weave-haystack 0.0.1

An integration of Weights & Biases Weave tracer with Haystack

weave-haystack

• Installation
• Example
• License

Installation

pip install weave-haystack

Weave by Weights & Biases

Example

You need to have a Weave account to use this feature. You can sign up for free at https://wandb.ai/site.

You then need to set the WANDB_API_KEY: environment variable with your Weights & Biases API key. You should find your API key in https://wandb.ai/home when you are logged in.

You should then head to https://wandb.ai/<user_name>/projects and see the complete trace for your pipeline under the pipeline name you specified, when creating the WeaveConnector.

You also need to have the HAYSTACK_CONTENT_TRACING_ENABLED environment variable set to true.

To use this connector simply add it to your pipeline without any connections, and it will automatically start sending traces to Weights & Biases.

import os

from haystack import Pipeline
from haystack.components.builders import ChatPromptBuilder
from haystack.components.generators.chat import OpenAIChatGenerator
from haystack.dataclasses import ChatMessage

from haystack_integrations.components.connectors import WeaveConnector

os.environ["HAYSTACK_CONTENT_TRACING_ENABLED"] = "true"

pipe = Pipeline()
pipe.add_component("prompt_builder", ChatPromptBuilder())
pipe.add_component("llm", OpenAIChatGenerator(model="gpt-3.5-turbo"))
pipe.connect("prompt_builder.prompt", "llm.messages")

connector = WeaveConnector(pipeline_name="test_pipeline")
pipe.add_component("weave", connector)

messages = [
    ChatMessage.from_system(
        "Always respond in German even if some input data is in other languages."
    ),
    ChatMessage.from_user("Tell me about {{location}}"),
]

response = pipe.run(
    data={
        "prompt_builder": {
            "template_variables": {"location": "Berlin"},
            "template": messages,
        }
    }
)
print(response["llm"]["replies"][0])

License

weave-haystack is distributed under the terms of the Apache-2.0 license.