Coinflip agent deployment (#64)

.dockerignore

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+# Docker specific ignores:
+.git
+
+# .gitignore ignores:
+.env
+.agents_workspace
+.cache
+__pycache__
+*.egg-info
+logs
+.mypy_cache
+.pytest_cache

.gitignore

@@ -1,5 +1,3 @@
-requirements.txt
-.venv
 .env
 .agents_workspace
 .cache

Dockerfile

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+# Install Poetry and create venv in the builder step,
+# then copy the venv to the runtime image, so that the runtime image is as small as possible.
+FROM --platform=linux/amd64 python:3.10.14-slim-bookworm AS builder
+
+RUN pip install poetry==1.8.2
+
+ENV POETRY_NO_INTERACTION=1 \
+    POETRY_VIRTUALENVS_IN_PROJECT=1 \
+    POETRY_VIRTUALENVS_CREATE=1 \
+    POETRY_CACHE_DIR=/tmp/poetry_cache
+
+WORKDIR /app
+
+COPY pyproject.toml poetry.lock ./
+
+RUN --mount=type=cache,target=$POETRY_CACHE_DIR poetry install --no-root --only main
+
+FROM --platform=linux/amd64 python:3.10.14-slim-bookworm AS runtime
+
+ENV VIRTUAL_ENV=/app/.venv \
+    PATH="/app/.venv/bin:$PATH"
+
+WORKDIR /app
+
+COPY --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
+
+COPY prediction_market_agent ./prediction_market_agent
+
+ENV PYTHONPATH=/app
+
+CMD ["bash", "-c", "python prediction_market_agent/run_agent.py ${runnable_agent_name} ${market_type}"]

build.sh

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+#!/bin/bash
+# TODO: This should be automated as part of CI/CD pipeline, but for now, execute it locally on the main branch.
+docker build . -t ghcr.io/gnosis/pma:latest && docker push ghcr.io/gnosis/pma:latest

prediction_market_agent/agents/coinflip_agent/deploy.py

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+import random
+import typing as t
+
+from prediction_market_agent_tooling.deploy.agent import DeployableAgent
+from prediction_market_agent_tooling.markets.agent_market import AgentMarket
+
+
+class DeployableCoinFlipAgent(DeployableAgent):
+    def pick_markets(self, markets: t.Sequence[AgentMarket]) -> t.Sequence[AgentMarket]:
+        return random.sample(markets, 1)
+
+    def answer_binary_market(self, market: AgentMarket) -> bool | None:
+        return random.choice([True, False])

prediction_market_agent/run_agent.py

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+"""
+Entrypoint for running the agent in GKE.
+If the agent adheres to PMAT standard (subclasses DeployableAgent), 
+simply add the agent to the `RunnableAgent` enum and then `RUNNABLE_AGENTS` dict.
+
+Can also be executed locally, simply by running `python prediction_market_agent/run_agent.py <agent> <market_type>`.
+"""
+
+from enum import Enum
+
+import typer
+from prediction_market_agent_tooling.markets.markets import MarketType
+
+from prediction_market_agent.agents.coinflip_agent.deploy import DeployableCoinFlipAgent
+
+
+class RunnableAgent(str, Enum):
+    coinflip = "coinflip"
+
+
+RUNNABLE_AGENTS = {
+    RunnableAgent.coinflip: DeployableCoinFlipAgent,
+}
+
+
+def main(agent: RunnableAgent, market_type: MarketType) -> None:
+    RUNNABLE_AGENTS[agent]().run(market_type)
+
+
+if __name__ == "__main__":
+    typer.run(main)