In the relation associated with AI continues to be closed. In the past few days, you have released a new Gemini tool called the URL in the basic context.
The foundation of the URL context can be used to stand firm or combine with Google search foundation to make deep wires into internet content.
What is the placement side of the URL?
In short, it is a formal planning, straightforward and answers the content and data contained in each Web URLs (including what points to PDFs) without the need to do what we know.
In other words, there is no need to extract the URL text and content, chunk it, vemerise it, keep you yet more. You tell Google what you like and go walking. As you will see a while, it is very specific in the code and most honesty.
In those reasons what I had said could be one of the peak in the Rag box.
But it works? Let us look at a few examples.
I will set up my development environment first under the Ubuntu WSL2 Windows. Follow or use any method used for it.
$ uv init url_context
$ cd url_context
$ uv venv url_context
$ uv pip install jupyter
$ uv pip install "google-genai>=1.16.0"You will need Google API key. If you do not make one, head head to Google Ai Studio, Sign up if you need, and set your key up. The link to do so will approach the main corner of the Dashboard.
Google Ai Studio
Now using this command should now bring a new tab to your browser in a manual.
$ jupyter notebookSome limitations that should be known
Before we move on our coding examples, there are fewer limits and restrictions on using the URL context you should know.
- 20 high URLs can be applied for each request.
- The main size of content returned to one URL is 34MB.
- Types of following content – denied
- Content of written content
- YouTube Videos
- Google Workspace files, such as Google Docs or Spreadsheet
- Video files and noise
Concerning what is said, let us continue our examples.
Example 1 – Investigating a complex PDF
My test file when I test Rag or the same processing against the data in PDFs to use another Tesla's 10-Q Quarterly Realings. Long time around 50 pages and have complicated structures and tables etc.
As it is a text to complete the SEC, it means that it is available in public and completely free to use the content.
If you want to look for yourself, the document can be found in this KL.
With this PDF, the question I always put on this,
"What are the Total liabilities and Total assets for 2022 and 2023"The answer to that question is on page 4 of the document. Here is that page.
To the people, the answer is easy to find. Since you can see, the total number of 2022/2023 was ($ 82,338 / $ 93,941. Complete bills of existence (for millions) $ 36,440 / $ 39,446.
Back a day (ie about 18 months ago!), It was a challenge to find this information in this text using traditional RAG.
How will we stand at Google URL Rext Groveld Cope?
In your Jobyter book, type in this code.
from google import genai
from google.genai import types
from IPython.display import HTML, Markdown
client = genai.Client(api_key='YOUR_API_KEY HERE')
# We can use most of the Gemini models such as 2.5 Flash etc... here
MODEL_ID = "gemini-2.5-pro"
prompt = """
Based on the contents of this PDF , What
are the Total liabilities and Total assets for 2022 and 2023. Lay them out in this format
September 30 2023 December 31, 2022
Total Assets $123 $456
Total Liabilities $67 $23
Don't output anything else, just the above information
"""
config = {
"tools": [{"url_context": {}}],
}
response = client.models.generate_content(
contents=[prompt],
model=MODEL_ID,
config=config
)
display(response.text)That's, few of the lines, but let's see the result.
'September 30 2023 December 31, 2022nTotal Assets $93,941 $82,338nTotal Liabilities $39,446 $36,440'They, not too shack.
Let's see if you can choose more information. Next to the end of the PDF, there is a letter to work that will leave a company explaining their medication. Does the URL base decide on why the outcome of the book mentioned asterisks (***)? Here is a book snippet.
The reason for blurding with the outgoing line is given in the floor of the floor.
The code that we need to remove this information is very similar to our first example. In fact, the only changing thing is fast, so I will show that.
...
...
prompt = """
Based on , an employee severance letter is displayed
Why is the exit date referred to in the letter marked with ***
"""
...
...And the result?
'Based on the provided document, the exit date in the employee severance
letter is marked with "[***]" because specific, non-material information
that the company treats as private or confidential has been intentionally
omitted from the public filing.nnThe document includes a note clarifying
this practice: "Certain identified information has been omitted from this
document because it is not material and is the type that the company treats
as private or confidential, and has been marked with "[***]" to indicate
where omissions have been made."'As you can see, that is too much.
What other use of the URL context?
In my opinion, it opens the wealth of new opportunities, including: –
Analysis of deep content and integration.
- Data release. The tool can draw some information, such as prices, words, or finding key, from many URLs.
- Comparison of documents. It can analyze many reports, articles, or PDFs to identify differences and trends.
- Content creation. By combining information from a few Source URLs, AI can produce accurate summaries, blog posts, or reports. For example, an engineer can use the selection of two recipes from different websites, angratement of ingredients and comments.
- Code and Scriptural analysis. Engineers can point AI in GitHub repository or technical documents to describe the code, produce the setup instructions, or answer specific questions about.
The flow of a complex wise work.
- A combination of wide receiving with Google's search and a shallow analysis about the URL content tool creates a basis for a complex, most steps. AI agent can start the appropriate articles on the topic and use the URL player tool for the deeper “learning” and the most relevant search results.
- Gemini Cli, an open AI agent, uses the URL player tool for its Web Web command. This allows developers to quickly summarize web pages, issue important information, or translate direct content from their end.
Advanced advanced correctness and hallucinations reduction.
- By responding to answers of certain web pages, the authentic AI accuracy increased, reducing the likelihood of producing incorrect or done information. This also allows AI to provide the quotations of its application, create user reliability by showing sources of information.
It supports many types of content.
- PDFs. AI can issue a text and understand the shape of tables within the PDF documents, making reports and manuals available.
- Photographs. It can process and analyze pictures in various formats (PNG, BMP, Webb, WebP), many skills for understanding charts and drawings.
- Web files and data. Continuous Support of HTML, JSON, XML, CSV, and obvious text files confirm a comprehensive functionality.
Example 2 – Make price comparison
Our second example, let us think that we are hunting for a new set of headphones. We will feed the list of a few online stores selling the product on our code and asks the model to get three cheap products that meet our clarification.
This example may feel a bit repeated as much comparative websites, but it is actually intended to highlight the types of tools you can do with the tool.
Say we want to buy some headphones model, e.g. We have identified online stores at the most competitive rates, but these prices fluctuate almost every day. Let's build a text that you can work at any time to retrieve stores at three prices cheap.
Also, the only difference between this instance code is the first to hurry. Some references are the same.
prompt = """
Based on these URL links, output the three cheapest prices for these
headphones and the relevant store.
Sony WH-1000XM5 Noise-Canceling Wireless Over-Ear Headphones (Black)
"""In this coming out is.
'Based on the provided URLs, here are the three cheapest prices for the
Sony WH-1000XM5 headphones:nn1.
**$145.00** at Reverb.n2.
**$258.99** at Teds Electronics.n3.
**$329.99** at Sony.'Example 3 – Financial and comparative financial analysis.
In this example, we will compare a quarter 2, receiving reports of 2025 from Amazon and Microsoft. We will ask the model to analyze both reports, issue important information and conclude a summary that reflects the main powers and two-operators. Details are also obtained by its Public-Q SECT 10-Q reports.
from google import genai
from google.genai import types
from IPython.display import HTML, Markdown
client = genai.Client(api_key='YOUR_API_KEY_HERE')
MODEL_ID = "gemini-2.5-pro"
microsoft_earnings_url = "
amazon_earnings_url = "
# --- Step 3: Construct the Detailed, Non-Trivial Prompt ---
# This prompt guides the AI to perform a deep, comparative analysis
# rather than just a simple data extraction.
prompt = f"""
Please act as a senior financial analyst and provide a comparative analysis of the latest quarterly earnings reports for Amazon and Microsoft.
Access and thoroughly analyse the content from the following two URLs:
1. **Microsoft Earnings Report:** {microsoft_earnings_url}
2. **Amazon's Earnings Report:** {amazon_earnings_url}
Based *only* on the information contained within these two documents, please perform the following tasks:
1. **Extract and Compare Key Financial Metrics:**
* Identify and extract the Total Revenue, Net Income, and Diluted Earnings Per Share (EPS) for both companies.
* Present these core metrics in a clear, formatted markdown table for easy comparison.
2. **Analyse and Summarise Management Commentary:**
* Review the sections containing quotes from the CEOs (Satya Nadella for Microsoft, Jeff Bezos for Amazon) and CFOs.
* For each company, write a paragraph summarising the key themes they are emphasising. What are the primary drivers of their performance, according to them? What is the overall tone of their commentary (e.g., optimistic, cautious)?
3. **Identify and Contrast Strategic Focus:**
* Pinpoint the specific business segments or product categories that each company highlights as major growth drivers (e.g., Microsoft Cloud and AI, Amazon's AWS services, etc).
* Contrast their primary strategic focus for the quarter. Is one more focused on enterprise/cloud, while the other is more focused on consumer hardware and ecosystem growth?
4. **Synthesise a Conclusive Executive Summary:**
* Write a final, concise paragraph that synthesises the findings. Compare the overall health and current strategic posture of the two companies based on these reports. For example, conclude which company demonstrated stronger growth in this specific quarter and in which areas.
Just output your final analysis. There is no need to output intervening steps thopughts or data
"""
config = {
"tools": [{"url_context": {}}],
}
response = client.models.generate_content(
contents=[prompt],
model=MODEL_ID,
config=config
)
display(Markdown(response.text))Here's the outgoing.
Here is a comparative analysis of the latest quarterly earnings reports for
Amazon and Microsoft.
1. Key Financial Metrics
Metric Amazon (Q2 2025) Microsoft (FY25 Q2)
Total Revenue 143.7 billion 61 9 billion
Net Income 10.4 billion 21.9 billion
Diluted EPS 1 2.94
2. Management Commentary Analysis
Microsoft:
Microsoft's management, led by CEO Satya Nadella, maintains a highly
optimistic tone, emphasizing the transformative impact of AI on their
business. Nadella's commentary highlights the "Microsoft Cloud" as a primary
performance driver, citing its role in helping customers apply AI at scale.
The company's CFO, Amy Hood, reinforces this by noting that the strong
quarterly results were driven by the Microsoft Cloud, which saw a 23% increase
in revenue. The overarching theme from Microsoft's leadership is that their
investments in AI are not just paying off but are fundamentally reshaping their
product offerings and customer relationships, leading to significant growth
and market leadership.
Amazon:
Amazon's leadership, including CEO Jeff Bezos, presents a confident and
forward-looking perspective. The commentary highlights the strong performance
of Amazon Web Services (AWS) and the company's continued innovation in AI,
particularly with services like Bedrock and the development of custom AI chips.
Bezos emphasizes the company's focus on long-term, customer-centric innovation.
The overall tone is one of robust optimism, with a clear message that Amazon's
investments in AI and cloud computing are yielding substantial results and
will continue to be central to their strategy.
3. Strategic Focus Contrast
Microsoft:
Microsoft's strategic focus for the quarter is heavily centered on its
enterprise and cloud offerings, with a particular emphasis on artificial
intelligence. The report repeatedly highlights the "Microsoft Cloud" as the
cornerstone of its success, with specific mentions of products like Azure,
Dynamics 365, and Microsoft 365, all of which are being infused with AI
capabilities. The commentary from CEO Satya Nadella explicitly points to the
company's success in helping customers apply AI at scale as a key
differentiator and growth driver.
Amazon:
Amazon's strategic focus, while also heavily invested in cloud and AI through
AWS, is broader, encompassing its vast e-commerce and consumer-facing
businesses. The report underscores the growth of AWS, with a notable increase
in revenue and operating income, and highlights the company's innovation in
AI with services like Bedrock. However, unlike Microsoft, Amazon's report also
points to the strength of its consumer business, with a focus on selection,
price, and convenience, as well as the growth of its advertising services.
4. Executive Summary
Based on their latest quarterly reports, both Microsoft and Amazon are
demonstrating strong financial health and are strategically positioned to
capitalize on the growth of cloud computing and artificial intelligence.
Microsoft's report indicates a more focused strategy, with the "Microsoft
Cloud" and its integrated AI capabilities serving as the primary engine of
growth, resulting in impressive profitability. Amazon, while also experiencing
significant growth in its AWS segment, presents a more diversified strategy,
balancing its enterprise cloud business with its massive e-commerce and
advertising operations. In this specific quarter, Microsoft has shown stronger
growth in net income and EPS, reflecting the high margins of its enterprise
software and cloud business.Summary
The article introduces a new Gemino content tool, which allows developers to ask and analyze certain web URLs (including PDFs) directly, without the Chunking, and Vectation veins.
I showed its easy use for the examples of Python Code running on Jophstrokoc, showing successful data from the online stores, and Q2 20 2025 financial comparatives.
While noticing the limitations such as a mixed URLs and the media content such as YouTube videos, I highlighted the highest web pages and Opnline PDFS for the correct answers.
For many cases, this tool has successfully replaced by the flow of the activity, especially if the Google search is to allow the Aventic, authenticity, and multimodal content, and multimodal content analysis.
I hope this article has left your desire for trials to use that this practical work can offer.
