pass new flag and fix db path passing issue

Author: ollmer

src/agentlab/agents/generic_agent_hinter/generic_agent_prompt.py

@@ -51,6 +51,7 @@ class GenericPromptFlags(dp.Flags):
     use_hints: bool = False
     use_task_hint: bool = False
     task_hint_retrieval_mode: Literal["direct", "llm", "emb"] = "direct"
+    skip_hints_for_current_task: bool = False
     hint_db_path: str = None
     enable_chat: bool = False
     max_prompt_tokens: int = None
@@ -113,6 +114,7 @@ def time_for_caution():
             goal=goal,
             hint_retrieval_mode=flags.task_hint_retrieval_mode,
             llm=llm,
+            skip_hints_for_current_task=flags.skip_hints_for_current_task,
         )
         self.plan = Plan(previous_plan, step, lambda: flags.use_plan)  # TODO add previous plan
         self.criticise = Criticise(visible=lambda: flags.use_criticise)
@@ -299,13 +301,15 @@ def __init__(
         hint_db_path: str,
         goal: str,
         hint_retrieval_mode: Literal["direct", "llm", "emb"],
+        skip_hints_for_current_task: bool,
         llm: ChatModel,
     ) -> None:
         super().__init__(visible=use_task_hint)
         self.use_task_hint = use_task_hint
         self.hint_db_rel_path = "hint_db.csv"
         self.hint_db_path = hint_db_path  # Allow external path override
         self.hint_retrieval_mode: Literal["direct", "llm", "emb"] = hint_retrieval_mode
+        self.skip_hints_for_current_task = skip_hints_for_current_task
         self.goal = goal
         self.llm = llm
         self._init()
@@ -346,8 +350,9 @@ def _init(self):
                 print(f"Warning: Hint database not found at {hint_db_path}")
                 self.hint_db = pd.DataFrame(columns=["task_name", "hint"])
             self.hints_source = HintsSource(
-                hint_db_path=self.hint_db_rel_path,
+                hint_db_path=hint_db_path.as_posix(),
                 hint_retrieval_mode=self.hint_retrieval_mode,
+                skip_hints_for_current_task=self.skip_hints_for_current_task,
             )
         except Exception as e:
             # Fallback to empty database on any error

src/agentlab/agents/tool_use_agent/tool_use_agent.py

@@ -375,6 +375,7 @@ def __init__(
         else:
             self.hint_db_path = (Path(__file__).parent / self.hint_db_path).as_posix()
         self.hint_db = pd.read_csv(self.hint_db_path, header=0, index_col=None, dtype=str)
+        logger.info(f"Loaded {len(self.hint_db)} hints from database {self.hint_db_path}")
         if self.hint_retrieval_mode == "emb":
             self.load_hint_vectors()
 
@@ -395,16 +396,19 @@ def load_hint_vectors(self):
 
     def choose_hints(self, llm, task_name: str, goal: str) -> list[str]:
         """Choose hints based on the task name."""
+        logger.info(
+            f"Choosing hints for task: {task_name}, goal: {goal} from db: {self.hint_db_path} using mode: {self.hint_retrieval_mode}"
+        )
         if self.hint_retrieval_mode == "llm":
-            return self.choose_hints_llm(llm, goal)
+            return self.choose_hints_llm(llm, goal, task_name)
         elif self.hint_retrieval_mode == "direct":
             return self.choose_hints_direct(task_name)
         elif self.hint_retrieval_mode == "emb":
-            return self.choose_hints_emb(goal)
+            return self.choose_hints_emb(goal, task_name)
         else:
             raise ValueError(f"Unknown hint retrieval mode: {self.hint_retrieval_mode}")
 
-    def choose_hints_llm(self, llm, goal: str) -> list[str]:
+    def choose_hints_llm(self, llm, goal: str, task_name: str) -> list[str]:
         """Choose hints using LLM to filter the hints."""
         topic_to_hints = defaultdict(list)
         hints_df = self.hint_db
@@ -439,7 +443,7 @@ def choose_hints_llm(self, llm, goal: str) -> list[str]:
             hints = []
         return hints
 
-    def choose_hints_emb(self, goal: str) -> list[str]:
+    def choose_hints_emb(self, goal: str, task_name: str) -> list[str]:
         """Choose hints using embeddings to filter the hints."""
         goal_embeddings = self._encode([goal], prompt="task description")
         hint_embeddings = self.hint_embeddings