Initial commit

hooks/utils/llm/anth.py

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+#!/usr/bin/env -S uv run --script
+# /// script
+# requires-python = ">=3.8"
+# dependencies = [
+#     "anthropic",
+#     "python-dotenv",
+# ]
+# ///
+
+import os
+import sys
+
+from dotenv import load_dotenv
+
+
+def prompt_llm(prompt_text):
+    """
+    Base Anthropic LLM prompting method using fastest model.
+
+    Args:
+        prompt_text (str): The prompt to send to the model
+
+    Returns:
+        str: The model's response text, or None if error
+    """
+    load_dotenv()
+
+    api_key = os.getenv("ANTHROPIC_API_KEY")
+    if not api_key:
+        return None
+
+    try:
+        import anthropic
+
+        client = anthropic.Anthropic(api_key=api_key)
+
+        message = client.messages.create(
+            model="claude-3-5-haiku-20241022",  # Fastest Anthropic model
+            max_tokens=100,
+            temperature=0.7,
+            messages=[{"role": "user", "content": prompt_text}],
+        )
+
+        return message.content[0].text.strip()
+
+    except Exception:
+        return None
+
+
+def generate_completion_message():
+    """
+    Generate a completion message using Anthropic LLM.
+
+    Returns:
+        str: A natural language completion message, or None if error
+    """
+    engineer_name = os.getenv("ENGINEER_NAME", "").strip()
+
+    if engineer_name:
+        name_instruction = f"Sometimes (about 30% of the time) include the engineer's name '{engineer_name}' in a natural way."
+        examples = f"""Examples of the style: 
+- Standard: "Work complete!", "All done!", "Task finished!", "Ready for your next move!"
+- Personalized: "{engineer_name}, all set!", "Ready for you, {engineer_name}!", "Complete, {engineer_name}!", "{engineer_name}, we're done!" """
+    else:
+        name_instruction = ""
+        examples = """Examples of the style: "Work complete!", "All done!", "Task finished!", "Ready for your next move!" """
+
+    prompt = f"""Generate a short, friendly completion message for when an AI coding assistant finishes a task. 
+
+Requirements:
+- Keep it under 10 words
+- Make it positive and future focused
+- Use natural, conversational language
+- Focus on completion/readiness
+- Do NOT include quotes, formatting, or explanations
+- Return ONLY the completion message text
+{name_instruction}
+
+{examples}
+
+Generate ONE completion message:"""
+
+    response = prompt_llm(prompt)
+
+    # Clean up response - remove quotes and extra formatting
+    if response:
+        response = response.strip().strip('"').strip("'").strip()
+        # Take first line if multiple lines
+        response = response.split("\n")[0].strip()
+
+    return response
+
+
+def main():
+    """Command line interface for testing."""
+    if len(sys.argv) > 1:
+        if sys.argv[1] == "--completion":
+            message = generate_completion_message()
+            if message:
+                print(message)
+            else:
+                print("Error generating completion message")
+        else:
+            prompt_text = " ".join(sys.argv[1:])
+            response = prompt_llm(prompt_text)
+            if response:
+                print(response)
+            else:
+                print("Error calling Anthropic API")
+    else:
+        print("Usage: ./anth.py 'your prompt here' or ./anth.py --completion")
+
+
+if __name__ == "__main__":
+    main()

hooks/utils/llm/oai.py

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+#!/usr/bin/env -S uv run --script
+# /// script
+# requires-python = ">=3.8"
+# dependencies = [
+#     "openai",
+#     "python-dotenv",
+# ]
+# ///
+
+import os
+import sys
+
+from dotenv import load_dotenv
+
+
+def prompt_llm(prompt_text):
+    """
+    Base OpenAI LLM prompting method using fastest model.
+
+    Args:
+        prompt_text (str): The prompt to send to the model
+
+    Returns:
+        str: The model's response text, or None if error
+    """
+    load_dotenv()
+
+    api_key = os.getenv("OPENAI_API_KEY")
+    if not api_key:
+        return None
+
+    try:
+        from openai import OpenAI
+
+        client = OpenAI(api_key=api_key)
+
+        response = client.chat.completions.create(
+            model="gpt-4.1-nano",  # Fastest OpenAI model
+            messages=[{"role": "user", "content": prompt_text}],
+            max_tokens=100,
+            temperature=0.7,
+        )
+
+        return response.choices[0].message.content.strip()
+
+    except Exception:
+        return None
+
+
+def generate_completion_message():
+    """
+    Generate a completion message using OpenAI LLM.
+
+    Returns:
+        str: A natural language completion message, or None if error
+    """
+    engineer_name = os.getenv("ENGINEER_NAME", "").strip()
+
+    if engineer_name:
+        name_instruction = f"Sometimes (about 30% of the time) include the engineer's name '{engineer_name}' in a natural way."
+        examples = f"""Examples of the style: 
+- Standard: "Work complete!", "All done!", "Task finished!", "Ready for your next move!"
+- Personalized: "{engineer_name}, all set!", "Ready for you, {engineer_name}!", "Complete, {engineer_name}!", "{engineer_name}, we're done!" """
+    else:
+        name_instruction = ""
+        examples = """Examples of the style: "Work complete!", "All done!", "Task finished!", "Ready for your next move!" """
+
+    prompt = f"""Generate a short, friendly completion message for when an AI coding assistant finishes a task. 
+
+Requirements:
+- Keep it under 10 words
+- Make it positive and future focused
+- Use natural, conversational language
+- Focus on completion/readiness
+- Do NOT include quotes, formatting, or explanations
+- Return ONLY the completion message text
+{name_instruction}
+
+{examples}
+
+Generate ONE completion message:"""
+
+    response = prompt_llm(prompt)
+
+    # Clean up response - remove quotes and extra formatting
+    if response:
+        response = response.strip().strip('"').strip("'").strip()
+        # Take first line if multiple lines
+        response = response.split("\n")[0].strip()
+
+    return response
+
+
+def main():
+    """Command line interface for testing."""
+    if len(sys.argv) > 1:
+        if sys.argv[1] == "--completion":
+            message = generate_completion_message()
+            if message:
+                print(message)
+            else:
+                print("Error generating completion message")
+        else:
+            prompt_text = " ".join(sys.argv[1:])
+            response = prompt_llm(prompt_text)
+            if response:
+                print(response)
+            else:
+                print("Error calling OpenAI API")
+    else:
+        print("Usage: ./oai.py 'your prompt here' or ./oai.py --completion")
+
+
+if __name__ == "__main__":
+    main()