(Perl) OpenAI (ChatGTP) Simple Request

See more OpenAI ChatGPT Examples

Demonstrate a simple ChatGPT request with authentication using your OPENAI_API_KEY.

For more information, see https://platform.openai.com/docs/api-reference/making-requests

Chilkat Perl Downloads Perl Module for Windows, MacOS, Linux, Alpine Linux, Solaris

use chilkat();

# 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/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 = chilkat::CkJsonObject->new();
$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->put_AuthToken("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");
$http->SetRequestHeader("Content-Type","application/json");

# resp is a HttpResponse
$resp = $http->PostJson3("https://api.openai.com/v1/chat/completions","application/json",$json);
if ($http->get_LastMethodSuccess() == 0) {
    print $http->lastErrorText() . "\r\n";
    exit;
}

$sbResponseBody = chilkat::CkStringBuilder->new();
$resp->GetBodySb($sbResponseBody);

$jResp = chilkat::CkJsonObject->new();
$jResp->LoadSb($sbResponseBody);
$jResp->put_EmitCompact(0);

print "Response Body:" . "\r\n";
print $jResp->emit() . "\r\n";

$respStatusCode = $resp->get_StatusCode();
print "Response Status Code = " . $respStatusCode . "\r\n";
if ($respStatusCode >= 400) {
    print "Response Header:" . "\r\n";
    print $resp->header() . "\r\n";
    print "Failed." . "\r\n";

    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) {
    $jResp->put_I($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;
}