Add pqa tool (#16)

Author: ludomitch

src/fhda/config.py

@@ -1,5 +1,6 @@
 import os
 from pathlib import Path
+from futurehouse_client.models import Stage
 
 USE_DOCKER = bool(os.getenv("USE_DOCKER", "true").lower() == "true")
 NB_ENVIRONMENT_DOCKER_IMAGE = os.getenv(
@@ -20,3 +21,8 @@
     DATA_STORAGE_PATH = Path("/storage")
 
 VALID_FROM_TASK_KWARGS = ["run_notebook_on_edit", "exclude_tools"]
+
+# FutureHosue client config
+ENVIRONMENT = os.getenv("ENVIRONMENT", "prod")
+CROW_STAGE = getattr(Stage, ENVIRONMENT.upper(), Stage.PROD)
+PLATFORM_API_KEY = os.getenv("CROW_API_KEY")

src/fhda/data_analysis_env.py

@@ -12,6 +12,8 @@
 )
 
 from lmi.cost_tracker import GLOBAL_COST_TRACKER, enable_cost_tracking
+from futurehouse_client.models import TaskRequest, AuthType
+from futurehouse_client import FutureHouseClient
 
 from .notebook_env import NBEnvironment
 from .utils import NBLanguage, MultipleChoiceQuestion, nb_to_html
@@ -36,7 +38,8 @@ def __init__(
         eval_mode: EvalAnswerMode | None = None,
         metadata: dict[str, Any] | None = None,  # used for NBEvalExpt
         mcqs: list[MultipleChoiceQuestion] | None = None,
-        exclude_tools: list[str] | None = None,
+        # Exclude list_workdir and query_literature tools by default
+        exclude_tools: list[str] | None = ["list_workdir", "query_literature"],
         **kwargs,
     ):
         super().__init__(**kwargs)
@@ -55,6 +58,9 @@ def __init__(
     async def reset(self) -> tuple[Messages, list[Tool]]:
         # Discard base class's init_obs and make our own with the problem statement
         _, tools = await super().reset()
+
+        tools.append(Tool.from_function(self.query_literature))
+
         if self.exclude_tools:
             tools = [
                 tool
@@ -83,6 +89,43 @@ async def reset(self) -> tuple[Messages, list[Tool]]:
 
         return init_obs, tools
 
+    # DA Specific Tools
+
+    async def query_literature(self, query: str) -> str:
+        """Query the scientific literature. Produces a succinct answer citing the scientific literature.
+
+        Args:
+            query: The scientific question to answer
+        """
+        logger.info("Running PQA query")
+        client = FutureHouseClient(
+            stage=cfg.CROW_STAGE,
+            auth_type=AuthType.API_KEY,
+            api_key=cfg.PLATFORM_API_KEY,
+        )
+
+        job_data = TaskRequest(
+            name="job-futurehouse-paperqa2",
+            query=query,
+        )
+        job_id = client.create_task(job_data)
+        status = "in progress"
+        while status in ["in progress", "queued"]:
+            logger.info(
+                "Waiting for pqa task to complete... checking again in 5 seconds"
+            )
+            time.sleep(5)
+            status = client.get_task(job_id).status
+
+        if status == "failed":
+            raise Exception("PaperQA platform job failed")
+
+        job_result = client.get_task(job_id, verbose=True)
+        answer = job_result.environment_frame["state"]["state"]["response"]["answer"][
+            "answer"
+        ]
+        return answer
+
     async def submit_answer(self, answer: str) -> str:  # type: ignore[override]
         """Submit an answer to the problem.
 

src/scripts/deploy.py

@@ -12,13 +12,16 @@
 )
 from futurehouse_client.models.app import TaskQueuesConfig
 
-HIGH = True
+HIGH = False
+ENVIRONMENT = "DEV"
 
 ENV_VARS = {
     "OPENAI_API_KEY": os.environ["OPENAI_API_KEY"],
     "ANTHROPIC_API_KEY": os.environ["ANTHROPIC_API_KEY"],
     "USE_DOCKER": "false",
-    "STAGE": "PROD",
+    "STAGE": ENVIRONMENT,
+    "ENVIRONMENT": ENVIRONMENT,
+    "API_KEY": os.environ[f"CROW_API_KEY_{ENVIRONMENT}"],
 }
 
 CONTAINER_CONFIG = DockerContainerConfiguration(cpu="8", memory="16Gi")