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Running
on
Zero
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 | |
#from logger import logger | |
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 | |
import sqlite3 | |
from datetime import datetime | |
from command.postgresz import initialize_db,add_message_to_db,get_recent_messages | |
# SQLiteの設定 | |
db_name = "chat_historys.db" | |
def initialize_dbs(): | |
# データベースファイルが存在しない場合に新しく作成 | |
if not os.path.exists(db_name): | |
conn = sqlite3.connect(db_name) | |
cursor = conn.cursor() | |
# テーブルを作成するSQL文 | |
create_table_query = """ | |
CREATE TABLE IF NOT EXISTS chat_history ( | |
id INTEGER PRIMARY KEY AUTOINCREMENT, | |
role TEXT, | |
type TEXT, | |
content TEXT, | |
timestamp DATETIME DEFAULT CURRENT_TIMESTAMP | |
) | |
""" | |
cursor.execute(create_table_query) | |
conn.commit() | |
conn.close() | |
print("データベースとテーブルが作成されました。") | |
else: | |
print("データベースは既に存在しています。") | |
conn = sqlite3.connect(db_name) | |
cursor = conn.cursor() | |
cursor.execute(""" | |
CREATE TABLE IF NOT EXISTS history ( | |
id INTEGER PRIMARY KEY AUTOINCREMENT, | |
role TEXT, | |
type TEXT, | |
content TEXT, | |
timestamp DATETIME DEFAULT CURRENT_TIMESTAMP | |
) | |
""") | |
conn.commit() | |
conn.close() | |
def add_message_to_dbs(role, message_type, content): | |
conn = sqlite3.connect(db_name) | |
cursor = conn.cursor() | |
cursor.execute("INSERT INTO history (role, type, content) VALUES (?, ?, ?)", (role, message_type, content)) | |
conn.commit() | |
conn.close() | |
def get_recent_messagess(limit=5): | |
conn = sqlite3.connect(db_name) | |
cursor = conn.cursor() | |
cursor.execute("SELECT role, type, content FROM history ORDER BY timestamp DESC LIMIT ?", (limit,)) | |
messages = cursor.fetchall() | |
conn.close() | |
return messages[::-1] # 最新の20件を取得して逆順にする | |
def format_responses(chunk, full_response): | |
# This function will format the response from the interpreter | |
return full_response + chunk.get("content", "") | |
def chat_with_interpreter(message, history=None, a=None, b=None, c=None, d=None,f=None): | |
if c != os.getenv("openinterpreter_secret"): | |
return message, history | |
if message == "reset": | |
interpreter.reset() | |
return "Interpreter reset", history | |
full_response = "" | |
recent_messages = get_recent_messages() | |
for role, message_type, content in recent_messages: | |
entry = {"role": role, "type": message_type, "content": content} | |
interpreter.messages.append(entry) | |
user_entry = {"role": "user", "type": "message", "content": message} | |
interpreter.messages.append(user_entry) | |
add_message_to_db("user", "message", message) | |
for chunk in interpreter.chat(message, display=False, stream=True): | |
if isinstance(chunk, dict): | |
full_response = format_response(chunk, full_response) | |
else: | |
raise TypeError("Expected chunk to be a dictionary") | |
print(full_response) | |
yield full_response | |
assistant_entry = {"role": "assistant", "type": "message", "content": full_response} | |
interpreter.messages.append(assistant_entry) | |
add_message_to_db("assistant", "message", full_response) | |
yield full_response | |
return full_response, history | |
def chat_with_interpreter_no_stream(message, history=None, a=None, b=None, c=None, d=None): | |
if message == "reset": | |
interpreter.reset() | |
return "Interpreter reset", history | |
full_response = "" | |
recent_messages = get_recent_messages() | |
for role, message_type, content in recent_messages: | |
entry = {"role": role, "type": message_type, "content": content} | |
interpreter.messages.append(entry) | |
user_entry = {"role": "user", "type": "message", "content": message} | |
interpreter.messages.append(user_entry) | |
add_message_to_db("user", "message", message) | |
chunks = interpreter.chat(message, display=False, stream=False) | |
for chunk in chunks: | |
if isinstance(chunk, dict): | |
full_response = format_response(chunk, full_response) | |
else: | |
raise TypeError("Expected chunk to be a dictionary") | |
#yield full_response | |
assistant_entry = {"role": "assistant", "type": "message", "content": str(full_response)} | |
interpreter.messages.append(assistant_entry) | |
add_message_to_db("assistant", "message", str(full_response)) | |
#yield full_response | |
return str(full_response), history | |
# 初期化 | |
initialize_db() | |
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=450, 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, | |
), | |
gr.Textbox(lines=2, placeholder="テキストを入力してください...", label="Text"), | |
], | |
# 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, | |
) | |
if __name__ == '__main__': | |
message = f""" | |
postgres connection is this postgresql://miyataken999:yz1wPf4KrWTm@ep-odd-mode-93794521.us-east-2.aws.neon.tech/neondb?sslmode=require | |
create this tabale | |
CREATE TABLE items ( | |
id INT PRIMARY KEY, | |
brand_name VARCHAR(255), | |
model_name VARCHAR(255), | |
product_number VARCHAR(255), | |
purchase_store VARCHAR(255), | |
purchase_date DATE, | |
purchase_price INT, | |
accessories TEXT, | |
condition INT, | |
metal_type VARCHAR(255), | |
metal_weight DECIMAL(10, 2), | |
diamond_certification BLOB, | |
initial BOOLEAN | |
); | |
""" | |
chat_with_interpreter(message) | |