Merge pull request #32 from gnosis/evan/tidy

Update PMAT version and remove broken tests

main.py

@@ -1,10 +1,9 @@
 from decimal import Decimal
 
 import typer
-from prediction_market_agent_tooling.markets.markets import (
-    MarketType,
-    get_binary_markets,
-)
+from prediction_market_agent_tooling.markets.agent_market import SortBy
+from prediction_market_agent_tooling.markets.markets import MARKET_TYPE_MAP, MarketType
+from prediction_market_agent_tooling.tools.utils import check_not_none
 
 import prediction_market_agent as pma
 from prediction_market_agent.agents.all_agents import AgentType, get_agent
@@ -19,7 +18,8 @@ def main(
     Picks one market and answers it, optionally placing a bet.
     """
     # Pick a market
-    market = get_binary_markets(market_type)[0]
+    cls = check_not_none(MARKET_TYPE_MAP.get(market_type))
+    market = cls.get_binary_markets(limit=1, sort_by=SortBy.NEWEST)[0]
 
     # Create the agent and run it
     agent = get_agent(agent_type)

prediction_market_agent/agents/autogen_agent.py

@@ -18,7 +18,7 @@ def get_base_llm_config(self) -> dict[str, t.Any]:
             "config_list": [
                 {
                     "model": "gpt-4",
-                    "api_key": keys.openai_api_key,
+                    "api_key": keys.openai_api_key.get_secret_value(),
                 }
             ],
             "temperature": 0,

prediction_market_agent/agents/langchain_agent.py

@@ -12,12 +12,18 @@
 class LangChainAgent(AbstractAgent):
     def __init__(self, llm: Optional[BaseLLM] = None) -> None:
         keys = utils.APIKeys()
-        llm = OpenAI(openai_api_key=keys.openai_api_key) if not llm else llm
+        llm = (
+            OpenAI(openai_api_key=keys.openai_api_key.get_secret_value())
+            if not llm
+            else llm
+        )
         # Can use pre-defined search tool
         # TODO: Tavily tool could give better results
         # https://docs.tavily.com/docs/tavily-api/langchain
         tools = load_tools(
-            ["serpapi", "llm-math"], llm=llm, serpapi_api_key=keys.serp_api_key
+            ["serpapi", "llm-math"],
+            llm=llm,
+            serpapi_api_key=keys.serp_api_key.get_secret_value(),
         )
         self._agent = initialize_agent(
             tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True

prediction_market_agent/tools/google_search.py

@@ -4,7 +4,11 @@
 
 
 def google_search(query: str) -> list[str]:
-    params = {"q": query, "api_key": utils.APIKeys().serp_api_key, "num": 4}
+    params = {
+        "q": query,
+        "api_key": utils.APIKeys().serp_api_key.get_secret_value(),
+        "num": 4,
+    }
     search = serpapi.GoogleSearch(params)
     urls = [result["link"] for result in search.get_dict()["organic_results"]]
     return urls

prediction_market_agent/utils.py

@@ -5,20 +5,21 @@
     check_not_none,
     should_not_happen,
 )
+from pydantic import SecretStr
 
 
 class APIKeys(APIKeysBase):
-    SERP_API_KEY: t.Optional[str] = None
-    OPENAI_API_KEY: t.Optional[str] = None
+    SERP_API_KEY: t.Optional[SecretStr] = None
+    OPENAI_API_KEY: t.Optional[SecretStr] = None
 
     @property
-    def serp_api_key(self) -> str:
+    def serp_api_key(self) -> SecretStr:
         return check_not_none(
             self.SERP_API_KEY, "SERP_API_KEY missing in the environment."
         )
 
     @property
-    def openai_api_key(self) -> str:
+    def openai_api_key(self) -> SecretStr:
         return check_not_none(
             self.OPENAI_API_KEY, "OPENAI_API_KEY missing in the environment."
         )

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 = "0.2.6"
+prediction-market-agent-tooling = "^0.5.0"
 pydantic-settings = "^2.1.0"
 autoflake = "^2.2.1"
 isort = "^5.13.2"