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| from flask import Flask,request,make_response | |
| import os | |
| import logging | |
| from dotenv import load_dotenv | |
| from heyoo import WhatsApp | |
| import assemblyai as aai | |
| import openai | |
| from utility import parse_multiple_transactions | |
| # load env data | |
| load_dotenv() | |
| # messenger object | |
| messenger = WhatsApp( | |
| os.environ["whatsapp_token"], | |
| phone_number_id=os.environ["phone_number_id"] ) | |
| # aai.settings.api_key = os.environ["aai_key"] | |
| # transcriber = aai.Transcriber() | |
| # Authenticate to Firesotre with the JSON account key | |
| # db = firestore.Client.from_service_account_json("firestore-key.json") | |
| app = Flask(__name__) | |
| VERIFY_TOKEN = "30cca545-3838-48b2-80a7-9e43b1ae8ce4" | |
| client = openai.OpenAI( | |
| api_key=os.environ.get("sambanova_api_key"), | |
| base_url="https://api.sambanova.ai/v1", | |
| ) | |
| def generateResponse(prompt): | |
| #----- Call API to classify and extract relevant transaction information | |
| # These templates help provide a unified response format for use as context clues when | |
| # parsing the AI generated response into a structured data format | |
| relevant_info_template = """ | |
| Intent: The CRUD operation | |
| Transaction Type: The type of transaction | |
| Details: as a sublist of the key details like name of item, amount, description, among other details you are able to extract. | |
| """ | |
| sample_response_template = """ | |
| The information provided indicates that you want to **create/record** a new transaction. | |
| **Extracted Information**: | |
| **Intent**: Create | |
| Transaction 1: | |
| **Transaction Type**: Purchase | |
| **Details**: | |
| - Item: Car | |
| - Purpose: Business | |
| - Amount: 1000 | |
| - Tax: 200 | |
| - Note: A new car for business | |
| Transaction 2: | |
| **Transaction Type**: Expense | |
| **Details**: | |
| - Item: Office Chair | |
| - Amount: 300 USD | |
| - Category: Furniture | |
| """ | |
| response = client.chat.completions.create( | |
| model='Meta-Llama-3.1-70B-Instruct', | |
| messages=[ | |
| {"role": "system", "content": f"You are a helpful assistant that classifies transactions written in natural language into CRUD operations (Create, Read, Update, and Delete) and extracts relevant information. Format the relevant information extracted from the transaction text in this format: {relevant_info_template}. You can use markdown syntax to present a nicely formated and readable response to the user, but make sure the user does not see the markdown keyword. Keywords and field names must be in bold face. A sample response could look like this: {sample_response_template}. Delineate multiple transactions with the label 'Transaction 1' before the start of the relevant information for each transaction. There should be only one intent even in the case of multiple transactions."}, | |
| {"role": "user", "content": prompt} | |
| ] | |
| ) | |
| #----- Process response | |
| try: | |
| response = response.choices[0].message.content | |
| except Exception as e: | |
| print(f'An error occurred: {str(e)}') | |
| response = None | |
| return response | |
| def respond(query_str:str): | |
| response = "hello, I don't have a brain yet" | |
| return response | |
| def hook(): | |
| if request.method == "GET": | |
| if request.args.get("hub.verify_token") == VERIFY_TOKEN: | |
| logging.info("Verified webhook") | |
| response = make_response(request.args.get("hub.challenge"), 200) | |
| response.mimetype = "text/plain" | |
| return response | |
| logging.error("Webhook Verification failed") | |
| return "Invalid verification token" | |
| # get message update.. | |
| data = request.get_json() | |
| changed_field = messenger.changed_field(data) | |
| if changed_field == "messages": | |
| new_message = messenger.get_mobile(data) | |
| if new_message: | |
| mobile = messenger.get_mobile(data) | |
| message_type = messenger.get_message_type(data) | |
| if message_type == "text": | |
| message = messenger.get_message(data) | |
| # Handle greetings | |
| if message.lower() in ("hi", "hello", "help", "how are you"): | |
| response = "Hi there! My name is BuzyHelper. How can I help you today?" | |
| messenger.send_message(message=f"{response}",recipient_id=mobile) | |
| else: | |
| response = str(generateResponse(message)) | |
| # Parse AI generated response into a structured format | |
| parsed_trans_data = parse_multiple_transactions(response) | |
| print("Response:", response) | |
| logging.info(f"\nAnswer: {response}\n") | |
| # Handle cases where response is not a valid image path | |
| messenger.send_message(message=f"{response}\n\n {parsed_trans_data}", recipient_id=mobile) | |
| # elif message_type == "audio": | |
| # audio = messenger.get_audio(data) | |
| # audio_id, mime_type = audio["id"], audio["mime_type"] | |
| # audio_url = messenger.query_media_url(audio_id) | |
| # audio_filename = messenger.download_media(audio_url, mime_type) | |
| # transcript =transcriber.transcribe(audio_filename) | |
| # print(audio_filename) | |
| # print(transcript.text) | |
| # res = transcript.text | |
| # logging.info(f"\nAudio: {audio}\n") | |
| # response = str(generateResponse(res)) | |
| # if isinstance(response, str): | |
| # messenger.send_message(message=f"{response}", recipient_id=mobile) | |
| # elif isinstance(response, str) and os.path.isfile(response): | |
| # messenger.send_image(image_path=response, recipient_id=mobile) | |
| else: | |
| messenger.send_message(message="Please send me text or audio messages",recipient_id=mobile) | |
| return "ok" | |
| if __name__ == '__main__': | |
| app.run(debug=True,host="0.0.0.0", port=7860) |