engine.tools import ToolFactory
+from app.workflows.single import FunctionCallingAgent
+from llama_index.core.chat_engine.types import ChatMessage
+from llama_index.core.tools import FunctionTool
+
+
+def _get_analyst_params() -> Tuple[List[type[FunctionTool]], str, str]:
+ tools = []
+ prompt_instructions = dedent(
+ """
+ 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 a textual format like 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.
+ """
+ )
+ description = "Expert in analyzing financial data"
+ configured_tools = ToolFactory.from_env(map_result=True)
+ # Check if the interpreter tool is configured
+ if "interpreter" in configured_tools.keys():
+ tools.extend(configured_tools["interpreter"])
+ prompt_instructions += dedent("""
+ You are able to visualize the financial data using code interpreter tool.
+ It's very useful to create and include visualizations to the report (make sure you include the right code and data for the visualization).
+ Never include any code into the report, just the visualization.
+ """)
+ description += (
+ ", able to visualize the financial data using code interpreter tool."
+ )
+ return tools, prompt_instructions, description
+
+
+def create_analyst(chat_history: List[ChatMessage]):
+ tools, prompt_instructions, description = _get_analyst_params()
+
+ return FunctionCallingAgent(
+ name="analyst",
+ tools=tools,
+ description=description,
+ system_prompt=dedent(prompt_instructions),
+ chat_history=chat_history,
+ )
diff --git a/templates/components/agents/python/financial_report/app/agents/reporter.py b/templates/components/agents/python/financial_report/app/agents/reporter.py
new file mode 100644
index 0000000000000000000000000000000000000000..b1337bb033c792a4268573ad73be68fc4fce0cbc
--- /dev/null
+++ b/templates/components/agents/python/financial_report/app/agents/reporter.py
@@ -0,0 +1,44 @@
+from textwrap import dedent
+from typing import List, Tuple
+
+from app.engine.tools import ToolFactory
+from app.workflows.single import FunctionCallingAgent
+from llama_index.core.chat_engine.types import ChatMessage
+from llama_index.core.tools import BaseTool
+
+
+def _get_reporter_params(
+ chat_history: List[ChatMessage],
+) -> Tuple[List[type[BaseTool]], str, str]:
+ tools: List[type[BaseTool]] = []
+ description = "Expert in representing a financial report"
+ prompt_instructions = dedent(
+ """
+ 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 provided, add them to the right sections that are most relevant.
+ Use only the provided information to create the report. Do not make up any information yourself.
+ Finally, the report should be presented in markdown format.
+ """
+ )
+ configured_tools = ToolFactory.from_env(map_result=True)
+ if "document_generator" in configured_tools: # type: ignore
+ tools.extend(configured_tools["document_generator"]) # type: ignore
+ prompt_instructions += (
+ "\nYou are also able to generate a file document (PDF/HTML) of the report."
+ )
+ description += " and generate a file document (PDF/HTML) of the report."
+ return tools, description, prompt_instructions
+
+
+def create_reporter(chat_history: List[ChatMessage]):
+ tools, description, prompt_instructions = _get_reporter_params(chat_history)
+ return FunctionCallingAgent(
+ name="reporter",
+ tools=tools,
+ description=description,
+ system_prompt=prompt_instructions,
+ chat_history=chat_history,
+ )
diff --git a/templates/components/agents/python/financial_report/app/agents/researcher.py b/templates/components/agents/python/financial_report/app/agents/researcher.py
new file mode 100644
index 0000000000000000000000000000000000000000..4d1459a5f790b7329c43e43a3c4dda8a35179f08
--- /dev/null
+++ b/templates/components/agents/python/financial_report/app/agents/researcher.py
@@ -0,0 +1,105 @@
+import os
+from textwrap import dedent
+from typing import List, Optional
+
+from app.engine.index import IndexConfig, get_index
+from app.workflows.single import FunctionCallingAgent
+from llama_index.core.chat_engine.types import ChatMessage
+from llama_index.core.tools import BaseTool, QueryEngineTool, ToolMetadata
+from llama_index.indices.managed.llama_cloud import LlamaCloudIndex
+
+
+def _create_query_engine_tools(params=None) -> Optional[list[type[BaseTool]]]:
+ """
+ Provide an agent worker that can be used to query the index.
+ """
+ # Add query tool if index exists
+ index_config = IndexConfig(**(params or {}))
+ index = get_index(index_config)
+ if index is None:
+ return None
+
+ top_k = int(os.getenv("TOP_K", 5))
+
+ # Construct query engine tools
+ tools = []
+ # If index is LlamaCloudIndex, we need to add chunk and doc retriever tools
+ if isinstance(index, LlamaCloudIndex):
+ # Document retriever
+ doc_retriever = index.as_query_engine(
+ retriever_mode="files_via_content",
+ similarity_top_k=top_k,
+ )
+ chunk_retriever = index.as_query_engine(
+ retriever_mode="chunks",
+ similarity_top_k=top_k,
+ )
+ tools.append(
+ QueryEngineTool(
+ query_engine=doc_retriever,
+ metadata=ToolMetadata(
+ name="document_retriever",
+ description=dedent(
+ """
+ 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.
+ """
+ ),
+ ),
+ )
+ )
+ tools.append(
+ QueryEngineTool(
+ query_engine=chunk_retriever,
+ metadata=ToolMetadata(
+ name="chunk_retriever",
+ description=dedent(
+ """
+ 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:
+ query_engine = index.as_query_engine(
+ **({"similarity_top_k": top_k} if top_k != 0 else {})
+ )
+ tools.append(
+ QueryEngineTool(
+ query_engine=query_engine,
+ metadata=ToolMetadata(
+ name="retrieve_information",
+ description="Use this tool to retrieve information about the text corpus from the index.",
+ ),
+ )
+ )
+ return tools
+
+
+def create_researcher(chat_history: List[ChatMessage], **kwargs):
+ """
+ Researcher is an agent that take responsibility for using tools to complete a given task.
+ """
+ tools = _create_query_engine_tools(**kwargs)
+
+ if tools is None:
+ raise ValueError("No tools found for researcher agent")
+
+ return FunctionCallingAgent(
+ name="researcher",
+ tools=tools,
+ description="expert in retrieving any unknown content from the corpus",
+ system_prompt=dedent(
+ """
+ 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 response with: "There is no new information, please reuse the information from the conversation."
+ """
+ ),
+ chat_history=chat_history,
+ )
diff --git a/templates/components/agents/python/financial_report/app/agents/workflow.py b/templates/components/agents/python/financial_report/app/agents/workflow.py
new file mode 100644
index 0000000000000000000000000000000000000000..d995bab2eae5310fd2eb99f764968912c32c88be
--- /dev/null
+++ b/templates/components/agents/python/financial_report/app/agents/workflow.py
@@ -0,0 +1,175 @@
+from textwrap import dedent
+from typing import AsyncGenerator, List, Optional
+
+from app.agents.analyst import create_analyst
+from app.agents.reporter import create_reporter
+from app.agents.researcher import create_researcher
+from app.workflows.single import AgentRunEvent, AgentRunResult, FunctionCallingAgent
+from llama_index.core.chat_engine.types import ChatMessage
+from llama_index.core.prompts import PromptTemplate
+from llama_index.core.settings import Settings
+from llama_index.core.workflow import (
+ Context,
+ Event,
+ StartEvent,
+ StopEvent,
+ Workflow,
+ step,
+)
+
+
+def create_workflow(chat_history: Optional[List[ChatMessage]] = None, **kwargs):
+ researcher = create_researcher(
+ chat_history=chat_history,
+ **kwargs,
+ )
+
+ analyst = create_analyst(chat_history=chat_history)
+
+ reporter = create_reporter(chat_history=chat_history)
+
+ workflow = FinancialReportWorkflow(timeout=360, chat_history=chat_history)
+
+ workflow.add_workflows(
+ researcher=researcher,
+ analyst=analyst,
+ reporter=reporter,
+ )
+ return workflow
+
+
+class ResearchEvent(Event):
+ input: str
+
+
+class AnalyzeEvent(Event):
+ input: str
+
+
+class ReportEvent(Event):
+ input: str
+
+
+class FinancialReportWorkflow(Workflow):
+ def __init__(
+ self, timeout: int = 360, chat_history: Optional[List[ChatMessage]] = None
+ ):
+ super().__init__(timeout=timeout)
+ self.chat_history = chat_history or []
+
+ @step()
+ async def start(self, ctx: Context, ev: StartEvent) -> ResearchEvent | ReportEvent:
+ # set streaming
+ ctx.data["streaming"] = getattr(ev, "streaming", False)
+ # start the workflow with researching about a topic
+ ctx.data["task"] = ev.input
+ ctx.data["user_input"] = ev.input
+
+ # Decision-making process
+ decision = await self._decide_workflow(ev.input, self.chat_history)
+
+ if decision != "publish":
+ return ResearchEvent(input=f"Research for this task: {ev.input}")
+ else:
+ chat_history_str = "\n".join(
+ [f"{msg.role}: {msg.content}" for msg in self.chat_history]
+ )
+ return ReportEvent(
+ input=f"Create a report based on the chat history\n{chat_history_str}\n\n and task: {ev.input}"
+ )
+
+ async def _decide_workflow(
+ self, input: str, chat_history: List[ChatMessage]
+ ) -> str:
+ # TODO: Refactor this by using prompt generation
+ prompt_template = PromptTemplate(
+ dedent(
+ """
+ You are an expert in decision-making, helping people create financial reports for the provided data.
+ If the user doesn't need to add or update anything, respond with 'publish'.
+ Otherwise, respond with 'research'.
+
+ Here is the chat history:
+ {chat_history}
+
+ The current user request is:
+ {input}
+
+ Given the chat history and the new user request, decide whether to create a report based on existing information.
+ Decision (respond with either 'not_publish' or 'publish'):
+ """
+ )
+ )
+
+ chat_history_str = "\n".join(
+ [f"{msg.role}: {msg.content}" for msg in chat_history]
+ )
+ prompt = prompt_template.format(chat_history=chat_history_str, input=input)
+
+ output = await Settings.llm.acomplete(prompt)
+ decision = output.text.strip().lower()
+
+ return "publish" if decision == "publish" else "research"
+
+ @step()
+ async def research(
+ self, ctx: Context, ev: ResearchEvent, researcher: FunctionCallingAgent
+ ) -> AnalyzeEvent:
+ result: AgentRunResult = await self.run_agent(ctx, researcher, ev.input)
+ content = result.response.message.content
+ return AnalyzeEvent(
+ input=dedent(
+ f"""
+ Given the following research content:
+ {content}
+ Provide a comprehensive analysis of the data for the user's request: {ctx.data["task"]}
+ """
+ )
+ )
+
+ @step()
+ async def analyze(
+ self, ctx: Context, ev: AnalyzeEvent, analyst: FunctionCallingAgent
+ ) -> ReportEvent | StopEvent:
+ result: AgentRunResult = await self.run_agent(ctx, analyst, ev.input)
+ content = result.response.message.content
+ return ReportEvent(
+ input=dedent(
+ f"""
+ Given the following analysis:
+ {content}
+ Create a report for the user's request: {ctx.data["task"]}
+ """
+ )
+ )
+
+ @step()
+ async def report(
+ self, ctx: Context, ev: ReportEvent, reporter: FunctionCallingAgent
+ ) -> StopEvent:
+ try:
+ result: AgentRunResult = await self.run_agent(ctx, reporter, ev.input)
+ return StopEvent(result=result)
+ except Exception as e:
+ ctx.write_event_to_stream(
+ AgentRunEvent(
+ name=reporter.name,
+ msg=f"Error creating a report: {e}",
+ )
+ )
+ return StopEvent(result=None)
+
+ async def run_agent(
+ self,
+ ctx: Context,
+ agent: FunctionCallingAgent,
+ input: str,
+ streaming: bool = False,
+ ) -> AgentRunResult | AsyncGenerator:
+ handler = agent.run(input=input, streaming=streaming)
+ # bubble all events while running the executor to the planner
+ async for event in handler.stream_events():
+ # Don't write the StopEvent from sub task to the stream
+ if type(event) is not StopEvent:
+ ctx.write_event_to_stream(event)
+ return await handler
diff --git a/templates/components/agents/python/financial_report/app/engine/engine.py b/templates/components/agents/python/financial_report/app/engine/engine.py
new file mode 100644
index 0000000000000000000000000000000000000000..0ea21ab29ae6a8581ede7b80d392e17a9bab2d87
--- /dev/null
+++ b/templates/components/agents/python/financial_report/app/engine/engine.py
@@ -0,0 +1,12 @@
+from typing import List, Optional
+
+from app.agents.workflow import create_workflow
+from llama_index.core.chat_engine.types import ChatMessage
+from llama_index.core.workflow import Workflow
+
+
+def get_chat_engine(
+ chat_history: Optional[List[ChatMessage]] = None, **kwargs
+) -> Workflow:
+ agent_workflow = create_workflow(chat_history, **kwargs)
+ return agent_workflow
diff --git a/templates/components/multiagent/python/app/api/routers/vercel_response.py b/templates/components/multiagent/python/app/api/routers/vercel_response.py
index 82f2e7056aba5bd63022cb129425d60d9656509f..2c23b6a758bb0ced0b6f308bd83cb9b0c497c310 100644
--- a/templates/components/multiagent/python/app/api/routers/vercel_response.py
+++ b/templates/components/multiagent/python/app/api/routers/vercel_response.py
@@ -4,9 +4,9 @@ import logging
from typing import AsyncGenerator, List
from aiostream import stream
-from app.agents.single import AgentRunEvent, AgentRunResult
from app.api.routers.models import ChatData, Message
from app.api.services.suggestion import NextQuestionSuggestion
+from app.workflows.single import AgentRunEvent, AgentRunResult
from fastapi import Request
from fastapi.responses import StreamingResponse
@@ -28,7 +28,6 @@ class VercelStreamResponse(StreamingResponse):
super().__init__(content=content)
async def content_generator(self, event_handler, events):
- logger.info("Starting content_generator")
stream = self._create_stream(
self.request, self.chat_data, event_handler, events
)
diff --git a/templates/components/multiagent/python/app/agents/multi.py b/templates/components/multiagent/python/app/workflows/multi.py
similarity index 96%
rename from templates/components/multiagent/python/app/agents/multi.py
rename to templates/components/multiagent/python/app/workflows/multi.py
index 1150385020d0f53f224474f403c3f837ca4ff36b..5ec62d0db75232ccaa8ea329939fb72304a744f8 100644
--- a/templates/components/multiagent/python/app/agents/multi.py
+++ b/templates/components/multiagent/python/app/workflows/multi.py
@@ -1,7 +1,7 @@
from typing import Any, List
-from app.agents.planner import StructuredPlannerAgent
-from app.agents.single import (
+from app.workflows.planner import StructuredPlannerAgent
+from app.workflows.single import (
AgentRunResult,
ContextAwareTool,
FunctionCallingAgent,
diff --git a/templates/components/multiagent/python/app/agents/planner.py b/templates/components/multiagent/python/app/workflows/planner.py
similarity index 99%
rename from templates/components/multiagent/python/app/agents/planner.py
rename to templates/components/multiagent/python/app/workflows/planner.py
index 8bb4fd721eec549639546f3c27e99051ef484927..339bb739b5cbe638934f2052f6c512982711d58f 100644
--- a/templates/components/multiagent/python/app/agents/planner.py
+++ b/templates/components/multiagent/python/app/workflows/planner.py
@@ -2,7 +2,7 @@ import uuid
from enum import Enum
from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple, Union
-from app.agents.single import AgentRunEvent, AgentRunResult, FunctionCallingAgent
+from app.workflows.single import AgentRunEvent, AgentRunResult, FunctionCallingAgent
from llama_index.core.agent.runner.planner import (
DEFAULT_INITIAL_PLAN_PROMPT,
DEFAULT_PLAN_REFINE_PROMPT,
diff --git a/templates/components/multiagent/python/app/agents/single.py b/templates/components/multiagent/python/app/workflows/single.py
similarity index 100%
rename from templates/components/multiagent/python/app/agents/single.py
rename to templates/components/multiagent/python/app/workflows/single.py