Use Sonnet for Buh hunter iteration

core/agents/bug_hunter.py

@@ -5,7 +5,7 @@ from pydantic import BaseModel, Field
 from core.agents.base import BaseAgent
 from core.agents.convo import AgentConvo
 from core.agents.response import AgentResponse
-from core.config import magic_words
+from core.config import BUG_HUNT_AGENT_NAME, magic_words
 from core.db.models.project_state import IterationStatus
 from core.llm.parser import JSONParser
 from core.log import get_logger
@@ -61,7 +61,7 @@ class BugHunter(BaseAgent):
         self.next_state.current_iteration["bug_reproduction_description"] = bug_reproduction_instructions
 
     async def check_logs(self, logs_message: str = None):
-        llm = self.get_llm()
+        llm = self.get_llm(BUG_HUNT_AGENT_NAME)
         convo = AgentConvo(self).template(
             "iteration",
             current_task=self.current_state.current_task,
@@ -90,6 +90,7 @@ class BugHunter(BaseAgent):
             )
             .require_schema(HuntConclusionOptions)
         )
+        llm = self.get_llm()
         hunt_conclusion = await llm(convo, parser=JSONParser(HuntConclusionOptions), temperature=0)
 
         self.next_state.current_iteration["description"] = human_readable_instructions

core/config/__init__.py

@@ -36,6 +36,7 @@ IGNORE_SIZE_THRESHOLD = 50000  # 50K+ files are ignored by default
 DEFAULT_AGENT_NAME = "default"
 DESCRIBE_FILES_AGENT_NAME = "CodeMonkey.describe_files"
 ROUTE_FILES_AGENT_NAME = "Troubleshooter.get_route_files"
+BUG_HUNT_AGENT_NAME = "BugHunter.logs_or_fix"
 
 # Endpoint for the external documentation
 EXTERNAL_DOCUMENTATION_API = "http://docs-pythagora-io-439719575.us-east-1.elb.amazonaws.com"
@@ -310,6 +311,7 @@ class Config(_StrictModel):
         default={
             DEFAULT_AGENT_NAME: AgentLLMConfig(),
             DESCRIBE_FILES_AGENT_NAME: AgentLLMConfig(model="gpt-3.5-turbo", temperature=0.0),
+            BUG_HUNT_AGENT_NAME: AgentLLMConfig(model="claude-3-5-sonnet-20240620", temperature=0.0),
             ROUTE_FILES_AGENT_NAME: AgentLLMConfig(model="gpt-4o", temperature=0.0),
         }
     )

core/llm/anthropic_client.py

@@ -23,7 +23,7 @@ class AnthropicClient(BaseLLMClient):
     def _init_client(self):
         self.client = AsyncAnthropic(
             api_key=self.config.api_key,
-            base_url=self.config.base_url,
+            # base_url=self.config.base_url,
             timeout=Timeout(
                 max(self.config.connect_timeout, self.config.read_timeout),
                 connect=self.config.connect_timeout,