From 7781f39154e3f587eaf3b9cbe20436e261d4a7f2 Mon Sep 17 00:00:00 2001
From: Piotr Duda <piotrekno1@gmail.com>
Date: Wed, 18 Mar 2026 08:34:30 +0100
Subject: [PATCH 01/11] Remove stale files + smarter CI

---
 .github/workflows/ci.yml     | 14 ++++++++++++++
 .github/workflows/compat.yml | 12 ++++++++++++
 CHANGELOG.md                 | 32 --------------------------------
 3 files changed, 26 insertions(+), 32 deletions(-)
 delete mode 100644 CHANGELOG.md

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index eef4186..c9d68b8 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -3,8 +3,22 @@ name: CI
 on:
   push:
     branches: [ main, devel ]
+    paths:
+      - 'wildedge/**'
+      - 'tests/**'
+      - 'scripts/**'
+      - 'pyproject.toml'
+      - 'uv.lock'
+      - '.github/workflows/ci.yml'
   pull_request:
     branches: [ main, devel ]
+    paths:
+      - 'wildedge/**'
+      - 'tests/**'
+      - 'scripts/**'
+      - 'pyproject.toml'
+      - 'uv.lock'
+      - '.github/workflows/ci.yml'
 
 jobs:
   test:
diff --git a/.github/workflows/compat.yml b/.github/workflows/compat.yml
index 30cb542..392a299 100644
--- a/.github/workflows/compat.yml
+++ b/.github/workflows/compat.yml
@@ -3,9 +3,21 @@ name: Compatibility
 on:
   push:
     branches: [ main, devel ]
+    paths:
+      - 'wildedge/**'
+      - 'tests/compat/**'
+      - 'scripts/compat_matrix.py'
+      - 'pyproject.toml'
+      - '.github/workflows/compat.yml'
   pull_request:
     branches: [ main, devel ]
     types: [opened, synchronize, reopened, labeled]
+    paths:
+      - 'wildedge/**'
+      - 'tests/compat/**'
+      - 'scripts/compat_matrix.py'
+      - 'pyproject.toml'
+      - '.github/workflows/compat.yml'
   schedule:
     - cron: "0 3 * * *"
   workflow_dispatch:
diff --git a/CHANGELOG.md b/CHANGELOG.md
deleted file mode 100644
index cd804b0..0000000
--- a/CHANGELOG.md
+++ /dev/null
@@ -1,32 +0,0 @@
-# Changelog
-
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.1.0] - 2026-03-05
-
-### Added
-- Initial release of WildEdge Python SDK
-- Support for ONNX Runtime, GGUF/llama.cpp, timm, PyTorch, and Keras integrations
-- Automatic latency and error tracking without capturing inputs/outputs
-- Event batching and transmission to WildEdge servers
-- Configuration via DSN and environment variables
-- Comprehensive test suite with tox support for multiple Python versions
-- CI/CD pipeline with GitHub Actions
-
-### Changed
-- N/A
-
-### Deprecated
-- N/A
-
-### Removed
-- N/A
-
-### Fixed
-- N/A
-
-### Security
-- N/A
\ No newline at end of file

From 9b95783f86390a62dbb82446c7dd3c93715e79f2 Mon Sep 17 00:00:00 2001
From: Piotr Duda <piotrekno1@gmail.com>
Date: Thu, 19 Mar 2026 08:44:47 +0100
Subject: [PATCH 02/11] Smarter CI + coverage updates for the compatibility
 matrix (#21)

---
 .github/workflows/compat.yml             | 34 +++++++++-
 scripts/compat_matrix.py                 | 44 ++++++++++++
 scripts/run_compat_local.py              | 86 +++++++++++++++---------
 tests/compat/test_gguf_compat.py         |  9 +++
 tests/compat/test_mlx_compat.py          | 17 +++++
 tests/compat/test_openai_compat.py       |  9 +++
 tests/compat/test_transformers_compat.py | 25 +++++++
 tests/compat/test_ultralytics_compat.py  |  9 +++
 8 files changed, 199 insertions(+), 34 deletions(-)
 create mode 100644 tests/compat/test_gguf_compat.py
 create mode 100644 tests/compat/test_mlx_compat.py
 create mode 100644 tests/compat/test_openai_compat.py
 create mode 100644 tests/compat/test_transformers_compat.py
 create mode 100644 tests/compat/test_ultralytics_compat.py

diff --git a/.github/workflows/compat.yml b/.github/workflows/compat.yml
index 392a299..a411710 100644
--- a/.github/workflows/compat.yml
+++ b/.github/workflows/compat.yml
@@ -30,7 +30,7 @@ jobs:
       fail-fast: false
       matrix:
         python-version: ["3.10", "3.11", "3.12", "3.13"]
-        integration: ["onnx", "torch", "timm", "tensorflow"]
+        integration: ["onnx", "torch", "timm", "tensorflow", "gguf", "openai", "transformers", "ultralytics"]
         version-set: ["min", "current"]
         exclude:
           - python-version: "3.13"
@@ -44,7 +44,7 @@ jobs:
       - name: Install project
         run: |
           python -m pip install --upgrade pip
-          pip install -e . pytest
+          pip install -e . pytest pytest-asyncio pytest-mock
       - name: Install compatibility dependencies
         run: |
           python scripts/compat_matrix.py deps \
@@ -55,6 +55,34 @@ jobs:
       - name: Run compatibility test
         run: python -m pytest "tests/compat/test_${{ matrix.integration }}_compat.py" -q
 
+  compat-mlx:
+    if: github.event_name == 'schedule' || github.event_name == 'workflow_dispatch'
+    runs-on: macos-14
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.12", "3.13"]
+        version-set: ["current"]
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install project
+        run: |
+          python -m pip install --upgrade pip
+          pip install -e . pytest pytest-asyncio pytest-mock
+      - name: Install compatibility dependencies
+        run: |
+          python scripts/compat_matrix.py deps \
+            --integration "mlx" \
+            --version-set "${{ matrix.version-set }}" \
+            --python-version "${{ matrix.python-version }}" > compat-requirements.txt
+          pip install -r compat-requirements.txt
+      - name: Run compatibility test
+        run: python -m pytest tests/compat/test_mlx_compat.py -q
+
   compat-canary-314:
     if: github.event_name != 'pull_request' || contains(github.event.pull_request.labels.*.name, 'compat')
     runs-on: ubuntu-latest
@@ -75,7 +103,7 @@ jobs:
       - name: Install project
         run: |
           python -m pip install --upgrade pip
-          pip install -e . pytest
+          pip install -e . pytest pytest-asyncio pytest-mock
       - name: Install compatibility dependencies
         run: |
           python scripts/compat_matrix.py deps \
diff --git a/scripts/compat_matrix.py b/scripts/compat_matrix.py
index 18f48dd..610df72 100644
--- a/scripts/compat_matrix.py
+++ b/scripts/compat_matrix.py
@@ -4,6 +4,7 @@
 from __future__ import annotations
 
 import argparse
+import json
 import sys
 
 MATRIX = {
@@ -33,6 +34,25 @@
         "min": ["tensorflow==2.16.1", "keras==3.3.3", "numpy==1.26.4"],
         "current": ["tensorflow==2.18.0", "keras==3.8.0", "numpy==2.0.2"],
     },
+    "gguf": {
+        "min": ["llama-cpp-python==0.2.90", "numpy==1.26.4"],
+        "current": ["llama-cpp-python==0.3.4", "numpy==2.1.3"],
+    },
+    "openai": {
+        "min": ["openai==1.30.0"],
+        "current": ["openai==1.61.0"],
+    },
+    "transformers": {
+        "min": ["transformers==4.40.0", "torch==2.4.1", "numpy==1.26.4"],
+        "current": ["transformers==4.47.0", "torch==2.6.0", "numpy==2.1.3"],
+    },
+    "ultralytics": {
+        "min": ["ultralytics==8.0.0", "numpy==1.26.4"],
+        "current": ["ultralytics==8.3.4", "numpy==2.1.3"],
+    },
+    "mlx": {
+        "current": ["mlx==0.22.0", "mlx-lm==0.21.0"],
+    },
 }
 
 SUPPORTED_PYTHON = {
@@ -40,6 +60,11 @@
     "torch": ["3.10", "3.11", "3.12", "3.13", "3.14"],
     "timm": ["3.10", "3.11", "3.12", "3.13", "3.14"],
     "tensorflow": ["3.10", "3.11", "3.12"],
+    "gguf": ["3.10", "3.11", "3.12", "3.13"],
+    "openai": ["3.10", "3.11", "3.12", "3.13"],
+    "transformers": ["3.10", "3.11", "3.12", "3.13"],
+    "ultralytics": ["3.10", "3.11", "3.12", "3.13"],
+    "mlx": ["3.12", "3.13"],
 }
 
 # Interpreter-specific overrides where upstream wheels are unavailable for older pins.
@@ -58,6 +83,11 @@
             "3.14": ["torch==2.10.0", "numpy==2.1.3"],
         },
     },
+    "transformers": {
+        "min": {
+            "3.13": ["transformers==4.45.0", "torch==2.5.0", "numpy==2.1.3"],
+        }
+    },
     "timm": {
         "min": {
             "3.13": [
@@ -113,6 +143,17 @@ def print_deps(integration: str, version_set: str, python_version: str) -> int:
     return 0
 
 
+def print_rows() -> int:
+    rows = [
+        {"integration": integration, "version_set": version_set, "python_version": py}
+        for integration, sets in MATRIX.items()
+        for version_set in sets
+        for py in SUPPORTED_PYTHON[integration]
+    ]
+    print(json.dumps(rows))
+    return 0
+
+
 def print_table() -> int:
     print("| Integration | Version set | Dependencies | Supported Python |")
     print("|---|---|---|---|")
@@ -140,11 +181,14 @@ def main() -> int:
     deps.add_argument("--version-set", required=True, choices=["min", "current"])
     deps.add_argument("--python-version", required=True)
 
+    sub.add_parser("rows")
     sub.add_parser("table")
 
     args = parser.parse_args()
     if args.cmd == "deps":
         return print_deps(args.integration, args.version_set, args.python_version)
+    if args.cmd == "rows":
+        return print_rows()
     if args.cmd == "table":
         return print_table()
     return 2
diff --git a/scripts/run_compat_local.py b/scripts/run_compat_local.py
index 8ab3846..44fe82f 100755
--- a/scripts/run_compat_local.py
+++ b/scripts/run_compat_local.py
@@ -4,8 +4,12 @@
 from __future__ import annotations
 
 import argparse
+import json
+import os
 import subprocess
 import sys
+import tempfile
+from concurrent.futures import ThreadPoolExecutor, as_completed
 from dataclasses import dataclass
 from pathlib import Path
 
@@ -19,18 +23,18 @@ class Row:
     version_set: str
 
 
-WORKFLOW_ROWS: list[Row] = [
-    # compat job
-    *[
-        Row(py, integration, version_set)
-        for py in ("3.10", "3.11", "3.12", "3.13")
-        for integration in ("onnx", "torch", "timm", "tensorflow")
-        for version_set in ("min", "current")
-        if not (py == "3.13" and integration == "tensorflow")
-    ],
-    # compat-canary-314 job
-    *[Row("3.14", integration, "current") for integration in ("torch", "timm")],
-]
+def load_rows() -> list[Row]:
+    result = subprocess.run(
+        [sys.executable, str(REPO_ROOT / "scripts" / "compat_matrix.py"), "rows"],
+        check=True,
+        capture_output=True,
+        text=True,
+        cwd=REPO_ROOT,
+    )
+    return [Row(**r) for r in json.loads(result.stdout)]
+
+
+WORKFLOW_ROWS: list[Row] = load_rows()
 
 
 UNSUPPORTED_MARKERS = (
@@ -67,10 +71,15 @@ def run_row(row: Row) -> tuple[str, str]:
         "run",
         "--python",
         row.python_version,
+        "--link-mode=copy",
         "--with-editable",
         ".",
         "--with",
         "pytest",
+        "--with",
+        "pytest-asyncio",
+        "--with",
+        "pytest-mock",
     ]
     for dep in deps:
         cmd.extend(["--with", dep])
@@ -84,9 +93,11 @@ def run_row(row: Row) -> tuple[str, str]:
         ]
     )
 
-    result = subprocess.run(
-        cmd, check=False, capture_output=True, text=True, cwd=REPO_ROOT
-    )
+    with tempfile.TemporaryDirectory() as tmpdir:
+        env = {**os.environ, "UV_PROJECT_ENVIRONMENT": tmpdir}
+        result = subprocess.run(
+            cmd, check=False, capture_output=True, text=True, cwd=REPO_ROOT, env=env
+        )
     output = f"{result.stdout}\n{result.stderr}".strip()
 
     if result.returncode == 0:
@@ -103,29 +114,42 @@ def main() -> int:
         action="store_true",
         help="Treat unsupported dependency rows as failures.",
     )
+    parser.add_argument(
+        "--jobs",
+        "-j",
+        type=int,
+        default=os.cpu_count() or 4,
+        help="Number of rows to run in parallel (default: cpu count).",
+    )
     args = parser.parse_args()
 
     passed = 0
     failed = 0
     skipped = 0
 
-    for row in WORKFLOW_ROWS:
-        label = f"{row.python_version} | {row.integration} | {row.version_set}"
-        print(f"==> {label}")
-        status, output = run_row(row)
-        print(status)
-        if output:
-            print(output)
-        print()
-
-        if status == "PASS":
-            passed += 1
-        elif status == "SKIP_UNSUPPORTED":
-            skipped += 1
-            if args.strict_unsupported:
+    futures = {}
+    with ThreadPoolExecutor(max_workers=args.jobs) as executor:
+        for row in WORKFLOW_ROWS:
+            futures[executor.submit(run_row, row)] = row
+
+        for future in as_completed(futures):
+            row = futures[future]
+            label = f"{row.python_version} | {row.integration} | {row.version_set}"
+            status, output = future.result()
+            print(f"==> {label}")
+            print(status)
+            if output:
+                print(output)
+            print()
+
+            if status == "PASS":
+                passed += 1
+            elif status == "SKIP_UNSUPPORTED":
+                skipped += 1
+                if args.strict_unsupported:
+                    failed += 1
+            else:
                 failed += 1
-        else:
-            failed += 1
 
     print(
         "SUMMARY "
diff --git a/tests/compat/test_gguf_compat.py b/tests/compat/test_gguf_compat.py
new file mode 100644
index 0000000..9512db6
--- /dev/null
+++ b/tests/compat/test_gguf_compat.py
@@ -0,0 +1,9 @@
+from __future__ import annotations
+
+import pytest
+
+
+def test_gguf_import_and_instrument(compat_client):
+    llama_cpp = pytest.importorskip("llama_cpp")
+    assert hasattr(llama_cpp, "Llama")
+    compat_client.instrument("gguf")
diff --git a/tests/compat/test_mlx_compat.py b/tests/compat/test_mlx_compat.py
new file mode 100644
index 0000000..d66db56
--- /dev/null
+++ b/tests/compat/test_mlx_compat.py
@@ -0,0 +1,17 @@
+from __future__ import annotations
+
+import pytest
+
+
+def test_mlx_import_and_instrumentation(compat_client):
+    pytest.importorskip("mlx_lm")
+    mx = pytest.importorskip("mlx.core")
+    nn = pytest.importorskip("mlx.nn")
+
+    compat_client.instrument("mlx")
+
+    model = nn.Linear(4, 2)
+    x = mx.ones((3, 4))
+    y = model(x)
+    mx.eval(y)
+    assert y.shape == (3, 2)
diff --git a/tests/compat/test_openai_compat.py b/tests/compat/test_openai_compat.py
new file mode 100644
index 0000000..a704734
--- /dev/null
+++ b/tests/compat/test_openai_compat.py
@@ -0,0 +1,9 @@
+from __future__ import annotations
+
+import pytest
+
+
+def test_openai_import_and_instrument(compat_client):
+    openai = pytest.importorskip("openai")
+    assert getattr(openai, "__version__", None)
+    compat_client.instrument("openai")
diff --git a/tests/compat/test_transformers_compat.py b/tests/compat/test_transformers_compat.py
new file mode 100644
index 0000000..01b22cf
--- /dev/null
+++ b/tests/compat/test_transformers_compat.py
@@ -0,0 +1,25 @@
+from __future__ import annotations
+
+import pytest
+
+
+def test_transformers_import_and_instrumentation(compat_client):
+    torch = pytest.importorskip("torch")
+    transformers = pytest.importorskip("transformers")
+
+    compat_client.instrument("transformers")
+
+    config = transformers.BertConfig(
+        hidden_size=32,
+        num_hidden_layers=2,
+        num_attention_heads=2,
+        intermediate_size=64,
+        num_labels=2,
+    )
+    model = transformers.BertForSequenceClassification(config)
+    inputs = {
+        "input_ids": torch.zeros((1, 4), dtype=torch.long),
+        "attention_mask": torch.ones((1, 4), dtype=torch.long),
+    }
+    out = model(**inputs)
+    assert tuple(out.logits.shape) == (1, 2)
diff --git a/tests/compat/test_ultralytics_compat.py b/tests/compat/test_ultralytics_compat.py
new file mode 100644
index 0000000..6f6e5e5
--- /dev/null
+++ b/tests/compat/test_ultralytics_compat.py
@@ -0,0 +1,9 @@
+from __future__ import annotations
+
+import pytest
+
+
+def test_ultralytics_import_and_instrument(compat_client):
+    ultralytics = pytest.importorskip("ultralytics")
+    assert getattr(ultralytics, "__version__", None)
+    compat_client.instrument("ultralytics")

From 60d22663bce810075879b29e8507d8b23bb7c8ec Mon Sep 17 00:00:00 2001
From: Piotr Duda <piotrekno1@gmail.com>
Date: Thu, 19 Mar 2026 10:18:24 +0100
Subject: [PATCH 03/11] Fixes #23 (#24)

---
 examples/cli/uv.lock                          |  10 +-
 examples/django_gemma/uv.lock                 |   3 +-
 examples/fastapi_openai/app/__init__.py       |   0
 examples/fastapi_openai/app/main.py           |  54 ++
 examples/fastapi_openai/app/static/index.html |  39 +
 examples/fastapi_openai/demo.sh               |  37 +
 examples/fastapi_openai/pyproject.toml        |  13 +
 examples/fastapi_openai/uv.lock               | 844 ++++++++++++++++++
 tests/test_autoload.py                        |  91 +-
 wildedge/autoload/sitecustomize.py            |  15 +-
 wildedge/constants.py                         |   1 -
 11 files changed, 1086 insertions(+), 21 deletions(-)
 create mode 100644 examples/fastapi_openai/app/__init__.py
 create mode 100644 examples/fastapi_openai/app/main.py
 create mode 100644 examples/fastapi_openai/app/static/index.html
 create mode 100755 examples/fastapi_openai/demo.sh
 create mode 100644 examples/fastapi_openai/pyproject.toml
 create mode 100644 examples/fastapi_openai/uv.lock

diff --git a/examples/cli/uv.lock b/examples/cli/uv.lock
index b0e3583..6103e3b 100644
--- a/examples/cli/uv.lock
+++ b/examples/cli/uv.lock
@@ -948,6 +948,13 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/0f/8b/4b61d6e13f7108f36910df9ab4b58fd389cc2520d54d81b88660804aad99/torch-2.10.0-2-cp311-none-macosx_11_0_arm64.whl", hash = "sha256:418997cb02d0a0f1497cf6a09f63166f9f5df9f3e16c8a716ab76a72127c714f", size = 79423467, upload-time = "2026-02-10T21:44:48.711Z" },
     { url = "https://files.pythonhosted.org/packages/d3/54/a2ba279afcca44bbd320d4e73675b282fcee3d81400ea1b53934efca6462/torch-2.10.0-2-cp312-none-macosx_11_0_arm64.whl", hash = "sha256:13ec4add8c3faaed8d13e0574f5cd4a323c11655546f91fbe6afa77b57423574", size = 79498202, upload-time = "2026-02-10T21:44:52.603Z" },
     { url = "https://files.pythonhosted.org/packages/ec/23/2c9fe0c9c27f7f6cb865abcea8a4568f29f00acaeadfc6a37f6801f84cb4/torch-2.10.0-2-cp313-none-macosx_11_0_arm64.whl", hash = "sha256:e521c9f030a3774ed770a9c011751fb47c4d12029a3d6522116e48431f2ff89e", size = 79498254, upload-time = "2026-02-10T21:44:44.095Z" },
+    { url = "https://files.pythonhosted.org/packages/16/ee/efbd56687be60ef9af0c9c0ebe106964c07400eade5b0af8902a1d8cd58c/torch-2.10.0-3-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:a1ff626b884f8c4e897c4c33782bdacdff842a165fee79817b1dd549fdda1321", size = 915510070, upload-time = "2026-03-11T14:16:39.386Z" },
+    { url = "https://files.pythonhosted.org/packages/36/ab/7b562f1808d3f65414cd80a4f7d4bb00979d9355616c034c171249e1a303/torch-2.10.0-3-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:ac5bdcbb074384c66fa160c15b1ead77839e3fe7ed117d667249afce0acabfac", size = 915518691, upload-time = "2026-03-11T14:15:43.147Z" },
+    { url = "https://files.pythonhosted.org/packages/b3/7a/abada41517ce0011775f0f4eacc79659bc9bc6c361e6bfe6f7052a6b9363/torch-2.10.0-3-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:98c01b8bb5e3240426dcde1446eed6f40c778091c8544767ef1168fc663a05a6", size = 915622781, upload-time = "2026-03-11T14:17:11.354Z" },
+    { url = "https://files.pythonhosted.org/packages/ab/c6/4dfe238342ffdcec5aef1c96c457548762d33c40b45a1ab7033bb26d2ff2/torch-2.10.0-3-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:80b1b5bfe38eb0e9f5ff09f206dcac0a87aadd084230d4a36eea5ec5232c115b", size = 915627275, upload-time = "2026-03-11T14:16:11.325Z" },
+    { url = "https://files.pythonhosted.org/packages/d8/f0/72bf18847f58f877a6a8acf60614b14935e2f156d942483af1ffc081aea0/torch-2.10.0-3-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:46b3574d93a2a8134b3f5475cfb98e2eb46771794c57015f6ad1fb795ec25e49", size = 915523474, upload-time = "2026-03-11T14:17:44.422Z" },
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@@ -1088,7 +1095,7 @@ requires-dist = [
 
 [[package]]
 name = "wildedge-sdk"
-version = "0.1.0"
+version = "0.1.1"
 source = { editable = "../../" }
 
 [package.metadata]
@@ -1097,6 +1104,7 @@ source = { editable = "../../" }
 dev = [
     { name = "coverage" },
     { name = "pytest", specifier = ">=9.0.2" },
+    { name = "pytest-asyncio", specifier = ">=0.25" },
     { name = "pytest-mock", specifier = ">=3.15.1" },
     { name = "ruff", specifier = ">=0.15.4" },
     { name = "tox" },
diff --git a/examples/django_gemma/uv.lock b/examples/django_gemma/uv.lock
index 1a86ad7..ca6b004 100644
--- a/examples/django_gemma/uv.lock
+++ b/examples/django_gemma/uv.lock
@@ -728,7 +728,7 @@ requires-dist = [
 
 [[package]]
 name = "wildedge-sdk"
-version = "0.1.0"
+version = "0.1.1"
 source = { editable = "../../" }
 
 [package.metadata]
@@ -737,6 +737,7 @@ source = { editable = "../../" }
 dev = [
     { name = "coverage" },
     { name = "pytest", specifier = ">=9.0.2" },
+    { name = "pytest-asyncio", specifier = ">=0.25" },
     { name = "pytest-mock", specifier = ">=3.15.1" },
     { name = "ruff", specifier = ">=0.15.4" },
     { name = "tox" },
diff --git a/examples/fastapi_openai/app/__init__.py b/examples/fastapi_openai/app/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/examples/fastapi_openai/app/main.py b/examples/fastapi_openai/app/main.py
new file mode 100644
index 0000000..4ba3c5d
--- /dev/null
+++ b/examples/fastapi_openai/app/main.py
@@ -0,0 +1,54 @@
+"""FastAPI + OpenRouter example.
+
+WildEdge is injected via `wildedge run` before the app starts, so inference
+tracking happens automatically for every chat.completions.create call.
+
+Run with: see demo.sh
+Requires: WILDEDGE_DSN and OPENROUTER_API_KEY environment variables.
+"""
+
+import os
+import pathlib
+
+from fastapi import FastAPI
+from fastapi.responses import FileResponse
+from openai import OpenAI
+from pydantic import BaseModel
+
+STATIC = pathlib.Path(__file__).parent / "static"
+
+app = FastAPI()
+
+
+@app.get("/")
+def index() -> FileResponse:
+    return FileResponse(STATIC / "index.html")
+
+
+client = OpenAI(
+    api_key=os.environ["OPENROUTER_API_KEY"],
+    base_url="https://openrouter.ai/api/v1",
+)
+
+
+class ChatRequest(BaseModel):
+    prompt: str
+    model: str = "openai/gpt-4o-mini"
+
+
+class ChatResponse(BaseModel):
+    response: str
+    model: str
+
+
+@app.post("/chat", response_model=ChatResponse)
+def chat(req: ChatRequest) -> ChatResponse:
+    completion = client.chat.completions.create(
+        model=req.model,
+        messages=[{"role": "user", "content": req.prompt}],
+        max_tokens=512,
+    )
+    return ChatResponse(
+        response=completion.choices[0].message.content,
+        model=completion.model,
+    )
diff --git a/examples/fastapi_openai/app/static/index.html b/examples/fastapi_openai/app/static/index.html
new file mode 100644
index 0000000..e10ba6d
--- /dev/null
+++ b/examples/fastapi_openai/app/static/index.html
@@ -0,0 +1,39 @@
+<!doctype html>
+<html lang="en">
+<head>
+  <meta charset="utf-8">
+  <title>WildEdge + OpenRouter</title>
+  <style>
+    body { font-family: sans-serif; max-width: 640px; margin: 3rem auto; padding: 0 1rem; }
+    textarea { width: 100%; box-sizing: border-box; }
+    #response { white-space: pre-wrap; background: #f4f4f4; padding: 1rem; margin-top: 1rem; min-height: 3rem; }
+    #model-label { font-size: 0.8rem; color: #666; margin-top: 0.5rem; }
+  </style>
+</head>
+<body>
+  <h2>WildEdge + OpenRouter</h2>
+  <textarea id="prompt" rows="4" placeholder="Enter a prompt..."></textarea>
+  <br>
+  <label>Model: <input id="model" value="openai/gpt-4o-mini" size="30"></label>
+  <br><br>
+  <button onclick="send()">Send</button>
+  <div id="model-label"></div>
+  <div id="response"></div>
+  <script>
+    async function send() {
+      const prompt = document.getElementById("prompt").value.trim();
+      if (!prompt) return;
+      document.getElementById("response").textContent = "...";
+      document.getElementById("model-label").textContent = "";
+      const res = await fetch("/chat", {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify({ prompt, model: document.getElementById("model").value }),
+      });
+      const data = await res.json();
+      document.getElementById("response").textContent = data.response;
+      document.getElementById("model-label").textContent = "model: " + data.model;
+    }
+  </script>
+</body>
+</html>
diff --git a/examples/fastapi_openai/demo.sh b/examples/fastapi_openai/demo.sh
new file mode 100755
index 0000000..21a7ca0
--- /dev/null
+++ b/examples/fastapi_openai/demo.sh
@@ -0,0 +1,37 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+if [[ -z "${WILDEDGE_DSN:-}" ]]; then
+  echo 'Set WILDEDGE_DSN first, e.g. export WILDEDGE_DSN="https://<secret>@ingest.wildedge.dev/<key>"' >&2
+  exit 1
+fi
+
+if [[ -z "${OPENROUTER_API_KEY:-}" ]]; then
+  echo 'Set OPENROUTER_API_KEY first, e.g. export OPENROUTER_API_KEY="sk-or-..."' >&2
+  exit 1
+fi
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+cd "${SCRIPT_DIR}"
+
+uv sync
+
+uv run wildedge doctor --integrations openai
+
+# wildedge run execs uvicorn with wildedge/autoload/ prepended to PYTHONPATH.
+# sitecustomize.py bootstraps the runtime before the app loads, instrumenting
+# the OpenAI client for automatic inference tracking.
+#
+# --reload spawns a fresh worker process via exec each time code changes.
+# The module-level guard in sitecustomize.py ensures that worker bootstraps
+# correctly (unlike the old os.environ guard, which propagated across exec
+# and blocked the worker's init).
+uv run wildedge run \
+  --print-startup-report \
+  --integrations openai \
+  -- uvicorn app.main:app --reload --port 8000
+
+# Test with:
+#   curl -s -X POST http://localhost:8000/chat \
+#     -H "Content-Type: application/json" \
+#     -d '{"prompt": "What is on-device AI in one sentence?"}' | jq .
diff --git a/examples/fastapi_openai/pyproject.toml b/examples/fastapi_openai/pyproject.toml
new file mode 100644
index 0000000..06d118c
--- /dev/null
+++ b/examples/fastapi_openai/pyproject.toml
@@ -0,0 +1,13 @@
+[project]
+name = "wildedge-fastapi-openrouter"
+version = "0.1.0"
+requires-python = ">=3.10"
+dependencies = [
+    "wildedge-sdk",
+    "fastapi",
+    "uvicorn[standard]",
+    "openai",
+]
+
+[tool.uv.sources]
+wildedge-sdk = { path = "../..", editable = true }
diff --git a/examples/fastapi_openai/uv.lock b/examples/fastapi_openai/uv.lock
new file mode 100644
index 0000000..fff8ef0
--- /dev/null
+++ b/examples/fastapi_openai/uv.lock
@@ -0,0 +1,844 @@
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+    { url = "https://files.pythonhosted.org/packages/9a/3f/f70e03f40ffc9a30d817eef7da1be72ee4956ba8d7255c399a01b135902a/websockets-16.0-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:a653aea902e0324b52f1613332ddf50b00c06fdaf7e92624fbf8c77c78fa5767", size = 178735, upload-time = "2026-01-10T09:23:42.259Z" },
+    { url = "https://files.pythonhosted.org/packages/6f/28/258ebab549c2bf3e64d2b0217b973467394a9cea8c42f70418ca2c5d0d2e/websockets-16.0-py3-none-any.whl", hash = "sha256:1637db62fad1dc833276dded54215f2c7fa46912301a24bd94d45d46a011ceec", size = 171598, upload-time = "2026-01-10T09:23:45.395Z" },
+]
+
+[[package]]
+name = "wildedge-fastapi-openrouter"
+version = "0.1.0"
+source = { virtual = "." }
+dependencies = [
+    { name = "fastapi" },
+    { name = "openai" },
+    { name = "uvicorn", extra = ["standard"] },
+    { name = "wildedge-sdk" },
+]
+
+[package.metadata]
+requires-dist = [
+    { name = "fastapi" },
+    { name = "openai" },
+    { name = "uvicorn", extras = ["standard"] },
+    { name = "wildedge-sdk", editable = "../../" },
+]
+
+[[package]]
+name = "wildedge-sdk"
+version = "0.1.1"
+source = { editable = "../../" }
+
+[package.metadata]
+
+[package.metadata.requires-dev]
+dev = [
+    { name = "coverage" },
+    { name = "pytest", specifier = ">=9.0.2" },
+    { name = "pytest-asyncio", specifier = ">=0.25" },
+    { name = "pytest-mock", specifier = ">=3.15.1" },
+    { name = "ruff", specifier = ">=0.15.4" },
+    { name = "tox" },
+]
diff --git a/tests/test_autoload.py b/tests/test_autoload.py
index 302a3c0..d16c04a 100644
--- a/tests/test_autoload.py
+++ b/tests/test_autoload.py
@@ -4,11 +4,15 @@
 
 import importlib
 import importlib.util
+import subprocess
 import sys
+import textwrap
 from unittest.mock import patch
 
 import wildedge.autoload.sitecustomize as _sc_mod
 
+_MARKER = _sc_mod._INSTALLED_MARKER
+
 
 def _reload_sitecustomize():
     """Reload sitecustomize module so module-level code re-executes."""
@@ -17,10 +21,14 @@ def _reload_sitecustomize():
     return _sc_mod
 
 
-def test_guard_prevents_double_init(monkeypatch):
-    """WILDEDGE_AUTOLOAD_ACTIVE set: install_runtime not called."""
-    monkeypatch.setenv("WILDEDGE_AUTOLOAD_ACTIVE", "1")
+def test_gunicorn_prefork_skips_double_init(monkeypatch):
+    """Gunicorn pre-fork: sys.modules marker blocks re-init in the same interpreter.
+
+    In gunicorn's fork-only model, workers inherit the parent's sys.modules so
+    sitecustomize never re-executes. This covers the explicit reload edge case.
+    """
     monkeypatch.setenv("WILDEDGE_AUTOLOAD", "1")
+    monkeypatch.setitem(sys.modules, _MARKER, True)  # type: ignore[arg-type]
 
     calls = []
     with patch("wildedge.runtime.bootstrap.install_runtime", side_effect=calls.append):
@@ -30,8 +38,8 @@ def test_guard_prevents_double_init(monkeypatch):
 
 
 def test_skips_when_no_dsn(monkeypatch):
-    """No DSN env vars: silent skip."""
-    monkeypatch.delenv("WILDEDGE_AUTOLOAD_ACTIVE", raising=False)
+    """No activation env vars present: silent skip regardless of server."""
+    monkeypatch.delitem(sys.modules, _MARKER, raising=False)
     monkeypatch.delenv("WILDEDGE_AUTOLOAD", raising=False)
     monkeypatch.delenv("WILDEDGE_DSN", raising=False)
 
@@ -42,9 +50,13 @@ def test_skips_when_no_dsn(monkeypatch):
     assert calls == []
 
 
-def test_autoload_flag_triggers_install(monkeypatch):
-    """WILDEDGE_AUTOLOAD=1 present: install_runtime called with install_signal_handlers=False."""
-    monkeypatch.delenv("WILDEDGE_AUTOLOAD_ACTIVE", raising=False)
+def test_waitress_autoload_triggers_install(monkeypatch):
+    """Waitress (single-process, thread-pool): WILDEDGE_AUTOLOAD=1 bootstraps the runtime.
+
+    Waitress has no forking or reloader subprocess, so sitecustomize runs once
+    in the server process and install_runtime is called.
+    """
+    monkeypatch.delitem(sys.modules, _MARKER, raising=False)
     monkeypatch.setenv("WILDEDGE_AUTOLOAD", "1")
 
     calls = []
@@ -58,9 +70,13 @@ def fake_install(**kwargs):
     assert calls == [{"install_signal_handlers": False}]
 
 
-def test_dsn_triggers_install(monkeypatch):
-    """WILDEDGE_DSN present: install_runtime called."""
-    monkeypatch.delenv("WILDEDGE_AUTOLOAD_ACTIVE", raising=False)
+def test_granian_dsn_triggers_install(monkeypatch):
+    """Granian (direct DSN config): WILDEDGE_DSN alone is sufficient to bootstrap.
+
+    Users running granian without `wildedge run` can set WILDEDGE_DSN and
+    prepend wildedge/autoload/ to PYTHONPATH to get instrumentation.
+    """
+    monkeypatch.delitem(sys.modules, _MARKER, raising=False)
     monkeypatch.delenv("WILDEDGE_AUTOLOAD", raising=False)
     monkeypatch.setenv("WILDEDGE_DSN", "https://secret@ingest.wildedge.dev/key")
 
@@ -77,7 +93,7 @@ def fake_install(**kwargs):
 
 def test_bootstrap_exception_is_caught(monkeypatch, capsys):
     """Exception from install_runtime must not propagate; message written to stderr."""
-    monkeypatch.delenv("WILDEDGE_AUTOLOAD_ACTIVE", raising=False)
+    monkeypatch.delitem(sys.modules, _MARKER, raising=False)
     monkeypatch.setenv("WILDEDGE_AUTOLOAD", "1")
 
     with patch(
@@ -95,7 +111,7 @@ def test_chains_existing_sitecustomize(monkeypatch, tmp_path):
     sc_file = tmp_path / "sitecustomize.py"
     sc_file.write_text(f"open({str(marker)!r}, 'w').close()\n")
 
-    monkeypatch.delenv("WILDEDGE_AUTOLOAD_ACTIVE", raising=False)
+    monkeypatch.delitem(sys.modules, _MARKER, raising=False)
     monkeypatch.delenv("WILDEDGE_AUTOLOAD", raising=False)
     monkeypatch.delenv("WILDEDGE_DSN", raising=False)
     sys.modules.pop("sitecustomize", None)
@@ -111,3 +127,52 @@ def patched_find_spec(name):
         _sc_mod._load_existing_sitecustomize()
 
     assert marker.exists(), "chained sitecustomize.py was not executed"
+
+
+def test_uvicorn_reload_worker_bootstraps(tmp_path):
+    """Uvicorn --reload: the server worker process bootstraps after the reloader already did.
+
+    Uvicorn's reloader runs sitecustomize in the reloader process, then spawns
+    the actual server worker via exec (fresh interpreter). The worker must be
+    instrumented. The old os.environ guard (WILDEDGE_AUTOLOAD_ACTIVE) propagated
+    across exec and blocked the worker's bootstrap. sys.modules is not inherited
+    across exec, so the worker re-initialises correctly.
+    """
+    import os
+    import pathlib
+
+    autoload_dir = str(
+        pathlib.Path(
+            importlib.util.find_spec("wildedge.autoload.sitecustomize").origin
+        ).parent
+    )
+
+    # Probe script: verify sitecustomize entered the bootstrap path in the child.
+    # install_runtime will raise (no DSN) but the marker is set before the call,
+    # so its presence in sys.modules means the worker reached the bootstrap code.
+    script = textwrap.dedent("""\
+        import sys
+        import wildedge.autoload.sitecustomize as sc
+        print("installed:", sc._INSTALLED_MARKER in sys.modules)
+    """)
+    script_file = tmp_path / "probe.py"
+    script_file.write_text(script)
+
+    env = os.environ.copy()
+    env["WILDEDGE_AUTOLOAD"] = "1"
+    # Simulate the env state the reloader leaves behind. This is what caused
+    # the regression with the old os.environ guard.
+    env["WILDEDGE_AUTOLOAD_ACTIVE"] = "1"
+    env.pop("WILDEDGE_DSN", None)
+
+    pythonpath = env.get("PYTHONPATH", "")
+    env["PYTHONPATH"] = autoload_dir + (os.pathsep + pythonpath if pythonpath else "")
+
+    result = subprocess.run(
+        [sys.executable, str(script_file)],
+        env=env,
+        capture_output=True,
+        text=True,
+    )
+    assert result.returncode == 0, result.stderr
+    assert "installed: True" in result.stdout
diff --git a/wildedge/autoload/sitecustomize.py b/wildedge/autoload/sitecustomize.py
index c77db79..da87129 100644
--- a/wildedge/autoload/sitecustomize.py
+++ b/wildedge/autoload/sitecustomize.py
@@ -11,18 +11,23 @@
 import os
 import sys
 
-_GUARD = "WILDEDGE_AUTOLOAD_ACTIVE"
 _AUTOLOAD = "WILDEDGE_AUTOLOAD"  # set to "1" by `wildedge run`
 _DSN = "WILDEDGE_DSN"  # user-configured DSN
 
-# Idempotent: skip if already initialized (e.g. in a forked worker that
-# exec'd a subprocess, or if sitecustomize.py is imported twice).
-if not os.environ.get(_GUARD):
+# sys.modules is used as the guard against re-entry within the same interpreter.
+# A module-level variable resets when the module object is re-created (e.g. if
+# _load_existing_sitecustomize finds this file via a second sys.path entry in an
+# editable install). os.environ would persist but propagates to child processes
+# spawned via exec (e.g. uvicorn --reload workers) and blocks their bootstrap.
+# sys.modules is process-local and survives module re-execution.
+_INSTALLED_MARKER = "wildedge.__autoload_installed__"
+
+if _INSTALLED_MARKER not in sys.modules:
     # Activate if the CLI launched this process, or if WILDEDGE_DSN is set
     # and the user has manually prepended wildedge/autoload/ to PYTHONPATH.
     if os.environ.get(_AUTOLOAD) or os.environ.get(_DSN):
         # Set the guard before importing wildedge to prevent re-entry.
-        os.environ[_GUARD] = "1"
+        sys.modules[_INSTALLED_MARKER] = True  # type: ignore[assignment]
         try:
             from wildedge.runtime.bootstrap import install_runtime  # noqa: PLC0415
 
diff --git a/wildedge/constants.py b/wildedge/constants.py
index 91a8e28..8c3ebd0 100644
--- a/wildedge/constants.py
+++ b/wildedge/constants.py
@@ -45,7 +45,6 @@
 WILDEDGE_AUTOLOAD = (
     "WILDEDGE_AUTOLOAD"  # set to "1" by `wildedge run` to activate sitecustomize
 )
-WILDEDGE_AUTOLOAD_ACTIVE = "WILDEDGE_AUTOLOAD_ACTIVE"  # guard against double-init
 
 # Runtime validation limits
 BATCH_SIZE_MIN = 1

From 8b8fe663fad1cee43a3d2e406d5d8ee5be32750e Mon Sep 17 00:00:00 2001
From: Piotr Duda <piotrekno1@gmail.com>
Date: Sat, 21 Mar 2026 15:36:26 +0100
Subject: [PATCH 04/11] Lack of DSN should turn client into nop (#26)

---
 README.md                        |  4 ++-
 docs/configuration.md            |  2 +-
 docs/manual-tracking.md          |  2 +-
 examples/feedback_example.py     |  2 +-
 examples/gguf_example.py         |  2 +-
 examples/gguf_gemma_example.py   |  2 +-
 examples/keras_example.py        |  2 +-
 examples/mlx_example.py          |  4 ++-
 examples/onnx_example.py         |  2 +-
 examples/openai_example.py       |  4 ++-
 examples/pytorch_example.py      |  2 +-
 examples/tensorflow_example.py   |  2 +-
 examples/timm_example.py         |  2 +-
 examples/transformers_example.py |  4 ++-
 tests/test_client.py             | 32 ++++++++++++++++++++++
 wildedge/client.py               | 47 +++++++++++++++++++++++++++++---
 16 files changed, 97 insertions(+), 18 deletions(-)

diff --git a/README.md b/README.md
index f5a7e14..7c10bae 100644
--- a/README.md
+++ b/README.md
@@ -53,6 +53,8 @@ client.instrument("transformers", hubs=["huggingface"])
 # models loaded after this point are tracked automatically
 ```
 
+If no DSN is configured, the client becomes a no-op and logs a warning.
+
 ## Supported integrations
 
 **On-device**
@@ -90,7 +92,7 @@ For unsupported frameworks, see [Manual tracking](https://github.com/wild-edge/w
 
 | Parameter | Default | Description |
 |---|---|---|
-| `dsn` | - | `https://<secret>@ingest.wildedge.dev/<key>` (or `WILDEDGE_DSN`) |
+| `dsn` | - | `https://<secret>@ingest.wildedge.dev/<key>` (or `WILDEDGE_DSN`). If unset, the client is a no-op. |
 | `app_version` | `None` | Your app's version string |
 | `app_identity` | `<project_key>` | Namespace for offline persistence. Set per-app in multi-process workloads (or `WILDEDGE_APP_IDENTITY`) |
 | `enable_offline_persistence` | `true` | Persist unsent events to disk and replay on restart |
diff --git a/docs/configuration.md b/docs/configuration.md
index 6244fc8..566738b 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -6,7 +6,7 @@ Full reference for all `WildEdge` client parameters.
 
 | Parameter | Default | Env var | Description |
 |---|---|---|---|
-| `dsn` | - | `WILDEDGE_DSN` | `https://<secret>@ingest.wildedge.dev/<key>` |
+| `dsn` | - | `WILDEDGE_DSN` | `https://<secret>@ingest.wildedge.dev/<key>`. If unset, the client is a no-op. |
 | `app_version` | `None` | - | Your app's version string |
 | `app_identity` | `<project_key>` | `WILDEDGE_APP_IDENTITY` | Namespace for offline persistence. Set per-app in multi-process workloads |
 | `enable_offline_persistence` | `true` | - | Persist unsent events to disk and replay on restart |
diff --git a/docs/manual-tracking.md b/docs/manual-tracking.md
index 20d2fe5..e3b1615 100644
--- a/docs/manual-tracking.md
+++ b/docs/manual-tracking.md
@@ -25,7 +25,7 @@ Every model needs a handle before you can track events against it. Pass the mode
 ```python
 import wildedge
 
-client = wildedge.WildEdge()  # set WILDEDGE_DSN env var
+client = wildedge.WildEdge()  # uses WILDEDGE_DSN if set; otherwise no-op
 
 handle = client.register_model(
     my_model,
diff --git a/examples/feedback_example.py b/examples/feedback_example.py
index 11f9e7c..4644e9e 100644
--- a/examples/feedback_example.py
+++ b/examples/feedback_example.py
@@ -22,7 +22,7 @@
 CONFIDENCE_THRESHOLD = 0.6
 
 client = wildedge.WildEdge(
-    app_version="1.0.0",  # set WILDEDGE_DSN env var
+    app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
 )
 client.instrument("timm")
 
diff --git a/examples/gguf_example.py b/examples/gguf_example.py
index 074d535..5af3f25 100644
--- a/examples/gguf_example.py
+++ b/examples/gguf_example.py
@@ -13,7 +13,7 @@
 import wildedge
 
 client = wildedge.WildEdge(
-    app_version="1.0.0",  # set WILDEDGE_DSN env var
+    app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
 )
 client.instrument("gguf", hubs=["huggingface"])
 
diff --git a/examples/gguf_gemma_example.py b/examples/gguf_gemma_example.py
index f3962cf..94afd36 100644
--- a/examples/gguf_gemma_example.py
+++ b/examples/gguf_gemma_example.py
@@ -28,7 +28,7 @@
 FILE = "gemma-2-2b-it-Q4_K_M.gguf"
 
 client = wildedge.WildEdge(
-    app_version="1.0.0",  # set WILDEDGE_DSN env var
+    app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
 )
 
 # --- Download ---
diff --git a/examples/keras_example.py b/examples/keras_example.py
index b782139..0fc2e1c 100644
--- a/examples/keras_example.py
+++ b/examples/keras_example.py
@@ -28,7 +28,7 @@
     exit(1)
 
 client = wildedge.WildEdge(
-    app_version="1.0.0",  # set WILDEDGE_DSN env var
+    app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
 )
 
 # Load a pre-trained MobileNetV2 model using client to track construction and lifecycle
diff --git a/examples/mlx_example.py b/examples/mlx_example.py
index 2c87a3a..1e70b82 100644
--- a/examples/mlx_example.py
+++ b/examples/mlx_example.py
@@ -52,7 +52,9 @@ def main() -> None:
 
     # instrument() patches mlx_lm.load and mlx_lm.generate; must be called
     # before any model is loaded.
-    client = wildedge.WildEdge(app_version="1.0.0")  # set WILDEDGE_DSN env var
+    client = wildedge.WildEdge(
+        app_version="1.0.0"
+    )  # uses WILDEDGE_DSN if set; otherwise no-op
     client.instrument("mlx", hubs=["huggingface"])
 
     print(f"\nLoading {args.model} ...")
diff --git a/examples/onnx_example.py b/examples/onnx_example.py
index a5a9232..e9c4318 100644
--- a/examples/onnx_example.py
+++ b/examples/onnx_example.py
@@ -14,7 +14,7 @@
 import wildedge
 
 client = wildedge.WildEdge(
-    app_version="1.0.0",  # set WILDEDGE_DSN env var
+    app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
 )
 client.instrument("onnx", hubs=["huggingface"])
 
diff --git a/examples/openai_example.py b/examples/openai_example.py
index e2e2e87..4515d4e 100644
--- a/examples/openai_example.py
+++ b/examples/openai_example.py
@@ -18,7 +18,9 @@
 
 import wildedge
 
-client = wildedge.WildEdge(app_version="1.0.0")  # set WILDEDGE_DSN env var
+client = wildedge.WildEdge(
+    app_version="1.0.0"
+)  # uses WILDEDGE_DSN if set; otherwise no-op
 client.instrument("openai")
 
 openai_client = OpenAI()  # set OPENAI_API_KEY env var or pass api_key= explicitly
diff --git a/examples/pytorch_example.py b/examples/pytorch_example.py
index c384b15..8868455 100644
--- a/examples/pytorch_example.py
+++ b/examples/pytorch_example.py
@@ -13,7 +13,7 @@
 import wildedge
 
 client = wildedge.WildEdge(
-    app_version="1.0.0",  # set WILDEDGE_DSN env var
+    app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
 )
 
 
diff --git a/examples/tensorflow_example.py b/examples/tensorflow_example.py
index 41641e2..cd6d1b0 100644
--- a/examples/tensorflow_example.py
+++ b/examples/tensorflow_example.py
@@ -18,7 +18,7 @@
 import wildedge
 
 client = wildedge.WildEdge(
-    app_version="1.0.0",  # set WILDEDGE_DSN env var
+    app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
 )
 client.instrument("tensorflow")
 
diff --git a/examples/timm_example.py b/examples/timm_example.py
index 1a302e7..ffea6c3 100644
--- a/examples/timm_example.py
+++ b/examples/timm_example.py
@@ -20,7 +20,7 @@
 import wildedge
 
 client = wildedge.WildEdge(
-    app_version="1.0.0",  # set WILDEDGE_DSN env var
+    app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
 )
 client.instrument("timm", hubs=["huggingface", "torchhub"])
 
diff --git a/examples/transformers_example.py b/examples/transformers_example.py
index bac9df4..cff9277 100644
--- a/examples/transformers_example.py
+++ b/examples/transformers_example.py
@@ -92,7 +92,9 @@ def main() -> None:
     )
     args = parser.parse_args()
 
-    client = wildedge.WildEdge(app_version="1.0.0")  # set WILDEDGE_DSN env var
+    client = wildedge.WildEdge(
+        app_version="1.0.0"
+    )  # uses WILDEDGE_DSN if set; otherwise no-op
     client.instrument("transformers", hubs=["huggingface"])
 
     print()
diff --git a/tests/test_client.py b/tests/test_client.py
index 971c64a..3417ba8 100644
--- a/tests/test_client.py
+++ b/tests/test_client.py
@@ -31,6 +31,38 @@ def test_batch_size_too_low():
         WildEdge(dsn="https://test@test.com/key", batch_size=0)
 
 
+def test_no_dsn_is_noop(monkeypatch, caplog):
+    from wildedge.client import WildEdge
+
+    monkeypatch.delenv(constants.ENV_DSN, raising=False)
+    with caplog.at_level("WARNING"):
+        client = WildEdge()
+
+    assert client.noop is True
+    assert client.closed is True
+    assert "no DSN configured" in caplog.text
+
+
+def test_no_dsn_instrument_does_not_raise(monkeypatch):
+    from wildedge.client import WildEdge
+
+    monkeypatch.delenv(constants.ENV_DSN, raising=False)
+    client = WildEdge()
+
+    # No-DSN client should ignore instrument() entirely (even for unknown integration).
+    client.instrument("definitely-not-real")
+
+
+def test_no_dsn_publish_does_not_enqueue(monkeypatch):
+    from wildedge.client import WildEdge
+
+    monkeypatch.delenv(constants.ENV_DSN, raising=False)
+    client = WildEdge()
+
+    client.publish({"event_type": "inference", "model_id": "m"})
+    client.queue.add.assert_not_called()
+
+
 def test_batch_size_too_high():
     from wildedge.client import WildEdge
 
diff --git a/wildedge/client.py b/wildedge/client.py
index da08f02..da5e052 100644
--- a/wildedge/client.py
+++ b/wildedge/client.py
@@ -68,6 +68,14 @@
 )
 
 
+class _NoopConsumer:
+    def flush(self, timeout: float = 0) -> None:
+        return None
+
+    def close(self, timeout: float | None = None) -> None:
+        return None
+
+
 def parse_dsn(dsn: str) -> tuple[str, str, str]:
     """Parse DSN into (secret, host, project_key)."""
     parsed = urlparse(dsn)
@@ -153,10 +161,12 @@ def __init__(
     ):
         env = read_client_env(dsn=dsn, debug=debug, app_identity=app_identity)
         dsn = env.dsn
+        debug = env.debug
+        self.noop = False
         if not dsn:
-            raise ValueError(ERROR_DSN_REQUIRED)
+            self._init_noop(debug=debug, device=device)
+            return
         api_key, host, project_key = parse_dsn(dsn)
-        debug = env.debug
         app_identity = resolve_app_identity(
             explicit=env.app_identity,
             project_key=project_key,
@@ -258,8 +268,32 @@ def __init__(
         if debug:
             logger.debug("wildedge: client initialized (session=%s)", self.session_id)
 
+    def _init_noop(self, *, debug: bool, device: DeviceInfo | None) -> None:
+        self.noop = True
+        self.debug = debug
+        self.closed = True
+        logger.warning(
+            "wildedge: no DSN configured; client is disabled (events will be dropped)"
+        )
+        self.api_key = None
+        self.device = device
+        self.session_id = str(uuid.uuid4())
+        self.created_at = datetime.now(timezone.utc)
+        self.queue = EventQueue(
+            max_size=1,
+            policy=QueuePolicy.OPPORTUNISTIC,
+            persist_to_disk=False,
+        )
+        self.registry = ModelRegistry(persist_path=None)
+        self.transmitter = None
+        self.dead_letter_store = None
+        self.consumer = _NoopConsumer()
+        self.auto_loaded = set()
+        self._auto_load_finalizers = {}
+        self.hub_trackers = {}
+
     def publish(self, event_dict: dict) -> None:
-        if self.closed:
+        if self.closed or self.noop:
             return
 
         if self.debug:
@@ -472,6 +506,10 @@ def instrument(
         Each integration or hub tracker is installed at most once per process
         regardless of how many times ``instrument()`` is called.
         """
+        if self.noop:
+            if self.debug:
+                logger.debug("wildedge: instrument skipped (no DSN configured)")
+            return
         if integration is None:
             if not hubs:
                 raise ValueError(
@@ -658,7 +696,8 @@ def flush(self, timeout: float = 5.0) -> None:
     def close(self, timeout: float | None = None) -> None:
         """Best-effort shutdown; pass timeout to attempt bounded flush first."""
         self.closed = True
-        stop_sampler()
+        if not self.noop:
+            stop_sampler()
         if timeout is None:
             self.consumer.close()
         else:

From 7bbb380b1d8523869c7418ead601d0909553d2e3 Mon Sep 17 00:00:00 2001
From: Piotr Duda <piotrekno1@gmail.com>
Date: Sat, 21 Mar 2026 16:13:03 +0100
Subject: [PATCH 05/11] More pythonic sdk init (#27)

---
 README.md                        |  9 ++++-
 docs/manual-tracking.md          |  5 ++-
 examples/feedback_example.py     |  4 +-
 examples/gguf_example.py         |  5 ++-
 examples/mlx_example.py          | 11 ++---
 examples/onnx_example.py         |  5 ++-
 examples/openai_example.py       | 10 ++---
 examples/tensorflow_example.py   |  6 +--
 examples/timm_example.py         |  5 ++-
 examples/transformers_example.py |  9 +++--
 tests/test_init.py               | 69 ++++++++++++++++++++++++++++++++
 wildedge/__init__.py             |  2 +
 wildedge/convenience.py          | 41 +++++++++++++++++++
 13 files changed, 153 insertions(+), 28 deletions(-)
 create mode 100644 tests/test_init.py
 create mode 100644 wildedge/convenience.py

diff --git a/README.md b/README.md
index 7c10bae..cbe9c81 100644
--- a/README.md
+++ b/README.md
@@ -47,14 +47,19 @@ Useful flags:
 ```python
 import wildedge
 
-client = wildedge.WildEdge(dsn="...")  # or WILDEDGE_DSN env var
-client.instrument("transformers", hubs=["huggingface"])
+client = wildedge.init(
+    dsn="...",  # or WILDEDGE_DSN env var
+    integrations=["transformers"],
+    hubs=["huggingface"],
+)
 
 # models loaded after this point are tracked automatically
 ```
 
 If no DSN is configured, the client becomes a no-op and logs a warning.
 
+`init(...)` is a convenience wrapper for `WildEdge(...)` + `instrument(...)`.
+
 ## Supported integrations
 
 **On-device**
diff --git a/docs/manual-tracking.md b/docs/manual-tracking.md
index e3b1615..f90f58a 100644
--- a/docs/manual-tracking.md
+++ b/docs/manual-tracking.md
@@ -25,7 +25,10 @@ Every model needs a handle before you can track events against it. Pass the mode
 ```python
 import wildedge
 
-client = wildedge.WildEdge()  # uses WILDEDGE_DSN if set; otherwise no-op
+client = wildedge.init()  # uses WILDEDGE_DSN if set; otherwise no-op
+
+# Optional: enable auto-instrumentation alongside manual tracking.
+# client = wildedge.init(integrations=["transformers"], hubs=["huggingface"])
 
 handle = client.register_model(
     my_model,
diff --git a/examples/feedback_example.py b/examples/feedback_example.py
index 4644e9e..ff06292 100644
--- a/examples/feedback_example.py
+++ b/examples/feedback_example.py
@@ -21,10 +21,10 @@
 
 CONFIDENCE_THRESHOLD = 0.6
 
-client = wildedge.WildEdge(
+client = wildedge.init(
     app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
+    integrations="timm",
 )
-client.instrument("timm")
 
 model = timm.create_model("resnet18", pretrained=True)
 model.eval()
diff --git a/examples/gguf_example.py b/examples/gguf_example.py
index 5af3f25..cf58f88 100644
--- a/examples/gguf_example.py
+++ b/examples/gguf_example.py
@@ -12,10 +12,11 @@
 
 import wildedge
 
-client = wildedge.WildEdge(
+client = wildedge.init(
     app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
+    integrations="gguf",
+    hubs=["huggingface"],
 )
-client.instrument("gguf", hubs=["huggingface"])
 
 model_path = hf_hub_download(
     "bartowski/Llama-3.2-1B-Instruct-GGUF",
diff --git a/examples/mlx_example.py b/examples/mlx_example.py
index 1e70b82..61906e0 100644
--- a/examples/mlx_example.py
+++ b/examples/mlx_example.py
@@ -50,12 +50,13 @@ def main() -> None:
     )
     args = parser.parse_args()
 
-    # instrument() patches mlx_lm.load and mlx_lm.generate; must be called
+    # init() constructs the client and instruments mlx; must be called
     # before any model is loaded.
-    client = wildedge.WildEdge(
-        app_version="1.0.0"
-    )  # uses WILDEDGE_DSN if set; otherwise no-op
-    client.instrument("mlx", hubs=["huggingface"])
+    client = wildedge.init(
+        app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
+        integrations="mlx",
+        hubs=["huggingface"],
+    )
 
     print(f"\nLoading {args.model} ...")
     model, tokenizer = mlx_lm.load(args.model)  # load + download tracked automatically
diff --git a/examples/onnx_example.py b/examples/onnx_example.py
index e9c4318..e7a6f78 100644
--- a/examples/onnx_example.py
+++ b/examples/onnx_example.py
@@ -13,10 +13,11 @@
 
 import wildedge
 
-client = wildedge.WildEdge(
+client = wildedge.init(
     app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
+    integrations="onnx",
+    hubs=["huggingface"],
 )
-client.instrument("onnx", hubs=["huggingface"])
 
 model_path = hf_hub_download("Xenova/resnet-50", "onnx/model.onnx")
 session = ort.InferenceSession(model_path)
diff --git a/examples/openai_example.py b/examples/openai_example.py
index 4515d4e..d9410e4 100644
--- a/examples/openai_example.py
+++ b/examples/openai_example.py
@@ -11,17 +11,17 @@
 inference tracking happens automatically for every chat.completions.create call.
 
 Run with: uv run openai_example.py
-Requires: WILDEDGE_DSN and OPENAI_API_KEY environment variables.
+Requires: OPENAI_API_KEY environment variable. Set WILDEDGE_DSN to send events.
 """
 
 from openai import OpenAI
 
 import wildedge
 
-client = wildedge.WildEdge(
-    app_version="1.0.0"
-)  # uses WILDEDGE_DSN if set; otherwise no-op
-client.instrument("openai")
+client = wildedge.init(
+    app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
+    integrations="openai",
+)
 
 openai_client = OpenAI()  # set OPENAI_API_KEY env var or pass api_key= explicitly
 
diff --git a/examples/tensorflow_example.py b/examples/tensorflow_example.py
index cd6d1b0..3cf1962 100644
--- a/examples/tensorflow_example.py
+++ b/examples/tensorflow_example.py
@@ -17,10 +17,10 @@
 
 import wildedge
 
-client = wildedge.WildEdge(
+client = wildedge.init(
     app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
+    integrations="tensorflow",
 )
-client.instrument("tensorflow")
 
 
 def build_and_save_model(save_path: Path) -> None:
@@ -40,7 +40,7 @@ def build_and_save_model(save_path: Path) -> None:
     model_path = Path(temp_dir) / "demo_model.keras"
     build_and_save_model(model_path)
 
-    # load_model is auto-instrumented by client.instrument("tensorflow")
+    # load_model is auto-instrumented by init(..., integrations="tensorflow")
     loaded = tf.keras.models.load_model(model_path)
 
     batch = np.random.randn(4, 16).astype(np.float32)
diff --git a/examples/timm_example.py b/examples/timm_example.py
index ffea6c3..5b4ffa1 100644
--- a/examples/timm_example.py
+++ b/examples/timm_example.py
@@ -19,10 +19,11 @@
 
 import wildedge
 
-client = wildedge.WildEdge(
+client = wildedge.init(
     app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
+    integrations="timm",
+    hubs=["huggingface", "torchhub"],
 )
-client.instrument("timm", hubs=["huggingface", "torchhub"])
 
 model = timm.create_model("resnet18", pretrained=True)
 model.eval()
diff --git a/examples/transformers_example.py b/examples/transformers_example.py
index cff9277..92e8a1d 100644
--- a/examples/transformers_example.py
+++ b/examples/transformers_example.py
@@ -92,10 +92,11 @@ def main() -> None:
     )
     args = parser.parse_args()
 
-    client = wildedge.WildEdge(
-        app_version="1.0.0"
-    )  # uses WILDEDGE_DSN if set; otherwise no-op
-    client.instrument("transformers", hubs=["huggingface"])
+    client = wildedge.init(
+        app_version="1.0.0",  # uses WILDEDGE_DSN if set; otherwise no-op
+        integrations="transformers",
+        hubs=["huggingface"],
+    )
 
     print()
     {"classify": run_classify, "generate": run_generate, "embed": run_embed}[
diff --git a/tests/test_init.py b/tests/test_init.py
new file mode 100644
index 0000000..3450446
--- /dev/null
+++ b/tests/test_init.py
@@ -0,0 +1,69 @@
+from __future__ import annotations
+
+import wildedge
+import wildedge.convenience as convenience
+
+
+def test_init_calls_instrument_for_integrations(monkeypatch):
+
+    calls: list[tuple[str | None, list[str] | None]] = []
+
+    class DummyClient:
+        def __init__(self, **kwargs):
+            self.kwargs = kwargs
+
+        def instrument(self, integration, *, hubs=None):
+            calls.append((integration, hubs))
+
+    monkeypatch.setattr(convenience, "WildEdge", DummyClient)
+
+    client = wildedge.init(
+        dsn="https://secret@ingest.wildedge.dev/key",
+        integrations=["onnx", "timm"],
+        hubs=["huggingface"],
+    )
+
+    assert isinstance(client, DummyClient)
+    assert calls == [("onnx", ["huggingface"]), ("timm", ["huggingface"])]
+
+
+def test_init_hubs_only(monkeypatch):
+
+    calls: list[tuple[str | None, list[str] | None]] = []
+
+    class DummyClient:
+        def __init__(self, **kwargs):
+            self.kwargs = kwargs
+
+        def instrument(self, integration, *, hubs=None):
+            calls.append((integration, hubs))
+
+    monkeypatch.setattr(convenience, "WildEdge", DummyClient)
+
+    client = wildedge.init(
+        dsn="https://secret@ingest.wildedge.dev/key",
+        hubs=["huggingface"],
+    )
+
+    assert isinstance(client, DummyClient)
+    assert calls == [(None, ["huggingface"])]
+
+
+def test_init_logs_debug_when_no_integrations_or_hubs(monkeypatch):
+    logs: list[str] = []
+
+    class DummyClient:
+        def __init__(self, **kwargs):
+            self.kwargs = kwargs
+            self.debug = True
+
+        def instrument(self, integration, *, hubs=None):
+            raise AssertionError("instrument should not be called")
+
+    monkeypatch.setattr(convenience, "WildEdge", DummyClient)
+    monkeypatch.setattr(convenience.logger, "debug", lambda msg: logs.append(msg))
+
+    client = wildedge.init(dsn="https://secret@ingest.wildedge.dev/key")
+
+    assert isinstance(client, DummyClient)
+    assert logs == ["wildedge: init called without integrations or hubs"]
diff --git a/wildedge/__init__.py b/wildedge/__init__.py
index 73f74ef..f1f449b 100644
--- a/wildedge/__init__.py
+++ b/wildedge/__init__.py
@@ -1,6 +1,7 @@
 """WildEdge Python SDK."""
 
 from wildedge.client import WildEdge
+from wildedge.convenience import init
 from wildedge.decorators import track
 from wildedge.events import (
     AdapterDownload,
@@ -24,6 +25,7 @@
 
 __all__ = [
     "WildEdge",
+    "init",
     "capture_hardware",
     "HardwareContext",
     "ThermalContext",
diff --git a/wildedge/convenience.py b/wildedge/convenience.py
new file mode 100644
index 0000000..a9e61aa
--- /dev/null
+++ b/wildedge/convenience.py
@@ -0,0 +1,41 @@
+from __future__ import annotations
+
+from collections.abc import Iterable
+from typing import Any
+
+from wildedge.client import WildEdge
+from wildedge.logging import logger
+
+
+def _normalize_list(value: str | Iterable[str] | None) -> list[str]:
+    if value is None:
+        return []
+    if isinstance(value, str):
+        return [value]
+    return [item for item in value if item]
+
+
+def init(
+    *,
+    integrations: str | Iterable[str] | None = None,
+    hubs: str | Iterable[str] | None = None,
+    **kwargs: Any,
+) -> WildEdge:
+    """
+    Convenience initializer: construct a WildEdge client and instrument integrations.
+
+    Additional keyword arguments are forwarded to WildEdge(...).
+    """
+    client = WildEdge(**kwargs)
+    normalized_integrations = _normalize_list(integrations)
+    normalized_hubs = _normalize_list(hubs)
+
+    if normalized_integrations:
+        for integration in normalized_integrations:
+            client.instrument(integration, hubs=normalized_hubs or None)
+    elif normalized_hubs:
+        client.instrument(None, hubs=normalized_hubs)
+    elif getattr(client, "debug", False):
+        logger.debug("wildedge: init called without integrations or hubs")
+
+    return client

From 72b6e555129b7fb3bd2a45bd636ab04a872b64ee Mon Sep 17 00:00:00 2001
From: Piotr Duda <piotrekno1@gmail.com>
Date: Mon, 23 Mar 2026 09:46:21 +0100
Subject: [PATCH 06/11] Release 0.1.2 (#29)

* Release 0.1.2
---
 .github/workflows/ci.yml           |  2 +-
 .github/workflows/compat.yml       | 10 ++---
 .github/workflows/release-pr.yml   | 30 ++++++++++++++
 .github/workflows/release.yml      | 12 +++++-
 CONTRIBUTING.md                    | 11 ++++-
 examples/cli/uv.lock               |  2 +-
 examples/django_gemma/uv.lock      |  2 +-
 examples/fastapi_openai/uv.lock    |  2 +-
 pyproject.toml                     |  2 +-
 scripts/build_changelog_comment.py | 66 ++++++++++++++++++++++++++++++
 uv.lock                            |  2 +-
 11 files changed, 128 insertions(+), 13 deletions(-)
 create mode 100644 .github/workflows/release-pr.yml
 create mode 100644 scripts/build_changelog_comment.py

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index c9d68b8..4f942d3 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -2,7 +2,7 @@ name: CI
 
 on:
   push:
-    branches: [ main, devel ]
+    branches: [ main, devel, 'release/**' ]
     paths:
       - 'wildedge/**'
       - 'tests/**'
diff --git a/.github/workflows/compat.yml b/.github/workflows/compat.yml
index a411710..3e267e3 100644
--- a/.github/workflows/compat.yml
+++ b/.github/workflows/compat.yml
@@ -2,7 +2,7 @@ name: Compatibility
 
 on:
   push:
-    branches: [ main, devel ]
+    branches: [ main, 'release/**' ]
     paths:
       - 'wildedge/**'
       - 'tests/compat/**'
@@ -10,8 +10,8 @@ on:
       - 'pyproject.toml'
       - '.github/workflows/compat.yml'
   pull_request:
-    branches: [ main, devel ]
-    types: [opened, synchronize, reopened, labeled]
+    branches: [ main ]
+    types: [opened, synchronize, reopened]
     paths:
       - 'wildedge/**'
       - 'tests/compat/**'
@@ -24,7 +24,7 @@ on:
 
 jobs:
   compat:
-    if: github.event_name != 'pull_request' || contains(github.event.pull_request.labels.*.name, 'compat')
+    if: github.event_name != 'pull_request' || startsWith(github.head_ref, 'release/')
     runs-on: ubuntu-latest
     strategy:
       fail-fast: false
@@ -84,7 +84,7 @@ jobs:
         run: python -m pytest tests/compat/test_mlx_compat.py -q
 
   compat-canary-314:
-    if: github.event_name != 'pull_request' || contains(github.event.pull_request.labels.*.name, 'compat')
+    if: github.event_name != 'pull_request' || startsWith(github.head_ref, 'release/')
     runs-on: ubuntu-latest
     continue-on-error: true
     strategy:
diff --git a/.github/workflows/release-pr.yml b/.github/workflows/release-pr.yml
new file mode 100644
index 0000000..efb015d
--- /dev/null
+++ b/.github/workflows/release-pr.yml
@@ -0,0 +1,30 @@
+name: Release PR
+
+on:
+  pull_request:
+    branches: [ main ]
+    types: [opened, synchronize, reopened]
+
+jobs:
+  changelog-preview:
+    if: startsWith(github.head_ref, 'release/')
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      pull-requests: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Generate changelog preview
+        env:
+          GH_TOKEN: ${{ github.token }}
+          HEAD_REF: ${{ github.head_ref }}
+          REPO: ${{ github.repository }}
+          OUTPUT: /tmp/changelog-preview.md
+        run: python3 scripts/build_changelog_comment.py
+
+      - name: Post changelog preview comment
+        uses: marocchino/sticky-pull-request-comment@v2
+        with:
+          header: changelog-preview
+          path: /tmp/changelog-preview.md
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index 9fe7013..732a462 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -38,12 +38,22 @@ jobs:
       - name: Check package metadata
         run: twine check dist/*
 
+      - name: Generate release notes
+        if: github.ref_type == 'tag'
+        env:
+          GH_TOKEN: ${{ github.token }}
+          REPO: ${{ github.repository }}
+          HEAD_REF: ${{ github.ref_name }}
+          TAG_NAME: ${{ github.ref_name }}
+          OUTPUT: /tmp/release-notes.md
+        run: python3 scripts/build_changelog_comment.py
+
       - name: Create GitHub release
         if: github.ref_type == 'tag'
         uses: softprops/action-gh-release@v2
         with:
           files: dist/*
-          generate_release_notes: true
+          body_path: /tmp/release-notes.md
 
       - name: Publish package to PyPI
         uses: pypa/gh-action-pypi-publish@release/v1
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 7679f3e..5de252b 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -38,7 +38,16 @@
 1. Fork the repository and create a feature branch off `devel`.
 2. Make your changes and ensure tests pass.
 3. Update documentation if needed.
-4. Submit a pull request with a clear description of the changes.
+4. Submit a pull request targeting `devel` with a clear description of the changes.
+
+## Release process
+
+Releases follow a `release/<version>` branching flow:
+
+1. Cut a `release/<version>` branch from `devel`.
+2. Bump the version in `pyproject.toml`.
+3. Open a pull request targeting `main`. CI will automatically run the full compatibility matrix and post a changelog preview comment.
+4. Once merged, tag the commit as `v<version>`. The release workflow publishes to PyPI and creates a GitHub release.
 
 ## Reporting issues
 
diff --git a/examples/cli/uv.lock b/examples/cli/uv.lock
index 6103e3b..4d86671 100644
--- a/examples/cli/uv.lock
+++ b/examples/cli/uv.lock
@@ -1095,7 +1095,7 @@ requires-dist = [
 
 [[package]]
 name = "wildedge-sdk"
-version = "0.1.1"
+version = "0.1.2"
 source = { editable = "../../" }
 
 [package.metadata]
diff --git a/examples/django_gemma/uv.lock b/examples/django_gemma/uv.lock
index ca6b004..75f37c8 100644
--- a/examples/django_gemma/uv.lock
+++ b/examples/django_gemma/uv.lock
@@ -728,7 +728,7 @@ requires-dist = [
 
 [[package]]
 name = "wildedge-sdk"
-version = "0.1.1"
+version = "0.1.2"
 source = { editable = "../../" }
 
 [package.metadata]
diff --git a/examples/fastapi_openai/uv.lock b/examples/fastapi_openai/uv.lock
index fff8ef0..b620a91 100644
--- a/examples/fastapi_openai/uv.lock
+++ b/examples/fastapi_openai/uv.lock
@@ -828,7 +828,7 @@ requires-dist = [
 
 [[package]]
 name = "wildedge-sdk"
-version = "0.1.1"
+version = "0.1.2"
 source = { editable = "../../" }
 
 [package.metadata]
diff --git a/pyproject.toml b/pyproject.toml
index 7f83e84..3a7e63e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "wildedge-sdk"
-version = "0.1.1"
+version = "0.1.2"
 description = "On-device ML inference monitoring for Python"
 readme = "README.md"
 requires-python = ">=3.10"
diff --git a/scripts/build_changelog_comment.py b/scripts/build_changelog_comment.py
new file mode 100644
index 0000000..9e54df7
--- /dev/null
+++ b/scripts/build_changelog_comment.py
@@ -0,0 +1,66 @@
+#!/usr/bin/env python3
+"""Generate a changelog preview comment for release PRs using the GitHub API."""
+
+from __future__ import annotations
+
+import os
+import subprocess
+from pathlib import Path
+
+import tomllib
+
+
+def get_version() -> str:
+    data = tomllib.loads(Path("pyproject.toml").read_text())
+    return data["project"]["version"]
+
+
+def get_previous_tag(repo: str) -> str | None:
+    result = subprocess.run(
+        ["gh", "api", f"repos/{repo}/releases/latest", "--jq", ".tag_name"],
+        capture_output=True,
+        text=True,
+    )
+    tag = result.stdout.strip()
+    return tag if result.returncode == 0 and tag else None
+
+
+def generate_notes(repo: str, tag_name: str, target: str, prev_tag: str | None) -> str:
+    args = [
+        "gh",
+        "api",
+        f"repos/{repo}/releases/generate-notes",
+        "-f",
+        f"tag_name={tag_name}",
+        "-f",
+        f"target_commitish={target}",
+    ]
+    if prev_tag:
+        args += ["-f", f"previous_tag_name={prev_tag}"]
+    args += ["--jq", ".body"]
+
+    result = subprocess.run(args, capture_output=True, text=True, check=True)
+    return result.stdout
+
+
+def build_comment(tag_name: str, notes: str) -> str:
+    return (
+        f"## Changelog preview for `{tag_name}`\n\n"
+        "> Preview of the GitHub release notes that will be generated when this is tagged.\n\n"
+        + notes
+    )
+
+
+def main() -> None:
+    repo = os.environ["REPO"]
+    head_ref = os.environ["HEAD_REF"]
+    output = os.environ.get("OUTPUT", "/tmp/changelog-preview.md")
+    tag_name = os.environ.get("TAG_NAME") or f"v{get_version()}"
+
+    prev_tag = get_previous_tag(repo)
+    notes = generate_notes(repo, tag_name, head_ref, prev_tag)
+    Path(output).write_text(build_comment(tag_name, notes))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/uv.lock b/uv.lock
index dca8b1c..5043436 100644
--- a/uv.lock
+++ b/uv.lock
@@ -419,7 +419,7 @@ wheels = [
 
 [[package]]
 name = "wildedge-sdk"
-version = "0.1.1"
+version = "0.1.2"
 source = { editable = "." }
 
 [package.dev-dependencies]

From 4c80592c4eb68560c107e4643fd9d26d03842e79 Mon Sep 17 00:00:00 2001
From: Piotr Duda <piotrekno1@gmail.com>
Date: Mon, 23 Mar 2026 12:19:34 +0100
Subject: [PATCH 07/11] Used in projects table in README

---
 README.md | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/README.md b/README.md
index cbe9c81..1c24d0b 100644
--- a/README.md
+++ b/README.md
@@ -105,6 +105,15 @@ For unsupported frameworks, see [Manual tracking](https://github.com/wild-edge/w
 
 For advanced options (batching, queue tuning, dead-letter storage), see [Configuration](https://github.com/wild-edge/wildedge-python/blob/main/docs/configuration.md).
 
+## Projects using this SDK
+
+| Name | Link |
+|---|---|
+| agntr | [github.com/pmaciolek/agntr](https://github.com/pmaciolek/agntr) |
+| *(your project here)* | - |
+
+Using WildEdge in your project? Open a PR to add it to the list.
+
 ## Privacy
 
 Report security & priact issues to: wildedge@googlegroups.com.

From 79de451005ea2967050bfd5d4fbdf22be84493fa Mon Sep 17 00:00:00 2001
From: Piotr Duda <piotrekno1@gmail.com>
Date: Wed, 25 Mar 2026 16:24:29 +0100
Subject: [PATCH 08/11] TTFT support for remote llm + GGUF integrations (#32)

---
 examples/gguf_example.py          |   9 +-
 examples/openai_example.py        |  10 +-
 tests/test_integrations_openai.py | 151 ++++++++++++++++++++++++++++--
 wildedge/integrations/common.py   | 123 +++++++++++++++++++++++-
 wildedge/integrations/gguf.py     | 105 ++++++++++++++++-----
 wildedge/integrations/openai.py   |  88 ++++++++++++++++-
 6 files changed, 439 insertions(+), 47 deletions(-)

diff --git a/examples/gguf_example.py b/examples/gguf_example.py
index cf58f88..bd50f98 100644
--- a/examples/gguf_example.py
+++ b/examples/gguf_example.py
@@ -31,6 +31,9 @@
 ]
 
 for prompt in prompts:
-    result = llm(prompt, max_tokens=128, temperature=0.7)
-    text = result["choices"][0]["text"].strip()
-    print(f"Q: {prompt}\nA: {text}\n")
+    stream = llm(prompt, max_tokens=128, temperature=0.7, stream=True)
+    print(f"Q: {prompt}\nA: ", end="", flush=True)
+    for chunk in stream:
+        token = chunk["choices"][0].get("text", "")
+        print(token, end="", flush=True)
+    print("\n")
diff --git a/examples/openai_example.py b/examples/openai_example.py
index d9410e4..ad2d3a9 100644
--- a/examples/openai_example.py
+++ b/examples/openai_example.py
@@ -32,13 +32,19 @@
 ]
 
 for prompt in prompts:
-    response = openai_client.chat.completions.create(
+    stream = openai_client.chat.completions.create(
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}],
         temperature=0.7,
         max_tokens=256,
+        stream=True,
+        stream_options={"include_usage": True},
     )
-    print(f"Q: {prompt}\nA: {response.choices[0].message.content}\n")
+    print(f"Q: {prompt}\nA: ", end="", flush=True)
+    for chunk in stream:
+        if chunk.choices and chunk.choices[0].delta.content:
+            print(chunk.choices[0].delta.content, end="", flush=True)
+    print("\n")
 
 client.flush()
 print("Done. Events flushed to WildEdge.")
diff --git a/tests/test_integrations_openai.py b/tests/test_integrations_openai.py
index 9fea3ce..dbba8d0 100644
--- a/tests/test_integrations_openai.py
+++ b/tests/test_integrations_openai.py
@@ -9,6 +9,7 @@
 import pytest
 
 import wildedge.integrations.openai as openai_mod
+from wildedge.integrations.common import AsyncStreamWrapper, SyncStreamWrapper
 from wildedge.integrations.openai import (
     OpenAIExtractor,
     build_api_meta,
@@ -83,6 +84,56 @@ async def create(self, *args, **kwargs):
         return self._response
 
 
+def make_stream_chunk(content=None, finish_reason=None, usage=None):
+    chunk = SimpleNamespace(
+        choices=[
+            SimpleNamespace(
+                delta=SimpleNamespace(content=content),
+                finish_reason=finish_reason,
+            )
+        ],
+        usage=usage,
+        model="gpt-4o",
+        system_fingerprint=None,
+        service_tier=None,
+    )
+    return chunk
+
+
+class FakeStreamingCompletions:
+    def __init__(self, chunks):
+        self._chunks = chunks
+
+    def create(self, *args, **kwargs):
+        if kwargs.get("stream"):
+            return iter(self._chunks)
+        return FakeResponse()
+
+
+class FakeAsyncStreamingCompletions:
+    def __init__(self, chunks):
+        self._chunks = chunks
+
+    async def create(self, *args, **kwargs):
+        if kwargs.get("stream"):
+            return FakeAsyncIterator(self._chunks)
+        return FakeResponse()
+
+
+class FakeAsyncIterator:
+    def __init__(self, items):
+        self._iter = iter(items)
+
+    def __aiter__(self):
+        return self
+
+    async def __anext__(self):
+        try:
+            return next(self._iter)
+        except StopIteration:
+            raise StopAsyncIteration
+
+
 # Named "OpenAI" / "AsyncOpenAI" so can_handle sees the right type name.
 class OpenAI:
     def __init__(self, base_url="https://api.openai.com/v1", api_key=None):
@@ -371,11 +422,65 @@ def create(self, *args, **kwargs):
         client.handles["gpt-4o"].track_error.assert_called_once()
         client.handles["gpt-4o"].track_inference.assert_not_called()
 
-    def test_streaming_skips_tracking(self):
-        completions, client = self.setup()
-        completions.create(model="gpt-4o", messages=[], stream=True)
-        if "gpt-4o" in client.handles:
-            client.handles["gpt-4o"].track_inference.assert_not_called()
+    def test_streaming_returns_sync_stream_wrapper(self):
+        chunks = [make_stream_chunk("hi", None), make_stream_chunk(None, "stop")]
+        completions = FakeStreamingCompletions(chunks)
+        client = make_fake_client()
+        wrap_sync_completions(completions, "openai", lambda: client)
+        result = completions.create(model="gpt-4o", messages=[], stream=True)
+        assert isinstance(result, SyncStreamWrapper)
+
+    def test_streaming_records_inference_on_exhaustion(self):
+        chunks = [
+            make_stream_chunk("Hello", None),
+            make_stream_chunk(" world", "stop"),
+        ]
+        completions = FakeStreamingCompletions(chunks)
+        client = make_fake_client()
+        wrap_sync_completions(completions, "openai", lambda: client)
+        stream = completions.create(
+            model="gpt-4o", messages=[{"role": "user", "content": "hi"}], stream=True
+        )
+        list(stream)
+        handle = client.handles["gpt-4o"]
+        handle.track_inference.assert_called_once()
+        kwargs = handle.track_inference.call_args.kwargs
+        assert kwargs["output_meta"].time_to_first_token_ms is not None
+        assert kwargs["output_meta"].stop_reason == "stop"
+        assert kwargs["input_modality"] == "text"
+        assert kwargs["success"] is True
+
+    def test_streaming_captures_usage_from_chunks(self):
+        usage_chunk = SimpleNamespace(prompt_tokens=8, completion_tokens=15)
+        chunks = [
+            make_stream_chunk("hi", None),
+            make_stream_chunk(None, "stop", usage=usage_chunk),
+        ]
+        completions = FakeStreamingCompletions(chunks)
+        client = make_fake_client()
+        wrap_sync_completions(completions, "openai", lambda: client)
+        list(completions.create(model="gpt-4o", messages=[], stream=True))
+        out = client.handles["gpt-4o"].track_inference.call_args.kwargs["output_meta"]
+        assert out.tokens_in == 8
+        assert out.tokens_out == 15
+
+    def test_streaming_error_during_iteration_tracks_error(self):
+        def bad_iter():
+            yield make_stream_chunk("hi", None)
+            raise RuntimeError("stream error")
+
+        class ErrorStreamCompletions:
+            def create(self, *args, **kwargs):
+                return bad_iter()
+
+        client = make_fake_client()
+        completions = ErrorStreamCompletions()
+        wrap_sync_completions(completions, "openai", lambda: client)
+        stream = completions.create(model="gpt-4o", messages=[], stream=True)
+        with pytest.raises(RuntimeError, match="stream error"):
+            list(stream)
+        client.handles["gpt-4o"].track_error.assert_called_once()
+        client.handles["gpt-4o"].track_inference.assert_not_called()
 
     def test_closed_client_passes_through(self):
         completions, client = self.setup(closed=True)
@@ -438,11 +543,37 @@ async def create(self, *args, **kwargs):
 
         client.handles["gpt-4o"].track_error.assert_called_once()
 
-    async def test_streaming_skips_tracking(self):
-        completions, client = self.setup()
-        await completions.create(model="qwen/qwen3-235b", messages=[], stream=True)
-        if "qwen/qwen3-235b" in client.handles:
-            client.handles["qwen/qwen3-235b"].track_inference.assert_not_called()
+    async def test_streaming_returns_async_stream_wrapper(self):
+        chunks = [make_stream_chunk("hi", None), make_stream_chunk(None, "stop")]
+        completions = FakeAsyncStreamingCompletions(chunks)
+        client = make_fake_client()
+        wrap_async_completions(completions, "openrouter", lambda: client)
+        result = await completions.create(
+            model="qwen/qwen3-235b", messages=[], stream=True
+        )
+        assert isinstance(result, AsyncStreamWrapper)
+
+    async def test_streaming_records_inference_on_exhaustion(self):
+        chunks = [
+            make_stream_chunk("Hello", None),
+            make_stream_chunk(" world", "stop"),
+        ]
+        completions = FakeAsyncStreamingCompletions(chunks)
+        client = make_fake_client()
+        wrap_async_completions(completions, "openrouter", lambda: client)
+        stream = await completions.create(
+            model="qwen/qwen3-235b",
+            messages=[{"role": "user", "content": "hi"}],
+            stream=True,
+        )
+        async for _ in stream:
+            pass
+        handle = client.handles["qwen/qwen3-235b"]
+        handle.track_inference.assert_called_once()
+        kwargs = handle.track_inference.call_args.kwargs
+        assert kwargs["output_meta"].time_to_first_token_ms is not None
+        assert kwargs["output_meta"].stop_reason == "stop"
+        assert kwargs["success"] is True
 
 
 # ---------------------------------------------------------------------------
diff --git a/wildedge/integrations/common.py b/wildedge/integrations/common.py
index 22a431a..1506b01 100644
--- a/wildedge/integrations/common.py
+++ b/wildedge/integrations/common.py
@@ -2,9 +2,15 @@
 
 from __future__ import annotations
 
-from typing import Any
+from collections.abc import Callable
+from typing import TYPE_CHECKING, Any
 
+from wildedge import constants
 from wildedge.logging import logger
+from wildedge.timing import elapsed_ms
+
+if TYPE_CHECKING:
+    from wildedge.model import ModelHandle
 
 
 def debug_failure(framework: str, context: str, exc: BaseException) -> None:
@@ -110,3 +116,118 @@ def num_classes_from_output_shape(shape: tuple) -> int:
     if len(shape) >= 2 and isinstance(shape[-1], int) and shape[-1] > 1:
         return int(shape[-1])
     return 0
+
+
+# ---------------------------------------------------------------------------
+# Generic streaming wrappers
+# ---------------------------------------------------------------------------
+# Each integration provides:
+#   on_chunk(chunk) -> None        : update mutable state from a single chunk
+#   on_done(duration_ms, ttft_ms)  : record inference once the stream is exhausted
+#
+# The wrappers handle TTFT capture, error tracking, context-manager delegation,
+# and attribute proxying so callers get a drop-in replacement for the raw stream.
+
+
+class SyncStreamWrapper:
+    """Wraps a sync iterable stream to capture TTFT and record inference on exhaustion."""
+
+    def __init__(
+        self,
+        original: object,
+        handle: ModelHandle,
+        t0: float,
+        on_chunk: Callable[[object], None] | None,
+        on_done: Callable[[int, int | None], None],
+    ) -> None:
+        self._original = original
+        self._handle = handle
+        self._t0 = t0
+        self._on_chunk = on_chunk
+        self._on_done = on_done
+
+    def __iter__(self):
+        return self._track()
+
+    def _track(self):
+        ttft_ms: int | None = None
+        try:
+            for chunk in self._original:  # type: ignore[union-attr]
+                if ttft_ms is None:
+                    ttft_ms = elapsed_ms(self._t0)
+                if self._on_chunk is not None:
+                    self._on_chunk(chunk)
+                yield chunk
+        except Exception as exc:
+            self._handle.track_error(
+                error_code="UNKNOWN",
+                error_message=str(exc)[: constants.ERROR_MSG_MAX_LEN],
+            )
+            raise
+        else:
+            self._on_done(elapsed_ms(self._t0), ttft_ms)
+
+    def __enter__(self) -> SyncStreamWrapper:
+        if hasattr(self._original, "__enter__"):
+            self._original.__enter__()  # type: ignore[union-attr]
+        return self
+
+    def __exit__(self, *args: object) -> object:
+        if hasattr(self._original, "__exit__"):
+            return self._original.__exit__(*args)  # type: ignore[union-attr]
+        return None
+
+    def __getattr__(self, name: str) -> object:
+        return getattr(self._original, name)
+
+
+class AsyncStreamWrapper:
+    """Wraps an async iterable stream to capture TTFT and record inference on exhaustion."""
+
+    def __init__(
+        self,
+        original: object,
+        handle: ModelHandle,
+        t0: float,
+        on_chunk: Callable[[object], None] | None,
+        on_done: Callable[[int, int | None], None],
+    ) -> None:
+        self._original = original
+        self._handle = handle
+        self._t0 = t0
+        self._on_chunk = on_chunk
+        self._on_done = on_done
+
+    def __aiter__(self):
+        return self._track()
+
+    async def _track(self):
+        ttft_ms: int | None = None
+        try:
+            async for chunk in self._original:  # type: ignore[union-attr]
+                if ttft_ms is None:
+                    ttft_ms = elapsed_ms(self._t0)
+                if self._on_chunk is not None:
+                    self._on_chunk(chunk)
+                yield chunk
+        except Exception as exc:
+            self._handle.track_error(
+                error_code="UNKNOWN",
+                error_message=str(exc)[: constants.ERROR_MSG_MAX_LEN],
+            )
+            raise
+        else:
+            self._on_done(elapsed_ms(self._t0), ttft_ms)
+
+    async def __aenter__(self) -> AsyncStreamWrapper:
+        if hasattr(self._original, "__aenter__"):
+            await self._original.__aenter__()  # type: ignore[union-attr]
+        return self
+
+    async def __aexit__(self, *args: object) -> object:
+        if hasattr(self._original, "__aexit__"):
+            return await self._original.__aexit__(*args)  # type: ignore[union-attr]
+        return None
+
+    def __getattr__(self, name: str) -> object:
+        return getattr(self._original, name)
diff --git a/wildedge/integrations/gguf.py b/wildedge/integrations/gguf.py
index 9937cdd..dc44360 100644
--- a/wildedge/integrations/gguf.py
+++ b/wildedge/integrations/gguf.py
@@ -12,7 +12,7 @@
 from wildedge import constants
 from wildedge.events.inference import GenerationOutputMeta, TextInputMeta
 from wildedge.integrations.base import BaseExtractor, patch_instance_call_once
-from wildedge.integrations.common import debug_failure
+from wildedge.integrations.common import SyncStreamWrapper, debug_failure
 from wildedge.logging import logger
 from wildedge.model import ModelInfo
 from wildedge.platforms import CURRENT_PLATFORM
@@ -69,6 +69,76 @@ def parse_quantization(filename: str) -> str | None:
     return None
 
 
+def make_gguf_input_meta(prompt: object, tokens_in: int | None) -> TextInputMeta | None:
+    if not isinstance(prompt, str) or not prompt:
+        return None
+    return TextInputMeta(
+        char_count=len(prompt),
+        word_count=len(prompt.split()),
+        token_count=tokens_in,
+    )
+
+
+def make_gguf_output_meta(
+    tokens_in: int | None,
+    tokens_out: int | None,
+    stop_reason: str | None,
+    ttft_ms: int | None,
+    duration_ms: int,
+) -> GenerationOutputMeta | None:
+    if tokens_out is None and ttft_ms is None:
+        return None
+    tps = (
+        round(tokens_out / duration_ms * 1000, 1)
+        if duration_ms > 0 and tokens_out
+        else None
+    )
+    return GenerationOutputMeta(
+        task="generation",
+        tokens_in=tokens_in,
+        tokens_out=tokens_out,
+        time_to_first_token_ms=ttft_ms,
+        tokens_per_second=tps,
+        stop_reason=stop_reason,
+    )
+
+
+def make_gguf_stream_callbacks(handle: object, prompt: object) -> tuple:
+    """Return (on_chunk, on_done) callbacks for a llama-cpp-python streaming response.
+
+    Chunks are dicts; usage appears in the final chunk when available.
+    """
+    tokens_in: list[int | None] = [None]
+    tokens_out: list[int | None] = [None]
+    stop_reason: list[str | None] = [None]
+
+    def on_chunk(chunk: object) -> None:
+        if not isinstance(chunk, dict):
+            return
+        usage = chunk.get("usage")
+        if usage:
+            tokens_in[0] = usage.get("prompt_tokens")
+            tokens_out[0] = usage.get("completion_tokens")
+        choices = chunk.get("choices") or []
+        if choices:
+            reason = choices[0].get("finish_reason")
+            if reason:
+                stop_reason[0] = reason
+
+    def on_done(duration_ms: int, ttft_ms: int | None) -> None:
+        ti, to, sr = tokens_in[0], tokens_out[0], stop_reason[0]
+        handle.track_inference(  # type: ignore[union-attr]
+            duration_ms=duration_ms,
+            input_modality="text",
+            output_modality="generation",
+            input_meta=make_gguf_input_meta(prompt, ti),
+            success=True,
+            output_meta=make_gguf_output_meta(ti, to, sr, ttft_ms, duration_ms),
+        )
+
+    return on_chunk, on_done
+
+
 def build_patched_call(original_call):
     def patched_call(self_inner, *args, **kwargs):
         handle = getattr(self_inner, GGUF_HANDLE_ATTR, None)
@@ -76,9 +146,13 @@ def patched_call(self_inner, *args, **kwargs):
             return original_call(self_inner, *args, **kwargs)
 
         prompt = args[0] if args else kwargs.get("prompt", "")
+        is_streaming: bool = bool(kwargs.get("stream", False))
         t0 = time.perf_counter()
         try:
             result = original_call(self_inner, *args, **kwargs)
+            if is_streaming:
+                on_chunk, on_done = make_gguf_stream_callbacks(handle, prompt)
+                return SyncStreamWrapper(result, handle, t0, on_chunk, on_done)
             duration_ms = elapsed_ms(t0)
             tokens_in = None
             tokens_out = None
@@ -89,36 +163,15 @@ def patched_call(self_inner, *args, **kwargs):
                     tokens_out = usage.get("completion_tokens")
             except Exception as exc:
                 debug_gguf_failure("usage extraction", exc)
-
-            input_meta = None
-            if isinstance(prompt, str) and prompt:
-                input_meta = TextInputMeta(
-                    char_count=len(prompt),
-                    word_count=len(prompt.split()),
-                    token_count=tokens_in,
-                )
-
-            output_meta = None
-            if tokens_out is not None:
-                tps = (
-                    round(tokens_out / duration_ms * 1000, 1)
-                    if duration_ms > 0
-                    else None
-                )
-                output_meta = GenerationOutputMeta(
-                    task="generation",
-                    tokens_in=tokens_in,
-                    tokens_out=tokens_out,
-                    tokens_per_second=tps,
-                )
-
             handle.track_inference(
                 duration_ms=duration_ms,
                 input_modality="text",
                 output_modality="generation",
-                input_meta=input_meta,
+                input_meta=make_gguf_input_meta(prompt, tokens_in),
                 success=True,
-                output_meta=output_meta,
+                output_meta=make_gguf_output_meta(
+                    tokens_in, tokens_out, None, None, duration_ms
+                ),
             )
             return result
         except Exception as exc:
diff --git a/wildedge/integrations/openai.py b/wildedge/integrations/openai.py
index e5d1525..31281e9 100644
--- a/wildedge/integrations/openai.py
+++ b/wildedge/integrations/openai.py
@@ -11,7 +11,11 @@
 from wildedge import constants
 from wildedge.events.inference import ApiMeta, GenerationOutputMeta, TextInputMeta
 from wildedge.integrations.base import BaseExtractor
-from wildedge.integrations.common import debug_failure
+from wildedge.integrations.common import (
+    AsyncStreamWrapper,
+    SyncStreamWrapper,
+    debug_failure,
+)
 from wildedge.model import ModelInfo
 from wildedge.timing import elapsed_ms
 
@@ -58,6 +62,28 @@ def build_input_meta(messages: list, tokens_in: int | None) -> TextInputMeta | N
     )
 
 
+def build_streaming_output_meta(
+    ttft_ms: int | None,
+    tokens_in: int | None,
+    tokens_out: int | None,
+    stop_reason: str | None,
+    duration_ms: int,
+) -> GenerationOutputMeta:
+    tps = (
+        round(tokens_out / duration_ms * 1000, 1)
+        if duration_ms > 0 and tokens_out
+        else None
+    )
+    return GenerationOutputMeta(
+        task="generation",
+        tokens_in=tokens_in,
+        tokens_out=tokens_out,
+        time_to_first_token_ms=ttft_ms,
+        tokens_per_second=tps,
+        stop_reason=stop_reason,
+    )
+
+
 def build_output_meta(
     response: object, duration_ms: int
 ) -> GenerationOutputMeta | None:
@@ -145,6 +171,50 @@ def record_inference(
     )
 
 
+def make_openai_stream_callbacks(
+    handle: ModelHandle,
+    messages: list,
+) -> tuple:
+    """Return (on_chunk, on_done) callbacks for an OpenAI streaming response.
+
+    on_chunk updates mutable state from each ChatCompletionChunk.
+    on_done is called with (duration_ms, ttft_ms) when the stream is exhausted.
+    """
+    tokens_in: list[int | None] = [None]
+    tokens_out: list[int | None] = [None]
+    stop_reason: list[str | None] = [None]
+    last_chunk: list[object] = [None]
+
+    def on_chunk(chunk: object) -> None:
+        last_chunk[0] = chunk
+        chunk_usage = getattr(chunk, "usage", None)
+        if chunk_usage is not None:
+            tokens_in[0] = getattr(chunk_usage, "prompt_tokens", None)
+            tokens_out[0] = getattr(chunk_usage, "completion_tokens", None)
+        choices = getattr(chunk, "choices", None) or []
+        if choices:
+            reason = getattr(choices[0], "finish_reason", None)
+            if reason:
+                stop_reason[0] = reason
+
+    def on_done(duration_ms: int, ttft_ms: int | None) -> None:
+        ti, to, sr = tokens_in[0], tokens_out[0], stop_reason[0]
+        output_meta = build_streaming_output_meta(ttft_ms, ti, to, sr, duration_ms)
+        handle.track_inference(
+            duration_ms=duration_ms,
+            input_modality="text",
+            output_modality="generation",
+            success=True,
+            input_meta=build_input_meta(messages, ti),
+            output_meta=output_meta,
+            api_meta=build_api_meta(last_chunk[0])
+            if last_chunk[0] is not None
+            else None,
+        )
+
+    return on_chunk, on_done
+
+
 def wrap_sync_completions(completions: object, source: str, client_ref: object) -> None:
     original_create = completions.create  # type: ignore[attr-defined]
     model_handles: dict[str, ModelHandle] = {}
@@ -160,8 +230,12 @@ def patched_create(*args, **kwargs):
         t0 = time.perf_counter()
         try:
             result = original_create(*args, **kwargs)
-            if not is_streaming and handle is not None:
-                record_inference(handle, result, messages, elapsed_ms(t0))
+            if handle is not None:
+                if is_streaming:
+                    on_chunk, on_done = make_openai_stream_callbacks(handle, messages)
+                    return SyncStreamWrapper(result, handle, t0, on_chunk, on_done)
+                else:
+                    record_inference(handle, result, messages, elapsed_ms(t0))
             return result
         except Exception as exc:
             if handle is not None:
@@ -191,8 +265,12 @@ async def patched_create(*args, **kwargs):
         t0 = time.perf_counter()
         try:
             result = await original_create(*args, **kwargs)
-            if not is_streaming and handle is not None:
-                record_inference(handle, result, messages, elapsed_ms(t0))
+            if handle is not None:
+                if is_streaming:
+                    on_chunk, on_done = make_openai_stream_callbacks(handle, messages)
+                    return AsyncStreamWrapper(result, handle, t0, on_chunk, on_done)
+                else:
+                    record_inference(handle, result, messages, elapsed_ms(t0))
             return result
         except Exception as exc:
             if handle is not None:

From d26d404dcd30474eb51a9e081a225a664e1a02ad Mon Sep 17 00:00:00 2001
From: Piotr Duda <piotrekno1@gmail.com>
Date: Fri, 27 Mar 2026 08:25:40 +0100
Subject: [PATCH 09/11] Exclude /examples from sdist

---
 pyproject.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pyproject.toml b/pyproject.toml
index 3a7e63e..7f15e04 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -42,6 +42,7 @@ build-backend = "hatchling.build"
 [tool.hatch.build]
 exclude = [
     "/scripts",
+    "/examples",
 ]
 
 [tool.hatch.build.targets.wheel]

From 7b547c5d0ab8549361211a7fc5eabdb148430970 Mon Sep 17 00:00:00 2001
From: Piotr Duda <piotrekno1@gmail.com>
Date: Tue, 31 Mar 2026 19:38:22 +0200
Subject: [PATCH 10/11] Support for Agentic workflow monitoring (#28)

---
 .gitignore                        |   3 +-
 README.md                         |   1 -
 docs/manual-tracking.md           |  55 ++++++++
 examples/agentic_example.py       | 181 ++++++++++++++++++++++++++
 tests/test_event_serialization.py |  42 ++++++
 tests/test_tracing.py             |  93 +++++++++++++
 wildedge/__init__.py              |  20 ++-
 wildedge/client.py                | 209 ++++++++++++++++++++++++++++++
 wildedge/decorators.py            |  22 ++++
 wildedge/events/__init__.py       |   2 +
 wildedge/events/common.py         |  11 ++
 wildedge/events/error.py          |  26 +++-
 wildedge/events/feedback.py       |  26 +++-
 wildedge/events/inference.py      |  26 +++-
 wildedge/events/model_download.py |  26 +++-
 wildedge/events/model_load.py     |  26 +++-
 wildedge/events/model_unload.py   |  26 +++-
 wildedge/events/span.py           |  79 +++++++++++
 wildedge/integrations/openai.py   |  12 +-
 wildedge/model.py                 | 115 ++++++++++++++++
 wildedge/tracing.py               | 167 ++++++++++++++++++++++++
 21 files changed, 1157 insertions(+), 11 deletions(-)
 create mode 100644 examples/agentic_example.py
 create mode 100644 tests/test_tracing.py
 create mode 100644 wildedge/events/common.py
 create mode 100644 wildedge/events/span.py
 create mode 100644 wildedge/tracing.py

diff --git a/.gitignore b/.gitignore
index 64d49ae..468c518 100644
--- a/.gitignore
+++ b/.gitignore
@@ -213,4 +213,5 @@ marimo/_lsp/
 __marimo__/
 
 # Streamlit
-.streamlit/secrets.toml
\ No newline at end of file
+.streamlit/secrets.toml
+internal/
diff --git a/README.md b/README.md
index 1c24d0b..1777cd2 100644
--- a/README.md
+++ b/README.md
@@ -59,7 +59,6 @@ client = wildedge.init(
 If no DSN is configured, the client becomes a no-op and logs a warning.
 
 `init(...)` is a convenience wrapper for `WildEdge(...)` + `instrument(...)`.
-
 ## Supported integrations
 
 **On-device**
diff --git a/docs/manual-tracking.md b/docs/manual-tracking.md
index f90f58a..0fa227e 100644
--- a/docs/manual-tracking.md
+++ b/docs/manual-tracking.md
@@ -215,3 +215,58 @@ handle.feedback(FeedbackType.THUMBS_DOWN)
 ```
 
 `FeedbackType` values: `THUMBS_UP`, `THUMBS_DOWN`.
+
+## Track spans for agentic workflows
+
+Use span events to track non-inference steps like planning, tool calls, retrieval, or memory updates.
+
+```python
+from wildedge.timing import Timer
+
+with Timer() as t:
+    tool_result = call_tool()
+
+client.track_span(
+    kind="tool",
+    name="call_tool",
+    duration_ms=t.elapsed_ms,
+    status="ok",
+    attributes={"tool": "search"},
+)
+```
+
+You can also attach optional correlation fields (`trace_id`, `span_id`,
+`parent_span_id`, `run_id`, `agent_id`, `step_index`, `conversation_id`) to any
+event by passing them into `track_inference`, `track_error`, `track_feedback`,
+or `track_span`. Use `context=` for correlation attributes shared across events.
+
+### Trace context helpers
+
+Use `client.trace()` and `client.span()` to auto-populate correlation fields for
+all events emitted inside the block. `client.span()` times the block and emits a
+span event on exit:
+
+```python
+import wildedge
+from wildedge.timing import Timer
+
+client = wildedge.init()
+handle = client.register_model(my_model, model_id="my-org/my-model")
+
+with client.trace(run_id="run-123", agent_id="agent-1"):
+    with client.span(kind="agent_step", name="plan", step_index=1):
+        with Timer() as t:
+            result = my_model(prompt)
+        handle.track_inference(duration_ms=t.elapsed_ms, input_modality="text", output_modality="generation")
+```
+
+If you need to set correlation fields without emitting a span event, use the
+lower-level `span_context()` directly:
+
+```python
+with client.trace(run_id="run-123", agent_id="agent-1"):
+    with wildedge.span_context(step_index=1):
+        with Timer() as t:
+            result = my_model(prompt)
+        handle.track_inference(duration_ms=t.elapsed_ms, input_modality="text", output_modality="generation")
+```
diff --git a/examples/agentic_example.py b/examples/agentic_example.py
new file mode 100644
index 0000000..446c812
--- /dev/null
+++ b/examples/agentic_example.py
@@ -0,0 +1,181 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["wildedge-sdk", "openai"]
+#
+# [tool.uv.sources]
+# wildedge-sdk = { path = "..", editable = true }
+# ///
+"""Agentic workflow example with tool use.
+
+Demonstrates WildEdge tracing for a simple agent that:
+  - Runs within a trace (one per agent session)
+  - Wraps each reasoning step in an agent_step span
+  - Wraps each tool call in a tool span
+  - Tracks LLM inference automatically via the OpenAI integration
+
+Run with: uv run agentic_example.py
+Requires: OPENROUTER_API_KEY environment variable. Set WILDEDGE_DSN to send events.
+"""
+
+import json
+import os
+import time
+import uuid
+
+from openai import OpenAI
+
+import wildedge
+
+we = wildedge.init(
+    app_version="1.0.0",
+    integrations="openai",
+)
+
+openai_client = OpenAI(
+    base_url="https://openrouter.ai/api/v1",
+    api_key=os.getenv("OPENROUTER_API_KEY"),
+)
+
+# --- Tools -------------------------------------------------------------------
+
+TOOLS = [
+    {
+        "type": "function",
+        "function": {
+            "name": "get_weather",
+            "description": "Return current weather for a city.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "city": {"type": "string"},
+                },
+                "required": ["city"],
+            },
+        },
+    },
+    {
+        "type": "function",
+        "function": {
+            "name": "calculator",
+            "description": "Evaluate a simple arithmetic expression.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "expression": {"type": "string"},
+                },
+                "required": ["expression"],
+            },
+        },
+    },
+]
+
+
+def get_weather(city: str) -> str:
+    # ~150ms to simulate a real weather API call.
+    time.sleep(0.15)
+    return json.dumps({"city": city, "temperature_c": 18, "condition": "partly cloudy"})
+
+
+def calculator(expression: str) -> str:
+    # ~60ms to simulate a remote computation call.
+    time.sleep(0.06)
+    try:
+        result = eval(expression, {"__builtins__": {}})  # noqa: S307
+        return json.dumps({"expression": expression, "result": result})
+    except Exception as e:
+        return json.dumps({"error": str(e)})
+
+
+TOOL_HANDLERS = {
+    "get_weather": get_weather,
+    "calculator": calculator,
+}
+
+
+# --- Agent loop --------------------------------------------------------------
+
+
+def call_tool(name: str, arguments: dict) -> str:
+    with we.span(
+        kind="tool",
+        name=name,
+        input_summary=json.dumps(arguments)[:200],
+    ) as span:
+        result = TOOL_HANDLERS[name](**arguments)
+        span.output_summary = result[:200]
+    return result
+
+
+def retrieve_context(query: str) -> str:
+    """Fetch relevant context from the vector store (~120ms)."""
+    with we.span(
+        kind="retrieval",
+        name="vector_search",
+        input_summary=query[:200],
+    ) as span:
+        time.sleep(0.12)
+        result = f"[context: background knowledge relevant to '{query[:40]}']"
+        span.output_summary = result
+    return result
+
+
+def run_agent(task: str, step_index: int, messages: list) -> str:
+    # Fetch context before the first reasoning step, include it in the user turn.
+    context = retrieve_context(task)
+    messages.append({"role": "user", "content": f"{task}\n\nContext: {context}"})
+
+    while True:
+        with we.span(
+            kind="agent_step",
+            name="reason",
+            step_index=step_index,
+            input_summary=task[:200],
+        ) as span:
+            response = openai_client.chat.completions.create(
+                model="qwen/qwen3.5-flash-02-23",
+                messages=messages,
+                tools=TOOLS,
+                tool_choice="auto",
+                max_tokens=512,
+            )
+            choice = response.choices[0]
+            span.output_summary = choice.finish_reason
+
+        messages.append(choice.message.model_dump(exclude_none=True))
+
+        if choice.finish_reason == "tool_calls":
+            step_index += 1
+            for tool_call in choice.message.tool_calls:
+                arguments = json.loads(tool_call.function.arguments)
+                result = call_tool(tool_call.function.name, arguments)
+                messages.append(
+                    {
+                        "role": "tool",
+                        "tool_call_id": tool_call.id,
+                        "content": result,
+                    }
+                )
+                # Not instrumented: context window update between tool calls (~80ms).
+                # Shows up as a gap stripe in the trace view.
+                time.sleep(0.08)
+        else:
+            return choice.message.content or ""
+
+
+# --- Main --------------------------------------------------------------------
+
+TASKS = [
+    "What's the weather like in Tokyo, and what is 42 * 18?",
+    "Is it warmer in Paris or Berlin right now?",
+]
+
+system_prompt = "You are a helpful assistant. Use tools when needed."
+messages = [{"role": "system", "content": system_prompt}]
+
+with we.trace(agent_id="demo-agent", run_id=str(uuid.uuid4())):
+    for i, task in enumerate(TASKS, start=1):
+        print(f"\nTask {i}: {task}")
+        reply = run_agent(task, step_index=i, messages=messages)
+        print(f"Reply: {reply}")
+
+we.flush()
diff --git a/tests/test_event_serialization.py b/tests/test_event_serialization.py
index 12028c7..587940b 100644
--- a/tests/test_event_serialization.py
+++ b/tests/test_event_serialization.py
@@ -4,6 +4,7 @@
 from wildedge.events.inference import InferenceEvent, TextInputMeta
 from wildedge.events.model_download import AdapterDownload, ModelDownloadEvent
 from wildedge.events.model_load import AdapterLoad, ModelLoadEvent
+from wildedge.events.span import SpanEvent
 
 
 def test_inference_event_to_dict_omits_none_fields():
@@ -72,3 +73,44 @@ def test_feedback_event_enum_and_string_forms():
     )
     assert enum_event.to_dict()["feedback"]["feedback_type"] == "accept"
     assert string_event.to_dict()["feedback"]["feedback_type"] == "reject"
+
+
+def test_span_event_to_dict_includes_required_fields():
+    event = SpanEvent(
+        kind="tool",
+        name="search",
+        duration_ms=250,
+        status="ok",
+        attributes={"provider": "custom"},
+    )
+    data = event.to_dict()
+    assert data["event_type"] == "span"
+    assert data["span"]["kind"] == "tool"
+    assert data["span"]["attributes"]["provider"] == "custom"
+
+
+def test_span_event_context_serializes_under_context_key():
+    event = SpanEvent(
+        kind="agent_step",
+        name="plan",
+        duration_ms=10,
+        status="ok",
+        context={"user_id": "u1"},
+    )
+    data = event.to_dict()
+    assert data["context"] == {"user_id": "u1"}
+    assert "attributes" not in data
+
+
+def test_span_event_attributes_and_context_are_independent():
+    event = SpanEvent(
+        kind="tool",
+        name="search",
+        duration_ms=50,
+        status="ok",
+        attributes={"provider": "custom"},
+        context={"user_id": "u1"},
+    )
+    data = event.to_dict()
+    assert data["span"]["attributes"] == {"provider": "custom"}
+    assert data["context"] == {"user_id": "u1"}
diff --git a/tests/test_tracing.py b/tests/test_tracing.py
new file mode 100644
index 0000000..944f1e0
--- /dev/null
+++ b/tests/test_tracing.py
@@ -0,0 +1,93 @@
+from __future__ import annotations
+
+from wildedge.client import SpanContextManager
+from wildedge.model import ModelHandle, ModelInfo
+from wildedge.tracing import get_span_context, span_context, trace_context
+
+
+def test_track_inference_uses_trace_context():
+    events: list[dict] = []
+
+    def publish(event: dict) -> None:
+        events.append(event)
+
+    handle = ModelHandle(
+        "model-1",
+        ModelInfo(
+            model_name="test",
+            model_version="1.0",
+            model_source="local",
+            model_format="onnx",
+        ),
+        publish,
+    )
+
+    with trace_context(
+        trace_id="trace-123",
+        run_id="run-1",
+        agent_id="agent-1",
+        attributes={"trace_key": "trace_val"},
+    ):
+        with span_context(span_id="span-abc", step_index=2, attributes={"span_key": 2}):
+            handle.track_inference(duration_ms=5)
+
+    assert events[0]["trace_id"] == "trace-123"
+    assert events[0]["parent_span_id"] == "span-abc"
+    assert events[0]["run_id"] == "run-1"
+    assert events[0]["agent_id"] == "agent-1"
+    assert events[0]["step_index"] == 2
+    assert events[0]["attributes"] == {"trace_key": "trace_val", "span_key": 2}
+
+
+class _FakeClient:
+    def __init__(self, events: list[dict]) -> None:
+        self._events = events
+
+    def track_span(self, **kwargs) -> str:
+        self._events.append(kwargs)
+        return kwargs.get("span_id", "")
+
+
+def test_span_root_has_no_parent():
+    """A root span must not reference itself as its own parent."""
+    events: list[dict] = []
+    client = _FakeClient(events)
+
+    with SpanContextManager(client, kind="agent_step", name="root"):
+        pass
+
+    assert len(events) == 1
+    assert events[0]["parent_span_id"] is None
+
+
+def test_span_context_restored_after_exit():
+    """The active span context must revert to the parent after a span exits."""
+    events: list[dict] = []
+    client = _FakeClient(events)
+
+    with span_context(span_id="parent-span"):
+        with SpanContextManager(client, kind="agent_step", name="child"):
+            inner_id = get_span_context().span_id
+
+        assert get_span_context().span_id == "parent-span"
+
+    assert inner_id != "parent-span"
+    assert events[0]["parent_span_id"] == "parent-span"
+    assert events[0]["span_id"] != "parent-span"
+
+
+def test_nested_spans_correct_parent_chain():
+    """Nested spans must each point to their direct parent, not themselves."""
+    events: list[dict] = []
+    client = _FakeClient(events)
+
+    with SpanContextManager(client, kind="agent_step", name="outer") as outer:
+        with SpanContextManager(client, kind="tool", name="inner") as inner:
+            pass
+
+    assert len(events) == 2
+    inner_ev, outer_ev = events[0], events[1]
+    assert inner_ev["span_id"] == inner.span_id
+    assert inner_ev["parent_span_id"] == outer.span_id
+    assert outer_ev["span_id"] == outer.span_id
+    assert outer_ev["parent_span_id"] is None
diff --git a/wildedge/__init__.py b/wildedge/__init__.py
index f1f449b..2b7993f 100644
--- a/wildedge/__init__.py
+++ b/wildedge/__init__.py
@@ -1,6 +1,6 @@
 """WildEdge Python SDK."""
 
-from wildedge.client import WildEdge
+from wildedge.client import SpanContextManager, WildEdge
 from wildedge.convenience import init
 from wildedge.decorators import track
 from wildedge.events import (
@@ -15,13 +15,22 @@
     GenerationConfig,
     GenerationOutputMeta,
     ImageInputMeta,
+    SpanEvent,
     TextInputMeta,
 )
+from wildedge.events.span import SpanKind, SpanStatus
 from wildedge.platforms import capture_hardware
 from wildedge.platforms.device_info import DeviceInfo
 from wildedge.platforms.hardware import HardwareContext, ThermalContext
 from wildedge.queue import QueuePolicy
 from wildedge.timing import Timer
+from wildedge.tracing import (
+    SpanContext,
+    TraceContext,
+    get_span_context,
+    get_trace_context,
+    span_context,
+)
 
 __all__ = [
     "WildEdge",
@@ -42,7 +51,16 @@
     "GenerationConfig",
     "AdapterLoad",
     "AdapterDownload",
+    "SpanEvent",
     "FeedbackType",
     "ErrorCode",
     "Timer",
+    "span_context",
+    "TraceContext",
+    "SpanContext",
+    "get_trace_context",
+    "get_span_context",
+    "SpanKind",
+    "SpanStatus",
+    "SpanContextManager",
 ]
diff --git a/wildedge/client.py b/wildedge/client.py
index da5e052..627cbc1 100644
--- a/wildedge/client.py
+++ b/wildedge/client.py
@@ -12,6 +12,8 @@
 from wildedge import constants
 from wildedge.consumer import Consumer
 from wildedge.dead_letters import DeadLetterStore
+from wildedge.events import SpanEvent
+from wildedge.events.span import SpanKind, SpanStatus
 from wildedge.hubs.base import BaseHubTracker
 from wildedge.hubs.huggingface import HuggingFaceHubTracker
 from wildedge.hubs.registry import supported_hubs
@@ -39,6 +41,14 @@
 from wildedge.queue import EventQueue, QueuePolicy
 from wildedge.settings import read_client_env, resolve_app_identity
 from wildedge.timing import Timer, elapsed_ms
+from wildedge.tracing import (
+    SpanContext,
+    _merge_correlation_fields,
+    _reset_span_context,
+    _set_span_context,
+    get_span_context,
+    trace_context,
+)
 from wildedge.transmitter import Transmitter
 
 DSN_FORMAT = "'https://<project-secret>@ingest.wildedge.dev/<project-key>'"
@@ -103,6 +113,101 @@ def parse_dsn(dsn: str) -> tuple[str, str, str]:
 ]
 
 
+class SpanContextManager:
+    def __init__(
+        self,
+        client: WildEdge,
+        *,
+        kind: SpanKind,
+        name: str,
+        status: SpanStatus = "ok",
+        model_id: str | None = None,
+        input_summary: str | None = None,
+        output_summary: str | None = None,
+        attributes: dict[str, Any] | None = None,
+        trace_id: str | None = None,
+        span_id: str | None = None,
+        parent_span_id: str | None = None,
+        run_id: str | None = None,
+        agent_id: str | None = None,
+        step_index: int | None = None,
+        conversation_id: str | None = None,
+        context: dict[str, Any] | None = None,
+    ):
+        self._client = client
+        self.kind = kind
+        self.name = name
+        self.status = status
+        self.model_id = model_id
+        self.input_summary = input_summary
+        self.output_summary = output_summary
+        self.attributes = attributes
+        self.trace_id = trace_id
+        self.span_id = span_id
+        self.parent_span_id = parent_span_id
+        self.run_id = run_id
+        self.agent_id = agent_id
+        self.step_index = step_index
+        self.conversation_id = conversation_id
+        self.context = context
+        self._t0: float | None = None
+        self._span_token = None
+
+    def __enter__(self):
+        self._t0 = time.perf_counter()
+        if self.span_id is None:
+            self.span_id = str(uuid.uuid4())
+        if self.parent_span_id is None:
+            current = get_span_context()
+            self.parent_span_id = current.span_id if current else None
+        self._span_token = _set_span_context(
+            SpanContext(
+                span_id=self.span_id,
+                parent_span_id=self.parent_span_id,
+                step_index=self.step_index,
+                attributes=self.context,
+            )
+        )
+        return self
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        if self._t0 is None:
+            return False
+        duration_ms = elapsed_ms(self._t0)
+        status = "error" if exc_type else self.status
+        # Restore parent span context before emitting, so _merge_correlation_fields
+        # sees the parent context rather than this span (which would make the span
+        # appear as its own parent).
+        if self._span_token is not None:
+            _reset_span_context(self._span_token)
+            self._span_token = None
+        self._client.track_span(
+            kind=self.kind,
+            name=self.name,
+            duration_ms=duration_ms,
+            status=status,
+            model_id=self.model_id,
+            input_summary=self.input_summary,
+            output_summary=self.output_summary,
+            attributes=self.attributes,
+            trace_id=self.trace_id,
+            span_id=self.span_id,
+            parent_span_id=self.parent_span_id,
+            run_id=self.run_id,
+            agent_id=self.agent_id,
+            step_index=self.step_index,
+            conversation_id=self.conversation_id,
+            context=self.context,
+        )
+        return False
+
+    async def __aenter__(self):
+        return self.__enter__()
+
+    async def __aexit__(self, exc_type, exc_val, exc_tb):
+        return self.__exit__(exc_type, exc_val, exc_tb)
+
+
 class WildEdge:
     """
     WildEdge on-device ML monitoring client.
@@ -381,6 +486,110 @@ def register_model(
 
         return handle
 
+    def trace(
+        self,
+        *,
+        trace_id: str | None = None,
+        run_id: str | None = None,
+        agent_id: str | None = None,
+        conversation_id: str | None = None,
+        attributes: dict[str, Any] | None = None,
+    ):
+        """Context manager that sets trace correlation fields."""
+        return trace_context(
+            trace_id=trace_id,
+            run_id=run_id,
+            agent_id=agent_id,
+            conversation_id=conversation_id,
+            attributes=attributes,
+        )
+
+    def span(
+        self,
+        *,
+        kind: SpanKind,
+        name: str,
+        status: SpanStatus = "ok",
+        model_id: str | None = None,
+        input_summary: str | None = None,
+        output_summary: str | None = None,
+        attributes: dict[str, Any] | None = None,
+        trace_id: str | None = None,
+        span_id: str | None = None,
+        parent_span_id: str | None = None,
+        run_id: str | None = None,
+        agent_id: str | None = None,
+        step_index: int | None = None,
+        conversation_id: str | None = None,
+        context: dict[str, Any] | None = None,
+    ) -> SpanContextManager:
+        """Context manager that times and emits a span event."""
+        return SpanContextManager(
+            self,
+            kind=kind,
+            name=name,
+            status=status,
+            model_id=model_id,
+            input_summary=input_summary,
+            output_summary=output_summary,
+            attributes=attributes,
+            trace_id=trace_id,
+            span_id=span_id,
+            parent_span_id=parent_span_id,
+            run_id=run_id,
+            agent_id=agent_id,
+            step_index=step_index,
+            conversation_id=conversation_id,
+            context=context,
+        )
+
+    def track_span(
+        self,
+        *,
+        kind: SpanKind,
+        name: str,
+        duration_ms: int,
+        status: SpanStatus = "ok",
+        model_id: str | None = None,
+        input_summary: str | None = None,
+        output_summary: str | None = None,
+        attributes: dict[str, Any] | None = None,
+        trace_id: str | None = None,
+        span_id: str | None = None,
+        parent_span_id: str | None = None,
+        run_id: str | None = None,
+        agent_id: str | None = None,
+        step_index: int | None = None,
+        conversation_id: str | None = None,
+        context: dict[str, Any] | None = None,
+    ) -> str:
+        """Emit a span event for agentic workflows and tooling."""
+        correlation = _merge_correlation_fields(
+            trace_id=trace_id,
+            span_id=span_id,
+            parent_span_id=parent_span_id,
+            run_id=run_id,
+            agent_id=agent_id,
+            step_index=step_index,
+            conversation_id=conversation_id,
+            context=context,
+        )
+        if correlation["span_id"] is None:
+            correlation["span_id"] = str(uuid.uuid4())
+        event = SpanEvent(
+            kind=kind,
+            name=name,
+            duration_ms=duration_ms,
+            status=status,
+            model_id=model_id,
+            input_summary=input_summary,
+            output_summary=output_summary,
+            attributes=attributes,
+            **correlation,
+        )
+        self.publish(event.to_dict())
+        return correlation["span_id"]
+
     def _find_extractor(self, model_obj: object) -> BaseExtractor | None:
         for candidate in DEFAULT_EXTRACTORS:
             if candidate.can_handle(model_obj):
diff --git a/wildedge/decorators.py b/wildedge/decorators.py
index fe2e3ff..f953159 100644
--- a/wildedge/decorators.py
+++ b/wildedge/decorators.py
@@ -38,6 +38,14 @@ def __init__(
         input_meta: Any = None,
         output_meta: Any = None,
         generation_config: Any = None,
+        trace_id: str | None = None,
+        span_id: str | None = None,
+        parent_span_id: str | None = None,
+        run_id: str | None = None,
+        agent_id: str | None = None,
+        step_index: int | None = None,
+        conversation_id: str | None = None,
+        context: dict[str, Any] | None = None,
     ):
         self.handle = handle
         self.input_type = input_type
@@ -46,6 +54,16 @@ def __init__(
         self.input_meta = input_meta
         self.output_meta = output_meta
         self.generation_config = generation_config
+        self._correlation = dict(
+            trace_id=trace_id,
+            span_id=span_id,
+            parent_span_id=parent_span_id,
+            run_id=run_id,
+            agent_id=agent_id,
+            step_index=step_index,
+            conversation_id=conversation_id,
+            context=context,
+        )
         self.start_time: float | None = None
 
     def __call__(self, func):
@@ -62,6 +80,7 @@ def wrapper(*args, **kwargs):
                     input_meta=self.input_meta,
                     output_meta=self.output_meta,
                     generation_config=self.generation_config,
+                    **self._correlation,
                 )
                 return result
             except Exception as exc:
@@ -69,6 +88,7 @@ def wrapper(*args, **kwargs):
                     self.handle.track_error(
                         error_code="UNKNOWN",
                         error_message=str(exc)[: constants.ERROR_MSG_MAX_LEN],
+                        **self._correlation,
                     )
                 raise
 
@@ -89,6 +109,7 @@ def __exit__(self, exc_type, exc_val, exc_tb):
                     error_message=str(exc_val)[: constants.ERROR_MSG_MAX_LEN]
                     if exc_val
                     else None,
+                    **self._correlation,
                 )
         else:
             self.handle.track_inference(
@@ -99,5 +120,6 @@ def __exit__(self, exc_type, exc_val, exc_tb):
                 input_meta=self.input_meta,
                 output_meta=self.output_meta,
                 generation_config=self.generation_config,
+                **self._correlation,
             )
         return False
diff --git a/wildedge/events/__init__.py b/wildedge/events/__init__.py
index b08bc78..6648c40 100644
--- a/wildedge/events/__init__.py
+++ b/wildedge/events/__init__.py
@@ -19,6 +19,7 @@
 from wildedge.events.model_download import AdapterDownload, ModelDownloadEvent
 from wildedge.events.model_load import AdapterLoad, ModelLoadEvent
 from wildedge.events.model_unload import ModelUnloadEvent
+from wildedge.events.span import SpanEvent
 
 __all__ = [
     "ApiMeta",
@@ -40,6 +41,7 @@
     "ModelDownloadEvent",
     "ModelLoadEvent",
     "ModelUnloadEvent",
+    "SpanEvent",
     "TextInputMeta",
     "TopKPrediction",
 ]
diff --git a/wildedge/events/common.py b/wildedge/events/common.py
new file mode 100644
index 0000000..399b55b
--- /dev/null
+++ b/wildedge/events/common.py
@@ -0,0 +1,11 @@
+from __future__ import annotations
+
+from typing import Any
+
+
+def add_optional_fields(event: dict, fields: dict[str, Any]) -> dict:
+    """Add non-None fields to an event payload."""
+    for key, value in fields.items():
+        if value is not None:
+            event[key] = value
+    return event
diff --git a/wildedge/events/error.py b/wildedge/events/error.py
index 13d29f1..e814120 100644
--- a/wildedge/events/error.py
+++ b/wildedge/events/error.py
@@ -23,6 +23,14 @@ class ErrorEvent:
     error_message: str | None = None
     stack_trace_hash: str | None = None
     related_event_id: str | None = None
+    trace_id: str | None = None
+    span_id: str | None = None
+    parent_span_id: str | None = None
+    run_id: str | None = None
+    agent_id: str | None = None
+    step_index: int | None = None
+    conversation_id: str | None = None
+    context: dict[str, Any] | None = None
     event_id: str = field(default_factory=lambda: str(uuid.uuid4()))
     timestamp: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
 
@@ -40,10 +48,26 @@ def to_dict(self) -> dict:
         if self.related_event_id is not None:
             error_data["related_event_id"] = self.related_event_id
 
-        return {
+        event = {
             "event_id": self.event_id,
             "event_type": "error",
             "timestamp": self.timestamp.isoformat(),
             "model_id": self.model_id,
             "error": error_data,
         }
+        from wildedge.events.common import add_optional_fields
+
+        add_optional_fields(
+            event,
+            {
+                "trace_id": self.trace_id,
+                "span_id": self.span_id,
+                "parent_span_id": self.parent_span_id,
+                "run_id": self.run_id,
+                "agent_id": self.agent_id,
+                "step_index": self.step_index,
+                "conversation_id": self.conversation_id,
+                "attributes": self.context,
+            },
+        )
+        return event
diff --git a/wildedge/events/feedback.py b/wildedge/events/feedback.py
index 650904b..dfb6efa 100644
--- a/wildedge/events/feedback.py
+++ b/wildedge/events/feedback.py
@@ -24,6 +24,14 @@ class FeedbackEvent:
     feedback_type: str | FeedbackType
     delay_ms: int | None = None
     edit_distance: int | None = None
+    trace_id: str | None = None
+    span_id: str | None = None
+    parent_span_id: str | None = None
+    run_id: str | None = None
+    agent_id: str | None = None
+    step_index: int | None = None
+    conversation_id: str | None = None
+    context: dict[str, Any] | None = None
     event_id: str = field(default_factory=lambda: str(uuid.uuid4()))
     timestamp: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
 
@@ -42,10 +50,26 @@ def to_dict(self) -> dict:
         if self.edit_distance is not None:
             feedback_data["edit_distance"] = self.edit_distance
 
-        return {
+        event = {
             "event_id": self.event_id,
             "event_type": "feedback",
             "timestamp": self.timestamp.isoformat(),
             "model_id": self.model_id,
             "feedback": feedback_data,
         }
+        from wildedge.events.common import add_optional_fields
+
+        add_optional_fields(
+            event,
+            {
+                "trace_id": self.trace_id,
+                "span_id": self.span_id,
+                "parent_span_id": self.parent_span_id,
+                "run_id": self.run_id,
+                "agent_id": self.agent_id,
+                "step_index": self.step_index,
+                "conversation_id": self.conversation_id,
+                "attributes": self.context,
+            },
+        )
+        return event
diff --git a/wildedge/events/inference.py b/wildedge/events/inference.py
index 0c02996..ef76ae5 100644
--- a/wildedge/events/inference.py
+++ b/wildedge/events/inference.py
@@ -304,6 +304,14 @@ class InferenceEvent:
     generation_config: GenerationConfig | None = None
     hardware: HardwareContext | None = None
     api_meta: ApiMeta | None = None
+    trace_id: str | None = None
+    span_id: str | None = None
+    parent_span_id: str | None = None
+    run_id: str | None = None
+    agent_id: str | None = None
+    step_index: int | None = None
+    conversation_id: str | None = None
+    context: dict[str, Any] | None = None
     event_id: str = field(default_factory=lambda: str(uuid.uuid4()))
     timestamp: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
     inference_id: str = field(default_factory=lambda: str(uuid.uuid4()))
@@ -333,10 +341,26 @@ def to_dict(self) -> dict:
         if self.api_meta is not None:
             inference_data["api_meta"] = self.api_meta.to_dict()
 
-        return {
+        event = {
             "event_id": self.event_id,
             "event_type": "inference",
             "timestamp": self.timestamp.isoformat(),
             "model_id": self.model_id,
             "inference": inference_data,
         }
+        from wildedge.events.common import add_optional_fields
+
+        add_optional_fields(
+            event,
+            {
+                "trace_id": self.trace_id,
+                "span_id": self.span_id,
+                "parent_span_id": self.parent_span_id,
+                "run_id": self.run_id,
+                "agent_id": self.agent_id,
+                "step_index": self.step_index,
+                "conversation_id": self.conversation_id,
+                "attributes": self.context,
+            },
+        )
+        return event
diff --git a/wildedge/events/model_download.py b/wildedge/events/model_download.py
index 784c62f..2e68a3a 100644
--- a/wildedge/events/model_download.py
+++ b/wildedge/events/model_download.py
@@ -49,6 +49,14 @@ class ModelDownloadEvent:
     cdn_edge: str | None = None
     error_code: str | None = None
     adapter: AdapterDownload | None = None
+    trace_id: str | None = None
+    span_id: str | None = None
+    parent_span_id: str | None = None
+    run_id: str | None = None
+    agent_id: str | None = None
+    step_index: int | None = None
+    conversation_id: str | None = None
+    context: dict[str, Any] | None = None
     event_id: str = field(default_factory=lambda: str(uuid.uuid4()))
     timestamp: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
 
@@ -83,10 +91,26 @@ def to_dict(self) -> dict:
         if self.adapter is not None:
             download_data["adapter"] = self.adapter.to_dict()
 
-        return {
+        event = {
             "event_id": self.event_id,
             "event_type": "model_download",
             "timestamp": self.timestamp.isoformat(),
             "model_id": self.model_id,
             "download": download_data,
         }
+        from wildedge.events.common import add_optional_fields
+
+        add_optional_fields(
+            event,
+            {
+                "trace_id": self.trace_id,
+                "span_id": self.span_id,
+                "parent_span_id": self.parent_span_id,
+                "run_id": self.run_id,
+                "agent_id": self.agent_id,
+                "step_index": self.step_index,
+                "conversation_id": self.conversation_id,
+                "attributes": self.context,
+            },
+        )
+        return event
diff --git a/wildedge/events/model_load.py b/wildedge/events/model_load.py
index 9fae742..e058092 100644
--- a/wildedge/events/model_load.py
+++ b/wildedge/events/model_load.py
@@ -55,6 +55,14 @@ class ModelLoadEvent:
     cold_start: bool | None = None
     compile_time_ms: int | None = None
     adapter: AdapterLoad | None = None
+    trace_id: str | None = None
+    span_id: str | None = None
+    parent_span_id: str | None = None
+    run_id: str | None = None
+    agent_id: str | None = None
+    step_index: int | None = None
+    conversation_id: str | None = None
+    context: dict[str, Any] | None = None
     event_id: str = field(default_factory=lambda: str(uuid.uuid4()))
     timestamp: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
 
@@ -84,10 +92,26 @@ def to_dict(self) -> dict:
         if self.adapter is not None:
             load_data["adapter"] = self.adapter.to_dict()
 
-        return {
+        event = {
             "event_id": self.event_id,
             "event_type": "model_load",
             "timestamp": self.timestamp.isoformat(),
             "model_id": self.model_id,
             "load": load_data,
         }
+        from wildedge.events.common import add_optional_fields
+
+        add_optional_fields(
+            event,
+            {
+                "trace_id": self.trace_id,
+                "span_id": self.span_id,
+                "parent_span_id": self.parent_span_id,
+                "run_id": self.run_id,
+                "agent_id": self.agent_id,
+                "step_index": self.step_index,
+                "conversation_id": self.conversation_id,
+                "attributes": self.context,
+            },
+        )
+        return event
diff --git a/wildedge/events/model_unload.py b/wildedge/events/model_unload.py
index 9dab481..16def90 100644
--- a/wildedge/events/model_unload.py
+++ b/wildedge/events/model_unload.py
@@ -14,6 +14,14 @@ class ModelUnloadEvent:
     memory_freed_bytes: int | None = None
     peak_memory_bytes: int | None = None
     uptime_ms: int | None = None
+    trace_id: str | None = None
+    span_id: str | None = None
+    parent_span_id: str | None = None
+    run_id: str | None = None
+    agent_id: str | None = None
+    step_index: int | None = None
+    conversation_id: str | None = None
+    context: dict[str, Any] | None = None
     event_id: str = field(default_factory=lambda: str(uuid.uuid4()))
     timestamp: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
 
@@ -30,10 +38,26 @@ def to_dict(self) -> dict:
             if v is not None:
                 unload_data[k] = v
 
-        return {
+        event = {
             "event_id": self.event_id,
             "event_type": "model_unload",
             "timestamp": self.timestamp.isoformat(),
             "model_id": self.model_id,
             "unload": unload_data,
         }
+        from wildedge.events.common import add_optional_fields
+
+        add_optional_fields(
+            event,
+            {
+                "trace_id": self.trace_id,
+                "span_id": self.span_id,
+                "parent_span_id": self.parent_span_id,
+                "run_id": self.run_id,
+                "agent_id": self.agent_id,
+                "step_index": self.step_index,
+                "conversation_id": self.conversation_id,
+                "attributes": self.context,
+            },
+        )
+        return event
diff --git a/wildedge/events/span.py b/wildedge/events/span.py
new file mode 100644
index 0000000..9d5be3c
--- /dev/null
+++ b/wildedge/events/span.py
@@ -0,0 +1,79 @@
+from __future__ import annotations
+
+import uuid
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from typing import Any, Literal
+
+from wildedge.events.common import add_optional_fields
+
+SpanKind = Literal[
+    "agent_step",
+    "tool",
+    "retrieval",
+    "memory",
+    "router",
+    "guardrail",
+    "cache",
+    "eval",
+    "custom",
+]
+SpanStatus = Literal["ok", "error"]
+
+
+@dataclass
+class SpanEvent:
+    kind: SpanKind
+    name: str
+    duration_ms: int
+    status: SpanStatus
+    model_id: str | None = None
+    input_summary: str | None = None
+    output_summary: str | None = None
+    attributes: dict[str, Any] | None = None
+    trace_id: str | None = None
+    span_id: str | None = None
+    parent_span_id: str | None = None
+    run_id: str | None = None
+    agent_id: str | None = None
+    step_index: int | None = None
+    conversation_id: str | None = None
+    context: dict[str, Any] | None = None
+    event_id: str = field(default_factory=lambda: str(uuid.uuid4()))
+    timestamp: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+
+    def to_dict(self) -> dict:
+        span_data: dict[str, Any] = {
+            "kind": self.kind,
+            "name": self.name,
+            "duration_ms": self.duration_ms,
+            "status": self.status,
+        }
+        if self.input_summary is not None:
+            span_data["input_summary"] = self.input_summary
+        if self.output_summary is not None:
+            span_data["output_summary"] = self.output_summary
+        if self.attributes is not None:
+            span_data["attributes"] = self.attributes
+
+        event = {
+            "event_id": self.event_id,
+            "event_type": "span",
+            "timestamp": self.timestamp.isoformat(),
+            "span": span_data,
+        }
+        add_optional_fields(
+            event,
+            {
+                "model_id": self.model_id,
+                "trace_id": self.trace_id,
+                "span_id": self.span_id,
+                "parent_span_id": self.parent_span_id,
+                "run_id": self.run_id,
+                "agent_id": self.agent_id,
+                "step_index": self.step_index,
+                "conversation_id": self.conversation_id,
+                "context": self.context,
+            },
+        )
+        return event
diff --git a/wildedge/integrations/openai.py b/wildedge/integrations/openai.py
index 31281e9..700aace 100644
--- a/wildedge/integrations/openai.py
+++ b/wildedge/integrations/openai.py
@@ -45,13 +45,21 @@ def source_from_base_url(base_url: str | None) -> str:
     return SOURCE_BY_HOSTNAME.get(hostname or "", hostname or "openai")
 
 
+def _msg_role(m) -> str | None:
+    return m.get("role") if isinstance(m, dict) else getattr(m, "role", None)
+
+
+def _msg_content(m) -> str | None:
+    return m.get("content") if isinstance(m, dict) else getattr(m, "content", None)
+
+
 def build_input_meta(messages: list, tokens_in: int | None) -> TextInputMeta | None:
     if not messages:
         return None
-    last_user = next((m for m in reversed(messages) if m.get("role") == "user"), None)
+    last_user = next((m for m in reversed(messages) if _msg_role(m) == "user"), None)
     if not last_user:
         return None
-    content = last_user.get("content", "")
+    content = _msg_content(last_user) or ""
     if not isinstance(content, str) or not content:
         return None
     return TextInputMeta(
diff --git a/wildedge/model.py b/wildedge/model.py
index de7e7b1..2502b14 100644
--- a/wildedge/model.py
+++ b/wildedge/model.py
@@ -28,6 +28,7 @@
 from wildedge.logging import logger
 from wildedge.platforms import capture_hardware, is_sampling
 from wildedge.platforms.hardware import HardwareContext
+from wildedge.tracing import _merge_correlation_fields
 
 
 @dataclass
@@ -68,8 +69,26 @@ def track_load(
         accelerator: str | None = None,
         success: bool = True,
         error_code: str | None = None,
+        trace_id: str | None = None,
+        span_id: str | None = None,
+        parent_span_id: str | None = None,
+        run_id: str | None = None,
+        agent_id: str | None = None,
+        step_index: int | None = None,
+        conversation_id: str | None = None,
+        context: dict[str, Any] | None = None,
         **kwargs: Any,
     ) -> None:
+        correlation = _merge_correlation_fields(
+            trace_id=trace_id,
+            span_id=span_id,
+            parent_span_id=parent_span_id,
+            run_id=run_id,
+            agent_id=agent_id,
+            step_index=step_index,
+            conversation_id=conversation_id,
+            context=context,
+        )
         event = ModelLoadEvent(
             model_id=self.model_id,
             duration_ms=duration_ms,
@@ -77,6 +96,7 @@ def track_load(
             accelerator=accelerator or self.detected_accelerator,
             success=success,
             error_code=error_code,
+            **correlation,
             **kwargs,
         )
         self.publish(event.to_dict())
@@ -89,7 +109,25 @@ def track_unload(
         memory_freed_bytes: int | None = None,
         peak_memory_bytes: int | None = None,
         uptime_ms: int | None = None,
+        trace_id: str | None = None,
+        span_id: str | None = None,
+        parent_span_id: str | None = None,
+        run_id: str | None = None,
+        agent_id: str | None = None,
+        step_index: int | None = None,
+        conversation_id: str | None = None,
+        context: dict[str, Any] | None = None,
     ) -> None:
+        correlation = _merge_correlation_fields(
+            trace_id=trace_id,
+            span_id=span_id,
+            parent_span_id=parent_span_id,
+            run_id=run_id,
+            agent_id=agent_id,
+            step_index=step_index,
+            conversation_id=conversation_id,
+            context=context,
+        )
         event = ModelUnloadEvent(
             model_id=self.model_id,
             duration_ms=duration_ms,
@@ -97,6 +135,7 @@ def track_unload(
             memory_freed_bytes=memory_freed_bytes,
             peak_memory_bytes=peak_memory_bytes,
             uptime_ms=uptime_ms,
+            **correlation,
         )
         self.publish(event.to_dict())
 
@@ -111,8 +150,26 @@ def track_download(
         resumed: bool,
         cache_hit: bool,
         success: bool,
+        trace_id: str | None = None,
+        span_id: str | None = None,
+        parent_span_id: str | None = None,
+        run_id: str | None = None,
+        agent_id: str | None = None,
+        step_index: int | None = None,
+        conversation_id: str | None = None,
+        context: dict[str, Any] | None = None,
         **kwargs: Any,
     ) -> None:
+        correlation = _merge_correlation_fields(
+            trace_id=trace_id,
+            span_id=span_id,
+            parent_span_id=parent_span_id,
+            run_id=run_id,
+            agent_id=agent_id,
+            step_index=step_index,
+            conversation_id=conversation_id,
+            context=context,
+        )
         event = ModelDownloadEvent(
             model_id=self.model_id,
             source_url=source_url,
@@ -124,6 +181,7 @@ def track_download(
             resumed=resumed,
             cache_hit=cache_hit,
             success=success,
+            **correlation,
             **kwargs,
         )
         self.publish(event.to_dict())
@@ -146,9 +204,27 @@ def track_inference(
         generation_config: GenerationConfig | None = None,
         hardware: HardwareContext | None = None,
         api_meta: ApiMeta | None = None,
+        trace_id: str | None = None,
+        span_id: str | None = None,
+        parent_span_id: str | None = None,
+        run_id: str | None = None,
+        agent_id: str | None = None,
+        step_index: int | None = None,
+        conversation_id: str | None = None,
+        context: dict[str, Any] | None = None,
     ) -> str:
         if hardware is None and is_sampling():
             hardware = capture_hardware()
+        correlation = _merge_correlation_fields(
+            trace_id=trace_id,
+            span_id=span_id,
+            parent_span_id=parent_span_id,
+            run_id=run_id,
+            agent_id=agent_id,
+            step_index=step_index,
+            conversation_id=conversation_id,
+            context=context,
+        )
         event = InferenceEvent(
             model_id=self.model_id,
             duration_ms=duration_ms,
@@ -162,6 +238,7 @@ def track_inference(
             generation_config=generation_config,
             hardware=hardware,
             api_meta=api_meta,
+            **correlation,
         )
         self.last_inference_id = event.inference_id
         self.publish(event.to_dict())
@@ -174,13 +251,32 @@ def track_feedback(
         *,
         delay_ms: int | None = None,
         edit_distance: int | None = None,
+        trace_id: str | None = None,
+        span_id: str | None = None,
+        parent_span_id: str | None = None,
+        run_id: str | None = None,
+        agent_id: str | None = None,
+        step_index: int | None = None,
+        conversation_id: str | None = None,
+        context: dict[str, Any] | None = None,
     ) -> None:
+        correlation = _merge_correlation_fields(
+            trace_id=trace_id,
+            span_id=span_id,
+            parent_span_id=parent_span_id,
+            run_id=run_id,
+            agent_id=agent_id,
+            step_index=step_index,
+            conversation_id=conversation_id,
+            context=context,
+        )
         event = FeedbackEvent(
             model_id=self.model_id,
             related_inference_id=related_inference_id,
             feedback_type=feedback_type,
             delay_ms=delay_ms,
             edit_distance=edit_distance,
+            **correlation,
         )
         self.publish(event.to_dict())
 
@@ -205,13 +301,32 @@ def track_error(
         error_message: str | None = None,
         stack_trace_hash: str | None = None,
         related_event_id: str | None = None,
+        trace_id: str | None = None,
+        span_id: str | None = None,
+        parent_span_id: str | None = None,
+        run_id: str | None = None,
+        agent_id: str | None = None,
+        step_index: int | None = None,
+        conversation_id: str | None = None,
+        context: dict[str, Any] | None = None,
     ) -> None:
+        correlation = _merge_correlation_fields(
+            trace_id=trace_id,
+            span_id=span_id,
+            parent_span_id=parent_span_id,
+            run_id=run_id,
+            agent_id=agent_id,
+            step_index=step_index,
+            conversation_id=conversation_id,
+            context=context,
+        )
         event = ErrorEvent(
             model_id=self.model_id,
             error_code=error_code,
             error_message=error_message,
             stack_trace_hash=stack_trace_hash,
             related_event_id=related_event_id,
+            **correlation,
         )
         self.publish(event.to_dict())
 
diff --git a/wildedge/tracing.py b/wildedge/tracing.py
new file mode 100644
index 0000000..a205543
--- /dev/null
+++ b/wildedge/tracing.py
@@ -0,0 +1,167 @@
+from __future__ import annotations
+
+import contextlib
+import contextvars
+import uuid
+from dataclasses import dataclass
+from typing import Any
+
+
+@dataclass(frozen=True)
+class TraceContext:
+    trace_id: str
+    run_id: str | None = None
+    agent_id: str | None = None
+    conversation_id: str | None = None
+    attributes: dict[str, Any] | None = None
+
+
+@dataclass(frozen=True)
+class SpanContext:
+    span_id: str
+    parent_span_id: str | None = None
+    step_index: int | None = None
+    attributes: dict[str, Any] | None = None
+
+
+_TRACE_CTX: contextvars.ContextVar[TraceContext | None] = contextvars.ContextVar(
+    "wildedge_trace_ctx", default=None
+)
+_SPAN_CTX: contextvars.ContextVar[SpanContext | None] = contextvars.ContextVar(
+    "wildedge_span_ctx", default=None
+)
+
+
+def get_trace_context() -> TraceContext | None:
+    return _TRACE_CTX.get()
+
+
+def get_span_context() -> SpanContext | None:
+    return _SPAN_CTX.get()
+
+
+def _set_trace_context(ctx: TraceContext) -> contextvars.Token:
+    return _TRACE_CTX.set(ctx)
+
+
+def _reset_trace_context(token: contextvars.Token) -> None:
+    _TRACE_CTX.reset(token)
+
+
+def _set_span_context(ctx: SpanContext) -> contextvars.Token:
+    return _SPAN_CTX.set(ctx)
+
+
+def _reset_span_context(token: contextvars.Token) -> None:
+    _SPAN_CTX.reset(token)
+
+
+@contextlib.contextmanager
+def trace_context(
+    *,
+    trace_id: str | None = None,
+    run_id: str | None = None,
+    agent_id: str | None = None,
+    conversation_id: str | None = None,
+    attributes: dict[str, Any] | None = None,
+):
+    if trace_id is None:
+        trace_id = str(uuid.uuid4())
+    token = _set_trace_context(
+        TraceContext(
+            trace_id=trace_id,
+            run_id=run_id,
+            agent_id=agent_id,
+            conversation_id=conversation_id,
+            attributes=attributes,
+        )
+    )
+    try:
+        yield get_trace_context()
+    finally:
+        _reset_trace_context(token)
+
+
+@contextlib.contextmanager
+def span_context(
+    *,
+    span_id: str | None = None,
+    parent_span_id: str | None = None,
+    step_index: int | None = None,
+    attributes: dict[str, Any] | None = None,
+):
+    """Low-level context manager that sets span correlation fields without emitting a span event.
+
+    Prefer client.span() for most use cases. Use this only when you need correlation
+    fields attached to auto-instrumented events (e.g. an OpenAI call) without emitting
+    a redundant span wrapper.
+    """
+    if span_id is None:
+        span_id = str(uuid.uuid4())
+    if parent_span_id is None:
+        current = get_span_context()
+        parent_span_id = current.span_id if current else None
+    token = _set_span_context(
+        SpanContext(
+            span_id=span_id,
+            parent_span_id=parent_span_id,
+            step_index=step_index,
+            attributes=attributes,
+        )
+    )
+    try:
+        yield get_span_context()
+    finally:
+        _reset_span_context(token)
+
+
+def _merge_context(*candidates: dict[str, Any] | None) -> dict[str, Any] | None:
+    merged: dict[str, Any] = {}
+    for attrs in candidates:
+        if not attrs:
+            continue
+        merged.update(attrs)
+    return merged or None
+
+
+def _merge_correlation_fields(
+    *,
+    trace_id: str | None = None,
+    span_id: str | None = None,
+    parent_span_id: str | None = None,
+    run_id: str | None = None,
+    agent_id: str | None = None,
+    step_index: int | None = None,
+    conversation_id: str | None = None,
+    context: dict[str, Any] | None = None,
+) -> dict[str, Any]:
+    trace = get_trace_context()
+    span = get_span_context()
+
+    resolved_trace_id = trace_id or (trace.trace_id if trace else None)
+    resolved_span_id = span_id
+    resolved_parent_span_id = parent_span_id or (span.span_id if span else None)
+    resolved_run_id = run_id or (trace.run_id if trace else None)
+    resolved_agent_id = agent_id or (trace.agent_id if trace else None)
+    resolved_step_index = (
+        step_index if step_index is not None else (span.step_index if span else None)
+    )
+    resolved_conversation_id = conversation_id or (
+        trace.conversation_id if trace else None
+    )
+    resolved_context = _merge_context(
+        trace.attributes if trace else None,
+        span.attributes if span else None,
+        context,
+    )
+
+    return {
+        "trace_id": resolved_trace_id,
+        "span_id": resolved_span_id,
+        "parent_span_id": resolved_parent_span_id,
+        "run_id": resolved_run_id,
+        "agent_id": resolved_agent_id,
+        "step_index": resolved_step_index,
+        "conversation_id": resolved_conversation_id,
+        "context": resolved_context,
+    }

From fced74b3bfba59d169e83a4033b134defb63145f Mon Sep 17 00:00:00 2001
From: Piotr Duda <piotrekno1@gmail.com>
Date: Tue, 31 Mar 2026 20:45:58 +0300
Subject: [PATCH 11/11] 0.1.3 release bump

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 7f15e04..fa9edea 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "wildedge-sdk"
-version = "0.1.2"
+version = "0.1.3"
 description = "On-device ML inference monitoring for Python"
 readme = "README.md"
 requires-python = ">=3.10"