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skills/pocketflow/assets/template/utils.py

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+"""
+PocketFlow Template - Utility Functions
+
+Source: https://github.com/The-Pocket/PocketFlow-Template-Python
+
+This module contains utility functions like LLM wrappers.
+"""
+
+import os
+
+
+def call_llm(prompt):
+    """
+    Call your LLM provider
+
+    Args:
+        prompt (str): The prompt to send to the LLM
+
+    Returns:
+        str: The LLM response
+
+    TODO: Implement your LLM provider here
+    """
+
+    # Example: OpenAI
+    """
+    from openai import OpenAI
+    client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+    response = client.chat.completions.create(
+        model="gpt-4o",
+        messages=[{"role": "user", "content": prompt}]
+    )
+    return response.choices[0].message.content
+    """
+
+    # Example: Anthropic
+    """
+    from anthropic import Anthropic
+    client = Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
+    response = client.messages.create(
+        model="claude-sonnet-4-0",
+        messages=[{"role": "user", "content": prompt}]
+    )
+    return response.content[0].text
+    """
+
+    # Example: Google Gemini
+    """
+    from google import genai
+    client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))
+    response = client.models.generate_content(
+        model='gemini-2.0-flash-exp',
+        contents=prompt
+    )
+    return response.text
+    """
+
+    raise NotImplementedError(
+        "Implement your LLM provider in utils.py\n"
+        "See examples above for OpenAI, Anthropic, or Google Gemini"
+    )