update config.json default models

Author: LeonOstrez

core/agents/spec_writer.py

@@ -1,6 +1,7 @@
 from core.agents.base import BaseAgent
 from core.agents.convo import AgentConvo
 from core.agents.response import AgentResponse, ResponseType
+from core.config import SPEC_WRITER_AGENT_NAME
 from core.db.models import Complexity
 from core.db.models.project_state import IterationStatus
 from core.llm.parser import StringParser
@@ -95,7 +96,7 @@ async def update_spec(self, iteration_mode) -> AgentResponse:
         await self.send_message(
             f"Making the following changes to project specification:\n\n{feature_description}\n\nUpdated project specification:"
         )
-        llm = self.get_llm()
+        llm = self.get_llm(SPEC_WRITER_AGENT_NAME)
         convo = AgentConvo(self).template("add_new_feature", feature_description=feature_description)
         llm_response: str = await llm(convo, temperature=0, parser=StringParser())
         updated_spec = llm_response.strip()
@@ -124,7 +125,7 @@ async def update_spec(self, iteration_mode) -> AgentResponse:
 
     async def check_prompt_complexity(self, prompt: str) -> str:
         await self.send_message("Checking the complexity of the prompt ...")
-        llm = self.get_llm()
+        llm = self.get_llm(SPEC_WRITER_AGENT_NAME)
         convo = AgentConvo(self).template("prompt_complexity", prompt=prompt)
         llm_response: str = await llm(convo, temperature=0, parser=StringParser())
         return llm_response.lower()
@@ -154,7 +155,7 @@ async def analyze_spec(self, spec: str) -> str:
         )
         await self.send_message(msg)
 
-        llm = self.get_llm()
+        llm = self.get_llm(SPEC_WRITER_AGENT_NAME)
         convo = AgentConvo(self).template("ask_questions").user(spec)
         n_questions = 0
         n_answers = 0
@@ -204,7 +205,7 @@ async def analyze_spec(self, spec: str) -> str:
 
     async def review_spec(self, spec: str) -> str:
         convo = AgentConvo(self).template("review_spec", spec=spec)
-        llm = self.get_llm()
+        llm = self.get_llm(SPEC_WRITER_AGENT_NAME)
         llm_response: str = await llm(convo, temperature=0)
         additional_info = llm_response.strip()
         if additional_info and len(additional_info) > 6:

core/cli/helpers.py

@@ -27,7 +27,7 @@ def parse_llm_endpoint(value: str) -> Optional[tuple[LLMProvider, str]]:
     Option syntax is: --llm-endpoint <provider>:<url>
 
     :param value: Argument value.
-    :return: Tuple with LLM provider and URL, or None if if the option wasn't provided.
+    :return: Tuple with LLM provider and URL, or None if the option wasn't provided.
     """
     if not value:
         return None

core/config/__init__.py

@@ -38,6 +38,7 @@
 DESCRIBE_FILES_AGENT_NAME = "CodeMonkey.describe_files"
 CHECK_LOGS_AGENT_NAME = "BugHunter.check_logs"
 TASK_BREAKDOWN_AGENT_NAME = "Developer.breakdown_current_task"
+SPEC_WRITER_AGENT_NAME = "SpecWriter"
 
 # Endpoint for the external documentation
 EXTERNAL_DOCUMENTATION_API = "http://docs-pythagora-io-439719575.us-east-1.elb.amazonaws.com"
@@ -112,7 +113,7 @@ class AgentLLMConfig(_StrictModel):
     AgentLLMConfig is not specified, default will be used.
     """
 
-    provider: LLMProvider = LLMProvider.OPENAI
+    provider: Optional[LLMProvider] = Field(default=LLMProvider.OPENAI, description="LLM provider")
     model: str = Field(description="Model to use", default="gpt-4o-2024-05-13")
     temperature: float = Field(
         default=0.5,
@@ -318,8 +319,17 @@ class Config(_StrictModel):
             DEFAULT_AGENT_NAME: AgentLLMConfig(),
             CODE_MONKEY_AGENT_NAME: AgentLLMConfig(model="gpt-4-0125-preview", temperature=0.0),
             DESCRIBE_FILES_AGENT_NAME: AgentLLMConfig(model="gpt-3.5-turbo", temperature=0.0),
-            CHECK_LOGS_AGENT_NAME: AgentLLMConfig(model="claude-3-5-sonnet-20240620", temperature=0.5),
-            TASK_BREAKDOWN_AGENT_NAME: AgentLLMConfig(model="claude-3-5-sonnet-20240620", temperature=0.5),
+            CHECK_LOGS_AGENT_NAME: AgentLLMConfig(
+                provider=LLMProvider.ANTHROPIC,
+                model="claude-3-5-sonnet-20240620",
+                temperature=0.5,
+            ),
+            TASK_BREAKDOWN_AGENT_NAME: AgentLLMConfig(
+                provider=LLMProvider.ANTHROPIC,
+                model="claude-3-5-sonnet-20240620",
+                temperature=0.5,
+            ),
+            SPEC_WRITER_AGENT_NAME: AgentLLMConfig(model="gpt-4-0125-preview", temperature=0.0),
         }
     )
     prompt: PromptConfig = PromptConfig()

example-config.json

@@ -52,6 +52,16 @@
       "provider": "anthropic",
       "model": "claude-3-5-sonnet-20240620",
       "temperature": 0.0
+    },
+    "Developer.breakdown_current_task": {
+      "provider": "anthropic",
+      "model": "claude-3-5-sonnet-20240620",
+      "temperature": 0.5
+    },
+    "SpecWriter": {
+      "provider": "openai",
+      "model": "gpt-4-0125-preview",
+      "temperature": 0.5
     }
   },
   // Logging configuration outputs debug log to "pythagora.log" by default. If you set this to null,