Log to phospho with Javascript
Log tasks to phospho
Tasks are the basic bricks that make up your LLM apps. If you're a programmer, you can think of tasks like functions.
A task is made of at least two things:
input (string)
: What goes into a task. Eg: what the user asks to the assistant.output (string?)
: What goes out of the task. Eg: what the assistant replied to the user.
Example of tasks you can log to phospho:
- Call to an LLM (input = query, output = llm response)
- Answering a question (input = question, output = answer)
- Searching in documents (input = search query, output = document)
- Summarizing a text (input = text, output = summary)
- Performing inference of a model (input = X, output = y)
Install the phospho module
The phospho JavaScript module is the easiest way to log to phospho. It is compatible with Node.js.
Types are available for your Typescript codebase.
Info
The phospho module is an open source work in progress. Your help is deeply appreciated!
Initialize phospho
In your app, initialize the phospho module. By default, phospho will look for PHOSPHO_API_KEY
and PHOSPHO_PROJECT_ID
environment variables.
Tip
Learn how to get your api key and project id by clicking here!
You can also pass the api_key
and project_id
parameters to phospho.init
.
Log with phospho.log
The most minimal way to log a task is to use phospho.log
.
Logging text inputs and outputs
const question = "What's the capital of Fashion?";
const myAgent = (query) => {
// Here, you'd do complex stuff.
// But for this example we'll just return the same answer every time.
return "It's Paris of course.";
};
// Log events to phospho by passing strings directly
phospho.log({
input: question,
output: myAgent(question),
});
Note that the output is optional. If you don't pass an output, phospho will log null
.
Logging OpenAI queries and responses
phospho aims to be battery included. So if you pass something else than a string
to phospho.log
, phospho extracts what's usually considered "the input" or "the output".
For example, if you use the OpenAI API:
// If you pass full OpenAI queries and results to phospho, it will extract the input and output for you.
const question = "What's the capital of Fashion?";
const query = {
model: "gpt-3.5-turbo",
temperature: 0,
seed: 123,
messages: [
{
role: "system",
content:
"You are an helpful frog who gives life advice to people. You say *ribbit* at the end of each sentence and make other frog noises in between. You answer shortly in less than 50 words.",
},
{
role: "user",
content: question,
},
],
stream: false,
};
const result = openai.chat.completions.create(query);
const loggedContent = await phospho.log({ input: query, output: result });
// Look at the fields "input" and "output" in the logged content
// Original fields are in "raw_input" and "raw_output"
console.log("The following content was logged to phospho:", loggedContent);
Custom extractors
Pass custom extractors to phospho.log
to extract the input and output from any object. The original object will be converted to a dict (if jsonable) or a string and stored in raw_input
and raw_output
.
phospho.log({
input: { custom_input: "this is a complex object" },
output: { custom_output: "which is not a string nor a standard object" },
// Custom extractors return a string
inputToStrFunction: (x) => x.custom_input,
outputToStrFunction: (x) => x.custom_output,
});
Logging additional metadata
You can log additional data with each interaction (user id, version id,...) by passing arguments to phospho.log
.
log = phospho.log({
input: "log this",
output: "and that",
// There is a metadata field
metadata: { always: "moooore" },
// Every extra keyword argument is logged as metadata
log_anything_and_everything: "even this is ok",
});
Streaming
phospho supports streamed outputs. This is useful when you want to log the output of a streaming API.
Example with phospho.log
Pass stream: true
to phospho.log
to handle streaming responses. When iterating over the response, phospho will automatically log each chunk until the iteration is completed.
For example, you can pass streaming OpenAI responses to phospho.log
the following way:
// This should also work with streaming
const question = "What's the capital of Fashion?";
const query = {
model: "gpt-3.5-turbo",
temperature: 0,
seed: 123,
messages: [
{
role: "system",
content:
"You are an helpful frog who gives life advice to people. You say *ribbit* at the end of each sentence and make other frog noises in between. You answer shortly in less than 50 words.",
},
{
role: "user",
content: question,
},
],
stream: true,
};
const streamedResult = await openai.chat.completions.create(query);
phospho.log({ input: query, output: streamedResult, stream: true });
for await (const chunk of streamedResult) {
process.stdout.write(chunk.choices[0]?.delta?.content || "");
}