mirror of
https://github.com/run-llama/create-llama.git
synced 2026-07-18 13:05:55 -04:00
Compare commits
4 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 988bfc2a60 | |||
| 056e376ee0 | |||
| 819cccb11a | |||
| 8a5ece10c2 |
@@ -1,5 +1,11 @@
|
||||
# create-llama
|
||||
|
||||
## 0.1.2
|
||||
|
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### Patch Changes
|
||||
|
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- 056e376: Add support for displaying tool outputs (including weather widget as example)
|
||||
|
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## 0.1.1
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||||
|
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### Patch Changes
|
||||
|
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@@ -217,13 +217,7 @@ const getFrameworkEnvs = (
|
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name: "SYSTEM_PROMPT",
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description: `Custom system prompt.
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Example:
|
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SYSTEM_PROMPT="
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We have provided context information below.
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---------------------
|
||||
{context_str}
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||||
---------------------
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||||
Given this information, please answer the question: {query_str}
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"`,
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SYSTEM_PROMPT="You are a helpful assistant who helps users with their questions."`,
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},
|
||||
];
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||||
};
|
||||
|
||||
@@ -8,7 +8,7 @@ import { questionHandlers } from "../../questions";
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|
||||
const OPENAI_API_URL = "https://api.openai.com/v1";
|
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|
||||
const DEFAULT_MODEL = "gpt-4-turbo";
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const DEFAULT_MODEL = "gpt-3.5-turbo";
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const DEFAULT_EMBEDDING_MODEL = "text-embedding-3-large";
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||||
|
||||
export async function askOpenAIQuestions({
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|
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+44
-33
@@ -24,7 +24,7 @@ interface Dependency {
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const getAdditionalDependencies = (
|
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modelConfig: ModelConfig,
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vectorDb?: TemplateVectorDB,
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dataSource?: TemplateDataSource,
|
||||
dataSources?: TemplateDataSource[],
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||||
tools?: Tool[],
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||||
) => {
|
||||
const dependencies: Dependency[] = [];
|
||||
@@ -43,6 +43,7 @@ const getAdditionalDependencies = (
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name: "llama-index-vector-stores-postgres",
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version: "^0.1.1",
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||||
});
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||||
break;
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||||
}
|
||||
case "pinecone": {
|
||||
dependencies.push({
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||||
@@ -72,38 +73,43 @@ const getAdditionalDependencies = (
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}
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||||
|
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// Add data source dependencies
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const dataSourceType = dataSource?.type;
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switch (dataSourceType) {
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case "file":
|
||||
dependencies.push({
|
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name: "docx2txt",
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version: "^0.8",
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});
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break;
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||||
case "web":
|
||||
dependencies.push({
|
||||
name: "llama-index-readers-web",
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||||
version: "^0.1.6",
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||||
});
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||||
break;
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||||
case "db":
|
||||
dependencies.push({
|
||||
name: "llama-index-readers-database",
|
||||
version: "^0.1.3",
|
||||
});
|
||||
dependencies.push({
|
||||
name: "pymysql",
|
||||
version: "^1.1.0",
|
||||
extras: ["rsa"],
|
||||
});
|
||||
dependencies.push({
|
||||
name: "psycopg2",
|
||||
version: "^2.9.9",
|
||||
});
|
||||
break;
|
||||
if (dataSources) {
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for (const ds of dataSources) {
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const dsType = ds?.type;
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switch (dsType) {
|
||||
case "file":
|
||||
dependencies.push({
|
||||
name: "docx2txt",
|
||||
version: "^0.8",
|
||||
});
|
||||
break;
|
||||
case "web":
|
||||
dependencies.push({
|
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name: "llama-index-readers-web",
|
||||
version: "^0.1.6",
|
||||
});
|
||||
break;
|
||||
case "db":
|
||||
dependencies.push({
|
||||
name: "llama-index-readers-database",
|
||||
version: "^0.1.3",
|
||||
});
|
||||
dependencies.push({
|
||||
name: "pymysql",
|
||||
version: "^1.1.0",
|
||||
extras: ["rsa"],
|
||||
});
|
||||
dependencies.push({
|
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name: "psycopg2",
|
||||
version: "^2.9.9",
|
||||
});
|
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break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Add tools dependencies
|
||||
console.log("Adding tools dependencies");
|
||||
tools?.forEach((tool) => {
|
||||
tool.dependencies?.forEach((dep) => {
|
||||
dependencies.push(dep);
|
||||
@@ -298,9 +304,14 @@ export const installPythonTemplate = async ({
|
||||
cwd: path.join(compPath, "engines", "python", engine),
|
||||
});
|
||||
|
||||
const addOnDependencies = dataSources
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||||
.map((ds) => getAdditionalDependencies(modelConfig, vectorDb, ds, tools))
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||||
.flat();
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console.log("Adding additional dependencies");
|
||||
|
||||
const addOnDependencies = getAdditionalDependencies(
|
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modelConfig,
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vectorDb,
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dataSources,
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||||
tools,
|
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);
|
||||
|
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if (observability === "opentelemetry") {
|
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addOnDependencies.push({
|
||||
|
||||
+27
-2
@@ -5,12 +5,18 @@ import yaml from "yaml";
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import { makeDir } from "./make-dir";
|
||||
import { TemplateFramework } from "./types";
|
||||
|
||||
export enum ToolType {
|
||||
LLAMAHUB = "llamahub",
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||||
LOCAL = "local",
|
||||
}
|
||||
|
||||
export type Tool = {
|
||||
display: string;
|
||||
name: string;
|
||||
config?: Record<string, any>;
|
||||
dependencies?: ToolDependencies[];
|
||||
supportedFrameworks?: Array<TemplateFramework>;
|
||||
type: ToolType;
|
||||
};
|
||||
|
||||
export type ToolDependencies = {
|
||||
@@ -35,6 +41,7 @@ export const supportedTools: Tool[] = [
|
||||
},
|
||||
],
|
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supportedFrameworks: ["fastapi"],
|
||||
type: ToolType.LLAMAHUB,
|
||||
},
|
||||
{
|
||||
display: "Wikipedia",
|
||||
@@ -46,6 +53,14 @@ export const supportedTools: Tool[] = [
|
||||
},
|
||||
],
|
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supportedFrameworks: ["fastapi", "express", "nextjs"],
|
||||
type: ToolType.LLAMAHUB,
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||||
},
|
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{
|
||||
display: "Weather",
|
||||
name: "weather",
|
||||
dependencies: [],
|
||||
supportedFrameworks: ["fastapi", "express", "nextjs"],
|
||||
type: ToolType.LOCAL,
|
||||
},
|
||||
];
|
||||
|
||||
@@ -90,9 +105,19 @@ export const writeToolsConfig = async (
|
||||
type: ConfigFileType = ConfigFileType.YAML,
|
||||
) => {
|
||||
if (tools.length === 0) return; // no tools selected, no config need
|
||||
const configContent: Record<string, any> = {};
|
||||
const configContent: {
|
||||
[key in ToolType]: Record<string, any>;
|
||||
} = {
|
||||
local: {},
|
||||
llamahub: {},
|
||||
};
|
||||
tools.forEach((tool) => {
|
||||
configContent[tool.name] = tool.config ?? {};
|
||||
if (tool.type === ToolType.LLAMAHUB) {
|
||||
configContent.llamahub[tool.name] = tool.config ?? {};
|
||||
}
|
||||
if (tool.type === ToolType.LOCAL) {
|
||||
configContent.local[tool.name] = tool.config ?? {};
|
||||
}
|
||||
});
|
||||
const configPath = path.join(root, "config");
|
||||
await makeDir(configPath);
|
||||
|
||||
@@ -105,7 +105,7 @@ export const installTSTemplate = async ({
|
||||
const enginePath = path.join(root, relativeEngineDestPath, "engine");
|
||||
|
||||
// copy vector db component
|
||||
console.log("\nUsing vector DB:", vectorDb, "\n");
|
||||
console.log("\nUsing vector DB:", vectorDb ?? "none", "\n");
|
||||
await copy("**", enginePath, {
|
||||
parents: true,
|
||||
cwd: path.join(compPath, "vectordbs", "typescript", vectorDb ?? "none"),
|
||||
|
||||
+1
-1
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "create-llama",
|
||||
"version": "0.1.1",
|
||||
"version": "0.1.2",
|
||||
"description": "Create LlamaIndex-powered apps with one command",
|
||||
"keywords": [
|
||||
"rag",
|
||||
|
||||
@@ -1,35 +0,0 @@
|
||||
import os
|
||||
import yaml
|
||||
import importlib
|
||||
|
||||
from llama_index.core.tools.tool_spec.base import BaseToolSpec
|
||||
from llama_index.core.tools.function_tool import FunctionTool
|
||||
|
||||
|
||||
class ToolFactory:
|
||||
|
||||
@staticmethod
|
||||
def create_tool(tool_name: str, **kwargs) -> list[FunctionTool]:
|
||||
try:
|
||||
tool_package, tool_cls_name = tool_name.split(".")
|
||||
module_name = f"llama_index.tools.{tool_package}"
|
||||
module = importlib.import_module(module_name)
|
||||
tool_class = getattr(module, tool_cls_name)
|
||||
tool_spec: BaseToolSpec = tool_class(**kwargs)
|
||||
return tool_spec.to_tool_list()
|
||||
except (ImportError, AttributeError) as e:
|
||||
raise ValueError(f"Unsupported tool: {tool_name}") from e
|
||||
except TypeError as e:
|
||||
raise ValueError(
|
||||
f"Could not create tool: {tool_name}. With config: {kwargs}"
|
||||
) from e
|
||||
|
||||
@staticmethod
|
||||
def from_env() -> list[FunctionTool]:
|
||||
tools = []
|
||||
if os.path.exists("config/tools.yaml"):
|
||||
with open("config/tools.yaml", "r") as f:
|
||||
tool_configs = yaml.safe_load(f)
|
||||
for name, config in tool_configs.items():
|
||||
tools += ToolFactory.create_tool(name, **config)
|
||||
return tools
|
||||
@@ -0,0 +1,56 @@
|
||||
import os
|
||||
import yaml
|
||||
import importlib
|
||||
|
||||
from llama_index.core.tools.tool_spec.base import BaseToolSpec
|
||||
from llama_index.core.tools.function_tool import FunctionTool
|
||||
|
||||
|
||||
class ToolType:
|
||||
LLAMAHUB = "llamahub"
|
||||
LOCAL = "local"
|
||||
|
||||
|
||||
class ToolFactory:
|
||||
|
||||
TOOL_SOURCE_PACKAGE_MAP = {
|
||||
ToolType.LLAMAHUB: "llama_index.tools",
|
||||
ToolType.LOCAL: "app.engine.tools",
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def load_tools(tool_type: str, tool_name: str, config: dict) -> list[FunctionTool]:
|
||||
source_package = ToolFactory.TOOL_SOURCE_PACKAGE_MAP[tool_type]
|
||||
try:
|
||||
if "ToolSpec" in tool_name:
|
||||
tool_package, tool_cls_name = tool_name.split(".")
|
||||
module_name = f"{source_package}.{tool_package}"
|
||||
module = importlib.import_module(module_name)
|
||||
tool_class = getattr(module, tool_cls_name)
|
||||
tool_spec: BaseToolSpec = tool_class(**config)
|
||||
return tool_spec.to_tool_list()
|
||||
else:
|
||||
module = importlib.import_module(f"{source_package}.{tool_name}")
|
||||
tools = getattr(module, "tools")
|
||||
if not all(isinstance(tool, FunctionTool) for tool in tools):
|
||||
raise ValueError(
|
||||
f"The module {module} does not contain valid tools"
|
||||
)
|
||||
return tools
|
||||
except ImportError as e:
|
||||
raise ValueError(f"Failed to import tool {tool_name}: {e}")
|
||||
except AttributeError as e:
|
||||
raise ValueError(f"Failed to load tool {tool_name}: {e}")
|
||||
|
||||
@staticmethod
|
||||
def from_env() -> list[FunctionTool]:
|
||||
tools = []
|
||||
if os.path.exists("config/tools.yaml"):
|
||||
with open("config/tools.yaml", "r") as f:
|
||||
tool_configs = yaml.safe_load(f)
|
||||
for tool_type, config_entries in tool_configs.items():
|
||||
for tool_name, config in config_entries.items():
|
||||
tools.extend(
|
||||
ToolFactory.load_tools(tool_type, tool_name, config)
|
||||
)
|
||||
return tools
|
||||
@@ -0,0 +1,72 @@
|
||||
"""Open Meteo weather map tool spec."""
|
||||
|
||||
import logging
|
||||
import requests
|
||||
import pytz
|
||||
from llama_index.core.tools import FunctionTool
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class OpenMeteoWeather:
|
||||
geo_api = "https://geocoding-api.open-meteo.com/v1"
|
||||
weather_api = "https://api.open-meteo.com/v1"
|
||||
|
||||
@classmethod
|
||||
def _get_geo_location(cls, location: str) -> dict:
|
||||
"""Get geo location from location name."""
|
||||
params = {"name": location, "count": 10, "language": "en", "format": "json"}
|
||||
response = requests.get(f"{cls.geo_api}/search", params=params)
|
||||
if response.status_code != 200:
|
||||
raise Exception(f"Failed to fetch geo location: {response.status_code}")
|
||||
else:
|
||||
data = response.json()
|
||||
result = data["results"][0]
|
||||
geo_location = {
|
||||
"id": result["id"],
|
||||
"name": result["name"],
|
||||
"latitude": result["latitude"],
|
||||
"longitude": result["longitude"],
|
||||
}
|
||||
return geo_location
|
||||
|
||||
@classmethod
|
||||
def get_weather_information(cls, location: str) -> dict:
|
||||
"""Use this function to get the weather of any given location.
|
||||
Note that the weather code should follow WMO Weather interpretation codes (WW):
|
||||
0: Clear sky
|
||||
1, 2, 3: Mainly clear, partly cloudy, and overcast
|
||||
45, 48: Fog and depositing rime fog
|
||||
51, 53, 55: Drizzle: Light, moderate, and dense intensity
|
||||
56, 57: Freezing Drizzle: Light and dense intensity
|
||||
61, 63, 65: Rain: Slight, moderate and heavy intensity
|
||||
66, 67: Freezing Rain: Light and heavy intensity
|
||||
71, 73, 75: Snow fall: Slight, moderate, and heavy intensity
|
||||
77: Snow grains
|
||||
80, 81, 82: Rain showers: Slight, moderate, and violent
|
||||
85, 86: Snow showers slight and heavy
|
||||
95: Thunderstorm: Slight or moderate
|
||||
96, 99: Thunderstorm with slight and heavy hail
|
||||
"""
|
||||
logger.info(
|
||||
f"Calling open-meteo api to get weather information of location: {location}"
|
||||
)
|
||||
geo_location = cls._get_geo_location(location)
|
||||
timezone = pytz.timezone("UTC").zone
|
||||
params = {
|
||||
"latitude": geo_location["latitude"],
|
||||
"longitude": geo_location["longitude"],
|
||||
"current": "temperature_2m,weather_code",
|
||||
"hourly": "temperature_2m,weather_code",
|
||||
"daily": "weather_code",
|
||||
"timezone": timezone,
|
||||
}
|
||||
response = requests.get(f"{cls.weather_api}/forecast", params=params)
|
||||
if response.status_code != 200:
|
||||
raise Exception(
|
||||
f"Failed to fetch weather information: {response.status_code}"
|
||||
)
|
||||
return response.json()
|
||||
|
||||
|
||||
tools = [FunctionTool.from_defaults(OpenMeteoWeather.get_weather_information)]
|
||||
@@ -4,9 +4,10 @@ import fs from "node:fs/promises";
|
||||
import path from "node:path";
|
||||
import { getDataSource } from "./index";
|
||||
import { STORAGE_CACHE_DIR } from "./shared";
|
||||
import { createLocalTools } from "./tools";
|
||||
|
||||
export async function createChatEngine() {
|
||||
let tools: BaseToolWithCall[] = [];
|
||||
const tools: BaseToolWithCall[] = [];
|
||||
|
||||
// Add a query engine tool if we have a data source
|
||||
// Delete this code if you don't have a data source
|
||||
@@ -28,7 +29,14 @@ export async function createChatEngine() {
|
||||
const config = JSON.parse(
|
||||
await fs.readFile(path.join("config", "tools.json"), "utf8"),
|
||||
);
|
||||
tools = tools.concat(await ToolsFactory.createTools(config));
|
||||
|
||||
// add local tools from the 'tools' folder (if configured)
|
||||
const localTools = createLocalTools(config.local);
|
||||
tools.push(...localTools);
|
||||
|
||||
// add tools from LlamaIndexTS (if configured)
|
||||
const llamaTools = await ToolsFactory.createTools(config.llamahub);
|
||||
tools.push(...llamaTools);
|
||||
} catch {}
|
||||
|
||||
return new OpenAIAgent({
|
||||
|
||||
@@ -0,0 +1,26 @@
|
||||
import { BaseToolWithCall } from "llamaindex";
|
||||
import { WeatherTool, WeatherToolParams } from "./weather";
|
||||
|
||||
type ToolCreator = (config: unknown) => BaseToolWithCall;
|
||||
|
||||
const toolFactory: Record<string, ToolCreator> = {
|
||||
weather: (config: unknown) => {
|
||||
return new WeatherTool(config as WeatherToolParams);
|
||||
},
|
||||
};
|
||||
|
||||
export function createLocalTools(
|
||||
localConfig: Record<string, unknown>,
|
||||
): BaseToolWithCall[] {
|
||||
const tools: BaseToolWithCall[] = [];
|
||||
|
||||
Object.keys(localConfig).forEach((key) => {
|
||||
if (key in toolFactory) {
|
||||
const toolConfig = localConfig[key];
|
||||
const tool = toolFactory[key](toolConfig);
|
||||
tools.push(tool);
|
||||
}
|
||||
});
|
||||
|
||||
return tools;
|
||||
}
|
||||
@@ -0,0 +1,81 @@
|
||||
import type { JSONSchemaType } from "ajv";
|
||||
import { BaseTool, ToolMetadata } from "llamaindex";
|
||||
|
||||
interface GeoLocation {
|
||||
id: string;
|
||||
name: string;
|
||||
latitude: number;
|
||||
longitude: number;
|
||||
}
|
||||
|
||||
export type WeatherParameter = {
|
||||
location: string;
|
||||
};
|
||||
|
||||
export type WeatherToolParams = {
|
||||
metadata?: ToolMetadata<JSONSchemaType<WeatherParameter>>;
|
||||
};
|
||||
|
||||
const DEFAULT_META_DATA: ToolMetadata<JSONSchemaType<WeatherParameter>> = {
|
||||
name: "get_weather_information",
|
||||
description: `
|
||||
Use this function to get the weather of any given location.
|
||||
Note that the weather code should follow WMO Weather interpretation codes (WW):
|
||||
0: Clear sky
|
||||
1, 2, 3: Mainly clear, partly cloudy, and overcast
|
||||
45, 48: Fog and depositing rime fog
|
||||
51, 53, 55: Drizzle: Light, moderate, and dense intensity
|
||||
56, 57: Freezing Drizzle: Light and dense intensity
|
||||
61, 63, 65: Rain: Slight, moderate and heavy intensity
|
||||
66, 67: Freezing Rain: Light and heavy intensity
|
||||
71, 73, 75: Snow fall: Slight, moderate, and heavy intensity
|
||||
77: Snow grains
|
||||
80, 81, 82: Rain showers: Slight, moderate, and violent
|
||||
85, 86: Snow showers slight and heavy
|
||||
95: Thunderstorm: Slight or moderate
|
||||
96, 99: Thunderstorm with slight and heavy hail
|
||||
`,
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
location: {
|
||||
type: "string",
|
||||
description: "The location to get the weather information",
|
||||
},
|
||||
},
|
||||
required: ["location"],
|
||||
},
|
||||
};
|
||||
|
||||
export class WeatherTool implements BaseTool<WeatherParameter> {
|
||||
metadata: ToolMetadata<JSONSchemaType<WeatherParameter>>;
|
||||
|
||||
private getGeoLocation = async (location: string): Promise<GeoLocation> => {
|
||||
const apiUrl = `https://geocoding-api.open-meteo.com/v1/search?name=${location}&count=10&language=en&format=json`;
|
||||
const response = await fetch(apiUrl);
|
||||
const data = await response.json();
|
||||
const { id, name, latitude, longitude } = data.results[0];
|
||||
return { id, name, latitude, longitude };
|
||||
};
|
||||
|
||||
private getWeatherByLocation = async (location: string) => {
|
||||
console.log(
|
||||
"Calling open-meteo api to get weather information of location:",
|
||||
location,
|
||||
);
|
||||
const { latitude, longitude } = await this.getGeoLocation(location);
|
||||
const timezone = Intl.DateTimeFormat().resolvedOptions().timeZone;
|
||||
const apiUrl = `https://api.open-meteo.com/v1/forecast?latitude=${latitude}&longitude=${longitude}¤t=temperature_2m,weather_code&hourly=temperature_2m,weather_code&daily=weather_code&timezone=${timezone}`;
|
||||
const response = await fetch(apiUrl);
|
||||
const data = await response.json();
|
||||
return data;
|
||||
};
|
||||
|
||||
constructor(params?: WeatherToolParams) {
|
||||
this.metadata = params?.metadata || DEFAULT_META_DATA;
|
||||
}
|
||||
|
||||
async call(input: WeatherParameter) {
|
||||
return await this.getWeatherByLocation(input.location);
|
||||
}
|
||||
}
|
||||
@@ -14,8 +14,9 @@
|
||||
"cors": "^2.8.5",
|
||||
"dotenv": "^16.3.1",
|
||||
"express": "^4.18.2",
|
||||
"llamaindex": "0.3.3",
|
||||
"pdf2json": "3.0.5"
|
||||
"llamaindex": "0.3.7",
|
||||
"pdf2json": "3.0.5",
|
||||
"ajv": "^8.12.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/cors": "^2.8.16",
|
||||
|
||||
@@ -1,14 +1,9 @@
|
||||
import { Message, StreamData, streamToResponse } from "ai";
|
||||
import { Request, Response } from "express";
|
||||
import {
|
||||
CallbackManager,
|
||||
ChatMessage,
|
||||
MessageContent,
|
||||
Settings,
|
||||
} from "llamaindex";
|
||||
import { ChatMessage, MessageContent, Settings } from "llamaindex";
|
||||
import { createChatEngine } from "./engine/chat";
|
||||
import { LlamaIndexStream } from "./llamaindex-stream";
|
||||
import { appendEventData } from "./stream-helper";
|
||||
import { createCallbackManager } from "./stream-helper";
|
||||
|
||||
const convertMessageContent = (
|
||||
textMessage: string,
|
||||
@@ -52,18 +47,7 @@ export const chat = async (req: Request, res: Response) => {
|
||||
const vercelStreamData = new StreamData();
|
||||
|
||||
// Setup callbacks
|
||||
const callbackManager = new CallbackManager();
|
||||
callbackManager.on("retrieve", (data) => {
|
||||
const { nodes } = data.detail;
|
||||
appendEventData(
|
||||
vercelStreamData,
|
||||
`Retrieving context for query: '${userMessage.content}'`,
|
||||
);
|
||||
appendEventData(
|
||||
vercelStreamData,
|
||||
`Retrieved ${nodes.length} sources to use as context for the query`,
|
||||
);
|
||||
});
|
||||
const callbackManager = createCallbackManager(vercelStreamData);
|
||||
|
||||
// Calling LlamaIndex's ChatEngine to get a streamed response
|
||||
const response = await Settings.withCallbackManager(callbackManager, () => {
|
||||
|
||||
@@ -1,5 +1,11 @@
|
||||
import { StreamData } from "ai";
|
||||
import { Metadata, NodeWithScore } from "llamaindex";
|
||||
import {
|
||||
CallbackManager,
|
||||
Metadata,
|
||||
NodeWithScore,
|
||||
ToolCall,
|
||||
ToolOutput,
|
||||
} from "llamaindex";
|
||||
|
||||
export function appendImageData(data: StreamData, imageUrl?: string) {
|
||||
if (!imageUrl) return;
|
||||
@@ -37,3 +43,55 @@ export function appendEventData(data: StreamData, title?: string) {
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
export function appendToolData(
|
||||
data: StreamData,
|
||||
toolCall: ToolCall,
|
||||
toolOutput: ToolOutput,
|
||||
) {
|
||||
data.appendMessageAnnotation({
|
||||
type: "tools",
|
||||
data: {
|
||||
toolCall: {
|
||||
id: toolCall.id,
|
||||
name: toolCall.name,
|
||||
input: toolCall.input,
|
||||
},
|
||||
toolOutput: {
|
||||
output: toolOutput.output,
|
||||
isError: toolOutput.isError,
|
||||
},
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
export function createCallbackManager(stream: StreamData) {
|
||||
const callbackManager = new CallbackManager();
|
||||
|
||||
callbackManager.on("retrieve", (data) => {
|
||||
const { nodes, query } = data.detail;
|
||||
appendEventData(stream, `Retrieving context for query: '${query}'`);
|
||||
appendEventData(
|
||||
stream,
|
||||
`Retrieved ${nodes.length} sources to use as context for the query`,
|
||||
);
|
||||
});
|
||||
|
||||
callbackManager.on("llm-tool-call", (event) => {
|
||||
const { name, input } = event.detail.payload.toolCall;
|
||||
const inputString = Object.entries(input)
|
||||
.map(([key, value]) => `${key}: ${value}`)
|
||||
.join(", ");
|
||||
appendEventData(
|
||||
stream,
|
||||
`Using tool: '${name}' with inputs: '${inputString}'`,
|
||||
);
|
||||
});
|
||||
|
||||
callbackManager.on("llm-tool-result", (event) => {
|
||||
const { toolCall, toolResult } = event.detail.payload;
|
||||
appendToolData(stream, toolCall, toolResult);
|
||||
});
|
||||
|
||||
return callbackManager;
|
||||
}
|
||||
|
||||
@@ -1,10 +1,7 @@
|
||||
from pydantic import BaseModel
|
||||
from typing import List, Any, Optional, Dict, Tuple
|
||||
from fastapi import APIRouter, Depends, HTTPException, Request, status
|
||||
from llama_index.core.chat_engine.types import (
|
||||
BaseChatEngine,
|
||||
StreamingAgentChatResponse,
|
||||
)
|
||||
from llama_index.core.chat_engine.types import BaseChatEngine
|
||||
from llama_index.core.schema import NodeWithScore
|
||||
from llama_index.core.llms import ChatMessage, MessageRole
|
||||
from app.engine import get_chat_engine
|
||||
@@ -109,12 +106,9 @@ async def chat(
|
||||
# Yield the events from the event handler
|
||||
async def _event_generator():
|
||||
async for event in event_handler.async_event_gen():
|
||||
yield VercelStreamResponse.convert_data(
|
||||
{
|
||||
"type": "events",
|
||||
"data": {"title": event.get_title()},
|
||||
}
|
||||
)
|
||||
event_response = event.to_response()
|
||||
if event_response is not None:
|
||||
yield VercelStreamResponse.convert_data(event_response)
|
||||
|
||||
combine = stream.merge(_text_generator(), _event_generator())
|
||||
async with combine.stream() as streamer:
|
||||
|
||||
@@ -1,8 +1,9 @@
|
||||
import json
|
||||
import asyncio
|
||||
from typing import AsyncGenerator, Dict, Any, List, Optional
|
||||
|
||||
from llama_index.core.callbacks.base import BaseCallbackHandler
|
||||
from llama_index.core.callbacks.schema import CBEventType
|
||||
from llama_index.core.tools.types import ToolOutput
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
@@ -11,19 +12,73 @@ class CallbackEvent(BaseModel):
|
||||
payload: Optional[Dict[str, Any]] = None
|
||||
event_id: str = ""
|
||||
|
||||
def get_title(self) -> str | None:
|
||||
# Return as None for the unhandled event types
|
||||
# to avoid showing them in the UI
|
||||
def get_retrieval_message(self) -> dict | None:
|
||||
if self.payload:
|
||||
nodes = self.payload.get("nodes")
|
||||
if nodes:
|
||||
msg = f"Retrieved {len(nodes)} sources to use as context for the query"
|
||||
else:
|
||||
msg = f"Retrieving context for query: '{self.payload.get('query_str')}'"
|
||||
return {
|
||||
"type": "events",
|
||||
"data": {"title": msg},
|
||||
}
|
||||
else:
|
||||
return None
|
||||
|
||||
def get_tool_message(self) -> dict | None:
|
||||
func_call_args = self.payload.get("function_call")
|
||||
if func_call_args is not None and "tool" in self.payload:
|
||||
tool = self.payload.get("tool")
|
||||
return {
|
||||
"type": "events",
|
||||
"data": {
|
||||
"title": f"Calling tool: {tool.name} with inputs: {func_call_args}",
|
||||
},
|
||||
}
|
||||
|
||||
def _is_output_serializable(self, output: Any) -> bool:
|
||||
try:
|
||||
json.dumps(output)
|
||||
return True
|
||||
except TypeError:
|
||||
return False
|
||||
|
||||
def get_agent_tool_response(self) -> dict | None:
|
||||
response = self.payload.get("response")
|
||||
if response is not None:
|
||||
sources = response.sources
|
||||
for source in sources:
|
||||
# Return the tool response here to include the toolCall information
|
||||
if isinstance(source, ToolOutput):
|
||||
if self._is_output_serializable(source.raw_output):
|
||||
output = source.raw_output
|
||||
else:
|
||||
output = source.content
|
||||
|
||||
return {
|
||||
"type": "tools",
|
||||
"data": {
|
||||
"toolOutput": {
|
||||
"output": output,
|
||||
"isError": source.is_error,
|
||||
},
|
||||
"toolCall": {
|
||||
"id": None, # There is no tool id in the ToolOutput
|
||||
"name": source.tool_name,
|
||||
"input": source.raw_input,
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
def to_response(self):
|
||||
match self.event_type:
|
||||
case "retrieve":
|
||||
if self.payload:
|
||||
nodes = self.payload.get("nodes")
|
||||
if nodes:
|
||||
return f"Retrieved {len(nodes)} sources to use as context for the query"
|
||||
else:
|
||||
return f"Retrieving context for query: '{self.payload.get('query_str')}'"
|
||||
else:
|
||||
return None
|
||||
return self.get_retrieval_message()
|
||||
case "function_call":
|
||||
return self.get_tool_message()
|
||||
case "agent_step":
|
||||
return self.get_agent_tool_response()
|
||||
case _:
|
||||
return None
|
||||
|
||||
@@ -54,7 +109,7 @@ class EventCallbackHandler(BaseCallbackHandler):
|
||||
**kwargs: Any,
|
||||
) -> str:
|
||||
event = CallbackEvent(event_id=event_id, event_type=event_type, payload=payload)
|
||||
if event.get_title() is not None:
|
||||
if event.to_response() is not None:
|
||||
self._aqueue.put_nowait(event)
|
||||
|
||||
def on_event_end(
|
||||
@@ -65,7 +120,7 @@ class EventCallbackHandler(BaseCallbackHandler):
|
||||
**kwargs: Any,
|
||||
) -> None:
|
||||
event = CallbackEvent(event_id=event_id, event_type=event_type, payload=payload)
|
||||
if event.get_title() is not None:
|
||||
if event.to_response() is not None:
|
||||
self._aqueue.put_nowait(event)
|
||||
|
||||
def start_trace(self, trace_id: Optional[str] = None) -> None:
|
||||
|
||||
@@ -1,16 +1,11 @@
|
||||
import { initObservability } from "@/app/observability";
|
||||
import { Message, StreamData, StreamingTextResponse } from "ai";
|
||||
import {
|
||||
CallbackManager,
|
||||
ChatMessage,
|
||||
MessageContent,
|
||||
Settings,
|
||||
} from "llamaindex";
|
||||
import { ChatMessage, MessageContent, Settings } from "llamaindex";
|
||||
import { NextRequest, NextResponse } from "next/server";
|
||||
import { createChatEngine } from "./engine/chat";
|
||||
import { initSettings } from "./engine/settings";
|
||||
import { LlamaIndexStream } from "./llamaindex-stream";
|
||||
import { appendEventData } from "./stream-helper";
|
||||
import { createCallbackManager } from "./stream-helper";
|
||||
|
||||
initObservability();
|
||||
initSettings();
|
||||
@@ -64,18 +59,7 @@ export async function POST(request: NextRequest) {
|
||||
const vercelStreamData = new StreamData();
|
||||
|
||||
// Setup callbacks
|
||||
const callbackManager = new CallbackManager();
|
||||
callbackManager.on("retrieve", (data) => {
|
||||
const { nodes } = data.detail;
|
||||
appendEventData(
|
||||
vercelStreamData,
|
||||
`Retrieving context for query: '${userMessage.content}'`,
|
||||
);
|
||||
appendEventData(
|
||||
vercelStreamData,
|
||||
`Retrieved ${nodes.length} sources to use as context for the query`,
|
||||
);
|
||||
});
|
||||
const callbackManager = createCallbackManager(vercelStreamData);
|
||||
|
||||
// Calling LlamaIndex's ChatEngine to get a streamed response
|
||||
const response = await Settings.withCallbackManager(callbackManager, () => {
|
||||
|
||||
@@ -1,5 +1,11 @@
|
||||
import { StreamData } from "ai";
|
||||
import { Metadata, NodeWithScore } from "llamaindex";
|
||||
import {
|
||||
CallbackManager,
|
||||
Metadata,
|
||||
NodeWithScore,
|
||||
ToolCall,
|
||||
ToolOutput,
|
||||
} from "llamaindex";
|
||||
|
||||
export function appendImageData(data: StreamData, imageUrl?: string) {
|
||||
if (!imageUrl) return;
|
||||
@@ -37,3 +43,55 @@ export function appendEventData(data: StreamData, title?: string) {
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
export function appendToolData(
|
||||
data: StreamData,
|
||||
toolCall: ToolCall,
|
||||
toolOutput: ToolOutput,
|
||||
) {
|
||||
data.appendMessageAnnotation({
|
||||
type: "tools",
|
||||
data: {
|
||||
toolCall: {
|
||||
id: toolCall.id,
|
||||
name: toolCall.name,
|
||||
input: toolCall.input,
|
||||
},
|
||||
toolOutput: {
|
||||
output: toolOutput.output,
|
||||
isError: toolOutput.isError,
|
||||
},
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
export function createCallbackManager(stream: StreamData) {
|
||||
const callbackManager = new CallbackManager();
|
||||
|
||||
callbackManager.on("retrieve", (data) => {
|
||||
const { nodes, query } = data.detail;
|
||||
appendEventData(stream, `Retrieving context for query: '${query}'`);
|
||||
appendEventData(
|
||||
stream,
|
||||
`Retrieved ${nodes.length} sources to use as context for the query`,
|
||||
);
|
||||
});
|
||||
|
||||
callbackManager.on("llm-tool-call", (event) => {
|
||||
const { name, input } = event.detail.payload.toolCall;
|
||||
const inputString = Object.entries(input)
|
||||
.map(([key, value]) => `${key}: ${value}`)
|
||||
.join(", ");
|
||||
appendEventData(
|
||||
stream,
|
||||
`Using tool: '${name}' with inputs: '${inputString}'`,
|
||||
);
|
||||
});
|
||||
|
||||
callbackManager.on("llm-tool-result", (event) => {
|
||||
const { toolCall, toolResult } = event.detail.payload;
|
||||
appendToolData(stream, toolCall, toolResult);
|
||||
});
|
||||
|
||||
return callbackManager;
|
||||
}
|
||||
|
||||
@@ -17,7 +17,8 @@ export default function ChatSection() {
|
||||
headers: {
|
||||
"Content-Type": "application/json", // using JSON because of vercel/ai 2.2.26
|
||||
},
|
||||
onError: (error) => {
|
||||
onError: (error: unknown) => {
|
||||
if (!(error instanceof Error)) throw error;
|
||||
const message = JSON.parse(error.message);
|
||||
alert(message.detail);
|
||||
},
|
||||
|
||||
@@ -7,6 +7,7 @@ import ChatAvatar from "./chat-avatar";
|
||||
import { ChatEvents } from "./chat-events";
|
||||
import { ChatImage } from "./chat-image";
|
||||
import { ChatSources } from "./chat-sources";
|
||||
import ChatTools from "./chat-tools";
|
||||
import {
|
||||
AnnotationData,
|
||||
EventData,
|
||||
@@ -14,6 +15,7 @@ import {
|
||||
MessageAnnotation,
|
||||
MessageAnnotationType,
|
||||
SourceData,
|
||||
ToolData,
|
||||
} from "./index";
|
||||
import Markdown from "./markdown";
|
||||
import { useCopyToClipboard } from "./use-copy-to-clipboard";
|
||||
@@ -52,19 +54,27 @@ function ChatMessageContent({
|
||||
annotations,
|
||||
MessageAnnotationType.SOURCES,
|
||||
);
|
||||
const toolData = getAnnotationData<ToolData>(
|
||||
annotations,
|
||||
MessageAnnotationType.TOOLS,
|
||||
);
|
||||
|
||||
const contents: ContentDisplayConfig[] = [
|
||||
{
|
||||
order: -2,
|
||||
order: -3,
|
||||
component: imageData[0] ? <ChatImage data={imageData[0]} /> : null,
|
||||
},
|
||||
{
|
||||
order: -1,
|
||||
order: -2,
|
||||
component:
|
||||
eventData.length > 0 ? (
|
||||
<ChatEvents isLoading={isLoading} data={eventData} />
|
||||
) : null,
|
||||
},
|
||||
{
|
||||
order: -1,
|
||||
component: toolData[0] ? <ChatTools data={toolData[0]} /> : null,
|
||||
},
|
||||
{
|
||||
order: 0,
|
||||
component: <Markdown content={message.content} />,
|
||||
|
||||
@@ -40,9 +40,16 @@ export default function ChatMessages(
|
||||
className="flex h-[50vh] flex-col gap-5 divide-y overflow-y-auto pb-4"
|
||||
ref={scrollableChatContainerRef}
|
||||
>
|
||||
{props.messages.map((m) => (
|
||||
<ChatMessage key={m.id} chatMessage={m} isLoading={props.isLoading} />
|
||||
))}
|
||||
{props.messages.map((m, i) => {
|
||||
const isLoadingMessage = i === messageLength - 1 && props.isLoading;
|
||||
return (
|
||||
<ChatMessage
|
||||
key={m.id}
|
||||
chatMessage={m}
|
||||
isLoading={isLoadingMessage}
|
||||
/>
|
||||
);
|
||||
})}
|
||||
{isPending && (
|
||||
<div className="flex justify-center items-center pt-10">
|
||||
<Loader2 className="h-4 w-4 animate-spin" />
|
||||
|
||||
@@ -0,0 +1,26 @@
|
||||
import { ToolData } from "./index";
|
||||
import { WeatherCard, WeatherData } from "./widgets/WeatherCard";
|
||||
|
||||
// TODO: If needed, add displaying more tool outputs here
|
||||
export default function ChatTools({ data }: { data: ToolData }) {
|
||||
if (!data) return null;
|
||||
const { toolCall, toolOutput } = data;
|
||||
|
||||
if (toolOutput.isError) {
|
||||
return (
|
||||
<div className="border-l-2 border-red-400 pl-2">
|
||||
There was an error when calling the tool {toolCall.name} with input:{" "}
|
||||
<br />
|
||||
{JSON.stringify(toolCall.input)}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
switch (toolCall.name) {
|
||||
case "get_weather_information":
|
||||
const weatherData = toolOutput.output as unknown as WeatherData;
|
||||
return <WeatherCard data={weatherData} />;
|
||||
default:
|
||||
return null;
|
||||
}
|
||||
}
|
||||
@@ -1,3 +1,4 @@
|
||||
import { JSONValue } from "ai";
|
||||
import ChatInput from "./chat-input";
|
||||
import ChatMessages from "./chat-messages";
|
||||
|
||||
@@ -8,6 +9,7 @@ export enum MessageAnnotationType {
|
||||
IMAGE = "image",
|
||||
SOURCES = "sources",
|
||||
EVENTS = "events",
|
||||
TOOLS = "tools",
|
||||
}
|
||||
|
||||
export type ImageData = {
|
||||
@@ -30,7 +32,21 @@ export type EventData = {
|
||||
isCollapsed: boolean;
|
||||
};
|
||||
|
||||
export type AnnotationData = ImageData | SourceData | EventData;
|
||||
export type ToolData = {
|
||||
toolCall: {
|
||||
id: string;
|
||||
name: string;
|
||||
input: {
|
||||
[key: string]: JSONValue;
|
||||
};
|
||||
};
|
||||
toolOutput: {
|
||||
output: JSONValue;
|
||||
isError: boolean;
|
||||
};
|
||||
};
|
||||
|
||||
export type AnnotationData = ImageData | SourceData | EventData | ToolData;
|
||||
|
||||
export type MessageAnnotation = {
|
||||
type: MessageAnnotationType;
|
||||
|
||||
@@ -0,0 +1,213 @@
|
||||
export interface WeatherData {
|
||||
latitude: number;
|
||||
longitude: number;
|
||||
generationtime_ms: number;
|
||||
utc_offset_seconds: number;
|
||||
timezone: string;
|
||||
timezone_abbreviation: string;
|
||||
elevation: number;
|
||||
current_units: {
|
||||
time: string;
|
||||
interval: string;
|
||||
temperature_2m: string;
|
||||
weather_code: string;
|
||||
};
|
||||
current: {
|
||||
time: string;
|
||||
interval: number;
|
||||
temperature_2m: number;
|
||||
weather_code: number;
|
||||
};
|
||||
hourly_units: {
|
||||
time: string;
|
||||
temperature_2m: string;
|
||||
weather_code: string;
|
||||
};
|
||||
hourly: {
|
||||
time: string[];
|
||||
temperature_2m: number[];
|
||||
weather_code: number[];
|
||||
};
|
||||
daily_units: {
|
||||
time: string;
|
||||
weather_code: string;
|
||||
};
|
||||
daily: {
|
||||
time: string[];
|
||||
weather_code: number[];
|
||||
};
|
||||
}
|
||||
|
||||
// Follow WMO Weather interpretation codes (WW)
|
||||
const weatherCodeDisplayMap: Record<
|
||||
string,
|
||||
{
|
||||
icon: JSX.Element;
|
||||
status: string;
|
||||
}
|
||||
> = {
|
||||
"0": {
|
||||
icon: <span>☀️</span>,
|
||||
status: "Clear sky",
|
||||
},
|
||||
"1": {
|
||||
icon: <span>🌤️</span>,
|
||||
status: "Mainly clear",
|
||||
},
|
||||
"2": {
|
||||
icon: <span>☁️</span>,
|
||||
status: "Partly cloudy",
|
||||
},
|
||||
"3": {
|
||||
icon: <span>☁️</span>,
|
||||
status: "Overcast",
|
||||
},
|
||||
"45": {
|
||||
icon: <span>🌫️</span>,
|
||||
status: "Fog",
|
||||
},
|
||||
"48": {
|
||||
icon: <span>🌫️</span>,
|
||||
status: "Depositing rime fog",
|
||||
},
|
||||
"51": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Drizzle",
|
||||
},
|
||||
"53": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Drizzle",
|
||||
},
|
||||
"55": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Drizzle",
|
||||
},
|
||||
"56": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Freezing Drizzle",
|
||||
},
|
||||
"57": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Freezing Drizzle",
|
||||
},
|
||||
"61": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Rain",
|
||||
},
|
||||
"63": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Rain",
|
||||
},
|
||||
"65": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Rain",
|
||||
},
|
||||
"66": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Freezing Rain",
|
||||
},
|
||||
"67": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Freezing Rain",
|
||||
},
|
||||
"71": {
|
||||
icon: <span>❄️</span>,
|
||||
status: "Snow fall",
|
||||
},
|
||||
"73": {
|
||||
icon: <span>❄️</span>,
|
||||
status: "Snow fall",
|
||||
},
|
||||
"75": {
|
||||
icon: <span>❄️</span>,
|
||||
status: "Snow fall",
|
||||
},
|
||||
"77": {
|
||||
icon: <span>❄️</span>,
|
||||
status: "Snow grains",
|
||||
},
|
||||
"80": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Rain showers",
|
||||
},
|
||||
"81": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Rain showers",
|
||||
},
|
||||
"82": {
|
||||
icon: <span>🌧️</span>,
|
||||
status: "Rain showers",
|
||||
},
|
||||
"85": {
|
||||
icon: <span>❄️</span>,
|
||||
status: "Snow showers",
|
||||
},
|
||||
"86": {
|
||||
icon: <span>❄️</span>,
|
||||
status: "Snow showers",
|
||||
},
|
||||
"95": {
|
||||
icon: <span>⛈️</span>,
|
||||
status: "Thunderstorm",
|
||||
},
|
||||
"96": {
|
||||
icon: <span>⛈️</span>,
|
||||
status: "Thunderstorm",
|
||||
},
|
||||
"99": {
|
||||
icon: <span>⛈️</span>,
|
||||
status: "Thunderstorm",
|
||||
},
|
||||
};
|
||||
|
||||
const displayDay = (time: string) => {
|
||||
return new Date(time).toLocaleDateString("en-US", {
|
||||
weekday: "long",
|
||||
});
|
||||
};
|
||||
|
||||
export function WeatherCard({ data }: { data: WeatherData }) {
|
||||
const currentDayString = new Date(data.current.time).toLocaleDateString(
|
||||
"en-US",
|
||||
{
|
||||
weekday: "long",
|
||||
month: "long",
|
||||
day: "numeric",
|
||||
},
|
||||
);
|
||||
|
||||
return (
|
||||
<div className="bg-[#61B9F2] rounded-2xl shadow-xl p-5 space-y-4 text-white w-fit">
|
||||
<div className="flex justify-between">
|
||||
<div className="space-y-2">
|
||||
<div className="text-xl">{currentDayString}</div>
|
||||
<div className="text-5xl font-semibold flex gap-4">
|
||||
<span>
|
||||
{data.current.temperature_2m} {data.current_units.temperature_2m}
|
||||
</span>
|
||||
{weatherCodeDisplayMap[data.current.weather_code].icon}
|
||||
</div>
|
||||
</div>
|
||||
<span className="text-xl">
|
||||
{weatherCodeDisplayMap[data.current.weather_code].status}
|
||||
</span>
|
||||
</div>
|
||||
<div className="gap-2 grid grid-cols-6">
|
||||
{data.daily.time.map((time, index) => {
|
||||
if (index === 0) return null; // skip the current day
|
||||
return (
|
||||
<div key={time} className="flex flex-col items-center gap-4">
|
||||
<span>{displayDay(time)}</span>
|
||||
<div className="text-4xl">
|
||||
{weatherCodeDisplayMap[data.daily.weather_code[index]].icon}
|
||||
</div>
|
||||
<span className="text-sm">
|
||||
{weatherCodeDisplayMap[data.daily.weather_code[index]].status}
|
||||
</span>
|
||||
</div>
|
||||
);
|
||||
})}
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -14,10 +14,11 @@
|
||||
"@radix-ui/react-hover-card": "^1.0.7",
|
||||
"@radix-ui/react-slot": "^1.0.2",
|
||||
"ai": "^3.0.21",
|
||||
"ajv": "^8.12.0",
|
||||
"class-variance-authority": "^0.7.0",
|
||||
"clsx": "^1.2.1",
|
||||
"clsx": "^2.1.1",
|
||||
"dotenv": "^16.3.1",
|
||||
"llamaindex": "0.3.3",
|
||||
"llamaindex": "0.3.9",
|
||||
"lucide-react": "^0.294.0",
|
||||
"next": "^14.0.3",
|
||||
"pdf2json": "3.0.5",
|
||||
|
||||
Reference in New Issue
Block a user