Add files via upload

waifu/anilistpart.py

@@ -0,0 +1,114 @@
+import requests
+import re
+
+
+class AnilistHandler:
+    def __init__(self):
+        self.url = 'https://graphql.anilist.co'
+
+    def strip_html_tags(self, text):
+        clean = re.compile('<.*?>')
+        return re.sub(clean, '', text)
+
+    def get_anime_description(self, name):
+        query = '''
+        query ($name: String!) {
+            Media(search: $name, type: ANIME) {
+                description
+            }
+        }
+        '''
+        variables = {'name': name}
+        response = requests.post(self.url, json={'query': query, 'variables': variables})
+        if response.status_code == 200:
+            data = response.json()
+            description = data.get('data', {}).get('Media', {}).get('description', 'No description available')
+            return self.strip_html_tags(description)
+        else:
+            return f"Error fetching anime description: {response.status_code}"
+
+    def get_manga_description(self, name):
+        query = '''
+        query ($name: String!) {
+            Media(search: $name, type: MANGA) {
+                description
+            }
+        }
+        '''
+        variables = {'name': name}
+        response = requests.post(self.url, json={'query': query, 'variables': variables})
+        if response.status_code == 200:
+            data = response.json()
+            description = data.get('data', {}).get('Media', {}).get('description', 'No description available')
+            return self.strip_html_tags(description)
+        else:
+            return f"Error fetching manga description: {response.status_code}"
+
+    def get_character_description(self, name):
+        query = '''
+        query ($name: String!) {
+            Character(search: $name) {
+                description
+            }
+        }
+        '''
+        variables = {'name': name}
+        response = requests.post(self.url, json={'query': query, 'variables': variables})
+        if response.status_code == 200:
+            data = response.json()
+            description = data.get('data', {}).get('Character', {}).get('description', 'No description available')
+            return self.strip_html_tags(description)
+        else:
+            return f"Error fetching character description: {response.status_code}"
+
+    def get_anime_details(self, name):
+        query = '''
+        query ($name: String!) {
+            Media(search: $name, type: ANIME) {
+                description
+                averageScore
+                status
+            }
+        }
+        '''
+        variables = {'name': name}
+        response = requests.post(self.url, json={'query': query, 'variables': variables})
+        if response.status_code == 200:
+            data = response.json()
+            details = data.get('data', {}).get('Media', {})
+            description = details.get('description', 'No description available')
+            average_score = details.get('averageScore', 'No average score available')
+            status = details.get('status', 'No status available')
+            return {
+                'description': self.strip_html_tags(description),
+                'averageScore': average_score,
+                'status': status
+            }
+        else:
+            return f"Error fetching anime details: {response.status_code}"
+
+    def get_manga_details(self, name):
+        query = '''
+        query ($name: String!) {
+            Media(search: $name, type: MANGA) {
+                description
+                averageScore
+                status
+            }
+        }
+        '''
+        variables = {'name': name}
+        response = requests.post(self.url, json={'query': query, 'variables': variables})
+        if response.status_code == 200:
+            data = response.json()
+            details = data.get('data', {}).get('Media', {})
+            description = details.get('description', 'No description available')
+            average_score = details.get('averageScore', 'No average score available')
+            status = details.get('status', 'No status available')
+            return {
+                'description': self.strip_html_tags(description),
+                'averageScore': average_score,
+                'status': status
+            }
+        else:
+            return f"Error fetching manga details: {response.status_code}"

waifu/apicode.py

@@ -0,0 +1,20 @@
+token = '' # add your discord token
+
+aiclient =('') # Add your c.ai API key here
+
+channel_id = ''
+
+lama=""
+
+
+#1292207460131667969
+#1264627297411924140
+
+
+# if you dont knoe how to
+
+# for discord watch this one = https://www.youtube.com/watch?v=dR9n1zmw-Go
+
+# for c.ai look this one = https://github.com/kramcat/CharacterAI
+
+# lama or anymodel used is from  https://openrouter.ai

waifu/imagetotext.py

@@ -0,0 +1,51 @@
+from transformers import BlipProcessor, BlipForConditionalGeneration
+from PIL import Image
+import torch
+import os
+
+class ImageCaptioning:
+    def __init__(self):
+        # Load pre-trained processor and model for image captioning
+        self.processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+        self.model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
+        self.supported_extensions = (".jpg", ".jpeg", ".png", ".bmp", ".gif", ".tiff")
+
+    def load_image(self, image_path):
+        # Check if the file exists and has a supported extension
+        if not os.path.exists(image_path):
+            print("File does not exist. Please provide a valid file path.")
+            return None
+
+        if not image_path.lower().endswith(self.supported_extensions):
+            print("Unsupported file type. Please provide an image with a supported extension.")
+            return None
+
+        try:
+            # Open the image file
+            image = Image.open(image_path)
+            return image
+        except Exception as e:
+            print(f"Error loading image: {e}")
+            return None
+
+    def generate_caption(self, image_path):
+        # Load the image
+        image = self.load_image(image_path)
+        if image is None:
+            return None
+
+        # Convert the image to RGB mode if it's not already
+        if image.mode != "RGB":
+            image = image.convert("RGB")
+
+        # Preprocess the image for the BLIP model
+        inputs = self.processor(image, return_tensors="pt")
+
+        # Perform inference (Image Captioning)
+        with torch.no_grad():
+            generated_ids = self.model.generate(**inputs)
+
+        # Decode the generated caption
+        generated_caption = self.processor.decode(generated_ids[0], skip_special_tokens=True)
+
+        return generated_caption