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import gradio as gr | |
import base64 | |
import os | |
from mistralai import Mistral | |
import json | |
import fitz | |
from PIL import Image | |
import io | |
from settings_mgr import generate_download_settings_js, generate_upload_settings_js | |
from doc2json import process_docx | |
dump_controls = False | |
log_to_console = False | |
temp_files = [] | |
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 process_pdf_img(pdf_fn: str): | |
pdf = fitz.open(pdf_fn) | |
message_parts = [] | |
for page in pdf.pages(): | |
# Create a transformation matrix for rendering at the calculated scale | |
mat = fitz.Matrix(0.6, 0.6) | |
# Render the page to a pixmap | |
pix = page.get_pixmap(matrix=mat, alpha=False) | |
# Convert pixmap to PIL Image | |
img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples) | |
# Convert PIL Image to bytes | |
img_byte_arr = io.BytesIO() | |
img.save(img_byte_arr, format='PNG') | |
img_byte_arr = img_byte_arr.getvalue() | |
# Encode image to base64 | |
base64_encoded = base64.b64encode(img_byte_arr).decode('utf-8') | |
# Construct the data URL | |
image_url = f"data:image/png;base64,{base64_encoded}" | |
# Append the message part | |
message_parts.append({ | |
"type": "text", | |
"text": f"Page {page.number} of file '{pdf_fn}'" | |
}) | |
message_parts.append({ | |
"type": "image_url", | |
"image_url": image_url | |
}) | |
pdf.close() | |
return message_parts | |
def encode_file(fn: str) -> list: | |
user_msg_parts = [] | |
if fn.endswith(".docx"): | |
user_msg_parts.append({"type": "text", "text": process_docx(fn)}) | |
elif fn.endswith(".pdf"): | |
user_msg_parts.extend(process_pdf_img(fn)) | |
else: | |
with open(fn, mode="rb") as f: | |
content = f.read() | |
isImage = False | |
if isinstance(content, bytes): | |
try: | |
# try to add as image | |
content = encode_image(content) | |
isImage = True | |
except: | |
# not an image, try text | |
content = content.decode('utf-8', 'replace') | |
else: | |
content = str(content) | |
if isImage: | |
user_msg_parts.append({"type": "image_url", "image_url": content}) | |
else: | |
user_msg_parts.append({"type": "text", "text": content}) | |
return user_msg_parts | |
def bot(message, history, mistral_key, system_prompt, seed, temperature, max_tokens, model): | |
try: | |
client = Mistral( | |
api_key=mistral_key | |
) | |
history_mistral_format = [] | |
user_msg_parts = [] | |
if system_prompt: | |
history_mistral_format.append({"role": "system", "content": system_prompt}) | |
for human, assi in history: | |
if human is not None: | |
if type(human) is tuple: | |
user_msg_parts.extend(encode_file(human[0])) | |
else: | |
user_msg_parts.append({"type": "text", "text": human}) | |
if assi is not None: | |
if user_msg_parts: | |
history_mistral_format.append({"role": "user", "content": user_msg_parts}) | |
user_msg_parts = [] | |
history_mistral_format.append({"role": "assistant", "content": assi}) | |
if message["text"]: | |
user_msg_parts.append({"type": "text", "text": message["text"]}) | |
if message["files"]: | |
for file in message["files"]: | |
user_msg_parts.extend(encode_file(file)) | |
history_mistral_format.append({"role": "user", "content": user_msg_parts}) | |
if log_to_console: | |
print(f"br_prompt: {str(history_mistral_format)}") | |
response = client.chat.stream( | |
model=model, | |
messages=history_mistral_format, | |
temperature=temperature, | |
max_tokens=max_tokens | |
) | |
partial_response = "" | |
for chunk in response: | |
if chunk.data.choices: | |
txt = chunk.data.choices[0].delta.content | |
if txt: | |
partial_response += txt | |
yield partial_response | |
if log_to_console: | |
print(f"br_result: {str(history)}") | |
except Exception as e: | |
raise gr.Error(f"Error: {str(e)}") | |
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 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) | |
os.remove(file.name) | |
# 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 | |
with gr.Blocks(delete_cache=(86400, 86400)) as demo: | |
gr.Markdown("# Mistral Chat") | |
with gr.Accordion("Startup"): | |
gr.Markdown("""Use of this interface permitted under the terms and conditions of the | |
[MIT license](https://github.com/ndurner/mistral_chat/blob/main/LICENSE). | |
Third party terms and conditions apply. This app and the AI models may make mistakes, so verify any outputs.""") | |
mistral_key = gr.Textbox(label="Mistral API Key", elem_id="mistral_key") | |
model = gr.Dropdown(label="Model", value="pixtral-large-latest", allow_custom_value=True, elem_id="model", | |
choices=["pixtral-large-latest", "mistral-large-latest", "pixtral-12b-2409"]) | |
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") | |
seed = gr.Textbox(label="Seed", elem_id="seed") | |
temp = gr.Slider(0, 1, label="Temperature", elem_id="temp", value=0.7) | |
max_tokens = gr.Slider(1, 4096, 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 = ['#mistral_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, [mistral_key, system_prompt, seed, temp, max_tokens, model], js=""" | |
(key, sys, seed, temp, ntok, model) => { | |
localStorage.setItem('mistral_key', key); | |
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); | |
} | |
""") | |
control_ids = [('mistral_key', '#mistral_key textarea'), | |
('system_prompt', '#system_prompt textarea'), | |
('seed', '#seed textarea'), | |
('temp', '#temp input'), | |
('max_tokens', '#max_tokens input'), | |
('model', '#model')] | |
controls = [mistral_key, system_prompt, seed, temp, max_tokens, model] | |
dl_settings_button.click(None, controls, js=generate_download_settings_js("mistral_chat_settings.bin", control_ids)) | |
ul_settings_button.click(None, None, None, js=generate_upload_settings_js(control_ids)) | |
chat = gr.ChatInterface(fn=bot, multimodal=True, additional_inputs=controls, autofocus=False) | |
chat.textbox.file_count = "multiple" | |
chatbot = chat.chatbot | |
chatbot.show_copy_button = True | |
chatbot.height = 450 | |
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) => { | |
const languageToExt = { | |
'python': 'py', | |
'javascript': 'js', | |
'typescript': 'ts', | |
'csharp': 'cs', | |
'ruby': 'rb', | |
'shell': 'sh', | |
'bash': 'sh', | |
'markdown': 'md', | |
'yaml': 'yml', | |
'rust': 'rs', | |
'golang': 'go', | |
'kotlin': 'kt' | |
}; | |
const contentRegex = /```(?:([^\\n]+)?\\n)?([\\s\\S]*?)```/; | |
const match = contentRegex.exec(chat_history[chat_history.length - 1][1]); | |
if (match && match[2]) { | |
const specifier = match[1] ? match[1].trim() : ''; | |
const content = match[2]; | |
let filename = 'download'; | |
let fileExtension = 'txt'; // default | |
if (specifier) { | |
if (specifier.includes('.')) { | |
// If specifier contains a dot, treat it as a filename | |
const parts = specifier.split('.'); | |
filename = parts[0]; | |
fileExtension = parts[1]; | |
} else { | |
// Use mapping if exists, otherwise use specifier itself | |
const langLower = specifier.toLowerCase(); | |
fileExtension = languageToExt[langLower] || langLower; | |
filename = 'code'; | |
} | |
} | |
const blob = new Blob([content], {type: 'text/plain'}); | |
const url = URL.createObjectURL(blob); | |
const a = document.createElement('a'); | |
a.href = url; | |
a.download = `${filename}.${fileExtension}`; | |
document.body.appendChild(a); | |
a.click(); | |
document.body.removeChild(a); | |
URL.revokeObjectURL(url); | |
} | |
} | |
""") | |
import_button.upload(import_history, inputs=[chatbot, import_button], outputs=[chatbot, system_prompt]) | |
demo.unload(lambda: [os.remove(file) for file in temp_files]) | |
demo.launch() |