Only show the top contexts to the agent for the specific question

paperqa/agents/tools.py

@@ -251,8 +251,15 @@ async def gather_evidence(self, question: str, state: EnvironmentState) -> str:
 
         status = state.status
         logger.info(status)
+        # only show top n contexts for this particular question to the agent
         sorted_contexts = sorted(
-            state.session.contexts, key=lambda x: x.score, reverse=True
+            [
+                c
+                for c in state.session.contexts
+                if (c.question is None or c.question == question)
+            ],
+            key=lambda x: x.score,
+            reverse=True,
         )
 
         top_contexts = "\n".join(

paperqa/core.py

@@ -207,6 +207,7 @@ async def map_fxn_summary(
     return (
         Context(
             context=context,
+            question=question,
             text=Text(
                 text=text.text,
                 name=text.name,

paperqa/types.py

@@ -110,6 +110,13 @@ class Context(BaseModel):
     model_config = ConfigDict(extra="allow")
 
     context: str = Field(description="Summary of the text with respect to a question.")
+    question: str | None = Field(
+        default=None,
+        description=(
+            "Question that the context is summarizing for. "
+            "Note this can differ from the user query."
+        ),
+    )
     text: Text
     score: int = 5
 
@@ -236,6 +243,7 @@ def filter_content_for_user(self) -> None:
         self.contexts = [
             Context(
                 context=c.context,
+                question=c.question,
                 score=c.score,
                 text=Text(
                     text="",

tests/test_agents.py

@@ -670,10 +670,27 @@ def new_status(state: EnvironmentState) -> str:
 
         # now adjust to give the agent 2x pieces of evidence
         gather_evidence_tool.settings.agent.agent_evidence_n = 2
+        # also reset the question to ensure that contexts are
+        # only returned to the agent for the new question
+        new_question = "How does XAI relate to a self-explanatory model?"
         response = await gather_evidence_tool.gather_evidence(
-            session.question, state=env_state
+            new_question, state=env_state
         )
-
+        assert len({c.question for c in session.contexts}) == 2, "Expected 2 questions"
+        # now we make sure this is only for the old question
+        for context in session.contexts:
+            if context.question != new_question:
+                assert (
+                    context.context[:20] not in response
+                ), "gather_evidence should not return any contexts for the old question"
+        assert (
+            sum(
+                (1 if (context.context[:20] in response) else 0)
+                for context in session.contexts
+                if context.question == new_question
+            )
+            == 2
+        ), "gather_evidence should only return 2 contexts for the new question"
         split = re.split(
             r"(\d+) pieces of evidence, (\d+) of which were relevant",
             response,
@@ -899,6 +916,7 @@ def test_answers_are_striped() -> None:
         contexts=[
             Context(
                 context="bla",
+                question="foo",
                 text=Text(
                     name="text",
                     text="The meaning of life is 42.",