Integration: Context AI
A component to log conversations for analytics by Context.ai - built for Haystack 2.0.
Table of Contents
Overview
Context.ai is an evaluations and analytics tool for products powered by LLMs.
With Context.ai, you can understand how your users are interacting with natural language interfaces. This helps you know where your customers are having great experiences, but also proactively detect potential areas of improvement. You can test the performance impact of changes before you ship them to production with evaluations, and can identify where inappropriate conversations taking place.
Login to Context Dashboard to create a token and see your analytics.
Installation
pip install --upgrade context-haystack
Usage
Components
The ContextAIAnalytics component allows you to seamlessly integrate with Context.ai, uploading your messages to the Context AI platform.
When running your pipeline you must include thread_id in the parameters where each unique thread_id identifies a conversation. You can optionally include metadata with user_id and model reserved for special analytics.
Use an instance of the ContextAIAnalytics component at each stage of your pipeline where you wish to log a message. In the example below the output of the prompt_builder and the llm components are captured.
Example
import uuid
import os
from haystack.components.generators.chat import OpenAIChatGenerator
from haystack.components.builders import DynamicChatPromptBuilder
from haystack import Pipeline
from haystack.dataclasses import ChatMessage
from context_haystack.context import ContextAIAnalytics
model = "gpt-3.5-turbo"
os.environ["GETCONTEXT_TOKEN"] = "GETCONTEXT_TOKEN"
os.environ["OPENAI_API_KEY"] = "OPENAI_API_KEY"
prompt_builder = DynamicChatPromptBuilder()
llm = OpenAIChatGenerator(model=model)
prompt_analytics = ContextAIAnalytics()
assistant_analytics = ContextAIAnalytics()
pipe = Pipeline()
pipe.add_component("prompt_builder", prompt_builder)
pipe.add_component("llm", llm)
pipe.add_component("prompt_analytics", prompt_analytics)
pipe.add_component("assistant_analytics", assistant_analytics)
pipe.connect("prompt_builder.prompt", "llm.messages")
pipe.connect("prompt_builder.prompt", "prompt_analytics")
pipe.connect("llm.replies", "assistant_analytics")
# thread_id is unique to each conversation
context_parameters = {"thread_id": uuid.uuid4(), "metadata": {"model": model, "user_id": "1234"}}
location = "Berlin"
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": location}, "prompt_source": messages},
"prompt_analytics": context_parameters,
"assistant_analytics": context_parameters,
}
)
print(response)
License
context-haystack is distributed under the terms of the
Apache-2.0 license.