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| import requests | |
| import json | |
| import os | |
| from .moderation import check_moderation_text | |
| from openai import OpenAI | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| client = OpenAI() | |
| def auto_suggest_normalize(text): | |
| try: | |
| # make post request | |
| texts = text.split('\n') | |
| for text in texts: | |
| text = text.strip() | |
| if text == "": continue | |
| yield text | |
| except Exception as e: | |
| print(e) | |
| return texts | |
| headers = {"Authorization": f'Bearer {os.environ["HF_ACCESS_TOKEN"]}'} | |
| def query(payload): | |
| response = requests.post(os.environ["LLAMA2_INFERENCE_API_URL"], headers=headers, json=payload) | |
| return response.json() | |
| def query_openai(prompt): | |
| if check_moderation_text(prompt): return None | |
| response = client.chat.completions.create( | |
| model="gpt-3.5-turbo", | |
| messages=[{"role": "user", "content": prompt}] | |
| ) | |
| return response.choices[0].message.content.strip() | |
| def remove_extras(text): | |
| return text.replace('\\', '').replace('"', '').replace('1.', '').replace('2.', '').replace('3.', '').strip() | |
| def auto_suggest_ask_llama2(prompt): | |
| try: | |
| answer = query({ | |
| "inputs": prompt, | |
| }) | |
| print(answer) | |
| return answer | |
| except Exception as e: | |
| print(e) | |
| return False | |
| def auto_suggest_ask_gpt(prompt): | |
| try: | |
| output = query_openai(prompt) | |
| print(output, 'output') | |
| return output | |
| except Exception as e: | |
| print(e) | |
| return False | |
| def auto_suggest_normalize_llama2(text): | |
| text_list = [] | |
| try: | |
| # make post request | |
| texts = text.split('\n') | |
| for text in texts: | |
| if ("1." in text.strip()[:2]) or ("2." in text.strip()[:2]) or ("3." in text.strip()[:2]) or ("4." in text.strip()[:2]) or ("5." in text.strip()[:2]): | |
| text = remove_extras(text) | |
| text_list.append(text) | |
| except Exception as e: | |
| print(e) | |
| return text_list if len(text_list) > 0 else [] | |
| def auto_suggest_ask(prompt): | |
| try: | |
| # make post request | |
| response = requests.post('http://localhost:11434/api/generate', json={ | |
| "model": "mistral:v0.2", | |
| "prompt": prompt | |
| }) | |
| responses = response.text.split('\n') | |
| text = "" | |
| for response in responses: | |
| dict = json.loads(response) | |
| if dict["done"] == True: break | |
| text += dict["response"] | |
| return text | |
| except Exception as e: | |
| print(e) | |
| return False | |