Merged in hotfix/one-to-one-missing (pull request #744)

Return one_to_one results if one_to_n is empty

* Return one_to_one results if one_to_n is empty


Approved-by: Sha Brown
Approved-by: Karan Desai

fieldExtraction/src/investment/file_processing.py

@@ -29,6 +29,13 @@ def process_file(file_object, constants: Constants, run_timestamp):
     logging_utils.set_current_file(filename)
     logging.info(f"{datetime_str()} Processing {filename}...")
 
+    # Set default values
+    dynamic_one_to_one_fields = FieldSet()
+    process_one_to_n = config.FIELDS in ['all', 'one_to_n']
+    process_one_to_one = config.FIELDS in ['all', 'one_to_one']
+    # Initialize default fallback for final results
+    final_results = pd.DataFrame([{"FILE_NAME": filename}])
+
     ################## PREPROCESS ##################
     contract_text = preprocess.clean_text(contract_text)
     text_dict, top_sheet_dict = preprocess.split_text(contract_text)
@@ -37,14 +44,6 @@ def process_file(file_object, constants: Constants, run_timestamp):
         text_dict, constants.EXHIBIT_HEADER_MARKERS, filename
     )
 
-    # Set default values
-    dynamic_one_to_one_fields = FieldSet()
-    process_one_to_n = config.FIELDS in ['all', 'one_to_n']
-    process_one_to_one = config.FIELDS in ['all', 'one_to_one']
-
-    # Initialize default fallback for final results
-    final_results = pd.DataFrame([{"FILE_NAME": filename}])
-
     # ONE TO N PROCESSING
     if process_one_to_n:
         exhibit_dict, all_exhibit_headers = preprocess.one_to_n_exhibit_chunking(
@@ -58,8 +57,9 @@ def process_file(file_object, constants: Constants, run_timestamp):
             one_to_n_results, dynamic_one_to_one_fields = run_one_to_n_prompts(
                 filename, exhibit_dict, all_exhibit_headers, constants
             )
-            one_to_n_results["FILE_NAME"] = filename
-            one_to_n_results = postprocessing_funcs.generate_reimb_ids(one_to_n_results)
+            if not one_to_n_results.empty:
+                one_to_n_results["FILE_NAME"] = filename
+                one_to_n_results = postprocessing_funcs.generate_reimb_ids(one_to_n_results)
             logging.info(f"{datetime_str()} One to N Complete - {filename}")
         else:
             logging.info(f"{datetime_str()} No Reimbursement Found, Skipping - {filename}")
@@ -82,7 +82,7 @@ def process_file(file_object, constants: Constants, run_timestamp):
         logging.info(f"{datetime_str()} One to One Complete - {filename}")
         
         # Decide how to handle one_to_one results
-        if process_one_to_n:
+        if not one_to_n_results.empty:
             # BOTH processed - merge into one_to_n
             final_results = row_funcs.merge_one_to_one_into_one_to_n(
                 one_to_n_results, one_to_one_results, constants
@@ -94,7 +94,7 @@ def process_file(file_object, constants: Constants, run_timestamp):
         logging.info(f"{datetime_str()} Fields not configured for One to One, Skipping - {filename}")
 
     # APPLY CODES IF ONE_TO_N WAS PROCESSED
-    if process_one_to_n:
+    if not one_to_n_results.empty:
         results_with_code = code_funcs.code_breakout(final_results, constants)
         final_results = code_funcs.grouper_breakout(results_with_code)
         logging.info(f"{datetime_str()} Codes Complete - {filename}")

fieldExtraction/src/investment/main.py

@@ -100,7 +100,7 @@ def main(testing=False, test_params={}):
 
     # Warm prompt caches before parallel processing
     # This ensures the cache is registered before multiple threads try to use it
-    logging.debug("Warming prompt caches before parallel processing...")
+    logging.info("Warming prompt caches before parallel processing...")
     try:
         cacheable_instructions = prompt_templates.get_cacheable_instructions(constants)
         for cache_key, instruction in cacheable_instructions.items():
@@ -109,7 +109,7 @@ def main(testing=False, test_params={}):
                 cache_key=cache_key,
                 model_id="sonnet_latest"
             )
-        logging.debug(f"Successfully warmed {len(cacheable_instructions)} prompt caches")
+        logging.info(f"Successfully warmed {len(cacheable_instructions)} prompt caches")
     except Exception as e:
         logging.warning(f"Error warming caches (will proceed anyway): {str(e)}")
 

fieldExtraction/src/investment/row_funcs.py

@@ -66,6 +66,7 @@ def merge_one_to_one_into_one_to_n(
     Returns:
         pd.DataFrame: Updated one_to_n_results with merged values from one_to_one_results.
     """
+
     # Iterate over all key-value pairs in one_to_one_results
     for k, v in one_to_one_results.items():
         if k not in one_to_n_results.columns: