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add linting
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ishaan-jaff
parent
fa108c998d
commit
2c7ffb7c75
40 changed files with 3110 additions and 1709 deletions
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@ -3,31 +3,94 @@
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import dotenv, os
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import requests
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dotenv.load_dotenv() # Loading env variables using dotenv
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dotenv.load_dotenv() # Loading env variables using dotenv
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import traceback
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import datetime, subprocess, sys
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model_cost = {
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"gpt-3.5-turbo": {"max_tokens": 4000, "input_cost_per_token": 0.0000015, "output_cost_per_token": 0.000002},
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"gpt-35-turbo": {"max_tokens": 4000, "input_cost_per_token": 0.0000015, "output_cost_per_token": 0.000002}, # azure model name
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"gpt-3.5-turbo-0613": {"max_tokens": 4000, "input_cost_per_token": 0.0000015, "output_cost_per_token": 0.000002},
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"gpt-3.5-turbo-0301": {"max_tokens": 4000, "input_cost_per_token": 0.0000015, "output_cost_per_token": 0.000002},
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"gpt-3.5-turbo-16k": {"max_tokens": 16000, "input_cost_per_token": 0.000003, "output_cost_per_token": 0.000004},
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"gpt-35-turbo-16k": {"max_tokens": 16000, "input_cost_per_token": 0.000003, "output_cost_per_token": 0.000004}, # azure model name
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"gpt-3.5-turbo-16k-0613": {"max_tokens": 16000, "input_cost_per_token": 0.000003, "output_cost_per_token": 0.000004},
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"gpt-4": {"max_tokens": 8000, "input_cost_per_token": 0.000003, "output_cost_per_token": 0.00006},
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"gpt-4-0613": {"max_tokens": 8000, "input_cost_per_token": 0.000003, "output_cost_per_token": 0.00006},
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"gpt-4-32k": {"max_tokens": 8000, "input_cost_per_token": 0.00006, "output_cost_per_token": 0.00012},
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"claude-instant-1": {"max_tokens": 100000, "input_cost_per_token": 0.00000163, "output_cost_per_token": 0.00000551},
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"claude-2": {"max_tokens": 100000, "input_cost_per_token": 0.00001102, "output_cost_per_token": 0.00003268},
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"text-bison-001": {"max_tokens": 8192, "input_cost_per_token": 0.000004, "output_cost_per_token": 0.000004},
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"chat-bison-001": {"max_tokens": 4096, "input_cost_per_token": 0.000002, "output_cost_per_token": 0.000002},
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"command-nightly": {"max_tokens": 4096, "input_cost_per_token": 0.000015, "output_cost_per_token": 0.000015},
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"gpt-3.5-turbo": {
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"max_tokens": 4000,
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"input_cost_per_token": 0.0000015,
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"output_cost_per_token": 0.000002,
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},
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"gpt-35-turbo": {
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"max_tokens": 4000,
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"input_cost_per_token": 0.0000015,
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"output_cost_per_token": 0.000002,
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}, # azure model name
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"gpt-3.5-turbo-0613": {
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"max_tokens": 4000,
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"input_cost_per_token": 0.0000015,
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"output_cost_per_token": 0.000002,
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},
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"gpt-3.5-turbo-0301": {
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"max_tokens": 4000,
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"input_cost_per_token": 0.0000015,
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"output_cost_per_token": 0.000002,
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},
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"gpt-3.5-turbo-16k": {
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"max_tokens": 16000,
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"input_cost_per_token": 0.000003,
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"output_cost_per_token": 0.000004,
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},
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"gpt-35-turbo-16k": {
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"max_tokens": 16000,
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"input_cost_per_token": 0.000003,
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"output_cost_per_token": 0.000004,
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}, # azure model name
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"gpt-3.5-turbo-16k-0613": {
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"max_tokens": 16000,
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"input_cost_per_token": 0.000003,
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"output_cost_per_token": 0.000004,
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},
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"gpt-4": {
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"max_tokens": 8000,
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"input_cost_per_token": 0.000003,
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"output_cost_per_token": 0.00006,
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},
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"gpt-4-0613": {
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"max_tokens": 8000,
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"input_cost_per_token": 0.000003,
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"output_cost_per_token": 0.00006,
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},
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"gpt-4-32k": {
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"max_tokens": 8000,
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"input_cost_per_token": 0.00006,
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"output_cost_per_token": 0.00012,
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},
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"claude-instant-1": {
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"max_tokens": 100000,
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"input_cost_per_token": 0.00000163,
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"output_cost_per_token": 0.00000551,
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},
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"claude-2": {
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"max_tokens": 100000,
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"input_cost_per_token": 0.00001102,
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"output_cost_per_token": 0.00003268,
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},
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"text-bison-001": {
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"max_tokens": 8192,
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"input_cost_per_token": 0.000004,
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"output_cost_per_token": 0.000004,
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},
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"chat-bison-001": {
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"max_tokens": 4096,
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"input_cost_per_token": 0.000002,
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"output_cost_per_token": 0.000002,
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},
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"command-nightly": {
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"max_tokens": 4096,
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"input_cost_per_token": 0.000015,
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"output_cost_per_token": 0.000015,
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},
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}
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class Supabase:
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# Class variables or attributes
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supabase_table_name = "request_logs"
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def __init__(self):
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# Instance variables
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self.supabase_url = os.getenv("SUPABASE_URL")
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@ -35,9 +98,11 @@ class Supabase:
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try:
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import supabase
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except ImportError:
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subprocess.check_call([sys.executable, '-m', 'pip', 'install', 'supabase'])
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subprocess.check_call([sys.executable, "-m", "pip", "install", "supabase"])
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import supabase
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self.supabase_client = supabase.create_client(self.supabase_url, self.supabase_key)
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self.supabase_client = supabase.create_client(
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self.supabase_url, self.supabase_key
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)
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def price_calculator(self, model, response_obj, start_time, end_time):
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# try and find if the model is in the model_cost map
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@ -45,17 +110,23 @@ class Supabase:
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prompt_tokens_cost_usd_dollar = 0
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completion_tokens_cost_usd_dollar = 0
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if model in model_cost:
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prompt_tokens_cost_usd_dollar = model_cost[model]["input_cost_per_token"] * response_obj["usage"]["prompt_tokens"]
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completion_tokens_cost_usd_dollar = model_cost[model]["output_cost_per_token"] * response_obj["usage"]["completion_tokens"]
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elif "replicate" in model:
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prompt_tokens_cost_usd_dollar = (
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model_cost[model]["input_cost_per_token"]
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* response_obj["usage"]["prompt_tokens"]
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)
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completion_tokens_cost_usd_dollar = (
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model_cost[model]["output_cost_per_token"]
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* response_obj["usage"]["completion_tokens"]
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)
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elif "replicate" in model:
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# replicate models are charged based on time
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# llama 2 runs on an nvidia a100 which costs $0.0032 per second - https://replicate.com/replicate/llama-2-70b-chat
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model_run_time = end_time - start_time # assuming time in seconds
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model_run_time = end_time - start_time # assuming time in seconds
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cost_usd_dollar = model_run_time * 0.0032
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prompt_tokens_cost_usd_dollar = cost_usd_dollar / 2
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completion_tokens_cost_usd_dollar = cost_usd_dollar / 2
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else:
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# calculate average input cost
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# calculate average input cost
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input_cost_sum = 0
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output_cost_sum = 0
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for model in model_cost:
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@ -63,41 +134,75 @@ class Supabase:
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output_cost_sum += model_cost[model]["output_cost_per_token"]
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avg_input_cost = input_cost_sum / len(model_cost.keys())
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avg_output_cost = output_cost_sum / len(model_cost.keys())
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prompt_tokens_cost_usd_dollar = model_cost[model]["input_cost_per_token"] * response_obj["usage"]["prompt_tokens"]
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completion_tokens_cost_usd_dollar = model_cost[model]["output_cost_per_token"] * response_obj["usage"]["completion_tokens"]
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prompt_tokens_cost_usd_dollar = (
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model_cost[model]["input_cost_per_token"]
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* response_obj["usage"]["prompt_tokens"]
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)
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completion_tokens_cost_usd_dollar = (
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model_cost[model]["output_cost_per_token"]
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* response_obj["usage"]["completion_tokens"]
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)
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return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar
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def log_event(self, model, messages, end_user, response_obj, start_time, end_time, print_verbose):
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def log_event(
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self,
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model,
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messages,
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end_user,
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response_obj,
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start_time,
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end_time,
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print_verbose,
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):
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try:
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print_verbose(f"Supabase Logging - Enters logging function for model {model}, response_obj: {response_obj}")
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print_verbose(
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f"Supabase Logging - Enters logging function for model {model}, response_obj: {response_obj}"
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)
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prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar = self.price_calculator(model, response_obj, start_time, end_time)
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total_cost = prompt_tokens_cost_usd_dollar + completion_tokens_cost_usd_dollar
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(
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prompt_tokens_cost_usd_dollar,
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completion_tokens_cost_usd_dollar,
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) = self.price_calculator(model, response_obj, start_time, end_time)
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total_cost = (
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prompt_tokens_cost_usd_dollar + completion_tokens_cost_usd_dollar
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)
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response_time = (end_time-start_time).total_seconds()
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response_time = (end_time - start_time).total_seconds()
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if "choices" in response_obj:
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supabase_data_obj = {
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"response_time": response_time,
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"model": response_obj["model"],
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"total_cost": total_cost,
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"total_cost": total_cost,
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"messages": messages,
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"response": response_obj['choices'][0]['message']['content'],
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"end_user": end_user
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"response": response_obj["choices"][0]["message"]["content"],
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"end_user": end_user,
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}
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print_verbose(f"Supabase Logging - final data object: {supabase_data_obj}")
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data, count = self.supabase_client.table(self.supabase_table_name).insert(supabase_data_obj).execute()
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print_verbose(
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f"Supabase Logging - final data object: {supabase_data_obj}"
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)
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data, count = (
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self.supabase_client.table(self.supabase_table_name)
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.insert(supabase_data_obj)
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.execute()
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)
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elif "error" in response_obj:
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supabase_data_obj = {
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"response_time": response_time,
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"model": response_obj["model"],
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"total_cost": total_cost,
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"total_cost": total_cost,
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"messages": messages,
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"error": response_obj['error'],
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"end_user": end_user
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"error": response_obj["error"],
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"end_user": end_user,
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}
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print_verbose(f"Supabase Logging - final data object: {supabase_data_obj}")
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data, count = self.supabase_client.table(self.supabase_table_name).insert(supabase_data_obj).execute()
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print_verbose(
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f"Supabase Logging - final data object: {supabase_data_obj}"
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)
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data, count = (
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self.supabase_client.table(self.supabase_table_name)
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.insert(supabase_data_obj)
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.execute()
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)
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except:
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# traceback.print_exc()
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print_verbose(f"Supabase Logging Error - {traceback.format_exc()}")
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