Dev pull

.env.example

@@ -38,10 +38,14 @@ TWITTER_EMAIL=    # Account email
 TWITTER_2FA_SECRET=
 TWITTER_COOKIES= # Account cookies
 TWITTER_POLL_INTERVAL=120 # How often (in seconds) the bot should check for interactions
+POST_IMMEDIATELY=1                  # Default: false
+
 X_SERVER_URL=
 XAI_API_KEY=
 XAI_MODEL=
 
+
+
 # Post Interval Settings (in minutes)
 POST_INTERVAL_MIN= # Default: 90
 POST_INTERVAL_MAX= # Default: 180
@@ -189,3 +193,49 @@ INTERNET_COMPUTER_ADDRESS=
 # Aptos
 APTOS_PRIVATE_KEY= # Aptos private key
 APTOS_NETWORK=     # must be one of mainnet, testnet
+
+
+MY_APP_URL=https://web3agent.site/dev
+
+TAVILY_API_KEY=
+PRIVY_APP_ID=
+PRIVY_APP_SECRET=
+
+# Web3Agent Watcher KOL
+TW_KOL_LIST=`[
+    "elonmusk",
+    "cz_binance",
+    "aeyakovenko",
+    "jessepollak",
+    "shawmakesmagic",
+    "everythingempt0"
+]`
+TW_KOL_LIST_MORE=`[
+    "JoshRMeier",
+    "coinbureau"
+]`
+
+# Web3Agent Watcher
+AGENT_WATCHER_INSTRUCTION='
+Please find the following data according to the text provided in the following format:
+ (1) Token Symbol by json name "token";
+ (2) Token Interaction Information by json name "interact";
+ (3) Token Interaction Count by json name "count";
+ (4) Token Key Event Description by json name "event".
+The detail information of each item as following:
+ The (1) item is the token/coin/meme name involved in the text provided.
+ The (2) item include the interactions(mention/like/comment/repost/post/reply) between each token/coin/meme and the twitter account, the output is "@somebody mention/like/comment/repost/post/reply @token, @someone post @token, etc."; providing at most 2 interactions is enough.
+ The (3) item is the data of the count of interactions between each token and the twitter account.
+ The (4) item is the about 30 words description of the key event for each token/coin/meme. If the description is too short, please attach the tweets.
+Please skip the top token, such as btc, eth, sol, base, bnb.
+Use the list format and only provide these 4 pieces of information.'
+
+AGENT_WATCHER_INSTRUCTION_0='
+Please find the token/project involved according to the text provided, and obtain the data of the number of interactions between each token and the three category of accounts (mentions/likes/comments/reposts/posts) in the tweets related to these tokens; mark the tokens as category 1, category 2 or category 3; if there are both category 1 and category 2, choose category 1, which has a higher priority.
+ And provide the brief introduction of the key event for each token. And also skip the top/famous tokens.
+Please reply in English and in the following format:
+- Token Symbol by json name "token";
+- Token Interaction Category by json name "category";
+- Token Interaction Count by json name "count";
+- Token Key Event Introduction by json name "event";
+Use the list format and only provide these 4 pieces of information.'

agent/package.json

@@ -39,6 +39,7 @@
         "@ai16z/plugin-solana": "workspace:*",
         "@ai16z/plugin-starknet": "workspace:*",
         "@ai16z/plugin-tee": "workspace:*",
+        "@ai16z/plugin-data-enrich": "workspace:*",
         "readline": "1.3.0",
         "ws": "8.18.0",
         "yargs": "17.7.2"

agent/src/index.ts

@@ -16,6 +16,7 @@ import {
     ICacheManager,
     IDatabaseAdapter,
     IDatabaseCacheAdapter,
+    Memory,
     ModelProviderName,
     defaultCharacter,
     elizaLogger,
@@ -26,6 +27,7 @@ import {
 import { zgPlugin } from "@ai16z/plugin-0g";
 import { goatPlugin } from "@ai16z/plugin-goat";
 import { bootstrapPlugin } from "@ai16z/plugin-bootstrap";
+import { dataEnrichPlugin } from "@ai16z/plugin-data-enrich";
 // import { buttplugPlugin } from "@ai16z/plugin-buttplug";
 import {
     coinbaseCommercePlugin,
@@ -47,6 +49,28 @@ import readline from "readline";
 import { fileURLToPath } from "url";
 import yargs from "yargs";
 
+export interface AgentConfig {
+    prompt: string;
+    name: string;
+    clients: string[];
+    modelProvider: string;
+    bio: string[];
+    lore?: string[];
+    knowledge?: string[];
+    topics?: string[];
+    style?: {
+        all: string[];
+        chat: string[];
+        post: string[];
+    };
+    adjectives?: string[];
+    x: {
+        username: string;
+        email: string;
+        password: string;
+    };
+}
+
 const __filename = fileURLToPath(import.meta.url); // get the resolved path to the file
 const __dirname = path.dirname(__filename); // get the name of the directory
 
@@ -365,7 +389,8 @@ export function createAgent(
         evaluators: [],
         character,
         plugins: [
-            bootstrapPlugin,
+            //bootstrapPlugin,
+            dataEnrichPlugin,
             getSecret(character, "CONFLUX_CORE_PRIVATE_KEY")
                 ? confluxPlugin
                 : null,
@@ -417,7 +442,12 @@ function intializeDbCache(character: Character, db: IDatabaseCacheAdapter) {
     return cache;
 }
 
-async function startAgent(character: Character, directClient) {
+async function startAgent(
+    character: Character,
+    directClient,
+    config?: AgentConfig,
+    memory?: Memory
+) {
     let db: IDatabaseAdapter & IDatabaseCacheAdapter;
     try {
         character.id ??= stringToUuid(character.name);
@@ -434,16 +464,22 @@ async function startAgent(character: Character, directClient) {
             IDatabaseCacheAdapter;
 
         await db.init();
+        db.setCache({
+            agentId: character.id,
+            key: "agentConfig",
+            value: JSON.stringify(config),
+        });
 
         const cache = intializeDbCache(character, db);
         const runtime = createAgent(character, db, cache, token);
 
         await runtime.initialize();
 
-        const clients = await initializeClients(character, runtime);
-
         directClient.registerAgent(runtime);
 
+        // 初始化 agent client
+        const clients = await initializeClients(character, runtime);
+
         return clients;
     } catch (error) {
         elizaLogger.error(
@@ -470,6 +506,88 @@ const startAgents = async () => {
         characters = await loadCharacters(charactersArg);
     }
 
+    // @ts-ignore
+    directClient.registerCallback(
+        async (config: AgentConfig, memory: Memory) => {
+            // 动态启动 Agent
+            const characters0 = { ...characters?.[0] };
+
+            // 需要处理的字段列表
+            const arrayFields = [
+                "bio",
+                "lore",
+                "style",
+                "knowledge",
+                "adjectives",
+            ] as const;
+
+            // 统一处理数组字段
+            arrayFields.forEach((field) => {
+                const value = config?.[field];
+                if (field === "style") {
+                    // 特殊处理 style 字段
+                    let styles: string[] = [];
+                    if (typeof value === "string") {
+                        styles = value
+                            // @ts-ignore
+                            ?.split(",")
+                            .map((s) => s.trim())
+                            .filter(Boolean);
+                    } else if (Array.isArray(value)) {
+                        styles = value.filter(Boolean);
+                    }
+                    if (styles.length > 0) {
+                        characters0[field] = {
+                            all: styles,
+                            chat: styles,
+                            post: styles,
+                        };
+                    }
+                } else {
+                    // 处理其他数组字段
+                    if (value && typeof value === "string") {
+                        // 处理非空字符串
+                        // @ts-ignore
+                        const trimmed = value?.trim();
+                        if (trimmed) {
+                            characters0[field] = trimmed
+                                .split(",")
+                                .map((str) => str.trim())
+                                .filter(Boolean);
+                        }
+                    } else if (Array.isArray(value)) {
+                        // 处理数组，过滤掉空值
+                        characters0[field] = value.filter(Boolean);
+                    }
+                }
+            });
+
+            // 处理普通字段
+            if (config?.name) {
+                characters0.name = config.name || config.x.username;
+            }
+
+            const character = {
+                ...characters?.[0],
+                // 排除 Twitter 凭证
+                x: undefined,
+            };
+
+            character.settings.secrets = {
+                ...character.settings.secrets,
+                TWITTER_USERNAME: config?.x?.username,
+                TWITTER_PASSWORD: config?.x?.password,
+                TWITTER_EMAIL: config?.x?.email,
+                POST_IMMEDIATELY: "1",
+                AGENT_PROMPT: config?.prompt,
+            };
+
+            await startAgent(character, directClient, config, memory);
+
+            console.log("req.params registerCallbackFn character:", character);
+        }
+    );
+
     try {
         for (const character of characters) {
             await startAgent(character, directClient);