The Pragmatic Path: From Grand Vision to Achievable Steps
The new philosophy is: Build it inside DSPEx
first. Once it’s mature and proves its value, then consider extracting it into a separate library.
This is a common and highly effective way to evolve a software ecosystem. Build the monolith first, then break it apart when the boundaries become clear and the need arises.
Here is your new, achievable, step-by-step plan:
Step 0: Stabilize the Now (1-2 Days)
- Goal: Stop the bleeding. Make what you have less fragile.
- Action:
- Simplify
Foundation
Interaction: Instead of the hugetry/rescue
blocks, create a tiny internalDSPEx.Foundation.Client
module. This module will be the only place in your app that callsFoundation
. It will contain thetry/rescue
block. IfFoundation
fails, this client will return a standard{:error, :foundation_unavailable}
tuple. - Now, all your other
DSPEx
modules can callDSPEx.Foundation.Client.emit_telemetry(...)
and just handle a simple error tuple. This contains the problem and makes your core logic cleaner.
- Simplify
Step 1: Build the Exdantic
MVP… as a single module. (1 Week)
- Goal: Get the core value of
Ecto
-based structured data without building a whole new library. - Action:
- Create a new file:
dspex/schema.ex
. - Inside, create
defmodule DSPEx.Schema
. - Implement the
use DSPEx.Schema
macro as we discussed. It willuse Ecto.Schema
, add thefrom_llm_map/1
validation function, and theto_json_schema/1
generator. - Crucially, this lives inside
DSPEx
. It’s just another feature of your library.
- Create a new file:
Step 2: Build the ExLLMAdapter
MVP… as a single function. (1 Week)
- Goal: Make one real, modern, structured API call work.
- Action:
- Go into
dspex/client.ex
. - Add a new public function:
def request_structured(prompt, schema_module, opts)
. - Implement the logic we sketched out:
- It takes a
DSPEx.Schema
module. - It calls
DSPEx.Schema.to_json_schema(schema_module)
. - It builds the correct Gemini request body for their “Function Calling” / structured output API.
- It makes the
Req.post
call. - It gets the JSON back and calls
DSPEx.Schema.from_llm_map(json)
.
- It takes a
- Go into
- You are not building a whole library. You are building one function that does the job correctly.
Step 3: Connect the Pieces and Demonstrate Value (A few hours)
- Goal: Make your
PredictStructured
module actually use the new stuff and feel like magic. - Action:
- Refactor
DSPEx.PredictStructured
. - Its
forward
function will now callDSPEx.Client.request_structured(...)
. - Update your
QASignature
or create a new example schema usinguse DSPEx.Schema
with multiple types (e.g.,field :confidence, :float
). - Run it. When you see your LLM return a fully-typed, validated Elixir struct from a simple definition, you will have proven the entire concept.
- Refactor
What about Foundation
?
Defer the big refactor. For now, Foundation
is what it is. You’ve contained the chaos behind the DSPEx.Foundation.Client
facade in Step 0. Your new DSPEx.Client.request_structured
function can still call DSPEx.Foundation.Client.emit_telemetry
to log its calls. It’s not perfect, but it’s contained. You can tackle the bigger platform refactor after.
Your New Reality
This new plan is drastically simpler. You are not building three libraries. You are adding two modules and one function to your existing DSPEx
library.
DSPEx.Schema
(The Exdantic MVP)DSPEx.Client.request_structured/3
(The LLM Adapter MVP)- An updated
DSPEx.PredictStructured
to use them.