| import random |
| from typing import List, Optional |
|
|
| from openai import OpenAI |
| import os |
| import dotenv |
|
|
| |
| dotenv.load_dotenv() |
| def sota_model( |
| history: List[List[Optional[str]]], |
| temperature: float = 0.6, |
| top_p: float = 0.7, |
| max_output_tokens: int = 2048, |
| ): |
| |
| client = OpenAI( |
| api_key=os.environ.get("SOTA_API_KEY"), |
| base_url=os.environ.get("SOTA_API_BASE") |
| ) |
| messages = [] |
| for human, ai in history: |
| if human: |
| messages.append({"role": "user", "content": human}) |
| if ai: |
| messages.append({"role": "assistant", "content": ai}) |
|
|
| stream = client.chat.completions.create( |
| model=os.environ.get("SOTA_API_MODEL"), |
| messages=messages, |
| stream=True, |
| temperature=temperature, |
| top_p=top_p, |
| max_tokens=max_output_tokens, |
| ) |
| for chunk in stream: |
| if chunk.choices[0].delta.content is not None: |
| yield chunk.choices[0].delta.content |
|
|
|
|
| def model1( |
| history: List[List[Optional[str]]], |
| temperature: float = 0.8, |
| top_p: float = 0.7, |
| max_output_tokens: int = 2048, |
| ): |
| |
| client = OpenAI( |
| api_key=os.environ.get("OPENAI_API_KEY"), |
| base_url=os.environ.get("OPENAI_API_BASE") |
| ) |
| messages = [] |
| for human, ai in history: |
| if human: |
| messages.append({"role": "user", "content": human}) |
| if ai: |
| messages.append({"role": "assistant", "content": ai}) |
|
|
| stream = client.chat.completions.create( |
| |
| model=os.environ.get("API_MODEL_1"), |
| messages=messages, |
| stream=True, |
| temperature=temperature, |
| top_p=top_p, |
| max_tokens=max_output_tokens, |
| ) |
| for chunk in stream: |
| if chunk.choices[0].delta.content is not None: |
| yield chunk.choices[0].delta.content |
|
|
|
|
| def model2( |
| history: List[List[Optional[str]]], |
| temperature: float = 0.8, |
| top_p: float = 0.7, |
| max_output_tokens: int = 2048, |
| ): |
| |
| client = OpenAI( |
| api_key=os.environ.get("OPENAI_API_KEY"), |
| base_url=os.environ.get("OPENAI_API_BASE") |
| ) |
| messages = [] |
| for human, ai in history: |
| if human: |
| messages.append({"role": "user", "content": human}) |
| if ai: |
| messages.append({"role": "assistant", "content": ai}) |
|
|
| stream = client.chat.completions.create( |
| |
| model=os.environ.get("API_MODEL_2"), |
| messages=messages, |
| stream=True, |
| temperature=temperature, |
| top_p=top_p, |
| max_tokens=max_output_tokens, |
| ) |
| for chunk in stream: |
| if chunk.choices[0].delta.content is not None: |
| yield chunk.choices[0].delta.content |
|
|
|
|
| def model3( |
| history: List[List[Optional[str]]], |
| temperature: float = 0.8, |
| top_p: float = 0.7, |
| max_output_tokens: int = 2048, |
| ): |
| |
| client = OpenAI( |
| api_key=os.environ.get("OPENAI_API_KEY"), |
| base_url=os.environ.get("OPENAI_API_BASE") |
| ) |
| messages = [] |
| for human, ai in history: |
| if human: |
| messages.append({"role": "user", "content": human}) |
| if ai: |
| messages.append({"role": "assistant", "content": ai}) |
|
|
| stream = client.chat.completions.create( |
| |
| model=os.environ.get("API_MODEL_3"), |
| messages=messages, |
| stream=True, |
| temperature=temperature, |
| top_p=top_p, |
| max_tokens=max_output_tokens, |
| ) |
| for chunk in stream: |
| if chunk.choices[0].delta.content is not None: |
| yield chunk.choices[0].delta.content |
|
|
|
|
| def get_all_models(): |
| return [ |
| { |
| |
| "name": 'Cherokee Language Preserve Model V0.4', |
| "model": sota_model, |
| }, |
| { |
| "name":os.environ.get("API_MODEL_1"), |
| "model": model1, |
| }, |
| { |
| "name": os.environ.get("API_MODEL_2"), |
| "model": model2, |
| }, |
| { |
| "name": os.environ.get("API_MODEL_3"), |
| "model": model3, |
| }, |
| ] |
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| def get_random_models(number: int = 4): |
| return random.sample(get_all_models(), number) |
| |
| |
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|
