Chilkat2-Python
Chilkat2-Python
OpenAI (ChatGPT) Simple Request
See more OpenAI ChatGPT Examples
Demonstrate a simple ChatGPT request with authentication using your OPENAI_API_KEY.Chilkat Chilkat2-Python Downloads
import sys
import chilkat2
success = False
# This example assumes the Chilkat API to have been previously unlocked.
# See Global Unlock Sample for sample code.
http = chilkat2.Http()
# Implements the following CURL command:
# curl https://api.openai.com/v1/chat/completions \
# -H "Content-Type: application/json" \
# -H "Authorization: Bearer $OPENAI_API_KEY" \
# -d '{
# "model": "gpt-3.5-turbo",
# "messages": [{"role": "user", "content": "Say this is a test!"}],
# "temperature": 0.7
# }'
# Use the following online tool to generate HTTP code from a CURL command
# Convert a cURL Command to HTTP Source Code
# Use this online tool to generate code from sample JSON:
# Generate Code to Create JSON
# The following JSON is sent in the request body.
# {
# "model": "gpt-3.5-turbo",
# "messages": [
# {
# "role": "user",
# "content": "Say this is a test!"
# }
# ],
# "temperature": 0.7
# }
json = chilkat2.JsonObject()
json.UpdateString("model","gpt-3.5-turbo")
json.UpdateString("messages[0].role","user")
json.UpdateString("messages[0].content","Say this is a test!")
json.UpdateNumber("temperature","0.7")
# Adds the "Authorization: Bearer $OPENAI_API_KEY" header.
# This is NOT a real key. Change the "sk-vi...." to your own key.
http.AuthToken = "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"
resp = chilkat2.HttpResponse()
success = http.HttpJson("POST","https://api.openai.com/v1/chat/completions",json,"application/json",resp)
if (success == False):
print(http.LastErrorText)
sys.exit()
sbResponseBody = chilkat2.StringBuilder()
resp.GetBodySb(sbResponseBody)
jResp = chilkat2.JsonObject()
jResp.LoadSb(sbResponseBody)
jResp.EmitCompact = False
print("Response Body:")
print(jResp.Emit())
respStatusCode = resp.StatusCode
print("Response Status Code = " + str(respStatusCode))
if (respStatusCode >= 400):
print("Response Header:")
print(resp.Header)
print("Failed.")
sys.exit()
# Sample JSON response:
# (Sample code for parsing the JSON response is shown below)
# {
# "id": "chatcmpl-abc123",
# "object": "chat.completion",
# "created": 1677858242,
# "model": "gpt-3.5-turbo-0301",
# "usage": {
# "prompt_tokens": 13,
# "completion_tokens": 7,
# "total_tokens": 20
# },
# "choices": [
# {
# "message": {
# "role": "assistant",
# "content": "\n\nThis is a test!"
# },
# "finish_reason": "stop",
# "index": 0
# }
# ]
# }
# Sample code for parsing the JSON response...
# Use the following online tool to generate parsing code from sample JSON:
# Generate Parsing Code from JSON
id = jResp.StringOf("id")
v_object = jResp.StringOf("object")
created = jResp.IntOf("created")
model = jResp.StringOf("model")
Prompt_tokens = jResp.IntOf("usage.prompt_tokens")
Completion_tokens = jResp.IntOf("usage.completion_tokens")
Total_tokens = jResp.IntOf("usage.total_tokens")
i = 0
count_i = jResp.SizeOfArray("choices")
while i < count_i :
jResp.I = i
Role = jResp.StringOf("choices[i].message.role")
Content = jResp.StringOf("choices[i].message.content")
finish_reason = jResp.StringOf("choices[i].finish_reason")
index = jResp.IntOf("choices[i].index")
i = i + 1