chore: mati commits

gpt_chunks.py

@@ -24,7 +24,7 @@ def process_sentence(sentence, chunked_sentences):
   return chunked_sentences
 
 
-def chunk_sentences(file_path, output_path, api_key):
+def chunk_sentences(file_path, output_path):
   # Read the sentences from the file
   with open(file_path, 'r') as file:
     sentences = file.readlines()
@@ -39,9 +39,9 @@ def chunk_sentences(file_path, output_path, api_key):
 
 
 # Usage
-file_path = 'STSint.testinput.answers-students.sent1.txt'
+file_path = 'test_goldStandard/headlines/STSint.testinput.headlines.sent2.txt'
-output_path = 'chunks_one.txt'
+output_path = 'chunks_gpt_headlines_two.txt'
-api_key = os.environ['API_KEY']
+# Change me to os.environ['API_KEY']
-client = OpenAI(api_key=os.environ['API_KEY'])
+client = OpenAI(api_key='REDACTED_OPENAI_API_KEY')
 
-chunk_sentences(file_path, output_path, api_key)
+chunk_sentences(file_path, output_path)

main.py

@@ -1,8 +1,18 @@
-import processing.py
+import processing
+import pandas as pd
 
 # paths to students andsewrs database
-studentAnswers1_path = "\test_goldstandard\STSint.testinput.answers-students.sent1.txt"
+studentAnswers1_path = "test_goldStandard/student/STSint.testinput.answers-students.sent1.txt"
-studentAnswers2_path = "\test_goldstandard\STSint.testinput.answers-students.sent2.txt"
+studentAnswers2_path = "test_goldStandard/student/STSint.testinput.answers-students.sent2.txt"
-studentAnsewrs_chunked_path1 = "test_goldstandard\STSint.testinput.answers-students.sent1.chunk.txt"
+studentAnsewrs_chunked_path1 = "test_goldStandard/student/STSint.testinput.answers-students.sent1.chunk.txt"
-studentAnsewrs_chunked_path2 = "test_goldstandard\STSint.testinput.answers-students.sent2.chunk.txt"
+studentAnsewrs_chunked_path2 = "test_goldStandard/student/STSint.testinput.answers-students.sent2.chunk.txt"
-studentsAnsewrs_alignment_path = "test_goldstandard\STSint.testinput.answers-students.wa"
+studentsAnsewrs_alignment_path = "test_goldStandard/student/STSint.testinput.answers-students.wa"
+
+# load data
+studentAnserws = processing.load_sentences(studentAnswers1_path, studentAnswers1_path)
+goldstandard_chunked = processing.load_chunked(studentAnsewrs_chunked_path1, studentAnsewrs_chunked_path2)
+goldstandard_alignment = processing.load_alignment(studentsAnsewrs_alignment_path)
+
+
+data = pd.merge(goldstandard_chunked, goldstandard_alignment, left_index=True, right_index=True).head(5)
+print(data)

processing.py

@@ -3,7 +3,7 @@ import numpy as np
 from lxml import etree
 
 
-def load_sentences(senteance1_path: str, sentance2_path: str) -> pd.dataframe:
+def load_sentences(senteance1_path: str, sentance2_path: str) -> pd.DataFrame:
   """
   Loads the sentences from the given paths and outputs in a 2 columns dataframe
   """
@@ -34,7 +34,7 @@ def chunk2list(chunks: str) -> list:
   return split
 
 
-def load_chunked(chunked_path1: str, chunked_path2: str) -> pd.dataframe:
+def load_chunked(chunked_path1: str, chunked_path2: str) -> pd.DataFrame:
   """
   Loads chunked sentances in [ chunk1 ] [ chunk2 ] format into dataframe with lists of chunks
   """
@@ -65,12 +65,12 @@ def return_characteers(cell: str) -> str:
   """
   converts the alignment data to restore the <==> and & tokens
   """
-    cell = cell.replace('ARROWS_PLACEHOLDER', '<==>')
+  cell = cell.replace('ARROWS_PLACEHOLDER', '<==>')
-    cell = cell.replace('AMPERSAND_PLACEHOLDER', '&')
+  cell = cell.replace('AMPERSAND_PLACEHOLDER', '&')
-    return cell
+  return cell
 
 
-def load_alignment(alignment_path: str) -> pd.dataframe:
+def load_alignment(alignment_path: str) -> pd.DataFrame:
   """
   Loads the alignment file. Parses only the <alignment> tag and puts the data into a dataframe
   """
@@ -82,7 +82,7 @@ def load_alignment(alignment_path: str) -> pd.dataframe:
   # it also needs a root wrapped to function properly 
   modified_content = f'<root>{modified_content}</root>'
 
-  modified_file_path = 'test_goldstandard/fixedarrows.wa'
+  modified_file_path = 'temp.wa'
   with open(modified_file_path, 'w') as modified_file:
     modified_file.write(modified_content)
 
@@ -116,7 +116,7 @@ def test_XML():
   # test out the format
   print(alignments_data[0]["alignment_text"])
 
-def generate_train_test_split(x: pd.dataframe, y: pd.dataframe) -> train, validate, test: pd.dataframe:
+def generate_train_test_split(x: pd.DataFrame, y: pd.DataFrame):
   """
   Generates a train, validate, test split of the given dataframes in a 60% 20% 20% ratio
   """
@@ -125,5 +125,3 @@ def generate_train_test_split(x: pd.dataframe, y: pd.dataframe) -> train, valida
 
   return train, validate, test
 
-
-