testing
This commit is contained in:
t.me/xtekky
parent
f236f0764e
commit
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### Example: `sqlchat` (use like openai pypi package) <a name="example-sqlchat"></a>
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```python
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# Import sqlchat
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import sqlchat
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# sqlchat.Completion.create
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# sqlchat.StreamCompletion.create
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[...]
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```
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#### Example Chatbot
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```python
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messages = []
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while True:
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user = input('you: ')
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sqlchat_cmpl = sqlchat.Completion.create(
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prompt = user,
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messages = messages
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)
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print('gpt:', sqlchat_cmpl.completion.choices[0].text)
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messages.extend([
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{'role': 'user', 'content': user },
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{'role': 'assistant', 'content': sqlchat_cmpl.completion.choices[0].text}
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])
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```
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#### Streaming Response:
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```python
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for response in sqlchat.StreamCompletion.create(
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prompt = 'write python code to reverse a string',
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messages = []):
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print(response.completion.choices[0].text)
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```
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@ -1,117 +0,0 @@
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from requests import post
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from time import time
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headers = {
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'authority' : 'www.sqlchat.ai',
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'accept' : '*/*',
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'accept-language': 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3',
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'content-type' : 'text/plain;charset=UTF-8',
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'origin' : 'https://www.sqlchat.ai',
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'referer' : 'https://www.sqlchat.ai/',
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'sec-fetch-dest' : 'empty',
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'sec-fetch-mode' : 'cors',
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'sec-fetch-site' : 'same-origin',
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'user-agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36',
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}
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class SqlchatResponse:
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class Completion:
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class Choices:
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def __init__(self, choice: dict) -> None:
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self.text = choice['text']
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self.content = self.text.encode()
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self.index = choice['index']
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self.logprobs = choice['logprobs']
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self.finish_reason = choice['finish_reason']
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def __repr__(self) -> str:
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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>'''
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def __init__(self, choices: dict) -> None:
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self.choices = [self.Choices(choice) for choice in choices]
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class Usage:
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def __init__(self, usage_dict: dict) -> None:
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self.prompt_tokens = usage_dict['prompt_chars']
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self.completion_tokens = usage_dict['completion_chars']
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self.total_tokens = usage_dict['total_chars']
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def __repr__(self):
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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>'''
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def __init__(self, response_dict: dict) -> None:
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self.response_dict = response_dict
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self.id = response_dict['id']
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self.object = response_dict['object']
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self.created = response_dict['created']
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self.model = response_dict['model']
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self.completion = self.Completion(response_dict['choices'])
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self.usage = self.Usage(response_dict['usage'])
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def json(self) -> dict:
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return self.response_dict
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class Completion:
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def create(
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prompt: str = 'hello world',
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messages: list = []) -> SqlchatResponse:
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response = post('https://www.sqlchat.ai/api/chat', headers=headers, stream=True,
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json = {
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'messages': messages,
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'openAIApiConfig':{'key':'','endpoint':''}})
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return SqlchatResponse({
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'id' : f'cmpl-1337-{int(time())}',
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'object' : 'text_completion',
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'created': int(time()),
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'model' : 'gpt-3.5-turbo',
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'choices': [{
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'text' : response.text,
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'index' : 0,
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'logprobs' : None,
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'finish_reason' : 'stop'
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}],
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'usage': {
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'prompt_chars' : len(prompt),
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'completion_chars' : len(response.text),
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'total_chars' : len(prompt) + len(response.text)
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}
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})
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class StreamCompletion:
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def create(
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prompt : str = 'hello world',
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messages: list = []) -> SqlchatResponse:
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messages.append({
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'role':'user',
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'content':prompt
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})
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response = post('https://www.sqlchat.ai/api/chat', headers=headers, stream=True,
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json = {
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'messages': messages,
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'openAIApiConfig':{'key':'','endpoint':''}})
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for chunk in response.iter_content(chunk_size = 2046):
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yield SqlchatResponse({
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'id' : f'cmpl-1337-{int(time())}',
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'object' : 'text_completion',
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'created': int(time()),
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'model' : 'gpt-3.5-turbo',
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'choices': [{
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'text' : chunk.decode(),
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'index' : 0,
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'logprobs' : None,
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'finish_reason' : 'stop'
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}],
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'usage': {
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'prompt_chars' : len(prompt),
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'completion_chars' : len(chunk.decode()),
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'total_chars' : len(prompt) + len(chunk.decode())
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}
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})
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### note: currently patched
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### Example: `t3nsor` (use like openai pypi package) <a name="example-t3nsor"></a>
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```python
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@ -1,6 +1,4 @@
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import asyncio
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import websockets
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from json import dumps, loads
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async def test():
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@ -20,6 +18,8 @@ async def test():
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try:
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response = await wss.recv()
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json_response = loads(response)
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print(json_response)
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ended = json_response.get('eof')
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if not ended:
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@ -28,4 +28,3 @@ async def test():
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except websockets.ConnectionClosed:
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break
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asyncio.run(test())
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# inport ora
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import ora
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# create model
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model = ora.CompletionModel.create(
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system_prompt = 'You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible',
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description = 'ChatGPT Openai Language Model',
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name = 'gpt-3.5')
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print(model.id)
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# init conversation (will give you a conversationId)
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init = ora.Completion.create(
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model = model,
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prompt = 'hello world')
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print(init.completion.choices[0].text)
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while True:
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# pass in conversationId to continue conversation
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prompt = input('>>> ')
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response = ora.Completion.create(
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model = model,
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prompt = prompt,
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includeHistory = True,
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conversationId = init.id)
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print(response.completion.choices[0].text)
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12
unfinished/test.py
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12
unfinished/test.py
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import gptbz
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import asyncio
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# asyncio.run(gptbz.test())
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import requests
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image = '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'
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response = requests.get('https://ocr.holey.cc/ncku?base64_str=%s' % image) #.split('base64,')[1])
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print(response.content)
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