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api_fn.py

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+# -*- coding: utf-8 -*-
+import gradio as gr
+import requests
+import json
+import os
+
+api_key_primary_val = os.getenv('api_key_primary_val')
+api_key = os.getenv('api_key')
+
+def request_hyper(message):
+    class CompletionExecutor:
+        def __init__(self, host, api_key, api_key_primary_val, request_id):
+            self._host = host
+            self._api_key = api_key
+            self._api_key_primary_val = api_key_primary_val
+            self._request_id = request_id
+
+        def execute(self, completion_request):
+            headers = {
+                'X-NCP-CLOVASTUDIO-API-KEY': self._api_key,
+                'X-NCP-APIGW-API-KEY': self._api_key_primary_val,
+                'X-NCP-CLOVASTUDIO-REQUEST-ID': self._request_id,
+                'Content-Type': 'application/json; charset=utf-8',
+                'Accept': 'text/event-stream'
+            }
+
+            with requests.post(self._host + '/testapp/v1/chat-completions/HCX-002',
+                            headers=headers, json=completion_request, stream=False) as r:
+                stop_reason = ""
+                messages = []
+                for line in r.iter_lines():
+                    if line:
+                        raw_data = line.decode("utf-8")
+                        if raw_data.startswith('data:'):
+                            json_part = raw_data.split('data:', 1)[1].strip()
+                            decoded_text = json.loads(json_part)
+                            message_content = decoded_text["message"]["content"]
+                            stop_reason = decoded_text["stopReason"]
+                            print(f"메시지:{message_content}")
+                            messages.append(message_content)
+                            # yield "AI : " + message_content
+                            # print(f"메시지:{message},{stop_reason}끝")
+                    if stop_reason == "stop_before":
+                        print("stop_before 출력. 반복 종료")
+                        print(f"messages:{messages}")
+                        return messages
+                        # return line.decode("utf-8")
+
+
+
+    completion_executor = CompletionExecutor(
+        host='https://clovastudio.stream.ntruss.com',
+        api_key=api_key,
+        api_key_primary_val=api_key_primary_val,
+        request_id='73f8978312ed4ca0bbef6fa7f86edfc3'
+    )
+    # text = "안녕?"
+    preset_text = [{"role":"system","content":"대답은 하지마. 다음 질문을 블룸의 질문의 단계 중 몇 번째 단계에 해당하는 질문인지 알려주고 피드백 해줘."},{"role":"user","content":message}]
+
+    request_data = {
+        'messages': preset_text,
+        'topP': 0.8,
+        'topK': 0,
+        'maxTokens': 3000,
+        'temperature': 0.5,
+        'repeatPenalty': 5.0,
+        'stopBefore': [],
+        'includeAiFilters': True
+    }
+
+    print(f"프리셋텍스트: {preset_text}")
+    completion_result = completion_executor.execute(request_data)
+    return completion_result

app.py

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+import time
+import gradio as gr
+from api_fn import request_hyper
+
+def echo(message, history):
+    result = request_hyper(message)
+    msg_text = ""
+    for msg in result:
+        msg_text += msg
+        yield "AI : " + msg_text
+        time.sleep(0.1)
+
+
+demo = gr.ChatInterface(echo).queue()
+demo.launch()