05c OpenAi的API - cccbook/py2gpt GitHub Wiki
範例：
要使用 Python 调用 OpenAI 的 ChatGPT，您需要先安装 openai 包并获取您的 API 密钥。在安装包之前，您需要确保已安装 Python 环境。下面是使用 pip 安装 openai 包的示例命令：
pip install openai
在安装完成后，您可以使用以下代码调用 ChatGPT：
import openai
openai.api_key = "YOUR_API_KEY" # 将 YOUR_API_KEY 替换为您的 API 密钥
prompt = "Hello, how are you?"
# 调用 GPT-3 API
response = openai.Completion.create(
engine="davinci", # 使用 davinci 引擎
prompt=prompt,
max_tokens=60, # 最大标记数
n=1, # 生成一条完整的回复
stop=None,
temperature=0.5 # 控制生成文本的随机性。范围从 0（完全确定）到 1（完全随机）
)
print(response.choices[0].text.strip())
https://platform.openai.com/docs/guides/embeddings/what-are-embeddings
-
How to get embeddings
To get an embedding, send your text string to the embeddings API endpoint along with a choice of embedding model ID (e.g., text-embedding-ada-002). The response will contain an embedding, which you can extract, save, and use.
curl https://api.openai.com/v1/embeddings \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"input": "Your text string goes here",
"model": "text-embedding-ada-002"
}'
Text search using embeddings
from openai.embeddings_utils import get_embedding, cosine_similarity
df['code_embedding'] = df['code'].apply(lambda x: get_embedding(x, model='text-embedding-ada-002'))
def search_functions(df, code_query, n=3, pprint=True, n_lines=7):
embedding = get_embedding(code_query, model='text-embedding-ada-002')
df['similarities'] = df.code_embedding.apply(lambda x: cosine_similarity(x, embedding))
res = df.sort_values('similarities', ascending=False).head(n)
return res
res = search_functions(df, 'Completions API tests', n=3)