チャット形式に変更

app.py

@@ -1,116 +1,51 @@
-import codecs
-import json
-import time
-import openai
 import gradio as gr
-import os
-from dotenv import load_dotenv
+import random
 
-# OpenAI API キーの設定
-load_dotenv()
-openai.api_key = os.getenv('OPENAI_API_KEY')
-assistant_id = os.getenv('OPENAI_ASSISTANT_ID')
+from llm.openai import Llm
 
-import json
+# # mock for testing
+# from llm.mock import Llm
 
-assistant = None
-client = openai.OpenAI()
-
-print("### Step 1: Get the Assistant's ID ###")
-assistant = client.beta.assistants.retrieve(assistant_id)
-print(assistant)
-assistant_name = assistant.name
-assistant_description = assistant.description
-assistant_model = assistant.model
-assistant_tools = assistant.tools
-assistant_file_ids = assistant.file_ids
-
-if assistant_description is None:
-    
-    assistant_description += f"このアシスタントは、OpenAI APIで {assistant_model} を使用して作成されました。"
+llm = Llm()
 
 def assistant_response(prompt):
-
-    "### Step 2: Create a Thread ###"
-    empty_thread = client.beta.threads.create()
-    thread_id = empty_thread.id
-    print(empty_thread)
-
-    print("### Step 3: Add a Message to the Thread ###")
-    thread = client.beta.threads.retrieve(thread_id)
-    print(thread)
-
-    print("### Step 4: Add a Message to the Thread ###")
-    thread_message = client.beta.threads.messages.create(
-        thread_id,
-        role="user",
-        content=prompt,
-    )
-    message_id = thread_message.id
-    print(thread_message)
-
-    print("### Step 5: Retrieve the Message ###")
-    message = client.beta.threads.messages.retrieve(
-        message_id=message_id,
-        thread_id=thread_id,
-    )
-    print(message)
-
-    print("### Step 6: Run the Assistant ###")
-    run = client.beta.threads.runs.create(
-        thread_id=thread.id,
-        assistant_id=assistant.id,
-    )
-
-    print("### Step 7: Wait for the Assistant to Finish ###")
-    def wait_on_run(run, thread):
-        while run.status == "queued" or run.status == "in_progress":
-            run = client.beta.threads.runs.retrieve(
-                thread_id=thread.id,
-                run_id=run.id,
-            )
-            time.sleep(0.5)
-        return run
-
-    run = wait_on_run(run, thread)
-    print(run)
-
-    print("### Step 8: Retrieve the Messages ###")
-    messages = client.beta.threads.messages.list(
-        thread_id=thread.id
-    )
-
-    messages_str = json.dumps(messages.dict(), indent=2)
-    print(codecs.decode(messages_str, 'unicode-escape'))
-
-    print("### Step 9: Retrieve the Assistant's Response ###")
-    answers = []
-    for message in messages.data:
-        if message.role == "assistant":
-            if message.content[0].type == "text":
-                answers.append(message.content[0].text.value + "\n\n")
-            else:
-                answers.append("Content is not text.\n\n")
-        elif message.role == "user":
-            break
-
-    # answersを逆順にする
-    answers.reverse()
+    answer = llm.chatcompletion(prompt)
+    return answer
+
+def respond(message, chat_history):
+    answer = llm.chatcompletion(message)
+    print(answer)
+    chat_history.append((message, answer))
+    return "", chat_history
+
+title = "OpenAPI Assistant API: " + llm.assistant.name
+
+if llm.assistant.description is None:
+    model = llm.assistant.model
+    description = f"このデモはOpenAPI Assistant APIのデモです。テキストボックスにテキストを入力すると、{model}モデルが応答します。"
+else:
+    description = llm.assistant.description
+
+# 実行例のリスト (現在使用してない)
+import csv
+examples = []
+with open('flagged/log.csv', 'r', encoding='utf-8') as file:
+    reader = csv.DictReader(file)
+    examples = [row['prompt'] for row in reader]
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+    f"""
+    # {title}
+    {description}
+    """)
     
-    return "".join(answers)
-    
-
-title = "OpenAPI Assistant API: " + assistant_name
-description = assistant_description
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox()
+    clear = gr.ClearButton([msg, chatbot])
+    examples=examples
 
-# Gradio インターフェースの設定
-iface = gr.Interface(
-    title=title,
-    description=description,
-    fn=assistant_response,
-    inputs=gr.Textbox(lines=2, placeholder="Enter your prompt here..."),
-    outputs=gr.Textbox(),
-)
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
 
-# アプリケーションの起動
-iface.launch()
+if __name__ == "__main__":
+    demo.launch()

llm/mock.py

@@ -0,0 +1,50 @@
+import codecs
+import json
+import time
+import openai
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+class Llm:
+    def __init__(self):
+        print("### Step 1: Get the Assistant's ID ###")
+
+        # OpenAI API キーの設定
+        self.client = openai.OpenAI()
+        openai.api_key = os.getenv('OPENAI_API_KEY')
+        self.assistant_id = os.getenv('OPENAI_ASSISTANT_ID')
+        
+        self.assistant = self.client.beta.assistants.retrieve(self.assistant_id)
+        print(self.assistant)
+        assistant_description = self.assistant.description
+        self.assistant.model = "mock"
+        assistant_model = self.assistant.model
+
+        if assistant_description is None:
+            
+            assistant_description = f"このアシスタントは、OpenAI APIで {assistant_model} を使用して作成されました。"
+
+    def setup(self):
+        load_dotenv()
+        self.api_key = os.getenv('OPENAI_API_KEY')
+        self.assistant_id = os.getenv('OPENAI_ASSISTANT_ID')
+        self.client = openai.OpenAI()
+
+    def retrieve_assistant(self):
+        self.assistant = self.client.beta.assistants.retrieve(self.assistant_id)
+        return self.assistant
+
+    def chatcompletion(self, prompt):
+        import random
+        import csv
+
+        with open('flagged/log.csv', 'r') as file:
+            reader = csv.DictReader(file)
+            logs = [row for row in reader]
+
+        random_log = random.choice(logs)
+        answer = random_log['output']
+        
+        return answer

llm/openai.py

@@ -0,0 +1,124 @@
+import codecs
+import json
+import time
+import openai
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+class Llm:
+    def __init__(self):
+        print("### Step 1: Get the Assistant's ID ###")
+
+        # OpenAI API キーの設定
+        self.client = openai.OpenAI()
+        openai.api_key = os.getenv('OPENAI_API_KEY')
+        self.assistant_id = os.getenv('OPENAI_ASSISTANT_ID')
+        
+        self.assistant = self.client.beta.assistants.retrieve(self.assistant_id)
+        print(self.assistant)
+        assistant_description = self.assistant.description
+        assistant_model = self.assistant.model
+
+        if assistant_description is None:
+            
+            assistant_description = f"このアシスタントは、OpenAI APIで {assistant_model} を使用して作成されました。"
+
+
+    def setup(self):
+        load_dotenv()
+        self.api_key = os.getenv('OPENAI_API_KEY')
+        self.assistant_id = os.getenv('OPENAI_ASSISTANT_ID')
+        self.client = openai.OpenAI()
+
+    def retrieve_assistant(self):
+        self.assistant = self.client.beta.assistants.retrieve(self.assistant_id)
+        return self.assistant
+
+    # def openai_completion(self, prompt):
+    #     import random
+    #     import csv
+
+    #     with open('flagged/log.csv', 'r') as file:
+    #         reader = csv.DictReader(file)
+    #         logs = [row for row in reader]
+
+    #     random_log = random.choice(logs)
+    #     answer = random_log['output']
+        
+    #     return answer
+
+    def chatcompletion(self, prompt):
+
+        try:
+            "### Step 2: Create a Thread ###"
+            empty_thread = self.client.beta.threads.create()
+            thread_id = empty_thread.id
+            print(empty_thread)
+
+            print("### Step 3: Add a Message to the Thread ###")
+            thread = self.client.beta.threads.retrieve(thread_id)
+            print(thread)
+
+            print("### Step 4: Add a Message to the Thread ###")
+            thread_message = self.client.beta.threads.messages.create(
+                thread_id,
+                role="user",
+                content=prompt,
+            )
+            message_id = thread_message.id
+            print(thread_message)
+
+            print("### Step 5: Retrieve the Message ###")
+            message = self.client.beta.threads.messages.retrieve(
+                message_id=message_id,
+                thread_id=thread_id,
+            )
+            print(message)
+
+            print("### Step 6: Run the Assistant ###")
+            run = self.client.beta.threads.runs.create(
+                thread_id=thread.id,
+                assistant_id=self.assistant.id,
+            )
+
+            print("### Step 7: Wait for the Assistant to Finish ###")
+            def wait_on_run(run, thread):
+                while run.status == "queued" or run.status == "in_progress":
+                    run = self.client.beta.threads.runs.retrieve(
+                        thread_id=thread.id,
+                        run_id=run.id,
+                    )
+                    time.sleep(0.5)
+                return run
+
+            run = wait_on_run(run, thread)
+            print(run)
+
+            print("### Step 8: Retrieve the Messages ###")
+            messages = self.client.beta.threads.messages.list(
+                thread_id=thread.id
+            )
+
+            messages_str = json.dumps(messages.dict(), indent=2)
+            print(codecs.decode(messages_str, 'unicode-escape'))
+
+            print("### Step 9: Retrieve the Assistant's Response ###")
+            answers = []
+            for message in messages.data:
+                if message.role == "assistant":
+                    if message.content[0].type == "text":
+                        answers.append(message.content[0].text.value + "\n\n")
+                    else:
+                        answers.append("Content is not text.\n\n")
+                elif message.role == "user":
+                    break
+
+            # answersを逆順にする
+            answers.reverse()
+            
+            return "".join(answers)
+        except Exception as e:
+            print(f"スレッドの作成中にエラーが発生しました: {e}")
+            raise