fix: wire AgentGraph to read LLM and embedding from YAML config

Updated the Config Pydantic model and YAML schema to include llm and
embedding fields. Modified AgentGraph constructor to accept these
configurations and updated the chat-chainlit.py entry point to pass
them from the loaded configuration.

This removes hardcoded 'gpt-4o-mini' and 'text-embedding-3-large'
references, making the agent models fully configurable.

Author: bhavyakeerthi3

.config.schema.yaml

@@ -78,4 +78,10 @@ properties:
               pattern: "^[0-9]+[smhdw]$"
           required: ["users", "max_messages", "interval"]
     required: ["message_rates"]
+  llm:
+    type: string
+    pattern: "^[a-z0-9_-]+/.+$"
+  embedding:
+    type: string
+    pattern: "^[a-z0-9_-]+/.+$"
 required: ["features", "messages", "profiles", "usage_limits"]

bin/chat-chainlit.py

@@ -20,7 +20,9 @@
 config: Config | None = Config.from_yaml()
 
 profiles: list[ProfileName] = config.profiles if config else [ProfileName.React_to_Me]
-llm_graph = AgentGraph(profiles)
+llm_config: str = config.llm if config else "openai/gpt-4o-mini"
+embedding_config: str = config.embedding if config else "openai/text-embedding-3-large"
+llm_graph = AgentGraph(profiles, llm_config=llm_config, embedding_config=embedding_config)
 
 POSTGRES_CHAINLIT_DB = os.getenv("POSTGRES_CHAINLIT_DB")
 POSTGRES_USER = os.getenv("POSTGRES_USER")

config_default.yml

@@ -3,6 +3,9 @@
 profiles:
   - React-to-Me
 
+llm: openai/gpt-4o-mini
+embedding: openai/text-embedding-3-large
+
 features:
   postprocessing:  # external web search feature
     enabled: true

src/agent/graph.py

@@ -28,10 +28,12 @@ class AgentGraph:
     def __init__(
         self,
         profiles: list[ProfileName],
+        llm_config: str = "openai/gpt-4o-mini",
+        embedding_config: str = "openai/text-embedding-3-large",
     ) -> None:
         # Get base models
-        llm: BaseChatModel = get_llm("openai", "gpt-4o-mini")
-        embedding: Embeddings = get_embedding("openai", "text-embedding-3-large")
+        llm: BaseChatModel = get_llm(llm_config)
+        embedding: Embeddings = get_embedding(embedding_config)
 
         self.uncompiled_graph: dict[str, StateGraph] = create_profile_graphs(
             profiles, llm, embedding

src/util/config_yml/__init__.py

@@ -20,6 +20,8 @@ class Config(BaseModel):
     messages: dict[str, Message]
     profiles: list[ProfileName]
     usage_limits: UsageLimits
+    llm: str = "openai/gpt-4o-mini"
+    embedding: str = "openai/text-embedding-3-large"
 
     def get_feature(
         self,