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import gradio as gr | |
from mysite.libs.utilities import chat_with_interpreter, completion, process_file,no_process_file | |
from interpreter import interpreter | |
import mysite.interpreter.interpreter_config # インポートするだけで設定が適用されます | |
import duckdb | |
def format_response(chunk, full_response): | |
# Message | |
if chunk["type"] == "message": | |
full_response += chunk.get("content", "") | |
if chunk.get("end", False): | |
full_response += "\n" | |
# Code | |
if chunk["type"] == "code": | |
if chunk.get("start", False): | |
full_response += "```python\n" | |
full_response += chunk.get("content", "").replace("`", "") | |
if chunk.get("end", False): | |
full_response += "\n```\n" | |
# Output | |
if chunk["type"] == "confirmation": | |
if chunk.get("start", False): | |
full_response += "```python\n" | |
full_response += chunk.get("content", {}).get("code", "") | |
if chunk.get("end", False): | |
full_response += "```\n" | |
# Console | |
if chunk["type"] == "console": | |
if chunk.get("start", False): | |
full_response += "```python\n" | |
if chunk.get("format", "") == "active_line": | |
console_content = chunk.get("content", "") | |
if console_content is None: | |
full_response += "No output available on console." | |
if chunk.get("format", "") == "output": | |
console_content = chunk.get("content", "") | |
full_response += console_content | |
if chunk.get("end", False): | |
full_response += "\n```\n" | |
# Image | |
if chunk["type"] == "image": | |
if chunk.get("start", False) or chunk.get("end", False): | |
full_response += "\n" | |
else: | |
image_format = chunk.get("format", "") | |
if image_format == "base64.png": | |
image_content = chunk.get("content", "") | |
if image_content: | |
image = Image.open(BytesIO(base64.b64decode(image_content))) | |
new_image = Image.new("RGB", image.size, "white") | |
new_image.paste(image, mask=image.split()[3]) | |
buffered = BytesIO() | |
new_image.save(buffered, format="PNG") | |
img_str = base64.b64encode(buffered.getvalue()).decode() | |
full_response += f"![Image](data:image/png;base64,{img_str})\n" | |
return full_response | |
# Set the environment variable. | |
def chat_with_interpreter( | |
message, history, a=None, b=None, c=None, d=None | |
): # , openai_api_key): | |
# Set the API key for the interpreter | |
# interpreter.llm.api_key = openai_api_key | |
if message == "reset": | |
interpreter.messages = [] | |
interpreter.reset() | |
return "Interpreter reset", history | |
full_response = "" | |
# add_conversation(history,20) | |
user_entry = {"role": "user", "type": "message", "content": message} | |
#messages.append(user_entry) | |
# Call interpreter.chat and capture the result | |
# message = message + "\nシンタックスを確認してください。" | |
# result = interpreter.chat(message) | |
for chunk in interpreter.chat(message, display=False, stream=True): | |
# print(chunk) | |
# output = '\n'.join(item['content'] for item in result if 'content' in item) | |
full_response = format_response(chunk, full_response) | |
yield full_response # chunk.get("content", "") | |
no_process_file(message,"ai") | |
# Extract the 'content' field from all elements in the result | |
yield full_response | |
return full_response, history | |
PLACEHOLDER = """ | |
<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;"> | |
<img src="https://ysharma-dummy-chat-app.hf.space/file=/tmp/gradio/8e75e61cc9bab22b7ce3dec85ab0e6db1da5d107/Meta_lockup_positive%20primary_RGB.jpg" style="width: 80%; max-width: 550px; height: auto; opacity: 0.55; "> | |
<h1 style="font-size: 28px; margin-bottom: 2px; opacity: 0.55;">Meta llama3</h1> | |
<p style="font-size: 18px; margin-bottom: 2px; opacity: 0.65;">Ask me anything...</p> | |
</div> | |
""" | |
chatbot = gr.Chatbot(height=650, placeholder=PLACEHOLDER, label="Gradio ChatInterface") | |
gradio_interface = gr.ChatInterface( | |
fn=chat_with_interpreter, | |
chatbot=chatbot, | |
fill_height=True, | |
additional_inputs_accordion=gr.Accordion( | |
label="⚙️ Parameters", open=False, render=False | |
), | |
additional_inputs=[ | |
gr.Slider( | |
minimum=0, | |
maximum=1, | |
step=0.1, | |
value=0.95, | |
label="Temperature", | |
render=False, | |
), | |
gr.Slider( | |
minimum=128, | |
maximum=4096, | |
step=1, | |
value=512, | |
label="Max new tokens", | |
render=False, | |
), | |
], | |
# democs, | |
examples=[ | |
["HTMLのサンプルを作成して"], | |
[ | |
"CUDA_VISIBLE_DEVICES=0 llamafactory-cli train examples/lora_single_gpu/llama3_lora_sft.yaml" | |
], | |
], | |
cache_examples=False, | |
) | |