aljaz/Auto-GPT
1
0
Fork 0
mirror of https://github.com/aljazceru/Auto-GPT.git synced 2025-12-28 03:14:32 +01:00
Code Issues Packages Projects Releases Wiki Activity

Update OpenAI model info and remove duplicate modelsinfo.py (#4700)

Browse Source 
* Update OpenAI model info and remove duplicate modelsinfo.py

* Fix max_tokens for gpt-4-0613
This commit is contained in:
Reinier van der Leer
2023-06-15 17:14:24 +02:00
committed by GitHub
parent bbaa5b89c2
commit a1e5be7077
5 changed files with 81 additions and 59 deletions
Download Patch File Download Diff File Expand all files Collapse all files

13
autogpt/llm/api_manager.py
View File

@@ -6,8 +6,8 @@ import openai
from openai import Model
from autogpt.config import Config
from autogpt.llm.base import MessageDict
from autogpt.llm.modelsinfo import COSTS
from autogpt.llm.base import CompletionModelInfo, MessageDict
from autogpt.llm.providers.openai import OPEN_AI_MODELS
from autogpt.logs import logger
from autogpt.singleton import Singleton
@@ -83,13 +83,14 @@ class ApiManager(metaclass=Singleton):
"""
# the .model property in API responses can contain version suffixes like -v2
model = model[:-3] if model.endswith("-v2") else model
model_info = OPEN_AI_MODELS[model]
self.total_prompt_tokens += prompt_tokens
self.total_completion_tokens += completion_tokens
self.total_cost += (
prompt_tokens * COSTS[model]["prompt"]
+ completion_tokens * COSTS[model]["completion"]
) / 1000
self.total_cost += prompt_tokens * model_info.prompt_token_cost / 1000
if issubclass(type(model_info), CompletionModelInfo):
self.total_cost += completion_tokens * model_info.completion_token_cost / 1000
logger.debug(f"Total running cost: ${self.total_cost:.3f}")
def set_total_budget(self, total_budget):

15
autogpt/llm/base.py
View File

@@ -31,22 +31,27 @@ class ModelInfo:
Would be lovely to eventually get this directly from APIs, but needs to be scraped from
websites for now.
"""
name: str
prompt_token_cost: float
completion_token_cost: float
max_tokens: int
prompt_token_cost: float
@dataclass
class ChatModelInfo(ModelInfo):
class CompletionModelInfo(ModelInfo):
"""Struct for generic completion model information."""
completion_token_cost: float
@dataclass
class ChatModelInfo(CompletionModelInfo):
"""Struct for chat model information."""
@dataclass
class TextModelInfo(ModelInfo):
class TextModelInfo(CompletionModelInfo):
"""Struct for text completion model information."""

11
autogpt/llm/modelsinfo.py
View File

@@ -1,11 +0,0 @@
COSTS = {
"gpt-3.5-turbo": {"prompt": 0.002, "completion": 0.002},
"gpt-3.5-turbo-0301": {"prompt": 0.002, "completion": 0.002},
"gpt-4-0314": {"prompt": 0.03, "completion": 0.06},
"gpt-4": {"prompt": 0.03, "completion": 0.06},
"gpt-4-0314": {"prompt": 0.03, "completion": 0.06},
"gpt-4-32k": {"prompt": 0.06, "completion": 0.12},
"gpt-4-32k-0314": {"prompt": 0.06, "completion": 0.12},
"text-embedding-ada-002": {"prompt": 0.0004, "completion": 0.0},
"text-davinci-003": {"prompt": 0.02, "completion": 0.02},
}

44
autogpt/llm/providers/openai.py
View File

@@ -3,23 +3,23 @@ from autogpt.llm.base import ChatModelInfo, EmbeddingModelInfo, TextModelInfo
OPEN_AI_CHAT_MODELS = {
info.name: info
for info in [
ChatModelInfo(
name="gpt-3.5-turbo",
prompt_token_cost=0.002,
completion_token_cost=0.002,
max_tokens=4096,
),
ChatModelInfo(
name="gpt-3.5-turbo-0301",
prompt_token_cost=0.002,
prompt_token_cost=0.0015,
completion_token_cost=0.002,
max_tokens=4096,
),
ChatModelInfo(
name="gpt-4",
prompt_token_cost=0.03,
completion_token_cost=0.06,
max_tokens=8192,
name="gpt-3.5-turbo-0613",
prompt_token_cost=0.0015,
completion_token_cost=0.002,
max_tokens=4096,
),
ChatModelInfo(
name="gpt-3.5-turbo-16k-0613",
prompt_token_cost=0.003,
completion_token_cost=0.004,
max_tokens=16384,
),
ChatModelInfo(
name="gpt-4-0314",
@@ -28,10 +28,10 @@ OPEN_AI_CHAT_MODELS = {
max_tokens=8192,
),
ChatModelInfo(
name="gpt-4-32k",
prompt_token_cost=0.06,
completion_token_cost=0.12,
max_tokens=32768,
name="gpt-4-0613",
prompt_token_cost=0.03,
completion_token_cost=0.06,
max_tokens=8192,
),
ChatModelInfo(
name="gpt-4-32k-0314",
@@ -39,8 +39,19 @@ OPEN_AI_CHAT_MODELS = {
completion_token_cost=0.12,
max_tokens=32768,
),
ChatModelInfo(
name="gpt-4-32k-0613",
prompt_token_cost=0.06,
completion_token_cost=0.12,
max_tokens=32768,
),
]
}
# Set aliases for rolling model IDs
OPEN_AI_CHAT_MODELS["gpt-3.5-turbo"] = OPEN_AI_CHAT_MODELS["gpt-3.5-turbo-0301"]
OPEN_AI_CHAT_MODELS["gpt-3.5-turbo-16k"] = OPEN_AI_CHAT_MODELS["gpt-3.5-turbo-16k-0613"]
OPEN_AI_CHAT_MODELS["gpt-4"] = OPEN_AI_CHAT_MODELS["gpt-4-0314"]
OPEN_AI_CHAT_MODELS["gpt-4-32k"] = OPEN_AI_CHAT_MODELS["gpt-4-32k-0314"]
OPEN_AI_TEXT_MODELS = {
info.name: info
@@ -59,8 +70,7 @@ OPEN_AI_EMBEDDING_MODELS = {
for info in [
EmbeddingModelInfo(
name="text-embedding-ada-002",
prompt_token_cost=0.0004,
completion_token_cost=0.0,
prompt_token_cost=0.0001,
max_tokens=8191,
embedding_dimensions=1536,
),

57
tests/unit/test_api_manager.py
View File

@@ -1,8 +1,9 @@
from unittest.mock import MagicMock, patch
import pytest
from pytest_mock import MockerFixture
from autogpt.llm.api_manager import COSTS, ApiManager
from autogpt.llm.api_manager import OPEN_AI_MODELS, ApiManager
api_manager = ApiManager()
@@ -14,16 +15,17 @@ def reset_api_manager():
@pytest.fixture(autouse=True)
def mock_costs():
with patch.dict(
COSTS,
{
"gpt-3.5-turbo": {"prompt": 0.002, "completion": 0.002},
"text-embedding-ada-002": {"prompt": 0.0004, "completion": 0},
},
clear=True,
):
yield
def mock_costs(mocker: MockerFixture):
mocker.patch.multiple(
OPEN_AI_MODELS["gpt-3.5-turbo"],
prompt_token_cost=0.0013,
completion_token_cost=0.0025,
)
mocker.patch.multiple(
OPEN_AI_MODELS["text-embedding-ada-002"],
prompt_token_cost=0.0004,
)
yield
class TestApiManager:
@@ -87,15 +89,15 @@ class TestApiManager:
assert api_manager.get_total_prompt_tokens() == 10
assert api_manager.get_total_completion_tokens() == 20
assert api_manager.get_total_cost() == (10 * 0.002 + 20 * 0.002) / 1000
assert api_manager.get_total_cost() == (10 * 0.0013 + 20 * 0.0025) / 1000
def test_getter_methods(self):
"""Test the getter methods for total tokens, cost, and budget."""
api_manager.update_cost(60, 120, "gpt-3.5-turbo")
api_manager.update_cost(600, 1200, "gpt-3.5-turbo")
api_manager.set_total_budget(10.0)
assert api_manager.get_total_prompt_tokens() == 60
assert api_manager.get_total_completion_tokens() == 120
assert api_manager.get_total_cost() == (60 * 0.002 + 120 * 0.002) / 1000
assert api_manager.get_total_prompt_tokens() == 600
assert api_manager.get_total_completion_tokens() == 1200
assert api_manager.get_total_cost() == (600 * 0.0013 + 1200 * 0.0025) / 1000
assert api_manager.get_total_budget() == 10.0
@staticmethod
@@ -107,7 +109,7 @@ class TestApiManager:
assert api_manager.get_total_budget() == total_budget
@staticmethod
def test_update_cost():
def test_update_cost_completion_model():
"""Test if updating the cost works correctly."""
prompt_tokens = 50
completion_tokens = 100
@@ -115,9 +117,24 @@ class TestApiManager:
api_manager.update_cost(prompt_tokens, completion_tokens, model)
assert api_manager.get_total_prompt_tokens() == 50
assert api_manager.get_total_completion_tokens() == 100
assert api_manager.get_total_cost() == (50 * 0.002 + 100 * 0.002) / 1000
assert api_manager.get_total_prompt_tokens() == prompt_tokens
assert api_manager.get_total_completion_tokens() == completion_tokens
assert (
api_manager.get_total_cost()
== (prompt_tokens * 0.0013 + completion_tokens * 0.0025) / 1000
)
@staticmethod
def test_update_cost_embedding_model():
"""Test if updating the cost works correctly."""
prompt_tokens = 1337
model = "text-embedding-ada-002"
api_manager.update_cost(prompt_tokens, 0, model)
assert api_manager.get_total_prompt_tokens() == prompt_tokens
assert api_manager.get_total_completion_tokens() == 0
assert api_manager.get_total_cost() == (prompt_tokens * 0.0004) / 1000
@staticmethod
def test_get_models():