Add isort and autoflake to CI

.github/workflows/python_ci.yaml

@@ -50,3 +50,23 @@ jobs:
       - uses: ./.github/actions/python_prepare
       - name: Check with black
         run: poetry run black --check .
+
+  autoflake:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - uses: ./.github/actions/python_prepare
+      - name: Check with autoflake
+        run: |
+          poetry run autoflake --in-place --remove-all-unused-imports --remove-unused-variables --recursive .
+          git diff --exit-code --quiet || exit 1
+
+  isort:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - uses: ./.github/actions/python_prepare
+      - name: Check with isort
+        run: |
+          poetry run isort --profile black .
+          git diff --exit-code --quiet || exit 1

main.py

@@ -1,14 +1,16 @@
-import typer
-import prediction_market_agent as pma
 from decimal import Decimal
-from prediction_market_agent.agents.all_agents import AgentType, get_agent
+
+import typer
 from prediction_market_agent_tooling.markets.markets import (
     MarketType,
     get_bet_amount,
     get_binary_markets,
     place_bet,
 )
 
+import prediction_market_agent as pma
+from prediction_market_agent.agents.all_agents import AgentType, get_agent
+
 
 def main(
     market_type: MarketType = MarketType.MANIFOLD,
@@ -18,8 +20,6 @@ def main(
     """
     Picks one market and answers it, optionally placing a bet.
     """
-    keys = pma.utils.APIKeys()
-
     # Pick a market
     market = get_binary_markets(market_type)[0].to_agent_market()
 

prediction_market_agent/__init__.py

@@ -1,2 +0,0 @@
-from . import utils
-from . import agents

prediction_market_agent/agents/__init__.py

@@ -1,7 +0,0 @@
-from . import langchain_agent
-from . import autogen_agent
-from . import always_yes
-from . import llamaindex_agent
-from . import metagpt_agent
-from . import crewai_agent
-from . import custom_agent

prediction_market_agent/agents/all_agents.py

@@ -1,16 +1,17 @@
 import typing as t
 from enum import Enum
+
 from prediction_market_agent.agents.abstract import AbstractAgent
-from prediction_market_agent.agents.langchain_agent import LangChainAgent
-from prediction_market_agent.agents.autogen_agent import AutoGenAgent
 from prediction_market_agent.agents.always_yes import AlwaysYesAgent
-from prediction_market_agent.agents.llamaindex_agent import LlamaIndexAgent
-from prediction_market_agent.agents.metagpt_agent import MetaGPTAgent
+from prediction_market_agent.agents.autogen_agent import AutoGenAgent
 from prediction_market_agent.agents.crewai_agent import CrewAIAgent
 from prediction_market_agent.agents.custom_agent import (
-    CustomAgentOpenAi,
     CustomAgentLlama,
+    CustomAgentOpenAi,
 )
+from prediction_market_agent.agents.langchain_agent import LangChainAgent
+from prediction_market_agent.agents.llamaindex_agent import LlamaIndexAgent
+from prediction_market_agent.agents.metagpt_agent import MetaGPTAgent
 
 
 class AgentType(str, Enum):

prediction_market_agent/agents/always_yes.py

@@ -1,6 +1,7 @@
-from prediction_market_agent.agents.abstract import AbstractAgent
 from prediction_market_agent_tooling.markets.data_models import AgentMarket
 
+from prediction_market_agent.agents.abstract import AbstractAgent
+
 
 class AlwaysYesAgent(AbstractAgent):
     """

prediction_market_agent/agents/autogen_agent.py

@@ -1,14 +1,14 @@
-import autogen
 import re
 import typing as t
 
+import autogen
 from autogen.agentchat.contrib.gpt_assistant_agent import GPTAssistantAgent
+from prediction_market_agent_tooling.markets.data_models import AgentMarket
 
 from prediction_market_agent import utils
 from prediction_market_agent.agents.abstract import AbstractAgent
 from prediction_market_agent.tools.google_search import GoogleSearchTool
 from prediction_market_agent.tools.web_scrape import WebScrapingTool
-from prediction_market_agent_tooling.markets.data_models import AgentMarket
 
 
 class AutoGenAgent(AbstractAgent):

prediction_market_agent/agents/crewai_agent.py

@@ -1,8 +1,9 @@
 import json
-from prediction_market_agent.agents.abstract import AbstractAgent
-from prediction_market_agent_tooling.markets.data_models import AgentMarket
 
 from langchain_community.tools import DuckDuckGoSearchRun
+from prediction_market_agent_tooling.markets.data_models import AgentMarket
+
+from prediction_market_agent.agents.abstract import AbstractAgent
 
 # TODO can use langchain's @tool decorator on our own tool methods to create a
 # tool useable by a crew agent
@@ -32,7 +33,7 @@ def __init__(self) -> None:
         )
 
     def answer_binary_market(self, market: AgentMarket) -> bool:
-        from crewai import Task, Crew
+        from crewai import Crew, Task
 
         task1 = Task(
             description=(

prediction_market_agent/agents/custom_agent.py

@@ -1,24 +1,26 @@
 import json
-import requests
 from typing import Optional
+
+import requests
+from prediction_market_agent_tooling.markets.data_models import AgentMarket
+from prediction_market_agent_tooling.tools.utils import (
+    check_not_none,
+    should_not_happen,
+)
+
 from prediction_market_agent import utils
 from prediction_market_agent.agents.abstract import AbstractAgent
 from prediction_market_agent.ai_models.abstract_ai_models import (
-    Message,
     AbstractAiChatModel,
+    Message,
 )
 from prediction_market_agent.ai_models.llama_ai_models import ChatReplicateLLamaModel
 from prediction_market_agent.ai_models.openai_ai_models import ChatOpenAIModel
 from prediction_market_agent.tools.google_search import google_search
+from prediction_market_agent.tools.tool_exception_handler import tool_exception_handler
 from prediction_market_agent.tools.web_scrape_structured import (
     web_scrape_structured_and_summarized,
 )
-from prediction_market_agent.tools.tool_exception_handler import tool_exception_handler
-from prediction_market_agent_tooling.tools.utils import (
-    check_not_none,
-    should_not_happen,
-)
-from prediction_market_agent_tooling.markets.data_models import AgentMarket
 
 
 class CustomAgent(AbstractAgent):

prediction_market_agent/agents/langchain_agent.py

@@ -1,11 +1,9 @@
-from langchain.agents import load_tools
-from langchain.agents import initialize_agent
-from langchain.agents import AgentType
+from langchain.agents import AgentType, initialize_agent, load_tools
 from langchain_community.llms import OpenAI
+from prediction_market_agent_tooling.markets.data_models import AgentMarket
 
 from prediction_market_agent import utils
 from prediction_market_agent.agents.abstract import AbstractAgent
-from prediction_market_agent_tooling.markets.data_models import AgentMarket
 
 
 class LangChainAgent(AbstractAgent):

prediction_market_agent/agents/llamaindex_agent.py

@@ -1,12 +1,12 @@
 from llama_index.agent import OpenAIAgent
 from llama_index.llms import OpenAI
 from llama_index.tools import FunctionTool
+from prediction_market_agent_tooling.markets.data_models import AgentMarket
 
+from prediction_market_agent import utils
 from prediction_market_agent.agents.abstract import AbstractAgent
 from prediction_market_agent.tools.google_search import google_search
 from prediction_market_agent.tools.web_scrape import web_scrape
-from prediction_market_agent import utils
-from prediction_market_agent_tooling.markets.data_models import AgentMarket
 
 
 class LlamaIndexAgent(AbstractAgent):

prediction_market_agent/agents/metagpt_agent.py

@@ -1,11 +1,12 @@
 import asyncio
-import dotenv
 import json
 import os
 
-from prediction_market_agent.agents.abstract import AbstractAgent
-from prediction_market_agent_tooling.tools.utils import check_not_none
+import dotenv
 from prediction_market_agent_tooling.markets.data_models import AgentMarket
+from prediction_market_agent_tooling.tools.utils import check_not_none
+
+from prediction_market_agent.agents.abstract import AbstractAgent
 
 
 class MetaGPTAgent(AbstractAgent):

prediction_market_agent/ai_models/abstract_ai_models.py

@@ -1,4 +1,5 @@
 from typing import Optional
+
 from pydantic import BaseModel
 
 

prediction_market_agent/ai_models/llama_ai_models.py

@@ -1,11 +1,13 @@
+from enum import Enum
+from typing import Literal, Optional
+
+import replicate
+from prediction_market_agent_tooling.tools.utils import should_not_happen
+
 from prediction_market_agent.ai_models.abstract_ai_models import (
     AbstractAiChatModel,
     Message,
 )
-from enum import Enum
-from typing import Optional, Literal
-from prediction_market_agent_tooling.tools.utils import should_not_happen
-import replicate
 
 
 class LlamaRole(Enum):

prediction_market_agent/ai_models/openai_ai_models.py

@@ -1,17 +1,19 @@
-from prediction_market_agent.ai_models.abstract_ai_models import (
-    AbstractAiChatModel,
-    Message,
-)
 from enum import Enum
+from typing import Literal, Optional
+
 from openai import OpenAI
-from typing import Optional, Literal
 from openai.types.chat.chat_completion import ChatCompletion
 from openai.types.chat.chat_completion_message_param import (
     ChatCompletionMessageParam,
     ChatCompletionSystemMessageParam,
     ChatCompletionUserMessageParam,
 )
 
+from prediction_market_agent.ai_models.abstract_ai_models import (
+    AbstractAiChatModel,
+    Message,
+)
+
 ROLE_KEY = "role"
 CONTENT_KEY = "content"
 

prediction_market_agent/tools/betting_strategies.py

@@ -1,27 +1,23 @@
+import typing as t
 from decimal import Decimal
 from functools import reduce
-import numpy as np
-import typing as t
-from web3 import Web3
-from prediction_market_agent_tooling.markets.data_models import (
-    BetAmount,
-    Currency,
-)
 
+import numpy as np
+from prediction_market_agent_tooling.gtypes import Probability, wei_type, xDai
+from prediction_market_agent_tooling.markets.data_models import BetAmount, Currency
+from prediction_market_agent_tooling.markets.markets import MarketType
 from prediction_market_agent_tooling.markets.omen import (
-    omen_calculate_buy_amount,
     OmenMarket,
+    omen_calculate_buy_amount,
 )
-from prediction_market_agent_tooling.markets.markets import MarketType
 from prediction_market_agent_tooling.tools.gnosis_rpc import GNOSIS_RPC_URL
+from prediction_market_agent_tooling.tools.utils import check_not_none
 from prediction_market_agent_tooling.tools.web3_utils import (
-    xdai_to_wei,
-    wei_to_xdai,
     ONE_XDAI,
+    wei_to_xdai,
+    xdai_to_wei,
 )
-from prediction_market_agent_tooling.gtypes import Probability, xDai, wei_type
-from prediction_market_agent_tooling.tools.utils import check_not_none
-
+from web3 import Web3
 
 OutcomeIndex = t.Literal[0, 1]
 

prediction_market_agent/tools/web_scrape.py

@@ -1,10 +1,9 @@
 import bs4
 import requests
-
 from langchain.chains.summarize import load_summarize_chain
-from langchain_openai import ChatOpenAI
 from langchain.prompts import PromptTemplate
 from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_openai import ChatOpenAI
 
 
 def _summary(objective: str, content: str) -> str:

prediction_market_agent/tools/web_scrape_structured.py

@@ -1,5 +1,6 @@
 import requests
 from bs4 import BeautifulSoup, Comment, Tag
+
 from prediction_market_agent.tools.web_scrape import _summary
 
 

prediction_market_agent/utils.py

@@ -1,9 +1,10 @@
 import typing as t
+
+from prediction_market_agent_tooling.config import APIKeys as APIKeysBase
 from prediction_market_agent_tooling.tools.utils import (
     check_not_none,
     should_not_happen,
 )
-from prediction_market_agent_tooling.config import APIKeys as APIKeysBase
 
 
 class APIKeys(APIKeysBase):