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from llms import LLM
from utils.remote_client import execute_remote_task
def topic_classification(text: str, model: str, candidate_labels=None, custom_instructions: str = "", use_llm: bool = True) -> str:
"""
Classify text into topics using either LLM or traditional (Modal API) method.
Args:
text: The text to classify
model: The model to use
candidate_labels: List of candidate topics/categories
custom_instructions: Optional instructions for LLM
use_llm: Whether to use LLM or traditional method
"""
if not text.strip():
return ""
if use_llm:
return _topic_classification_with_llm(text, model, candidate_labels, custom_instructions)
else:
return _topic_classification_with_traditional(text, model, candidate_labels)
def _topic_classification_with_llm(text: str, model: str, candidate_labels=None, custom_instructions: str = "") -> str:
try:
llm = LLM(model=model)
labels_str = ", ".join(candidate_labels) if candidate_labels else "any appropriate topic"
prompt = (
f"Classify the following text into ONE of these categories: {labels_str}.\n" +
f"Return ONLY the most appropriate category name.\n" +
(f"{custom_instructions}\n" if custom_instructions else "") +
f"Text: {text}\nCategory:"
)
result = llm.generate(prompt)
return result.strip()
except Exception as e:
print(f"Error in LLM topic classification: {str(e)}")
return "Oops! Something went wrong. Please try again later."
def _topic_classification_with_traditional(text: str, model: str, labels=None) -> str:
try:
payload = {
"text": text,
"model": model,
"task": "topic"
}
if labels is not None:
payload["labels"] = labels
resp = execute_remote_task("classification", payload)
if "error" in resp:
return "Oops! Something went wrong. Please try again later."
return resp.get("labels", "")
except Exception as e:
print(f"Error in traditional topic classification: {str(e)}")
return "Oops! Something went wrong. Please try again later."
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