GraphRAG Studio — initial commit: multimodal RAG system with KG visualization

Full-stack application for document-to-knowledge-graph pipeline:
- Backend: FastAPI + LangGraph ReAct agent + DeepSeek + MinerU parsing
- Frontend: React 19 + Vite + D3.js + shadcn/ui
- Pipeline: MinerU parsing → LangExtract entity extraction → KG building

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

backend/pipeline/text_assembler.py

@@ -0,0 +1,107 @@
+"""
+Text Assembler — MinerU content_list.json → per-page plain text.
+Independent implementation for the GraphRAG Studio backend.
+"""
+from __future__ import annotations
+
+import dataclasses
+import json
+from collections import defaultdict
+from pathlib import Path
+
+from bs4 import BeautifulSoup
+
+
+@dataclasses.dataclass
+class BlockSpan:
+    block_index: int
+    block_type: str
+    page_idx: int
+    char_start: int
+    char_end: int
+    bbox: list
+
+
+@dataclasses.dataclass
+class PageText:
+    page_idx: int
+    text: str
+    block_spans: list[BlockSpan]
+
+
+def html_table_to_text(table_body: str) -> str:
+    soup = BeautifulSoup(table_body, "html.parser")
+    rows = []
+    for tr in soup.find_all("tr"):
+        cells = [td.get_text(strip=True) for td in tr.find_all(["td", "th"])]
+        rows.append(" | ".join(cells))
+    return "\n".join(rows)
+
+
+def load_content_list(path: Path) -> list[dict]:
+    if path.is_dir():
+        matches = list(path.glob("*_content_list.json"))
+        if not matches:
+            matches = list(path.glob("*content_list.json"))
+        if not matches:
+            raise FileNotFoundError(f"No content_list.json found in {path}")
+        path = matches[0]
+    with open(path, "r", encoding="utf-8") as f:
+        return json.load(f)
+
+
+def assemble_pages(content_list: list[dict]) -> list[PageText]:
+    pages: dict[int, list[tuple[int, dict]]] = defaultdict(list)
+    for i, block in enumerate(content_list):
+        page_idx = block.get("page_idx", 0)
+        pages[page_idx].append((i, block))
+
+    result = []
+    for page_idx in sorted(pages.keys()):
+        blocks = pages[page_idx]
+        buffer = []
+        spans = []
+        cursor = 0
+
+        for block_index, block in blocks:
+            block_type = block.get("type", "unknown")
+            bbox = block.get("bbox", [0, 0, 0, 0])
+
+            if block_type == "text":
+                block_text = block.get("text", "").rstrip()
+            elif block_type == "table":
+                table_body = block.get("table_body", "")
+                block_text = html_table_to_text(table_body) if table_body else ""
+            else:
+                continue
+
+            if not block_text:
+                continue
+
+            char_start = cursor
+            buffer.append(block_text)
+            cursor += len(block_text)
+            char_end = cursor
+
+            spans.append(BlockSpan(
+                block_index=block_index,
+                block_type=block_type,
+                page_idx=page_idx,
+                char_start=char_start,
+                char_end=char_end,
+                bbox=bbox,
+            ))
+            buffer.append("\n")
+            cursor += 1
+
+        text = "".join(buffer).rstrip("\n")
+        result.append(PageText(page_idx=page_idx, text=text, block_spans=spans))
+
+    return result
+
+
+def count_blocks_by_type(content_list: list[dict]) -> dict[str, int]:
+    counts: dict[str, int] = defaultdict(int)
+    for block in content_list:
+        counts[block.get("type", "unknown")] += 1
+    return dict(counts)