Create app.py

app.py

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+import gradio as gr
+from openai import OpenAI
+from API_KEY import OPENAI_API_KEY
+import sqlite3
+import base64
+
+client = OpenAI(api_key=OPENAI_API_KEY)
+
+# Database setup
+conn = sqlite3.connect('faqs.db')
+c = conn.cursor()
+c.execute('''CREATE TABLE IF NOT EXISTS faq (id INTEGER PRIMARY KEY, question TEXT, answer TEXT)''')
+conn.commit()
+
+global_system_prompt = None
+global_model = 'gpt-4o'
+
+def encode_image(image_path):
+  with open(image_path, "rb") as image_file:
+    return base64.b64encode(image_file.read()).decode('utf-8')
+
+def build_assistant(field, lang, name, model, description, rules):
+    global global_system_prompt
+    global global_model
+    list_faqs = get_faqs()
+    system_prompt = f'''You are a helpful chatbot that helps customers and answers based on FAQs. 
+                        You must answer only in {lang}.
+                        your name is {name}.
+                     '''
+    global_system_prompt = system_prompt
+    if len(description) > 0:
+        global_system_prompt = system_prompt + ' {description}.'
+    if model != 'gpt-4o':
+        global_model = model
+    if len(rules) > 0:
+        global_system_prompt = system_prompt + f'you must follow these rules: {rules}'
+    if len(list_faqs) > 0:
+        global_system_prompt = system_prompt + f'if the customer asks a question first check these list of faqs for the answer. if theres is no answer suggest this phone number to the customer to call 09999999999'
+
+def add_faq(question, answer):
+    conn = sqlite3.connect('faqs.db')
+    c = conn.cursor()
+    c.execute('INSERT INTO faq (question, answer) VALUES (?, ?)', (question, answer))
+    conn.commit()
+    conn.close()
+
+def get_faqs():
+    faq_list = ''
+    conn = sqlite3.connect('faqs.db')
+    c = conn.cursor()
+    c.execute('SELECT question, answer FROM faq')
+    faqs = c.fetchall()
+    if len(faqs) > 0:
+        faq_list = "\n\n".join([f"Q: {faq[0]}\nA: {faq[1]}" for faq in faqs])
+    conn.close()
+    return faq_list
+
+def send_message(user_message, chat_history):
+    chat_history.append((f"User: {user_message}", 'Hi there'))
+    return "", chat_history
+
+def convert_history_to_openai_format(history):
+    """
+    Convert chat history to OpenAI format.
+    
+    Parameters:
+    history (list of tuples): The chat history where each tuple consists of (message, sender).
+    
+    Returns:
+    list of dict: The formatted history for OpenAI with "role" as either "user" or "assistant".
+    """
+    global global_system_prompt
+    if global_system_prompt == None:
+        global_system_prompt = "You are a helpful assistant."
+    formatted_history = [{"role": "system", "content": global_system_prompt},]
+    for user_msg, assistant_msg in history:
+        if ('.png' in user_msg[0]) or ('.jpg' in user_msg[0]):
+            encoded_image = encode_image(user_msg[0])
+            text = 'help me based on the image'
+            if user_msg[1] != '':
+                text = user_msg[1]
+            content = [{'type':'text', 'text':text},{'type':'image_url','image_url':{'url':f'data:image/jpeg;base64,{encoded_image}'}}]
+            formatted_history.append({"role": 'user', "content": content})
+        else:
+            formatted_history.append({"role": 'user', "content": user_msg})
+        if isinstance(assistant_msg,str):
+            formatted_history.append({"role": 'assistant', "content": assistant_msg})
+    return formatted_history
+def add_message(history, message):
+    if len(message["files"]) > 0:
+        for x in message["files"]:
+            history.append(((x,message["text"]), None))
+    else:
+        if message["text"]!='':
+            history.append((message["text"], None))
+    print(history)
+    return history, gr.MultimodalTextbox(value=None, interactive=False)
+def bot(history):
+    global global_model
+    response = client.chat.completions.create(
+        model=global_model,
+        messages=convert_history_to_openai_format(history)
+    )
+    
+    chatbot_message = response.choices[0].message.content.strip()
+    history[-1][1] = chatbot_message
+    return history
+# Create Gradio interface
+with gr.Blocks() as demo:
+    # Assistant settings section
+    warning_markdown = gr.Markdown(value="", visible=False)
+    with gr.Row():
+        with gr.Column(scale=1, min_width=200):
+            gr.Markdown("### Assistant settings")
+            field = gr.Textbox(label="Field", value='AI')
+            lang = gr.Dropdown(label='Language', choices=['English', 'Persian'], value='English')
+            name = gr.Textbox(label="Name", value='AIBOT')
+            model = gr.Dropdown(label="Model", choices=['gpt-4o','gpt-4','gpt-3.5'], value='gpt-4o')
+            description = gr.Textbox(label="Description", lines=3)
+            rules = gr.Textbox(label="Rules", lines=3)
+            build_button = gr.Button("Build")
+        
+        # Add FAQ section
+        with gr.Column(scale=1, min_width=200):
+            gr.Markdown("### Add FAQ")
+            question = gr.Textbox(label="Question", lines=2)
+            answer = gr.Textbox(label="Answer", lines=3)
+            add_button = gr.Button("Add")
+    
+        # List of FAQs section
+        with gr.Column(scale=1, min_width=200):
+            gr.Markdown("### List of FAQs")
+            faq_list = gr.Textbox(label="", interactive=False, lines=15, max_lines=15, placeholder="No FAQs available")
+            refresh_button = gr.Button("Refresh")
+
+    # Chatbot Playground section
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Markdown("### Chatbot Playground")
+            chatbot = gr.Chatbot(label="Chatbot:", bubble_full_width=False,show_copy_button=True,min_width=400,
+                avatar_images=(r"C:\Users\A\Desktop\My_Projects\chatbot_builder\user.png",r"C:\Users\A\Desktop\My_Projects\chatbot_builder\ai.png"))
+            chat_input = gr.MultimodalTextbox(interactive=True,
+                                      placeholder="Enter message or upload file...", show_label=False)
+
+    # Define button actions
+    build_button.click(build_assistant, inputs=[field, lang,
+                             name, model, description, rules], outputs=[])
+    add_button.click(add_faq, inputs=[question, answer], outputs=[])
+    refresh_button.click(get_faqs, inputs=[], outputs=[faq_list])
+    chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input])
+    bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name="bot_response")
+    bot_msg.then(lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input])
+
+
+
+# Launch the demo
+demo.launch()