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import os
import requests
from dotenv import load_dotenv
load_dotenv()
HF_API_TOKEN = os.getenv("HF_API_TOKEN")
SUMMARIZATION_MODEL = "facebook/bart-large-cnn"
TAGS_MODEL = "dslim/bert-base-NER"
SENTIMENT_MODEL = "cardiffnlp/twitter-roberta-base-sentiment"
LABEL_MAP = {"LABEL_0": "Negative", "LABEL_1": "Neutral", "LABEL_2": "Positive"}
ERROR_400_MSG = "Oops! Error 400 — this model might not understand that language. Try using English! If you did, then something went wrong on our end. Sorry x("
TIMEOUT = 30
def summarize_text(text):
headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}
payload = {"inputs": text, "parameters": {"min_length": 30, "max_length": 130}}
try:
resp = requests.post(
f"https://api-inference.huggingface.co/models/{SUMMARIZATION_MODEL}",
headers=headers,
json=payload,
timeout=TIMEOUT
)
resp.raise_for_status()
out = resp.json()
if isinstance(out, list) and out:
return out[0]["summary_text"]
return str(out)
except requests.exceptions.HTTPError as e:
if e.response.status_code == 400:
return ERROR_400_MSG
return f"Hugging Face API inference failed: {e}"
def extract_tags(text):
headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}
payload = {"inputs": text}
try:
resp = requests.post(
f"https://api-inference.huggingface.co/models/{TAGS_MODEL}",
headers=headers,
json=payload,
timeout=TIMEOUT
)
resp.raise_for_status()
out = resp.json()
entities = [item.get("word") for item in out if "word" in item]
tags = list(set(entities))
return ", ".join(tags) if tags else "No tags found."
except requests.exceptions.HTTPError as e:
if e.response.status_code == 400:
return ERROR_400_MSG
return f"Hugging Face API inference failed: {e}"
def detect_sentiment(text):
headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}
payload = {"inputs": text}
try:
resp = requests.post(
f"https://api-inference.huggingface.co/models/{SENTIMENT_MODEL}",
headers=headers,
json=payload,
timeout=TIMEOUT
)
resp.raise_for_status()
out = resp.json()
if isinstance(out, list) and len(out) > 0:
result = out[0] if isinstance(out[0], list) else out
best = max(result, key=lambda x: x["score"])
return LABEL_MAP.get(best["label"], "Unknown")
return "Unknown"
except requests.exceptions.HTTPError as e:
if e.response.status_code == 400:
return ERROR_400_MSG
return f"Hugging Face API inference failed: {e}" |