Ruby
Ruby
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 Ruby Downloads
require 'chilkat'
success = false
# This example assumes the Chilkat API to have been previously unlocked.
# See Global Unlock Sample for sample code.
http = Chilkat::CkHttp.new()
# 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.put_AuthToken("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")
sbResponseBody = Chilkat::CkStringBuilder.new()
success = http.QuickGetSb("https://api.openai.com/v1/models",sbResponseBody)
if (success == false)
print http.lastErrorText() + "\n";
exit
end
jResp = Chilkat::CkJsonObject.new()
jResp.LoadSb(sbResponseBody)
jResp.put_EmitCompact(false)
print "Response Body:" + "\n";
print jResp.emit() + "\n";
respStatusCode = http.get_LastStatus()
print "Response Status Code = " + respStatusCode.to_s() + "\n";
if (respStatusCode >= 400)
print "Response Header:" + "\n";
print http.lastHeader() + "\n";
print "Failed." + "\n";
exit
end
# 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.put_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.put_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
end
i = i + 1
end