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from huggingface_hub import InferenceClient
import re
import os
api_key = f"{os.getenv('ImagiGen_HF_secret')}"
def clean_generated_text(text):
# Remove asterisks (e.g., **text** or *text*)
text = re.sub(r"\*+", "", text)
# Remove special characters (except common punctuation and alphanumeric)
text = re.sub(r'[^a-zA-Z0-9 .,!?\'"-]', "", text)
# Normalize multiple spaces into a single space
text = re.sub(r"\s+", " ", text).strip()
return text
def generate_prompt_response(api_key, model_name, user_message, max_tokens=1000):
client = InferenceClient(api_key=api_key)
messages = [{"role": "user", "content": user_message}]
# Generate the completion response
stream = client.chat.completions.create(
model=model_name, messages=messages, max_tokens=max_tokens, stream=True
)
# Collect the response
response = ""
for chunk in stream:
response += chunk.choices[0].delta.content
return clean_generated_text(response)
def Qwen_72b(user_input):
model_name = "Qwen/Qwen2.5-72B-Instruct"
response = generate_prompt_response(api_key, model_name, user_message=user_input)
return clean_generated_text(response)
def Mixtral(user_input):
model_name = "mistralai/Mixtral-8x7B-Instruct-v0.1"
response = generate_prompt_response(api_key, model_name, user_message=user_input)
return clean_generated_text(response)
def microsoft_phi(user_input):
model_name = "microsoft/Phi-3-mini-4k-instruct"
response = generate_prompt_response(api_key, model_name, user_message=user_input)
return clean_generated_text(response)
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