Multi-Model Conversations in SecureAI

SecureAI gives you access to multiple AI models through the OpenWebUI interface. You can switch between models mid-conversation, compare outputs side by side, and pick the best response for each task. This guide explains when and how to use multi-model conversations effectively.

Why Use Multiple Models?

Different models have different strengths. In the automotive aftermarket context:

Faster models are better for quick lookups like part numbers, basic fitment checks, and simple questions.
Larger models handle complex tasks better: multi-step diagnostics, interpreting ambiguous catalog data, or analyzing uploaded documents.
Specialized models (when available) may have deeper knowledge of specific parts databases or manufacturer catalogs.

Switching models lets you match the tool to the task without starting a new conversation.

How to Switch Models Mid-Conversation

Using the Model Selector

Look for the model selector dropdown at the top of the chat interface (or next to the message input, depending on your OpenWebUI version).
Click the dropdown and choose a different model.
Type your next message. It will be processed by the newly selected model.

The conversation history stays intact. The new model can see all previous messages in the thread, regardless of which model generated them.

What Happens When You Switch

The new model receives the full conversation context (your messages and all previous responses).
The new model does not know which model produced earlier responses. It treats them as part of the conversation.
Response style, formatting, and level of detail may change because each model has its own behavior.

Comparing Model Outputs

When you need to verify a critical result — like a safety-related part cross-reference or a diagnostic conclusion — you can ask the same question to two models and compare.

Side-by-Side Comparison Pattern

Ask your question with Model A selected.
Switch to Model B.
Ask the same question again (copy-paste or rephrase).
Compare the two responses for consistency.

Example:

[Model A selected]
What is the correct brake pad part number for a 2021 Toyota Camry SE
with the 2.5L engine? Include OEM and aftermarket options.

Switch to Model B and repeat:

[Model B selected]
What is the correct brake pad part number for a 2021 Toyota Camry SE
with the 2.5L engine? Include OEM and aftermarket options.

If both models agree on the OEM part number, you have higher confidence in the result. If they disagree, investigate further — check your catalog or ask one model to verify the other's answer.

When to Compare

Safety-critical parts: Brakes, steering, suspension. A wrong part number can cause real harm.
Ambiguous fitment: When a vehicle has multiple sub-models or mid-year changes.
High-value orders: When the cost of a return or incorrect part is significant.
Unfamiliar applications: Vehicles or part categories you do not work with regularly.

Practical Workflows

Quick Lookup, Then Deep Dive

Start with a fast model for the initial lookup, then switch to a more capable model if you need deeper analysis.

[Fast model]
What oil filter fits a 2023 Honda CR-V 1.5T?

If the answer is straightforward, you are done. If the result seems incomplete or you need cross-references:

[Switch to larger model]
The previous response listed one OEM filter. Can you also provide
aftermarket equivalents from Wix, Mann, and Purolator, and note any
differences in filter media or bypass valve pressure?

The larger model sees the full conversation and can build on the earlier answer.

Second Opinion on a Diagnosis

If you are using SecureAI to help diagnose a vehicle issue, get a second opinion by switching models.

[Model A]
Customer reports a P0442 code on a 2019 Subaru Outback 2.5i.
What are the most likely causes and recommended diagnostic steps?

[Switch to Model B]
Review the diagnostic steps above. Would you change the order or add
any checks specific to the 2019 Outback platform?

Comparing Catalog Interpretations

When an uploaded catalog page is ambiguous, different models may parse it differently.

[Model A]
I uploaded a page from the Dorman catalog. What part numbers are listed
for 2018-2022 Ford F-150 exhaust manifold studs?

[Switch to Model B]
Look at the same uploaded catalog page. What part numbers do you see
for 2018-2022 Ford F-150 exhaust manifold studs? Do your results match
the previous response?

Tips for Best Results

Keep context clean. If you switch models frequently in one conversation, the context can get long and confusing. Start a new conversation if the thread becomes cluttered.
Label your requests. When comparing, explicitly ask the second model to compare against the earlier response. This makes differences easier to spot.
Use the same prompt. When comparing outputs, copy-paste the exact same question to both models. Rewording can change results.
Note which model you trust for which task. Over time you will learn which models are strongest for parts lookup vs. diagnostics vs. document analysis.
Do not over-compare. For routine lookups with a clear answer, one model is enough. Save multi-model comparison for high-stakes or ambiguous cases.

Common Issues

The New Model Contradicts the Previous One

This is normal. Models have different training data and reasoning approaches. When you see a contradiction:

Check which answer aligns with your catalog or known data.
Ask the second model to explain its reasoning.
If still uncertain, verify against your physical catalog or parts database.

The New Model Ignores Previous Context

If a model seems to disregard earlier messages after a switch:

The conversation may be too long. Summarize the key facts and ask again.
Some models handle long context better than others. Try rephrasing with the essential details.

Not Sure Which Model to Use

Start with the default model. If the response is too slow for your workflow, try a faster model. If the response lacks detail or accuracy, try a larger model. There is no single best model for all tasks.