Menene bambanci tsakanin prompt engineering, RAG, da fine-tuning, da kuma yaushe kake amfani da kowannen?

Question

Accepted Answer

Waɗannan sune hanyoyi uku na sa LLM yayi abin da kake so, suna aiki a **matakan daban-daban**: prompt engineering yana samuwa da *halayen*, RAG yana shigar da *ilimi*, da fine-tuning yana canja da *model*.

## Hanyoyi uku

- **Prompt engineering** — samuwa da halayen model ta hanyar umarnin, mahallin, da misalai a cikin prompt. Babu abin da ya canja a model; kawai kana sadarwa sosai (system prompts, few-shot examples, tsarin output). Mafi arha da mafi sauri; abin da kake fita dashi **na farko**.
- **RAG (retrieval-augmented generation)** — a lokacin tambaya, dawo jiya watswa masu alaka (daga vector store, bayani-base, ko bincike) da bugi su cikin prompt. Model yana amsa *daga* mahallin da aka bayar. Mafi kyau lokacin da ilimi **waje, sirri, ko bani-bani**.
- **Fine-tuning** — ci gaba da horo da model akan abubuwan misalai naka, daidaita **weights** sa. Wannan yana bugi jiya fassara mai walwala, tsarin, ko fasaha maras faɗi. Yana da iko sosai amma jiya mai tsada da **tsinkayi** — ilimi ya kurmintawa lokacin horo.

## Kwatanta

| | Prompt engineering | RAG | Fine-tuning |
|---|---|---|---|
| **Canja** | Prompt | Prompt (+ dawo jiya) | Model weights |
| **Mafi kyau don** | Halayen, tsarin, muryar | Gida-gida / sirraa gida | Fassara mai walwala, ayyukan maras faɗi |
| **Saurin ilimi** | N/A | Mai rayuwa (sake-index data) | Tsinkayi a lokacin horo |
| **Jiya / yunƙuri** | Mafi arha | Tsakanin (infra) | Mafi tsada (horo + data) |
| **Sabuntawa** | Gyara rubutu | Sabunta index | Sake-horo |

## Jagora matakin yanke shawara

- Fara da **prompting** — warware shi kyauta da farko.
- Buƙa gida da model ba ya sani, ko waɗannan da suna bani-bani (abubuwan rubutu, farashi, bayani na ciki)? Amfani da **RAG**.
- Buƙa fasara mai azumi/tsarin ko aiki na musamman a girma, da kuma prompting ba ya zama tabbas? **Fine-tune**.
- Waɗannan sune **haduwa**: model da aka fine-tune tare da RAG da prompt mai kyau yana yiwu a aiki.

## Menene mahaɗin abin ya haɗa

Neman kayan aiki mara laifi yana jiya: siffofin jiya sukan yunƙura shine fine-tune don ƙara ilimi (wanda RAG ke yi mafi kyau da arha) ko gyara halayen (wanda prompting yana gudana). Sanin cewa **prompting yana samuwa da halayen, RAG yana bugi ilimi, da fine-tuning yana canja model** yana ba ka damar zaɓi mafi arha hanya ta aiki — da haduwa da gaba-gaba maimakon kusan gida.

	Prompt engineering	RAG	Fine-tuning
Canja	Prompt	Prompt (+ dawo jiya)	Model weights
Mafi kyau don	Halayen, tsarin, muryar	Gida-gida / sirraa gida	Fassara mai walwala, ayyukan maras faɗi
Saurin ilimi	N/A	Mai rayuwa (sake-index data)	Tsinkayi a lokacin horo
Jiya / yunƙuri	Mafi arha	Tsakanin (infra)	Mafi tsada (horo + data)
Sabuntawa	Gyara rubutu	Sabunta index	Sake-horo