Merge pull request #92 from autonomys/agent-framework

Add Auto agent framework

auto-agents-framework/.env.sample

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+# Twitter Credentials
+TWITTER_USERNAME=<twitter_username>
+TWITTER_PASSWORD=<twitter_password>
+
+# Twitter data fetch and post configuration
+NUM_TIMELINE_TWEETS=10
+NUM_FOLLOWING_RECENT_TWEETS=10
+NUM_RANDOM_FOLLOWERS=5
+MAX_MENTIONS=20
+MAX_THREAD_LENGTH=20
+MAX_MY_RECENT_TWEETS=10
+POST_TWEETS=false
+RESPONSE_INTERVAL_MINUTES=26
+POST_INTERVAL_MINUTES=30
+
+# AutoDrive Configuration
+AUTO_DRIVE_API_KEY=<auto_drive_api_key>
+AUTO_DRIVE_ENCRYPTION_PASSWORD=<auto_drive_encryption_password>
+AUTO_DRIVE_UPLOAD=false
+
+# SC Configuration
+RPC_URL=<rpc_url>
+CONTRACT_ADDRESS=<contract_address>
+PRIVATE_KEY=<private_key>
+
+# LLM Configuration
+SMALL_LLM_MODEL=gpt-4o-mini
+LARGE_LLM_MODEL=<large_llm_model>
+OPENAI_API_KEY=<openai_api_key>
+
+# SerpAPI Configuration
+SERPAPI_API_KEY=<serpapi_api_key>
+
+# Server Configuration
+PORT=<port>
+
+# Environment
+NODE_ENV=<node_env> 

auto-agents-framework/.gitignore

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+character.ts

auto-agents-framework/.prettierrc

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+{
+  "semi": true,
+  "trailingComma": "all",
+  "singleQuote": true,
+  "quoteProps": "as-needed",
+  "jsxSingleQuote": true,
+  "printWidth": 100,
+  "tabWidth": 2,
+  "arrowParens": "avoid"
+} 

auto-agents-framework/README.md

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+# Auto-Agents-Framework: Framework for building AI agents
+
+Auto-Agents-Framework is an experimental framework for building AI agents that can interact with social networks and maintain permanent memory through the Autonomys Network. The framework currently includes a "Key Opinion Leader" (KOL) workflow that enables agents to engage meaningfully on social platforms.
+
+## Features
+
+- 🤖 Autonomous social media engagement
+- 🧠 Permanent agent memory storage via Autonomys Network
+- 🔄 Built-in workflow system
+- 🐦 Twitter integration (with more platforms planned)
+- 🎭 Customizable agent personalities
+- 🛠️ Extensible tool system
+
+## Getting Started
+
+1. Install dependencies:
+   `yarn install`
+
+2. Copy the environment file and configure your credentials:
+   `cp .env.sample .env`
+
+3. Create your agent character by copying the example:
+   `cp src/agents/workflows/kol/characters/character.example.ts src/agents/workflows/kol/characters/character.ts`
+
+4. Configure your character:
+
+   ```
+   // character.ts
+   const name = 'Your Agent Name';
+   const username = 'twitter_handle';
+   const walletAddress = '0x...'; // Your Autonomys Network wallet
+   const description = 'Your agent's personality description...';
+
+
+    // Configure additional personality traits, expertise, rules, etc.
+   ```
+
+## Character Configuration
+
+The character configuration defines your agent's personality and behavior. Key sections include:
+
+- `description`: Core personality and background
+- `personality`: Key behavioral traits
+- `expertise`: Areas of knowledge
+- `rules`: Operating guidelines
+- `trendFocus`: Topics to monitor
+- `contentFocus`: Content creation guidelines
+- `replyStyle`: Engagement approach
+- `wordsToAvoid`: Restricted vocabulary
+
+## Autonomys Network Integration
+
+The framework uses the Autonomys Network for permanent storage of agent memory and interactions. This enables:
+
+- Persistent agent memory across sessions
+- Verifiable interaction history
+- Cross-agent memory sharing
+- Decentralized agent identity
+
+To use this feature:
+
+1. Configure your Autonomys Network credentials in `.env`
+2. Set `AUTO_DRIVE_UPLOAD=true`
+3. Provide your wallet details and encryption password
+
+## Workflows
+
+### KOL (Key Opinion Leader)
+
+The KOL workflow enables agents to:
+
+- Monitor social media for relevant discussions
+- Analyze trends and conversations
+- Engage meaningfully with other users
+- Generate original content
+- Maintain consistent personality
+- Store interactions in permanent memory
+
+## Running the Agent
+
+Start the agent with:
+`yarn dev`
+
+Monitor the agent's activity in the console and configured log files.
+
+## License
+
+MIT

auto-agents-framework/examples/twitter.ts

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+import { TwitterApi } from '../src/services/twitter/types.js';
+import { createTwitterApi } from '../src/services/twitter/client.js';
+import { config } from '../src/config/index.js';
+import { createLogger } from '../src/utils/logger.js';
+import { SearchMode, Scraper, Tweet } from 'agent-twitter-client';
+
+const logger = createLogger('twitter', './examples/logs');
+
+const { USERNAME, PASSWORD, COOKIES_PATH } = config.twitterConfig;
+
+const twitterApi: TwitterApi = await createTwitterApi(USERNAME, PASSWORD, COOKIES_PATH);
+const { scraper } = twitterApi;
+// const myMentions = await twitterApi.getMyMentions(5);
+// logger.info('My Mentions', { myMentions });
+
+const iterateResponse = async <T>(response: AsyncGenerator<T>): Promise<T[]> => {
+  const tweets: T[] = [];
+  for await (const tweet of response) {
+    tweets.push(tweet);
+  }
+  return tweets;
+};
+
+const myMentions = await twitterApi.getMyUnrepliedToMentions(5);
+logger.info('My Mentions', { myMentions });
+
+
+const conversationId = '1874032422175858869';
+const tweetId = '1874146661251113110';
+
+// const conversation = await iterateResponse(
+//   scraper.searchTweets(`conversation_id:${conversationId}`, 100, SearchMode.Latest),
+// );
+// const tweet = await scraper.getTweet(tweetId);
+// logger.info('Conversation', {
+//   tweet: {
+//     text: tweet!.text,
+//     conversationId: tweet!.conversationId,
+//     inReplyToStatusId: tweet!.inReplyToStatusId,
+//     id: tweet!.id,
+//   },
+//   conversation: conversation.map(t => ({
+//     text: t.text,
+//     username: t.username,
+//     conversationId: t.conversationId,
+//     id: t.id,
+//   })),
+// });
+
+// const conversationWithReplies = await iterateResponse(scraper.searchTweets(`to:${twitterApi.username} conversation_id:${conversationId}`, 100, SearchMode.Latest));
+// logger.info('Conversation With Replies', { conversationWithReplies: conversationWithReplies.map(t => ({
+//     text: t.text,
+//     username: t.username,
+//     conversationId: t.conversationId,
+//     id: t.id,
+//   })),
+// });
+
+
+//logger.info('Conversation', { conversation });
+
+//const myMentions = await twitterApi.getMyUnrepliedToMentions(5);

auto-agents-framework/package.json

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+{
+    "name": "auto-agents-framework",
+    "version": "0.0.1",
+    "description": "Auto Agents Framework",
+    "main": "dist/index.js",
+    "type": "module",
+    "scripts": {
+        "build": "tsc",
+        "start": "node dist/index.js",
+        "dev": "tsx watch src/index.ts",
+        "format": "prettier --write \"src/**/*.ts\"",
+        "format:check": "prettier --check \"src/**/*.ts\"",
+        "example:twitter": "tsx examples/twitter.ts"
+    },
+    "dependencies": {
+        "@autonomys/auto-dag-data": "1.2.1",
+        "@autonomys/auto-drive": "1.2.1",
+        "@langchain/community": "0.3.20",
+        "@langchain/core": "0.3.19",
+        "@langchain/langgraph": "0.2.36",
+        "@langchain/openai": "0.3.16",
+        "agent-twitter-client": "0.0.18",
+        "dotenv": "^16.3.1",
+        "ethers": "^6.13.4",        
+        "winston": "^3.11.0",
+        "zod": "^3.22.4"
+    },
+    "devDependencies": {
+        "@tsconfig/node20": "^20.1.4",
+        "@types/node": "22.10.0",
+        "@types/sqlite3": "^3.1.11",
+        "prettier": "^3.2.2",
+        "tsx": "^4.7.1",
+        "typescript": "^5.3.3"
+    }
+}

auto-agents-framework/src/agents/tools/fetchMentionsTool.ts

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+import { DynamicStructuredTool } from '@langchain/core/tools';
+import { z } from 'zod';
+import { createLogger } from '../../utils/logger.js';
+import { TwitterApi } from '../../services/twitter/types.js';
+import { ToolNode } from '@langchain/langgraph/prebuilt';
+import { AIMessage } from '@langchain/core/messages';
+
+const logger = createLogger('fetch-mentions-tool');
+
+export const createFetchMentionsTool = (twitterApi: TwitterApi) =>
+  new DynamicStructuredTool({
+    name: 'fetch_mentions',
+    description: 'Fetch recent mentions',
+    schema: z.object({ maxMentions: z.number(), sinceId: z.string().optional() }),
+    func: async ({ maxMentions, sinceId }: { maxMentions: number; sinceId?: string }) => {
+      try {
+        const recentMentions = await twitterApi.getMyUnrepliedToMentions(maxMentions, sinceId);
+
+        return {
+          tweets: recentMentions,
+        };
+      } catch (error) {
+        logger.error('Error in fetchTimelineTool:', error);
+        return {
+          tweets: [],
+        };
+      }
+    },
+  });
+
+export const invokeFetchMentionsTool = async (
+  toolNode: ToolNode,
+  { maxMentions, sinceId }: { maxMentions: number; sinceId?: string },
+) => {
+  const toolResponse = await toolNode.invoke({
+    messages: [
+      new AIMessage({
+        content: '',
+        tool_calls: [
+          {
+            name: 'fetch_mentions',
+            args: { maxMentions, sinceId },
+            id: 'fetch_mentions_call',
+            type: 'tool_call',
+          },
+        ],
+      }),
+    ],
+  });
+  return toolResponse;
+};

auto-agents-framework/src/agents/tools/fetchMyRecentTweetsTool.ts

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+import { DynamicStructuredTool } from '@langchain/core/tools';
+import { z } from 'zod';
+import { createLogger } from '../../utils/logger.js';
+import { TwitterApi } from '../../services/twitter/types.js';
+import { ToolNode } from '@langchain/langgraph/prebuilt';
+import { AIMessage } from '@langchain/core/messages';
+
+const logger = createLogger('fetch-recent-tweets-tool');
+
+export const createFetchMyRecentTweetsTool = (twitterApi: TwitterApi) =>
+  new DynamicStructuredTool({
+    name: 'fetch_my_recent_tweets',
+    description: 'Fetch the agents recent tweets',
+    schema: z.object({ maxMyRecentTweets: z.number() }),
+    func: async ({ maxMyRecentTweets }: { maxMyRecentTweets: number }) => {
+      try {
+        const myRecentTweets = await twitterApi.getMyRecentTweets(maxMyRecentTweets);
+        const repliedToTweetIds = await twitterApi.getMyRepliedToIds();
+        logger.info('Fetch My Recent Tweets Tool - Result', {
+          tweets: myRecentTweets.length,
+          repliedToTweetIds: repliedToTweetIds.length,
+        });
+
+        return {
+          tweets: myRecentTweets,
+          repliedToTweetIds: repliedToTweetIds,
+        };
+      } catch (error) {
+        logger.error('Error in fetchRecentTweetsTool:', error);
+        return {
+          tweets: [],
+          repliedToTweetIds: [],
+        };
+      }
+    },
+  });
+
+export const invokeFetchMyRecentTweetsTool = async (
+  toolNode: ToolNode,
+  { maxMyRecentTweets }: { maxMyRecentTweets: number },
+) => {
+  const toolResponse = await toolNode.invoke({
+    messages: [
+      new AIMessage({
+        content: '',
+        tool_calls: [
+          {
+            name: 'fetch_my_recent_tweets',
+            args: { maxMyRecentTweets },
+            id: 'fetch_my_recent_tweets_call',
+            type: 'tool_call',
+          },
+        ],
+      }),
+    ],
+  });
+  return toolResponse;
+};