How to Build an AI Recipe Finder Assistant That Surfaces Your Recipes

AI Recipe Finder Assistant Overview

An AI recipe finder assistant is essentially a smart chat interface with a search bar that has personality. It combines the intelligence of an AI language model with your own recipe content to let visitors ask questions and get relevant answers instantly.

Instead of typing keywords and hoping for the right result, your readers can interact with a friendly chatbot that understands natural language. Ask “I have white chocolate and need a quick dessert”, and it will suggest recipes from your blog that use white chocolate, even if the exact words “white chocolate” aren’t in the title.

The assistant grasps context and synonyms (it knows a “quick dessert” likely means under 30 minutes, for example), making the search experience far more intuitive and a strong foundation when you set out to build an AI recipe finder that feels human.

What’s happening behind the scenes?

Think of it in two parts: a brain and a memory. The “brain” is the AI model, in our case, a fast, compact model called GPT-5-mini (LeadsWithDemos default choice) that excels at understanding questions and phrasing helpful answers. The “memory” is a custom knowledge base containing your recipe posts.

You’ll feed your assistant relevant content (post URLs, titles, ingredients, etc.) by indexing your blog’s pages. Then, the AI searches this index using semantic meaning, not just exact keywords, so it can find connections a normal search might miss. (No coding required; an AI assistant builder tool does the heavy lifting of creating this index, also known as a vector database).

Pitfall: An AI assistant is only as reliable as its knowledge. If you don’t include all your key recipe posts in the knowledge base (or if some content is outdated), the assistant might give incomplete answers. Take time to feed it quality, up‑to‑date information so it doesn’t accidentally suggest a recipe that isn’t actually on your site. This prep is essential when you build an AI recipe finder that readers will trust.

Why add an AI recipe finder to your site?

The immediate benefit is happier readers… They can finally ask for recipes the way they’d ask a friend or personal chef and get quick suggestions that link directly to your content.

Newcomers won’t feel lost in your archive, and regulars can discover dishes they might have otherwise missed. Beyond user experience, this assistant can boost engagement metrics, if people find what they need faster, they’ll view more pages (and possibly increase ad views, comments, or shares).

It’s also a gentle way to build your email list: after helping someone find the perfect recipe, the assistant can offer to email them the recipes, turning a satisfied reader into a subscriber.

In short… An AI recipe finder assistant makes your blog more interactive, personalized, and sticky. It’s like upgrading your site’s search into a conversation.

Now that we understand its value and basic workings, let’s roll up our sleeves and build an AI recipe finder assistant together.

Step-by-Step Implementation

Now for the fun part! Building your own AI recipe finder assistant involves two main phases: first configuring the AI and giving it your recipe knowledge, and then personalizing the chat interface so it feels like an integrated part of your site. Follow these steps and you’ll have a working assistant in no time:

Create the AI Assistant.

Start by accessing the AI Assistants section in your LeadsWithDemos dashboard (look for the “AI Assistants” option in the left sidebar).

• Click the + Add assistant button to create a new assistant.
• Give it a clear name like “AI Recipe Finder Assistant“.
• In the model selection, you’ll see GPT-5-mini chosen by default; leave it as is. This model is ideal here because it’s fast and cost-effective for browsing through your blog posts.
• Next, in Add instructions, paste the following prompt block. It sets the tone, structure, and guardrails specifically for an AI Recipe Finder Assistant.

Prompt template:

# Role
Serve as an AI Recipe Finder Assistant that only searches my personal recipe library and routes users to the correct recipe pages.

# Objective
Help users discover the most relevant recipes from my blog only and provide direct links to those recipes, without giving cooking instructions, method details, or meta-explanations.

# Instructions
- Scope and Behavior
-- Use only recipes and equipment links from my recipe database / blog.
-- Treat every query as a search request, even if it sounds like “How can I make this recipe?”
-- Your job is to find and recommend recipes, not to teach cooking or explain steps.

- What You May Include
-- For the primary recommended recipe, you may output: 
--- Recipe title.
--- Very short description (max 1–2 sentences)
--- Optional short meta (e.g., time, diet tags), The source URL (recipe blog post).
-- Then, optionally:
--- A short heading like “More related recipes:”
--- Up to three additional recipes with:
---- Recipe title and its URL
---- No extra description for these secondary recipes.
-- No other sentences, explanations, or closing remarks.

- What You Must NOT Do
-- Do not provide step-by-step instructions, method summaries, or cooking tips.
-- Do not explain what you can or cannot do (no “Note: I can only…”).
-- Do not offer options like “If you’d like, I can…” or ask what the user prefers next.
-- Do not invite open-ended conversation.
-- Do not add any extra commentary after the list of recipes.
-- For queries like “How can I make this recipe?”, only return:
--- Title, 1–2 sentence description (optional meta),
--- “Click here to view the complete recipe” link,
--- Optional list of up to three related recipes (No additional text).

- Refinement & No-Result Case
-- If results are too broad, you may briefly suggest how to refine the search (e.g., “Try adding a main ingredient or diet preference.”).
-- Do not add tips or examples on how to refine the search.
-- If no recipe matches, return a short message under 100 characters, e.g.: “No recipes in my collection match that search. Please try again”.

• Once you’ve added that, click Create assistant to save your new assistant configuration.

Pitfall: Don’t skip the custom instructions! Without clear instructions, your assistant might respond with generic info or stray off-topic. Make sure to define its role (e.g., a helpful recipe expert for YourSiteName) and emphasize that it should stick to your provided recipe content. A little upfront guidance here leads to much better answers later.

Create a Custom Knowledge Base.

Right now your assistant exists, but it knows nothing about your recipes. We need to give it your content in a form it can search.

• In the LeadsWithDemos interface, go to the assistant’s settings and find the Vectors tab (this is where custom knowledge bases live).
• Click the Add Vector button to create a new knowledge base for your recipes.
• When prompted, enter a name like “My Recipe Knowledge”; something identifiable.
• Hit Continue, and the system will set up an empty vector (think of this as an index or database that will hold your recipe content for the AI to retrieve).
• At this point, you have an empty knowledge base ready to fill. The next step is to populate it with your actual recipe content.

Add Your Recipe Content.

Now, populate the vector with all the recipes you want the assistant to retrieve from.

• Switch to the Knowledge sources tab in the AI Assistants settings.
• Click Add new to add a source of content.
• There are a few ways to add data, but one of the easiest is using a Sitemap URL if your blog site has one. Select the “Sitemap URL” option.
• Give this source a name like “My Recipe Posts” so you know what it is.
• Then enter the URL of your blog’s recipe sitemap (for example, https://yourblog.com/sitemap.xml or a specific recipe sitemap URL if you have one).
• Choose how often the system should refresh this source; if you’re adding new recipes frequently, pick daily or weekly.
• Click Continue, and the platform will fetch the list of URLs from your sitemap. You’ll typically see a list of all your site’s pages or all your recipe posts.
• Go ahead and select the specific URLs that are recipe pages (often there’s a “Select All” if your sitemap is only recipes). This tells the assistant which pages to index.

Pro Tip: If you don’t have a sitemap or if your recipes are scattered, you can add content manually. For instance, you could input individual recipe page URLs one by one, or upload HTML/text files of your recipes. It might take a bit more work, but it achieves the same result – giving your AI assistant access to all the important content. The more complete your knowledge base, the more helpful your assistant will be.

Sync the Content.

After you’ve selected the recipe URLs to include, the system will need to grab the content from those pages and add it into your vector.

• You may see a button to Sync with Vector (usually at the bottom of the knowledge source setup window). Click that, then choose the “My Recipe Knowledge” vector (the one you created earlier) as the destination for the sync.
• Hit Continue or confirm to start the syncing process. The platform will now crawl each selected page, extract the content (including text of the recipe posts), and store it in the vector database.
• Give it a minute or two to pull in all the data, especially if you have many recipes. Once done, you should see your vector now contains a number of documents (entries) corresponding to the recipes you added.

In short… you’ve built a specialized recipe knowledge base that the AI can search through. Now we just need to assign it to the assistant.

Connect the Knowledge to Your Assistant.

This step links your new recipe index with the AI assistant so it actually knows to use that information.

• Navigate back to My Assistants and open your “AI Recipe Finder Assistant” settings page.
• Here, look for the option to manage knowledge or sources. You should find a toggle for something like File search or “Enable vector search”. Turn that on.
• A dropdown menu or selector will appear to choose which knowledge base to use; select the “My Recipe Knowledge” vector you populated.
• Save or apply this change. Now your assistant is officially fueled by your content: when a user asks something, the AI will search within “My Recipe Knowledge” (your recipes) to compose its answer. This ensures it won’t just make up answers or pull random info; It’s bounded by the recipes and info you gave it.

Pitfall: Double-check this connection before moving on. If you forget to assign the vector to the assistant, it will have nothing to reference and might return random answers or apologize that it can’t find anything. This is the number one cause of an AI assistant “not working” after setup. The fix is easy: always verify the correct knowledge base is attached to your assistant.

Customize the Conversation Interface.

Now the backend is ready, let’s make the user-facing chat interface look great. In your assistant’s settings, find the design customization area (in LeadsWithDemos, this is under an Embedded AI section where you also get the embed code).

We’ll start with the conversation screen; that’s the chat window that appears after the user starts interacting (where messages between the user and AI appear).

• Pick a background color for the chat window that matches or complements your site. I chose a neutral white (#FFFFFF) for a clean look, but you might go with a light beige or any color that isn’t distracting.
• Select a font style and size for the chat text. In my case, I went with the same font my blog uses (I picked “Lora” at 14px) to keep consistency. If you want another font, as font family, please go to the LeadsWithDemos site’s design settings to add any fonts that you would like to use for the chat interface.
• Set the loader color, this is the color of the typing indicator or spinner that shows when the AI is thinking. I changed mine to a warm brown (#8b5e3c) to stay on-brand (my site’s accent color), instead of a generic gray.
• Edit the progress indicator text that appears while the AI is searching. Rather than the default “Thinking…”, I wrote fun, relevant messages like “Searching my recipe collection…” and “Mixing ingredients…”. This adds a bit of personality and reassures the user that the assistant is working on their query.
• Style the user message bubble to fit your theme. I gave user messages a white background with a brown border and text (#8b5e3c). To create a chat “speech bubble” effect, I made the top-left and bottom-right corners rounded (12px) and left the other corners sharp (0px). A 2px border width looked clear on my design. You can adjust these values to get the bubble shape you like.
• Do the same for the assistant’s message bubble. I used a light gray background (#F6F6F6) for the assistant’s replies, this happened to match the background of my email sign-up form, making it look like the form is part of the assistant’s answer when it appears. The assistant’s text and border I set to a dark charcoal gray (#3D3D3C). I kept the border width at 2px and used the same corner rounding style as the user bubble (mirroring the rounded corners) so the chat bubbles have a consistent style.

After the chat bubbles, customize the message input box (where the reader types their question). Keep it simple and on-brand: I used the same white background and brown text for the input field, with a subtle border in that brown shade.

Update the placeholder text to something inviting, for example, “What recipe can I help you find?” instead of a plain “Type a message”. This helps users understand what to ask. I also renamed the “Clear” button to “Reset Chat”, making its purpose clearer (this button clears the conversation).

Since this is a recipe finder, I toggled off any file or image upload options (we don’t need those here, and removing extra buttons makes the interface cleaner).

Finally, for the option to hide the chat source citations, you can toggle that off ; for a casual recipe assistant, it’s often nicer to present the answer without a distracting list of sources.

Set Up Feedback & Email Capture.

One powerful feature of this assistant is the ability to capture emails via a feedback prompt. In the design settings, locate the Feedback or user feedback section.

• Toggle Allow user feedback to ON. This means after the assistant answers a question, it can ask the user a follow-up, like a thumbs-up/down or a custom question. We’ll use it to offer an email sign-up.
• For the feedback question, I wrote a friendly line: “Want to save these recipes for later?” which is a natural transition after showing someone a few recipe suggestions.
• Next, set up the feedback buttons. Turn on the option to use custom text for the buttons (instead of just icons). For the positive response, I put “Yes, email them to me”, and for the negative, “No, not right now” (you can phrase these however feels right for you).
• Style these buttons with your brand colors, I made the “Yes” button brown (to match my site’s accent) and the “No” button a neutral gray.
• Now, most importantly, configure the action: choose to trigger your email form when the user clicks the positive response. In other words, if they click “Yes, email them to me”, your email sign-up form will pop up right in the chat, asking for their email (you may need to have a email capture form created or integrated for this step). If they click “No, not right now”, the chat can simply continue without showing a form. This non-intrusive prompt is a great way to convert an engaged reader into a subscriber at the very moment they’ve found value in your site.

Metric to Watch: After launching your assistant, keep an eye on how users interact with this feedback step. How many people click “Yes, email them to me” versus “No, not right now”? That percentage of “Yes” clicks will tell you how compelling your offer is and how interested users are in saving recipes. Also track how many new subscribers you get through the assistant’s form. This data will help you tweak the wording or offers over time to maximize sign-ups.

Customize the Greeting (Initial Screen).

Before users start typing questions, they’ll see an initial greeting screen from your assistant. Let’s make sure that first impression counts. Enable the initial greeting screen (if it isn’t on already) in your assistant’s design settings.

You can then edit the welcome message, style, and any preset questions shown on this screen.

• Write a warm greeting message that fits your blog’s personality.

For example:

<p>Hi there! ?</p> 
<p> I’m your AI Recipe Finder. Search within my <strong>complete recipe library</strong> to quickly find the best recipes for your ingredients, diet, and cravings. </p>
<p> Want some inspiration? <a href="https://food-bloggers.demo.leadswithdemos.com/" target="_blank" rel="noopener noreferrer" style="color:#8b5e3cff; text-decoration:underline;"> <strong>Get my free mini cookbook</strong> </a> </p>

• In that greeting, I used a casual voice and even included a call-to-action (the “free mini cookbook” could be a link to a lead magnet or top recipes page). Use simple HTML or formatting if needed for links or emphasis, since this greeting allows basic HTML.
• Add a few example questions to guide the user. These appear as clickable buttons on the greeting screen and are super helpful for showing what your assistant can do. I included prompts like “Find Swiss white chocolate chip cookies”, “Show vegan oatmeal chocolate chip cookie recipes”, and “Find moist coconut flour chocolate chip cookies”. Think about your own content, choose 2–4 example searches that highlight popular or interesting topics on your site.
• To add these in the builder, click the + icon (Add question) and type in the question exactly how a user might ask it.
• Consider enabling an animated outline effect (or similar highlight) on the example question buttons if the option exists. I turned this on and picked an accent color for the outline, so each suggestion button has a gentle pulsing border. It’s a subtle visual cue that draws attention and invites the user to click one of the example queries.
• Tweak the design and spacing of the greeting elements as needed. You can adjust things like the border radius and padding of those question buttons (I used a small 5px radius to give them a pill-shaped look, and a very thin border for a polished touch).
• Make sure the text color on your greeting and buttons is easily readable against the background. Typically, using your brand’s primary color for headings and a slightly softer background color works well for a welcoming vibe.

Once the initial screen looks good in the preview, click Save to apply all your design changes. Your AI Recipe Finder Assistant is now fully configured and styled!

Deploy and Test Your Assistant.

The final step is to put this assistant on your website so visitors can use it. In the LeadsWithDemos platform, go to the Embedded AI section for your assistant and copy the embed code snippet provided. This is a small piece of iFrame code that you’ll paste into your website.

Decide where you want the assistant to live: you could embed it on a dedicated “Recipe Finder” page, insert it into your blog’s sidebar, or even have it appear as a pop-up on all pages.

For our example, we’ll embed the assistant as a widget in a modal and on the homepage. Paste the code into your page’s HTML where you want the chat interface to appear.

If you prefer a popup approach, you could integrate the code with a modal or use LeadsWithDemos’s popup box feature to have the assistant launch when a user clicks a button. Either way, once you add the embed code and publish the changes, your AI assistant will be live on your site.

Now it’s time to test it out. Visit your site and open the recipe finder assistant. Try asking a few questions as if you were a visitor (e.g., “What can I make with broccoli and chicken?” or use the example question buttons you set up).

See if the responses are correctly pulling from your recipes and whether the formatting looks right. If something seems off (say, the assistant gave an unexpected answer or a design element isn’t quite matching) go back to the LeadsWithDemos settings and tweak the prompt, knowledge base, or design as needed. It might take a couple of iterations to get everything perfect.

When you’re satisfied, congratulations! you’ve built and deployed your very own AI Recipe Finder Assistant! ? Your readers can now interact with your blog in a completely new way, discovering content through conversation.