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Maxim Python Library

Project description

Maxim SDK

This is Python SDK for enabling Maxim observability. Maxim is an enterprise grade evaluation and observability platform.

How to integrate

Install

pip install maxim-py

Initialize Maxim logger

from maxim.maxim import Maxim

maxim = Maxim(Config(apiKey=apiKey))

Start sending traces

from maxim.logger.logger import LoggerConfig
# Initializing logger
logger = maxim.logger(LoggerConfig(id="log-repository-id"))
# Initializing a new trace
trace = logger.trace(TraceConfig(id="trace-id",name="trace-name",tags={"key":"value"}))
# Creating the generation
generation = trace.generation(GenerationConfig(id=str(uuid4()), model="text-davinci-002", provider="azure", model_parameters={"temperature": 0.7, "max_tokens": 100}))
# Making LLM call
completion = self.client.completions.create(
   model="text-davinci-002",
   prompt="Translate the following English text to French: 'Hello, how are you?'",
   max_tokens=100,
   temperature=0.7
)
# Updating generation
generation.result(completion)
# Ending trace
trace.end()

Integrations with other frameworks

Langchain

We have built in Langchain tracer support

logger = self.maxim.logger(LoggerConfig(id=repoId))
trace_id = str(uuid4())
trace = logger.trace(TraceConfig(
   id=trace_id, name="pre-defined-trace"))

model = OpenAI(callbacks=[MaximLangchainTracer(logger)],api_key=openAIKey)
messages = [
   (
         "system",
         "You are a helpful assistant that translates English to French. Translate the user sentence.",
   ),
   ("human", "I love programming."),
]
model.invoke(messages, config={
   "metadata": {
         "maxim": {
            "trace_id": trace_id,
            "generation_name": "get-answer",
            "generation_tags": {
               "test": "123"
            }
         }
   }
})
trace.event(id=str(uuid4()), name="test event")
trace.end()

Version changelog

v1.5.4

  • Improvement - Improved fs access checks.
  • Improvement - Fixes threading locks for periodic syncs in Python3.9

v1.5.3

  • Improvement - Adds lambda env support for SDK with no access to filesystem.

v1.5.2

  • Feature - Adds support to new langchain_openai.AzureChatOpenAI class in langchain tracer

v1.5.1

  • Fix - Adds Python 3.9 compatibility

v1.5.0

  • Improvement - Updates connection pool to use session that enforces re-connects before making API calls.

v1.4.5

  • Improvement - Adds backoff retries to failed REST calls.

v1.4.4

  • Improvement - langchain becomes optional dependency

v1.4.3

  • Fix - connection pooling for network calls.
  • Fix - connection close issue.

v1.4.2 (🚧 Yanked)

  • Fix - connection close issue

v1.4.1

  • Adds validation for provider in generation

v1.4.0

  • Now generation.result accepts
    • OpenAI chat completion object
    • Azure OpenAI chat completion object
    • Langchain LLMResult, AIMessage object

v1.3.4

  • Fixes message_parser

v1.3.2

  • Fixes utility function for langchain to parse AIMessage into Maxim logger completion result

v1.3.1

  • Adds tool call parsing support for Langchain tracer

v1.3.0

  • Adds support for ChatCompletion in generations
  • Adds type safety for retrieval results

v1.2.7

  • Bug fix where input sent with trace.config was getting overridden with None

v1.2.6

  • Adds trace.set_input and trace.set_output methods to control what to show in logs dashboard

v1.2.5

  • Removes one no_op command while creating spans
  • Minor bug fixes

v1.2.1

  • Fixed MaximLangchainTracer error logging flow.

v1.2.0

  • Adds langchain support
  • Adds local parsers to validate payloads on client side

v1.1.0

  • Minor bug fixes around log writer cleanup

v1.0.0

  • Public release

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