Version update and documentation upto date

.github/workflows/ci.yml

@@ -23,7 +23,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
     steps:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v5

CHANGELOG.md

@@ -5,6 +5,26 @@ All notable changes to **LongParser** are documented here.
 This project follows [Semantic Versioning](https://semver.org/) and
 [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
 
+## [0.1.3] — 2026-04-13
+
+### Fixed
+
+- **Source code**: Added `DocumentPipeline` as a public alias for `PipelineOrchestrator` —
+  docs, quickstart, and all examples now use this name consistently
+- **Documentation**: Fixed wrong coverage path `long_parser` → `longparser` in `CONTRIBUTING.md`
+- **Documentation**: Replaced stale `cleanrag-api` reference in Docker deployment docs
+- **Documentation**: Standardized Gemini API key env var to `GOOGLE_API_KEY` across all docs
+- **Source code**: Updated default LLM model fallback from `gpt-4o` to `gpt-5.3` in
+  `schemas.py`, `llm_chain.py`, and `engine.py`
+- **Source code**: Renamed stale `cleanrag:` Redis key prefix to `longparser:` in embeddings
+
+### Changed
+
+- Python 3.13 added to CI matrix, badges, and installation docs
+- `SECURITY.md` updated with Redis rate-limiting and CORS threat mitigations
+
+---
+
 ## [0.1.2] — 2026-04-05
 
 ### Changed

CONTRIBUTING.md

@@ -84,7 +84,7 @@ Use Python 3.10+ type hints. All public API must be fully annotated.
 uv run pytest tests/unit/ -v
 
 # With coverage:
-uv run pytest tests/unit/ --cov=src/long_parser --cov-report=term-missing
+uv run pytest tests/unit/ --cov=src/longparser --cov-report=term-missing
 
 # Full test suite (requires MongoDB + Redis):
 uv run pytest tests/ -v

README.md

@@ -18,7 +18,7 @@
       <img src="https://static.pepy.tech/badge/longparser/month" alt="Monthly Downloads">
     </a>
     <a href="https://www.python.org/">
-      <img src="https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12-blue.svg" alt="Python">
+      <img src="https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue.svg" alt="Python">
     </a>
     <a href="LICENSE">
       <img src="https://img.shields.io/badge/License-MIT-brightgreen.svg" alt="MIT License">
@@ -105,9 +105,9 @@ pip install "longparser[cpu]"
 ### Python SDK
 
 ```python
-from longparser import PipelineOrchestrator, ProcessingConfig
+from longparser import DocumentPipeline, ProcessingConfig
 
-pipeline = PipelineOrchestrator()
+pipeline = DocumentPipeline(ProcessingConfig())
 result = pipeline.process_file("document.pdf")
 
 print(f"Pages: {result.document.metadata.total_pages}")
@@ -186,7 +186,7 @@ src/longparser/
 ├── schemas.py           ← core Pydantic models (Document, Block, Chunk, …)
 ├── extractors/          ← Docling, LaTeX OCR backends
 ├── chunkers/            ← HybridChunker
-├── pipeline/            ← PipelineOrchestrator
+├── pipeline/            ← DocumentPipeline
 ├── integrations/        ← LangChain loader & LlamaIndex reader
 ├── utils/               ← shared helpers (RTL detection, …)
 └── server/              ← REST API layer

SECURITY.md

@@ -35,6 +35,8 @@ Key risks:
 | **MongoDB injection** | Motor driver + typed Pydantic inputs prevent injection |
 | **SSRF via webhook** | No outbound HTTP made based on user input |
 | **Hallucinated citations** | Citation IDs validated against retrieved set before returning to client |
+| **DDoS / Spam via API** | Route-level Rate Limiting strictly isolated per tenant via Redis |
+| **Cross-Origin attacks** | Configurable CORS restrictions and strict Tenant Isolation |
 
 ## Dependency Security
 

docs/changelog.md

@@ -5,6 +5,26 @@ All notable changes to **LongParser** are documented here.
 This project follows [Semantic Versioning](https://semver.org/) and
 [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
 
+## [0.1.3] — 2026-04-13
+
+### Fixed
+
+- **Source code**: Added `DocumentPipeline` as a public alias for `PipelineOrchestrator` —
+  docs, quickstart, and all examples now use this name consistently
+- **Documentation**: Fixed wrong coverage path `long_parser` → `longparser` in `CONTRIBUTING.md`
+- **Documentation**: Replaced stale `cleanrag-api` reference in Docker deployment docs
+- **Documentation**: Standardized Gemini API key env var to `GOOGLE_API_KEY` across all docs
+- **Source code**: Updated default LLM model fallback from `gpt-4o` to `gpt-5.3` in
+  `schemas.py`, `llm_chain.py`, and `engine.py`
+- **Source code**: Renamed stale `cleanrag:` Redis key prefix to `longparser:` in embeddings
+
+### Changed
+
+- Python 3.13 added to CI matrix, badges, and installation docs
+- `SECURITY.md` updated with Redis rate-limiting and CORS threat mitigations
+
+---
+
 ## [0.1.2] — 2026-04-05
 
 ### Changed

docs/contributing.md

@@ -84,7 +84,7 @@ Use Python 3.10+ type hints. All public API must be fully annotated.
 uv run pytest tests/unit/ -v
 
 # With coverage:
-uv run pytest tests/unit/ --cov=src/long_parser --cov-report=term-missing
+uv run pytest tests/unit/ --cov=src/longparser --cov-report=term-missing
 
 # Full test suite (requires MongoDB + Redis):
 uv run pytest tests/ -v

docs/deployment/docker.md

@@ -49,5 +49,5 @@ docker compose up --scale longparser=3
 
 ```bash
 curl http://localhost:8000/health
-# {"status": "ok", "service": "cleanrag-api"}
+# {"status": "ok", "service": "longparser-api"}
 ```

docs/deployment/environment.md

@@ -16,7 +16,7 @@ Copy `.env.example` to `.env` and configure for your deployment.
 | `LONGPARSER_LLM_PROVIDER` | `openai` | LLM provider |
 | `LONGPARSER_LLM_MODEL` | _(provider default)_ | Model name |
 | `OPENAI_API_KEY` | — | OpenAI API key |
-| `GEMINI_API_KEY` | — | Google Gemini API key |
+| `GOOGLE_API_KEY` | — | Google Gemini API key |
 | `GROQ_API_KEY` | — | Groq API key |
 | `OPENROUTER_API_KEY` | — | OpenRouter API key |
 

docs/getting-started/configuration.md

@@ -33,7 +33,7 @@ cp .env.example .env
 |---|---|
 | `LONGPARSER_LLM_PROVIDER` | `openai` / `gemini` / `groq` / `openrouter` |
 | `LONGPARSER_LLM_MODEL` | Model name (uses provider default if unset) |
-| `GEMINI_API_KEY` | For Google Gemini |
+| `GOOGLE_API_KEY` | For Google Gemini |
 | `GROQ_API_KEY` | For Groq |
 
 ## Vector Store

docs/getting-started/installation.md

@@ -2,7 +2,7 @@
 
 ## Requirements
 
-- Python 3.10, 3.11, or 3.12
+- Python 3.10, 3.11, 3.12, or 3.13
 - Tesseract OCR (`brew install tesseract` / `apt install tesseract-ocr`)
 
 ---
@@ -104,5 +104,5 @@ The server starts on `http://localhost:8000`.
 
 ```python
 import longparser
-print(longparser.__version__)  # 0.1.2
+print(longparser.__version__)  # 0.1.3
 ```

docs/getting-started/quickstart.md

@@ -17,11 +17,11 @@ from longparser import DocumentPipeline, ProcessingConfig
 pipeline = DocumentPipeline(ProcessingConfig())
 
 # Parse a PDF
-doc = pipeline.process("research_paper.pdf")
+result = pipeline.process_file("research_paper.pdf")
 
-print(f"Pages: {len(doc.pages)}")
-print(f"Blocks: {len(doc.blocks)}")
-print(f"Chunks: {len(doc.chunks)}")
+print(f"Pages: {result.document.metadata.total_pages}")
+print(f"Chunks: {len(result.chunks)}")
+print(result.chunks[0].text)
 ```
 
 ## 3. Inspect Chunks

docs/guide/chat.md

@@ -70,6 +70,6 @@ Every answer's `cited_chunk_ids` are validated against the retrieved set. IDs no
 | Provider | Key |
 |---|---|
 | OpenAI | `OPENAI_API_KEY` |
-| Google Gemini | `GEMINI_API_KEY` |
+| Google Gemini | `GOOGLE_API_KEY` |
 | Groq | `GROQ_API_KEY` |
 | OpenRouter | `OPENROUTER_API_KEY` |

docs/guide/parsing.md

@@ -18,7 +18,7 @@ LongParser uses **Docling** with Tesseract CLI OCR as its extraction engine —
 from longparser import DocumentPipeline, ProcessingConfig
 
 pipeline = DocumentPipeline(ProcessingConfig())
-doc = pipeline.process("paper.pdf")
+result = pipeline.process_file("paper.pdf")
 ```
 
 ## Formula Modes
@@ -36,15 +36,15 @@ config = ProcessingConfig(formula_mode="smart")
 
 ```python
 # Pages
-for page in doc.pages:
+for page in result.document.pages:
     print(f"Page {page.page_number}: {page.width}x{page.height}")
 
 # Blocks (semantic units)
-for block in doc.blocks:
+for block in result.document.blocks:
     print(f"[{block.type}] p={block.provenance.page_number}: {block.text[:80]}")
 
 # Chunks (RAG-ready)
-for chunk in doc.chunks:
+for chunk in result.chunks:
     print(f"{chunk.chunk_type} | {chunk.token_count} tokens | pages={chunk.page_numbers}")
 ```
 

docs/index.md

@@ -16,7 +16,7 @@
       <img src="https://static.pepy.tech/badge/longparser/month" alt="Monthly Downloads">
     </a>&nbsp;
     <a href="https://www.python.org/">
-      <img src="https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12-blue.svg" alt="Python">
+      <img src="https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue.svg" alt="Python">
     </a>&nbsp;
     <a href="https://github.com/ENDEVSOLS/LongParser/blob/main/LICENSE">
       <img src="https://img.shields.io/badge/License-MIT-brightgreen.svg" alt="MIT License">
@@ -57,9 +57,10 @@ pip install longparser
 from longparser import DocumentPipeline, ProcessingConfig
 
 pipeline = DocumentPipeline(ProcessingConfig())
-doc = pipeline.process("report.pdf")
+result = pipeline.process_file("report.pdf")
 
-print(f"Extracted {len(doc.blocks)} blocks, {len(doc.chunks)} chunks")
+print(f"Chunks: {len(result.chunks)}")
+print(result.chunks[0].text)
 ```
 
 ---

docs/reference/pipeline.md

@@ -7,39 +7,49 @@ The `DocumentPipeline` is the main entry point for LongParser's extraction pipel
 ```python
 from longparser import DocumentPipeline, ProcessingConfig
 
-pipeline = DocumentPipeline(config=ProcessingConfig())
-doc = pipeline.process("document.pdf")
+pipeline = DocumentPipeline(ProcessingConfig())
+result = pipeline.process_file("document.pdf")
 ```
 
 ### Constructor
 
 ```python
-DocumentPipeline(config: ProcessingConfig)
+DocumentPipeline(config: ProcessingConfig | None = None)
 ```
 
 | Parameter | Type | Description |
 |---|---|---|
-| `config` | `ProcessingConfig` | Extraction and chunking configuration |
+| `config` | `ProcessingConfig \| None` | Extraction and chunking configuration (uses defaults if `None`) |
 
 ### Methods
 
-#### `process(file_path)`
+#### `process_file(file_path)`
 
 Process a document end-to-end through Extract → Validate → Chunk.
 
 ```python
-doc = pipeline.process("report.pdf")
-# Returns: longparser.schemas.Document
+result = pipeline.process_file("report.pdf")
+# Returns: longparser.pipeline.PipelineResult
 ```
 
-**Returns:** `Document` with `.pages`, `.blocks`, `.chunks` populated.
+**Returns:** `PipelineResult` with `.document` and `.chunks` populated.
+
+#### `process(request)`
+
+Process a document from a `JobRequest` object.
+
+```python
+from longparser import JobRequest
+request = JobRequest(file_path="report.pdf")
+result = pipeline.process(request)
+```
 
 #### `process_batch(file_paths)`
 
 Process multiple documents sequentially.
 
 ```python
-docs = pipeline.process_batch(["a.pdf", "b.docx", "c.pptx"])
+results = pipeline.process_batch(["a.pdf", "b.docx", "c.pptx"])
 ```
 
 ## ProcessingConfig

docs/reference/schemas.md

@@ -4,7 +4,7 @@ Core data models used throughout LongParser.
 
 ## Document
 
-Top-level container returned by `DocumentPipeline.process()`.
+Top-level container returned by `DocumentPipeline.process_file()`.
 
 ```python
 class Document:

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "longparser"
-version = "0.1.2"
+version = "0.1.3"
 description = "Privacy-first document intelligence engine — converts PDFs, DOCX, PPTX, XLSX, and CSV into AI-ready Markdown + structured JSON for RAG pipelines."
 readme = {file = "README.md", content-type = "text/markdown"}
 requires-python = ">=3.10"

src/longparser/__init__.py

@@ -9,23 +9,23 @@
 
 Quick start::
 
-    from longparser import PipelineOrchestrator, ProcessingConfig
+    from longparser import DocumentPipeline, ProcessingConfig
 
-    pipeline = PipelineOrchestrator()
+    pipeline = DocumentPipeline(ProcessingConfig())
     result = pipeline.process_file("document.pdf")
     print(result.chunks[0].text)
 
 For the full REST API server::
 
     uv run uvicorn longparser.server.app:app --reload --port 8000
 
-See :class:`~longparser.pipeline.PipelineOrchestrator` for the main SDK entry
+See :class:`~longparser.pipeline.DocumentPipeline` for the main SDK entry
 point and :mod:`longparser.server` for the REST API layer.
 """
 
 from __future__ import annotations
 
-__version__ = "0.1.2"
+__version__ = "0.1.3"
 __author__ = "ENDEVSOLS Team"
 __license__ = "MIT"
 
@@ -62,6 +62,9 @@ def __getattr__(name: str):
     if name == "PipelineOrchestrator":
         from .pipeline import PipelineOrchestrator
         return PipelineOrchestrator
+    if name == "DocumentPipeline":
+        from .pipeline import DocumentPipeline
+        return DocumentPipeline
     if name == "PipelineResult":
         from .pipeline import PipelineResult
         return PipelineResult
@@ -99,6 +102,7 @@ def __getattr__(name: str):
     # Lazily imported (require extras)
     "DoclingExtractor",
     "PipelineOrchestrator",
+    "DocumentPipeline",
     "PipelineResult",
     "HybridChunker",
 ]

src/longparser/pipeline/__init__.py

@@ -2,7 +2,11 @@
 
 from .orchestrator import PipelineOrchestrator, PipelineResult
 
+# Public alias — docs and quickstart use this name
+DocumentPipeline = PipelineOrchestrator
+
 __all__ = [
     "PipelineOrchestrator",
+    "DocumentPipeline",
     "PipelineResult",
 ]

src/longparser/server/chat/engine.py

@@ -76,7 +76,7 @@
 # Token Counting (model-aware) — kept as custom logic
 # ---------------------------------------------------------------------------
 
-def count_tokens(text: str, model: str = "gpt-4o") -> int:
+def count_tokens(text: str, model: str = "gpt-5.3") -> int:
     """Count tokens — exact for OpenAI models, conservative approx for others."""
     try:
         import tiktoken
@@ -96,7 +96,7 @@ def budget_trim(
     recent_turns: list[dict],
     rolling_summary: str,
     long_term_facts: list[dict],
-    model: str = "gpt-4o",
+    model: str = "gpt-5.3",
     max_prompt_tokens: int = 6000,
 ) -> dict:
     """Priority-ordered truncation of prompt variables to fit token budget.

src/longparser/server/chat/llm_chain.py

@@ -115,7 +115,7 @@ def get_chat_model(
     """
     config = config or ChatConfig()
     provider = provider or config.llm_provider
-    model = model or config.llm_model or DEFAULT_MODELS.get(provider, "gpt-4o")
+    model = model or config.llm_model or DEFAULT_MODELS.get(provider, "gpt-5.3")
     max_tokens = max_tokens or config.max_output_tokens
 
     creator = _CREATORS.get(provider)