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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
import os
#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"\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_interpreters(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_interpreters,
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)
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