chore: import upstream snapshot with attribution

.github/ISSUE_TEMPLATE/benchmark.yml

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+name: Benchmarking
+description: Add, update, or fix benchmark cases for zvec
+title: "[Benchmark]: "
+labels: ["benchmark"]
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Use this for benchmark-related work: new test cases, CI integration, or performance regression tracking.
+  
+  - type: input
+    id: benchmark_type
+    attributes:
+      label: Benchmark Type
+      description: e.g., filtered search, batch insert, recall@k, ARM64 vs x86
+    validations:
+      required: true
+  
+  - type: textarea
+    id: goal
+    attributes:
+      label: Goal
+      description: What performance aspect are you measuring or improving?
+    validations:
+      required: true
+  
+  - type: textarea
+    id: methodology
+    attributes:
+      label: Methodology
+      description: Dataset, query size, hardware, metrics (latency, throughput, memory)
+    validations:
+      required: true
+  
+  - type: textarea
+    id: baseline
+    attributes:
+      label: Baseline (if applicable)
+      description: Current performance numbers or competing systems for comparison.
+    validations:
+      required: false
+  
+  - type: textarea
+    id: ci_integration
+    attributes:
+      label: CI Integration Plan
+      description: Should this run in CI? How often?
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/bug_report.yml

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+name: Bug Report
+description: Report a bug or unexpected behavior (e.g., crash, incorrect vector query, memory leak)
+title: "[Bug]: "
+labels: ["bug", "triage"]
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Thank you for reporting! Please provide detailed info so we can reproduce and fix it quickly.
+
+  - type: textarea
+    id: description
+    attributes:
+      label: Description
+      description: What happened? What did you expect?
+      placeholder: |
+        e.g. "Query with vector field crashes when using Zvec Python API"
+    validations:
+      required: true
+
+  - type: textarea
+    id: steps_to_reproduce
+    attributes:
+      label: Steps to Reproduce
+      description: Exact steps to trigger the issue (code snippets welcome)
+      placeholder: |
+        1. Build Zvec with CMake (Debug/Release)
+        2. Run Python script: `python test.py`
+        3. Call `collection.query(VectorQuery())`
+        4. Process segfaults / hangs / returns wrong results
+      render: python
+    validations:
+      required: true
+
+  - type: textarea
+    id: logs_or_trace
+    attributes:
+      label: Logs / Stack Trace
+      description: Paste relevant logs, LLDB/GDB backtrace, or CI failures
+      placeholder: |
+        Thread 1 "python" received signal SIGSEGV, Segmentation fault.
+        0x0000000104a2c3f0 in std::__1::shared_ptr<...>::...
+      render: shell
+    validations:
+      required: false
+
+  - type: input
+    id: os
+    attributes:
+      label: Operating System
+      placeholder: macOS 14 (M1), Ubuntu 22.04, Windows 11 (WSL2)
+    validations:
+      required: true
+
+  - type: input
+    id: build_env
+    attributes:
+      label: Build & Runtime Environment
+      description: Compiler, CMake, Python, key dependencies
+      placeholder: |
+        clang 15.0.0, CMake 4.1.2, Python 3.11.9, magic_enum v0.9.7 (via git submodule)
+    validations:
+      required: true
+
+  - type: checkboxes
+    id: additional_context
+    attributes:
+      label: Additional Context
+      options:
+        - label: I've checked `git status` — no uncommitted submodule changes
+        - label: I built with `CMAKE_BUILD_TYPE=Debug`
+        - label: This occurs with or without `COVERAGE=ON`
+        - label: The issue involves Python ↔ C++ integration (pybind11)

.github/ISSUE_TEMPLATE/config.yml

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+blank_issues_enabled: false
+contact_links:
+  - name: Documentation
+    url: https://zvec.org/en/
+    about: Check the quickstart, build guide, and API docs first.
+
+  - name: Python API Examples
+    url: https://zvec.org/en/docs/quickstart/
+    about: See working usage examples.

.github/ISSUE_TEMPLATE/enhancement.yml

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+name: Enhancement
+description: Improve an existing feature or component
+title: "[Enhance]: "
+labels: ["enhancement"]
+body:
+  - type: markdown
+    attributes:
+      value: |
+        This template is for improving existing functionality (e.g., performance, usability, robustness).
+  
+  - type: input
+    id: component
+    attributes:
+      label: Affected Component
+      description: e.g., HNSW index, buffer manager, Python API
+    validations:
+      required: true
+  
+  - type: textarea
+    id: current
+    attributes:
+      label: Current Behavior
+      description: What is the current state and its limitations?
+    validations:
+      required: true
+  
+  - type: textarea
+    id: desired
+    attributes:
+      label: Desired Improvement
+      description: What should be improved and how?
+    validations:
+      required: true
+  
+  - type: textarea
+    id: impact
+    attributes:
+      label: Impact
+      description: How will this benefit users? (e.g., faster queries, lower memory, easier integration)
+    validations:
+      required: true

.github/ISSUE_TEMPLATE/feature_request.yml

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+name: Feature Request
+description: Suggest a new feature or improvement (e.g., better memory control, new query option)
+title: "[Feature]: "
+labels: ["feature"]
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Thanks for your idea! Help us understand the motivation and scope.
+
+  - type: textarea
+    id: problem_or_motivation
+    attributes:
+      label: Problem / Motivation
+      description: What problem does this solve? Why is it needed?
+      placeholder: |
+        e.g. "Current vector queries don't allow filtering by metadata + distance threshold at once"
+    validations:
+      required: true
+
+  - type: textarea
+    id: proposed_solution
+    attributes:
+      label: Proposed Solution
+      description: How should it work? API sketch or pseudocode welcome.
+      placeholder: |
+        Add `filter=` and `max_distance=` args to `Zvec.query()`:
+        ```python
+        results = db.query(vector, filter="category == 'A'", max_distance=0.5)
+        ```
+      render: python
+    validations:
+      required: false
+
+  - type: textarea
+    id: alternatives
+    attributes:
+      label: Alternatives Considered
+      description: Are there workarounds? Why not use them?
+    validations:
+      required: false
+
+  - type: dropdown
+    id: impact_area
+    attributes:
+      label: Affected Area
+      multiple: true
+      options:
+        - label: C++ Core (storage, indexing)
+        - label: Python API / Bindings
+        - label: Build System (CMake, Homebrew pkg)
+        - label: Testing / CI / Coverage
+        - label: Documentation
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/integration.yml

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+name: Ecosystem Integration
+description: Integrate zvec with external frameworks (e.g., LangChain, LlamaIndex)
+title: "[Integration]: "
+labels: ["integration"]
+body:
+  - type: input
+    id: framework
+    attributes:
+      label: Target Framework
+      description: e.g., LangChain, LlamaIndex, Haystack
+    validations:
+      required: true
+  
+  - type: textarea
+    id: motivation
+    attributes:
+      label: Motivation
+      description: Why integrate with this framework? Who benefits?
+    validations:
+      required: true
+  
+  - type: textarea
+    id: interface
+    attributes:
+      label: Required Interface
+      description: What adapter or interface must be implemented? (e.g., VectorStore base class)
+    validations:
+      required: true
+  
+  - type: textarea
+    id: reference
+    attributes:
+      label: Reference Implementations
+      description: Links to similar integrations in other vector DBs.
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/profiling.yml

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+name: Profiling / Investigation
+description: Profile performance, compatibility, or behavior in a specific scenario
+title: "[Profile]: "
+labels: ["profile"]
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Use this for tasks like performance profiling, architecture compatibility checks, or feasibility studies.
+  
+  - type: input
+    id: scenario
+    attributes:
+      label: Target Scenario
+      description: e.g., ARM64 deployment, high-concurrency load, large dataset ingestion
+    validations:
+      required: true
+  
+  - type: textarea
+    id: objective
+    attributes:
+      label: Objective
+      description: What do you want to learn or validate?
+    validations:
+      required: true
+  
+  - type: textarea
+    id: methodology
+    attributes:
+      label: Proposed Methodology
+      description: How will you conduct the investigation? (tools, metrics, test data)
+    validations:
+      required: true
+  
+  - type: textarea
+    id: expected_outcome
+    attributes:
+      label: Expected Outcome
+      description: What deliverables are expected? (e.g., report, optimization PR, benchmark results)
+    validations:
+      required: true