Use patched logger (#128)

main.py

@@ -1,5 +1,5 @@
 import typer
-from loguru import logger
+from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.markets.agent_market import SortBy
 from prediction_market_agent_tooling.markets.markets import (
     MarketType,

prediction_market_agent/agents/custom_agent.py

@@ -2,7 +2,7 @@
 from typing import Optional
 
 import requests
-from loguru import logger
+from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.markets.agent_market import AgentMarket
 from prediction_market_agent_tooling.tools.utils import (
     check_not_none,

prediction_market_agent/agents/known_outcome_agent/benchmark.py

@@ -3,14 +3,14 @@
 from datetime import timedelta
 
 from dotenv import load_dotenv
-from loguru import logger
 from prediction_market_agent_tooling.benchmark.agents import AbstractBenchmarkedAgent
 from prediction_market_agent_tooling.benchmark.benchmark import Benchmarker
 from prediction_market_agent_tooling.benchmark.utils import (
     OutcomePrediction,
     Prediction,
 )
 from prediction_market_agent_tooling.gtypes import Probability
+from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.markets.markets import AgentMarket
 from prediction_market_agent_tooling.tools.utils import check_not_none, utcnow
 from pydantic import BaseModel

prediction_market_agent/agents/known_outcome_agent/deploy.py

@@ -1,8 +1,8 @@
 import random
 import typing as t
 
-from loguru import logger
 from prediction_market_agent_tooling.deploy.agent import Answer, DeployableAgent
+from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.markets.agent_market import AgentMarket
 from prediction_market_agent_tooling.markets.data_models import BetAmount
 from prediction_market_agent_tooling.markets.omen.omen import OmenAgentMarket

prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py

@@ -4,8 +4,8 @@
 from langchain.prompts import ChatPromptTemplate
 from langchain_core.callbacks import Callbacks
 from langchain_openai import ChatOpenAI
-from loguru import logger
 from prediction_market_agent_tooling.gtypes import Probability
+from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.tools.utils import utcnow
 from pydantic import BaseModel
 

prediction_market_agent/agents/replicate_to_omen_agent/deploy.py

@@ -1,9 +1,9 @@
 from datetime import timedelta
 
-from loguru import logger
 from prediction_market_agent_tooling.config import APIKeys, PrivateCredentials
 from prediction_market_agent_tooling.deploy.agent import DeployableAgent
 from prediction_market_agent_tooling.gtypes import xdai_type
+from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.markets.markets import MarketType
 from prediction_market_agent_tooling.markets.omen.omen import (
     redeem_from_all_user_positions,

prediction_market_agent/agents/replicate_to_omen_agent/omen_replicate.py

@@ -1,8 +1,8 @@
 from datetime import datetime, timedelta
 
-from loguru import logger
 from prediction_market_agent_tooling.config import PrivateCredentials
 from prediction_market_agent_tooling.gtypes import ChecksumAddress, wei_type, xDai
+from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.markets.agent_market import FilterBy, SortBy
 from prediction_market_agent_tooling.markets.categorize import infer_category
 from prediction_market_agent_tooling.markets.markets import (

prediction_market_agent/agents/replicate_to_omen_agent/omen_resolve_replicated.py

@@ -1,8 +1,8 @@
 from datetime import timedelta
 
-from loguru import logger
 from prediction_market_agent_tooling.config import PrivateCredentials
 from prediction_market_agent_tooling.gtypes import HexAddress, HexBytes
+from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.markets.omen.data_models import RealityQuestion
 from prediction_market_agent_tooling.markets.omen.omen_resolving import (
     claim_bonds_on_realitio_questions,

prediction_market_agent/agents/think_thoroughly_agent/benchmark.py

@@ -2,7 +2,6 @@
 from datetime import datetime, timedelta
 
 import typer
-from loguru import logger
 from prediction_market_agent_tooling.benchmark.agents import (
     AbstractBenchmarkedAgent,
     FixedAgent,
@@ -14,6 +13,7 @@
     Prediction,
 )
 from prediction_market_agent_tooling.gtypes import Probability
+from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.markets.agent_market import (
     AgentMarket,
     FilterBy,

prediction_market_agent/agents/think_thoroughly_agent/think_thoroughly_agent.py

@@ -3,8 +3,8 @@
 from crewai import Agent, Crew, Process, Task
 from langchain_core.language_models import BaseChatModel
 from langchain_openai import ChatOpenAI
-from loguru import logger
 from prediction_market_agent_tooling.deploy.agent import Answer
+from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.tools.parallelism import par_generator
 from prediction_market_agent_tooling.tools.utils import utcnow
 from pydantic import BaseModel

prediction_market_agent/tools/streamlit_utils.py

@@ -1,7 +1,7 @@
 import typing as t
 
 import streamlit as st
-from loguru import logger
+from prediction_market_agent_tooling.loggers import logger
 
 if t.TYPE_CHECKING:
     from loguru import Message

prediction_market_agent/tools/web_scrape/markdown.py

@@ -1,8 +1,8 @@
 import requests
 import tenacity
 from bs4 import BeautifulSoup
-from loguru import logger
 from markdownify import markdownify
+from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.tools.cache import persistent_inmemory_cache
 from requests import Response
 

pyproject.toml

@@ -35,7 +35,7 @@ poetry = "^1.7.1"
 poetry-plugin-export = "^1.6.0"
 functions-framework = "^3.5.0"
 cron-validator = "^1.0.8"
-prediction-market-agent-tooling = { version = "^0.21.0", extras = ["langchain", "google", "mech-client"] }
+prediction-market-agent-tooling = { version = "^0.22.0", extras = ["langchain", "google", "mech-client"] }
 pydantic-settings = "^2.1.0"
 autoflake = "^2.2.1"
 isort = "^5.13.2"