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import openai
history = [
{"role": "system", "content": "You are a Python programming tutor and assistant."}
]
def query_dynamic_generation(user_input):
"""
Adjusts response verbosity based on query type.
"""
# Check for keywords to determine verbosity
if "explain" in user_input.lower() or "describe" in user_input.lower():
prompt = f"""
You are a Python tutor.Only answer questions related to Python programming and its libraries. Provide a concise explanation for the query, avoiding unnecessary details.
Focus on delivering the main point clearly and briefly.
Query: {user_input}
Response:
"""
elif "example" in user_input.lower() or "code" in user_input.lower():
prompt = f"""
You are a Python tutor.Only answer questions related to Python programming and its libraries. Provide a detailed code example for the query, formatted properly for readability with simple explanation.
Avoid lengthy explanations; focus on the code.
Query: {user_input}
Response:
"""
else:
prompt = f"""
You are a Python tutor.Only answer questions related to Python programming and its libraries. Provide a brief response that directly addresses the user's query.
Query: {user_input}
Response:
"""
# Generate response using OpenAI API
response = openai.ChatCompletion.create(
model="gpt-4o-mini",
messages=history + [{"role": "user", "content": prompt}], # Add the prompt to the message history
temperature=0.5,
max_tokens=500 # Ensure sufficient length for detailed code examples
)
return response.choices[0].message["content"].strip()
def format_code_block(response):
"""
Formats code blocks for proper HTML rendering.
"""
response = response.replace("```python", "<pre><code>").replace("```", "</code></pre>")
response = response.replace("\n", "<br>")
return response
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