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import os
import mysql.connector
import datetime
from dotenv import load_dotenv
from together import Together
from groq import Groq
load_dotenv()
# Database configuration
db_config = {
"user": os.environ.get("DB_USER"),
"password": os.environ.get("DB_PASSWORD"),
"host": os.environ.get("DB_HOST"),
"database": os.environ.get("DB_NAME"),
}
api_service = os.environ.get("API_SERVICE")
def create_tables() -> None:
"""
Create the ChatDB.Chat_history and ChatDB.Chat_data tables if they do not exist.
Also, create a trigger to update is_stream in Chat_data when Chat_history.is_stream is updated.
"""
try:
conn = mysql.connector.connect(**db_config)
cursor = conn.cursor()
cursor.execute(
"""
CREATE TABLE IF NOT EXISTS ChatDB.Chat_history (
chat_id INT AUTO_INCREMENT PRIMARY KEY,
start_time DATETIME,
is_stream INT
)
"""
)
cursor.execute(
"""
CREATE TABLE IF NOT EXISTS ChatDB.Chat_data (
id INT AUTO_INCREMENT PRIMARY KEY,
chat_id INT,
user TEXT,
assistant TEXT,
FOREIGN KEY (chat_id) REFERENCES ChatDB.Chat_history(chat_id)
)
"""
)
cursor.execute("DROP TRIGGER IF EXISTS update_is_stream;")
cursor.execute(
"""
CREATE TRIGGER update_is_stream
AFTER UPDATE ON ChatDB.Chat_history
FOR EACH ROW
BEGIN
UPDATE ChatDB.Chat_data
SET is_stream = NEW.is_stream
WHERE chat_id = NEW.chat_id;
END;
"""
)
conn.commit()
except mysql.connector.Error as err:
print(f"Error: {err}")
finally:
cursor.close()
conn.close()
print("Tables and trigger created successfully")
def insert_chat_history(start_time: datetime.datetime, is_stream: int) -> None:
"""
Insert a new row into the ChatDB.Chat_history table.
:param start_time: Timestamp of when the chat started
:param is_stream: Indicator of whether the conversation is ongoing, starting, or ending
"""
try:
conn = mysql.connector.connect(**db_config)
cursor = conn.cursor()
cursor.execute(
"""
INSERT INTO ChatDB.Chat_history (start_time, is_stream)
VALUES (%s, %s)
""",
(start_time, is_stream),
)
conn.commit()
except mysql.connector.Error as err:
print(f"Error: {err}")
finally:
cursor.close()
conn.close()
def get_latest_chat_id() -> int:
"""
Retrieve the latest chat_id from the ChatDB.Chat_history table.
:return: The latest chat_id or None if no chat_id exists.
"""
try:
conn = mysql.connector.connect(**db_config)
cursor = conn.cursor()
cursor.execute(
"""
SELECT chat_id FROM ChatDB.Chat_history
ORDER BY chat_id DESC LIMIT 1
"""
)
chat_id = cursor.fetchone()[0]
return chat_id if chat_id else None
except mysql.connector.Error as err:
print(f"Error: {err}")
return None
finally:
cursor.close()
conn.close()
def insert_chat_data(chat_id: int, user_message: str, assistant_message: str) -> None:
"""
Insert a new row into the ChatDB.Chat_data table.
:param chat_id: The ID of the chat session
:param user_message: The user's message
:param assistant_message: The assistant's message
"""
try:
conn = mysql.connector.connect(**db_config)
cursor = conn.cursor()
cursor.execute(
"""
INSERT INTO ChatDB.Chat_data (chat_id, user, assistant)
VALUES (%s, %s, %s)
""",
(chat_id, user_message, assistant_message),
)
conn.commit()
except mysql.connector.Error as err:
print(f"Error: {err}")
finally:
cursor.close()
conn.close()
def generate_llm_response(
conversation_history: list[dict], api_service: str = "Groq"
) -> str:
"""
Generate a response from the LLM based on the conversation history.
:param conversation_history: List of dictionaries representing the conversation so far
:param api_service: Choose between "Together" or "Groq" as the API service
:return: Assistant's response as a string
"""
bot_response = ""
if api_service == "Together":
client = Together(api_key=os.environ.get("TOGETHER_API_KEY"))
response = client.chat.completions.create(
model="meta-llama/Llama-3.2-3B-Instruct-Turbo",
messages=conversation_history,
max_tokens=512,
temperature=0.3,
top_p=0.7,
top_k=50,
repetition_penalty=1,
stop=["<|eot_id|>", "<|eom_id|>"],
stream=False,
)
bot_response = response.choices[0].message.content
else:
client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
response = client.chat.completions.create(
model="llama3-8b-8192",
messages=conversation_history,
max_tokens=1024,
temperature=0.3,
top_p=0.7,
stop=["<|eot_id|>", "<|eom_id|>"],
stream=False,
)
bot_response = response.choices[0].message.content
return bot_response
def chat_session() -> None:
"""
Start a chatbot session, allowing the user to interact with the LLM.
Saves conversation history in the database and ends the session on "/stop" command.
"""
print("Welcome to the chatbot! Type '/stop' to end the conversation.")
conversation_history = []
start_time = datetime.datetime.now()
chat_id_pk = None
api_service = "Groq" # or "Together"
while True:
user_input = input("\nYou: ").strip()
conversation_history.append({"role": "user", "content": user_input})
if chat_id_pk is None:
if user_input.lower() == "/stop":
break
bot_response = generate_llm_response(conversation_history, api_service)
conversation_history.append({"role": "assistant", "content": bot_response})
is_stream = 1 # New conversation
insert_chat_history(start_time, is_stream)
chat_id_pk = get_latest_chat_id()
insert_chat_data(chat_id_pk, user_input, bot_response)
else:
if user_input.lower() == "/stop":
is_stream = 2 # End of conversation
current_time = datetime.datetime.now()
insert_chat_history(current_time, is_stream)
break
bot_response = generate_llm_response(conversation_history, api_service)
conversation_history.append({"role": "assistant", "content": bot_response})
is_stream = 0 # Continuation of conversation
current_time = datetime.datetime.now()
insert_chat_history(current_time, is_stream)
insert_chat_data(chat_id_pk, user_input, bot_response)
if len(conversation_history) > 1000:
conversation_history = conversation_history[-3:]
# Example of starting a chat session
create_tables()
chat_session()