SKU: 71258453316
olive tree bonsai

olive tree bonsai Little Ollie European Olive Bonsai Tree

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Description

olive tree bonsai Little Ollie European Olive Bonsai TreeDescription The European, or Common olive, is known for it's silvery shiny leaves and white hued bark. This makes it remarkably interesting as a bonsai tree. This bonsai will flower, then create olives. They are edible as a fruit, or can be made into olive oil. Quick tip: Keep it just above freezing (around 35 degrees) for a few weeks over the winter, to encourage fruiting. It is a very beginner friendly tree, that does well with poor quality soil and

Description

The European, or Common olive, is known for it's silvery shiny leaves and white-hued bark. This makes it remarkably interesting as a bonsai tree.

This bonsai will flower, then create olives.  They are edible as a fruit, or can be made into olive oil.  Quick tip:  Keep it just above freezing (around 35 degrees) for a few weeks over the winter, to encourage fruiting.

It is a very beginner friendly tree, that does well with poor quality soil and handles drought well.

Great for indoors.

Specifications

 Little Ollie

  • 7 years old, 9" - 10" tall.
  • A flowering bonsai.
  • Makes edible fruit.
  • Recommended indoor bonsai tree.
  • Suitable humidity / drip tray is recommended.
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SKU: 71258453316

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Filipe Fernandes
Waukegan, US
★★★★★ 5
Great book
Format: Paperback
Love the fact you put examples in python and javascript. Great book.
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Reviewed in the United States on June 10, 2025
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Eddwin Paz
Whiting, US
★★★★★ 5
proper documentation from langchain
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Liked the book. But Still missing Human in the loop.
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Reviewed in the United States on April 19, 2025
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B. Black
Natrona Heights, US
★★★★★ 3
Already outdated
Format: Paperback
Concepts are sound but the code in this book is already obsolete
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Reviewed in the United States on August 5, 2025
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Joe Faith
Boise, US
★★★★★ 5
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Format: Paperback
If you're a developer eager to move beyond LLM experimentation and build robust, context-aware AI applications, this book offers both inspiration and practical guidance. The authors open with a clear passion for the transformative potential of large language models (LLMs) and LangChain, framing these technologies as not just enhancements to the developer’s toolkit, but as gateways to new kinds of “thing-building” superpowers. This sense of possibility is grounded in step-by-step instruction, making the book approachable for those with Python or JavaScript backgrounds who may be new to the world of production-grade AI agents. What stands out is the book’s careful scaffolding: starting with foundational concepts like prompt-based programming and progressing to advanced capabilities such as retrieval-augmented generation, agent planning, and tool integration. Each stage is contextualized with real-world use cases, like customizing chatbots to interact with your own documents, personalizing user experiences through memory, and deploying to production with reliability and security in mind. The focus on chain-of-thought reasoning and LangGraph’s agent architecture demonstrates the authors’ awareness of the current state of AI, where context and planning are just as important as raw language ability.
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Reviewed in the United States on July 17, 2025
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Tom C Taulli
Natrona Heights, US
★★★★★ 5
Excellent Handbook
Format: Paperback
What got my interest in this book is the author. He's well-known as a leader in the LangChain world. And his book did not disappoint. It goes through the whole life cycle of development and there is a lot useful insights. If you are looking to build real-world genAI/agentic apps, then this book is certainly a great choice.
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Reviewed in the United States on April 11, 2025

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