MULTI-MODEL WORKFLOWS

Several perspectives. One synthesis.

An exploration of local model orchestration: generate independently, review anonymously, then synthesize a final response.

BUILT / EXPLORED WITH
PythonJavaScriptOllama
THE PROCESSINPUT → UNDERSTANDING
01Generate

Collect answers from several local models.

02Review

Ask models to rank anonymized responses.

03Aggregate

Combine the peer rankings.

04Synthesize

Let a chairman model assemble the final response.

THE PROJECT

Ollama Council

Source and context from my portfolio

01 / CONTEXT

The question behind the work

Different models can bring different strengths to the same question. The council workflow explores how to collect those perspectives and make the review process explicit.

02 / APPROACH

How it comes together

Python, JavaScript and Ollama connect generation, anonymous peer review and synthesis. The repository contains the implementation and any upstream attribution.

03 / PERSPECTIVE

What to keep in mind

A council is a workflow for comparing answers. Its final output still needs evaluation; agreement between models does not establish correctness.

INTERACTIVE EXPLORER

Follow the conversation.

Step through an illustration of the council workflow. These are sample responses, not live model inference.

SAMPLE QUESTION How should a team evaluate a multilingual summarizer?

TAKE A CLOSER LOOK

Explore the work.
Start a conversation.