fix: update outdated configs and fix logging #95

agentverse/agents/base.py

@@ -6,6 +6,7 @@
 from pydantic import BaseModel, Field
 from agentverse.llms import BaseLLM
 
+from agentverse.logging import logger
 from agentverse.llms.utils import count_string_tokens
 from agentverse.memory import BaseMemory, ChatHistoryMemory
 from agentverse.message import Message
@@ -106,7 +107,7 @@ def remove_receiver(self, receiver: Union[Set[str], str]) -> None:
             try:
                 self.receiver.remove(receiver)
             except KeyError as e:
-                logging.warning(f"Receiver {receiver} not found.")
+                logger.warn(f"Receiver {receiver} not found.")
         elif isinstance(receiver, set):
             self.receiver = self.receiver.difference(receiver)
         else:

agentverse/agents/simulation_agent/prisoner_dilemma.py

@@ -1,10 +1,10 @@
 from __future__ import annotations
 
-import logging
 from string import Template
 from typing import TYPE_CHECKING, List
 
 from agentverse.message import Message
+from agentverse.logging import logger
 
 # from . import agent_registry
 # from .base import BaseAgent
@@ -30,12 +30,12 @@ def step(
                 parsed_response = self.output_parser.parse(self, environment, response)
                 break
             except Exception as e:
-                logging.error(e)
-                logging.warning("Retrying...")
+                logger.error(e)
+                logger.warn("Retrying...")
                 continue
 
         if parsed_response is None:
-            logging.error(f"{self.name} failed to generate valid response.")
+            logger.error(f"{self.name} failed to generate valid response.")
 
         message = Message(
             content=""
@@ -59,12 +59,12 @@ async def astep(
                 parsed_response = self.output_parser.parse(self, environment, response)
                 break
             except Exception as e:
-                logging.error(e)
-                logging.warning("Retrying...")
+                logger.error(e)
+                logger.warn("Retrying...")
                 continue
 
         if parsed_response is None:
-            logging.error(f"{self.name} failed to generate valid response.")
+            logger.error(f"{self.name} failed to generate valid response.")
 
         message = Message(
             content=""

agentverse/agents/simulation_agent/tool.py

@@ -1,4 +1,3 @@
-import logging
 from string import Template
 from typing import List, NamedTuple, Optional, Union
 
@@ -9,13 +8,15 @@
 from agentverse.memory import BaseMemory, ChatHistoryMemory
 from agentverse.message import Message
 from agentverse.utils import AgentAction, AgentFinish
+from agentverse.logging import logger
 
-#from . import agent_registry
-#from .base import BaseAgent
+# from . import agent_registry
+# from .base import BaseAgent
 
 from agentverse.agents import agent_registry
 from agentverse.agents.base import BaseAgent
 
+
 class ToolNotExistError(BaseException):
     """Exception raised when parsing output from a command fails."""
 
@@ -50,14 +51,14 @@ def step(self, env_description: str = "") -> Message:
                         )
                     break
                 except BaseException as e:
-                    logging.error(e)
-                    logging.warning("Retrying...")
+                    logger.error(e)
+                    logger.warn("Retrying...")
                     continue
             if parsed_response is None or isinstance(parsed_response, AgentFinish):
                 break
 
         if parsed_response is None:
-            logging.error(f"{self.name} failed to generate valid response.")
+            logger.error(f"{self.name} failed to generate valid response.")
 
         self._update_tool_memory(tool_observation)
 
@@ -92,14 +93,14 @@ async def astep(self, env_description: str = "") -> Message:
                         )
                     break
                 except BaseException as e:
-                    logging.error(e)
-                    logging.warning("Retrying...")
+                    logger.error(e)
+                    logger.warn("Retrying...")
                     continue
             if parsed_response is None or isinstance(parsed_response, AgentFinish):
                 break
 
         if parsed_response is None:
-            logging.error(f"{self.name} failed to generate valid response.")
+            logger.error(f"{self.name} failed to generate valid response.")
 
         self._update_tool_memory(tool_observation)
 

agentverse/environments/simulation_env/pokemon.py

@@ -1,10 +1,10 @@
 import asyncio
 import datetime
-import logging
 from typing import Any, Dict, List, Optional, Set
 
 # from agentverse.agents.agent import Agent
 from agentverse.agents.simulation_agent.conversation import BaseAgent
+from agentverse.logging import logger
 
 # from agentverse.environments.simulation_env.rules.base import Rule
 from agentverse.environments.simulation_env.rules.base import SimulationRule as Rule
@@ -167,7 +167,7 @@ def get_agent_to_location(self) -> Dict[str, str]:
     def print_messages(self, messages: List[Message]) -> None:
         for message in messages:
             if message is not None:
-                logging.info(f"{message.sender}: {message.content}")
+                logger.info(f"{message.sender}: {message.content}")
 
     def reset(self) -> None:
         """Reset the environment"""

agentverse/environments/simulation_env/rules/order/classroom.py

@@ -1,11 +1,11 @@
 from __future__ import annotations
 
-import logging
 import re
 from typing import TYPE_CHECKING, Any, List, Optional
 
 from . import order_registry as OrderRegistry
 from .base import BaseOrder
+from agentverse.logging import logger
 
 if TYPE_CHECKING:
     from agentverse.environments import BaseEnvironment
@@ -75,7 +75,7 @@ def get_next_agent_idx_grouped(self, environment: BaseEnvironment) -> List[int]:
         # `groups` should be set in the corresponding `visibility`,
         # and `group_speaker_mapping` should be maintained here.
         if "groups" not in environment.rule_params:
-            logging.warning(
+            logger.warn(
                 "The environment is grouped, but the grouping information is not provided."
             )
         groups = environment.rule_params.get(

agentverse/environments/simulation_env/sde_team.py

@@ -4,6 +4,7 @@
 import json
 
 from agentverse.agents.simulation_agent.conversation import BaseAgent
+from agentverse.logging import logger
 
 # from agentverse.environments.simulation_env.rules.base import Rule
 from agentverse.environments.simulation_env.rules.base import SimulationRule as Rule
@@ -116,7 +117,7 @@ async def step(self) -> List[Message]:
     def print_messages(self, messages: List[Message]) -> None:
         for message in messages:
             if message is not None:
-                logging.info(f"{message.sender}: {message.content}")
+                logger.info(f"{message.sender}: {message.content}")
 
     def reset(self) -> None:
         """Reset the environment"""

agentverse/environments/simulation_env/sde_team_given_tests.py

@@ -1,5 +1,4 @@
 import asyncio
-import logging
 from typing import Any, Dict, List
 import json
 
@@ -8,6 +7,7 @@
 # from agentverse.environments.simulation_env.rules.base import Rule
 from agentverse.environments.simulation_env.rules.base import SimulationRule as Rule
 from agentverse.message import Message
+from agentverse.logging import logger
 
 from .. import env_registry as EnvironmentRegistry
 from ..base import BaseEnvironment
@@ -104,7 +104,7 @@ async def step(self) -> List[Message]:
     def print_messages(self, messages: List[Message]) -> None:
         for message in messages:
             if message is not None:
-                logging.info(f"{message.sender}: {message.content}")
+                logger.info(f"{message.sender}: {message.content}")
 
     def reset(self) -> None:
         """Reset the environment"""

agentverse/llms/openai.py

@@ -22,7 +22,7 @@
     from openai.error import OpenAIError
 except ImportError:
     is_openai_available = False
-    logging.warning("openai package is not installed")
+    logger.warn("openai package is not installed")
 else:
     # openai.proxy = os.environ.get("http_proxy")
     # if openai.proxy is None:
@@ -37,7 +37,7 @@
         openai.api_version = "2023-05-15"
         is_openai_available = True
     else:
-        logging.warning(
+        logger.warn(
             "OpenAI API key is not set. Please set the environment variable OPENAI_API_KEY"
         )
         is_openai_available = False
@@ -110,7 +110,7 @@ def __init__(self, max_retry: int = 3, **kwargs):
         for k, v in args.items():
             args[k] = kwargs.pop(k, v)
         if len(kwargs) > 0:
-            logging.warning(f"Unused arguments: {kwargs}")
+            logger.warn(f"Unused arguments: {kwargs}")
         if args["model"] in LOCAL_LLMS:
             openai.api_base = "http://localhost:5000/v1"
         super().__init__(args=args, max_retry=max_retry)

agentverse/output_parser/output_parser.py

@@ -18,6 +18,7 @@
     from agentverse.agents.base import BaseAgent
     from agentverse.environments.base import BaseEnvironment
 
+
 class OutputParserError(Exception):
     """Exception raised when parsing output from a command fails."""
 
@@ -157,24 +158,38 @@ def parse(self, output: LLMResult) -> Union[AgentAction, AgentFinish]:
 class NlpClassroom9PlayersGroupParser(OutputParser):
     def parse(self, output: LLMResult) -> Union[AgentAction, AgentFinish]:
         text = output.content
-        cleaned_output = text.strip()
-        cleaned_output = re.sub(r"\n+", "\n", cleaned_output)
-        cleaned_output = cleaned_output.split("\n")
-        if not (
-            len(cleaned_output) == 2
-            and cleaned_output[0].startswith("Action:")
-            and cleaned_output[1].startswith("Action Input:")
-        ):
+        # cleaned_output = text.strip()
+        # cleaned_output = re.sub(r"\n+", "\n", cleaned_output)
+        # cleaned_output = cleaned_output.split("\n")
+        # if not (
+        #     len(cleaned_output) == 2
+        #     and cleaned_output[0].startswith("Action:")
+        #     and cleaned_output[1].startswith("Action Input:")
+        # ):
+        #     raise OutputParserError(text)
+        # action = cleaned_output[0][len("Action:") :].strip()
+        # action_input = cleaned_output[1][len("Action Input:") :].strip()
+        action_result = re.findall(r"Action:(.+)", text)
+        result = re.findall(r"Action:(.+?)Action Input:(.+)", text, re.DOTALL)
+        if len(action_result) == 0:
             raise OutputParserError(text)
-        action = cleaned_output[0][len("Action:") :].strip()
-        action_input = cleaned_output[1][len("Action Input:") :].strip()
+
+        action = action_result[0].strip()
+        if action not in ["Listen", "RaiseHand"]:
+            if len(result) == 0:
+                raise OutputParserError(text)
+            action_input = result[0][1].strip()
+        if action == "RaiseHand":
+            action_input = ""
+
         if action == "Speak":
             return AgentFinish({"output": action_input}, text)
-        elif action in ["CallOn", "RaiseHand", "GroupDiscuss"]:
+        elif action in ["CallOn", "GroupDiscuss", "RaiseHand"]:
             return AgentFinish({"output": f"[{action}] {action_input}"}, text)
-        elif action == "Listen":
+        elif action in ["Listen"]:
             return AgentFinish({"output": ""}, text)
         else:
+            action_input = result[0][1].strip()
             return AgentAction(action, action_input, text)
 
 

agentverse/tasks/simulation/math_problem_2players_tools/config.yaml

@@ -94,8 +94,8 @@ agents:
     prompt_template: *prompt
     verbose: true
     llm:
-      llm_type: text-davinci-003
-      model: text-davinci-003
+      llm_type: gpt-4
+      model: gpt-4
       temperature: 0.7
       max_tokens: 250
     output_parser:
@@ -110,8 +110,8 @@ agents:
     prompt_template: *prompt
     verbose: true
     llm:
-      llm_type: text-davinci-003
-      model: text-davinci-003
+      llm_type: gpt-4
+      model: gpt-4
       temperature: 0.7
       max_tokens: 250
     output_parser:

agentverse/tasks/simulation/nlp_classroom_3players_withtool/config.yaml

@@ -155,9 +155,8 @@ agents:
       5. Provide an envision towards the future development of neural networks.
       Your goal is to ensure that the students understand the material, so it's important to speak slowly and clearly. You don't necessarily have to strictly follow the course outline when teaching, you can also talk about some other relevant topics. Remember, in each round of conversation, your response should only address one topic at most. Please take your time and don't rush through the content.
     prompt_template: *professor_prompt
-    llm:
-      llm_type: text-davinci-003
-      model: text-davinci-003
+    ll gpt-4
+      model: gpt-4
       temperature: 0.7
       max_tokens: 250
     output_parser:
@@ -180,8 +179,8 @@ agents:
       prompt_template: *summary_prompt
       recursive: true
     llm:
-      llm_type: text-davinci-003
-      model: text-davinci-003
+      llm_type: gpt-4
+      model: gpt-4
       temperature: 0.7
       max_tokens: 100
     output_parser:
@@ -203,8 +202,8 @@ agents:
       prompt_template: *summary_prompt
       recursive: true
     llm:
-      llm_type: text-davinci-003
-      model: text-davinci-003
+      llm_type: gpt-4
+      model: gpt-4
       temperature: 0.7
       max_tokens: 100
     output_parser: