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/entity_extractor.py

@@ -0,0 +1,66 @@
+"""
+Entity Extractor — LangExtract + DeepSeek entity extraction.
+Independent implementation for the GraphRAG Studio backend.
+"""
+from __future__ import annotations
+
+import os
+from pathlib import Path
+
+from dotenv import load_dotenv
+
+import langextract as lx
+from langextract.providers.openai import OpenAILanguageModel
+
+load_dotenv(Path(__file__).parent.parent / ".env", override=True)
+
+DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_API_KEY", "")
+DEEPSEEK_BASE_URL = os.getenv("DEEPSEEK_BASE_URL", "https://api.deepseek.com")
+MODEL_ID = "deepseek-chat"
+
+PROMPT_DESCRIPTION = (
+    "Extract named entities from the text in order of appearance. "
+    "Entity types: TECHNOLOGY (software, algorithms, models, tools), "
+    "ORGANIZATION (companies, research groups, institutions), "
+    "PERSON (individual people), "
+    "LOCATION (places, geographic entities), "
+    "CONCEPT (technical concepts, methodologies, frameworks)."
+)
+
+EXAMPLES = [
+    lx.data.ExampleData(
+        text=(
+            "LangChain is a framework created by Harrison Chase for building "
+            "LLM applications. It integrates with OpenAI models and Pinecone "
+            "vector database for semantic search."
+        ),
+        extractions=[
+            lx.data.Extraction(extraction_class="TECHNOLOGY", extraction_text="LangChain"),
+            lx.data.Extraction(extraction_class="PERSON", extraction_text="Harrison Chase"),
+            lx.data.Extraction(extraction_class="CONCEPT", extraction_text="LLM applications"),
+            lx.data.Extraction(extraction_class="TECHNOLOGY", extraction_text="OpenAI models"),
+            lx.data.Extraction(extraction_class="TECHNOLOGY", extraction_text="Pinecone"),
+            lx.data.Extraction(extraction_class="CONCEPT", extraction_text="semantic search"),
+        ],
+    )
+]
+
+
+def create_model() -> OpenAILanguageModel:
+    if not DEEPSEEK_API_KEY:
+        raise ValueError("DEEPSEEK_API_KEY not set in backend/.env")
+    return OpenAILanguageModel(
+        model_id=MODEL_ID,
+        api_key=DEEPSEEK_API_KEY,
+        base_url=DEEPSEEK_BASE_URL,
+    )
+
+
+def extract_entities(page_text: str, model: OpenAILanguageModel) -> lx.data.AnnotatedDocument:
+    return lx.extract(
+        text_or_documents=page_text,
+        prompt_description=PROMPT_DESCRIPTION,
+        examples=EXAMPLES,
+        model=model,
+        show_progress=False,
+    )