Update app.py

app.py

@@ -59,8 +59,6 @@ FILE_EMOJIS = {
     "mp3": "🎵",
 }
 
-
-
 def get_high_info_terms(text: str) -> list:
     # Expanded stop words
     stop_words = set([
@@ -72,7 +70,7 @@ def get_high_info_terms(text: str) -> list:
         'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most',
         'other', 'some', 'such', 'than', 'too', 'very', 'just', 'there', 'as', 'if', 'while'
     ])
-    
+
     # Key phrases tailored to your interests
     key_phrases = [
         'artificial intelligence', 'machine learning', 'deep learning', 'neural networks',
@@ -112,53 +110,6 @@ def get_high_info_terms(text: str) -> list:
 
     # Return only the top 5 terms
     return unique_terms[:5]
-    
-
-def get_high_info_terms_old(text: str) -> list:
-    stop_words = set([
-        'the', 'a', 'an', 'and', 'or', 'but', 'in', 'on', 'at', 'to', 'for', 'of', 'with',
-        'by', 'from', 'up', 'about', 'into', 'over', 'after', 'is', 'are', 'was', 'were',
-        'be', 'been', 'being', 'have', 'has', 'had', 'do', 'does', 'did', 'will', 'would',
-        'should', 'could', 'might', 'must', 'shall', 'can', 'may', 'this', 'that', 'these',
-        'those', 'i', 'you', 'he', 'she', 'it', 'we', 'they', 'what', 'which', 'who',
-        'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most',
-        'other', 'some', 'such', 'than', 'too', 'very', 'just', 'there'
-    ])
-    key_phrases = [
-        'artificial intelligence', 'machine learning', 'deep learning', 'neural network',
-        'personal assistant', 'natural language', 'computer vision', 'data science',
-        'reinforcement learning', 'knowledge graph', 'semantic search', 'time series',
-        'large language model', 'transformer model', 'attention mechanism',
-        'autonomous system', 'edge computing', 'quantum computing', 'blockchain technology',
-        'cognitive science', 'human computer', 'decision making', 'arxiv search',
-        'research paper', 'scientific study', 'empirical analysis'
-    ]
-
-    preserved_phrases = []
-    lower_text = text.lower()
-    for phrase in key_phrases:
-        if phrase in lower_text:
-            preserved_phrases.append(phrase)
-            text = text.replace(phrase, '')
-
-    words = re.findall(r'\b\w+(?:-\w+)*\b', text)
-    high_info_words = [
-        word.lower() for word in words
-        if len(word) > 3
-        and word.lower() not in stop_words
-        and not word.isdigit()
-        and any(c.isalpha() for c in word)
-    ]
-
-    all_terms = preserved_phrases + high_info_words
-    seen = set()
-    unique_terms = []
-    for term in all_terms:
-        if term not in seen:
-            seen.add(term)
-            unique_terms.append(term)
-
-    return unique_terms[:5]
 
 def clean_text_for_filename(text: str) -> str:
     text = text.lower()
@@ -190,22 +141,6 @@ def generate_filename(prompt, response, file_type="md"):
     filename = f"{prefix}{full_name}.{file_type}"
     return filename
 
-def generate_filename_old(prompt, response, file_type="md"):
-    prefix = datetime.now().strftime("%m%d_%hh%mm") + "_"
-    combined = (prompt + " " + response).strip()
-    info_terms = get_high_info_terms(combined)
-
-    snippet = (prompt[:100] + " " + response[:100]).strip()
-    snippet_cleaned = clean_text_for_filename(snippet)
-    name_parts = info_terms + [snippet_cleaned]
-    full_name = '_'.join(name_parts)
-
-    if len(full_name) > 150:
-        full_name = full_name[:150]
-
-    filename = f"{prefix}{full_name}.{file_type}"
-    return filename
-
 def create_file(prompt, response, file_type="md"):
     filename = generate_filename(prompt.strip(), response.strip(), file_type)
     with open(filename, 'w', encoding='utf-8') as f: