claude_chat / app.py
ndurner's picture
backwards compat
86a3809
import gradio as gr
import base64
import os
from anthropic import Anthropic
import json
from doc2json import process_docx
from settings_mgr import generate_download_settings_js, generate_upload_settings_js
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:
An object encoding the image
"""
# 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 {"type": "base64",
"media_type": "image/" + image_type,
"data": 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)]
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 ["api_key", "system_prompt"];
}
"""
def bot(message, history, api_key, system_prompt, temperature, max_tokens, model):
try:
client = Anthropic(
api_key=api_key
)
if log_to_console:
print(f"bot history: {str(history)}")
history_openai_format = []
user_msg_parts = []
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",
"source": 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.messages.create(
model=model,
messages= history_openai_format,
temperature=temperature,
max_tokens=max_tokens,
system=system_prompt
)
if log_to_console:
print(f"br_response: {str(response)}")
resp = ""
for content in response.content:
resp += content.text
history[-1][1] = resp
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
import_data = json.loads(content)
# Check if 'history' key exists for backward compatibility
if 'history' in import_data:
history = import_data['history']
system_prompt.value = import_data.get('system_prompt', '') # Set default if not present
else:
# Assume it's an old format with only history data
history = import_data
return history, system_prompt.value # Return system prompt value to be set in the UI
with gr.Blocks() as demo:
gr.Markdown("# Anthropic™️ Claude™️ Chat (Nils' Version™️)")
with gr.Accordion("Startup"):
gr.Markdown("""Use of this interface permitted under the terms and conditions of the
[MIT license](https://github.com/ndurner/oai_chat/blob/main/LICENSE).
Third party terms and conditions apply, particularly
those of the LLM vendor (Anthropic) and hosting provider (Hugging Face).""")
api_key = gr.Textbox(label="Anthropic API Key", elem_id="api_key")
model = gr.Dropdown(label="Model", value="claude-3-opus-20240229", allow_custom_value=True, elem_id="model",
choices=["claude-3-opus-20240229", "claude-3-sonnet-20240229", "claude-3-haiku-20240307", "claude-2.1", "claude-2.0", "claude-instant-1.2"])
system_prompt = gr.TextArea("You are a helpful yet diligent AI assistant. Answer faithfully and factually correct. Respond with 'I do not know' if uncertain.", label="System Prompt", lines=3, max_lines=250, elem_id="system_prompt")
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")
dl_settings_button = gr.Button("Download Settings")
ul_settings_button = gr.Button("Upload Settings")
load_button.click(load_settings, js="""
() => {
let elems = ['#api_key textarea', '#system_prompt 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, [api_key, system_prompt, temp, max_tokens, model], js="""
(oai, sys, temp, ntok, model) => {
localStorage.setItem('api_key', oai);
localStorage.setItem('system_prompt', sys);
localStorage.setItem('temp', document.querySelector('#temp input').value);
localStorage.setItem('max_tokens', document.querySelector('#max_tokens input').value);
localStorage.setItem('model', model);
}
""")
control_ids = [('api_key', '#api_key textarea'),
('system_prompt', '#system_prompt textarea'),
('temp', '#temp input'),
('max_tokens', '#max_tokens input'),
('model', '#model')]
controls = [api_key, system_prompt, temp, max_tokens, model]
dl_settings_button.click(None, controls, js=generate_download_settings_js("claude_chat_settings.bin", control_ids))
ul_settings_button.click(None, None, None, js=generate_upload_settings_js(control_ids))
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, api_key, system_prompt, 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, api_key, system_prompt, 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, system_prompt], js="""
(chat_history, system_prompt) => {
const export_data = {
history: chat_history,
system_prompt: system_prompt
};
const history_json = JSON.stringify(export_data);
const blob = new Blob([history_json], {type: 'application/json'});
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, system_prompt])
demo.queue().launch()