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app.py
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app.py
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import gradio as gr
import json
import os
import boto3
from doc2json import process_docx
from settings_mgr import generate_download_settings_js, generate_upload_settings_js
from llm import LLM, log_to_console, image_embed_prefix
from botocore.config import Config
dump_controls = False
def add_text(history, text):
if 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)]
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):
# 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, system_prompt, temperature, max_tokens, model: str, region):
try:
llm = LLM.create_llm(model)
body = llm.generate_body(message, history, system_prompt, temperature, max_tokens)
config = Config(
read_timeout=600,
connect_timeout=30,
retries={
'max_attempts': 10,
'mode': 'adaptive'
}
)
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", config = config)
response = br.invoke_model(body=body, modelId=f"{model}",
accept="application/json", contentType="application/json")
response_body = json.loads(response.get('body').read())
br_result = llm.read_response(response_body)
history[-1][1] = br_result
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("# Amazon™️ Bedrock™️ Chat™️ (Nils' Version™️) feat. Mistral™️ AI & Anthropic™️ Claude™️")
with gr.Accordion("Startup"):
gr.Markdown("""Use of this interface permitted under the terms and conditions of the
[MIT license](https://github.com/ndurner/amz_bedrock_chat/blob/main/LICENSE).
Third party terms and conditions apply, particularly
those of the LLM vendor (AWS) and hosting provider (Hugging Face).""")
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="anthropic.claude-3-5-sonnet-20240620-v1:0", allow_custom_value=True, elem_id="model",
choices=["anthropic.claude-3-5-sonnet-20240620-v1:0", "anthropic.claude-3-opus-20240229-v1:0", "anthropic.claude-3-sonnet-20240229-v1:0", "anthropic.claude-3-haiku-20240307-v1:0", "anthropic.claude-v2:1", "anthropic.claude-v2",
"mistral.mistral-7b-instruct-v0:2", "mistral.mixtral-8x7b-instruct-v0:1", "mistral.mistral-large-2402-v1:0"])
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")
region = gr.Dropdown(label="Region", value="us-west-2", allow_custom_value=True, elem_id="region",
choices=["eu-central-1", "eu-west-3", "us-east-1", "us-west-1", "us-west-2"])
temp = gr.Slider(0, 1, label="Temperature", elem_id="temp", value=1)
max_tokens = gr.Slider(1, 8192, label="Max. Tokens", elem_id="max_tokens", value=4096)
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 = ['#aws_access textarea', '#aws_secret textarea', '#aws_token textarea', '#system_prompt 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, system_prompt, temp, max_tokens, model, region], js="""
(acc, sec, tok, system_prompt, temp, ntok, model, region) => {
localStorage.setItem('aws_access', acc);
localStorage.setItem('aws_secret', sec);
localStorage.setItem('aws_token', tok);
localStorage.setItem('system_prompt', system_prompt);
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);
}
""")
control_ids = [('aws_access', '#aws_access textarea'),
('aws_secret', '#aws_secret textarea'),
('aws_token', '#aws_token textarea'),
('system_prompt', '#system_prompt textarea'),
('temp', '#temp input'),
('max_tokens', '#max_tokens input'),
('model', '#model'),
('region', '#region')]
controls = [aws_access, aws_secret, aws_token, system_prompt, temp, max_tokens, model, region]
dl_settings_button.click(None, controls, js=generate_download_settings_js("amz_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():
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, system_prompt, 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")
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")
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, 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])
txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
bot, [txt, chatbot, aws_access, aws_secret, aws_token, system_prompt, 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)
img_msg = img_btn.upload(add_img, [chatbot, img_btn], [chatbot], queue=False, postprocess=False)
demo.queue().launch()