and toolkitsMemoryCallbacksChat loadersProvidersMoreLog10On this pageLog10This page covers how to use the Log10 within LangChain.What is Log10?‚ÄãLog10 is an open-source proxiless LLM data management and application development platform that lets you log, debug and tag your Langchain calls.Quick start‚ÄãCreate your free account at log10.ioAdd your LOG10_TOKEN and LOG10_ORG_ID from the Settings and Organization tabs respectively as environment variables.Also add LOG10_URL=https://log10.io and your usual LLM API key: for e.g. OPENAI_API_KEY or ANTHROPIC_API_KEY to your environmentHow to enable Log10 data management for Langchain‚ÄãIntegration with log10 is a simple one-line log10_callback integration as shown below:from langchain.chat_models import ChatOpenAIfrom langchain.schema import HumanMessagefrom log10.langchain import Log10Callbackfrom log10.llm import Log10Configlog10_callback = Log10Callback(log10_config=Log10Config())messages = [    HumanMessage(content="You are a ping pong machine"),    HumanMessage(content="Ping?"),]llm = ChatOpenAI(model_name="gpt-3.5-turbo", callbacks=[log10_callback])Log10 + Langchain + Logs docsMore details + screenshots including instructions for self-hosting logsHow to use tags with Log10‚Äãfrom langchain.llms import OpenAIfrom langchain.chat_models import ChatAnthropicfrom langchain.chat_models import ChatOpenAIfrom langchain.schema import HumanMessagefrom log10.langchain import Log10Callbackfrom log10.llm import Log10Configlog10_callback = Log10Callback(log10_config=Log10Config())messages = [    HumanMessage(content="You are a ping pong machine"),    HumanMessage(content="Ping?"),]llm = ChatOpenAI(model_name="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 =
This page covers how to use the Log10 within LangChain.
This page covers how to use the Log10 within LangChain. ->: and toolkitsMemoryCallbacksChat loadersProvidersMoreLog10On this pageLog10This page covers how to use the Log10 within LangChain.What is Log10?‚ÄãLog10 is an open-source proxiless LLM data management and application development platform that lets you log, debug and tag your Langchain calls.Quick start‚ÄãCreate your free account at log10.ioAdd your LOG10_TOKEN and LOG10_ORG_ID from the Settings and Organization tabs respectively as environment variables.Also add LOG10_URL=https://log10.io and your usual LLM API key: for e.g. OPENAI_API_KEY or ANTHROPIC_API_KEY to your environmentHow to enable Log10 data management for Langchain‚ÄãIntegration with log10 is a simple one-line log10_callback integration as shown below:from langchain.chat_models import ChatOpenAIfrom langchain.schema import HumanMessagefrom log10.langchain import Log10Callbackfrom log10.llm import Log10Configlog10_callback = Log10Callback(log10_config=Log10Config())messages = [    HumanMessage(content="You are a ping pong machine"),    HumanMessage(content="Ping?"),]llm = ChatOpenAI(model_name="gpt-3.5-turbo", callbacks=[log10_callback])Log10 + Langchain + Logs docsMore details + screenshots including instructions for self-hosting logsHow to use tags with Log10‚Äãfrom langchain.llms import OpenAIfrom langchain.chat_models import ChatAnthropicfrom langchain.chat_models import ChatOpenAIfrom langchain.schema import HumanMessagefrom log10.langchain import Log10Callbackfrom log10.llm import Log10Configlog10_callback = Log10Callback(log10_config=Log10Config())messages = [    HumanMessage(content="You are a ping pong machine"),    HumanMessage(content="Ping?"),]llm = ChatOpenAI(model_name="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 =