Add application file

app.py

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+import gradio as gr
+#from huggingface_hub import InferenceClient
+
+import os
+from pathlib import Path
+from openai import OpenAI
+
+class ChatgptAPI:
+    def __init__(self, ):
+        self.client = OpenAI(
+            api_key = os.environ.get("OPENAI_API_KEY"),
+            base_url = "https://api.moonshot.cn/v1",
+        )
+        
+        
+    def get_summary(self, file_path):
+        file_object = self.client.files.create(file=Path(file_path), purpose="file-extract")
+        file_content = self.client.files.content(file_id=file_object.id).text
+        messages = [
+            {
+                "role": "system",
+                "content": "���� Kimi���� Moonshot AI �ṩ���˹��������֣�����ó����ĺ�Ӣ�ĵĶԻ������Ϊ�û��ṩ��ȫ���а�����׼ȷ�Ļش�ͬʱ�����ܾ�һ���漰�ֲ����壬�������ӣ���ɫ����������Ļش�Moonshot AI Ϊר�����ʣ����ɷ�����������ԡ�",
+            },
+            {
+                "role": "system",
+                "content": file_content,
+            },
+            {"role": "user", "content": "��д���ܽ�"},
+        ]
+        completion = self.client.chat.completions.create(
+            model="moonshot-v1-32k",
+            messages=messages,
+            temperature=0.3,
+        )
+        message=completion.choices[0].message.content
+        return message
+        
+        
+    def get_single_round_completion(self, file_path, prompt, conversation):
+        conversation.append_question(prompt)
+        file_object = self.client.files.create(file=Path(file_path), purpose="file-extract")
+        file_content = self.client.files.content(file_id=file_object.id).text
+        messages = [
+            {
+                "role": "system",
+                "content": "���� Kimi���� Moonshot AI �ṩ���˹��������֣�����ó����ĺ�Ӣ�ĵĶԻ������Ϊ�û��ṩ��ȫ���а�����׼ȷ�Ļش�ͬʱ�����ܾ�һ���漰�ֲ����壬�������ӣ���ɫ����������Ļش�Moonshot AI Ϊר�����ʣ����ɷ�����������ԡ�",
+            },
+            {
+                "role": "system",
+                "content": file_content,
+            },
+            {"role": "user", "content": prompt},
+        ]
+        completion = self.client.chat.completions.create(
+            model="moonshot-v1-32k",
+            messages=messages,
+            temperature=0.3,
+        )
+        message=completion.choices[0].message.content
+        conversation.append_answer(message)
+        return message, conversation
+        
+    
+    def get_multi_round_completion(self, prompt, conversation, model='gpt-3.5-turbo'):
+        conversation.append_question(prompt)
+        prompts = conversation.get_prompts()
+
+        response = openai.ChatCompletion.create(
+            model=model,
+            messages=prompts,
+            temperature=0,
+            max_tokens=2048,
+            top_p=1,
+        )
+        message = response.choices[0].message['content']
+        conversation.append_answer(message)
+
+        return message, conversation
+
+class Conversation:
+    def __init__(self, system_prompt='iii', num_of_round = 5):
+        self.num_of_round = num_of_round
+        self.history = []
+        self.initialized = False
+        self.history.append({"role": "system", "content": system_prompt})
+
+        if len(system_prompt) > 0:
+            #logger.info(f'Conversation initialized with system prompt: {system_prompt}')
+            self.initialized = True
+
+    def is_initialized(self):
+        return self.initialized
+    
+    def append_question(self, question):
+        self.history.append({"role": "user", "content": question})
+
+    def append_answer(self, answer):
+        self.history.append({"role": "assistant", "content": answer})
+
+        if len(self.history) > self.num_of_round * 2:
+            del self.history[1:3]
+
+    def clear(self):
+        self.history.clear()
+        self.initialized = False
+
+    def get_prompts(self):
+        return self.history
+    
+    def round_size(self):
+        return 0 if len(self.history) < 2 else len(self.hitory) - 1
+    
+    def get_history_messages(self):
+        return [(u['content'], b['content']) for u,b in zip(self.history[1::2], self.history[2::2])]
+
+
+
+chat_api = ChatgptAPI()
+
+def predict(password_input, user_in_file):
+    if password_input != os.environ.get("USER_KEY"):
+       return [(None, "Wrong password!")], conversation, user_input
+
+    conversation = chat_api.get_summary(user_in_file)
+    return conversation
+    
+
+
+
+
+with gr.Blocks(css="#chatbot{height:350px} .overflow-y-auto{height:600px}") as demo:
+
+    with gr.Row():
+        system_in_txt = gr.Textbox(lines=1, label="User Name:", placeholder="Enter user name")
+        password_in_txt = gr.Textbox(lines=1, label="Password:", placeholder="Enter password")
+       
+    with gr.Row():
+        with gr.Column(scale=1, min_width=50):
+            user_in_file = gr.File(label="Upload File")
+            #submit_button = gr.Button("Submit")
+            summary_button = gr.Button("Summary")
+            target_button = gr.Button("Target")
+            
+        with gr.Column(scale=2):
+            system_in_txt = gr.Textbox(lines=1, label="Output Text:")
+    
+    run_button.click(fn=predict, inputs=[password_in_txt, user_in_file], outputs=[system_in_txt])
+    
+    #submit_button.click(predict, [system_in_txt, password_in_txt, user_in_file, user_in_txt, conversation], [chatbot, conversation, user_in_txt])
+    #reset_button.click(clear_history, [conversation], [chatbot, conversation], queue=False)
+
+
+if __name__ == "__main__":
+    demo.launch()
+

requirements.txt

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+openai
+gradio==3.40.0
+huggingface_hub==0.22.2