added really good token checking

This commit is contained in:
Falko Victor Habel 2024-10-16 09:26:14 +02:00
parent c3e66c64c1
commit 06d91153a2
4 changed files with 8 additions and 5 deletions

2
.gitignore vendored
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@ -155,7 +155,7 @@ cython_debug/
#ML #ML
VeraMind-Mini/ VeraMind-Mini/
Token.py Token.txt
# OS generated files # # OS generated files #
###################### ######################

0
Token/.gitignore vendored Normal file
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@ -1,11 +1,15 @@
from langchain_community.llms import Ollama from langchain_community.llms import Ollama
from Ai.Token import get_token
class ArticleRater: class ArticleRater:
def __init__(self): def __init__(self):
self.client = "https://ai.fabelous.app/v1/ollama/generic" self.client = "https://ai.fabelous.app/v1/ollama/generic"
self.headers = {"Authorization": f"Token {get_token()}"} self.token = self._get_token()
self.headers = {"Authorization": f"Token {self.token}"}
def _get_token(self):
with open("Token/Token.txt", "r") as t:
return t.readline().strip()
def get_response(self, article, result, confidence): def get_response(self, article, result, confidence):
ollama_params = { ollama_params = {
"base_url": self.client, "base_url": self.client,

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@ -7,7 +7,6 @@ from utils.database.database import FakeNewsChecker
from models.provider import Provider from models.provider import Provider
from collections import Counter from collections import Counter
from Ai.llm import ArticleRater from Ai.llm import ArticleRater
from Ai.Token import get_token
class MainFrameController: class MainFrameController:
@ -63,7 +62,7 @@ class MainFrameController:
confidence_color = "green" if confidence > 80 else ("orange" if confidence > 50 else "red") confidence_color = "green" if confidence > 80 else ("orange" if confidence > 50 else "red")
self.frame.confidence_label.configure(fg_color=confidence_color) self.frame.confidence_label.configure(fg_color=confidence_color)
if get_token().strip(): if self.rater.token:
response_stream = self.rater.get_response(text_data.text, text_data.result, confidence) response_stream = self.rater.get_response(text_data.text, text_data.result, confidence)
for chunk in response_stream: for chunk in response_stream: