fix tests

Author: codelion

optillm.py

@@ -34,6 +34,7 @@
 from optillm.cepo.cepo import cepo, CepoConfig, init_cepo_config
 from optillm.batching import RequestBatcher, BatchingError
 from optillm.conversation_logger import ConversationLogger
+import optillm.conversation_logger
 
 # Setup logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
@@ -1133,6 +1134,8 @@ def process_batch_requests(batch_requests):
         log_dir=Path(server_config['conversation_log_dir']),
         enabled=server_config['log_conversations']
     )
+    # Set the global logger instance for access from approach modules
+    optillm.conversation_logger.set_global_logger(conversation_logger)
     if server_config['log_conversations']:
         logger.info(f"Conversation logging enabled. Logs will be saved to: {server_config['conversation_log_dir']}")
 

optillm/bon.py

@@ -1,5 +1,6 @@
 import logging
 import optillm
+from optillm import conversation_logger
 
 logger = logging.getLogger(__name__)
 
@@ -23,9 +24,9 @@ def best_of_n_sampling(system_prompt: str, initial_query: str, client, model: st
         response = client.chat.completions.create(**provider_request)
 
         # Log provider call
-        if hasattr(optillm, 'conversation_logger') and optillm.conversation_logger and request_id:
+        if request_id:
             response_dict = response.model_dump() if hasattr(response, 'model_dump') else response
-            optillm.conversation_logger.log_provider_call(request_id, provider_request, response_dict)
+            conversation_logger.log_provider_call(request_id, provider_request, response_dict)
 
         completions = [choice.message.content for choice in response.choices]
         logger.info(f"Generated {len(completions)} initial completions using n parameter. Tokens used: {response.usage.completion_tokens}")
@@ -47,9 +48,9 @@ def best_of_n_sampling(system_prompt: str, initial_query: str, client, model: st
                 response = client.chat.completions.create(**provider_request)
 
                 # Log provider call
-                if hasattr(optillm, 'conversation_logger') and optillm.conversation_logger and request_id:
+                if request_id:
                     response_dict = response.model_dump() if hasattr(response, 'model_dump') else response
-                    optillm.conversation_logger.log_provider_call(request_id, provider_request, response_dict)
+                    conversation_logger.log_provider_call(request_id, provider_request, response_dict)
 
                 completions.append(response.choices[0].message.content)
                 bon_completion_tokens += response.usage.completion_tokens
@@ -84,9 +85,9 @@ def best_of_n_sampling(system_prompt: str, initial_query: str, client, model: st
         rating_response = client.chat.completions.create(**provider_request)
 
         # Log provider call
-        if hasattr(optillm, 'conversation_logger') and optillm.conversation_logger and request_id:
+        if request_id:
             response_dict = rating_response.model_dump() if hasattr(rating_response, 'model_dump') else rating_response
-            optillm.conversation_logger.log_provider_call(request_id, provider_request, response_dict)
+            conversation_logger.log_provider_call(request_id, provider_request, response_dict)
 
         bon_completion_tokens += rating_response.usage.completion_tokens
         try:

optillm/cepo/cepo.py

@@ -2,6 +2,7 @@
 import yaml
 import json
 import optillm
+from optillm import conversation_logger
 
 from dataclasses import dataclass
 from typing import Literal, Any, Optional

optillm/conversation_logger.py

@@ -10,6 +10,9 @@
 
 logger = logging.getLogger(__name__)
 
+# Global logger instance - will be set by optillm.py
+_global_logger: Optional['ConversationLogger'] = None
+
 @dataclass
 class ConversationEntry:
     """Represents a single conversation entry being logged"""
@@ -240,4 +243,23 @@ def get_stats(self) -> Dict[str, Any]:
                 "total_entries_approximate": total_entries
             })
 
-        return stats
+        return stats
+
+
+# Module-level functions for easy access from approach modules
+def set_global_logger(logger_instance: 'ConversationLogger') -> None:
+    """Set the global logger instance (called by optillm.py)"""
+    global _global_logger
+    _global_logger = logger_instance
+
+
+def log_provider_call(request_id: str, provider_request: Dict[str, Any], provider_response: Dict[str, Any]) -> None:
+    """Log a provider call using the global logger instance"""
+    if _global_logger and _global_logger.enabled:
+        _global_logger.log_provider_call(request_id, provider_request, provider_response)
+
+
+def log_error(request_id: str, error_message: str) -> None:
+    """Log an error using the global logger instance"""
+    if _global_logger and _global_logger.enabled:
+        _global_logger.log_error(request_id, error_message)

optillm/cot_reflection.py

@@ -1,6 +1,7 @@
 import re
 import logging
 import optillm
+from optillm import conversation_logger
 
 logger = logging.getLogger(__name__)
 

optillm/leap.py

@@ -3,6 +3,7 @@
 from typing import List, Tuple
 import json
 import optillm
+from optillm import conversation_logger
 
 # Setup logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

optillm/mcts.py

@@ -4,6 +4,7 @@
 import networkx as nx
 from typing import List, Dict
 import optillm
+from optillm import conversation_logger
 
 logger = logging.getLogger(__name__)
 
@@ -123,9 +124,9 @@ def generate_actions(self, state: DialogueState) -> List[str]:
         response = self.client.chat.completions.create(**provider_request)
 
         # Log provider call
-        if hasattr(optillm, 'conversation_logger') and optillm.conversation_logger and self.request_id:
+        if self.request_id:
             response_dict = response.model_dump() if hasattr(response, 'model_dump') else response
-            optillm.conversation_logger.log_provider_call(self.request_id, provider_request, response_dict)
+            conversation_logger.log_provider_call(self.request_id, provider_request, response_dict)
 
         completions = [choice.message.content.strip() for choice in response.choices]
         self.completion_tokens += response.usage.completion_tokens
@@ -152,9 +153,9 @@ def apply_action(self, state: DialogueState, action: str) -> DialogueState:
         response = self.client.chat.completions.create(**provider_request)
 
         # Log provider call
-        if hasattr(optillm, 'conversation_logger') and optillm.conversation_logger and self.request_id:
+        if self.request_id:
             response_dict = response.model_dump() if hasattr(response, 'model_dump') else response
-            optillm.conversation_logger.log_provider_call(self.request_id, provider_request, response_dict)
+            conversation_logger.log_provider_call(self.request_id, provider_request, response_dict)
 
         next_query = response.choices[0].message.content
         self.completion_tokens += response.usage.completion_tokens
@@ -182,9 +183,9 @@ def evaluate_state(self, state: DialogueState) -> float:
         response = self.client.chat.completions.create(**provider_request)
 
         # Log provider call
-        if hasattr(optillm, 'conversation_logger') and optillm.conversation_logger and self.request_id:
+        if self.request_id:
             response_dict = response.model_dump() if hasattr(response, 'model_dump') else response
-            optillm.conversation_logger.log_provider_call(self.request_id, provider_request, response_dict)
+            conversation_logger.log_provider_call(self.request_id, provider_request, response_dict)
 
         self.completion_tokens += response.usage.completion_tokens
         try:

optillm/moa.py

@@ -1,5 +1,6 @@
 import logging
 import optillm
+from optillm import conversation_logger
 
 logger = logging.getLogger(__name__)
 
@@ -29,8 +30,8 @@ def mixture_of_agents(system_prompt: str, initial_query: str, client, model: str
         response_dict = response.model_dump() if hasattr(response, 'model_dump') else response
 
         # Log provider call if conversation logging is enabled
-        if hasattr(optillm, 'conversation_logger') and optillm.conversation_logger and request_id:
-            optillm.conversation_logger.log_provider_call(request_id, provider_request, response_dict)
+        if request_id:
+            conversation_logger.log_provider_call(request_id, provider_request, response_dict)
 
         completions = [choice.message.content for choice in response.choices]
         moa_completion_tokens += response.usage.completion_tokens
@@ -60,8 +61,8 @@ def mixture_of_agents(system_prompt: str, initial_query: str, client, model: str
                 response_dict = response.model_dump() if hasattr(response, 'model_dump') else response
 
                 # Log provider call if conversation logging is enabled
-                if hasattr(optillm, 'conversation_logger') and optillm.conversation_logger and request_id:
-                    optillm.conversation_logger.log_provider_call(request_id, provider_request, response_dict)
+                if request_id:
+                    conversation_logger.log_provider_call(request_id, provider_request, response_dict)
 
                 completions.append(response.choices[0].message.content)
                 moa_completion_tokens += response.usage.completion_tokens
@@ -122,8 +123,8 @@ def mixture_of_agents(system_prompt: str, initial_query: str, client, model: str
     response_dict = critique_response.model_dump() if hasattr(critique_response, 'model_dump') else critique_response
 
     # Log provider call if conversation logging is enabled
-    if hasattr(optillm, 'conversation_logger') and optillm.conversation_logger and request_id:
-        optillm.conversation_logger.log_provider_call(request_id, provider_request, response_dict)
+    if request_id:
+        conversation_logger.log_provider_call(request_id, provider_request, response_dict)
 
     critiques = critique_response.choices[0].message.content
     moa_completion_tokens += critique_response.usage.completion_tokens
@@ -169,8 +170,8 @@ def mixture_of_agents(system_prompt: str, initial_query: str, client, model: str
     response_dict = final_response.model_dump() if hasattr(final_response, 'model_dump') else final_response
 
     # Log provider call if conversation logging is enabled
-    if hasattr(optillm, 'conversation_logger') and optillm.conversation_logger and request_id:
-        optillm.conversation_logger.log_provider_call(request_id, provider_request, response_dict)
+    if request_id:
+        conversation_logger.log_provider_call(request_id, provider_request, response_dict)
 
     moa_completion_tokens += final_response.usage.completion_tokens
     logger.info(f"Generated final response. Tokens used: {final_response.usage.completion_tokens}")

optillm/plansearch.py

@@ -1,6 +1,7 @@
 import logging
 from typing import List, Tuple
 import optillm
+from optillm import conversation_logger
 
 logger = logging.getLogger(__name__)
 

optillm/pvg.py

@@ -2,6 +2,7 @@
 import re
 from typing import List, Tuple
 import optillm
+from optillm import conversation_logger
 
 logger = logging.getLogger(__name__)