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MIGRATION.md

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Migrations

v4.x to v5.0.0

Phoenix 5 introduces authentication. By default authentication is disabled and Phoenix will operate exactly as previous versions. Phoenix's authentication is designed to be as flexible as possible and can be adopted incrementally.

With authentication enabled, all API and UI access will be gated with credentials or API keys. Because of this, you will encounter some down time so please plan accordingly.

Phoenix 5 also fully de-couples instrumentation from the Phoenix package. All instrumentation should be installed and run via the OpenInference package. This allows for more flexibility in instrumentation and allows Phoenix to focus on its core functionality.

Enabling Authentication

To get started, simply set two environment variables for your deployment:

export PHOENIX_ENABLE_AUTH=True
export PHOENIX_SECRET=a-sufficiently-long-secret

Once these environment variables are set, Phoenix scaffold and admin login and the entire server will be protected. Log in as the admin user and create a system key to use with your application(s). All API keys should be added as headers to your requests via the Authorization header using the Bearer scheme.

For more details, please see the authentication setup guide.

Migrating to OpenInference

If you are using Phoenix's phoenix.trace modules for LlamaIndex, LangChain, or OpenAI, you will need to migrate to OpenInference. OpenInference is a separate set of packages that provides instrumentation for Phoenix. Phoenix 5 no longer supports LlamaIndex or LangChain instrumentation from the phoenix.trace module.

Phoenix now includes a phoenix.otel module that provides simplified setup for OpenTelemetry. See the phoenix.otel documentation for more details.

Before

from phoenix.trace.openai import OpenAIInstrumentor

OpenAIInstrumentor().instrument()

After

from openinference.instrumentation.openai import OpenAIInstrumentor

OpenAIInstrumentor().instrument(tracer_provider=tracer_provider)

For an extensive list of supported instrumentation, please see the OpenInference

v3.x to v4.0.0

Migrating from legacy phoenix.Dataset to phoenix.Inferences

  • phoenix.Dataset has been renamed to phoenix.Inferences
  • phoenix.ExampleDataset has been renamed to phoenix.ExampleInferences
  • All other methods and related functions and classes remain under the phoenix namespace

Old

from phoenix import Dataset, ExampleDataset

New

from phoenix import Inferences, ExampleInferences

Migrating from phoenix.experimental.evals to phoenix.evals

  • Phoenix has now moved promoted the evals module out of experimental and can be installed as a separate extra.

Installing and Using the evals module

Old

pip install arize-phoenix[experimental]
from phoenix.experimental.evals import OpenAIModel
from phoenix.experimental.evals import llm_classify

model = OpenAIModel()

New

pip install arize-phoenix[evals]
from phoenix.evals import OpenAIModel
from phoenix.evals import llm_classify

Token counting has been removed evals

Old

from phoenix.experimental.evals import OpenAIModel
from phoenix.experimental.evals import processing # no longer supported in phoenix.evals

model = OpenAIModel()
model.max_context_size  # no longer supported in phoenix.evals
model.get_token_count_from_messages(...)  # no longer supported in phoenix.evals
model.get_tokens_from_text(...)  # no longer supported in phoenix.evals
model.get_text_from_tokens(...)  # no longer supported in phoenix.evals

BaseEvalModel has been renamed to BaseModel

When implementing a custom model wrapper for use with Phoenix, the base class has been renamed.

Old

from phoenix.experimental.evals.models import BaseEvalModel  # renamed to BaseModel

New

from phoenix.evals.models import BaseModel

Some modules in phoenix.evals have been relocated and renamed

Old

from phoenix.experimental.evals.functions import classify, generate
from phoenix.experimental.evals.templates import default_templates, template

New

from phoenix.evals import classify, generate
from phoenix.evals import default_templates, templates

v2.x to v3.0.0

  • v3.0.0 - Phoenix now exclusively uses OpenInference for instrumentation. OpenInference uses OpenTelemetry Protocol as the means for sending traces to a collector.

OpenAI Tracing

phoenix.trace.tracer.Tracer is defunct and should be removed.

Old (v2.x)
from phoenix.trace.exporter import HttpExporter  # no longer necessary
from phoenix.trace.openai import OpenAIInstrumentor
from phoenix.trace.tracer import Tracer  # no longer supported

tracer = Tracer(exporter=HttpExporter())  # no longer supported
OpenAIInstrumentor(tracer).instrument()  # tracer argument is no longer supported
New (v3.0.0)
from phoenix.trace.openai import OpenAIInstrumentor

OpenAIInstrumentor().instrument()

Endpoint should be configured via environment variables PHOENIX_HOST, PHOENIX_PORT, or PHOENIX_COLLECTOR_ENDPOINT.

Old (v2.x)
from phoenix.trace.exporter import HttpExporter  # no longer necessary
from phoenix.trace.openai import OpenAIInstrumentor
from phoenix.trace.tracer import Tracer  # no longer supported

tracer = Tracer(exporter=HttpExporter(port=12345))  # no longer supported
OpenAIInstrumentor(tracer).instrument()  # tracer argument is no longer supported
New (v3.0.0)
import os
from phoenix.trace.openai import OpenAIInstrumentor

os.environ["PHOENIX_PORT"] = "12345"
OpenAIInstrumentor().instrument()

Calling .get_spans() on a tracer is no longer supported. Use px.Client() to get the spans as a dataframe from Phoenix.

Old (v2.x)
from phoenix.trace.trace_dataset import TraceDataset  # no longer necessary
from phoenix.trace.tracer import Tracer  # no longer supported

tracer = Tracer()  # no longer supported
TraceDataset.from_spans(tracer.get_spans())  # no longer supported
New (v3.0.0)
import phoenix as px

px.Client().get_spans_dataframe()

LlamaIndex Tracing

The standard way of instrumenting your LlamaIndex application remains the same between 2.x and 3.x:

from llama_index import set_global_handler

set_global_handler("arize_phoenix")

User should not pass Phoenix handler to a callback manager. Use the set_global_handler method above.

from llama_index.callbacks import CallbackManager  # no longer necessary
from phoenix.trace.llama_index import OpenInferenceTraceCallbackHandler  # no longer supported

callback_handler = OpenInferenceTraceCallbackHandler()  # no longer supported
CallbackManager(handlers=[callback_handler])  # no longer supported

Endpoint should be configured via environment variables PHOENIX_HOST, PHOENIX_PORT, or PHOENIX_COLLECTOR_ENDPOINT.

Old (v2.x)
from llama_index import set_global_handler
from phoenix.trace.exporter import HttpExporter  # no longer necessary

exporter = HttpExporter(host="127.0.0.1", port=6007)  # no longer supported
set_global_handler("arize_phoenix", exporter=exporter)

New (v3.0.0)

import os
from llama_index import set_global_handler

os.environ["PHOENIX_HOST"] = "127.0.0.1"
os.environ["PHOENIX_PORT"] = "6007"
set_global_handler("arize_phoenix")

Calling .get_spans() on a handler is no longer supported. Use px.Client() to get the spans as a dataframe from Phoenix.

Old (v2.x)

from phoenix.trace.trace_dataset import TraceDataset  # no longer necessary
from phoenix.trace.llama_index import OpenInferenceTraceCallbackHandler  # no longer supported

handler = OpenInferenceTraceCallbackHandler()  # no longer supported
TraceDataset.from_spans(handler.get_spans())  # .get_spans() no longer supported
New (v3.0.0)
import phoenix as px

px.Client().get_spans_dataframe()

LangChain Tracing

phoenix.trace.langchain.OpenInferenceTracer is defunct and should be removed.

Old (v2.x)
from phoenix.trace.langchain import LangChainInstrumentor, OpenInferenceTracer

tracer = OpenInferenceTracer()  # no longer supported
LangChainInstrumentor(tracer).instrument()  # tracer argument is no longer supported
New (v3.0.0)
from phoenix.trace.langchain import LangChainInstrumentor

LangChainInstrumentor().instrument()

Endpoint should be configured via environment variables PHOENIX_HOST, PHOENIX_PORT, or PHOENIX_COLLECTOR_ENDPOINT.

Old (v2.x)
from phoenix.trace.exporter import HttpExporter  # no longer necessary
from phoenix.trace.langchain import LangChainInstrumentor, OpenInferenceTracer

tracer = OpenInferenceTracer(exporter=HttpExporter(port=12345))  # no longer supported
LangChainInstrumentor(tracer).instrument()
New (v3.0.0)
from phoenix.trace.langchain import LangChainInstrumentor

os.environ["PHOENIX_PORT"] = "12345"
LangChainInstrumentor().instrument()

Calling .get_spans() on a tracer is no longer supported. Use px.Client() to get the spans as a dataframe from Phoenix.

Old (v2.x)
from phoenix.trace.trace_dataset import TraceDataset  # no longer necessary
from phoenix.trace.langchain import OpenInferenceTracer  # no longer supported

tracer = OpenInferenceTracer()  # no longer supported
TraceDataset.from_spans(tracer.get_spans())  # .get_spans() no longer supported
New (v3.0.0)
import phoenix as px

px.Client().get_spans_dataframe()

v0.x to v1.0.0

  • v1.0.0 - Phoenix now exclusively supports the openai>=1.0.0 sdk. If you are using an older version of the OpenAI SDK, you can continue to use arize-phoenix==0.1.1. However, we recommend upgrading to the latest version of the OpenAI SDK as it contains many improvements. If you are using Phoenix with LlamaIndex and and LangChain, you will have to upgrade to the versions of these packages that support the OpenAI 1.0.0 SDK as well (llama-index>=0.8.64, langchain>=0.0.334)