zephyr

requirements.txt

@@ -11,6 +11,7 @@ playwright
 wget==3.2
 simpleaichat
 httpx
+torch
 ggl
 beautifulsoup4
 google-search-results==2.4.2

swarms/models/__init__.py

@@ -8,3 +8,4 @@ from swarms.models.openai_models import OpenAI, AzureOpenAI, OpenAIChat
 from swarms.models.idefics import Idefics
 from swarms.models.kosmos_two import Kosmos
 from swarms.models.vilt import Vilt
+from swarms.models.zephyr import Zephyr

swarms/models/bing_chat.py

@@ -1,10 +1,11 @@
 """EdgeGPT model by OpenAI"""
 import asyncio
 import json
+from pathlib import Path
+
 from EdgeGPT.EdgeGPT import Chatbot, ConversationStyle
-from EdgeGPT.EdgeUtils import ImageQuery, Query, Cookie
+from EdgeGPT.EdgeUtils import Cookie, ImageQuery, Query
 from EdgeGPT.ImageGen import ImageGen
-from pathlib import Path
 
 
 class BingChat:
@@ -28,22 +29,14 @@ class BingChat:
         self.cookies = json.loads(open(cookies_path, encoding="utf-8").read())
         self.bot = asyncio.run(Chatbot.create(cookies=self.cookies))
 
-    def __call__(
-        self, prompt: str, style: ConversationStyle = ConversationStyle.creative
-    ) -> str:
+    def __call__(self, prompt: str, style: ConversationStyle = ConversationStyle.creative) -> str:
         """
         Get a text response using the EdgeGPT model based on the provided prompt.
         """
-        response = asyncio.run(
-            self.bot.ask(
-                prompt=prompt, conversation_style=style, simplify_response=True
-            )
-        )
-        return response["text"]
+        response = asyncio.run(self.bot.ask(prompt=prompt, conversation_style=style, simplify_response=True))
+        return response['text']
 
-    def create_img(
-        self, prompt: str, output_dir: str = "./output", auth_cookie: str = None
-    ) -> str:
+    def create_img(self, prompt: str, output_dir: str = "./output", auth_cookie: str = None) -> str:
         """
         Generate an image based on the provided prompt and save it in the given output directory.
         Returns the path of the generated image.
@@ -55,7 +48,7 @@ class BingChat:
         images = image_generator.get_images(prompt)
         image_generator.save_images(images, output_dir=output_dir)
 
-        return Path(output_dir) / images[0]["path"]
+        return Path(output_dir) / images[0]['path']
 
     @staticmethod
     def set_cookie_dir_path(path: str):

swarms/models/idefics.py

@@ -87,7 +87,8 @@ class Idefics:
             prompts : list
                 A list of prompts. Each prompt is a list of text strings and images.
             batched_mode : bool, optional
-                Whether to process the prompts in batched mode. If True, all prompts are processed together. If False, only the first prompt is processed (default is True).
+                Whether to process the prompts in batched mode. If True, all prompts are 
+                processed together. If False, only the first prompt is processed (default is True).
 
         Returns
         -------
@@ -130,7 +131,9 @@ class Idefics:
             prompts : list
                 A list of prompts. Each prompt is a list of text strings and images.
             batched_mode : bool, optional
-                Whether to process the prompts in batched mode. If True, all prompts are processed together. If False, only the first prompt is processed (default is True).
+                Whether to process the prompts in batched mode. 
+                If True, all prompts are processed together. 
+                If False, only the first prompt is processed (default is True).
 
         Returns
         -------

swarms/models/zephyr.py

@@ -0,0 +1,53 @@
+"""Zephyr by HF"""
+import torch 
+from transformers import pipeline
+
+
+
+class Zephyr:
+    """
+    Zehpyr model from HF
+
+
+    Args:
+
+
+
+    Usage:
+    >>> model = Zephyr()
+    >>> output = model("Generate hello world in python")
+
+
+    """
+    def __init__(
+        self,
+        max_new_tokens: int = 300,
+        temperature: float = 0.5,
+        top_k: float = 50,
+        top_p: float = 0.95,
+    ):
+        super().__init__()
+        self.max_new_tokens = max_new_tokens
+        self.temperature = temperature
+        self.top_k = top_k
+        self.top_p = top_p
+
+        self.pipe = pipeline(
+            "text-generation",
+            model="HuggingFaceH4/zephyr-7b-alpha",
+            torch_dtype=torch.bfloa16,
+            device_map="auto"
+        )
+        self.messages = [
+            {
+                "role": "system",
+                "content": "You are a friendly chatbot who always responds in the style of a pirate",
+            },
+            {"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
+        ]
+
+    def __call__(self, text: str):
+        """Call the model"""
+        prompt = self.pipe.tokenizer.apply_chat_template(self.messages, tokenize=False, add_generation_prompt=True)
+        outputs = self.pipe(prompt, max_new_token=self.max_new_tokens)
+        print(outputs[0])["generated_text"]