refactor: encapsulated methods to a single doctype - AutoInscribe Int…

…egration

autoinscribe/autoinscribe/doctype/autoinscribe_integration/autoinscribe_integration.js

@@ -0,0 +1,8 @@
+// Copyright (c) 2024, RedSoft Solutions Pvt. Ltd. and contributors
+// For license information, please see license.txt
+
+// frappe.ui.form.on("AutoInscribe Integration", {
+// 	refresh(frm) {
+
+// 	},
+// });

autoinscribe/autoinscribe/doctype/autoinscribe_integration/autoinscribe_integration.json

@@ -0,0 +1,40 @@
+{
+ "actions": [],
+ "allow_rename": 1,
+ "creation": "2024-01-05 10:45:27.907271",
+ "doctype": "DocType",
+ "engine": "InnoDB",
+ "field_order": [
+  "section_break_ozge"
+ ],
+ "fields": [
+  {
+   "fieldname": "section_break_ozge",
+   "fieldtype": "Section Break"
+  }
+ ],
+ "index_web_pages_for_search": 1,
+ "issingle": 1,
+ "links": [],
+ "modified": "2024-01-05 10:45:39.174023",
+ "modified_by": "Administrator",
+ "module": "AutoInscribe",
+ "name": "AutoInscribe Integration",
+ "owner": "Administrator",
+ "permissions": [
+  {
+   "create": 1,
+   "delete": 1,
+   "email": 1,
+   "print": 1,
+   "read": 1,
+   "role": "System Manager",
+   "share": 1,
+   "write": 1
+  }
+ ],
+ "sort_field": "modified",
+ "sort_order": "DESC",
+ "states": [],
+ "track_changes": 1
+}

autoinscribe/autoinscribe/doctype/autoinscribe_integration/autoinscribe_integration.py

@@ -0,0 +1,112 @@
+# Copyright (c) 2024, RedSoft Solutions Pvt. Ltd. and contributors
+# For license information, please see license.txt
+
+import frappe
+from frappe.model.document import Document
+import base64
+import requests
+from openai import OpenAI
+from google.cloud import vision
+from google.oauth2 import service_account
+
+# autoinscribe_settings = frappe.get_doc("AutoInscribe Settings").as_dict()
+
+class AutoInscribeIntegration(Document):
+	'''Encapsulates a set of methods used to make external calls to OpenAI API & Google Vision API'''
+
+	def get_openai_gpt_key(self):
+		'''Returns decrypted OpenAI API key from AutoInscribe Settings'''
+
+		return frappe.get_single("AutoInscribe Settings").get_password('openai_gpt_key')
+
+	def get_vision_client_email(self):
+		'''Returns Vision Client Email from AutoInscribe Settings'''
+
+		return frappe.get_single("AutoInscribe Settings").as_dict()["vision_client_email"]
+
+	def get_vision_project_id(self):
+		'''Returns Vision Project ID from AutoInscribe Settings'''
+
+		return frappe.get_single("AutoInscribe Settings").as_dict()["vision_project_id"]
+
+	def get_vision_token_uri(self):
+		'''Returns Vision Token URI from AutoInscribe Settings'''
+
+		return frappe.get_single("AutoInscribe Settings").as_dict()["vision_token_uri"]
+
+	def ask_gpt(self, prompt):
+		'''Returns response from OpenAI API given a prompt'''
+
+		try:
+			gpt_client = OpenAI(api_key=self.get_openai_gpt_key())
+			chat_completion = gpt_client.chat.completions.create(
+				messages=[
+					{
+						"role": "user",
+						"content": prompt,
+					}
+				],
+				model="gpt-3.5-turbo-1106",
+			)
+			return chat_completion.choices[0].message.content.strip()
+		except Exception as e:
+			frappe.throw("Please enter a valid OpenAI API key in AutoInscribe Settings")
+
+	def extract_text_from_img(self, img_url):
+		'''Extracts and returns first_name, middle_name, last_name, gender, salutation, designation contact_numbers, email_ids, company_name, website, address, mobile_number, phone_number, city, state and country from an image given the image URL'''
+
+		try:
+			credentials = service_account.Credentials.from_service_account_info({
+				"type": "service_account",
+				"project_id": self.get_vision_project_id(),
+				"private_key": frappe.conf["vision_private_key"],
+				"client_email": self.get_vision_client_email(),
+				"token_uri": self.get_vision_token_uri(),
+			})
+			response = requests.get(img_url)
+			# Encode the image content to base64
+			base64_img = base64.b64encode(response.content).decode('utf-8')
+			client = vision.ImageAnnotatorClient(credentials=credentials)
+			img_data = base64.b64decode(base64_img)
+			# Create an image object
+			image = vision.Image(content=img_data)
+			# Perform OCR on the image
+			response = client.text_detection(image=image)
+			texts = response.text_annotations
+		except Exception as e:
+			frappe.throw("Please check your AutoInscribe Settings and try again")
+		# Extracting detected text
+		if texts:
+			detected_text = texts[0].description
+			prompt = f"From the following text, identify the first_name, middle_name, last_name, gender, salutation, designation contact_numbers, email_ids, company_name, website, address, mobile_number, phone_number, city, state, country: {detected_text}. Output must be a string containing one key-value pair per line and for absence of values use 'NULL' for value as placeholder. contact_numbers and email_ids must be comma-separated if there are multiple. Guess the salutation and gender. gender can be Male, Female, Transgender or Other. phone_number must be the telephone number whereas mobile_number must be the mobile number. country must have the value as full country name, e.g, US becomes United States, UK becomes United Kingdom."
+			reply = self.ask_gpt(prompt)
+			return reply
+		else:
+			return "No text detected"
+
+	def create_address(self, address):
+		'''Given an address string, extract city, state, postal_code, country and create an address if country exists & return the inserted doc. Return None otherwise.'''
+
+		prompt = f"From the following address text, identify city, state, country and postal_code: {address}. Output must be a string containing one key-value pair per line and for absence of values use 'NULL'. country must have the value as full country name, e.g, US becomes United States, UK becomes United Kingdom"
+		reply = self.ask_gpt(prompt)
+		addr_lines = reply.strip().splitlines()
+		city = addr_lines[0].split(':')[1].strip()
+		state = addr_lines[1].split(':')[1].strip()
+		postal_code = addr_lines[3].split(':')[1].strip()
+		country = addr_lines[2].split(':')[1].strip()
+		country_exists = frappe.db.exists("Country", {"country_name": country})
+		if country_exists:
+			doc = frappe.get_doc({
+					"doctype": "Address",
+					"address_title": address,
+					"address_type": "Office",
+					"address_line1": address,
+					"city": city if city != "NULL" else None,
+					"state": state if state != "NULL" else None,
+					"country": country,
+					"pincode": postal_code if postal_code != "NULL" else None,
+			})
+			doc.insert()
+			return doc
+		else:
+			return None

autoinscribe/autoinscribe/doctype/autoinscribe_integration/test_autoinscribe_integration.py

@@ -0,0 +1,9 @@
+# Copyright (c) 2024, RedSoft Solutions Pvt. Ltd. and Contributors
+# See license.txt
+
+# import frappe
+from frappe.tests.utils import FrappeTestCase
+
+
+class TestAutoInscribeIntegration(FrappeTestCase):
+	pass

autoinscribe/fixtures/server_script.json

@@ -0,0 +1,21 @@
+[
+ {
+  "allow_guest": 0,
+  "api_method": null,
+  "cron_format": null,
+  "disabled": 0,
+  "docstatus": 0,
+  "doctype": "Server Script",
+  "doctype_event": "Before Save",
+  "enable_rate_limit": 0,
+  "event_frequency": "All",
+  "modified": "2024-01-05 14:32:56.543165",
+  "module": "AutoInscribe",
+  "name": "AutoInscribe Contact Error",
+  "rate_limit_count": 5,
+  "rate_limit_seconds": 86400,
+  "reference_doctype": "Contact",
+  "script": "if doc.custom_upload_image and not doc.first_name:\n    frappe.msgprint(\"Please check your AutoInscribe Settings and try again\", title=\"Invalid AutoInscribe Settings\", indicator=\"red\")\n",
+  "script_type": "DocType Event"
+ }
+]

autoinscribe/hooks.py

@@ -230,6 +230,7 @@
 fixtures = [
     {
         "doctype": "Client Script",
+        "doctype": "Server Script",
     },
     {
         "dt": "Custom Field",

autoinscribe/inscribe/api.py

@@ -1,118 +1,15 @@
-'''A set of methods used to make API calls to OpenAI & Google Vision API'''
+'''Responsible for calling methods in doctype class "AutoInscribe Integration"'''
 
 import frappe
-import base64
-import requests
-from openai import OpenAI
-from google.cloud import vision
-from google.oauth2 import service_account
-
-autoinscribe_settings = frappe.get_doc("AutoInscribe Settings").as_dict()
-
-def get_openai_gpt_key():
-    '''Returns decrypted OpenAI API key from AutoInscribe Settings'''
-    return frappe.get_single("AutoInscribe Settings").get_password('openai_gpt_key')
-
-
-def get_vision_client_email():
-    '''Returns Vision Client Email from AutoInscribe Settings'''
-    return autoinscribe_settings["vision_client_email"]
-
-
-def get_vision_project_id():
-    '''Returns Vision Project ID from AutoInscribe Settings'''
-    return autoinscribe_settings["vision_project_id"]
-
-
-def get_vision_token_uri():
-    '''Returns Vision Token URI from AutoInscribe Settings'''
-    return autoinscribe_settings["vision_token_uri"]
-
-
-credentials = service_account.Credentials.from_service_account_info({
-  "type": "service_account",
-  "project_id": get_vision_project_id(),
-  "private_key": frappe.conf["vision_private_key"],
-  "client_email": get_vision_client_email(),
-  "token_uri": get_vision_token_uri(),
-})
-
-
-@frappe.whitelist()
-def ask_gpt(prompt):
-    '''Returns response from OpenAI API given a prompt'''
-    try:
-        gpt_client = OpenAI(api_key=get_openai_gpt_key())
-        chat_completion = gpt_client.chat.completions.create(
-            messages=[
-                {
-                    "role": "user",
-                    "content": prompt,
-                }
-            ],
-            model="gpt-3.5-turbo-1106",
-        )
-        return chat_completion.choices[0].message.content.strip()
-    except Exception as e:
-        frappe.throw("Please enter a valid OpenAI API key in AutoInscribe Settings")
-
-
-@frappe.whitelist()
-def get_gpt_task(**args):
-    '''Returns task subject & description as a response from OpenAI API given task details'''
-    task_details = args.get('task_details')
-    prompt = f"You are an assistant that is responsible for generating the Subject and Details of the following task: {task_details}. Subject must be a string that gives an overview of the task. Details must be a formatted HTML body that describes that task."
-    reply = ask_gpt(prompt)
-    return reply
 
+doc = frappe.get_single("AutoInscribe Integration")
 
 @frappe.whitelist()
 def extract_text_from_img(img_url):
-    '''Extracts and returns first_name, middle_name, last_name, gender, salutation, designation contact_numbers, email_ids, company_name, website, address, mobile_number, phone_number, city, state and country from an image given the image URL'''
-    response = requests.get(img_url)
-    # Encode the image content to base64
-    base64_img = base64.b64encode(response.content).decode('utf-8')
-    client = vision.ImageAnnotatorClient(credentials=credentials)
-    img_data = base64.b64decode(base64_img)
-    # Create an image object
-    image = vision.Image(content=img_data)
-    # Perform OCR on the image
-    response = client.text_detection(image=image)
-    texts = response.text_annotations
-    # Extracting detected text
-    if texts:
-        detected_text = texts[0].description
-        prompt = f"From the following text, identify the first_name, middle_name, last_name, gender, salutation, designation contact_numbers, email_ids, company_name, website, address, mobile_number, phone_number, city, state, country: {detected_text}. Output must be a string containing one key-value pair per line and for absence of values use 'NULL' for value as placeholder. contact_numbers and email_ids must be comma-separated if there are multiple. Guess the salutation and gender. gender can be Male, Female, Transgender or Other. phone_number must be the telephone number whereas mobile_number must be the mobile number. country must have the value as full country name, e.g, US becomes United States, UK becomes United Kingdom."
-        reply = ask_gpt(prompt)
-        return reply
-    else:
-        return "No text detected"
+    return doc.extract_text_from_img(img_url)
 
 
 @frappe.whitelist()
 def create_address(address):
-    '''Given an address string, extract city, state, postal_code, country and create an address if country exists & return the inserted doc. Return False otherwise.'''
-    prompt = f"From the following address text, identify city, state, country and postal_code: {address}. Output must be a string containing one key-value pair per line and for absence of values use 'NULL'. country must have the value as full country name, e.g, US becomes United States, UK becomes United Kingdom"
-    reply = ask_gpt(prompt)
-    addr_lines = reply.strip().splitlines()
-    city = addr_lines[0].split(':')[1].strip()
-    state = addr_lines[1].split(':')[1].strip()
-    postal_code = addr_lines[3].split(':')[1].strip()
-    country = addr_lines[2].split(':')[1].strip()
-    country_exists = frappe.db.exists("Country", {"country_name": country})
-    if country_exists:
-        doc = frappe.get_doc({
-                "doctype": "Address",
-                "address_title": address,
-                "address_type": "Office",
-                "address_line1": address,
-                "city": city if city != "NULL" else None,
-                "state": state if state != "NULL" else None,
-                "country": country,
-                "pincode": postal_code if postal_code != "NULL" else None,
-        })
-        doc.insert()
-        return doc
-    else:
-        return False
+    return doc.create_address(address)