Skip to main content

Search Text

Giving your model the ability to overcome the cut-off knowledge in order to obtain the most recent data. Let's do search anything very precisely with luci agentic search mechanism.

Searching a text and get the precise answers. Here is the example -

from Luci import search_text

query="Recent trends of AI?" # Define your query

print(search_text(query, max_results=3))

Change the query as per your requirements. Here you get the json response like the below way. You can consider any object for your task and can easily modify it.

[{'body': 'In 2024, generative AI might actually become useful for the regular, non-tech person, and we are going to see more people tinkering with a million little AI models. State-of-the-art AI models ...', 'href': 'https://www.technologyreview.com/2024/01/04/1086046/whats-next-for-ai-in-2024/', 'title': "What's next for AI in 2024 | MIT Technology Review"}, {'body': "That's according to Stanford University's AI Index report. The report, which is in its seventh edition, covers trends such as technical advancements in AI, public perceptions of the technology and the geopolitical dynamics surrounding its development. Here are 10 key takeaways. 1. AI is outperforming humans on various tasks.", 'href': 'https://www.weforum.org/agenda/2024/04/stanford-university-ai-index-report/', 'title': "The current state of AI, according to Stanford's AI Index | World ..."}, {'body': 'Here are some important current AI trends to look out for in the coming year. Reality check: more realistic expectations. Multimodal AI. Small (er) language models and open source advancements. GPU shortages and cloud costs. Model optimization is getting more accessible. Customized local models and data pipelines.', 'href': 'https://www.ibm.com/think/insights/artificial-intelligence-trends', 'title': 'The Top Artificial Intelligence Trends - IBM'}]

Now you can understand, it is super easy to perform the agentic search using luci.

Search and Joined Response​

If you want to make a joined response in the optimized way, use our print_text_result function.

from Luci import Search

query = "Revmaxx LLC" # Define your query
search_instance = Search(query)

results = search_instance.search_text(max_results=5)
search_instance.print_text_result(results)

You will see the result like the below format.

Result 1:
  Body: RevMaxx LLC Visit us on social media: Facebook X LinkedIn YouTube. RevMaxx AI Medical Scribe Revolutionizig 2024. Legal Disclaimer: EIN Presswire provides this news content "as is" without ...
  Href: https://fox59.com/business/press-releases/ein-presswire/741403346/revmaxx-introduces-customization-studio-for-its-ai-medical-scribe-to-enhance-specialized-clinical-documentation/
  Title: RevMaxx Introduces Customization Studio for Its AI Medical Scribe to ...

Result 2:
  Body: REVMAXX LLC is a Florida Domestic Limited-Liability Company filed on March 5, 2024. The company's filing status is listed as Active and its File Number is L24000113789. The Registered Agent on file for this company is Patel Alpesh and is located at 10845 Standing Stone Dr, Wimauma, FL 33598. The company's principal address is 10845 Standing ...
  Href: https://www.bizapedia.com/fl/revmaxx-llc.html
  Title: REVMAXX LLC in Wimauma, FL | Company Information & Reviews - Bizapedia

Now you can use this data to feed your model with the latest information. In the next section, we introduce the agentic image search function.