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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,36 @@ | ||
| { | ||
| "name": "EternalAI", | ||
| "bio": [ | ||
| "You are EternalAI, 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." | ||
| ], | ||
| "loop_delay": 900, | ||
| "config": [ | ||
| { | ||
| "name": "twitter", | ||
| "timeline_read_count": 10, | ||
| "own_tweet_replies_count":2, | ||
| "tweet_interval": 5400 | ||
| }, | ||
| { | ||
| "name": "eternalai", | ||
| "model": "unsloth/Llama-3.3-70B-Instruct-bnb-4bit" | ||
| } | ||
| ], | ||
| "tasks": [ | ||
| {"name": "post-tweet", "weight": 1}, | ||
| {"name": "reply-to-tweet", "weight": 1}, | ||
| {"name": "like-tweet", "weight": 1} | ||
| ] | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,207 @@ | ||
| import logging | ||
| import os | ||
| from typing import Dict, Any | ||
| from dotenv import load_dotenv, set_key | ||
| from openai import OpenAI | ||
| from src.connections.base_connection import BaseConnection, Action, ActionParameter | ||
|
|
||
| logger = logging.getLogger(__name__) | ||
|
|
||
|
|
||
| class EternalAIConnectionError(Exception): | ||
| """Base exception for EternalAI connection errors""" | ||
| pass | ||
|
|
||
|
|
||
| class EternalAIConfigurationError(EternalAIConnectionError): | ||
| """Raised when there are configuration/credential issues""" | ||
| pass | ||
|
|
||
|
|
||
| class EternalAIAPIError(EternalAIConnectionError): | ||
| """Raised when EternalAI API requests fail""" | ||
| pass | ||
|
|
||
|
|
||
| class EternalAIConnection(BaseConnection): | ||
| def __init__(self, config: Dict[str, Any]): | ||
| super().__init__(config) | ||
| self._client = None | ||
|
|
||
| @property | ||
| def is_llm_provider(self) -> bool: | ||
| return True | ||
|
|
||
| def validate_config(self, config: Dict[str, Any]) -> Dict[str, Any]: | ||
| """Validate EternalAI configuration from JSON""" | ||
| required_fields = ["model"] | ||
| missing_fields = [field for field in required_fields if field not in config] | ||
|
|
||
| if missing_fields: | ||
| raise ValueError(f"Missing required configuration fields: {', '.join(missing_fields)}") | ||
|
|
||
| # Validate model exists (will be checked in detail during configure) | ||
| if not isinstance(config["model"], str): | ||
| raise ValueError("model must be a string") | ||
|
|
||
| return config | ||
|
|
||
| def register_actions(self) -> None: | ||
| """Register available EternalAI actions""" | ||
| self.actions = { | ||
| "generate-text": Action( | ||
| name="generate-text", | ||
| parameters=[ | ||
| ActionParameter("prompt", True, str, "The input prompt for text generation"), | ||
| ActionParameter("system_prompt", True, str, "System prompt to guide the model"), | ||
| ActionParameter("model", False, str, "Model to use for generation") | ||
| ], | ||
| description="Generate text using EternalAI models" | ||
| ), | ||
| "check-model": Action( | ||
| name="check-model", | ||
| parameters=[ | ||
| ActionParameter("model", True, str, "Model name to check availability") | ||
| ], | ||
| description="Check if a specific model is available" | ||
| ), | ||
| "list-models": Action( | ||
| name="list-models", | ||
| parameters=[], | ||
| description="List all available EternalAI models" | ||
| ) | ||
| } | ||
|
|
||
| def _get_client(self) -> OpenAI: | ||
| """Get or create EternalAI client""" | ||
| if not self._client: | ||
| api_key = os.getenv("EternalAI_API_KEY") | ||
| api_url = os.getenv("EternalAI_API_URL") | ||
| if not api_key: | ||
| raise EternalAIConfigurationError("EternalAI API key not found in environment") | ||
| self._client = OpenAI(api_key=api_key, base_url=api_url) | ||
| return self._client | ||
|
|
||
| def configure(self) -> bool: | ||
| """Sets up EternalAI API authentication""" | ||
| print("\n🤖 EternalAI API SETUP") | ||
|
|
||
| if self.is_configured(): | ||
| print("\nEternalAI API is already configured.") | ||
| response = input("Do you want to reconfigure? (y/n): ") | ||
| if response.lower() != 'y': | ||
| return True | ||
|
|
||
| print("\n📝 To get your EternalAI API credentials:") | ||
| print("1. Go to https://eternalai.org/api") | ||
| print("2. Generate an API Key") | ||
| print("3. Use API url as https://api.eternalai.org/v1/") | ||
|
|
||
| api_key = input("\nEnter your EternalAI API key: ") | ||
| api_url = input("\nEnter your EternalAI API url: ") | ||
|
|
||
| try: | ||
| if not os.path.exists('.env'): | ||
| with open('.env', 'w') as f: | ||
| f.write('') | ||
|
|
||
| set_key('.env', 'EternalAI_API_KEY', api_key) | ||
| set_key('.env', 'EternalAI_API_URL', api_url) | ||
|
|
||
| # Validate the API key by trying to list models | ||
| client = OpenAI(api_key=api_key, base_url=api_url) | ||
| client.models.list() | ||
|
|
||
| print("\n✅ EternalAI API configuration successfully saved!") | ||
| print("Your API key has been stored in the .env file.") | ||
| return True | ||
|
|
||
| except Exception as e: | ||
| logger.error(f"Configuration failed: {e}") | ||
| return False | ||
|
|
||
| def is_configured(self, verbose=False) -> bool: | ||
| """Check if EternalAI API key is configured and valid""" | ||
| try: | ||
| load_dotenv() | ||
| api_key = os.getenv('EternalAI_API_KEY') | ||
| api_url = os.getenv('EternalAI_API_URL') | ||
| if not api_key or not api_url: | ||
| return False | ||
|
|
||
| client = OpenAI(api_key=api_key, base_url=api_url) | ||
| client.models.list() | ||
| return True | ||
|
|
||
| except Exception as e: | ||
| if verbose: | ||
| logger.debug(f"Configuration check failed: {e}") | ||
| return False | ||
|
|
||
| def generate_text(self, prompt: str, system_prompt: str, model: str = None, **kwargs) -> str: | ||
| """Generate text using EternalAI models""" | ||
| try: | ||
| client = self._get_client() | ||
|
|
||
| # Use configured model if none provided | ||
| if not model: | ||
| model = self.config["model"] | ||
| print("model", model) | ||
| completion = client.chat.completions.create( | ||
| model=model, | ||
| messages=[ | ||
| {"role": "system", "content": system_prompt}, | ||
| {"role": "user", "content": prompt}, | ||
| ], | ||
| ) | ||
|
|
||
| return completion.choices[0].message.content | ||
|
|
||
| except Exception as e: | ||
| raise EternalAIAPIError(f"Text generation failed: {e}") | ||
|
|
||
| def check_model(self, model, **kwargs): | ||
| try: | ||
| client = self._get_client | ||
| try: | ||
| client.models.retrieve(model=model) | ||
| # If we get here, the model exists | ||
| return True | ||
| except Exception: | ||
| return False | ||
| except Exception as e: | ||
| raise EternalAIAPIError(e) | ||
|
|
||
| def list_models(self, **kwargs) -> None: | ||
| """List all available EternalAI models""" | ||
| try: | ||
| client = self._get_client() | ||
| response = client.models.list().data | ||
| # | ||
| fine_tuned_models = [ | ||
| model for model in response | ||
| if model.owned_by in ["organization", "user", "organization-owner"] | ||
| ] | ||
| # | ||
| if fine_tuned_models: | ||
| logger.info("\nFINE-TUNED MODELS:") | ||
| for i, model in enumerate(fine_tuned_models): | ||
| logger.info(f"{i + 1}. {model.id}") | ||
|
|
||
| except Exception as e: | ||
| raise EternalAIAPIError(f"Listing models failed: {e}") | ||
|
|
||
| def perform_action(self, action_name: str, kwargs) -> Any: | ||
| """Execute a Twitter action with validation""" | ||
| if action_name not in self.actions: | ||
| raise KeyError(f"Unknown action: {action_name}") | ||
|
|
||
| action = self.actions[action_name] | ||
| errors = action.validate_params(kwargs) | ||
| if errors: | ||
| raise ValueError(f"Invalid parameters: {', '.join(errors)}") | ||
|
|
||
| # Call the appropriate method based on action name | ||
| method_name = action_name.replace('-', '_') | ||
| method = getattr(self, method_name) | ||
| return method(**kwargs) |