fixed the review comments

Author: pavanjava

README.md

@@ -5,7 +5,7 @@
 [![PyPI version](https://img.shields.io/pypi/v/qql-cli?color=blue&label=PyPI)](https://pypi.org/project/qql-cli/)
 [![Python 3.12+](https://img.shields.io/pypi/pyversions/qql-cli)](https://pypi.org/project/qql-cli/)
 [![MIT License](https://img.shields.io/badge/license-MIT-green)](LICENSE)
-[![Tests](https://img.shields.io/badge/tests-371%20passing-brightgreen)](tests/)
+[![Tests](https://img.shields.io/badge/tests-375%20passing-brightgreen)](tests/)
 
 Write `INSERT`, `SEARCH`, `RECOMMEND`, `DELETE`, and `CREATE COLLECTION` statements instead of Python SDK calls. Supports hybrid dense+sparse vector search, cross-encoder reranking, quantization (scalar, binary, product), SQL-style `WHERE` filters, script execution, and collection dump/restore.
 
@@ -23,7 +23,7 @@ qql> SEARCH notes SIMILAR TO 'vector databases' LIMIT 5 USING HYBRID RERANK
 ✓ Found 1 result(s) (hybrid, reranked)
  Score  │ ID                                   │ Payload
 ────────┼──────────────────────────────────────┼──────────────────────────────────────
- 5.3714 │ 3f2e1a4b-8c91-4d0e-b123-abc123def456 │ {'text': 'Qdrant is a ...', 'author': 'alice', 'year': 2024}
+ 5.3754 │ 3f2e1a4b-8c91-4d0e-b123-abc123def456 │ {'text': 'Qdrant is a ...', 'author': 'alice', 'year': 2024}
 ```
 
 ---
@@ -134,7 +134,7 @@ Tests do not require a running Qdrant instance — the Qdrant client is mocked.
 pytest tests/ -v
 ```
 
-Expected: **371 tests passing**.
+Expected: **375 tests passing**.
 
 ---
 

docs/collections.md

@@ -85,7 +85,7 @@ CREATE COLLECTION <name> ... QUANTIZE PRODUCT [ALWAYS RAM]
 ```
 
 - **`QUANTILE <float>`** — (scalar only) calibration quantile for the INT8 conversion; defaults to Qdrant's built-in default (0.99) when omitted.
-- **`ALWAYS RAM`** — keep the **original** (unquantized) vectors in RAM for rescoring, sacrificing memory savings but preserving accuracy during re-ranking. Supported by all three types.
+- **`ALWAYS RAM`** — keep the **quantized** vectors in RAM at all times, regardless of the collection's `on_disk` setting. Improves search throughput at the cost of higher RAM usage for the compressed index. The original full-precision vectors are stored and managed independently of this flag. Supported by all three quantization types.
 - **`QUANTIZE`** always appears **after** all other clauses (`HYBRID`, `USING MODEL`, etc.).
 - For `PRODUCT`, the compression ratio is fixed at **4×** in this version.
 - When used with `HYBRID` collections, quantization applies only to the **dense** vector.
@@ -97,7 +97,7 @@ Scalar quantization (recommended default):
 CREATE COLLECTION research_papers QUANTIZE SCALAR
 ```
 
-Scalar with explicit calibration and original vectors kept in RAM:
+Scalar with explicit calibration and quantized vectors pinned to RAM:
 ```sql
 CREATE COLLECTION research_papers QUANTIZE SCALAR QUANTILE 0.95 ALWAYS RAM
 ```

docs/index.html

@@ -114,7 +114,7 @@ <h1>QQL</h1>
     <a href="https://pypi.org/project/qql-cli/"><img src="https://img.shields.io/pypi/v/qql-cli?color=blue&label=PyPI" alt="PyPI version" /></a>
     <a href="https://pypi.org/project/qql-cli/"><img src="https://img.shields.io/pypi/pyversions/qql-cli" alt="Python versions" /></a>
     <a href="https://github.com/pavanjava/qql/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-MIT-green" alt="MIT License" /></a>
-    <a href="https://github.com/pavanjava/qql/actions"><img src="https://img.shields.io/badge/tests-371%20passing-brightgreen" alt="371 tests" /></a>
+    <a href="https://github.com/pavanjava/qql/actions"><img src="https://img.shields.io/badge/tests-375%20passing-brightgreen" alt="375 tests" /></a>
   </div>
 
   <pre><span class="cmt"># Install</span>
@@ -139,35 +139,35 @@ <h1>QQL</h1>
 <div class="links">
   <h2>Documentation</h2>
   <div class="grid">
-    <a class="card" href="getting-started.md">
+    <a class="card" href="getting-started">
       <h3>Getting Started</h3>
       <p>Installation, connecting to Qdrant, your first queries</p>
     </a>
-    <a class="card" href="insert.md">
+    <a class="card" href="insert">
       <h3>INSERT / INSERT BULK</h3>
       <p>Adding documents, batch inserts, payload types</p>
     </a>
-    <a class="card" href="search.md">
+    <a class="card" href="search">
       <h3>SEARCH / RECOMMEND</h3>
       <p>Semantic search, hybrid search, reranking, recommendations</p>
     </a>
-    <a class="card" href="filters.md">
+    <a class="card" href="filters">
       <h3>WHERE Filters</h3>
       <p>Full SQL-style filter operators — range, IN, MATCH, AND/OR/NOT</p>
     </a>
-    <a class="card" href="collections.md">
+    <a class="card" href="collections">
       <h3>Collections &amp; Quantization</h3>
       <p>CREATE, DROP, quantize (scalar/binary/product), payload indexes</p>
     </a>
-    <a class="card" href="scripts.md">
+    <a class="card" href="scripts">
       <h3>Scripts: EXECUTE / DUMP</h3>
       <p>Run script files, export collections for backup/migration</p>
     </a>
-    <a class="card" href="programmatic.md">
+    <a class="card" href="programmatic">
       <h3>Programmatic Usage</h3>
       <p>Use QQL as a Python library without the CLI</p>
     </a>
-    <a class="card" href="reference.md">
+    <a class="card" href="reference">
       <h3>Reference</h3>
       <p>Embedding models, config file, project structure, error guide</p>
     </a>
@@ -177,7 +177,7 @@ <h3>Reference</h3>
 <div class="cta">
   <a class="btn btn-primary" href="https://github.com/pavanjava/qql">View on GitHub</a>
   <a class="btn btn-secondary" href="https://pypi.org/project/qql-cli/">PyPI Package</a>
-  <a class="btn btn-secondary" href="getting-started.md">Get Started →</a>
+  <a class="btn btn-secondary" href="getting-started">Get Started →</a>
 </div>
 
 <footer>

docs/reference.md

@@ -159,7 +159,7 @@ Tests do not require a running Qdrant instance — the Qdrant client is mocked.
 pytest tests/ -v
 ```
 
-Expected output: **371 tests passing**.
+Expected output: **375 tests passing**.
 
 ---
 

docs/scripts.md

@@ -72,7 +72,9 @@ Done. 3/3 statement(s) succeeded.
 
 ## DUMP COLLECTION — export collection to a .qql script file
 
-Export every point in a collection to a `.qql` script file. The generated file is valid QQL — it can be re-imported with `qql execute` to restore or migrate the collection. Points are written in batches of 50 as `INSERT BULK` statements.
+Export every point in a collection to a `.qql` script file. The generated file is valid QQL that re-creates the collection and re-inserts all payload data. Points are written in batches of 50 as `INSERT BULK` statements.
+
+> **Scope of a dump:** The generated script preserves collection topology (dense vs hybrid) and all point payloads. It does **not** preserve quantization config, pinned model / vector dimensions, or payload indexes — those must be re-applied manually after import if needed.
 
 **CLI usage:**
 ```bash
@@ -136,7 +138,7 @@ INSERT BULK INTO COLLECTION medical_records VALUES [
 -- ============================================================
 ```
 
-**Round-trip workflow — backup and restore:**
+**Round-trip workflow — data migration / partial restore:**
 ```bash
 # 1. Dump the collection
 qql dump medical_records backup.qql

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "qql-cli"
-version = "2.0.0"
+version = "1.4.0"
 description = "QQL is a SQL-like query language and CLI for Qdrant vector database. Write INSERT, SEARCH, RECOMMEND, DELETE, and CREATE COLLECTION statements instead of Python SDK calls. Supports hybrid dense+sparse vector search, cross-encoder reranking, quantization (scalar, binary, product), WHERE clause filters, script execution, and collection dump/restore."
 readme = "README.md"
 license = { file = "LICENSE" }