Delete app.py

app.py

@@ -1,314 +0,0 @@
-import gradio as gr
-import base64
-import os
-from openai import OpenAI
-import json
-
-from doc2json import process_docx
-
-dump_controls = False
-log_to_console = False
-
-# constants
-image_embed_prefix = "🖼️🆙 "
-
-def encode_image(image_data):
-    """Generates a prefix for image base64 data in the required format for the
-    four known image formats: png, jpeg, gif, and webp.
-
-    Args:
-    image_data: The image data, encoded in base64.
-
-    Returns:
-    A string containing the prefix.
-    """
-
-    # Get the first few bytes of the image data.
-    magic_number = image_data[:4]
-  
-    # Check the magic number to determine the image type.
-    if magic_number.startswith(b'\x89PNG'):
-        image_type = 'png'
-    elif magic_number.startswith(b'\xFF\xD8'):
-        image_type = 'jpeg'
-    elif magic_number.startswith(b'GIF89a'):
-        image_type = 'gif'
-    elif magic_number.startswith(b'RIFF'):
-        if image_data[8:12] == b'WEBP':
-            image_type = 'webp'
-        else:
-            # Unknown image type.
-            raise Exception("Unknown image type")
-    else:
-        # Unknown image type.
-        raise Exception("Unknown image type")
-
-    return f"data:image/{image_type};base64,{base64.b64encode(image_data).decode('utf-8')}"
-
-def add_text(history, text):
-    history = history + [(text, None)]
-    return history, gr.Textbox(value="", interactive=False)
-
-def add_file(history, files):
-    for file in files:
-        if file.name.endswith(".docx"):
-            content = process_docx(file.name)
-        else:
-            with open(file.name, mode="rb") as f:
-                content = f.read()
-
-                if isinstance(content, bytes):
-                    content = content.decode('utf-8', 'replace')
-                else:
-                    content = str(content)
-
-        fn = os.path.basename(file.name)
-        history = history + [(f'```{fn}\n{content}\n```', None)]
-
-        gr.Info(f"File added as {fn}")
-
-    return history
-
-def add_img(history, files):
-    for file in files:
-        if log_to_console:
-            print(f"add_img {file.name}")
-        history = history + [(image_embed_prefix + file.name, None)]
-
-        gr.Info(f"Image added as {file.name}")
-
-    return history
-
-def submit_text(txt_value):
-    return add_text([chatbot, txt_value], [chatbot, txt_value])
-
-def undo(history):
-    history.pop()
-    return history
-
-def dump(history):
-    return str(history)
-
-def load_settings():  
-    # Dummy Python function, actual loading is done in JS  
-    pass  
-
-def save_settings(acc, sec, prompt, temp, tokens, model):  
-    # Dummy Python function, actual saving is done in JS  
-    pass  
-
-def process_values_js():
-    return """
-    () => {
-        return ["oai_key", "system_prompt", "seed"];
-    }
-    """
-
-def bot(message, history, oai_key, system_prompt, seed, temperature, max_tokens, model):
-    try:
-        client = OpenAI(
-            api_key=oai_key
-        )
-
-        seed_i = None
-        if seed:
-            seed_i = int(seed)
-
-        if log_to_console:
-            print(f"bot history: {str(history)}")
-
-        history_openai_format = []
-        user_msg_parts = []
-        if system_prompt:
-                history_openai_format.append({"role": "system", "content": system_prompt})
-        for human, assi in history:
-            if human is not None:
-                if human.startswith(image_embed_prefix):
-                    with open(human.lstrip(image_embed_prefix), mode="rb") as f:
-                        content = f.read()
-                    user_msg_parts.append({"type": "image_url",
-                                           "image_url":{"url": encode_image(content)}})
-                else:
-                    user_msg_parts.append({"type": "text", "text": human})
-
-            if assi is not None:
-                if user_msg_parts:
-                    history_openai_format.append({"role": "user", "content": user_msg_parts})
-                    user_msg_parts = []
-
-                history_openai_format.append({"role": "assistant", "content": assi})
-
-        if message:
-            user_msg_parts.append({"type": "text", "text": human})
-        
-        if user_msg_parts:
-            history_openai_format.append({"role": "user", "content": user_msg_parts})
-
-        if log_to_console:
-            print(f"br_prompt: {str(history_openai_format)}")
-
-        response = client.chat.completions.create(
-            model=model,
-            messages= history_openai_format,
-            temperature=temperature,
-            seed=seed_i,
-            max_tokens=max_tokens
-        )
-
-        if log_to_console:
-            print(f"br_response: {str(response)}")
-
-        history[-1][1] = response.choices[0].message.content
-        if log_to_console:
-            print(f"br_result: {str(history)}")
-
-    except Exception as e:
-        raise gr.Error(f"Error: {str(e)}")
-
-    return "", history
-
-def import_history(history, file):
-    with open(file.name, mode="rb") as f:
-        content = f.read()
-
-        if isinstance(content, bytes):
-            content = content.decode('utf-8', 'replace')
-        else:
-            content = str(content)
-
-    # Deserialize the JSON content to history
-    history = json.loads(content)
-    # The history is returned and will be set to the chatbot component
-    return history
-
-with gr.Blocks() as demo:
-    gr.Markdown("# OAI Chat (Nils' Version™️)")
-
-    with gr.Accordion("Settings"):
-        oai_key = gr.Textbox(label="OpenAI API Key", elem_id="oai_key")
-        model = gr.Dropdown(label="Model", value="gpt-4-turbo-preview", allow_custom_value=True, elem_id="model",
-                            choices=["gpt-4-turbo-preview", "gpt-4-1106-preview", "gpt-4", "gpt-4-vision-preview", "gpt-3.5-turbo", "gpt-3.5-turbo-16k", "gpt-3.5-turbo-1106"])
-        system_prompt = gr.TextArea("You are a helpful AI.", label="System Prompt", lines=3, max_lines=250, elem_id="system_prompt")  
-        seed = gr.Textbox(label="Seed", elem_id="seed")
-        temp = gr.Slider(0, 1, label="Temperature", elem_id="temp", value=1)
-        max_tokens = gr.Slider(1, 4000, label="Max. Tokens", elem_id="max_tokens", value=800)
-        save_button = gr.Button("Save Settings")  
-        load_button = gr.Button("Load Settings")  
-
-        load_button.click(load_settings, js="""  
-            () => {  
-                let elems = ['#oai_key textarea', '#system_prompt textarea', '#seed textarea', '#temp input', '#max_tokens input', '#model'];
-                elems.forEach(elem => {
-                    let item = document.querySelector(elem);
-                    let event = new InputEvent('input', { bubbles: true });
-                    item.value = localStorage.getItem(elem.split(" ")[0].slice(1)) || '';
-                    item.dispatchEvent(event);
-                });
-            }  
-        """)
-
-        save_button.click(save_settings, [oai_key, system_prompt, seed, temp, max_tokens, model], js="""  
-            (oai, sys, seed, temp, ntok, model) => {  
-                localStorage.setItem('oai_key', oai);  
-                localStorage.setItem('system_prompt', sys);  
-                localStorage.setItem('seed', seed);  
-                localStorage.setItem('temp', document.querySelector('#temp input').value);  
-                localStorage.setItem('max_tokens', document.querySelector('#max_tokens input').value);  
-                localStorage.setItem('model', model);  
-            }  
-        """) 
-
-    chatbot = gr.Chatbot(
-        [],
-        elem_id="chatbot",
-        show_copy_button=True,
-        height=350
-    )
-
-    with gr.Row():
-        btn = gr.UploadButton("📁 Upload", size="sm", file_count="multiple")
-        img_btn = gr.UploadButton("🖼️ Upload", size="sm", file_count="multiple", file_types=["image"])
-        undo_btn = gr.Button("↩️ Undo")
-        undo_btn.click(undo, inputs=[chatbot], outputs=[chatbot])
-
-        clear = gr.ClearButton(chatbot, value="🗑️ Clear")
-
-    with gr.Row():
-        txt = gr.TextArea(
-            scale=4,
-            show_label=False,
-            placeholder="Enter text and press enter, or upload a file",
-            container=False,
-            lines=3,            
-        )
-        submit_btn = gr.Button("🚀 Send", scale=0)
-        submit_click = submit_btn.click(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
-            bot, [txt, chatbot, oai_key, system_prompt, seed, temp, max_tokens, model], [txt, chatbot],
-        )
-        submit_click.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
-
-    if dump_controls:
-        with gr.Row():
-            dmp_btn = gr.Button("Dump")
-            txt_dmp = gr.Textbox("Dump")
-            dmp_btn.click(dump, inputs=[chatbot], outputs=[txt_dmp])
-
-    txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
-        bot, [txt, chatbot, oai_key, system_prompt, seed, temp, max_tokens, model], [txt, chatbot],
-    )
-    txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
-    file_msg = btn.upload(add_file, [chatbot, btn], [chatbot], queue=False, postprocess=False)
-    img_msg = img_btn.upload(add_img, [chatbot, img_btn], [chatbot], queue=False, postprocess=False)
-
-    with gr.Accordion("Import/Export", open = False):
-        import_button = gr.UploadButton("History Import")
-        export_button = gr.Button("History Export")
-        export_button.click(lambda: None, [chatbot], js="""
-            (chat_history) => {
-                // Convert the chat history to a JSON string
-                const history_json = JSON.stringify(chat_history);
-                // Create a Blob from the JSON string
-                const blob = new Blob([history_json], {type: 'application/json'});
-                // Create a download link
-                const url = URL.createObjectURL(blob);
-                const a = document.createElement('a');
-                a.href = url;
-                a.download = 'chat_history.json';
-                document.body.appendChild(a);
-                a.click();
-                document.body.removeChild(a);
-                URL.revokeObjectURL(url);
-            }
-            """)
-        dl_button = gr.Button("File download")
-        dl_button.click(lambda: None, [chatbot], js="""
-            (chat_history) => {
-                // Attempt to extract content enclosed in backticks with an optional filename
-                const contentRegex = /```(\\S*\\.(\\S+))?\\n?([\\s\\S]*?)```/;
-                const match = contentRegex.exec(chat_history[chat_history.length - 1][1]);
-                if (match && match[3]) {
-                    // Extract the content and the file extension
-                    const content = match[3];
-                    const fileExtension = match[2] || 'txt'; // Default to .txt if extension is not found
-                    const filename = match[1] || `download.${fileExtension}`;
-                    // Create a Blob from the content
-                    const blob = new Blob([content], {type: `text/${fileExtension}`});
-                    // Create a download link for the Blob
-                    const url = URL.createObjectURL(blob);
-                    const a = document.createElement('a');
-                    a.href = url;
-                    // If the filename from the chat history doesn't have an extension, append the default
-                    a.download = filename.includes('.') ? filename : `${filename}.${fileExtension}`;
-                    document.body.appendChild(a);
-                    a.click();
-                    document.body.removeChild(a);
-                    URL.revokeObjectURL(url);
-                } else {
-                    // Inform the user if the content is malformed or missing
-                    alert('Sorry, the file content could not be found or is in an unrecognized format.');
-                }
-            }
-        """)
-        import_button.upload(import_history, inputs=[chatbot, import_button], outputs=[chatbot])
-
-demo.queue().launch()