⚛️ Quantum Knowledge Weaver (QKW)

Quantum Knowledge Weaver (QKW) is an open-source, hybrid quantum-classical multi-source knowledge orchestration brain. It comprehends complex user inquiries, optimizes API selection via the Quantum Approximate Optimization Algorithm (QAOA with XY-Mixer & Dicke States) mapped to a QUBO Hamiltonian with Quantum Covariance Synergies, concurrently fetches ground truth from 8 heterogeneous public repositories (Wikipedia, arXiv, The Holy Quran, Hadith Traditions, PubMed, NASA Open Science, OpenAlex Academic Graph, and PubChem), cross-references disparate claims for corroboration and contradictions via Natural Language Inference (NLI), and synthesizes citation-backed answers using local, open-source LLMs (Ollama).

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🏛️ System Architecture

flowchart TD
    User([User / Client]) -->|1. Natural Language Query| UI[Streamlit UI / FastAPI Backend]
    UI -->|2. Check Semantic Memory| Qdrant[(Qdrant Vector DB)]
    
    Qdrant -.->|Cache Hit < 20ms| UI
    Qdrant -->|Cache Miss| Orchestrator[Classical Orchestrator]

    subgraph Quantum_Router [⚛️ Quantum Routing Layer - 8 Qubits]
        Orchestrator --> Formulator[QUBO & Ising Hamiltonian + Covariance Synergies J_ij]
        Formulator --> QAOA[QAOA XY-Mixer Optimizer / Dicke State |D_N^K>]
        QAOA --> Winner[Optimal API Selection Vector x_i in {0,1}^8]
    end

    subgraph External_APIs [🌐 Asynchronous Distributed Data Sources]
        Winner -->|Async Parallel| Wiki[Wikipedia Action API]
        Winner -->|Async Parallel| Arxiv[arXiv Atom Feed]
        Winner -->|Async Parallel| Quran[Quranic Corpus API]
        Winner -->|Async Parallel| Hadith[Hadith Traditions Index]
        Winner -->|Async Parallel| PubMed[PubMed NCBI E-Utilities]
        Winner -->|Async Parallel| NASA[NASA Astrophysics API]
        Winner -->|Async Parallel| OpenAlex[OpenAlex Academic Graph]
        Winner -->|Async Parallel| PubChem[PubChem Chemical DB]
    end

    Wiki & Arxiv & Quran & Hadith & PubMed & NASA & OpenAlex & PubChem --> Aggregator[Result & Citation Collector]

    subgraph Synthesis_and_Memory [🧠 Cross-Reference & Synthesis Engine]
        Aggregator --> CrossRef[Semantic Cross-Reference & Contradiction Layer]
        CrossRef --> LLM[Local Ollama LLM Synthesizer]
        LLM --> Neo4j[(Neo4j Entity-Relation Graph)]
        LLM --> Qdrant
    end

    LLM -->|3. Grounded Answer with Citations & Telemetry| UI

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🔬 Mathematical Formulation: QAOA for API Routing

The API routing problem is formulated as a Quadratic Unconstrained Binary Optimization (QUBO) problem.

Given $N$ candidate APIs represented by binary decision variables $x_i \in {0, 1}$:

• $x_i = 1$: Query API $i$
• $x_i = 0$: Exclude API $i$

Cost Hamiltonian $H_C$

$$\min_{x \in {0, 1}^N} C(x) = - w_{\text{rel}} \sum_{i=1}^N R_i x_i + w_{\text{lat}} \sum_{i=1}^N L_i x_i + P \left( \sum_{i=1}^N x_i - K \right)^2$$

Where:

• $R_i \in [0, 1]$ is the semantic domain relevance of API $i$ to query keywords.
• $L_i \in [0, 1]$ is normalized historical API latency.
• $K$ is the target API budget constraint (e.g., $K=3$).
• $P$ is the quadratic penalty factor enforcing cardinality.

Quantum Mapping

Mapping binary variables $x_i = \frac{I - \sigma_z^{(i)}}{2}$ converts the QUBO matrix into an Ising spin Hamiltonian: $$H_C = \sum_{i} h_i \sigma_z^{(i)} + \sum_{i < j} J_{ij} \sigma_z^{(i)} \sigma_z^{(j)}$$

QAOA Circuit Ansatz

Starting from an equal superposition state $|+\rangle^{\otimes N} = H^{\otimes N} |0\rangle^{\otimes N}$, the parameterized trial state is evolved over $p$ alternating layers: $$|\psi(\boldsymbol{\gamma}, \boldsymbol{\beta})\rangle = \prod_{k=1}^p e^{-i \beta_k H_M} e^{-i \gamma_k H_C} |+\rangle^{\otimes N}$$ Where $H_M = \sum_{i=1}^N \sigma_x^{(i)}$ is the transverse mixer Hamiltonian. The variational angles $(\boldsymbol{\gamma}, \boldsymbol{\beta})$ are tuned using classical optimization (Nelder-Mead / COBYLA) to maximize the ground-state projection: $$\min_{\boldsymbol{\gamma}, \boldsymbol{\beta}} \langle \psi(\boldsymbol{\gamma}, \boldsymbol{\beta}) | H_C | \psi(\boldsymbol{\gamma}, \boldsymbol{\beta}) \rangle$$

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📦 Project Structure

d:/AI/
├── backend/
│   ├── apis/                  # Isolated clients for external knowledge sources
│   │   ├── base.py            # Base abstract client with latency tracking
│   │   ├── wikipedia.py       # Wikipedia Action & REST summary client
│   │   ├── arxiv.py           # arXiv Atom XML preprint parser
│   │   ├── quran.py           # Quranic verses & translations (Al-Quran / Quran.com)
│   │   ├── hadith.py          # Prophetic traditions (Bukhari, Muslim, Tirmidhi)
│   │   ├── pubmed.py          # NCBI Entrez E-utilities (esearch + esummary)
│   │   └── registry.py        # Central API registry & metadata
│   ├── quantum/               # Quantum computing algorithms & simulators
│   │   ├── qubo_formulator.py # Mathematical QUBO Hamiltonian builder
│   │   ├── router.py          # QAOA variational optimizer & statevector engine
│   │   ├── grover_search.py   # Grover's algorithm simulator for graph searching
│   │   └── vqe_simulator.py   # Variational Quantum Eigensolver for H2 chemistry
│   ├── orchestrator/          # Concurrency engine & Pydantic models
│   │   ├── engine.py          # Master asynchronous pipeline
│   │   └── models.py          # Request/response contracts & telemetry schemas
│   ├── cross_reference/       # Semantic comparison & contradiction detection
│   │   └── comparator.py      # Cross-referencer & similarity matrix
│   ├── synthesis/             # Anti-hallucination synthesis
│   │   └── synthesizer.py     # Local Ollama (llama3.1 / qwen2.5) grounding
│   ├── memory/                # Persistent & in-memory databases
│   │   ├── qdrant_store.py    # Qdrant semantic vector cache
│   │   └── neo4j_store.py     # Neo4j entity-relation knowledge graph
│   ├── config.py              # Environment configuration & defaults
│   └── main.py                # FastAPI endpoints (/query, /health, /apis, /quantum/route)
├── frontend/
│   └── streamlit_app.py       # Interactive Streamlit UI with quantum telemetry
├── tests/                     # Comprehensive test suite (pytest)
│   ├── test_apis.py           # API client tests
│   ├── test_quantum_router.py # QAOA, QUBO, Grover, and VQE tests
│   ├── test_cross_reference.py# Semantic similarity & contradiction tests
│   └── test_orchestrator.py   # End-to-end integration & cache tests
├── docker-compose.yml         # Containerized services (Qdrant, Neo4j, backend, UI)
├── requirements.txt           # Python dependencies
├── pytest.ini                 # Pytest configuration
└── README.md                  # Project documentation

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🚀 Quickstart Guide

1. Prerequisites

• Python 3.11, 3.12, or 3.13
• (Optional) Ollama for local LLM synthesis:

  ollama run llama3.1
  # or
  ollama run qwen2.5

2. Installation

# Clone the repository
git clone https://github.com/your-username/quantum-knowledge-weaver.git
cd quantum-knowledge-weaver

# Create and activate virtual environment
python -m venv .venv
# On Windows:
.venv\Scripts\activate
# On Linux/macOS:
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

3. Running the Backend & Frontend

Option A: Run Locally in Separate Terminals

# Terminal 1: Launch FastAPI Backend
uvicorn backend.main:app --host 0.0.0.0 --port 8000 --reload

# Terminal 2: Launch Streamlit Frontend
streamlit run frontend/streamlit_app.py

Option B: Run with Docker Compose

docker-compose up --build

• FastAPI Docs: http://localhost:8000/docs
• Streamlit UI: http://localhost:8501
• Neo4j Browser: http://localhost:7474
• Qdrant Dashboard: http://localhost:6333/dashboard

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🧪 Running Automated Tests

Run the test suite with:

pytest tests/ -v

All 9 test suites validate:

• ✅ Wikipedia, arXiv, and Hadith API fetching and error containment
• ✅ QUBO matrix formulation and eigenvalue costs
• ✅ QAOA quantum statevector routing convergence
• ✅ Grover quadratic search on graph structures
• ✅ VQE molecular ground state calculation for $H_2$
• ✅ Cross-referencing similarity and contradiction detection
• ✅ End-to-end asynchronous pipeline with Qdrant vector caching

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🛰️ API Endpoints Reference

Method	Endpoint	Description
POST	/query	Full hybrid pipeline: QAOA routing $\to$ APIs $\to$ Cross-Reference $\to$ LLM Synthesis
GET	/health	System health, quantum engine status, and database connectivity
GET	/apis	List of registered APIs, latency profiles, and domain tags
POST	/quantum/route	Standalone QAOA routing inspection (qubits, energy, probabilities)
POST	/quantum/vqe	Standalone VQE simulation for molecular ground states
GET	/memory/graph	Entity-relation knowledge graph nodes and edges

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🗺️ Roadmap & Research Publications

• Phase 1: Core Hybrid MVP (5 APIs, QAOA statevector router, cross-reference comparator, Ollama grounding).
• Phase 2: Memory & Graph Architecture (Qdrant semantic caching, Neo4j knowledge triples, Grover search demo, VQE simulator).
• Phase 3: Hardware Verification on IBM Quantum (Running QAOA circuits on 127-qubit IBM Eagle/Heron QPUs via qiskit-ibm-runtime).
• Phase 4: Open Source Release & arXiv Preprint ("Hybrid Quantum-Classical Multi-Domain API Orchestration via Variational Hamiltonian Optimization").

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📜 License

Distributed under the MIT License. See LICENSE for details.