modification

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]