chore: move use_auto_chat_cache_seed_gen and init_chat_cache_seed to …

…LLMSett… (#444)

* move use_auto_chat_cache_seed_gen and init_chat_cache_seed to LLMSettings

* remove RD_AGENT_SETTINGS in llm_utils.py

rdagent/core/conf.py

@@ -15,16 +15,6 @@ class RDAgentSettings(BaseSettings):
     # TODO: (xiao) think it can be a separate config.
     log_trace_path: str | None = None
 
-    # Behavior of returning answers to the same question when caching is enabled
-    use_auto_chat_cache_seed_gen: bool = False
-    """
-    `_create_chat_completion_inner_function` provdies a feature to pass in a seed to affect the cache hash key
-    We want to enable a auto seed generator to get different default seed for `_create_chat_completion_inner_function`
-    if seed is not given.
-    So the cache will only not miss you ask the same question on same round.
-    """
-    init_chat_cache_seed: int = 42
-
     # azure document intelligence configs
     azure_document_intelligence_key: str = ""
     azure_document_intelligence_endpoint: str = ""

rdagent/core/utils.py

@@ -14,6 +14,7 @@
 from fuzzywuzzy import fuzz  # type: ignore[import-untyped]
 
 from rdagent.core.conf import RD_AGENT_SETTINGS
+from rdagent.oai.llm_conf import LLM_SETTINGS
 
 
 class RDAgentException(Exception):  # noqa: N818
@@ -98,7 +99,7 @@ class CacheSeedGen:
     """
 
     def __init__(self) -> None:
-        self.set_seed(RD_AGENT_SETTINGS.init_chat_cache_seed)
+        self.set_seed(LLM_SETTINGS.init_chat_cache_seed)
 
     def set_seed(self, seed: int) -> None:
         random.seed(seed)

rdagent/oai/llm_conf.py

@@ -20,6 +20,16 @@ class LLMSettings(BaseSettings):
     prompt_cache_path: str = str(Path.cwd() / "prompt_cache.db")
     max_past_message_include: int = 10
 
+    # Behavior of returning answers to the same question when caching is enabled
+    use_auto_chat_cache_seed_gen: bool = False
+    """
+    `_create_chat_completion_inner_function` provdies a feature to pass in a seed to affect the cache hash key
+    We want to enable a auto seed generator to get different default seed for `_create_chat_completion_inner_function`
+    if seed is not given.
+    So the cache will only not miss you ask the same question on same round.
+    """
+    init_chat_cache_seed: int = 42
+
     # Chat configs
     openai_api_key: str = ""  # TODO: simplify the key design.
     chat_openai_api_key: str = ""

rdagent/oai/llm_utils.py

@@ -17,7 +17,6 @@
 import numpy as np
 import tiktoken
 
-from rdagent.core.conf import RD_AGENT_SETTINGS
 from rdagent.core.utils import LLM_CACHE_SEED_GEN, SingletonBaseClass
 from rdagent.log import LogColors
 from rdagent.log import rdagent_logger as logger
@@ -596,7 +595,7 @@ def _create_chat_completion_inner_function(  # noqa: C901, PLR0912, PLR0915
             To make retries useful, we need to enable a seed.
             This seed is different from `self.chat_seed` for GPT. It is for the local cache mechanism enabled by RD-Agent locally.
         """
-        if seed is None and RD_AGENT_SETTINGS.use_auto_chat_cache_seed_gen:
+        if seed is None and LLM_SETTINGS.use_auto_chat_cache_seed_gen:
             seed = LLM_CACHE_SEED_GEN.get_next_seed()
 
         # TODO: we can add this function back to avoid so much `self.cfg.log_llm_chat_content`

test/oai/test_completion.py

@@ -60,23 +60,22 @@ def test_chat_cache(self) -> None:
             - 2 pass
             - cache is not missed & same question get different answer.
         """
-        from rdagent.core.conf import RD_AGENT_SETTINGS
         from rdagent.core.utils import LLM_CACHE_SEED_GEN
         from rdagent.oai.llm_conf import LLM_SETTINGS
 
         system_prompt = "You are a helpful assistant."
         user_prompt = f"Give me {2} random country names, list {2} cities in each country, and introduce them"
 
         origin_value = (
-            RD_AGENT_SETTINGS.use_auto_chat_cache_seed_gen,
+            LLM_SETTINGS.use_auto_chat_cache_seed_gen,
             LLM_SETTINGS.use_chat_cache,
             LLM_SETTINGS.dump_chat_cache,
         )
 
         LLM_SETTINGS.use_chat_cache = True
         LLM_SETTINGS.dump_chat_cache = True
 
-        RD_AGENT_SETTINGS.use_auto_chat_cache_seed_gen = True
+        LLM_SETTINGS.use_auto_chat_cache_seed_gen = True
 
         LLM_CACHE_SEED_GEN.set_seed(10)
         response1 = APIBackend().build_messages_and_create_chat_completion(
@@ -110,7 +109,7 @@ def test_chat_cache(self) -> None:
 
         # Reset, for other tests
         (
-            RD_AGENT_SETTINGS.use_auto_chat_cache_seed_gen,
+            LLM_SETTINGS.use_auto_chat_cache_seed_gen,
             LLM_SETTINGS.use_chat_cache,
             LLM_SETTINGS.dump_chat_cache,
         ) = origin_value
@@ -132,23 +131,22 @@ def test_chat_cache_multiprocess(self) -> None:
             - 2 pass
             - cache is not missed & same question get different answer.
         """
-        from rdagent.core.conf import RD_AGENT_SETTINGS
         from rdagent.core.utils import LLM_CACHE_SEED_GEN, multiprocessing_wrapper
         from rdagent.oai.llm_conf import LLM_SETTINGS
 
         system_prompt = "You are a helpful assistant."
         user_prompt = f"Give me {2} random country names, list {2} cities in each country, and introduce them"
 
         origin_value = (
-            RD_AGENT_SETTINGS.use_auto_chat_cache_seed_gen,
+            LLM_SETTINGS.use_auto_chat_cache_seed_gen,
             LLM_SETTINGS.use_chat_cache,
             LLM_SETTINGS.dump_chat_cache,
         )
 
         LLM_SETTINGS.use_chat_cache = True
         LLM_SETTINGS.dump_chat_cache = True
 
-        RD_AGENT_SETTINGS.use_auto_chat_cache_seed_gen = True
+        LLM_SETTINGS.use_auto_chat_cache_seed_gen = True
 
         func_calls = [(_worker, (system_prompt, user_prompt)) for _ in range(4)]
 
@@ -161,7 +159,7 @@ def test_chat_cache_multiprocess(self) -> None:
 
         # Reset, for other tests
         (
-            RD_AGENT_SETTINGS.use_auto_chat_cache_seed_gen,
+            LLM_SETTINGS.use_auto_chat_cache_seed_gen,
             LLM_SETTINGS.use_chat_cache,
             LLM_SETTINGS.dump_chat_cache,
         ) = origin_value