Update README.md

README.md

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 **INF-Query-Aligner** is a specialized component of the **INF-X-Retriever** framework, designed to distill the core retrieval intent from complex, verbose, or reasoning-intensive queries. Built upon the **Qwen2.5-7B-instruct** foundation and fine-tuned via Reinforcement Learning, it transforms raw user queries into concise, search-optimized queries for dense retrieval systems.
 
 In our experiments, a single canonical query-writing prompt was applied across all datasets to ensure consistency and reproducibility.
+```python
+QUERY_WRITER_PROMPT = (
+    "For the input query, formulating a concise search query for dense retrieval by distilling the core intent from a complex user prompt and ignoring LLM instructions."
+    "The response should be less than 200 words"
+)
+```
 
 This model is a key enabler for **INF-X-Retriever**'s state-of-the-art performance, currently holding the **No. 1 position** on the [BRIGHT Benchmark](https://brightbenchmark.github.io/) (as of Dec 17, 2025).