Update prophet with reduced false errors

[kongzii]

No description provided.

[coderabbitai]

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Walkthrough

The changes in this pull request focus on modifications to the DeployableTraderAgentER class and its subclasses within the deploy.py file. Key updates include alterations to error handling in the answer_binary_market method, enhancements to logging capabilities, and adjustments to the instantiation of various PredictionProphetAgent models. New attributes have been introduced to manage betting strategies and market trading dates, reflecting a comprehensive refinement of the agents' functionalities.

Changes

File Path

Change Summary

prediction_market_agent/agents/prophet_agent/deploy.py

- Modified error handling in answer_binary_market method of DeployableTraderAgentER. - Updated logging to show prediction.outcome_prediction. - Added logger parameter in DeployableOlasEmbeddingOAAgent. - Updated load methods to instantiate PredictionProphetAgent with various model versions and parameters. - Defined bet_on_n_markets_per_run attribute across subclasses. - Introduced trade_on_markets_created_after attribute in DeployablePredictionProphetGPT4oAgentNewMarketTrader. - Added new classes extending DeployableTraderAgentER.

Possibly related PRs

• Migrate prophet #366: This PR modifies the DeployableTraderAgentER class and its answer_binary_market method, which is directly related to the changes made in the main PR regarding error handling and logging in the same method.
• Add missing agents to agent_app #382: This PR adds a new property method model to the DeployableTraderAgentER class, which is relevant as it pertains to the same class modified in the main PR.
• Prediction prophets based on o1 #469: This PR introduces new classes that extend DeployableTraderAgentER, which is the base class modified in the main PR, indicating a direct relationship through shared class hierarchy.
• Update DeployableTraderAgent betting stategies for max profit, based on historical simulations #494: This PR updates the get_betting_strategy method in DeployableTraderAgentER, which is relevant as the main PR also involves modifications to the betting strategies in subclasses of this class.
• Reduce bet_on_n_markets_per_run for expensive agents #534: This PR introduces new classes and modifies existing ones in deploy.py, including DeployablePredictionProphetGPTo1PreviewAgent, which is directly related to the changes made in the main PR regarding the bet_on_n_markets_per_run attribute.
• Add prophet-gpt4o agent that trades on new markets #537: This PR adds a new class DeployablePredictionProphetGPT4oAgentNewMarketTrader, which extends the functionality of the DeployablePredictionProphetGPT4oAgent, a class mentioned in the main PR, indicating a direct relationship through shared class hierarchy.

Suggested reviewers

• evangriffiths

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[coderabbitai]

Actionable comments posted: 0

🧹 Outside diff range and nitpick comments (2)

prediction_market_agent/agents/prophet_agent/deploy.py (2)

161-163: Consider model version management strategy

The implementation uses date-versioned models (e.g., "gpt-4o-2024-08-06", "o1-preview-2024-09-12"). Consider:

1. Implementing a version management strategy to handle model deprecations
2. Centralizing temperature constraints in a configuration file
3. Adding validation for temperature settings

Consider creating a model configuration class:

class ModelConfig:
    def __init__(self, name: str, supported_temperatures: list[float]):
        self.name = name
        self.supported_temperatures = supported_temperatures

    def validate_temperature(self, temp: float) -> None:
        if temp not in self.supported_temperatures:
            raise ValueError(f"Model {self.name} only supports temperatures: {self.supported_temperatures}")

Also applies to: 186-194, 208-216

---

Line range hint 78-79: Consider externalizing the deployment date configuration

The hardcoded deployment date (2024, 10, 31) could cause issues if:

1. The code is redeployed to other environments
2. The date needs to be adjusted for different trading strategies

Consider moving this to a configuration file or environment variable:

from datetime import datetime
from prediction_market_agent_tooling.tools.utils import DatetimeUTC

class Config:
    MARKET_TRADE_START_DATE: DatetimeUTC = DatetimeUTC.fromisoformat(
        os.getenv('MARKET_TRADE_START_DATE', '2024-10-31T00:00:00Z')
    )

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📥 Commits

Reviewing files that changed from the base of the PR and between 0166254 and 5396f1f.

⛔ Files ignored due to path filters (2)

• poetry.lock is excluded by !**/*.lock, !**/*.lock
• pyproject.toml is excluded by !**/*.toml

📒 Files selected for processing (1)

• prediction_market_agent/agents/prophet_agent/deploy.py (2 hunks)

🔇 Additional comments (1)

prediction_market_agent/agents/prophet_agent/deploy.py (1)

41-41: Verify error handling for None predictions

The removal of the None check on prediction.outcome_prediction could potentially lead to NoneType errors. While this aligns with reducing "false errors" (PR objective), we should ensure that:

1. The upstream predict method guarantees non-None outcome_prediction
2. Or the caller properly handles potential None returns