SoFunction
Updated on 2025-04-06

Deepseek usage guide and question optimization strategy method

Preface

With the rapid development of artificial intelligence technology, semantic search has become a core tool to improve information retrieval efficiency and user experience. As an advanced semantic search engine, DeepSeek can deeply understand the semantic intentions of user queries through natural language processing (NLP) and machine learning technology and provide highly accurate search results.

This article will introduce the core functions and integration methods of DeepSeek in detail, and explore in-depth how to maximize the use of DeepSeek's semantic search capabilities by optimizing questioning strategies, thereby improving the efficiency and accuracy of information retrieval.

Visit the DeepSeek official dialogue portal:

1. DeepSeek Overview

DeepSeek is a search engine based on semantic understanding. Unlike traditional keyword matching search, it can parse the semantic intent of user queries through natural language processing (NLP) and deep learning technology and return highly relevant search results. DeepSeek not only supports single query, but also maintains context consistency in multiple rounds of conversations, providing a more intelligent interactive experience.

The core advantages of DeepSeek:

  • Semantic understanding: DeepSeek can parse the semantics of the query instead of simply matching keywords, thereby providing results that are more in line with user intentions.
  • Contextual Awareness: In multiple rounds of conversations, DeepSeek is able to understand and utilize contextual information to provide coherent and accurate answers.
  • Continuous optimization: Through machine learning algorithms, DeepSeek continuously optimizes its search model to improve the relevance and accuracy of search results.

DeepSeek has a wide range of application scenarios, covering intelligent customer service, knowledge base search, recommendation systems and other fields, which can significantly improve the efficiency and user experience of information retrieval.

2. Integration and use of DeepSeek

2.1 DeepSeek API Integration

DeepSeek provides a powerful API interface that developers can seamlessly integrate into various applications. Here are the key steps to integrate the DeepSeek API:

  • Get API key: Register on the DeepSeek official website and obtain the API key.
  • Send a query request: Send user queries to the DeepSeek API endpoint via HTTP request.
  • Analyze the response result: The results returned by the API are usually in JSON format, and developers can extract the required information by parsing JSON data.

2.2 Implementing DeepSeekAPI Calls with Python

To further improve the interaction efficiency with DeepSeek, the following is a Python sample code that shows how to implement streaming queries through the DeepSeek API. Streaming queries allow developers to gradually obtain query results, which is suitable for scenarios where real-time response is required.

from openai import OpenAI

# Initialize the DeepSeek API clientclient = OpenAI(api_key="your_api_key", base_url="") 

# Send a query requestresponse = (
    model="deepseek-chat",
    messages=[
        {"role": "system", "content": "You are a poet"},
        {"role": "user", "content": "Let me introduce the * Festival"},
    ],
    #stream=False # Return directly    stream=True  # Enable streaming return)

# print([0].) # Return data directly
# Handle streaming responsesfor chunk in response:
    if [0].:
        print([0]., end="", flush=True)

Code parsing

  • API Configuration:passapi_keyandbase_urlConfigure the DeepSeek API connection.
  • Streaming query:set upstream=TrueEnable streaming return mode to get query results step by step.
  • Response processing: By traversing the response data blocks, output the answer generated by DeepSeek in real time.

3. Optimize questioning strategy: improve interaction with DeepSeek

The interaction effect with DeepSeek not only depends on its semantic understanding ability, but also closely related to the way users ask questions.

The following are strategies for optimizing questions to help users obtain more accurate and relevant information from DeepSeek.

3.1 Clarity and simplicity of the question

Clear and concise questions can help DeepSeek quickly understand user intentions, thereby improving search efficiency. Avoid using lengthy or complex sentences and express your needs directly and clearly.

Example:

  • Not clear: "I want to know everything about artificial intelligence."
  • Clear: "What are the core technologies of artificial intelligence?"

3.2 Provide adequate contextual information

When a question involves a specific context or situation, providing sufficient contextual information helps DeepSeek better understand the intent of the query, thus providing a more accurate answer.

Example:

  • Lack of context: "How to learn Java?"
  • Provide context: "I have mastered Python, how to quickly learn Java?"

3.4 Ask questions in natural language

DeepSeek supports natural language query, and users do not need to stick to keywords or professional terms. Using daily language questions, DeepSeek is able to provide the most relevant answers through semantic analysis.

Example:

  • Natural Language: "What is the main difference between deep learning and machine learning?"
  • Keyword form: "Deep Learning vs. Machine Learning"

3.4 Avoid ambiguity and ambiguity

Issues of ambiguity or ambiguity may cause DeepSeek to fail to accurately understand user intentions. Try to avoid using words that are prone to ambiguity to ensure the clarity of the problem.

Example:

  • Ambiguity issues: "What are the applications of machine learning?" This question may refer to algorithm applications or industry applications.
  • Clarity question: "What are the applications of machine learning in the medical field?"

3.5 Ask open questions

Open questions can guide DeepSeek to provide more comprehensive answers for scenarios requiring extensive information.

Example:

  • Closed issues: "What industries can machine learning be applied to?"
  • Open question: "What are the application scenarios of machine learning in different industries?"

4. Common misunderstandings and avoidance strategies in asking questions

4.1 Avoid asking too broad questions

Too broad questions can lead to excessive search results and lack of targeting, making it difficult to extract valuable information.

Example:

  • Broad questions: "What is artificial intelligence?"
  • Focus on the issue: "What are the applications of artificial intelligence in autonomous driving?"

4.2 Avoid excessive use of professional terms

While DeepSeek is able to understand professional terms, overuse can lead to semantic analytical bias. Try to ask questions in easy-to-understand language.

Example:

  • Over-term: "How to implement the backpropagation algorithm of convolutional neural networks?"
  • Popular language: "What is the training process of convolutional neural networks?"

5. Universal formula "4-step questioning method"

In order to further improve the accuracy of the question and combined with the previous optimization strategy, we can adopt a simple and effective question-asking method:4-step questioning method. By clarifying identity, specific tasks, detailed constraints and output formats, DeepSeek helps better understand user needs and provide efficient and targeted answers.

5.1 [Clear identity + specific tasks + detailed constraints + output format]

1. Identity: Who are you?

First, you need to be clear about your identity, which helps DeepSeek understand your background and needs.

For example, you may be a student, a workplace, a blogger and other roles, with different identities and different needs.

2. Task: What problems do you want to solve?

Defining tasks can help DeepSeek identify your core needs and avoid generating irrelevant or overly broad content.

For example, do you want to do market analysis or answer academic questions?

3. Details: What are the restrictions?

Providing specific details or constraints can make the query more operable.

For example, time limits, data range, regional characteristics, etc. can help DeepSeek customize more accurate answers.

4. Format: What is the expected output?

Identify the output format you need. Are the answers you want to get a short summary, detailed report, or charts, code, etc.? Specifying the output format can help DeepSeek provide more demand-compliant results.

5.2 Example

Working people: Invalid questions

  • Error demonstration: "Analyzing the new energy vehicle market" → Exporting general industry reports, talking in general
  • Question after optimization: "As a marketing specialist, please compare the social media volume of BYD and Tesla in Q4 2024, analyze users' emotional tendencies towards the 'price reduction strategy', and present it in a table" → Directly output the conclusion with data comparison, and complete the report PPT in 20 minutes

Student Party: The vague question was wrong DDL

  • Error demonstration: "Help to revise the paper" → Received untargeted content of "Suggestions to check more documents"
  • Question after optimization: "I am an undergraduate major in mechanical science and need to optimize the literature review part, focusing on the breakthrough of flexible robot sensors in the past three years. Please rewrite and mark the reference DOI in academic language" → Automatically generate paragraphs with authoritative citations, and the sludge check rate will drop by 15%.

Blogger: Records and records

  • Error demonstration: "Writing a copywriting for Shanghai coffee shop" → Generate a general template with "beautiful environment and good coffee"
  • Question after optimization: "As a 'social terror shop blogger', please recommend 3 niche cafes in Pudong with the theme of 'distance at the internet celebrity shop crowd', and require: 1) Write down the details suitable for working alone 2) Use the surprise tone of 'discovering a secret base' 3) At the end, guide fans to submit private stores" → Generate more distinctive and theme-oriented copywriting to highlight personality and actual needs.

6. Summary

Through the introduction of this article, we have in-depth discussions on the core functions, integration methods and strategies for optimizing questions, especially the "4-step questioning method", so that users can guide DeepSeek more accurately, thereby improving the effect and experience of semantic search.

I hope this article can help you better understand and use DeepSeek, and optimize the questioning strategy to fully utilize its potential for semantic search, and enjoy the convenience and efficiency brought by intelligent information retrieval.

The above is personal experience. I hope you can give you a reference and I hope you can support me more.