Fix bot trigger to respond only when mentioned at start of message

[avelytchko]

• Changed is_bot_mentioned() to use startswith() instead of 'in' operator
• Bot now only responds when "ботяра" or "bot_health" is at the beginning
• Prevents false triggers when trigger words appear mid-sentence
• Preserves special characters like underscore in "bot_health"

Summary by CodeRabbit

• Bug Fixes
  • Improved bot mention detection to use exact prefix matching with proper word boundaries, reducing false positives when trigger words appear within other text or phrases.

_{✏️ Tip: You can customize this high-level summary in your review settings.}

[coderabbitai]

Walkthrough

The is_bot_mentioned() function in src/main.py was refactored to use strict prefix-and-boundary checking instead of substring containment. The function now trims and lowercases the message, returning true only when a bot trigger word is the leading token with no alphabetic character following it, reducing false positives.

Changes

Cohort / File(s)	Summary
Bot mention detection logic src/main.py	Reworked is_bot_mentioned() to perform strict prefix-and-boundary validation instead of substring matching, trimming and lowercasing input to check if a trigger word is the leading token without a trailing alphabetic character.

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

• Key focus areas:
  • Verify the prefix-and-boundary logic correctly identifies bot mentions and rejects mid-message occurrences of trigger words
  • Ensure edge cases are handled (empty messages, trigger word at message end, messages with special characters)
  • Confirm test coverage reflects the new stricter detection behavior

Possibly related PRs

• PR #91: Also modifies is_bot_mentioned() in src/main.py but implements opposite detection logic (broadens vs. tightens trigger word matching).

Pre-merge checks and finishing touches

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title accurately describes the main change: converting bot trigger detection from substring matching to strict prefix-based detection with boundary checks, reducing false positives.
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%.

✨ Finishing touches

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🧪 Generate unit tests (beta)

• Create PR with unit tests
• Post copyable unit tests in a comment

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[coderabbitai]

Actionable comments posted: 1

📜 Review details

Configuration used: CodeRabbit UI

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between f1ae41d and 30a04b4.

📒 Files selected for processing (1)

• src/main.py (1 hunks)

[coderabbitai]

⚠️ Potential issue | 🟡 Minor

Consider stricter word boundary checking to avoid false positives.

The current boundary check uses isalpha(), which means messages like "ботяра123" or "bot_health_check" would trigger the bot since digits and underscores are not alphabetic. This could lead to unintended activations.

If you want strict word boundaries, consider checking for whitespace or end-of-string instead:

     bot_trigger_words = ["ботяра", "bot_health"]
     # Remove leading/trailing whitespace and convert to lowercase
     cleaned_text = message_text.strip().lower()
     for word in bot_trigger_words:
         if cleaned_text.startswith(word):
-            # Check if it's followed by space, punctuation, or is the whole message
-            if len(cleaned_text) == len(word) or not cleaned_text[len(word)].isalpha():
+            # Check if it's the whole message or followed by whitespace
+            if len(cleaned_text) == len(word) or cleaned_text[len(word)].isspace():
                 return True
     return False

Alternatively, if you want to allow punctuation but not alphanumeric characters:

     bot_trigger_words = ["ботяра", "bot_health"]
     # Remove leading/trailing whitespace and convert to lowercase
     cleaned_text = message_text.strip().lower()
     for word in bot_trigger_words:
         if cleaned_text.startswith(word):
-            # Check if it's followed by space, punctuation, or is the whole message
-            if len(cleaned_text) == len(word) or not cleaned_text[len(word)].isalpha():
+            # Check if it's the whole message or followed by non-alphanumeric character
+            if len(cleaned_text) == len(word) or not cleaned_text[len(word)].isalnum():
                 return True
     return False

📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change

	# Remove leading/trailing whitespace and convert to lowercase
	cleaned_text = message_text.strip().lower()
	for word in bot_trigger_words:
	if cleaned_text.startswith(word):
	# Check if it's followed by space, punctuation, or is the whole message
	if len(cleaned_text) == len(word) or not cleaned_text[len(word)].isalpha():
	return True
	return False
	# Remove leading/trailing whitespace and convert to lowercase
	cleaned_text = message_text.strip().lower()
	for word in bot_trigger_words:
	if cleaned_text.startswith(word):
	# Check if it's the whole message or followed by whitespace
	if len(cleaned_text) == len(word) or cleaned_text[len(word)].isspace():
	return True
	return False

Suggested change

	# Remove leading/trailing whitespace and convert to lowercase
	cleaned_text = message_text.strip().lower()
	for word in bot_trigger_words:
	if cleaned_text.startswith(word):
	# Check if it's followed by space, punctuation, or is the whole message
	if len(cleaned_text) == len(word) or not cleaned_text[len(word)].isalpha():
	return True
	return False
	# Remove leading/trailing whitespace and convert to lowercase
	cleaned_text = message_text.strip().lower()
	for word in bot_trigger_words:
	if cleaned_text.startswith(word):
	# Check if it's the whole message or followed by non-alphanumeric character
	if len(cleaned_text) == len(word) or not cleaned_text[len(word)].isalnum():
	return True
	return False

🤖 Prompt for AI Agents

In src/main.py around lines 109 to 116, the trigger-word boundary check using
cleaned_text[len(word)].isalpha() allows digits/underscores to pass and causes
false positives (e.g., "bot123" or "bot_health"); replace that check with a
stricter condition: treat the trigger as valid only if it's at end-of-string or
the following character is whitespace or a punctuation character (use
string.punctuation), e.g., check for len(cleaned_text)==len(word) or
cleaned_text[len(word)].isspace() or cleaned_text[len(word)] in
string.punctuation; ensure to import string at the top of the file.