| import requests | |
| LABELS = ["sadness", "joy", "love", "anger", "fear", "surprise"] | |
| FEW_SHOT_EXAMPLES = """Message: "I got the promotion!" | |
| Answer: joy | |
| Message: "I bought this and I'm not happy with it" | |
| Answer: anger | |
| Message: "I'm not afraid of you" | |
| Answer: joy | |
| Message: "I am afraid of the dark" | |
| Answer: fear | |
| Message: "This isn't what I expected" | |
| Answer: sadness | |
| Message: "I can't stop thinking about her" | |
| Answer: love""" | |
| def classify(text, model="llama3.2:3b"): | |
| prompt = f"""Classify the emotion in each message as exactly one word from: sadness, joy, love, anger, fear, surprise. | |
| Pay close attention to negation words like "not", "isn't", "don't" — they reverse or change the emotion. | |
| {FEW_SHOT_EXAMPLES} | |
| Message: "{text}" | |
| Answer:""" | |
| response = requests.post( | |
| "http://localhost:11434/api/generate", | |
| json={"model": model, "prompt": prompt, "stream": False}, | |
| ) | |
| raw = response.json()["response"].strip().lower() | |
| first_line = raw.splitlines()[0] if raw else "" | |
| for label in LABELS: | |
| if label in first_line: | |
| return label | |
| for label in LABELS: | |
| if label in raw: | |
| return label | |
| return "surprise" | |
| if __name__ == "__main__": | |
| tests = [ | |
| "I'm not happy", | |
| "I'm not afraid", | |
| "I am afraid", | |
| "I bought this and I'm not happy with it", | |
| ] | |
| for t in tests: | |
| print(f"{t!r} -> {classify(t)}") |