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from openai import OpenAI
import pandas as pd
import requests
# input model series and content
def LLM_request(model_series, model_name, content):
# Read API keys from txt file
df = pd.read_csv('./scripts/Task2/utils/LLM_APIs.txt')
# Split column names due to tab characters
df = pd.DataFrame([x.split('\t') for x in df.values.flatten()], columns=['name','API'])
# get corresponding API key
api_key = df[df['name'] == model_series]['API'].values[0]
if model_series == 'gpt':
client = OpenAI(
api_key=api_key,
base_url="https://api.bianxie.ai/v1"
)
completion = client.chat.completions.create(
model = model_name,
messages=[
{
"role": "user",
"content": content
}
]
)
return completion.choices[0].message
elif model_series == 'ds_V3_qwen_llama':
client = OpenAI(api_key=api_key,
base_url="https://api.studio.nebius.ai/v1")
response = client.chat.completions.create(
model=model_name,
messages=[
{"role": "user", "content": content},
],
stream=False
)
return response.choices[0].message.content
elif model_series == 'gemini':
api_key = api_key
url = 'https://api.bianxie.ai/v1/chat/completions'
headers = {
'Content-Type': 'application/json',
'Authorization': f'Bearer {api_key}'
}
data = {
'model': model_name,
'messages': [{'role': 'user', 'content': content}],
}
response = requests.post(url, headers=headers, json=data)
content = response.json()['choices'][0]['message']
return content
elif model_series == 'claude':
api_key = api_key
url = 'https://api.bianxie.ai/v1/chat/completions'
headers = {
'Content-Type': 'application/json',
'Authorization': f'Bearer {api_key}'
}
data = {
'model': model_name,
'messages': [{'role': 'user', 'content': content}],
}
response = requests.post(url, headers=headers, json=data)
content = response.json()['choices'][0]['message']
return content
else:
return "Unsupported model series. Please check the model series name."
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