Merged in bugfix/dynamic_issuefixes-clean (pull request #813)

Fix LOB_PROGRAM_RELATIONSHIP extraction and preserve debugging code

* Fix LOB_PROGRAM_RELATIONSHIP extraction and preserve debugging code

- Add format requirements to LOB_RELATIONSHIP_INSTRUCTION for proper caching
- Strengthen LOB_RELATIONSHIP prompt with explicit pipe delimiter requirements
- Preserve all DEBUG blocks and print statements in dynamic_funcs.py and file_processing.py
- Update crosswalk mappings and gitignore
- Ensure format instructions are cached at API level to prevent missing pipe delimiters

* Merge main into bugfix/dynamic_issuefixes-clean and remove all debug print statements

* Remove redundant one_to_one_fields initialization to match main


Approved-by: Katon Minhas

fieldExtraction/constants/mappings/crosswalk_product_lob.json

@@ -19,7 +19,7 @@
 
         },
         "Fidelis" : {
-            "Medicaid Managed Care" : "Medicaid"
+            
         },
         "Parkland" : {
             "HEALTHfirst" : "Medicaid",

fieldExtraction/constants/mappings/crosswalk_program.json

@@ -7,6 +7,7 @@
         "Children's Health Insurance Program (CHIP)" : "CHIP",
         "Children's Health Insurance Program Perinate (CHIP-P)" : "CHIPP",
         "Healthy Kids" : "CHIP",
+        "Medicaid Managed Care" : "MMC",
         "Affordable Care Act (ACA)" : "ACA",
         "Aged, Blind, and Disabled (ABD)" : "ABD",
         "Alternative Benefit Plan (ABP)" : "ABP",

fieldExtraction/constants/mappings/crosswalk_program_lob.json

@@ -6,6 +6,7 @@
     "mapping": {
         "CHIP" : "Medicaid",
         "CHIPP" : "Medicaid",
+        "MMC" : "Medicaid",
         "ACA" : "Marketplace",
         "ABD" : "Medicaid",
         "ABP" : "Medicaid",

fieldExtraction/src/investment/dynamic_funcs.py

@@ -35,7 +35,7 @@ def dynamic_primary(
 
     dynamic_reimbursement_fields = FieldSet()
     exhibit_level_answer_dict = {}
-    
+
     for field in dynamic_primary_fields.fields:
         exhibit_text_answer = prompt_calls.prompt_dynamic_primary(
             exhibit_text,
@@ -240,7 +240,7 @@ def get_dynamic_one_to_one_fields(answer_dicts: list[dict[str, str]], constants:
             ) # Try base_field first, fall back to field_name if base_field is None/empty
             one_to_one_fields = add_one_to_one_field(
                 one_to_one_fields, field_to_add, answer_dicts, constants
-            )            
+            )
     
     return one_to_one_fields
 

fieldExtraction/src/investment/file_processing.py

@@ -59,7 +59,7 @@ def process_file(file_object, constants: Constants, run_timestamp):
         logging.info(f"{datetime_str()} Fields not configured for One to N, Skipping - {filename}")
 
     # ONE TO ONE PROCESSING
-    if process_one_to_one:       
+    if process_one_to_one:
         one_to_one_results = run_one_to_one_prompts(
             filename,
             contract_text,
@@ -262,7 +262,7 @@ def run_one_to_n_prompts(text_dict: dict[str, str],
     dynamic_one_to_one_fields = dynamic_funcs.get_dynamic_one_to_one_fields(
         one_to_n_results, constants
     )
-    
+
     ################## CONVERT TO DF ##################
     one_to_n_df = pd.DataFrame(one_to_n_results)
 
@@ -273,7 +273,7 @@ def process_page_one_to_n(text_dict: dict[str, str], exhibit_page_nums: list[str
 
     page_text = text_dict[page_num]
     exhibit_text_simplified = preprocessing_funcs.simplify_exhibit(text_dict, exhibit_page_nums, page_num)
-    
+
     ############################### Reimbursement Primary ###############################
     reimbursement_level_answers = one_to_n_funcs.reimbursement_level(
         page_text,

fieldExtraction/src/investment/prompt_calls.py

@@ -209,7 +209,6 @@ def prompt_carveout_check(
         instruction=prompt_templates.CARVEOUT_CHECK_INSTRUCTION(),
         usage_label="CARVEOUT_CHECK",
     )
-    logging.debug(f"Carveout/ special case check for {filename}: {llm_answer_raw}")
 
     carveout_answer = string_utils.extract_text_from_delimiters(
         llm_answer_raw, Delimiter.PIPE

fieldExtraction/src/prompts/prompt_templates.py

@@ -1359,14 +1359,15 @@ It was previously identified that the Exhibit contains the following LOB and Pro
     - Some examples of language indicating an exlusive relationship are "Medicaid: CHIP", "Medicare advantage only", and "Duals - only the following SNP programs"
     - If the programs are represented with different sections of the Exhibit under the same higher-level LOB section, this is indicative of an Exclusive relationship.
         - For example, if an exhibit has a header that says "Medicaid & CHIP", but then there are different subsections within the Exhibit for "Medicaid" and "CHIP", this is an Exclusive relationship even though the "&" language is Inclusive.
-- Closely read the text, then write either |Inclusive| or |Exclusive| to indicate the nature of the relationship.
 
 [CONTEXT]
 Here is the Exhibit to be analyzed:
 {exhibit_text.replace('"', "'")}
 
-[OUTPUT]
-Briefly explain your reasoning, then put your final answer in |pipes|.
+[OUTPUT FORMAT - REQUIRED]
+You MUST format your response with pipe delimiters. Example format:
+"Based on the analysis... |Inclusive|" or "The relationship is... |Exclusive|"
+Your final answer MUST be enclosed in pipe delimiters: |Inclusive| or |Exclusive|
 """
 
 
@@ -1389,7 +1390,13 @@ def DERIVED_TERM_DATE_PROMPT(
 def LOB_RELATIONSHIP_INSTRUCTION() -> str:
     return (
         "[OBJECTIVE]\n"
-        "Determine if LOB and Program relationship in the exhibit is Inclusive or Exclusive."
+        "Determine if LOB and Program relationship in the exhibit is Inclusive or Exclusive.\n\n"
+        "[OUTPUT FORMAT - CRITICAL]\n"
+        "You MUST format your response as follows:\n"
+        "1. Briefly explain your reasoning\n"
+        "2. Then put your final answer in pipe delimiters: |Inclusive| or |Exclusive|\n"
+        "Example: 'The contract shows... |Inclusive|'\n"
+        "Your response MUST include the pipe delimiters (|) around your final answer."
     )