refactored for clarity

web_ui/brain.py

@@ -8,6 +8,7 @@ openai.api_key = util.read_file(r'.user\API-KEYS.txt').strip()
 BRAIN_DATA = util.read_json_file(r'.user\brain-data.json')
 prompt_dir = '.user/prompt'
 
+
 def build(chunk_size=4000):
     all_text = util.read_file(r'.user\input.txt')
 
@@ -18,12 +19,13 @@ def build(chunk_size=4000):
 
     for chunk in chunks:
         embedding = gpt.embedding(chunk.encode(encoding='ASCII', errors='ignore').decode())
-        info = {'content':chunk, 'vector':embedding}
+        info = {'content': chunk, 'vector': embedding}
         print(info, '\n\n\n')
         result.append(info)
 
     util.write_json_file(result, r'.user\brain-data.json')
 
+
 def run_answer(query, model, temp, max_tokens, top_p, freq_penl, pres_penl, chunk_count):
     results = gpt.search_chunks(query, BRAIN_DATA, chunk_count)
     answers = []
@@ -42,6 +44,7 @@ def run_answer(query, model, temp, max_tokens, top_p, freq_penl, pres_penl, chun
     # print('\n\n============ANSWER============\n\n', all_answers)
     return all_answers
 
+
 def run_summary(query, model, temp, max_tokens, top_p, freq_penl, pres_penl):
     chunks = textwrap.wrap(query, 10000)
     summaries = []
@@ -51,4 +54,4 @@ def run_summary(query, model, temp, max_tokens, top_p, freq_penl, pres_penl):
         summaries.append(summary)
     all_summary = '\n\n'.join(summaries)
     # print('\n\n============SUMMRY============\n\n', all_summary)
-    return all_summary
+    return all_summary