local-llm-server/llm_server/database.py

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import json
import sqlite3
import time
from pathlib import Path
import tiktoken
from llm_server import opts
tokenizer = tiktoken.get_encoding("cl100k_base")
def init_db():
if not Path(opts.database_path).exists():
conn = sqlite3.connect(opts.database_path)
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c = conn.cursor()
c.execute('''
CREATE TABLE prompts (
ip TEXT,
token TEXT DEFAULT NULL,
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model TEXT,
backend_mode TEXT,
backend_url TEXT,
request_url TEXT,
generation_time FLOAT,
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prompt TEXT,
prompt_tokens INTEGER,
response TEXT,
response_tokens INTEGER,
response_status INTEGER,
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parameters TEXT CHECK (parameters IS NULL OR json_valid(parameters)),
headers TEXT CHECK (headers IS NULL OR json_valid(headers)),
timestamp INTEGER
)
''')
c.execute('''
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CREATE TABLE token_auth (
token TEXT UNIQUE,
type TEXT NOT NULL,
priority INTEGER default 9999,
uses INTEGER default 0,
max_uses INTEGER,
expire INTEGER,
disabled BOOLEAN default 0
)
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''')
conn.commit()
conn.close()
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def log_prompt(ip, token, prompt, response, gen_time, parameters, headers, backend_response_code, request_url, response_tokens: int = None, is_error: bool = False):
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prompt_tokens = len(tokenizer.encode(prompt))
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if not is_error:
if not response_tokens:
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response_tokens = len(tokenizer.encode(response, disallowed_special=()))
else:
response_tokens = None
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# Sometimes we may want to insert null into the DB, but
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# usually we want to insert a float.
if gen_time:
gen_time = round(gen_time, 3)
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if is_error:
gen_time = None
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if not opts.log_prompts:
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prompt = None
if not opts.log_prompts and not is_error:
# TODO: test and verify this works as expected
response = None
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timestamp = int(time.time())
conn = sqlite3.connect(opts.database_path)
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c = conn.cursor()
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c.execute("INSERT INTO prompts VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
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(ip, token, opts.running_model, opts.mode, opts.backend_url, request_url, gen_time, prompt, prompt_tokens, response, response_tokens, backend_response_code, json.dumps(parameters), json.dumps(headers), timestamp))
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conn.commit()
conn.close()
def is_valid_api_key(api_key):
conn = sqlite3.connect(opts.database_path)
cursor = conn.cursor()
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cursor.execute("SELECT token, uses, max_uses, expire, disabled FROM token_auth WHERE token = ?", (api_key,))
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row = cursor.fetchone()
if row is not None:
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token, uses, max_uses, expire, disabled = row
disabled = bool(disabled)
if (uses is None or uses < max_uses) and (expire is None or expire > time.time()) and not disabled:
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return True
return False
def increment_uses(api_key):
conn = sqlite3.connect(opts.database_path)
cursor = conn.cursor()
cursor.execute("SELECT token FROM token_auth WHERE token = ?", (api_key,))
row = cursor.fetchone()
if row is not None:
cursor.execute("UPDATE token_auth SET uses = COALESCE(uses, 0) + 1 WHERE token = ?", (api_key,))
conn.commit()
return True
return False
def get_number_of_rows(table_name):
conn = sqlite3.connect(opts.database_path)
cur = conn.cursor()
cur.execute(f'SELECT COUNT(*) FROM {table_name}')
result = cur.fetchone()
conn.close()
return result[0]
def average_column(table_name, column_name):
conn = sqlite3.connect(opts.database_path)
cursor = conn.cursor()
cursor.execute(f"SELECT AVG({column_name}) FROM {table_name}")
result = cursor.fetchone()
conn.close()
return result[0]
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def average_column_for_model(table_name, column_name, model_name):
conn = sqlite3.connect(opts.database_path)
cursor = conn.cursor()
cursor.execute(f"SELECT AVG({column_name}) FROM {table_name} WHERE model = ?", (model_name,))
result = cursor.fetchone()
conn.close()
return result[0]
def weighted_average_column_for_model(table_name, column_name, model_name, backend_name, backend_url, exclude_zeros: bool = False):
conn = sqlite3.connect(opts.database_path)
cursor = conn.cursor()
# cursor.execute(f"SELECT DISTINCT model, backend_mode FROM {table_name}")
# models_backends = [(row[0], row[1]) for row in cursor.fetchall()]
#
# model_averages = {}
# for model, backend in models_backends:
# if backend != backend_name:
# continue
cursor.execute(f"SELECT {column_name}, ROWID FROM {table_name} WHERE model = ? AND backend_mode = ? AND backend_url = ? ORDER BY ROWID DESC", (model_name, backend_name, backend_url))
results = cursor.fetchall()
# if not results:
# continue
total_weight = 0
weighted_sum = 0
for i, (value, rowid) in enumerate(results):
if value is None or (exclude_zeros and value == 0):
continue
weight = i + 1
total_weight += weight
weighted_sum += weight * value
# if total_weight == 0:
# continue
if total_weight > 0:
# Avoid division by zero
calculated_avg = weighted_sum / total_weight
else:
calculated_avg = 0
conn.close()
return calculated_avg
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def sum_column(table_name, column_name):
conn = sqlite3.connect(opts.database_path)
cursor = conn.cursor()
cursor.execute(f"SELECT SUM({column_name}) FROM {table_name}")
result = cursor.fetchone()
conn.close()
return result[0] if result[0] else 0
def get_distinct_ips_24h():
# Get the current time and subtract 24 hours (in seconds)
past_24_hours = int(time.time()) - 24 * 60 * 60
conn = sqlite3.connect(opts.database_path)
cur = conn.cursor()
cur.execute("SELECT COUNT(DISTINCT ip) FROM prompts WHERE timestamp >= ?", (past_24_hours,))
result = cur.fetchone()
conn.close()
return result[0] if result else 0