OPENAI的ChatGPTAPI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
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
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
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
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 = 0for chunk in response:if i > 0 and chunk.choices[0].delta['content']:print(chunk.choices[0].delta.content, end='', flush=True)i += 1return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
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
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:continuetry:print('response_data:', response_data)if response_data.endswith("data: [DONE]"):breakjson_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
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
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:continuetry:if response_data.endswith("data: [DONE]"):breakdata_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)