refactor: Update logging levels for improved message severity clarity

planning_ai/logging.py

@@ -1,3 +1,3 @@
 from loguru import logger
 
-logger.add("logs/model.log", rotation="1 MB", retention="10 days", level="INFO")
+logger.add("logs/model.log", rotation="1 MB", retention="10 days", level="DEBUG")

planning_ai/nodes/hallucination_node.py

@@ -24,13 +24,13 @@ def check_hallucination(state: DocumentState):
         dict: A dictionary containing either a list of fixed summaries or hallucinations
         that need to be addressed.
     """
-    logger.warning(f"Checking hallucinations for document {state['filename']}")
+    logger.info(f"Checking hallucinations for document {state['filename']}")
 
     if state["processed"] or (state["refinement_attempts"] >= MAX_ATTEMPTS):
-        logger.warning(f"Max attempts exceeded for document: {state['filename']}")
+        logger.error(f"Max attempts exceeded for document: {state['filename']}")
         return {"documents": [{**state, "failed": True, "processed": True}]}
     elif not state["is_hallucinated"]:
-        logger.warning(f"Finished processing document: {state['filename']}")
+        logger.info(f"Finished processing document: {state['filename']}")
         return {"documents": [{**state, "processed": True}]}
 
     try:
@@ -40,7 +40,7 @@ def check_hallucination(state: DocumentState):
         is_hallucinated = response.score == 0
         refinement_attempts = state["refinement_attempts"] + 1
     except Exception as e:
-        logger.error(f"Failed to decode JSON {state['filename']}: {e}.")
+        logger.error(f"Failed to decode JSON {state['filename']}: {e}")
         return {
             "documents": [
                 {
@@ -60,7 +60,7 @@ def check_hallucination(state: DocumentState):
         "refinement_attempts": refinement_attempts,
         "is_hallucinated": is_hallucinated,
     }
-    logger.warning(f"Hallucination for {state['filename']}: {is_hallucinated}")
+    logger.info(f"Hallucination for {state['filename']}: {is_hallucinated}")
     return (
         {"documents": [{**out, "processed": False}]}
         if is_hallucinated

planning_ai/nodes/map_node.py

@@ -28,7 +28,7 @@ def retrieve_themes(state: DocumentState) -> DocumentState:
 
 
 def add_entities(state: OverallState) -> OverallState:
-    logger.warning("Adding entities to all documents.")
+    logger.info("Adding entities to all documents.")
     for idx, document in enumerate(
         nlp.pipe(
             [doc["document"].page_content for doc in state["documents"]],
@@ -73,15 +73,15 @@ def generate_summary(state: DocumentState) -> dict:
     Returns:
         dict: A dictionary containing the generated summary and updated document state.
     """
-    logger.warning(f"Generating summary for document: {state['filename']}")
+    logger.info(f"Generating summary for document: {state['filename']}")
 
-    logger.warning(f"Starting PII removal for: {state['filename']}")
+    logger.info(f"Starting PII removal for: {state['filename']}")
     state["document"].page_content = remove_pii(state["document"].page_content)
-    logger.warning(f"Retrieving themes for: {state['filename']}")
+    logger.info(f"Retrieving themes for: {state['filename']}")
     state = retrieve_themes(state)
 
     if not state["themes"]:
-        logger.error(f"No themes found for {state['filename']}")
+        logger.warning(f"No themes found for {state['filename']}")
         return {
             "documents": [
                 {
@@ -99,7 +99,7 @@ def generate_summary(state: DocumentState) -> dict:
     try:
         response = map_chain.invoke({"context": state["document"].page_content})
     except Exception as e:
-        logger.error(f"Failed to decode JSON {state['document']}: {e}.")
+        logger.error(f"Failed to decode JSON {state['document']}: {e}")
         return {
             "documents": [
                 {
@@ -112,7 +112,7 @@ def generate_summary(state: DocumentState) -> dict:
                 }
             ]
         }
-    logger.warning(f"Summary generation completed for document: {state['filename']}")
+    logger.info(f"Summary generation completed for document: {state['filename']}")
 
     return {
         "documents": [
@@ -129,5 +129,5 @@ def generate_summary(state: DocumentState) -> dict:
 
 
 def map_documents(state: OverallState) -> list[Send]:
-    logger.warning("Mapping documents to generate summaries.")
+    logger.info("Mapping documents to generate summaries.")
     return [Send("generate_summary", document) for document in state["documents"]]

planning_ai/nodes/reduce_node.py

@@ -82,7 +82,7 @@ def batch_generate_executive_summaries(summaries):
     final_responses = []
     batch_size = 50
     for i in range(0, len(summaries_text), batch_size):
-        logger.warning(
+        logger.info(
             f"Processing batches... {int(i/50)+1}/{(len(summaries_text)//batch_size)+1}"
         )
         batch = summaries_text[i : i + batch_size]
@@ -98,7 +98,7 @@ def generate_policy_output(policy_groups):
         .agg(pl.col("details"), pl.col("doc_id"))
         .rows(named=True)
     ):
-        logger.warning(f"Processing policies: {policy['policies']}...")
+        logger.info(f"Processing policies: {policy['policies']}...")
         zipped = [
             f"{bullet} Doc ID: {id}"
             for (bullet, id) in zip(policy["details"], policy["doc_id"], strict=True)
@@ -121,7 +121,7 @@ def generate_policy_output(policy_groups):
 def generate_final_report(state: OverallState):
     final_docs = [doc for doc in state["documents"] if doc["processed"]]
     if len(final_docs) == state["n_docs"]:
-        logging.warning(f"Generating final report... ({len(final_docs)} documents)")
+        logger.info(f"Generating final report... ({len(final_docs)} documents)")
         return final_output(final_docs)