Use latest PMAT (mostly caching stuff)

labs_api/insights/insights.py

@@ -1,3 +1,5 @@
+from datetime import timedelta
+
 import fastapi
 from langchain.prompts import ChatPromptTemplate
 from langchain_openai import ChatOpenAI
@@ -9,44 +11,22 @@
     OmenMarket,
     OmenSubgraphHandler,
 )
+from prediction_market_agent_tooling.tools.caches.db_cache import db_cache
 from prediction_market_agent_tooling.tools.langfuse_ import (
     get_langfuse_langchain_config,
     observe,
 )
-from prediction_market_agent_tooling.tools.tavily_storage.tavily_models import (
-    TavilyResponse,
-    TavilyStorage,
-)
-from prediction_market_agent_tooling.tools.tavily_storage.tavily_storage import (
-    TavilyStorage,
-    tavily_search,
-)
+from prediction_market_agent_tooling.tools.tavily.tavily_models import TavilyResponse
+from prediction_market_agent_tooling.tools.tavily.tavily_search import tavily_search
 from prediction_market_agent_tooling.tools.utils import (
     LLM_SUPER_LOW_TEMPERATURE,
     utcnow,
 )
 
-from labs_api.insights.insights_cache import (
-    MarketInsightsResponse,
-    MarketInsightsResponseCache,
-)
-
-
-# Don't observe the cached version, as it will always return the same thing that's already been observed.
-def market_insights_cached(
-    market_id: HexAddress, cache: MarketInsightsResponseCache
-) -> MarketInsightsResponse:
-    """Returns `market_insights`, but cached daily."""
-    if (cached := cache.find(market_id)) is not None:
-        return cached
-
-    else:
-        new = market_insights(market_id)
-        if new.has_insights:
-            cache.save(new)
-        return new
+from labs_api.insights.insights_models import MarketInsightsResponse
 
 
+@db_cache(max_age=timedelta(days=3))
 @observe()
 def market_insights(market_id: HexAddress) -> MarketInsightsResponse:
     """Returns market insights for a given market on Omen."""
@@ -56,17 +36,19 @@ def market_insights(market_id: HexAddress) -> MarketInsightsResponse:
         raise fastapi.HTTPException(
             status_code=404, detail=f"Market with id `{market_id}` not found."
         )
+    except Exception as e:
+        logger.error(f"Failed to fetch market for `{market_id}`: {e}")
+        raise fastapi.HTTPException(status_code=500)
     try:
         tavily_response = tavily_search(
             market.question_title,
             search_depth="basic",
             include_answer=True,
             max_results=5,
-            tavily_storage=TavilyStorage("market_insights"),
         )
     except Exception as e:
         logger.error(f"Failed to get tavily_response for market `{market_id}`: {e}")
-        tavily_response = None
+        raise fastapi.HTTPException(status_code=500)
     try:
         summary = (
             tavily_response_to_summary(market, tavily_response)

labs_api/insights/insights_models.py

@@ -0,0 +1,40 @@
+from prediction_market_agent_tooling.gtypes import HexAddress
+from prediction_market_agent_tooling.tools.datetime_utc import DatetimeUTC
+from prediction_market_agent_tooling.tools.tavily.tavily_models import (
+    TavilyResponse,
+    TavilyResult,
+)
+from pydantic import BaseModel
+
+
+class MarketInsightResult(BaseModel):
+    url: str
+    title: str
+
+    @staticmethod
+    def from_tavily_result(tavily_result: TavilyResult) -> "MarketInsightResult":
+        return MarketInsightResult(url=tavily_result.url, title=tavily_result.title)
+
+
+class MarketInsightsResponse(BaseModel):
+    market_id: HexAddress
+    created_at: DatetimeUTC
+    summary: str | None
+    results: list[MarketInsightResult]
+
+    @staticmethod
+    def from_tavily_response(
+        market_id: HexAddress,
+        created_at: DatetimeUTC,
+        summary: str | None,
+        tavily_response: TavilyResponse,
+    ) -> "MarketInsightsResponse":
+        return MarketInsightsResponse(
+            market_id=market_id,
+            created_at=created_at,
+            summary=summary,
+            results=[
+                MarketInsightResult.from_tavily_result(result)
+                for result in tavily_response.results
+            ],
+        )

labs_api/invalid/invalid.py

@@ -5,31 +5,15 @@
     HexAddress,
     OmenSubgraphHandler,
 )
+from prediction_market_agent_tooling.tools.caches.db_cache import db_cache
 from prediction_market_agent_tooling.tools.is_invalid import is_invalid
 from prediction_market_agent_tooling.tools.langfuse_ import observe
 from prediction_market_agent_tooling.tools.utils import utcnow
 
-from labs_api.invalid.invalid_cache import (
-    MarketInvalidResponse,
-    MarketInvalidResponseCache,
-)
-
-
-# Don't observe the cached version, as it will always return the same thing that's already been observed.
-def market_invalid_cached(
-    market_id: HexAddress, cache: MarketInvalidResponseCache
-) -> MarketInvalidResponse:
-    """Returns `market_invalid`, but cached daily."""
-    if (cached := cache.find(market_id)) is not None:
-        return cached
-
-    else:
-        new = market_invalid(market_id)
-        if new.has_invalid:
-            cache.save(new)
-        return new
+from labs_api.invalid.invalid_models import MarketInvalidResponse
 
 
+@db_cache
 @observe()
 def market_invalid(market_id: HexAddress) -> MarketInvalidResponse:
     """Returns market invalid for a given market on Omen."""
@@ -39,13 +23,15 @@ def market_invalid(market_id: HexAddress) -> MarketInvalidResponse:
         raise fastapi.HTTPException(
             status_code=404, detail=f"Market with id `{market_id}` not found."
         )
+    except Exception as e:
+        logger.error(f"Failed to fetch market for `{market_id}`: {e}")
+        raise fastapi.HTTPException(status_code=500)
     try:
-        invalid = is_invalid(market.question_title)
+        return MarketInvalidResponse(
+            market_id=market_id,
+            created_at=utcnow(),
+            invalid=is_invalid(market.question_title),
+        )
     except Exception as e:
         logger.error(f"Failed to get is_invalid for market `{market_id}`: {e}")
-        invalid = None
-    return MarketInvalidResponse(
-        market_id=market_id,
-        created_at=utcnow(),
-        invalid=invalid,
-    )
+        raise fastapi.HTTPException(status_code=500)

labs_api/invalid/invalid_models.py

@@ -0,0 +1,11 @@
+from prediction_market_agent_tooling.markets.omen.omen_subgraph_handler import (
+    HexAddress,
+)
+from prediction_market_agent_tooling.tools.datetime_utc import DatetimeUTC
+from pydantic import BaseModel
+
+
+class MarketInvalidResponse(BaseModel):
+    market_id: HexAddress
+    created_at: DatetimeUTC
+    invalid: bool