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Prompt Engineering Guide

Mastering Text translation
on DeepSeek V3

Stop guessing. See how professional prompt engineering transforms DeepSeek V3's output for specific technical tasks.

The "Vibe" Prompt

"Translate the following text into French: 'The cat sat on the mat.'"
Low specificity, inconsistent output

Optimized Version

STABLE
You are a highly proficient and accurate multilingual translator. Your task is to translate the provided English text into grammatically correct and stylistically appropriate French. Think step-by-step to ensure accuracy and nuance. **English Text:** "The cat sat on the mat." **Thought Process:** 1. Identify the core subject: 'The cat'. 2. Identify the verb and its tense: 'sat' (past simple). 3. Identify the prepositional phrase: 'on the mat'. 4. Translate 'The cat': 'Le chat'. 5. Translate 'sat' into past simple French: 's'est assis' (to sit, reflexive, passé composé for a completed action). 6. Translate 'on the mat': 'sur le tapis'. 7. Combine the translated phrases, ensuring correct French sentence structure. **French Translation:**
Structured, task-focused, reduced hallucinations

Engineering Rationale

The optimized prompt leverages a specific persona ('highly proficient and accurate multilingual translator') and explicitly requests a 'thought process' using chain-of-thought. This guides the model to break down the translation task into smaller, manageable steps, addressing subject, verb tense, and prepositions separately before reassembling. This significantly reduces the chance of errors, especially with more complex sentences. It explicitly asks for 'grammatically correct and stylistically appropriate French', setting a higher quality bar. The naive prompt offers no such guidance, relying solely on the model's inherent translation capabilities.

0%
Token Efficiency Gain
The optimized prompt's output for 'The cat sat on the mat.' must be 'Le chat s'est assis sur le tapis.'
The optimized prompt, when given a more complex sentence with idiomatic expressions, should demonstrate improved accuracy and nuance compared to the naive prompt.
The 'Thought Process' section of the optimized prompt's output should clearly articulate the translation steps undertaken by the model.

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