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feat: 使用langchain实现插件功能

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This commit is contained in:
Hk-Gosuto
2023-07-22 15:38:44 +08:00
parent 9223f95726
commit 2bb421b8bf
12 changed files with 906 additions and 128 deletions
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193
app/api/langchain/tool/agent/route.ts Normal file
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@@ -0,0 +1,193 @@
import { NextRequest, NextResponse } from "next/server";
import { getServerSideConfig } from "@/app/config/server";
import { auth } from "../../../auth";
import { ChatOpenAI } from "langchain/chat_models/openai";
import { BaseCallbackHandler } from "langchain/callbacks";
import {
DynamicTool,
RequestsGetTool,
RequestsPostTool,
} from "langchain/tools";
import { SerpAPI } from "langchain/tools";
import { Calculator } from "langchain/tools/calculator";
import { AIMessage, HumanMessage, SystemMessage } from "langchain/schema";
import { BufferMemory, ChatMessageHistory } from "langchain/memory";
import { initializeAgentExecutorWithOptions } from "langchain/agents";
const serverConfig = getServerSideConfig();
interface RequestMessage {
role: string;
content: string;
}
interface RequestBody {
messages: RequestMessage[];
model: string;
stream?: boolean;
temperature: number;
presence_penalty?: number;
frequency_penalty?: number;
top_p?: number;
}
class ResponseBody {
message!: string;
isToolMessage: boolean = false;
toolName?: string;
}
interface ToolInput {
input: string;
}
async function handle(req: NextRequest) {
if (req.method === "OPTIONS") {
return NextResponse.json({ body: "OK" }, { status: 200 });
}
try {
const encoder = new TextEncoder();
const transformStream = new TransformStream();
const writer = transformStream.writable.getWriter();
const reqBody: RequestBody = await req.json();
const handler = BaseCallbackHandler.fromMethods({
async handleLLMNewToken(token: string) {
if (token) {
// console.log("token", token);
var response = new ResponseBody();
response.message = token;
await writer.ready;
await writer.write(
encoder.encode(`data: ${JSON.stringify(response)}\n\n`),
);
}
},
// async handleChainError(err, runId, parentRunId, tags) {
// console.log("writer error");
// await writer.ready;
// await writer.abort(err);
// },
async handleChainEnd(outputs, runId, parentRunId, tags) {
// console.log("writer close");
await writer.ready;
await writer.close();
},
async handleLLMEnd() {
// console.log("writer close");
// await writer.ready;
// await writer.close();
},
async handleLLMError(e: Error) {
console.log("writer error");
await writer.ready;
await writer.abort(e);
},
handleLLMStart(llm, _prompts: string[]) {
// console.log("handleLLMStart: I'm the second handler!!", { llm });
},
handleChainStart(chain) {
// console.log("handleChainStart: I'm the second handler!!", { chain });
},
async handleAgentAction(action) {
console.log(
"agent (llm)",
`tool: ${action.tool} toolInput: ${action.toolInput}`,
{ action },
);
var response = new ResponseBody();
response.isToolMessage = true;
let toolInput = <ToolInput>(<unknown>action.toolInput);
response.message = toolInput.input;
response.toolName = action.tool;
await writer.ready;
await writer.write(
encoder.encode(`data: ${JSON.stringify(response)}\n\n`),
);
},
handleToolStart(tool, input) {
console.log("handleToolStart", { tool, input });
},
});
const tools = [
new RequestsGetTool(),
new RequestsPostTool(),
new SerpAPI(process.env.SERPAPI_API_KEY, {
location: "Austin,Texas,United States",
hl: "en",
gl: "us",
}),
// new DynamicTool({
// name: ddg.name,
// description: ddg.description,
// func: async (input: string) => ddg.call(input),
// }),
new Calculator(),
];
const pastMessages = new Array();
reqBody.messages
.slice(0, reqBody.messages.length - 1)
.forEach((message) => {
if (message.role === "system")
pastMessages.push(new SystemMessage(message.content));
if (message.role === "user")
pastMessages.push(new HumanMessage(message.content));
if (message.role === "assistant")
pastMessages.push(new AIMessage(message.content));
});
// console.log("mesage", { pastMessages })
const memory = new BufferMemory({
memoryKey: "chat_history",
returnMessages: true,
inputKey: "input",
outputKey: "output",
chatHistory: new ChatMessageHistory(pastMessages),
});
const llm = new ChatOpenAI({
modelName: reqBody.model,
openAIApiKey: serverConfig.apiKey,
temperature: reqBody.temperature,
streaming: reqBody.stream,
topP: reqBody.top_p,
presencePenalty: reqBody.presence_penalty,
frequencyPenalty: reqBody.frequency_penalty,
});
const executor = await initializeAgentExecutorWithOptions(tools, llm, {
agentType: "openai-functions",
returnIntermediateSteps: true,
maxIterations: 3,
memory: memory,
});
executor
.call(
{
input: reqBody.messages.slice(-1)[0].content,
},
[handler],
)
.catch((e: Error) => console.error(e));
console.log("returning response");
return new Response(transformStream.readable, {
headers: { "Content-Type": "text/event-stream" },
});
} catch (e) {
return new Response(JSON.stringify({ error: (e as any).message }), {
status: 500,
headers: { "Content-Type": "application/json" },
});
}
}
export const GET = handle;
export const POST = handle;
export const runtime = "edge";

4
app/client/api.ts
View File

@@ -13,7 +13,6 @@ export type ChatModel = ModelType;
export interface RequestMessage {
role: MessageRole;
content: string;
toolPrompt?: string;
}
export interface LLMConfig {
@@ -28,7 +27,7 @@ export interface LLMConfig {
export interface ChatOptions {
messages: RequestMessage[];
config: LLMConfig;
onToolUpdate?: (toolName: string, toolInput: string) => void;
onUpdate?: (message: string, chunk: string) => void;
onFinish: (message: string) => void;
onError?: (err: Error) => void;
@@ -47,6 +46,7 @@ export interface LLMModel {
export abstract class LLMApi {
abstract chat(options: ChatOptions): Promise<void>;
abstract toolAgentChat(options: ChatOptions): Promise<void>;
abstract usage(): Promise<LLMUsage>;
abstract models(): Promise<LLMModel[]>;
}

154
app/client/platforms/openai.ts
View File

@@ -23,6 +23,13 @@ export interface OpenAIListModelResponse {
}>;
}
interface LangChainAgentResponse {
message: string;
isToolMessage: boolean;
toolName?: string;
toolInput?: object;
}
export class ChatGPTApi implements LLMApi {
private disableListModels = true;
@@ -47,7 +54,7 @@ export class ChatGPTApi implements LLMApi {
async chat(options: ChatOptions) {
const messages = options.messages.map((v) => ({
role: v.role,
content: v.toolPrompt ?? v.content,
content: v.content,
}));
const modelConfig = {
@@ -182,6 +189,151 @@ export class ChatGPTApi implements LLMApi {
options.onError?.(e as Error);
}
}
async toolAgentChat(options: ChatOptions) {
const messages = options.messages.map((v) => ({
role: v.role,
content: v.content,
}));
const modelConfig = {
...useAppConfig.getState().modelConfig,
...useChatStore.getState().currentSession().mask.modelConfig,
...{
model: options.config.model,
},
};
const requestPayload = {
messages,
stream: options.config.stream,
model: modelConfig.model,
temperature: modelConfig.temperature,
presence_penalty: modelConfig.presence_penalty,
frequency_penalty: modelConfig.frequency_penalty,
top_p: modelConfig.top_p,
};
console.log("[Request] openai payload: ", requestPayload);
const shouldStream = true;
const controller = new AbortController();
options.onController?.(controller);
try {
const path = "/api/langchain/tool/agent";
const chatPayload = {
method: "POST",
body: JSON.stringify(requestPayload),
signal: controller.signal,
headers: getHeaders(),
};
// make a fetch request
const requestTimeoutId = setTimeout(
() => controller.abort(),
REQUEST_TIMEOUT_MS,
);
console.log("shouldStream", shouldStream);
if (shouldStream) {
let responseText = "";
let finished = false;
const finish = () => {
if (!finished) {
options.onFinish(responseText);
finished = true;
}
};
controller.signal.onabort = finish;
fetchEventSource(path, {
...chatPayload,
async onopen(res) {
clearTimeout(requestTimeoutId);
const contentType = res.headers.get("content-type");
console.log(
"[OpenAI] request response content type: ",
contentType,
);
if (contentType?.startsWith("text/plain")) {
responseText = await res.clone().text();
return finish();
}
if (
!res.ok ||
!res.headers
.get("content-type")
?.startsWith(EventStreamContentType) ||
res.status !== 200
) {
const responseTexts = [responseText];
let extraInfo = await res.clone().text();
console.warn(`extraInfo: ${extraInfo}`);
// try {
// const resJson = await res.clone().json();
// extraInfo = prettyObject(resJson);
// } catch { }
if (res.status === 401) {
responseTexts.push(Locale.Error.Unauthorized);
}
if (extraInfo) {
responseTexts.push(extraInfo);
}
responseText = responseTexts.join("\n\n");
return finish();
}
},
onmessage(msg) {
if (msg.data === "[DONE]" || finished) {
return finish();
}
let response: LangChainAgentResponse = JSON.parse(msg.data);
try {
if (response && !response.isToolMessage) {
responseText += response.message;
options.onUpdate?.(
responseText,
JSON.stringify(response.toolInput),
);
} else {
options.onToolUpdate?.(response.toolName!, response.message);
}
} catch (e) {
console.error("[Request] parse error", response, msg);
}
},
onclose() {
finish();
},
onerror(e) {
options.onError?.(e);
throw e;
},
openWhenHidden: true,
});
} else {
const res = await fetch(path, chatPayload);
clearTimeout(requestTimeoutId);
const resJson = await res.json();
const message = this.extractMessage(resJson);
options.onFinish(message);
}
} catch (e) {
console.log("[Request] failed to make a chat reqeust", e);
options.onError?.(e as Error);
}
}
async usage() {
const formatDate = (d: Date) =>
`${d.getFullYear()}-${(d.getMonth() + 1).toString().padStart(2, "0")}-${d

57
app/components/chat.tsx
View File

@@ -34,8 +34,6 @@ import AutoIcon from "../icons/auto.svg";
import BottomIcon from "../icons/bottom.svg";
import StopIcon from "../icons/pause.svg";
import RobotIcon from "../icons/robot.svg";
import SearchCloseIcon from "../icons/search_close.svg";
import SearchOpenIcon from "../icons/search_open.svg";
import CheckmarkIcon from "../icons/checkmark.svg";
import {
@@ -404,11 +402,11 @@ export function ChatActions(props: {
const navigate = useNavigate();
const chatStore = useChatStore();
// switch web search
const webSearch = chatStore.currentSession().webSearch;
function switchWebSearch() {
// switch tools
const useTools = chatStore.currentSession().useTools;
function switchUseTools() {
chatStore.updateCurrentSession((session) => {
session.webSearch = !session.webSearch;
session.useTools = !session.useTools;
});
}
@@ -513,15 +511,15 @@ export function ChatActions(props: {
icon={<RobotIcon />}
/>
<ChatAction
onClick={switchWebSearch}
{/* <ChatAction
onClick={switchUseTools}
text={
webSearch
? Locale.Chat.InputActions.CloseWebSearch
: Locale.Chat.InputActions.OpenWebSearch
useTools
? Locale.Chat.InputActions.CloseTools
: Locale.Chat.InputActions.OpenTools
}
icon={webSearch ? <SearchOpenIcon /> : <SearchCloseIcon />}
/>
icon={useTools ? <SearchOpenIcon /> : <SearchCloseIcon />}
/> */}
{showModelSelector && (
<Selector
@@ -1149,20 +1147,27 @@ export function Chat() {
</div>
)}
</div>
<div>
<div className={styles["chat-message-tools-status"]}>
<div className={styles["chat-message-tools-name"]}>
<CheckmarkIcon
className={styles["chat-message-checkmark"]}
/>
web search:
<code className={styles["chat-message-tools-details"]}>
xxxxxxxxxxxxxxxx
</code>
{session.useTools &&
!isUser &&
message.toolMessages &&
message.toolMessages.map((tool, index) => (
<div
className={styles["chat-message-tools-status"]}
key={index}
>
<div className={styles["chat-message-tools-name"]}>
<CheckmarkIcon
className={styles["chat-message-checkmark"]}
/>
{tool.toolName}:
<code
className={styles["chat-message-tools-details"]}
>
{tool.toolInput}
</code>
</div>
</div>
</div>
</div>
))}
{showTyping && (
<div className={styles["chat-message-status"]}>

1
app/icons/search_close.svg
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@@ -1 +0,0 @@
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app/icons/search_open.svg
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@@ -1 +0,0 @@
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4
app/locales/cn.ts
View File

@@ -57,8 +57,8 @@ const cn = {
Masks: "所有面具",
Clear: "清除聊天",
Settings: "对话设置",
OpenWebSearch: "开启联网",
CloseWebSearch: "关闭联网",
OpenTools: "开启插件",
CloseTools: "关闭插件",
},
Rename: "重命名对话",
Typing: "正在输入…",

4
app/locales/en.ts
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@@ -59,8 +59,8 @@ const en: LocaleType = {
Masks: "Masks",
Clear: "Clear Context",
Settings: "Settings",
OpenWebSearch: "Enable Web Search",
CloseWebSearch: "Disable Web Search",
OpenTools: "Enable Plugins",
CloseTools: "Disable Plugins",
},
Rename: "Rename Chat",
Typing: "Typing…",

210
app/store/chat.ts
View File

@@ -18,22 +18,27 @@ import { prettyObject } from "../utils/format";
import { estimateTokenLength } from "../utils/token";
import { nanoid } from "nanoid";
export interface ChatToolMessage {
toolName: string;
toolInput?: string;
}
export type ChatMessage = RequestMessage & {
date: string;
toolMessages: ChatToolMessage[];
streaming?: boolean;
isError?: boolean;
id: string;
model?: ModelType;
toolPrompt?: string;
};
export function createMessage(override: Partial<ChatMessage>): ChatMessage {
return {
id: nanoid(),
date: new Date().toLocaleString(),
toolMessages: new Array<ChatToolMessage>(),
role: "user",
content: "",
toolPrompt: undefined,
...override,
};
}
@@ -56,7 +61,7 @@ export interface ChatSession {
clearContextIndex?: number;
mask: Mask;
webSearch: boolean;
useTools: boolean;
}
export const DEFAULT_TOPIC = Locale.Store.DefaultTopic;
@@ -80,7 +85,7 @@ function createEmptySession(): ChatSession {
lastSummarizeIndex: 0,
mask: createEmptyMask(),
webSearch: false,
useTools: true,
};
}
@@ -308,91 +313,126 @@ export const useChatStore = create<ChatStore>()(
content,
};
session.messages.push(savedUserMessage);
});
if (session.webSearch) {
const query = encodeURIComponent(content);
let searchResult = await api.searchTool.call(query);
console.log("[Tools] ", searchResult);
const webSearchPrompt = `
Using the provided web search results, write a comprehensive reply to the given query.
If the provided search results refer to multiple subjects with the same name, write separate answers for each subject.
Make sure to cite results using \`[[number](URL)]\` notation after the reference.
Web search json results:
"""
${JSON.stringify(searchResult)}
"""
Current date:
"""
${new Date().toISOString()}
"""
Query:
"""
${content}
"""
Reply in ${getLang()} and markdown.`;
userMessage.toolPrompt = webSearchPrompt;
}
// save user's and bot's message
get().updateCurrentSession((session) => {
session.messages.push(botMessage);
});
// make request
api.llm.chat({
messages: sendMessages,
config: { ...modelConfig, stream: true },
onUpdate(message) {
botMessage.streaming = true;
if (message) {
botMessage.content = message;
}
get().updateCurrentSession((session) => {
session.messages = session.messages.concat();
});
},
onFinish(message) {
botMessage.streaming = false;
if (message) {
botMessage.content = message;
get().onNewMessage(botMessage);
}
ChatControllerPool.remove(session.id, botMessage.id);
},
onError(error) {
const isAborted = error.message.includes("aborted");
botMessage.content =
"\n\n" +
prettyObject({
error: true,
message: error.message,
if (session.useTools && modelConfig.model.endsWith("0613")) {
console.log("[ToolAgent] start");
api.llm.toolAgentChat({
messages: sendMessages,
config: { ...modelConfig, stream: true },
onUpdate(message) {
botMessage.streaming = true;
if (message) {
botMessage.content = message;
}
get().updateCurrentSession((session) => {
session.messages = session.messages.concat();
});
botMessage.streaming = false;
userMessage.isError = !isAborted;
botMessage.isError = !isAborted;
get().updateCurrentSession((session) => {
session.messages = session.messages.concat();
});
ChatControllerPool.remove(
session.id,
botMessage.id ?? messageIndex,
);
},
onToolUpdate(toolName, toolInput) {
botMessage.streaming = true;
if (toolName && toolInput) {
botMessage.toolMessages.push({
toolName,
toolInput,
});
}
get().updateCurrentSession((session) => {
session.messages = session.messages.concat();
});
},
onFinish(message) {
botMessage.streaming = false;
if (message) {
botMessage.content = message;
get().onNewMessage(botMessage);
}
ChatControllerPool.remove(session.id, botMessage.id);
},
onError(error) {
const isAborted = error.message.includes("aborted");
botMessage.content =
"\n\n" +
prettyObject({
error: true,
message: error.message,
});
botMessage.streaming = false;
userMessage.isError = !isAborted;
botMessage.isError = !isAborted;
get().updateCurrentSession((session) => {
session.messages = session.messages.concat();
});
ChatControllerPool.remove(
session.id,
botMessage.id ?? messageIndex,
);
console.error("[Chat] failed ", error);
},
onController(controller) {
// collect controller for stop/retry
ChatControllerPool.addController(
session.id,
botMessage.id ?? messageIndex,
controller,
);
},
});
console.error("[Chat] failed ", error);
},
onController(controller) {
// collect controller for stop/retry
ChatControllerPool.addController(
session.id,
botMessage.id ?? messageIndex,
controller,
);
},
});
} else {
// make request
api.llm.chat({
messages: sendMessages,
config: { ...modelConfig, stream: true },
onUpdate(message) {
botMessage.streaming = true;
if (message) {
botMessage.content = message;
}
get().updateCurrentSession((session) => {
session.messages = session.messages.concat();
});
},
onFinish(message) {
botMessage.streaming = false;
if (message) {
botMessage.content = message;
get().onNewMessage(botMessage);
}
ChatControllerPool.remove(session.id, botMessage.id);
},
onError(error) {
const isAborted = error.message.includes("aborted");
botMessage.content =
"\n\n" +
prettyObject({
error: true,
message: error.message,
});
botMessage.streaming = false;
userMessage.isError = !isAborted;
botMessage.isError = !isAborted;
get().updateCurrentSession((session) => {
session.messages = session.messages.concat();
});
ChatControllerPool.remove(
session.id,
botMessage.id ?? messageIndex,
);
console.error("[Chat] failed ", error);
},
onController(controller) {
// collect controller for stop/retry
ChatControllerPool.addController(
session.id,
botMessage.id ?? messageIndex,
controller,
);
},
});
}
},
getMemoryPrompt() {
@@ -532,7 +572,7 @@ Reply in ${getLang()} and markdown.`;
api.llm.chat({
messages: topicMessages,
config: {
model: "gpt-3.5-turbo",
model: "gpt-3.5-turbo-0613",
},
onFinish(message) {
get().updateCurrentSession(

2
app/store/config.ts
View File

@@ -38,7 +38,7 @@ export const DEFAULT_CONFIG = {
models: DEFAULT_MODELS as any as LLMModel[],
modelConfig: {
model: "gpt-3.5-turbo" as ModelType,
model: "gpt-3.5-turbo-0613" as ModelType,
temperature: 0.5,
top_p: 1,
max_tokens: 2000,