feat: add git workflow

.github/workflows/codex-pr-review.yml.disabled

@@ -0,0 +1,64 @@
+name: Codex PR Review
+on:
+  pull_request:
+    types: [opened]
+
+jobs:
+  codex:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+    outputs:
+      final_message: ${{ steps.run_codex.outputs.final-message }}
+    steps:
+      - uses: actions/checkout@v5
+        with:
+          # Explicitly check out the PR's merge commit.
+          ref: refs/pull/${{ github.event.pull_request.number }}/merge
+
+      - name: Pre-fetch base and head refs for the PR
+        run: |
+          git fetch --no-tags origin \
+            ${{ github.event.pull_request.base.ref }} \
+            +refs/pull/${{ github.event.pull_request.number }}/head
+
+      - name: Run Codex
+        id: run_codex
+        uses: openai/codex-action@v1
+        with:
+          openai-api-key: ${{ secrets.OPENAI_API_KEY }}
+          prompt: |
+            This is PR #${{ github.event.pull_request.number }} for ${{ github.repository }}.
+
+            Review ONLY the changes introduced by the PR, so consider:
+               git log --oneline ${{ github.event.pull_request.base.sha }}...${{ github.event.pull_request.head.sha }}
+
+            Suggest any improvements, potential bugs, or issues.
+            Be concise and specific in your feedback.
+
+            Pull request title and body:
+            ----
+            ${{ github.event.pull_request.title }}
+            ${{ github.event.pull_request.body }}
+
+  post_feedback:
+    runs-on: ubuntu-latest
+    needs: codex
+    if: needs.codex.outputs.final_message != ''
+    permissions:
+      issues: write
+      pull-requests: write
+    steps:
+      - name: Report Codex feedback
+        uses: actions/github-script@v7
+        env:
+          CODEX_FINAL_MESSAGE: ${{ needs.codex.outputs.final_message }}
+        with:
+          github-token: ${{ github.token }}
+          script: |
+            await github.rest.issues.createComment({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.payload.pull_request.number,
+              body: process.env.CODEX_FINAL_MESSAGE,
+            });

.github/workflows/pr-tests-and-format.yml

@@ -0,0 +1,26 @@
+name: PR Tests and Formatting
+
+on:
+  pull_request:
+
+jobs:
+  lint-and-test:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up uv
+        uses: astral-sh/setup-uv@v2
+        with:
+          python-version: "3.12"
+          cache: true
+
+      - name: Install dependencies
+        run: uv sync --frozen
+
+      - name: Check formatting with Black
+        run: uv run black . --check
+
+      - name: Run pytest
+        run: uv run pytest

pyproject.toml

@@ -15,7 +15,8 @@ dependencies = [
     "trustcall",
     "python-dotenv",
     "pytest",
-    "PyYAML"
+    "PyYAML",
+    "black"
 ]
 
 [tool.pytest.ini_options]

src/game/__init__.py

@@ -4,9 +4,17 @@
 
 from . import nodes
 from . import state
-from . import llm_strategy
+from .llm_strategy import llm_update_player_mindset, llm_generate_speech
 from . import rules
 from . import graph
 from . import config
 
-__all__ = ["nodes", "state", "llm_strategy", "rules", "graph", "config"]
+__all__ = [
+    "nodes",
+    "state",
+    "llm_update_player_mindset",
+    "llm_generate_speech",
+    "rules",
+    "graph",
+    "config",
+]

src/game/llm_strategy.py

@@ -28,18 +28,14 @@
 from typing import List, Dict, Any, Sequence
 
 from langchain_core.messages import HumanMessage, SystemMessage
-
 from trustcall import create_extractor
 
-from src.game.state import GameState, Speech, PlayerMindset, Suspicion, SelfBelief
-from src.tools.llm import create_llm
+from src.game.state import Speech, PlayerMindset, Suspicion, SelfBelief
+
 
 # Game rules are now managed by the configuration system
 # Use config.get_game_rules() to get game rules
 
-# --- LLM Clients ---
-llm_client = create_llm()
-
 
 # --- Helper Functions ---
 

src/game/nodes/player.py

@@ -27,9 +27,9 @@
 from ..llm_strategy import (
     llm_update_player_mindset,
     llm_generate_speech,
-    llm_client,  # Use the real LLM client
 )
 from ..metrics import metrics_collector
+from src.tools.llm import create_llm
 from ..state import (
     GameState,
     alive_players,
@@ -42,7 +42,14 @@
     merge_probs,
 )
 
-_llm_client = llm_client
+
+def _get_llm_client():
+    """Create and return an LLM client instance.
+
+    This function provides lazy initialization of the LLM client,
+    creating it only when needed and allowing for runtime configuration.
+    """
+    return create_llm()
 
 
 def _get_player_context(state: GameState, player_id: str):
@@ -104,8 +111,9 @@ def player_speech(state: GameState, player_id: str) -> Dict[str, Any]:
     private_state = cur_player_context["private"]
     existing_player_mindset = private_state.playerMindset
 
+    llm_client = _get_llm_client()
     updated_mindset = llm_update_player_mindset(
-        llm_client=_llm_client,
+        llm_client=llm_client,
         my_word=my_word,
         completed_speeches=state["completed_speeches"],
         players=state["players"],
@@ -117,7 +125,7 @@ def player_speech(state: GameState, player_id: str) -> Dict[str, Any]:
 
     # Generate speech using LLM
     new_speech_text = llm_generate_speech(
-        llm_client=_llm_client,
+        llm_client=llm_client,
         my_word=my_word,
         self_belief=updated_mindset.self_belief,
         suspicions=updated_mindset.suspicions,
@@ -236,8 +244,9 @@ def player_vote(state: GameState, player_id: str) -> Dict[str, Any]:
     private_state = cur_player_context["private"]
     existing_player_mindset = private_state.playerMindset
 
+    llm_client = _get_llm_client()
     updated_mindset = llm_update_player_mindset(
-        llm_client=_llm_client,
+        llm_client=llm_client,
         my_word=my_word,
         completed_speeches=state["completed_speeches"],
         players=state["players"],

tests/test_player_nodes.py

@@ -70,13 +70,17 @@ def base_player_state(player_id):
     }
 
 
+@patch("src.game.nodes.player._get_llm_client")
 @patch("src.game.nodes.player.llm_generate_speech")
 @patch("src.game.nodes.player.llm_update_player_mindset")
 def test_player_speech(
-    mock_infer, mock_speech, player_id, base_player_state: GameState
+    mock_infer, mock_speech, mock_get_llm, player_id, base_player_state: GameState
 ):
     """Tests the player_speech node with mocked LLM calls."""
     # Arrange: Configure mocks to return predictable values
+    mock_llm_client = MagicMock()
+    mock_get_llm.return_value = mock_llm_client
+
     mock_infer.return_value = PlayerMindset(
         self_belief=SelfBelief(role="civilian", confidence=0.9),
         suspicions={"c": Suspicion(role="spy", confidence=0.7, reason="vague")},
@@ -98,14 +102,19 @@ def test_player_speech(
     assert private_update.playerMindset.suspicions["c"].role == "spy"
 
     # Verify mocks were called correctly
+    mock_get_llm.assert_called_once()
     mock_infer.assert_called_once()
     mock_speech.assert_called_once()
 
 
+@patch("src.game.nodes.player._get_llm_client")
 @patch("src.game.nodes.player.llm_update_player_mindset")
-def test_player_vote(mock_infer, player_id, base_player_state: GameState):
+def test_player_vote(mock_infer, mock_get_llm, player_id, base_player_state: GameState):
     """Tests the player_vote node with mocked LLM calls."""
     # Arrange: Configure mocks
+    mock_llm_client = MagicMock()
+    mock_get_llm.return_value = mock_llm_client
+
     mock_infer.return_value = PlayerMindset(
         self_belief=SelfBelief(role="civilian", confidence=0.9),
         suspicions={"c": Suspicion(role="spy", confidence=0.8, reason="very vague")},
@@ -129,6 +138,7 @@ def test_player_vote(mock_infer, player_id, base_player_state: GameState):
     assert private_update.playerMindset.self_belief.role == "civilian"
 
     # Verify mocks
+    mock_get_llm.assert_called_once()
     mock_infer.assert_called_once()