Log10
本頁面涵蓋如何在 LangChain 中使用 Log10。
什麼是 Log10?
Log10 是一個 開放原始碼、無代理伺服器的 LLM 資料管理和應用程式開發平台,可讓您記錄、偵錯和標記您的 Langchain 呼叫。
快速入門
- 在 log10.io 建立您的免費帳戶
- 從「設定」和「組織」標籤分別新增您的
LOG10_TOKEN
和LOG10_ORG_ID
作為環境變數。 - 也將
LOG10_URL=https://log10.io
和您常用的 LLM API 金鑰新增至您的環境,例如:OPENAI_API_KEY
或ANTHROPIC_API_KEY
如何為 Langchain 啟用 Log10 資料管理
與 log10 的整合是一個簡單的單行 log10_callback
整合,如下所示
from langchain_openai import ChatOpenAI
from langchain_core.messages import HumanMessage
from log10.langchain import Log10Callback
from log10.llm import Log10Config
log10_callback = Log10Callback(log10_config=Log10Config())
messages = [
HumanMessage(content="You are a ping pong machine"),
HumanMessage(content="Ping?"),
]
llm = ChatOpenAI(model="gpt-3.5-turbo", callbacks=[log10_callback])
API 參考:ChatOpenAI | HumanMessage
更多詳細資訊 + 螢幕截圖,包括自我託管日誌的說明
如何在 Log10 中使用標籤
from langchain_openai import OpenAI
from langchain_community.chat_models import ChatAnthropic
from langchain_openai import ChatOpenAI
from langchain_core.messages import HumanMessage
from log10.langchain import Log10Callback
from log10.llm import Log10Config
log10_callback = Log10Callback(log10_config=Log10Config())
messages = [
HumanMessage(content="You are a ping pong machine"),
HumanMessage(content="Ping?"),
]
llm = ChatOpenAI(model="gpt-3.5-turbo", callbacks=[log10_callback], temperature=0.5, tags=["test"])
completion = llm.predict_messages(messages, tags=["foobar"])
print(completion)
llm = ChatAnthropic(model="claude-2", callbacks=[log10_callback], temperature=0.7, tags=["baz"])
llm.predict_messages(messages)
print(completion)
llm = OpenAI(model_name="gpt-3.5-turbo-instruct", callbacks=[log10_callback], temperature=0.5)
completion = llm.predict("You are a ping pong machine.\nPing?\n")
print(completion)
您也可以混合使用直接 OpenAI 呼叫和 Langchain LLM 呼叫
import os
from log10.load import log10, log10_session
import openai
from langchain_openai import OpenAI
log10(openai)
with log10_session(tags=["foo", "bar"]):
# Log a direct OpenAI call
response = openai.Completion.create(
model="text-ada-001",
prompt="Where is the Eiffel Tower?",
temperature=0,
max_tokens=1024,
top_p=1,
frequency_penalty=0,
presence_penalty=0,
)
print(response)
# Log a call via Langchain
llm = OpenAI(model_name="text-ada-001", temperature=0.5)
response = llm.predict("You are a ping pong machine.\nPing?\n")
print(response)
API 參考:OpenAI