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4415f20 22e29e9 4415f20 22e29e9 215ad0b 4415f20 22e29e9 4415f20 22e29e9 4415f20 22e29e9 4415f20 22e29e9 4415f20 22e29e9 4415f20 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | import json
from huggingface_hub import AsyncInferenceClient
from core import config
from core.globals import ml_models
async def predict_sentiment(text: str):
client: AsyncInferenceClient = ml_models.get("llm_client")
if not client:
raise RuntimeError("LLM Client not loaded.")
system_prompt = f"You are a strict classifier. Classify the user's text into one of these sentiments: {config.SENTIMENT_CLASSES}. Return ONLY a JSON object with 'prediction' (string) and 'confidence' (float between 0.0 and 1.0). Do not include any other text."
user_prompt = text
try:
response = await client.chat_completion(
messages=[{"role": "system", "content": system_prompt}, {"role": "user", "content": user_prompt}],
max_tokens=50, temperature=0.1
)
content = response.choices[0].message.content.strip()
# Clean potential markdown wrapping
if content.startswith("```json"): content = content[7:]
if content.endswith("```"): content = content[:-3]
data = json.loads(content)
return data.get("prediction", "Neutral"), float(data.get("confidence", 0.0))
except Exception as e:
print(f"Sentiment classification failed: {e}")
return "Neutral", 0.0
async def predict_ticket(text: str):
client: AsyncInferenceClient = ml_models.get("llm_client")
if not client:
raise RuntimeError("LLM Client not loaded.")
system_prompt = f"You are a strict classifier. Classify the user's text into one of these ticket categories: {config.TICKET_CLASSES}. Return ONLY a JSON object with 'prediction' (string) and 'confidence' (float between 0.0 and 1.0). Do not include any other text."
user_prompt = text
try:
response = await client.chat_completion(
messages=[{"role": "system", "content": system_prompt}, {"role": "user", "content": user_prompt}],
max_tokens=50, temperature=0.1
)
content = response.choices[0].message.content.strip()
if content.startswith("```json"): content = content[7:]
if content.endswith("```"): content = content[:-3]
data = json.loads(content)
return data.get("prediction", "General Inquiry"), float(data.get("confidence", 0.0))
except Exception as e:
print(f"Ticket classification failed: {e}")
return "General Inquiry", 0.0
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