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Langfuse

Mirascope provides out-of-the-box integration with Langfuse.

You can install the necessary packages directly or using the langfuse extras flag:

pip install "mirascope[langfuse]"

You can then use the with_langfuse decorator to automatically log calls:

from mirascope.core import openai
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@openai.call("gpt-4o-mini")
def recommend_book(genre: str) -> str:
    return f"Recommend a {genre} book."


print(recommend_book("fantasy"))

from mirascope.core import anthropic
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@anthropic.call("claude-3-5-sonnet-20240620")
def recommend_book(genre: str) -> str:
    return f"Recommend a {genre} book"


print(recommend_book("fantasy"))

from mirascope.core import mistral
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@mistral.call("mistral-large-latest")
def recommend_book(genre: str) -> str:
    return f"Recommend a {genre} book"


print(recommend_book("fantasy"))

from mirascope.core import gemini
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@gemini.call("gemini-1.5-flash")
def recommend_book(genre: str) -> str:
    return f"Recommend a {genre} book"


print(recommend_book("fantasy"))

from mirascope.core import groq
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@groq.call("llama-3.1-70b-versatile")
def recommend_book(genre: str) -> str:
    return f"Recommend a {genre} book"


print(recommend_book("fantasy"))

from mirascope.core import cohere
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@cohere.call("command-r-plus")
def recommend_book(genre: str) -> str:
    return f"Recommend a {genre} book"


print(recommend_book("fantasy"))

from mirascope.core import litellm
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@litellm.call("gpt-4o-mini")
def recommend_book(genre: str) -> str:
    return f"Recommend a {genre} book"


print(recommend_book("fantasy"))

from mirascope.core import azure
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@azure.call("gpt-4o-mini")
def recommend_book(genre: str) -> str:
    return f"Recommend a {genre} book"


print(recommend_book("fantasy"))

from mirascope.core import vertex
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@vertex.call("gemini-1.5-flash")
def recommend_book(genre: str) -> str:
    return f"Recommend a {genre} book"


print(recommend_book("fantasy"))

from mirascope.core import bedrock
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@bedrock.call("anthropic.claude-3-haiku-20240307-v1:0")
def recommend_book(genre: str) -> str:
    return f"Recommend a {genre} book."


print(recommend_book("fantasy"))

from mirascope.core import Messages, openai
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@openai.call("gpt-4o-mini")
def recommend_book(genre: str) -> Messages.Type:
    return Messages.User(f"Recommend a {genre} book.")


print(recommend_book("fantasy"))

from mirascope.core import Messages, anthropic
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@anthropic.call("claude-3-5-sonnet-20240620")
def recommend_book(genre: str) -> Messages.Type:
    return Messages.User(f"Recommend a {genre} book")


print(recommend_book("fantasy"))

from mirascope.core import Messages, mistral
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@mistral.call("mistral-large-latest")
def recommend_book(genre: str) -> Messages.Type:
    return Messages.User(f"Recommend a {genre} book")


print(recommend_book("fantasy"))

from mirascope.core import Messages, gemini
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@gemini.call("gemini-1.5-flash")
def recommend_book(genre: str) -> Messages.Type:
    return Messages.User(f"Recommend a {genre} book")


print(recommend_book("fantasy"))

from mirascope.core import Messages, groq
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@groq.call("llama-3.1-70b-versatile")
def recommend_book(genre: str) -> Messages.Type:
    return Messages.User(f"Recommend a {genre} book")


print(recommend_book("fantasy"))

from mirascope.core import Messages, cohere
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@cohere.call("command-r-plus")
def recommend_book(genre: str) -> Messages.Type:
    return Messages.User(f"Recommend a {genre} book")


print(recommend_book("fantasy"))

from mirascope.core import Messages, litellm
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@litellm.call("gpt-4o-mini")
def recommend_book(genre: str) -> Messages.Type:
    return Messages.User(f"Recommend a {genre} book")


print(recommend_book("fantasy"))

from mirascope.core import Messages, azure
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@azure.call("gpt-4o-mini")
def recommend_book(genre: str) -> Messages.Type:
    return Messages.User(f"Recommend a {genre} book")


print(recommend_book("fantasy"))

from mirascope.core import Messages, vertex
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@vertex.call("gemini-1.5-flash")
def recommend_book(genre: str) -> Messages.Type:
    return Messages.User(f"Recommend a {genre} book")


print(recommend_book("fantasy"))

from mirascope.core import Messages, bedrock
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@bedrock.call("anthropic.claude-3-haiku-20240307-v1:0")
def recommend_book(genre: str) -> Messages.Type:
    return Messages.User(f"Recommend a {genre} book.")


print(recommend_book("fantasy"))

from mirascope.core import openai, prompt_template
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@openai.call("gpt-4o-mini")
@prompt_template("Recommend a {genre} book")
def recommend_book(genre: str): ...


print(recommend_book("fantasy"))

from mirascope.core import anthropic, prompt_template
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@anthropic.call("claude-3-5-sonnet-20240620")
@prompt_template("Recommend a {genre} book")
def recommend_book(genre: str): ...


print(recommend_book("fantasy"))

from mirascope.core import mistral, prompt_template
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@mistral.call("mistral-large-latest")
@prompt_template("Recommend a {genre} book")
def recommend_book(genre: str): ...


print(recommend_book("fantasy"))

from mirascope.core import gemini, prompt_template
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@gemini.call("gemini-1.5-flash")
@prompt_template("Recommend a {genre} book")
def recommend_book(genre: str): ...


print(recommend_book("fantasy"))

from mirascope.core import groq, prompt_template
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@groq.call("llama-3.1-70b-versatile")
@prompt_template("Recommend a {genre} book")
def recommend_book(genre: str): ...


print(recommend_book("fantasy"))

from mirascope.core import cohere, prompt_template
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@cohere.call("command-r-plus")
@prompt_template("Recommend a {genre} book")
def recommend_book(genre: str): ...


print(recommend_book("fantasy"))

from mirascope.core import litellm, prompt_template
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@litellm.call("gpt-4o-mini")
@prompt_template("Recommend a {genre} book")
def recommend_book(genre: str): ...


print(recommend_book("fantasy"))

from mirascope.core import azure, prompt_template
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@azure.call("gpt-4o-mini")
@prompt_template("Recommend a {genre} book")
def recommend_book(genre: str): ...


print(recommend_book("fantasy"))

from mirascope.core import prompt_template, vertex
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@vertex.call("gemini-1.5-flash")
@prompt_template("Recommend a {genre} book")
def recommend_book(genre: str): ...


print(recommend_book("fantasy"))

from mirascope.core import bedrock, prompt_template
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@bedrock.call("anthropic.claude-3-haiku-20240307-v1:0")
@prompt_template("Recommend a {genre} book")
def recommend_book(genre: str): ...


print(recommend_book("fantasy"))

from mirascope.core import BaseMessageParam, openai
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@openai.call("gpt-4o-mini")
def recommend_book(genre: str) -> list[BaseMessageParam]:
    return [BaseMessageParam(role="user", content=f"Recommend a {genre} book.")]


print(recommend_book("fantasy"))

from mirascope.core import BaseMessageParam, anthropic
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@anthropic.call("claude-3-5-sonnet-20240620")
def recommend_book(genre: str) -> list[BaseMessageParam]:
    return [BaseMessageParam(role="user", content=f"Recommend a {genre} book")]


print(recommend_book("fantasy"))

from mirascope.core import BaseMessageParam, mistral
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@mistral.call("mistral-large-latest")
def recommend_book(genre: str) -> list[BaseMessageParam]:
    return [BaseMessageParam(role="user", content=f"Recommend a {genre} book")]


print(recommend_book("fantasy"))

from mirascope.core import BaseMessageParam, gemini
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@gemini.call("gemini-1.5-flash")
def recommend_book(genre: str) -> list[BaseMessageParam]:
    return [BaseMessageParam(role="user", content=f"Recommend a {genre} book")]


print(recommend_book("fantasy"))

from mirascope.core import BaseMessageParam, groq
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@groq.call("llama-3.1-70b-versatile")
def recommend_book(genre: str) -> list[BaseMessageParam]:
    return [BaseMessageParam(role="user", content=f"Recommend a {genre} book")]


print(recommend_book("fantasy"))

from mirascope.core import BaseMessageParam, cohere
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@cohere.call("command-r-plus")
def recommend_book(genre: str) -> list[BaseMessageParam]:
    return [BaseMessageParam(role="user", content=f"Recommend a {genre} book")]


print(recommend_book("fantasy"))

from mirascope.core import BaseMessageParam, litellm
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@litellm.call("gpt-4o-mini")
def recommend_book(genre: str) -> list[BaseMessageParam]:
    return [BaseMessageParam(role="user", content=f"Recommend a {genre} book")]


print(recommend_book("fantasy"))

from mirascope.core import BaseMessageParam, azure
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@azure.call("gpt-4o-mini")
def recommend_book(genre: str) -> list[BaseMessageParam]:
    return [BaseMessageParam(role="user", content=f"Recommend a {genre} book")]


print(recommend_book("fantasy"))

from mirascope.core import BaseMessageParam, vertex
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@vertex.call("gemini-1.5-flash")
def recommend_book(genre: str) -> list[BaseMessageParam]:
    return [BaseMessageParam(role="user", content=f"Recommend a {genre} book")]


print(recommend_book("fantasy"))

from mirascope.core import BaseMessageParam, bedrock
from mirascope.integrations.langfuse import with_langfuse


@with_langfuse()
@bedrock.call("anthropic.claude-3-haiku-20240307-v1:0")
def recommend_book(genre: str) -> list[BaseMessageParam]:
    return [BaseMessageParam(role="user", content=f"Recommend a {genre} book.")]


print(recommend_book("fantasy"))

This will give you:

  • A trace around the recommend_book function that captures items like the prompt template, and input/output attributes and more.
  • Human-readable display of the conversation with the agent
  • Details of the response, including the number of tokens used
Example trace

logfire-call

Handling streams

When logging streams, the span will not be logged until the stream has been exhausted. This is a function of how streaming works.

You will also need to set certain call_params for usage to be tracked for certain providers (such as OpenAI).