OPENAI的ChatGPT API调用方式有多种，有基于SDK和HTTP的调用方式，也有流式和非流式的调用方式，接下来将分别举例说明。
本文示例的普通模型是text-davinci-003模型，聊天模型是gpt-3.5-turbo，可以在OPENAI官网查看更多模型介绍：https://platform.openai.com/docs/models/overview.
示例中的temperature参数是是设置回答的随机性，取值0,1，值越大每次回答内容越随机。
基于SDK
基于SDK的方式调用，需要设置环境变量OPENAI_API_KEY,或者在代码中设置openai.api_key = your_api_key.
普通模型-API调用
代码语言：python代码运行次数：36复制model = "text-davinci-003"
def openai_sdk_http_api(content):
response = openai.Completion.create(
model=model,
prompt=content,
temperature=0.8,
)
answer = response.choices[0].text.strip()
return answer普通模型-API流式调用
代码语言：python代码运行次数：18复制model = "text-davinci-003"
def openai_sdk_stream_http_api(prompt):
response = openai.Completion.create(
model=model,
prompt=prompt,
stream=True
)
for message in response:
print(message.choices[0].text.strip(), end='', flush=True)聊天模型-API调用
代码语言：python代码运行次数：17复制model = "gpt-3.5-turbo"
def openai_sdk_chat_http_api(message):
response = openai.ChatCompletion.create(
model=model,
messages=[{"role": "user", "content": message}],
temperature=0.8,
top_p=1,
presence_penalty=1,
)
answer = response.choices[0].message.content.strip()
return answer聊天模型-API流式调用
代码语言：python代码运行次数：6复制model = "gpt-3.5-turbo"
def openai_sdk_stream_chat_http_api(content):
response = openai.ChatCompletion.create(
model=model,
messages=[{"role": "user", "content": content}],
temperature=0.8,
stream=True
)
i = 0
for chunk in response:
if i > 0 and chunk.choices[0].delta['content']:
print(chunk.choices[0].delta.content, end='', flush=True)
i = 1
return基于HTTP
基于HTTP的方式调用，需要在HTTP头部显示设置OPENAI的API KEY.
普通模型-API调用
代码语言：python代码运行次数：3复制api_key = "your api key"
model = "text-davinci-003"
def openai_http_api(message):
url = 'https://api.openai.com/v1/completions'
headers = {
"Authorization": "Bearer " api_key,
"Content-Type": "application/json"
}
data = {
"model": model,
"prompt": message,
"temperature": 0.8,
}
response = requests.post(url, headers=headers, data=json.dumps(data))
return response.json()['choices'][0]['text']普通模型-API流式调用
代码语言：python代码运行次数：12复制api_key = "your api key"
model = "text-davinci-003"
def openai_stream_http_api(message):
url = 'https://api.openai.com/v1/completions'
headers = {
"Authorization": "Bearer " api_key,
'Accept': 'text/event-stream',
}
data = {
"model": model,
"prompt": message,
"temperature": 0.8,
"stream": True
}
response = requests.post(url, headers=headers, json=data, stream=True)
for chunk in response.iter_lines():
response_data = chunk.decode("utf-8").strip()
if not response_data:
continue
try:
print('response_data:', response_data)
if response_data.endswith("data: [DONE]"):
break
json_data = json.loads(response_data.split("data: ")[1])
msg = json_data["choices"][0]["text"]
print(msg, end='', flush=True)
except:
print('json load error, data:', response_data)聊天模型-API调用
代码语言：python代码运行次数：3复制api_key = "your api key"
model = "gpt-3.5-turbo"
def openai_chat_http_api(message):
url = 'https://api.openai.com/v1/chat/completions'
headers = {
"Authorization": "Bearer " api_key,
"Content-Type": "application/json"
}
data = {
"model": model,
"messages": [{"role": "user", "content": message}],
"temperature": 0.8,
}
response = requests.post(url, headers=headers, data=json.dumps(data))
return response.json()['choices'][0]['message']['content']聊天模型-API流式调用
代码语言：python代码运行次数：11复制api_key = "your api key"
model = "gpt-3.5-turbo"
def openai_stream_chat_http_api(message):
url = 'https://api.openai.com/v1/chat/completions'
headers = {
"Authorization": "Bearer " api_key,
"Content-Type": "application/json"
}
data = {
"model": model,
"messages": [{"role": "user", "content": message}],
"temperature": 0.8,
"stream": True
}
response = requests.post(openai_url, headers=headers, json=data, stream=True)
for chunk in response.iter_lines():
response_data = chunk.decode("utf-8").strip()
if not response_data:
continue
try:
if response_data.endswith("data: [DONE]"):
break
data_list = response_data.split("data: ")
if len(data_list) > 2:
json_data = json.loads(data_list[2])
else:
json_data = json.loads(response_data.split("data: ")[1])
if 'content' in json_data["choices"][0]["delta"]:
msg = json_data["choices"][0]["delta"]['content']
print(msg, end='', flush=True)
except:
print('json load error:', response_data)
