Added deployment option for hackathon participants

deployment/README.md

@@ -0,0 +1,29 @@
+# Deployment of agents
+
+This folder contains scripts for quickly deploying your agent to a cloud provider (Modal) and have it executed on a cron schedule. Additionally, a local setup is also provided.
+
+## Pre-requisites
+
+We suggest using Modal (modal.com) for deploying the agents for its simplicity. We don't use Modal in production.
+
+For deploying on Modal, follow the steps below:
+- Create account (https://modal.com/)
+- Install modal, setup auth key
+- Run 
+```bash
+pip install modal
+python3 -m modal setup
+```
+
+## Run locally
+
+```shell
+modal run deployment/local_runner.py
+```
+
+## Run on the cloud
+
+- Run
+```shell
+modal deploy --name execute_agent deployment/remote_runner.py
+```

deployment/agent.py

@@ -0,0 +1,12 @@
+from eth_typing import HexAddress, HexStr
+from prediction_market_agent_tooling.markets.omen.omen_subgraph_handler import OmenSubgraphHandler
+
+
+def run():
+    # This class entails the agent logic for placing bets.
+    # It could call for example the main() function from the trader folder.
+    market_id = HexAddress(HexStr("0x57c6bab1ba758d911f11e67ef323acebcfca04b7"))
+    print("Started function execution")
+    market = OmenSubgraphHandler().get_omen_market_by_market_id(market_id)
+    print(f"market {market}")
+    print("Finished function execution")

deployment/local_runner.py

@@ -0,0 +1,15 @@
+import modal
+
+from deployment.agent import run
+
+app = modal.App("example-get-started")
+
+
+@app.function()
+def execute():
+    run()
+
+
+@app.local_entrypoint()
+def main():
+    execute.local()

deployment/remote_runner.py

@@ -0,0 +1,11 @@
+from modal import Image, App, Period
+
+from deployment.agent import run
+
+image = Image.from_registry("ghcr.io/gnosis/prediction-market-agent:main").pip_install("pydantic==2.6.1")
+
+app = App(image=image)
+
+@app.function(schedule=Period(minutes=5))
+def execute_remote():
+    run()