| def detect_language(text, Language, LanguageDetectorBuilder, client, logging): |
| """Detect language of a given text using an LLM for short texts and Lingua for longer ones.""" |
| text = text.lower().strip() |
|
|
| |
| if len(text.split()) < 5: |
| system_prompt = """ |
| You are a language detection assistant. Identify the language of the given text. |
| Return only the language code: "en" for English or "sw" for Swahili. |
| If the language is neither English nor Swahili, return "unknown". |
| """ |
|
|
| user_message = f"Text: \"{text}\"" |
|
|
| try: |
| completion = client.chat.completions.create( |
| model="gpt-3.5-turbo", |
| messages=[ |
| {"role": "system", "content": system_prompt}, |
| {"role": "user", "content": user_message} |
| ], |
| temperature=0 |
| ) |
| detected_language = completion.choices[0].message.content.strip() |
| return detected_language |
| except Exception as e: |
| logging.warning(f"Language detection error (LLM): {e}") |
| return "unknown" |
|
|
| |
| try: |
| languages = [Language.ENGLISH, Language.SWAHILI] |
| detector = LanguageDetectorBuilder.from_languages(*languages).build() |
| detected_language = detector.detect_language_of(text) |
| return "sw" if detected_language == Language.SWAHILI else "en" |
| except Exception as e: |
| logging.warning(f"Language detection error (Lingua): {e}") |
| return "unknown" |
|
|
|
|
| def detect_intention(user_input, client): |
| system_prompt = """ |
| You are an intent classification assistant. Classify the user's message into one of the following categories: |
| |
| - "greeting" for messages like "hi", "hello", or similar |
| - "acknowledgment" for messages like "thanks", "okay", or similar |
| - "message" for anything else that may require a response, including health concerns or information requests |
| |
| The user may speak in English or Swahili. Be aware that they might not use proper punctuation or grammar. |
| |
| Return only the label: "greeting", "acknowledgment", or "message". |
| """ |
|
|
| user_message = f"Message: \"{user_input}\"" |
|
|
| completion = client.chat.completions.create( |
| model="gpt-3.5-turbo", |
| messages=[ |
| {"role": "system", "content": system_prompt}, |
| {"role": "user", "content": user_message} |
| ], |
| temperature=0 |
| ) |
|
|
| return completion.choices[0].message.content |
|
|
| def convert_to_date(date_str, datetime): |
| """Convert date string in YYYYMMDD format to YYYY-MM-DD.""" |
| try: |
| return datetime.strptime(date_str, "%Y%m%d").strftime("%Y-%m-%d") |
| except ValueError: |
| return "Unknown Date" |
