Initial commit

hooks/utils/llm/anth.py

@@ -0,0 +1,186 @@
+#!/usr/bin/env python3
+
+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 generate_agent_name():
+    """
+    Generate a one-word agent name using Anthropic.
+
+    Returns:
+        str: A single-word agent name, or fallback name if error
+    """
+    import random
+
+    # Example names to guide generation
+    example_names = [
+        "Phoenix", "Sage", "Nova", "Echo", "Atlas", "Cipher", "Nexus",
+        "Oracle", "Quantum", "Zenith", "Aurora", "Vortex", "Nebula",
+        "Catalyst", "Prism", "Axiom", "Helix", "Flux", "Synth", "Vertex"
+    ]
+
+    # If no API key, return random fallback
+    if not os.getenv("__ANTHROPIC_API_KEY"):
+        return random.choice(example_names)
+
+    # Create examples string
+    examples_str = ", ".join(example_names[:10])  # Use first 10 as examples
+
+    prompt_text = f"""Generate exactly ONE unique agent/assistant name.
+
+Requirements:
+- Single word only (no spaces, hyphens, or punctuation)
+- Abstract and memorable
+- Professional sounding
+- Easy to pronounce
+- Similar style to these examples: {examples_str}
+
+Generate a NEW name (not from the examples). Respond with ONLY the name, nothing else.
+
+Name:"""
+
+    try:
+        # Use faster Haiku model with lower tokens for name generation
+        load_dotenv()
+        api_key = os.getenv("__ANTHROPIC_API_KEY")
+        if not api_key:
+            raise Exception("No API key")
+
+        import anthropic
+        client = anthropic.Anthropic(api_key=api_key)
+
+        message = client.messages.create(
+            model="claude-3-5-haiku-20241022",  # Fast model
+            max_tokens=20,
+            temperature=0.7,
+            messages=[{"role": "user", "content": prompt_text}],
+        )
+
+        # Extract and clean the name
+        name = message.content[0].text.strip()
+        # Ensure it's a single word
+        name = name.split()[0] if name else "Agent"
+        # Remove any punctuation
+        name = ''.join(c for c in name if c.isalnum())
+        # Capitalize first letter
+        name = name.capitalize() if name else "Agent"
+
+        # Validate it's not empty and reasonable length
+        if name and 3 <= len(name) <= 20:
+            return name
+        else:
+            raise Exception("Invalid name generated")
+
+    except Exception:
+        # Return random fallback name
+        return random.choice(example_names)
+
+
+def main():
+    """Command line interface for testing."""
+    import json
+
+    if len(sys.argv) > 1:
+        if sys.argv[1] == "--completion":
+            message = generate_completion_message()
+            if message:
+                print(message)
+            else:
+                print("Error generating completion message")
+        elif sys.argv[1] == "--agent-name":
+            # Generate agent name (no input needed)
+            name = generate_agent_name()
+            print(name)
+        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 or ./anth.py --agent-name")
+
+
+if __name__ == "__main__":
+    main()