Add langsmith
This commit is contained in:
Dianliang233
parent
551d88c90e
commit
5a330609ab
3 changed files with 134 additions and 120 deletions
|
|
@ -21,6 +21,7 @@ curseforge_api_key =
|
|||
exchange_rate_api_key =
|
||||
wolfram_alpha_appid =
|
||||
jwt_secret =
|
||||
langsmith_api_key =
|
||||
|
||||
[cfg]
|
||||
base_superuser = "QQ|2596322644"
|
||||
|
|
@ -63,3 +64,5 @@ dice_output_len = 200
|
|||
dice_detail_cnt = 5
|
||||
dice_count_limit = 10
|
||||
api_port = 5000
|
||||
langsmith_endpoint = "https://api.smith.langchain.com"
|
||||
langsmith_project =
|
||||
|
|
|
|||
|
|
@ -1,99 +1,106 @@
|
|||
import io
|
||||
import re
|
||||
from decimal import Decimal
|
||||
|
||||
from PIL import Image as PILImage
|
||||
from langchain.callbacks import get_openai_callback
|
||||
|
||||
from config import Config
|
||||
from core.builtins import Bot, Plain, Image
|
||||
from core.component import module
|
||||
from core.dirty_check import check_bool, rickroll
|
||||
from database import BotDBUtil
|
||||
from .agent import agent_executor
|
||||
from .formatting import generate_latex, generate_code_snippet
|
||||
|
||||
ONE_K = Decimal('1000')
|
||||
# https://openai.com/pricing
|
||||
BASE_COST_GPT_3_5 = Decimal('0.002') # gpt-3.5-turbo： $0.002 / 1K tokens
|
||||
# We are not tracking specific tool usage like searches b/c I'm too lazy, use a universal multiplier
|
||||
THIRD_PARTY_MULTIPLIER = Decimal('1.5')
|
||||
PROFIT_MULTIPLIER = Decimal('1.1') # At the time we are really just trying to break even
|
||||
PRICE_PER_1K_TOKEN = BASE_COST_GPT_3_5 * THIRD_PARTY_MULTIPLIER * PROFIT_MULTIPLIER
|
||||
# Assuming 1 USD = 7.3 CNY, 100 petal = 1 CNY
|
||||
USD_TO_CNY = Decimal('7.3')
|
||||
CNY_TO_PETAL = 100
|
||||
|
||||
a = module('ask', developers=['Dianliang233'], desc='{ask.help.desc}')
|
||||
|
||||
|
||||
@a.command('<question> {{ask.help}}')
|
||||
@a.regex(r'^(?:question||问|問)[\:：]\s?(.+?)[?？]$', flags=re.I, desc='{ask.help.regex}')
|
||||
async def _(msg: Bot.MessageSession):
|
||||
is_superuser = msg.check_super_user()
|
||||
if not Config('openai_api_key'):
|
||||
raise Exception(msg.locale.t('error.config.secret.not_found'))
|
||||
if not is_superuser and msg.data.petal <= 0: # refuse
|
||||
await msg.finish(msg.locale.t('core.message.petal.no_petals') + Config('issue_url'))
|
||||
|
||||
qc = BotDBUtil.CoolDown(msg, 'call_openai')
|
||||
c = qc.check(60)
|
||||
if c == 0 or msg.target.target_from == 'TEST|Console' or is_superuser:
|
||||
if hasattr(msg, 'parsed_msg'):
|
||||
question = msg.parsed_msg['<question>']
|
||||
else:
|
||||
question = msg.matched_msg[0]
|
||||
if await check_bool(question):
|
||||
rickroll(msg)
|
||||
with get_openai_callback() as cb:
|
||||
res = await agent_executor.arun(question)
|
||||
tokens = cb.total_tokens
|
||||
if not is_superuser:
|
||||
price = tokens / ONE_K * PRICE_PER_1K_TOKEN
|
||||
petal = price * USD_TO_CNY * CNY_TO_PETAL
|
||||
msg.data.modify_petal(-petal)
|
||||
|
||||
blocks = parse_markdown(res)
|
||||
|
||||
chain = []
|
||||
for block in blocks:
|
||||
if block['type'] == 'text':
|
||||
chain.append(Plain(block['content']))
|
||||
elif block['type'] == 'latex':
|
||||
chain.append(Image(PILImage.open(io.BytesIO(await generate_latex(block['content'])))))
|
||||
elif block['type'] == 'code':
|
||||
chain.append(Image(PILImage.open(
|
||||
io.BytesIO(await generate_code_snippet(block['content']['code'], block['content']['language'])))))
|
||||
|
||||
if await check_bool(res):
|
||||
rickroll(msg)
|
||||
await msg.send_message(chain)
|
||||
|
||||
if msg.target.target_from != 'TEST|Console' and not is_superuser:
|
||||
qc.reset()
|
||||
else:
|
||||
await msg.finish(msg.locale.t('ask.message.cooldown', time=int(c)))
|
||||
|
||||
|
||||
def parse_markdown(md: str):
|
||||
regex = r'(```[\s\S]*?\n```|\$[\s\S]*?\$|[^\n]+)'
|
||||
|
||||
blocks = []
|
||||
for match in re.finditer(regex, md):
|
||||
content = match.group(1)
|
||||
print(content)
|
||||
if content.startswith('```'):
|
||||
block = 'code'
|
||||
try:
|
||||
language, code = re.match(r'```(.*)\n([\s\S]*?)\n```', content).groups()
|
||||
except AttributeError:
|
||||
raise ValueError('Code block is missing language or code')
|
||||
content = {'language': language, 'code': code}
|
||||
elif content.startswith('$'):
|
||||
block = 'latex'
|
||||
content = content[1:-1].strip()
|
||||
else:
|
||||
block = 'text'
|
||||
blocks.append({'type': block, 'content': content})
|
||||
|
||||
return blocks
|
||||
import io
|
||||
import os
|
||||
import re
|
||||
from decimal import Decimal
|
||||
|
||||
from PIL import Image as PILImage
|
||||
|
||||
from config import Config
|
||||
from core.builtins import Bot, Plain, Image
|
||||
from core.component import module
|
||||
from core.dirty_check import check_bool, rickroll
|
||||
from database import BotDBUtil
|
||||
|
||||
os.environ['LANGCHAIN_TRACING_V2'] = "true"
|
||||
os.environ['LANGCHAIN_ENDPOINT'] = Config('langsmith_endpoint')
|
||||
os.environ['LANGCHAIN_PROJECT'] = Config('langsmith_project')
|
||||
os.environ['LANGCHAIN_API_KEY'] = Config('langsmith_api_key')
|
||||
|
||||
from langchain.callbacks import get_openai_callback # noqa: E402
|
||||
from .agent import agent_executor # noqa: E402
|
||||
from .formatting import generate_latex, generate_code_snippet # noqa: E402
|
||||
|
||||
ONE_K = Decimal('1000')
|
||||
# https://openai.com/pricing
|
||||
BASE_COST_GPT_3_5 = Decimal('0.002') # gpt-3.5-turbo： $0.002 / 1K tokens
|
||||
# We are not tracking specific tool usage like searches b/c I'm too lazy, use a universal multiplier
|
||||
THIRD_PARTY_MULTIPLIER = Decimal('1.5')
|
||||
PROFIT_MULTIPLIER = Decimal('1.1') # At the time we are really just trying to break even
|
||||
PRICE_PER_1K_TOKEN = BASE_COST_GPT_3_5 * THIRD_PARTY_MULTIPLIER * PROFIT_MULTIPLIER
|
||||
# Assuming 1 USD = 7.3 CNY, 100 petal = 1 CNY
|
||||
USD_TO_CNY = Decimal('7.3')
|
||||
CNY_TO_PETAL = 100
|
||||
|
||||
a = module('ask', developers=['Dianliang233'], desc='{ask.help.desc}')
|
||||
|
||||
|
||||
@a.command('[--verbose] <question> {{ask.help}}')
|
||||
@a.regex(r'^(?:question||问|問)[\:：]\s?(.+?)[?？]$', flags=re.I, desc='{ask.help.regex}')
|
||||
async def _(msg: Bot.MessageSession):
|
||||
is_superuser = msg.check_super_user()
|
||||
if not Config('openai_api_key'):
|
||||
raise Exception(msg.locale.t('error.config.secret.not_found'))
|
||||
if not is_superuser and msg.data.petal <= 0: # refuse
|
||||
await msg.finish(msg.locale.t('core.message.petal.no_petals') + Config('issue_url'))
|
||||
|
||||
qc = BotDBUtil.CoolDown(msg, 'call_openai')
|
||||
c = qc.check(60)
|
||||
if c == 0 or msg.target.target_from == 'TEST|Console' or is_superuser:
|
||||
if hasattr(msg, 'parsed_msg'):
|
||||
question = msg.parsed_msg['<question>']
|
||||
else:
|
||||
question = msg.matched_msg[0]
|
||||
if await check_bool(question):
|
||||
rickroll(msg)
|
||||
with get_openai_callback() as cb:
|
||||
res = await agent_executor.arun(question)
|
||||
tokens = cb.total_tokens
|
||||
if not is_superuser:
|
||||
price = tokens / ONE_K * PRICE_PER_1K_TOKEN
|
||||
petal = price * USD_TO_CNY * CNY_TO_PETAL
|
||||
msg.data.modify_petal(-petal)
|
||||
|
||||
blocks = parse_markdown(res)
|
||||
|
||||
chain = []
|
||||
for block in blocks:
|
||||
if block['type'] == 'text':
|
||||
chain.append(Plain(block['content']))
|
||||
elif block['type'] == 'latex':
|
||||
chain.append(Image(PILImage.open(io.BytesIO(await generate_latex(block['content'])))))
|
||||
elif block['type'] == 'code':
|
||||
chain.append(Image(PILImage.open(
|
||||
io.BytesIO(await generate_code_snippet(block['content']['code'], block['content']['language'])))))
|
||||
|
||||
if await check_bool(res):
|
||||
rickroll(msg)
|
||||
await msg.send_message(chain)
|
||||
|
||||
if msg.target.target_from != 'TEST|Console' and not is_superuser:
|
||||
qc.reset()
|
||||
else:
|
||||
await msg.finish(msg.locale.t('ask.message.cooldown', time=int(c)))
|
||||
|
||||
|
||||
def parse_markdown(md: str):
|
||||
regex = r'(```[\s\S]*?\n```|\$[\s\S]*?\$|[^\n]+)'
|
||||
|
||||
blocks = []
|
||||
for match in re.finditer(regex, md):
|
||||
content = match.group(1)
|
||||
print(content)
|
||||
if content.startswith('```'):
|
||||
block = 'code'
|
||||
try:
|
||||
language, code = re.match(r'```(.*)\n([\s\S]*?)\n```', content).groups()
|
||||
except AttributeError:
|
||||
raise ValueError('Code block is missing language or code')
|
||||
content = {'language': language, 'code': code}
|
||||
elif content.startswith('$'):
|
||||
block = 'latex'
|
||||
content = content[1:-1].strip()
|
||||
else:
|
||||
block = 'text'
|
||||
blocks.append({'type': block, 'content': content})
|
||||
|
||||
return blocks
|
||||
|
|
|
|||
|
|
@ -1,21 +1,25 @@
|
|||
from langchain.agents import AgentExecutor
|
||||
from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
|
||||
from langchain.callbacks.stdout import StdOutCallbackHandler
|
||||
from langchain.chat_models import ChatOpenAI
|
||||
|
||||
from config import Config
|
||||
from modules.ask.prompt import system_message
|
||||
from modules.ask.tools import tools
|
||||
|
||||
llm = ChatOpenAI(
|
||||
model='gpt-3.5-turbo-0613',
|
||||
temperature=0,
|
||||
openai_api_key=Config('openai_api_key'),
|
||||
model_kwargs={
|
||||
'frequency_penalty': 0.0,
|
||||
'presence_penalty': 0.0})
|
||||
|
||||
agent = OpenAIFunctionsAgent.from_llm_and_tools(llm=llm, tools=tools,
|
||||
callback_manager=StdOutCallbackHandler, system_message=system_message)
|
||||
|
||||
agent_executor = AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True)
|
||||
from langchain.agents import AgentExecutor
|
||||
from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
|
||||
from langchain.callbacks import StdOutCallbackHandler
|
||||
from langchain.chat_models import ChatOpenAI
|
||||
|
||||
from config import Config
|
||||
from modules.ask.prompt import system_message
|
||||
from modules.ask.tools import tools
|
||||
|
||||
llm = ChatOpenAI(
|
||||
model='gpt-3.5-turbo-0613',
|
||||
temperature=0,
|
||||
openai_api_key=Config('openai_api_key'),
|
||||
model_kwargs={
|
||||
'frequency_penalty': 0.0,
|
||||
'presence_penalty': 0.0})
|
||||
|
||||
|
||||
agent = OpenAIFunctionsAgent.from_llm_and_tools(
|
||||
llm=llm,
|
||||
tools=tools,
|
||||
callback_manager=[StdOutCallbackHandler],
|
||||
system_message=system_message)
|
||||
|
||||
agent_executor = AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True)
|
||||
|
|
|
|||
Reference in a new issue