update: look at todo

.github/TODO.md

@@ -1,2 +1,4 @@
-- Get package to use .env from django
+- [ ] make frontend
+- [ ] find better way of using .env from django (possibly)
+- [x] Get package to use .env from django
 - [x] IMP IMP work on API_KEY fixing config or use .env

Makefile

@@ -123,9 +123,17 @@ pytestcache-remove:
 pytestcache-remove:
 	find . | grep -E ".log" | xargs rm -rf
 
+.PHONY: env-remove
+pytestcache-remove:
+	find . | grep -E ".env" | xargs rm -rf
+
+.PHONY: env-fishremove
+pytestcache-remove:
+	find . | grep -E ".env-fish" | xargs rm -rf
+
 .PHONY: build-remove
 build-remove:
 	rm -rf build/
 
 .PHONY: cleanup
-cleanup: pycache-remove dsstore-remove mypycache-remove ipynbcheckpoints-remove pytestcache-remove pkl-remove log-remove
+cleanup: pycache-remove dsstore-remove mypycache-remove ipynbcheckpoints-remove pytestcache-remove pkl-remove log-remove env-remove env-fishremove

internet_ml/NLP/no_context/QA.py

@@ -8,8 +8,6 @@ from pathlib import Path
 import dotenv
 from transformers import pipeline
 
-dotenv.load_dotenv()
-
 logging.basicConfig(
     filename="QA.log",
     filemode="w",
@@ -27,8 +25,6 @@ def answer(
     query: str, GOOGLE_SEARCH_API_KEY: str, GOOGLE_SEARCH_ENGINE_ID: str
 ) -> tuple[Any, list[str]]:
     QA_MODEL: Any = pipeline("question-answering")
-    # GOOGLE_SEARCH_API_KEY = str(os.getenv("INTERNET_ML_GOOGLE_API"))
-    # GOOGLE_SEARCH_ENGINE_ID = str(os.getenv("INTERNET_ML_GOOGLE_SEARCH_ENGINE_ID"))
     results: tuple[list[str], list[str]] = internet.Google(
         query, GOOGLE_SEARCH_API_KEY, GOOGLE_SEARCH_ENGINE_ID
     ).google()
@@ -41,6 +37,6 @@ def answer(
     return answer
 
 
-# print(answer("Who is the author of TinTin?"))
-
+# print(os.environ)
+# print(answer("Who is Elon Musk?"))
 # def custom_answer

internet_ml/tools/NLP/data/internet.py

@@ -9,11 +9,6 @@ from pathlib import Path
 import dotenv
 import requests
 
-dotenv.load_dotenv()
-
-# GOOGLE_SEARCH_API_KEY = str(os.environ["INTERNET_ML_GOOGLE_API"])
-# GOOGLE_SEARCH_ENGINE_ID = str(os.environ["INTERNET_ML_GOOGLE_SEARCH_ENGINE_ID"])
-
 HTTP_USERAGENT: dict[str, str] = {
     "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3"
 }
@@ -54,6 +49,20 @@ class Google:
     ) -> None:
         self.__GOOGLE_SEARCH_API_KEY: str = GOOGLE_SEARCH_API_KEY
         self.__GOOGLE_SEARCH_ENGINE_ID: str = GOOGLE_SEARCH_ENGINE_ID
+        # dotenv_path = os.path.join(os.path.dirname(__file__), '.env')
+        # dotenv.load_dotenv(dotenv_path)
+        # self.__GOOGLE_SEARCH_API_KEY: str = ""
+        # self.__GOOGLE_SEARCH_ENGINE_ID: str = ""
+        # if (
+        #     "INTERNET_ML_GOOGLE_API" in os.environ
+        #     and "INTERNET_ML_GOOGLE_SEARCH_ENGINE_ID" in os.environ
+        # ):
+        #     self.__GOOGLE_SEARCH_API_KEY = str(os.environ.get("INTERNET_ML_GOOGLE_API"))
+        #     self.__GOOGLE_SEARCH_ENGINE_ID = str(
+        #         os.environ.get("INTERNET_ML_GOOGLE_SEARCH_ENGINE_ID")
+        #     )
+        # else:
+        #     exit("API KEYS")
         self.__num_res: int = (
             5
             if config.NLP_CONF_MODE == "speed"
@@ -62,8 +71,12 @@ class Google:
         self.__query = query
         self.__URL_EXTRACTOR: URLExtract = URLExtract()
         self.__urls: list[str] = self.__URL_EXTRACTOR.find_urls(query)
-        self.__query = re.sub(
-            r"\w+:\/{2}[\d\w-]+(\.[\d\w-]+)*(?:(?:\/[^\s/]*))*", "", self.__query
+        self.__query = str(
+            re.sub(
+                r"\w+:\/{2}[\d\w-]+(\.[\d\w-]+)*(?:(?:\/[^\s/]*))*",
+                "",
+                str(self.__query),
+            )
         )
 
     def __get_urls(self: "Google") -> None:
@@ -152,10 +165,6 @@ class Google:
         return (self.__content, self.__urls)
 
 
-# def google(query: str) -> tuple[list[str], list[str]]:
-# return Google(query).google()
-
-
 """
 Timing:
 import time

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "internet-ml"
-version = "1.0.6"
+version = "1.0.20"
 description = "Internet-ML: Allowing ML to connect to the internet"
 readme = "./.github/README.md"
 authors = ["Thamognya Kodi <contact@thamognya.com>"]

web/internet_ml_server/api/nlp/nocontext/tests.py

@@ -1,3 +0,0 @@
-from django.test import TestCase
-
-# Create your tests here.

web/internet_ml_server/api/nlp/nocontext/tools/question_answer.py

@@ -1,25 +0,0 @@
-from typing import Any
-
-import json
-
-import internet_ml.NLP.no_context.QA
-
-
-def QA(
-    query: str, INTERNET_ML_GOOGLE_API: str, INTERNET_ML_GOOGLE_SEARCH_ENGINE_ID: str
-) -> Any:
-    try:
-        answer = internet_ml.NLP.no_context.QA.answer(
-            query, INTERNET_ML_GOOGLE_API, INTERNET_ML_GOOGLE_SEARCH_ENGINE_ID
-        )
-        content = json.dumps(
-            {"error": "", "response": answer[0], "resources": answer[1]}
-        )
-    except:
-        content = json.dumps(
-            {"error": "Google API key not present in .env or environment"}
-        )
-    return content
-
-
-# print(QA("Who is Elon Musk?"))

web/internet_ml_server/api/nlp/nocontext/views.py

@@ -1,19 +1,18 @@
-import json
 import os
 
-from dotenv import load_dotenv
+import dotenv
 from rest_framework import status
 from rest_framework.response import Response
 from rest_framework.views import APIView
 
-from .tools import question_answer
-
-load_dotenv()
 import internet_ml.NLP.no_context.QA
 
+dotenv_path = os.path.join(os.path.dirname(__file__), ".env")
+dotenv.load_dotenv(dotenv_path)
+
 
 class QAView(APIView):
-    def post(self, request, format=None):
+    def post(self, request):
         """
         {"question": "Who is Elon Musk?"}
         {
@@ -37,11 +36,14 @@ class QAView(APIView):
         so check error if it exists first and then for other stuff
         """
         answer = internet_ml.NLP.no_context.QA.answer(
-            request.POST.get("question"),
-            str(os.getenv("INTERNET_ML_GOOGLE_API")),
-            str(os.getenv("INTERNET_ML_GOOGLE_SEARCH_ENGINE_ID")),
+            str(request.data["question"]),
+            str(os.environ.get("INTERNET_ML_GOOGLE_API")),
+            str(os.environ.get("INTERNET_ML_GOOGLE_SEARCH_ENGINE_ID")),
         )
-        content = json.dumps(
-            {"error": "", "response": answer[0], "resources": answer[1]}
-        )
-        return content
+        content = {
+            "error": "",
+            "question": str(request.data["question"]),
+            "response": answer[0],
+            "resources": answer[1],
+        }
+        return Response(content)

web/internet_ml_server/pyproject.toml

@@ -17,6 +17,7 @@ django-stubs = "^1.13.1"
 djangorestframework = "^3.14.0"
 python-dotenv = "^0.21.0"
 django-environ = "^0.9.0"
+internet-ml = "^1.0.11"
 
 [tool.mypy]
 plugins = ["mypy_django_plugin.main"]