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import gradio as gr
import json
import os
import boto3
from doc2json import process_docx
dump_controls = False
log_to_console = False
def add_text(history, text):
history = history + [(text, None)]
return history, gr.Textbox(value="", interactive=False)
def add_file(history, file):
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 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):
# Dummy Python function, actual saving is done in JS
pass
def process_values_js():
return """
() => {
return ["access_key", "secret_key", "token"];
}
"""
def bot(message, history, aws_access, aws_secret, aws_token, temperature, max_tokens, model, region):
try:
prompt = "\n\n"
for human, assi in history:
if prompt is not None:
prompt += f"Human: {human}\n\n"
if assi is not None:
prompt += f"Assistant: {assi}\n\n"
if message:
prompt += f"Human: {message}\n\n"
prompt += f"Assistant:"
if log_to_console:
print(f"br_prompt: {str(prompt)}")
body = json.dumps({
"prompt": prompt,
"max_tokens_to_sample": max_tokens,
"temperature": temperature,
})
sess = boto3.Session(
aws_access_key_id=aws_access,
aws_secret_access_key=aws_secret,
aws_session_token=aws_token,
region_name=region)
br = sess.client(service_name="bedrock-runtime")
response = br.invoke_model(body=body, modelId=f"anthropic.{model}",
accept="application/json", contentType="application/json")
response_body = json.loads(response.get('body').read())
br_result = response_body.get('completion')
history[-1][1] = br_result
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("# Amazon™️ Bedrock™️ Chat™️ (Nils' Version™️) feat. Anthropic™️ Claude-2™️")
with gr.Accordion("Settings"):
aws_access = gr.Textbox(label="AWS Access Key", elem_id="aws_access")
aws_secret = gr.Textbox(label="AWS Secret Key", elem_id="aws_secret")
aws_token = gr.Textbox(label="AWS Session Token", elem_id="aws_token")
model = gr.Dropdown(label="Model", value="claude-v2:1", allow_custom_value=True, elem_id="model",
choices=["claude-v2:1", "claude-v2"])
region = gr.Dropdown(label="Region", value="eu-central-1", allow_custom_value=True, elem_id="region",
choices=["eu-central-1", "us-east-1", "us-west-1"])
temp = gr.Slider(0, 1, label="Temperature", elem_id="temp", value=1)
max_tokens = gr.Slider(1, 200000, label="Max. Tokens", elem_id="max_tokens", value=4000)
save_button = gr.Button("Save Settings")
load_button = gr.Button("Load Settings")
load_button.click(load_settings, js="""
() => {
let elems = ['#aws_access textarea', '#aws_secret textarea', '#aws_token textarea', '#temp input', '#max_tokens input', '#model', '#region'];
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, [aws_access, aws_secret, aws_token, temp, max_tokens, model, region], js="""
(acc, sec, tok, prompt, temp, ntok, model, region) => {
localStorage.setItem('aws_access', acc);
localStorage.setItem('aws_secret', sec);
localStorage.setItem('aws_token', tok);
localStorage.setItem('temp', document.querySelector('#temp input').value);
localStorage.setItem('max_tokens', document.querySelector('#max_tokens input').value);
localStorage.setItem('model', model);
localStorage.setItem('region', region);
}
""")
chatbot = gr.Chatbot(
[],
elem_id="chatbot",
show_copy_button=True,
height=350
)
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, aws_access, aws_secret, aws_token, temp, max_tokens, model, region], [txt, chatbot],
)
submit_click.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
with gr.Row():
btn = gr.UploadButton("📁 Upload", size="sm")
undo_btn = gr.Button("↩️ Undo")
undo_btn.click(undo, inputs=[chatbot], outputs=[chatbot])
clear = gr.ClearButton(chatbot, value="🗑️ Clear")
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])
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])
txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
bot, [txt, chatbot, aws_access, aws_secret, aws_token, temp, max_tokens, model, region], [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)
demo.queue().launch() |