🗺 prompt playground

[mikeldking]

As a user of Phoenix I don't want to have to go back to my IDE to iterate on a prompt. I want to be able to use the data stored in Phoenix (spans, dataets) and run them through a prompt.

Use-cases

• Replay a template change on an LLM Span
• Run a template change on a dataset
• Construct an evaluation template on a single chosen production span or Dataset - Workflow is testing your Evals and be able to save as experiment
• Synthetic data Generation - Use to generate synthetic data, add columns to current rows of data in a dataset, to help create test data

Milestone 1 - LLM Replay

The most important thing to accomplish is the ability to take a specific LLM step (e.g. a span) and to be able to re-play that execution. In the process of re-executing that step, we should record the new response so that we can compare and evaluate.

Leads: @axiomofjoy @anticorrelator

Out of Scope

• focus on Chat Completions (things with roles) - not completions

Planning

• [playground] PRD #4658
• [playground][spike] API design for chat completions #4600

UI

• [playground][ui] UI skeleton and feature flag #4606
• [playground][ui] credential storage #4885
• [playground][ui] edit message role #4857
• [playground] llm span to playground parameter parsing utils #4886
• [playground][ui] edit model (e.g. model selector) #4887
• [playground][ui] mustache template editor for codemirror #4888
• [playground][ui] f-string vs mustache template formatting toggle #4889
• [playground][ui] f-string variable parsing utility function #4890
• [playground] Toggle to switch between f-string and mustache #4996
• [playground][ui] mustache template variable parsing utility function #5092
• [playground][ui] template variables (e.g. inputs) UI and storage #4891
• [playground][ui] message re-ordering via drag and drop #4892
• [playground][ui] add new tool UI #4902
• [playground][ui] UI for metrics for a chat completion (token count, latency) #5183
• [playground][ui] display playground instances in "alphabetic" order #4949
• [playground][ui] switch Input to be singular across all prompts / instances #4952
• [playground][ui] Provide a back button if coming from a span #4953
• [playground][ui] UI and playground store parsing of variables #4986
• [playground][ui] UI for editing input variables via resizing text area #4987
• [playground] copy prompt to clipboard button #4997
• [playground] parse and infer model config from span #4998
• [playground][ui] support function / tool call messages #5041
• [playground][ui] suppport function / tool call parsing from spans #5020
• [playground][ui] support azure params endpoint and api version #5023
• [playground] apply template variables when invoking the template #5034
• [playground][ui] invocation parameters ui #5040
• [playground] don't allow blank variable values before run (form validation)
• [playground][ui] create a non-streaming version of the playground #5181
• [playground] detect when phoenix is running in an environment that doesn't support streaming #5182
• [playground][ui] save off model config by provider and use as default in playground #5069
• [playground][ui] show token count, latency, after completing the invocation #5036
• [playground][ui] annotation slide-over #5035
• [playground] pull span information once the span is completed (e.g. latency, tokens) #5099
• [playground] tool JSON schema utils (anthropic -> open_ai -> ???) #5100
• [playground] option to view output as markdown #5112
• [playground][ui] support anthropic tool calls in playground #5209
• [playground][ui] support anthropic tools in playground #5210
• [playground][ui] add structured output support #5233
• [playground][ui] plumb through json invocation parameters #5252
• [playground][ui] create empty state for playground when no llm providers are installed on server #5253

API

• [playground][api] prototype a subscription for chat completion #4773
• [playground][api] use mutations to submit a chat completion #4774
• [playground][gql] invocation parameters to chat completion #4858
• [playground][api] Models and vendors listing resolver #4859
• [playground][api] websocket authentication #4793
• [playground][gql] LLM span recording of chat completions (persistence) #4856
• [playground][gql] server side messages input and roles #4893
• [playground][backend] span recording in the DB in the playground project #4894
• [playground][gql] model input to chat completion #4900
• [playground][gql] tool definition input to chat completion #5093
• [playground][gql] support for output schema (e.g. JSON mode) #4901
• [playground][gql] support for Azure OpenAI #4895
• [playground][gql] support for Anthropic #4897
• [playground][gql] support for Vertex #5154
• [playgound][gql] support for Bedrock #4898
• [playground][gql] surface up metrics for a chat completion (token count, latency) #5091
• [playground][api] dataset example chat completion subscription #4804
• [playground][gql] support anthropic for chatCompletionSubscription #4960
• [playground][gql] take in model as a parameter to chat completion #4975
• [playground][gql] model provider and model name #4989
• [playground][gql] model tool calling parameters #4988
• [playground][gql] invocation parameter input #4990
• [playground] record llm.model_name #4995
• [playground][api] record token counts #5030
• [playground] use wss when https is used to initiate websockets connection #4930
• [playground][api] add background task for creating playground span #5031
• [playground][gql] return the chatcompletion resulting span node when available #5037
• [playground][gql] support chatCompletion as a mutation (non-streaming) #5038
• [playground][gql] wire up azure openai #5039
• [playground] anthropic tool calling support #5097
• [playground][gql] filter down the list of providers depending on whether or not client packages are intalled #5116
• [playground] add anthropic token counts #5160
• [playground] improve error handling #5187

Testing

• [playground] anthropic fixture data #4962
• [playground][tests] add api tests for chat completion subscription #4984

Fix

• [playground] resolve span caching issue #4983
• [playground] add openai as a container dependency #5075
• [playground][fix] ensure chat completion subscription unit tests run on all os and on postgres #5126

Instrumentation

• [playground][instrumentation] support for model system and provider in the python instrumentation #5101
• [playground][instrumentation] semantic convention for output schema definition (JSON mode) #4896
• [playground][instrumentation] openai support for output schema #4904
• [playground][instrumentation] tool call id semantic conventions #4908
• [playground][instrumentation] capture tool ids in openai python instrumentaiton #5194
• [playground][instrumentation] capture tool ids in openai js instrumentaiton #5195
• [playground][instrumentation] openai node support for output schema
• openai node sdk support for llm.system and llm.provider #5102

Punt

• [playground] ensure strawberry errors masked #5090

Milestone 2 - Datasets on Playgrounds

Add support to run a set of dataset examples through a prompt

UI

• [playground][ui] dataset input mode #4803
• [playground][datasets] add rate limiter to llm clients #5238
• [playground] llm span context manager #5241

Milestone 3 - Add support for Annotations

As a user, I want the ability to quickly annotate the result of an invocation

[heralight]

Hi!

Enhancement proposal

This feature should be similar to #2462 but with more depth. It would involve a simple button to replicate a query into an edit mode, allowing you to replay it. Additionally, it should offer the possibility to add notes on the result iterations, such as rating the quality, format output, etc., on a scale of 1 to 10.

Goal

The goal is to facilitate quick testing of prompts and inputs, enabling evaluation and visualization of progression.

Thank you,

Alexandre

[mikeldking]

Hi!

Enhancement proposal

This feature should be similar to #2462 but with more depth. It would involve a simple button to replicate a query into an edit mode, allowing you to replay it. Additionally, it should offer the possibility to add notes on the result iterations, such as rating the quality, format output, etc., on a scale of 1 to 10.

Goal

The goal is to facilitate quick testing of prompts and inputs, enabling evaluation and visualization of progression.

Thank you,

Alexandre

@heralight Hey! Thanks for the feedback! We have a ton of features coming out with regards to prompt iteration, notably prompt experiments. Stay tuned. It has evaluations built in

Noted on the replay and the annotations:) will give it some thought. We have a few ideas around replaying data at prompts, but haven't thought about human annotations on different prom versions a ton. Would love to hear more.

[heralight]

Very nice!
my ideal workflow, would be:

• trace some openai calls made from code
• transform some into a replayable prompt, where each modification can be tested and versioned and annoted and ranked.
• prompt can parametized and call from code

best,