Merge pull request #30 from telexintegrations/main

merge: bring staging up to date with main

Author: iamprecieee

src/config/data.py

@@ -395,3 +395,18 @@
         ("streamline", "delivery"),
     ],
 }
+
+VALID_PAIRS = {
+    "bl", "br", "ch", "cl", "cr", "dr", "fl", "fr", "gl", "gr",
+    "ph", "pl", "pr", "sc", "sh", "sk", "sl", "sm", "sn", "sp",
+    "st", "sw", "th", "tr", "tw", "wh", "wr"
+}
+
+LETTER_FREQUENCY = {
+    "e": 12.7, "t": 9.1, "a": 8.2, "o": 7.5, "i": 7.0,
+    "n": 6.7, "s": 6.3, "h": 6.1, "r": 6.0, "d": 4.3,
+    "l": 4.0, "c": 2.8, "u": 2.8, "m": 2.4, "w": 2.4,
+    "f": 2.2, "g": 2.0, "y": 2.0, "p": 1.9, "b": 1.5,
+    "v": 0.98, "k": 0.77, "j": 0.15, "x": 0.15,
+    "q": 0.095, "z": 0.074
+}

src/core/analyzer.py

@@ -4,6 +4,8 @@
     example_commits,
     commit_training_data,
     semantic_patterns,
+    VALID_PAIRS,
+    LETTER_FREQUENCY
 )
 from fastapi import HTTPException, status
 from sklearn.metrics.pairwise import cosine_similarity
@@ -82,7 +84,7 @@ def _check_format(self, message: str) -> list[CommitIssue]:
                 CommitIssue(
                     severity="high",
                     message="Invalid commit type",
-                    suggestion=f"Use '{likely_type}' for this kind of change\nExample: `{self.example_commits[likely_type]}`",
+                    suggestion=f"Use '{likely_type}' for this kind of change\n└─ Example:\n• ```{self.example_commits[likely_type]}```",
                 )
             ]
         return []
@@ -121,24 +123,63 @@ def _suggest_commit_type(self, message: str) -> str:
 
     def _check_gibberish(self, word: str) -> bool:
         """
-        Determines if a word is likely to be gibberish based on vowel content.
+        Determines if a word is likely to be gibberish using multiple linguistic patterns.
         
-        Criteria for identifying gibberish:
-        - Words shorter than 2 characters must contain at least one vowel
-        - Words 2 characters or longer must have a vowel ratio of at least 0.2
+        The function employs four distinct checks to identify gibberish:
+        1. Vowel ratio: Words must maintain a minimum vowel-to-length ratio of 0.2
+        2. Consonant sequences: Flags sequences of more than 4 consecutive consonants
+        3. Letter frequency: For words >= 4 chars, compares letter frequencies against English language norms
+        4. Consonant pairs: Identifies invalid consonant combinations that rarely occur in English
+        
+        A word is considered gibberish if it fails two or more of these checks.
         """
-        cleaned_word = word.strip(string.punctuation)
-        if not cleaned_word:
+        VOWELS = set('aeiouyAEIOUY')
+            
+        word = word.lower().strip(string.punctuation)
+        if not word or len(word) < 2 or not word.isalpha():
             return False
 
-        vowels = set("aeiouyAEIOUY")
-        vowel_count = sum(1 for char in cleaned_word if char in vowels)
-        
-        if len(cleaned_word) < 2:
-            return vowel_count == 0
-        else:
-            vowel_ratio = vowel_count / len(cleaned_word)
-            return vowel_ratio < 0.2
+        failed_checks = 0
+
+        vowel_count = sum(1 for c in word if c in VOWELS)
+        if vowel_count / len(word) < 0.2:
+            failed_checks += 1
+            
+        consonant_sequence = 0
+        for char in word:
+            if char not in VOWELS:
+                consonant_sequence += 1
+                if consonant_sequence > 4:
+                    failed_checks += 1
+                    break
+            else:
+                consonant_sequence = 0
+                
+        if len(word) >= 4:
+            char_counts = {}
+            for char in word:
+                char_counts[char] = char_counts.get(char, 0) + 1
+
+            deviation = 0
+            for char, count in char_counts.items():
+                if char in LETTER_FREQUENCY:
+                    expected = LETTER_FREQUENCY[char] / 100
+                    actual = count / len(word)
+                    deviation += abs(expected - actual)
+
+            if (deviation / len(char_counts)) > 0.5:
+                failed_checks += 1
+                
+        invalid_pairs = 0
+        for i in range(len(word) - 1):
+            pair = word[i:i+2]
+            if pair not in VALID_PAIRS and pair[0] not in VOWELS and pair[1] not in VOWELS:
+                invalid_pairs += 1
+                if invalid_pairs > 1:
+                    failed_checks += 1
+                    break
+
+        return failed_checks >= 2
 
     def _check_content_quality(self, message: str) -> list[CommitIssue]:
         """
@@ -232,4 +273,4 @@ def format_analysis(self, commit: dict, issues: list[CommitIssue]) -> str:
             "└─ Git Best Practices: <https://git-scm.com/book/en/v2/Distributed-Git-Contributing-to-a-Project|Git Contributing>"
         )
 
-        return f"{commit_details}{analysis_section}{suggestions}"
+        return f"{commit_details}{analysis_section}{suggestions}"