emberlm

Official Python SDK for EmberLM. Run versioned prompts from your production code, evaluate LLM responses, and ship AI with confidence.

Install

pip install emberlm

Requires Python 3.8+. Zero third-party dependencies.

Quick start

Get an API key from Settings → API Keys in the dashboard. Keys start with pk_live_.

from emberlm import Client

client = Client(api_key="pk_live_...")

result = client.run(
    "summarize_docs",
    variables={"document": doc_text},
)

print(result["text"])
print("passed_evals:", result["passed_evals"])
print("confidence:", result["confidence"])
print("cost_usd:", result["cost_usd"])
print("latency_ms:", result["latency_ms"])

API

Client(api_key, base_url=..., timeout=60)

client = Client(
    api_key="pk_live_...",
    base_url="https://emberlm.dev",  # optional
    timeout=60,                        # optional, seconds
)

client.list_prompts()

List every prompt in the API key's workspace.

data = client.list_prompts()
for p in data["prompts"]:
    print(p["name"], p["current_version"])

client.get_prompt(name)

Fetch a single prompt by name. Returns the prod-tagged version if one exists, otherwise the latest.

prompt = client.get_prompt("summarize_docs")
print(prompt["system_prompt"], prompt["user_prompt"])

client.run(prompt_name, variables=None, model=None)

Run a saved prompt. Variables are substituted into {{placeholders}}. All workspace eval rules are applied to the output. The run is persisted and counts toward the workspace's analytics.

result = client.run(
    "classify_ticket",
    variables={"body": ticket_body},
    model="claude-haiku-4-5",  # optional override
)

# result keys:
#   run_id, prompt, version, model,
#   text,
#   input_tokens, output_tokens, total_tokens,
#   cost_usd, latency_ms,
#   passed_evals, confidence, evals,
#   error

client.eval(response, rule_ids=None, prompt=None, variables=None)

Evaluate an arbitrary response against the workspace's active eval rules. Useful when the response was generated by a different SDK or model.

result = client.eval(
    response=llm_response,
    prompt=user_prompt,            # optional
    variables={"name": "Jane"},    # optional
    rule_ids=["rule-id-1"],        # optional, defaults to all active
)
print(result["passed"], result["confidence"])

An alias client.evaluate(...) is also available for users who prefer to avoid the eval name.

Errors

Any non-2xx response raises EmberLMError:

from emberlm import Client, EmberLMError

try:
    client.run("missing_prompt")
except EmberLMError as e:
    print(e.status, str(e))

Status	Meaning
401	Missing or invalid API key
403	API key's plan does not permit the SDK
404	Prompt not found in the workspace
429	Monthly call limit reached, or rate limited

Rate limits

100 requests / minute per API key.

License

MIT