Merge branch 'main' into pull/50/head

Author: ef95023

.env.example

@@ -0,0 +1,10 @@
+ANTHROPIC_API_KEY=
+OPENAI_API_KEY=
+EternalAI_API_KEY=
+EternalAI_API_URL=
+FARCASTER_MNEMONIC=
+TWITTER_CONSUMER_KEY=            
+TWITTER_CONSUMER_SECRET=          
+TWITTER_ACCESS_TOKEN=            
+TWITTER_ACCESS_TOKEN_SECRET=      
+TWITTER_USER_ID=      

README.md

@@ -1,14 +1,17 @@
 # ZerePy
 
-ZerePy is an open-source Python framework designed to let you deploy your own agents on X, powered by OpenAI or Anthropic LLMs.
+ZerePy is an open-source Python framework designed to let you deploy your own agents on X, powered by OpenAI/Anthropic/EternalAI LLMs.
 
-ZerePy is built from a modularized version of the Zerebro backend. With ZerePy, you can launch your own agent with 
+ZerePy is built from a modularized version of the Zerebro backend. With ZerePy, you can launch your own agent with
 similar core functionality as Zerebro. For creative outputs, you'll need to fine-tune your own model.
 
 ## Features
+
 - CLI interface for managing agents
-- Twitter integration
-- OpenAI/Anthropic LLM support
+- Twitter/X integration
+- Farcaster integration
+- Echochambers integration
+- OpenAI/Anthropic/EternalAI LLM support
 - Modular connection system
 
 ## Quickstart
@@ -24,15 +27,20 @@ https://replit.com/@blormdev/ZerePy?v=1
 ## Requirements
 
 System:
-- Python 3.10 or higher
+
+- Python 3.10 or higher (3.10 and 3.11 are best for beginner users)
 - Poetry 1.5 or higher
 
 API keys:
-  - LLM: make an account and grab an API key 
-      + OpenAI: https://platform.openai.com/api-keys.
-      + Anthropic: https://console.anthropic.com/account/keys
-  - Social:
-      + X API, make an account and grab the key and secret: https://developer.x.com/en/docs/authentication/oauth-1-0a/api-key-and-secret
+
+- LLM: make an account and grab an API key (at least one)
+  - OpenAI: https://platform.openai.com/api-keys
+  - Anthropic: https://console.anthropic.com/account/keys
+  - EternalAI: https://eternalai.oerg/api
+- Social (based on your needs):
+  - X API: https://developer.x.com/en/docs/authentication/oauth-1-0a/api-key-and-secret
+  - Farcaster: Warpcast recovery phrase
+  - Echochambers: API key and endpoint
 
 ## Installation
 
@@ -41,16 +49,19 @@ API keys:
 Follow the steps here to use the official installation: https://python-poetry.org/docs/#installing-with-the-official-installer
 
 2. Clone the repository:
+
 ```bash
 git clone https://github.com/blorm-network/ZerePy.git
 ```
 
 3. Go to the `zerepy` directory:
+
 ```bash
 cd zerepy
 ```
 
 4. Install dependencies:
+
 ```bash
 poetry install --no-root
 ```
@@ -60,31 +71,66 @@ This will create a virtual environment and install all required dependencies.
 ## Usage
 
 1. Activate the virtual environment:
+
 ```bash
 poetry shell
 ```
 
 2. Run the application:
+
 ```bash
 poetry run python main.py
 ```
 
 ## Configure connections & launch an agent
 
-1. Configure your connections:
+1. Configure your desired connections:
+
    ```
-   configure-connection twitter
-   configure-connection openai
+   configure-connection twitter    # For Twitter/X integration
+   configure-connection openai     # For OpenAI
+   configure-connection anthropic  # For Anthropic
+   configure-connection farcaster  # For Farcaster
+   configure-connection eternalai  # For EternalAI
    ```
-4. Load your agent (usually one is loaded by default, which can be set using the CLI or in agents/general.json):
+
+2. Use `list-connections` to see all available connections and their status
+
+3. Load your agent (usually one is loaded by default, which can be set using the CLI or in agents/general.json):
+
    ```
    load-agent example
    ```
-5. Start your agent:
+
+4. Start your agent:
    ```
    start
    ```
 
+## Platform Features
+
+### Twitter/X
+
+- Post tweets from prompts
+- Read timeline with configurable count
+- Reply to tweets in timeline
+- Like tweets in timeline
+
+### Farcaster
+
+- Post casts
+- Reply to casts
+- Like and requote casts
+- Read timeline
+- Get cast replies
+
+### Echochambers
+
+- Post new messages to rooms
+- Reply to messages based on room context
+- Read room history
+- Get room information and topics
+
 ## Create your own agent
 
 The secret to having a good output from the agent is to provide as much detail as possible in the configuration file. Craft a story and a context for the agent, and pick very good examples of tweets to include.
@@ -95,29 +141,27 @@ Create a new JSON file in the `agents` directory following this structure:
 
 ```json
 {
- "name": "ExampleAgent",
- "bio": [
-   "You are ExampleAgent, the example agent created to showcase the capabilities of ZerePy.",
-   "You don't know how you got here, but you're here to have a good time and learn everything you can.",
-   "You are naturally curious, and ask a lot of questions."
-  ],
-  "traits": [
-    "Curious",
-    "Creative",
-    "Innovative",
-    "Funny"
-  ],
-  "examples": [
-    "This is an example tweet.",
-    "This is another example tweet."
+  "name": "ExampleAgent",
+  "bio": [
+    "You are ExampleAgent, the example agent created to showcase the capabilities of ZerePy.",
+    "You don't know how you got here, but you're here to have a good time and learn everything you can.",
+    "You are naturally curious, and ask a lot of questions."
   ],
-  "loop_delay": 60,
+  "traits": ["Curious", "Creative", "Innovative", "Funny"],
+  "examples": ["This is an example tweet.", "This is another example tweet."],
+  "example_accounts" : ["X_username_to_use_for_tweet_examples"]
+  "loop_delay": 900,
   "config": [
     {
       "name": "twitter",
       "timeline_read_count": 10,
-      "tweet_interval": 900,
-      "own_tweet_replies_count":2
+      "own_tweet_replies_count": 2,
+      "tweet_interval": 5400
+    },
+    {
+      "name": "farcaster",
+      "timeline_read_count": 10,
+      "cast_interval": 60
     },
     {
       "name": "openai",
@@ -129,16 +173,30 @@ Create a new JSON file in the `agents` directory following this structure:
     }
   ],
   "tasks": [
-    {"name": "post-tweet", "weight": 1},
-    {"name": "reply-to-tweet", "weight": 1},
-    {"name": "like-tweet", "weight": 1}
+    { "name": "post-tweet", "weight": 1 },
+    { "name": "reply-to-tweet", "weight": 1 },
+    { "name": "like-tweet", "weight": 1 }
   ]
 }
 ```
 
+## Available Commands
+
+Use `help` in the CLI to see all available commands. Key commands include:
+
+- `list-agents`: Show available agents
+- `load-agent`: Load a specific agent
+- `agent-loop`: Start autonomous behavior
+- `agent-action`: Execute single action
+- `list-connections`: Show available connections
+- `list-actions`: Show available actions for a connection
+- `configure-connection`: Set up a new connection
+- `chat`: Start interactive chat with agent
+
 ## Star History
 
 [![Star History Chart](https://api.star-history.com/svg?repos=blorm-network/ZerePy&type=Date)](https://star-history.com/#blorm-network/ZerePy&Date)
 
 ---
+
 Made with ♥ @Blorm.xyz

agents/example.json

@@ -15,6 +15,9 @@
     "This is an example tweet.",
     "This is another example tweet."
   ],
+  "example_accounts": [
+    "0xzerebro"
+  ],
   "loop_delay": 900,
   "config": [
     {
@@ -40,6 +43,11 @@
       "name": "eternalai",
       "model": "NousResearch/Hermes-3-Llama-3.1-70B-FP8",
       "chain_id": "45762"
+    },
+    {
+      "name": "ollama",
+      "base_url": "http://localhost:11434",
+      "model": "llama3.2"
     }
   ],
   "tasks": [

src/action_handler.py

@@ -0,0 +1,20 @@
+import logging
+
+logger = logging.getLogger("agent")
+
+action_registry = {}    
+
+def register_action(action_name):
+    def decorator(func):
+        action_registry[action_name] = func
+        return func
+    return decorator
+
+def execute_action(agent, action_name, **kwargs):
+    if action_name in action_registry:
+       return action_registry[action_name](agent, **kwargs)
+    else:
+        logger.error(f"Action {action_name} not found")
+        return None
+    
+

src/actions/echochamber_actions.py

@@ -0,0 +1,104 @@
+import time,random
+from src.action_handler import register_action
+from src.prompts import REPLY_ECHOCHAMBER_PROMPT, POST_ECHOCHAMBER_PROMPT
+
+@register_action("post-echochambers")
+def post_echochambers(agent, **kwargs):
+    current_time = time.time()
+
+    # Initialize state
+    if "echochambers_last_message" not in agent.state:
+        agent.state["echochambers_last_message"] = 0
+    if "echochambers_replied_messages" not in agent.state:
+        agent.state["echochambers_replied_messages"] = set()
+    
+    if current_time - agent.state["echochambers_last_message"] > agent.echochambers_message_interval:
+        agent.logger.info("\n📝 GENERATING NEW ECHOCHAMBERS MESSAGE")
+        
+        # Generate message based on room topic and tags
+        previous_messages = agent.connection_manager.connections["echochambers"].sent_messages
+        previous_content = "\n".join([f"- {msg['content']}" for msg in previous_messages])
+        agent.logger.info(f"Found {len(previous_messages)} messages in post history")
+        
+        prompt  = POST_ECHOCHAMBER_PROMPT.format(
+            room_topic=agent.state['room_info']['topic'],
+            tags=", ".join(agent.state['room_info']['tags']),
+            previous_content=previous_content
+        )
+        message = agent.prompt_llm(prompt)
+        
+        if message:
+            agent.logger.info(f"\n🚀 Posting message: '{message[:69]}...'")
+            agent.connection_manager.perform_action(
+                connection_name="echochambers",
+                action_name="send-message",
+                params=[message]  # Pass as list of values
+            )
+            agent.state["echochambers_last_message"] = current_time
+            agent.logger.info("✅ Message posted successfully!")
+            return True
+    return False
+
+@register_action("reply-echochambers")
+def reply_echochambers(agent, **kwargs):
+    agent.logger.info("\n🔍 CHECKING FOR MESSAGES TO REPLY TO")
+    
+    # Initialize replied messages set if not exists
+    if "echochambers_replied_messages" not in agent.state:
+        agent.state["echochambers_replied_messages"] = set()
+        
+
+    # Get recent messages
+    history = agent.connection_manager.perform_action(
+        connection_name="echochambers",
+        action_name="get-room-history",
+        params={}
+    )
+
+    if history:
+        agent.logger.info(f"Found {len(history)} messages in history")
+        for message in history:
+            message_id = message.get('id')
+            sender = message.get('sender', {})
+            sender_username = sender.get('username')
+            content = message.get('content', '')
+            
+            if not message_id or not sender_username or not content:
+                agent.logger.warning(f"Skipping message with missing fields: {message}")
+                continue
+            
+
+            # Skip if:
+            # 1. It's our message
+            # 2. We've already replied to it
+            if (sender_username == agent.connection_manager.connections["echochambers"].config["sender_username"] or 
+                message_id in agent.state.get("echochambers_replied_messages", set())):
+                agent.logger.info(f"Skipping message from {sender_username} (already replied or own message)")
+                continue
+                
+            agent.logger.info(f"\n💬 GENERATING REPLY to: @{sender_username} - {content[:69]}...")
+            
+            refer_username = random.random() < 0.7
+            username_prompt = f"Refer the sender by their @{sender_username}" if refer_username else "Respond without directly referring to the sender"
+            prompt = REPLY_ECHOCHAMBER_PROMPT.format(
+                content=content,
+                sender_username=sender_username,
+                room_topic=agent.state['room_info']['topic'],
+                tags=", ".join(agent.state['room_info']['tags']),
+                username_prompt=username_prompt
+            )
+            reply = agent.prompt_llm(prompt)
+            
+            if reply:
+                agent.logger.info(f"\n🚀 Posting reply: '{reply[:69]}...'")
+                agent.connection_manager.perform_action(
+                    connection_name="echochambers",
+                    action_name="send-message",
+                    params=[reply]
+                )
+                agent.state["echochambers_replied_messages"].add(message_id)
+                agent.logger.info("✅ Reply posted successfully!")
+                return True
+    else:
+        agent.logger.info("No messages in history")
+    return False