Implemented PaperQAEnvironment.from_task

paperqa/agents/env.py

@@ -12,6 +12,7 @@
     ToolRequestMessage,
     ToolResponseMessage,
 )
+from aviary.env import ENV_REGISTRY
 from aviary.utils import MultipleChoiceQuestion
 from lmi import EmbeddingModel, LiteLLMModel
 
@@ -222,6 +223,10 @@ def __init__(
         self._embedding_model = embedding_model
         self._session_id = session_id
 
+    @classmethod
+    def from_task(cls, task: str) -> Self:
+        return cls(query=task, settings=Settings(), docs=Docs())
+
     def make_tools(self) -> list[Tool]:
         return settings_to_tools(
             settings=self._settings,
@@ -346,3 +351,6 @@ def __deepcopy__(self, memo) -> Self:
         # tool functions within the tools
         copy_self.tools = copy_self.make_tools()
         return copy_self
+
+
+ENV_REGISTRY["paperqa"] = "paperqa.agents.env", PaperQAEnvironment.__name__

tests/test_agents.py

@@ -17,7 +17,13 @@
 
 import ldp.agent
 import pytest
-from aviary.core import Tool, ToolRequestMessage, ToolsAdapter, ToolSelector
+from aviary.core import (
+    Environment,
+    Tool,
+    ToolRequestMessage,
+    ToolsAdapter,
+    ToolSelector,
+)
 from ldp.agent import MemoryAgent, SimpleAgent
 from ldp.graph.memory import Memory, UIndexMemoryModel
 from ldp.graph.ops import OpResult
@@ -29,6 +35,7 @@
 from paperqa.agents import SearchIndex, agent_query
 from paperqa.agents.env import (
     CLINICAL_STATUS_SEARCH_REGEX_PATTERN,
+    PaperQAEnvironment,
     clinical_trial_status,
     settings_to_tools,
 )
@@ -1041,3 +1048,22 @@ async def test_index_build_concurrency(agent_test_settings: Settings) -> None:
         "Expected fewer save_index with high batch size, but got"
         f" {high_batch_save_count} vs {low_batch_save_count}"
     )
+
+
+def test_env_from_name(subtests: SubTests) -> None:
+    assert "paperqa" in Environment.available()
+
+    with subtests.test(msg="only-task"):
+        env = Environment.from_name(  # type: ignore[var-annotated]
+            "paperqa", "How can you use XAI for chemical property prediction?"
+        )
+        assert isinstance(env, PaperQAEnvironment)
+
+    with subtests.test(msg="env-kwargs"):
+        env = Environment.from_name(
+            "paperqa",
+            query="How can you use XAI for chemical property prediction?",
+            settings=Settings(),
+            docs=Docs(),
+        )
+        assert isinstance(env, PaperQAEnvironment)