Merge branch 'dev' into code_intepreter

tests/metagpt/actions/test_action_node.py

@@ -8,7 +8,7 @@
 from typing import List, Tuple
 
 import pytest
-from pydantic import ValidationError
+from pydantic import BaseModel, Field, ValidationError
 
 from metagpt.actions import Action
 from metagpt.actions.action_node import ActionNode, ReviewMode, ReviseMode
@@ -241,6 +241,47 @@ def test_create_model_class_with_mapping():
     assert value == ["game.py", "app.py", "static/css/styles.css", "static/js/script.js", "templates/index.html"]
 
 
+class ToolDef(BaseModel):
+    tool_name: str = Field(default="a", description="tool name", examples=[])
+    description: str = Field(default="b", description="tool description", examples=[])
+
+
+class Task(BaseModel):
+    task_id: int = Field(default=1, description="task id", examples=[1, 2, 3])
+    name: str = Field(default="Get data from ...", description="task name", examples=[])
+    dependent_task_ids: List[int] = Field(default=[], description="dependent task ids", examples=[1, 2, 3])
+    tool: ToolDef = Field(default=ToolDef(), description="tool use", examples=[])
+
+
+class Tasks(BaseModel):
+    tasks: List[Task] = Field(default=[], description="tasks", examples=[])
+
+
+def test_action_node_from_pydantic_and_print_everything():
+    node = ActionNode.from_pydantic(Task)
+    print("1. Tasks")
+    print(Task().model_dump_json(indent=4))
+    print(Tasks.model_json_schema())
+    print("2. Task")
+    print(Task.model_json_schema())
+    print("3. ActionNode")
+    print(node)
+    print("4. node.compile prompt")
+    prompt = node.compile(context="")
+    assert "tool_name" in prompt, "tool_name should be in prompt"
+    print(prompt)
+    print("5. node.get_children_mapping")
+    print(node._get_children_mapping())
+    print("6. node.create_children_class")
+    children_class = node._create_children_class()
+    print(children_class)
+    import inspect
+
+    code = inspect.getsource(Tasks)
+    print(code)
+    assert "tasks" in code, "tasks should be in code"
+
+
 if __name__ == "__main__":
     test_create_model_class()
     test_create_model_class_with_mapping()

tests/metagpt/learn/test_google_search.py

@@ -1,27 +1,21 @@
-import asyncio
-
+import pytest
 from pydantic import BaseModel
 
 from metagpt.learn.google_search import google_search
+from metagpt.tools import SearchEngineType
 
 
-async def mock_google_search():
+@pytest.mark.asyncio
+async def test_google_search(search_engine_mocker):
     class Input(BaseModel):
         input: str
 
     inputs = [{"input": "ai agent"}]
-
     for i in inputs:
         seed = Input(**i)
-        result = await google_search(seed.input)
+        result = await google_search(
+            seed.input,
+            engine=SearchEngineType.SERPER_GOOGLE,
+            serper_api_key="mock-serper-key",
+        )
         assert result != ""
-
-
-def test_suite():
-    loop = asyncio.get_event_loop()
-    task = loop.create_task(mock_google_search())
-    loop.run_until_complete(task)
-
-
-if __name__ == "__main__":
-    test_suite()

tests/metagpt/strategy/test_solver.py

@@ -0,0 +1,47 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2024/1/31 13:54
+@Author  : alexanderwu
+@File    : test_solver.py
+"""
+import pytest
+
+from metagpt.actions.action_graph import ActionGraph
+from metagpt.llm import LLM
+from metagpt.strategy.search_space import SearchSpace
+from metagpt.strategy.solver import NaiveSolver
+
+
+@pytest.mark.asyncio
+async def test_solver():
+    from metagpt.actions.write_prd_an import (
+        COMPETITIVE_ANALYSIS,
+        ISSUE_TYPE,
+        PRODUCT_GOALS,
+        REQUIREMENT_POOL,
+    )
+
+    graph = ActionGraph()
+    graph.add_node(ISSUE_TYPE)
+    graph.add_node(PRODUCT_GOALS)
+    graph.add_node(COMPETITIVE_ANALYSIS)
+    graph.add_node(REQUIREMENT_POOL)
+    graph.add_edge(ISSUE_TYPE, PRODUCT_GOALS)
+    graph.add_edge(PRODUCT_GOALS, COMPETITIVE_ANALYSIS)
+    graph.add_edge(PRODUCT_GOALS, REQUIREMENT_POOL)
+    graph.add_edge(COMPETITIVE_ANALYSIS, REQUIREMENT_POOL)
+    search_space = SearchSpace()
+    llm = LLM()
+    context = "Create a 2048 game"
+    solver = NaiveSolver(graph, search_space, llm, context)
+    await solver.solve()
+
+    print("## graph.nodes")
+    print(graph.nodes)
+    for k, v in graph.nodes.items():
+        print(f"{v.key} | prevs: {[i.key for i in v.prevs]} | nexts: {[i.key for i in v.nexts]}")
+
+    assert len(graph.nodes) == 4
+    assert len(graph.execution_order) == 4
+    assert graph.execution_order == [ISSUE_TYPE.key, PRODUCT_GOALS.key, COMPETITIVE_ANALYSIS.key, REQUIREMENT_POOL.key]