Detailed agent errors

agentcoinorg · Nov 18, 2024 · 4c72086 · 4c72086
1 parent 6069d05
commit 4c72086
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Showing 2 changed files with 22 additions and 7 deletions.
diff --git a/prediction_prophet/benchmark/agents.py b/prediction_prophet/benchmark/agents.py
@@ -12,7 +12,7 @@
 from prediction_prophet.autonolas.research import make_prediction, get_urls_from_queries
 from prediction_prophet.autonolas.research import research as research_autonolas
 from prediction_prophet.functions.rephrase_question import rephrase_question
-from prediction_prophet.functions.research import Research, research as prophet_research
+from prediction_prophet.functions.research import NoResulsFoundError, NotEnoughScrapedSitesError, Research, research as prophet_research
 from prediction_prophet.functions.search import search
 from prediction_prophet.functions.utils import url_is_older_than
 from prediction_prophet.models.WebSearchResult import WebSearchResult
@@ -71,10 +71,12 @@ def __init__(
         temperature: float = 0.0,
         agent_name: str = "question-only",
         max_workers: t.Optional[int] = None,
+        logger: t.Union[logging.Logger, "Logger"] = logging.getLogger(),
     ):
         super().__init__(agent_name=agent_name, max_workers=max_workers)
         self.model: str = model
         self.temperature = temperature
+        self.logger = logger
 
     def predict(
         self, market_question: str
@@ -87,7 +89,7 @@ def predict(
                 temperature=self.temperature,
             )
         except ValueError as e:
-            print(f"Error in QuestionOnlyAgent's predict: {e}")
+            self.logger.error(f"Error in QuestionOnlyAgent's predict: {e}")
             return Prediction()
 
     def predict_restricted(
@@ -104,11 +106,13 @@ def __init__(
         agent_name: str = "olas",
         max_workers: t.Optional[int] = None,
         embedding_model: EmbeddingModel = EmbeddingModel.spacy,
+        logger: t.Union[logging.Logger, "Logger"] = logging.getLogger(),
     ):
         super().__init__(agent_name=agent_name, max_workers=max_workers)
         self.model: str = model
         self.temperature = temperature
         self.embedding_model = embedding_model
+        self.logger = logger
 
     def is_predictable(self, market_question: str) -> bool:
         result = is_predictable_binary(question=market_question)
@@ -135,7 +139,7 @@ def predict(self, market_question: str) -> Prediction:
                 temperature=self.temperature,
             )
         except ValueError as e:
-            print(f"Error in OlasAgent's predict: {e}")
+            self.logger.error(f"Error in OlasAgent's predict: {e}")
             return Prediction()
 
     def predict_restricted(
@@ -215,8 +219,11 @@ def predict(self, market_question: str) -> Prediction:
                 temperature=self.prediction_temperature,
                 include_reasoning=self.include_reasoning,
         )
-        except ValueError as e:
-            print(f"Error in PredictionProphet's predict: {e}")
+        except (NoResulsFoundError, NotEnoughScrapedSitesError) as e:
+            self.logger.warning(f"Problem in PredictionProphet's predict: {e}")
+            return Prediction()
+        except Exception as e:
+            self.logger.error(f"Error in PredictionProphet's predict: {e}")
             return Prediction()
 
     def predict_restricted(

diff --git a/prediction_prophet/functions/research.py b/prediction_prophet/functions/research.py
@@ -25,6 +25,14 @@ class Research(BaseModel):
     websites_scraped: list[WebScrapeResult]
 
 
+class NoResulsFoundError(ValueError):
+    pass
+
+
+class NotEnoughScrapedSitesError(ValueError):
+    pass
+
+
 @observe()
 def research(
     goal: str,
@@ -72,7 +80,7 @@ def research(
     )
 
     if not search_results_with_queries:
-        raise ValueError(f"No search results found for the goal {goal}.")
+        raise NoResulsFoundError(f"No search results found for the goal {goal}.")
 
     scrape_args = [result for (_, result) in search_results_with_queries]
     websites_to_scrape = set(result.url for result in scrape_args)
@@ -92,7 +100,7 @@ def research(
     unique_scraped_websites = set([result.url for result in scraped])
     if len(scraped) < min_scraped_sites:
         # Get urls that were not scraped
-        raise ValueError(
+        raise NotEnoughScrapedSitesError(
             f"Only successfully scraped content from "
             f"{len(unique_scraped_websites)} websites, out of a possible "
             f"{len(websites_to_scrape)} websites, which is less than the "