Future AGI × DSPy

DSPy on Future AGI

Agent Frameworks

Declarative LLM programs with optimisable signatures and modules.

python · trace evaluate optimize

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What you get

Everything traced, scored, and improvable

One install instruments DSPy on OpenTelemetry. Future AGI then layers evaluators, optimisers, and simulations on top of the same trace tree — no second SDK, no double instrumentation.

Trace

Auto-instrumented spans

Every DSPy call becomes a span — inputs, outputs, latency, tokens, cost, model name, tool args, retrieval results, and chain steps captured automatically.

Evaluate

70+ evaluators on every span

Attach Groundedness, Context Relevance, Prompt Injection, Toxicity, and 70+ more — purpose-built scorers powered by the Turing eval models, not generic LLM-as-judge.

Optimize

Closed-loop improvement

Pipe failed traces into agent-opt: GEPA, PromptWizard, ProTeGi, and Bayesian search rewrite your prompts with proof of measured gains.

Simulate

Adversarial scenarios at scale

Generate hundreds of personas and run them through your DSPy agent before launch — text and voice, scripted or persona-driven.

Quickstart · <3 min

Instrument DSPy in three steps

Step 1

Install the traceAI package

One package per language, ships from PyPI, npm, and Maven Central.
Step 2

Register the trace provider

Set FI_API_KEY and FI_SECRET_KEY, then call DSPyInstrumentor().instrument().
Step 3

Run your existing DSPy app

No code changes. Traces appear in the Future AGI dashboard within seconds.

Install

pip install traceAI-dspy

Instrument

from fi_instrumentation import register
from fi_instrumentation.fi_types import ProjectType
from traceai_dspy import DSPyInstrumentor

trace_provider = register(
    project_type=ProjectType.OBSERVE,
    project_name="DSPY_APP",
)

DSPyInstrumentor().instrument(tracer_provider=trace_provider)

# Your existing DSPy code runs unchanged from here.
# Every call is now an OpenTelemetry span in Future AGI.

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