t3nsor api gpt-3.5

README.md

@@ -1 +1,42 @@
-soon.
+working on it...
+
+`t3nsor` (use like openai pypi package)
+
+Import t3nsor:
+
+```python
+import t3nsor
+
+# t3nsor.Completion.create
+# t3nsor.StreamCompletion.create
+```
+
+Example Chatbot
+```python
+messages = []
+
+while True:
+    user = input('you: ')
+
+    t3nsor_cmpl = t3nsor.Completion.create(
+        prompt   = user,
+        messages = messages
+    )
+
+    print('gpt:', t3nsor_cmpl.completion.choices[0].text)
+
+    messages.extend([
+        {'role': 'user', 'content': user }, 
+        {'role': 'assistant', 'content': t3nsor_cmpl.completion.choices[0].text}
+    ])
+```
+
+Streaming Response:
+
+```python
+for response in t3nsor.StreamCompletion.create(
+    prompt   = 'write python code to reverse a string',
+    messages = []):
+
+    print(response.completion.choices[0].text)
+```

t3nsor/__init__.py

@@ -0,0 +1,118 @@
+from requests import post
+from time     import time
+
+class T3nsorResponse:
+
+    class Completion:
+
+        class Choices:
+            def __init__(self, choice: dict) -> None:
+                self.text           = choice['text']
+                self.content        = self.text.encode()
+                self.index          = choice['index']
+                self.logprobs       = choice['logprobs']
+                self.finish_reason  = choice['finish_reason']
+
+            def __repr__(self) -> str:
+                return f'''<__main__.APIResponse.Completion.Choices(\n    text           = {self.text.encode()},\n    index          = {self.index},\n    logprobs       = {self.logprobs},\n    finish_reason  = {self.finish_reason})object at 0x1337>'''
+
+        def __init__(self, choices: dict) -> None:
+            self.choices = [self.Choices(choice) for choice in choices]
+
+    class Usage:
+        def __init__(self, usage_dict: dict) -> None:
+            self.prompt_tokens      = usage_dict['prompt_tokens']
+            self.completion_tokens  = usage_dict['completion_tokens']
+            self.total_tokens       = usage_dict['total_tokens']
+
+        def __repr__(self):
+            return f'''<__main__.APIResponse.Usage(\n    prompt_tokens      = {self.prompt_tokens},\n    completion_tokens  = {self.completion_tokens},\n    total_tokens       = {self.total_tokens})object at 0x1337>'''
+
+    def __init__(self, response_dict: dict) -> None:
+
+        self.response_dict  = response_dict
+        self.id             = response_dict['id']
+        self.object         = response_dict['object']
+        self.created        = response_dict['created']
+        self.model          = response_dict['model']
+        self.completion     = self.Completion(response_dict['choices'])
+        self.usage          = self.Usage(response_dict['usage'])
+
+    def json(self) -> dict:
+        return self.response_dict
+
+class Completion:
+    model = {
+        'model': {
+                'id'   : 'gpt-3.5-turbo', 
+                'name' : 'Default (GPT-3.5)'
+        }
+    }
+
+    def create(
+        prompt: str    = 'hello world',
+        messages: list = []) -> T3nsorResponse:
+
+        response = post('https://www.t3nsor.tech/api/chat', json = Completion.model | {
+            'messages'  : messages,
+            'key'       : '',
+            'prompt'    : prompt
+        })
+
+        return T3nsorResponse({
+            'id'     : f'cmpl-1337-{int(time())}', 
+            'object' : 'text_completion', 
+            'created': int(time()), 
+            'model'  : Completion.model, 
+            'choices': [{
+                    'text'          : response.text, 
+                    'index'         : 0, 
+                    'logprobs'      : None, 
+                    'finish_reason' : 'stop'
+            }], 
+            'usage': {
+                'prompt_chars'     : len(prompt), 
+                'completion_chars' : len(response.text), 
+                'total_chars'      : len(prompt) + len(response.text)
+            }
+        })
+
+class StreamCompletion:
+    model = {
+        'model': {
+            'id'   : 'gpt-3.5-turbo', 
+            'name' : 'Default (GPT-3.5)'
+        }
+    }
+
+    def create(
+        prompt: str    = 'hello world',
+        messages: list = [])  -> T3nsorResponse:
+
+        response = post('https://www.t3nsor.tech/api/chat', stream = True, json = Completion.model | {
+            'messages'  : messages,
+            'key'       : '',
+            'prompt'    : prompt
+        })
+
+        for resp in response.iter_lines():
+            if resp:
+                yield T3nsorResponse({
+                    'id'     : f'cmpl-1337-{int(time())}', 
+                    'object' : 'text_completion', 
+                    'created': int(time()), 
+                    'model'  : Completion.model, 
+
+                    'choices': [{
+                            'text'          : resp.decode(), 
+                            'index'         : 0, 
+                            'logprobs'      : None, 
+                            'finish_reason' : 'stop'
+                    }],
+
+                    'usage': {
+                        'prompt_chars'     : len(prompt), 
+                        'completion_chars' : len(resp.decode()), 
+                        'total_chars'      : len(prompt) + len(resp.decode())
+                    }
+                })