modification

.gitignore

@@ -14,3 +14,12 @@ app.py
 typing.py
 _init_.py
 you.py
+Provider.py
+Phind.py
+Bing.py
+Ails.py
+__init__.py
+you.py
+phind.py
+bing.py
+README.md

README.md

@@ -1,13 +1,27 @@
-unstable g4f-v2 early-beta, only for developers !!
+markdown
 
-### interference opneai-proxy api (use with openai python package)    
+# g4f-v2: An Unstable Early-Beta Interference OpenAI Proxy API (For Developers)
 
-run server:
-```sh
+**Note: This version of g4f is still unstable and intended for developers only. Use it with caution.**
+
+## Introduction
+
+g4f-v2 is a library that acts as an intermediary between your application and the OpenAI GPT-3.5 Turbo language model. It provides an API for interacting with the model and handling chat completions. 
+
+## Running the Server
+
+To start the g4f-v2 server, run the following command:
+
+```shell
 python3 -m interference.app
-```
 
-```py
+Usage Examples
+Using the OpenAI Python Package
+
+First, ensure you have the OpenAI Python package installed. You can then configure it to use g4f-v2 as the API endpoint:
+
+python
+
 import openai
 
 openai.api_key = ''
@@ -16,70 +30,46 @@ openai.api_base = 'http://127.0.0.1:1337'
 chat_completion = openai.ChatCompletion.create(stream=True,
     model='gpt-3.5-turbo', messages=[{'role': 'user', 'content': 'write a poem about a tree'}])
 
-#print(chat_completion.choices[0].message.content)
-
 for token in chat_completion:
-    
     content = token['choices'][0]['delta'].get('content')
-    if content != None:
+    if content is not None:
         print(content)
-```
 
-### simple usage:
+Simple Usage
 
-providers:
-```py
-g4f.Providers.You
-g4f.Providers.Ails
-g4f.Providers.Phind
+g4f-v2 supports multiple providers, including g4f.Providers.You, g4f.Providers.Ails, and g4f.Providers.Phind. Here's how you can use them:
 
-# usage:
+python
 
-response = g4f.ChatCompletion.create(..., provider=g4f.Providers.ProviderName)
-```
-
-```py
 import g4f
 
+# Accessing provider parameters
+print(g4f.Providers.Ails.params) # Displays supported arguments
 
-print(g4f.Providers.Ails.params) # supported args
-
-# Automatic selection of provider
-
-# streamed completion
+# Automatic provider selection
 response = g4f.ChatCompletion.create(model='gpt-3.5-turbo', messages=[
                                      {"role": "user", "content": "Hello world"}], stream=True)
 
 for message in response:
     print(message)
 
-# normal response
-response = g4f.ChatCompletion.create(model=g4f.Models.gpt_4, messages=[
-                                     {"role": "user", "content": "hi"}]) # alterative model setting
-
-print(response)
-
-
-# Set with provider
+# Using a specific provider
 response = g4f.ChatCompletion.create(model='gpt-3.5-turbo', provider=g4f.Providers.Phind, messages=[
                                      {"role": "user", "content": "Hello world"}], stream=True)
 
 for message in response:
     print(message)
-```
 
-### Dev
+Development
 
-(more instructions soon)
-the `g4f.Providers`class
+In the development section, we'll cover more instructions soon. The g4f.Providers class is a crucial component of the library. You can define default providers and their behavior in separate files within the g4f/Providers directory. Each provider file should have the following structure:
 
-default:
+./g4f/Providers/ProviderName.py:
+
+python
 
-`./g4f/Providers/ProviderName.py`:
-```python
 import os
 
-
 url: str = 'https://{site_link}'
 model: str = 'gpt-[version]'
 
@@ -88,7 +78,5 @@ def _create_completion(prompt: str, args...):
     or
     yield ...
 
-
 params = f'g4f.Providers.{os.path.basename(__file__)[:-3]} supports: ' + \
-    ', '.join([f"{name}: {get_type_hints(_create_completion)[name].__name__}" for name in _create_completion.__code__.co_varnames[:_create_completion.__code__.co_argcount]])
-```
+    ', '.join([f"{name}: {get_type_hints(_create_completion)[name]

g4f/Providers/Ails.py

@@ -1,11 +1,10 @@
 import os
-import time
 import json
+import time
 import uuid
 import hashlib
 import requests
 
-from ..typing import sha256, Dict, get_type_hints
 from datetime import datetime
 
 url: str = 'https://ai.ls'
@@ -13,29 +12,24 @@ model: str = 'gpt-3.5-turbo'
 
 
 class Utils:
-    def hash(json_data: Dict[str, str]) -> sha256:
+    @staticmethod
+    def hash(json_data: dict) -> str:
+        secretKey = bytearray([79, 86, 98, 105, 91, 84, 80, 78, 123, 83,
+                               35, 41, 99, 123, 51, 54, 37, 57, 63, 103, 59, 117, 115, 108, 41, 67, 76])
 
-        secretKey: bytearray = bytearray([79, 86, 98, 105, 91, 84, 80, 78, 123, 83,
-                                         35, 41, 99, 123, 51, 54, 37, 57, 63, 103, 59, 117, 115, 108, 41, 67, 76])
-
-        base_string: str = '%s:%s:%s:%s' % (
-            json_data['t'],
-            json_data['m'],
-            'OVbi[TPN{S#)c{36%9?g;usl)CL',
-            len(json_data['m'])
-        )
+        base_string = f"{json_data['t']}:{json_data['m']}:{'OVbi[TPN{S#)c{36%9?g;usl)CL'}:{len(json_data['m'])}"
         
         return hashlib.sha256(base_string.encode()).hexdigest()
 
+    @staticmethod
     def format_timestamp(timestamp: int) -> str:
-
         e = timestamp
         n = e % 10
         r = n + 1 if n % 2 == 0 else n
         return str(e - n + r)
 
 
-def _create_completion(model: str,messages: list, temperature: float = 0.6, stream: bool = False):
+def _create_completion(model: str, messages: list, temperature: float = 0.6, stream: bool = False):
     headers = {
         'authority': 'api.caipacity.com',
         'accept': '*/*',
@@ -61,13 +55,16 @@ def _create_completion(model: str,messages: list, temperature: float = 0.6, stre
         't': timestamp,
         's': Utils.hash({
             't': timestamp,
-            'm': messages[-1]['content']})}
+            'm': messages[-1]['content']
+        })
+    }
 
-    json_data = json.dumps(separators=(',', ':'), obj={
+    json_data = json.dumps({
         'model': 'gpt-3.5-turbo',
         'temperature': temperature,
         'stream': True,
-        'messages': messages} | sig)
+        'messages': messages
+    } | sig, separators=(',', ':'))
 
     response = requests.post('https://api.caipacity.com/v1/chat/completions?full=false',
                              headers=headers, data=json_data, stream=True)

g4f/Providers/Bing.py

@@ -1,15 +1,10 @@
-import os
-import json
-import time
 import subprocess
-
-from ..typing import sha256, Dict, get_type_hints
+import json
 
 url = 'https://bing.com/chat'
 model = ['gpt-3.5-turbo', 'gpt-4']
 
 def _create_completion(model: str, messages: list, **kwargs):
-
     path = os.path.dirname(os.path.realpath(__file__))
     config = json.dumps({
         'messages': messages,
@@ -20,8 +15,4 @@ def _create_completion(model: str, messages: list, **kwargs):
     p = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
 
     for line in iter(p.stdout.readline, b''):
-        yield line.decode('utf-8')[:-1]
-
-        
-params = f'g4f.Providers.{os.path.basename(__file__)[:-3]} supports: ' + \
-    '(%s)' % ', '.join([f"{name}: {get_type_hints(_create_completion)[name].__name__}" for name in _create_completion.__code__.co_varnames[:_create_completion.__code__.co_argcount]])
+        yield line.decode('utf-8')[:-1]

g4f/Providers/Phind.py

@@ -2,12 +2,13 @@ import os
 import json
 import time
 import subprocess
+import os
+import json
 
 url = 'https://phind.com'
 model = ['gpt-3.5-turbo', 'gpt-4']
     
 def _create_completion(model: str, messages: list, **kwargs):
-
     path = os.path.dirname(os.path.realpath(__file__))
     config = json.dumps({
         'messages': messages}, separators=(',', ':'))
@@ -19,7 +20,7 @@ def _create_completion(model: str, messages: list, **kwargs):
     for line in iter(p.stdout.readline, b''):
         if b'<title>Just a moment...</title>' in line:
             os.system('clear' if os.name == 'posix' else 'cls')
-            yield 'Clouflare error, please try again...'
+            yield 'Cloudflare error, please try again...'
             os._exit(0)
         
         else:

g4f/Providers/helpers/phind.py

@@ -50,4 +50,4 @@ def output(chunk):
 
 
 response = requests.post('https://www.phind.com/api/infer/answer',
-                         headers=headers, data=json_data, content_callback=output, timeout=999999, impersonate='safari15_5')
+                         headers=headers, data=json_data, content_callback=output, timeout=999999, impersonate='safari15_5')