Remove logging statements

Author: kdid

chat/src/agent/callbacks/metrics.py

@@ -35,8 +35,6 @@ def on_llm_end(self, response: LLMResult, **kwargs):
             if metadata is None:
                 continue
 
-            print(metadata)
-
             for k, v in metadata.items():
                 if isinstance(v, (int, float)):
                     self.accumulator[k] = self.accumulator.get(k, 0) + v

chat/src/agent/search_agent.py

@@ -43,8 +43,6 @@ def __call__(self, state: MessagesState):
         messages = state["messages"]
         last_message = messages[-1]
 
-        print(f"FacetsToolNode: Processing {len(last_message.tool_calls)} tool calls")
-
         # If there are tool calls and we have facets, inject them
         if hasattr(last_message, 'tool_calls') and self.facets:
             for tool_call in last_message.tool_calls:
@@ -54,7 +52,6 @@ def __call__(self, state: MessagesState):
                         print(f"Injecting facets into {tool_call['name']} tool: {self.facets}")
 
         result = self.tool_node.invoke(state)
-        print(f"FacetsToolNode: Tool execution result: {type(result)}")
         return result
 
 
@@ -67,42 +64,30 @@ def __init__(self, model: BaseModel, system_message: str, metrics=None):
     def should_continue(self, state: MessagesState) -> Literal["tools", END]:
         messages = state["messages"]
         last_message = messages[-1]
-        print(f"should_continue: last_message type: {type(last_message)}")
-        print(f"should_continue: last_message.tool_calls: {getattr(last_message, 'tool_calls', None)}")
-        # If the LLM makes a tool call, then we route to the "tools" node
+        # If the LLM makes a tool call, then route to the "tools" node
         if last_message.tool_calls:
             return "tools"
-        # Otherwise, we stop (reply to the user)
+        # Otherwise, stop (reply to the user)
         return END
 
     def summarize(self, state: MessagesState):
         messages = state["messages"]
         last_message = messages[-1]
-        print(f"summarize: last_message name: {getattr(last_message, 'name', None)}")
-        print(f"summarize: last_message type: {type(last_message)}")
 
         if not hasattr(last_message, 'name') or last_message.name not in ["search", "retrieve_documents"]:
-            print("summarize: Skipping summarization")
             return {"messages": messages}
 
-        print("summarize: Processing summarization")
-
-
         start_time = time.time()
 
         # Handle both JSON string and already parsed content
         if isinstance(last_message.content, str):
             try:
                 content = minimize_documents(json.loads(last_message.content))
-                print(f"summarize: Parsed JSON content, {len(content)} items")
             except json.JSONDecodeError:
-                print("summarize: Failed to parse JSON, leaving as is")
                 return {"messages": messages}
         elif isinstance(last_message.content, list):
             content = minimize_documents(last_message.content)
-            print(f"summarize: Used list content directly, {len(content)} items")
         else:
-            print(f"summarize: Unknown content type: {type(last_message.content)}")
             return {"messages": messages}
 
 

chat/src/agent/tools.py

@@ -61,8 +61,6 @@ def search(query: str, facets: list = None):
         query (str): The search query
         facets (list): Optional facet filters to apply, e.g. [{"collection.title.keyword": ["Posters from Herskovitz"]}, {"subject.label": ["Nigeria"]}]
     """
-
-    print(f"Search tool - using facets: {facets}")
     query_results = opensearch_vector_store().similarity_search(query, size=20, facets=facets)
     return filter_results(query_results)
 

chat/src/core/event_config.py

@@ -80,8 +80,6 @@ def __post_init__(self):
         self.prompt = ChatPromptTemplate.from_template(self.prompt_text)
 
     def user_can(self, scope):
-        print(f"Checking user permissions for scope: {scope}")
-        print(f"API Token: {self.api_token.token}")
         return self.api_token.can(scope)
 
     def _get_payload_value_with_superuser_check(self, key, default):

chat/src/handlers.py

@@ -123,8 +123,6 @@ def chat(event, context):
     model = chat_model(model=config.model, streaming=config.stream_response)
     search_agent = SearchAgent(model=model, metrics=metrics)
 
-    print(f"FACETS: {config.facets}")
-
     try:
         search_agent.invoke(
             config.question,