init

app.py

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+import gradio as gr
+import pandas as pd
+from io import StringIO
+import openai
+import pytesseract
+
+
+
+import os
+
+import numpy as np
+import time
+
+# Set up OpenAI API key
+from api_key import api_key
+openai.api_key = os.environ["CHATGPT_API_KEY"]
+
+Init_system_prompt = "You are an AI Assistant that tries to teach kids various subjects. You are given learning material and you task is to ask questions given the material and then you also grade answers and give feedback how to improve the answers"
+system_message = {"role": "system", "content": Init_system_prompt}
+
+import os
+from PIL import Image
+
+import pytesseract
+#os.system("rm -f path.txt")
+path = os.system("which tesseract >> path.txt")
+with open("path.txt", 'r') as file:
+    tesseract_path = file.read().replace('\n', '')
+
+
+########### TAB 1 (UPLOAD) FUNCTIONS  #############################
+
+def print_files(files):
+    for file in files:
+        print(file.__dir__())
+        print(file.name)
+        print(file.file)
+
+
+def create_data(files):
+    question_context = ''
+    for file in files:
+        if file.name.endswith('png') or file.name.endswith('.jpg'):
+            try:
+                question_context += (pytesseract.image_to_string(Image.open(file.name), lang='fin')) + '\n\n'
+            except Exception as e:
+                print(e)
+                pass
+
+    return question_context
+
+
+########### TAB 2 (CHROMA + PLOT) FUNCTIONS  #############################
+
+########### TAB 3 (CHAT) FUNCTIONS  #############################
+
+def user(user_message, history):
+        return "", history + [[user_message, None]]
+
+def bot(history, messages_history, system_prompt, teksti_contexti, temperature, max_tokens, chatgpt_model):
+    user_message = history[-1][0]
+
+    bot_message, messages_history = ask_gpt(user_message, messages_history, system_prompt, teksti_contexti, temperature, max_tokens,chatgpt_model)
+    messages_history += [{"role": "assistant", "content": bot_message}]
+    history[-1][1] = bot_message
+    time.sleep(0.2)
+    return history, messages_history, str(messages_history)
+
+def ask_gpt(message, messages_history, context, system_prompt, temperature, max_tokens, chatgpt_model):
+    if len(messages_history) < 1:
+        messages_history = [{"role": "system", "content": system_prompt}]
+    messages_history += [{"role": "user", "content": context + '\n Please ask a question about the previous paragramph?'}]
+    print(messages_history)
+    response = openai.ChatCompletion.create(
+        model=chatgpt_model,
+        messages=messages_history,
+        temperature=temperature,
+        max_tokens=max_tokens
+    )
+    return response['choices'][0]['message']['content'], messages_history
+
+def init_history(messages_history, system_prompt):
+    messages_history = []
+    messages_history += [{"role": "system", "content": system_prompt}]
+    msg_log = gr.Textbox.update(value="Tähän tulee message history")
+    system_prompt = gr.Textbox.update(value=system_prompt, label='Insert system message here')
+    return messages_history, system_prompt, msg_log
+
+
+############# INTERFACE ##########################
+with gr.Blocks() as demo:
+    gr.Markdown("ChatGPT demo with RAG using Chromadb")
+    
+    
+    
+    ############# TAB 1 ##########################
+    with gr.Tab("Upload documents"):
+        with gr.Row():
+            files = gr.File(file_count='multiple', file_types=['image'], interactivate = True)
+            gr.Markdown("")
+            testi = gr.Button()
+        
+    ############# TAB 2 ##########################
+    with gr.Tab("Create questions"):
+        
+        with gr.Row():
+            gr.Markdown("")
+        with gr.Row():
+            create_context_btn = gr.Button()
+            teksti_contexti = gr.Textbox(value='Tähän tulee konteksti', label='Dataframe columns')
+    
+    ############# TAB 3 ##########################
+
+    with gr.Tab("Chat"):
+        gr.Markdown("""<h1><center>ChatGPT 
+        ChatBot with Gradio and OpenAI</center></h1>
+        """)
+        with gr.Row():
+            system_prompt = gr.Textbox(value=Init_system_prompt, label='Insert system message here')
+            chatgpt_model = gr.Dropdown(choices=["gpt-3.5-turbo", "gpt-3.5-turbo-0301", "gpt-3.5-turbo-0613"], value='gpt-3.5-turbo',label='ChatGPT model to use', interactive=True)
+            temperature = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, value=0.0, label='temperature')
+            max_tokens = gr.Slider(minimum=10, maximum=600, step=10, value=100, label='Max tokens')
+        with gr.Row():
+            chatbot = gr.Chatbot(label='ChatGPT Chat')
+            state = gr.State([])
+        with gr.Row():
+            msg = gr.Textbox()
+        with gr.Row():
+            clear = gr.Button("Clear")
+        with gr.Row():
+            msg_log = gr.Textbox("Tähän tulee message history", label='Message history')
+                    
+        
+    with gr.Accordion("Klikkaa avataksesi ohjeet"):
+        gr.Markdown("Ohjeet tulee tänne")
+
+
+    # TAB 1 (UPLOAD) Interactive elements:
+    testi.click(print_files, [files])
+
+    # TAB 2 (CHROMA + PLOT) Interactive elements:
+    create_context_btn.click(create_data, files, teksti_contexti)
+
+
+    # TAB 3 (CHAT) Interactive elements:
+    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
+        bot, [chatbot, state, system_prompt, teksti_contexti, temperature, max_tokens, chatgpt_model], [chatbot, state, msg_log]
+    )
+    clear.click(lambda: None, None, chatbot, queue=False).success(init_history, [state, system_prompt], [state, system_prompt, msg_log])
+
+
+demo.launch(debug=True)