Chilkat2-Python
Chilkat2-Python
OpenAI (ChatGPT) List Models
See more OpenAI ChatGPT Examples
Show how to list available OpenAI models and shows how to parse the JSON model information.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/models \
# -H "Authorization: Bearer $OPENAI_API_KEY"
# Use the following online tool to generate HTTP code from a CURL command
# Convert a cURL Command to HTTP Source Code
# 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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"
sbResponseBody = chilkat2.StringBuilder()
success = http.QuickGetSb("https://api.openai.com/v1/models",sbResponseBody)
if (success == False):
print(http.LastErrorText)
sys.exit()
jResp = chilkat2.JsonObject()
jResp.LoadSb(sbResponseBody)
jResp.EmitCompact = False
print("Response Body:")
print(jResp.Emit())
respStatusCode = http.LastStatus
print("Response Status Code = " + str(respStatusCode))
if (respStatusCode >= 400):
print("Response Header:")
print(http.LastHeader)
print("Failed.")
sys.exit()
# Sample JSON response:
# (Sample code for parsing the JSON response is shown below)
# {
# "object": "list",
# "data": [
# {
# "id": "babbage",
# "object": "model",
# "created": 1649358449,
# "owned_by": "openai",
# "permission": [
# {
# "id": "modelperm-49FUp5v084tBB49tC4z8LPH5",
# "object": "model_permission",
# "created": 1669085501,
# "allow_create_engine": false,
# "allow_sampling": true,
# "allow_logprobs": true,
# "allow_search_indices": false,
# "allow_view": true,
# "allow_fine_tuning": false,
# "organization": "*",
# "group": null,
# "is_blocking": false
# }
# ],
# "root": "babbage",
# "parent": null
# },
# {
# "id": "davinci",
# "object": "model",
# "created": 1649359874,
# "owned_by": "openai",
# "permission": [
# {
# "id": "modelperm-U6ZwlyAd0LyMk4rcMdz33Yc3",
# "object": "model_permission",
# "created": 1669066355,
# "allow_create_engine": false,
# "allow_sampling": true,
# "allow_logprobs": true,
# "allow_search_indices": false,
# "allow_view": true,
# "allow_fine_tuning": false,
# "organization": "*",
# "group": null,
# "is_blocking": false
# }
# ],
# "root": "davinci",
# "parent": null
# },
# ...
# ...
# Sample code for parsing the JSON response...
# Use the following online tool to generate parsing code from sample JSON:
# Generate Parsing Code from JSON
v_object = jResp.StringOf("object")
i = 0
count_i = jResp.SizeOfArray("data")
while i < count_i :
jResp.I = i
id = jResp.StringOf("data[i].id")
v_object = jResp.StringOf("data[i].object")
created = jResp.IntOf("data[i].created")
owned_by = jResp.StringOf("data[i].owned_by")
root = jResp.StringOf("data[i].root")
parent = jResp.StringOf("data[i].parent")
j = 0
count_j = jResp.SizeOfArray("data[i].permission")
while j < count_j :
jResp.J = j
id = jResp.StringOf("data[i].permission[j].id")
v_object = jResp.StringOf("data[i].permission[j].object")
created = jResp.IntOf("data[i].permission[j].created")
allow_create_engine = jResp.BoolOf("data[i].permission[j].allow_create_engine")
allow_sampling = jResp.BoolOf("data[i].permission[j].allow_sampling")
allow_logprobs = jResp.BoolOf("data[i].permission[j].allow_logprobs")
allow_search_indices = jResp.BoolOf("data[i].permission[j].allow_search_indices")
allow_view = jResp.BoolOf("data[i].permission[j].allow_view")
allow_fine_tuning = jResp.BoolOf("data[i].permission[j].allow_fine_tuning")
organization = jResp.StringOf("data[i].permission[j].organization")
group = jResp.StringOf("data[i].permission[j].group")
is_blocking = jResp.BoolOf("data[i].permission[j].is_blocking")
j = j + 1
i = i + 1