Update agents/topic_agent.py
Browse files- agents/topic_agent.py +42 -16
agents/topic_agent.py
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# agents/topic_agent.py
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import openai
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import json
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class TopicAgent:
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def __init__(self, api_key=None):
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if not openai.api_key:
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return self._mock_outline(topic, duration, difficulty)
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def _mock_outline(self, topic, duration, difficulty):
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return {
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"topic": topic,
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"duration": f"{duration} hours",
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"difficulty": difficulty,
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"goals": [
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}
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import json
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import openai
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class TopicAgent:
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def __init__(self, api_key=None):
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if not openai.api_key:
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return self._mock_outline(topic, duration, difficulty)
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try:
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response = openai.ChatCompletion.create(
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model="gpt-4",
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messages=[
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{"role": "system", "content": "You're an expert corporate trainer creating AI workshop outlines"},
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{"role": "user", "content": (
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f"Create a {duration}-hour {difficulty} workshop outline on {topic}. "
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"Include: 1) Key learning goals, 2) 4 modules with titles and durations, "
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"3) Hands-on exercises per module. Output as JSON."
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)}
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]
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)
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return json.loads(response.choices[0].message.content)
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except:
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return self._mock_outline(topic, duration, difficulty)
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def _mock_outline(self, topic, duration, difficulty):
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return {
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"topic": topic,
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"duration": f"{duration} hours",
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"difficulty": difficulty,
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"goals": [
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f"Master advanced {topic} techniques",
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"Develop industry-specific applications",
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"Build and evaluate complex AI workflows",
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"Implement best practices for production"
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],
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"modules": [
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{
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"title": f"Fundamentals of {topic}",
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"duration": "30 min",
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"learning_points": [
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"Core principles and terminology",
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"Patterns and anti-patterns",
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"Evaluation frameworks"
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]
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},
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{
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"title": f"{topic} for Enterprise Applications",
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"duration": "45 min",
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"learning_points": [
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"Industry-specific use cases",
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"Integration with existing systems",
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"Scalability considerations"
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]
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}
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]
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}
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