Show me evidence of LangGraph
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AutoCare Agent: LangGraph connects request validation, planning, retrieval, tools, safety checks and response generation. 40 Diagnostic scenarios tested · unspecified. 40 vehicle-diagnostic scenarios; 1,000 PostgreSQL service-history records. Four tools: service-manual search, diagnostic-code lookup, maintenance-schedule retrieval and vehicle service-history lookup. FastAPI, PostgreSQL, Redis/Celery, Ollama and Docker Compose. Decision-support POC, not a substitute for a certified technician. Recall describes the 100-query retrieval evaluation, not field diagnostic accuracy. Separate lexical/dense scores and scenario pass rates are not supplied. Intelligent Patient Admission Triage Assistant: LangGraph orchestrates validation, scoring, LightGBM/XGBoost risk modeling, retrieval and explanation. ESI/MEWS deterministic scoring, LightGBM/XGBoost, FastAPI/Pydantic, Ollama, Redis/Celery, Docker Compose and GitHub Actions. In-progress research/portfolio system; synthetic Synthea / FHIR-compatible records, no hospital production deployment or clinical-validation result. RAGAS/Langfuse evaluation and Prometheus/Grafana/Loki observability are designed/planned. No completed benchmark values are supplied. GenAI Research Assistant: PDF ingestion, chunking, embedding, ANN benchmarking and answer generation in a Streamlit application. Python, LangGraph/LangChain, Sentence-Transformers, ChromaDB, FAISS, Annoy, Streamlit and RAGAS. Local research application and retrieval benchmark, not a production service benchmark. QPS and index build time are not application request latency. Benchmark hardware, query distribution, recall cutoff and full per-backend outputs are not supplied. Agentic LLM Evaluation Workflow for Resume Screening: A LangGraph workflow evaluates resume–job fit through typed extraction, gap analysis, deterministic score calibration and recommendation generation, with LangSmith tracing. Python pipeline accepts resume and job-description PDF/DOCX inputs; LangGraph runs parallel extraction followed by gap analysis, calibrated scoring and recommendation generation. LangSmith supports trace inspection and prompt debugging. Typed outputs and deterministic calibration support qualitative consistency claims; no benchmark dataset size, accuracy, precision, recall, F1 or agreement score is supplied. No validated hiring accuracy, bias reduction, recruiter productivity gain, ATS equivalence or production hiring outcome is established. The baseline workflow is completed; deployment remains in progress and must not be presented as a production service.