Implement PredictProbabilityForQuestion function for microchain agent

.gitignore

@@ -6,3 +6,6 @@ __pycache__
 logs
 .mypy_cache
 .pytest_cache
+
+# Created on mech-client `interact` call
+acn_cert.txt

prediction_market_agent/agents/microchain_agent/functions.py

@@ -1,7 +1,9 @@
+import json
 import typing as t
 from decimal import Decimal
 
 from eth_utils import to_checksum_address
+from mech_client.interact import interact
 from microchain import Function
 from prediction_market_agent_tooling.markets.agent_market import AgentMarket
 from prediction_market_agent_tooling.markets.data_models import Currency, TokenAmount
@@ -12,13 +14,15 @@
 )
 
 from prediction_market_agent.agents.microchain_agent.utils import (
+    MechResult,
     MicroMarket,
     get_balance,
     get_binary_markets,
     get_boolean_outcome,
     get_example_market_id,
     get_no_outcome,
     get_yes_outcome,
+    saved_str_to_tmpfile,
 )
 from prediction_market_agent.utils import APIKeys
 
@@ -101,19 +105,40 @@ def __call__(self, market_id: str) -> list[str]:
 class PredictPropabilityForQuestion(MarketFunction):
     @property
     def description(self) -> str:
-        return "Use this function to research the probability of an event occuring"
+        return (
+            "Use this function to research perform research and predict the "
+            "probability of an event occuring. Returns the probability. The "
+            "one parameter is the market id of the prediction market you want "
+            "to predict the probability of. Note, this costs money to run."
+        )
 
     @property
     def example_args(self) -> list[str]:
-        return ["Will Joe Biden get reelected in 2024?"]
-
-    def __call__(self, a: str) -> float:
-        if a == "Will Joe Biden get reelected in 2024?":
-            return 0.41
-        if a == "Will Bitcoin hit 100k in 2024?":
-            return 0.22
+        return [get_example_market_id(self.market_type)]
 
-        return 0.0
+    def __call__(self, question: str) -> str:
+        private_key = APIKeys().bet_from_private_key.get_secret_value()
+        # 0.01 xDai is hardcoded cost for an interaction with the mech-client
+        MECH_CALL_XDAI_LIMIT = 0.011
+        account_balance = float(get_balance(market_type=self.market_type).amount)
+        if account_balance < MECH_CALL_XDAI_LIMIT:
+            return (
+                f"Your balance of {self.currency} ({account_balance}) is not "
+                f"large enough to make a mech call (min required "
+                f"{MECH_CALL_XDAI_LIMIT})."
+            )
+        with saved_str_to_tmpfile(private_key) as tmpfile_path:
+            response = interact(
+                prompt=question,
+                # Taken from https://github.com/valory-xyz/mech?tab=readme-ov-file#examples-of-deployed-mechs
+                agent_id=3,
+                private_key_path=tmpfile_path,
+                # To see a list of available tools, comment out the tool parameter
+                # and run the function. You will be prompted to select a tool.
+                tool="claude-prediction-online",
+            )
+            result = json.loads(response["result"])
+            return str(MechResult.model_validate(result).p_yes)
 
 
 class BuyTokens(MarketFunction):

prediction_market_agent/agents/microchain_agent/utils.py

@@ -1,4 +1,7 @@
+import os
+import tempfile
 import typing as t
+from contextlib import contextmanager
 from decimal import Decimal
 
 from prediction_market_agent_tooling.markets.agent_market import (
@@ -36,6 +39,13 @@ def __str__(self) -> str:
         return f"'{self.question}', id: {self.id}"
 
 
+class MechResult(BaseModel):
+    p_yes: float
+    p_no: float
+    confidence: float
+    info_utility: float
+
+
 def get_binary_markets(market_type: MarketType) -> list[AgentMarket]:
     # Get the 5 markets that are closing soonest
     cls = market_type.market_class
@@ -89,3 +99,15 @@ def get_example_market_id(market_type: MarketType) -> str:
         return "0x0020d13c89140b47e10db54cbd53852b90bc1391"
     else:
         raise ValueError(f"Market type '{market_type}' not supported")
+
+
+@contextmanager
+def saved_str_to_tmpfile(s: str) -> t.Iterator[str]:
+    # Write the string to the temporary file
+    with tempfile.NamedTemporaryFile(delete=False) as tmp:
+        tmp.write(s.encode())
+
+    yield tmp.name
+
+    # Finally remove the temporary file
+    os.remove(tmp.name)

prediction_market_agent/utils.py

@@ -1,6 +1,7 @@
 import typing as t
 
 from prediction_market_agent_tooling.config import APIKeys as APIKeysBase
+from prediction_market_agent_tooling.gtypes import PrivateKey
 from prediction_market_agent_tooling.tools.utils import (
     check_not_none,
     should_not_happen,
@@ -31,6 +32,13 @@ def tavily_api_key(self) -> SecretStr:
             self.TAVILY_API_KEY, "OPENAI_API_KEY missing in the environment."
         )
 
+    @property
+    def bet_from_private_key(self) -> PrivateKey:
+        return check_not_none(
+            self.BET_FROM_PRIVATE_KEY,
+            "BET_FROM_PRIVATE_KEY missing in the environment.",
+        )
+
 
 def get_market_prompt(question: str) -> str:
     prompt = (

pyproject.toml

@@ -21,28 +21,30 @@ google-search-results = "*"
 pytest = "*"
 llama-index = "~0.9.0"
 duckduckgo-search = "*"
-crewai = {extras = ["tools"], version = "^0.22.5"}
+crewai = {extras = ["tools"], version = "^0.11.0"}
 # metagpt = "*" # Commented out because requires super old version of langchain, and conflicts with crewai.
 replicate = "*"
 typer = "^0.9.0"
 web3 = "^6.14.0"
 mypy = "^1.8.0"
-types-requests = "^2.31.0.20240106"
 black = "^23.12.1"
 google-cloud-functions = "^1.16.0"
 google-cloud-resource-manager = "^1.12.0"
 poetry = "^1.7.1"
 poetry-plugin-export = "^1.6.0"
 functions-framework = "^3.5.0"
 cron-validator = "^1.0.8"
-prediction-market-agent-tooling = "^0.13.1"
+prediction-market-agent-tooling = {git = "https://github.com/gnosis/prediction-market-agent-tooling.git", rev = "evan/add-mech-client-dependency"}
 pydantic-settings = "^2.1.0"
 autoflake = "^2.2.1"
 isort = "^5.13.2"
 markdownify = "^0.11.6"
 tavily-python = "^0.3.1"
 # TODO remove when PR is merged
 microchain-python = {git = "https://github.com/evangriffiths/microchain.git", rev = "evan/token-tracker"}
+types-requests = "2.31.0.0"
+setuptools = "^69.2.0"
+mech-client = "^0.2.13"
 
 [build-system]
 requires = ["poetry-core"]

tests/agents/microchain/test_functions.py

@@ -7,23 +7,11 @@
 from prediction_market_agent_tooling.tools.hexbytes_custom import HexBytes
 
 from prediction_market_agent.agents.microchain_agent.functions import (
-    MARKET_FUNCTIONS,
-    MISC_FUNCTIONS,
-    BuyNo,
-    BuyYes,
-    GetBalance,
-    GetMarketProbability,
-    GetMarkets,
-    GetUserPositions,
-    SellNo,
-    SellYes,
-)
+    MARKET_FUNCTIONS, MISC_FUNCTIONS, BuyNo, BuyYes, GetBalance,
+    GetMarketProbability, GetMarkets, GetUserPositions,
+    PredictPropabilityForQuestion, SellNo, SellYes)
 from prediction_market_agent.agents.microchain_agent.utils import (
-    get_balance,
-    get_binary_markets,
-    get_no_outcome,
-    get_yes_outcome,
-)
+    get_balance, get_binary_markets, get_no_outcome, get_yes_outcome)
 from prediction_market_agent.utils import APIKeys
 from tests.utils import RUN_PAID_TESTS
 
@@ -160,3 +148,15 @@ def get_balances() -> tuple[float, float]:
         n_tokens_bought = after_tokens - before_tokens
         n_tokens_sold = after_tokens - final_tokens
         assert np.isclose(n_tokens_bought, n_tokens_sold, rtol=0.02)
+
+
+@pytest.mark.skipif(not RUN_PAID_TESTS, reason="This test costs money to run.")
+@pytest.mark.parametrize("market_type", [MarketType.OMEN])
+def test_predict_probability(market_type: MarketType) -> None:
+    """
+    Test calling a mech to predict the probability of a market
+    """
+    predict_probability = PredictPropabilityForQuestion(market_type=market_type)
+    market = get_binary_markets(market_type=market_type)[0]
+    p_yes = predict_probability(market.id)
+    assert 0.0 <= float(p_yes) <= 1.0