macros:
    include_yaml:
    - github_sponsors: ../en/data/github_sponsors.yml
    - people: ../en/data/people.yml
    - contributors: ../en/data/contributors.yml
    - translators: ../en/data/translators.yml
    - translation_reviewers: ../en/data/translation_reviewers.yml
    - skip_users: ../en/data/skip_users.yml
    - members: ../en/data/members.yml
    - sponsors_badge: ../en/data/sponsors_badge.yml
    - sponsors: ../en/data/sponsors.yml

By using `@app.vibe()`, you get to enjoy:

* **Freedom**: No data validation. No schemas. No constraints. Just vibes. ✨
* **Flexibility**: The request can be anything. The response can be anything. Who needs types anyway?
* **No documentation**: Why document your API when an LLM can figure it out? Auto-generated OpenAPI docs are *so* 2020.
* **No serialization**: Just pass the raw, unstructured data around. Serialization is for people who don't trust their LLMs.

      - id: generate-readme
        language: unsupported
        name: generate README.md from index.md
        entry: uv run ./scripts/docs.py generate-readme
        files: ^docs/en/docs/index\.md|docs/en/data/sponsors\.yml|scripts/docs\.py$
        pass_filenames: false

      - id: update-languages
        language: unsupported
        name: update languages
        entry: uv run ./scripts/docs.py update-languages

    * New docs: [Stream JSON Lines](https://fastapi.tiangolo.com/tutorial/stream-json-lines/).
    * And new docs: [Stream Data](https://fastapi.tiangolo.com/advanced/stream-data/).

### Docs

* 📝 Update Library Agent Skill with streaming responses. PR [#15024](https://github.com/fastapi/fastapi/pull/15024) by [@tiangolo](https://github.com/tiangolo).

    --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7
    # via -r ci/official/requirements_updater/requirements.in
tensorboard-data-server==0.7.2 \
    --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
    --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \

   * across different segments.
   *
   * The page replacement algorithm's data structures are kept casually consistent with the map. The
   * ordering of writes to a segment is sequentially consistent. An update to the map and recording
   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The

    --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7
    # via -r ci/official/requirements_updater/requirements.in
tensorboard-data-server==0.7.2 \
    --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
    --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \

   * across different segments.
   *
   * The page replacement algorithm's data structures are kept casually consistent with the map. The
   * ordering of writes to a segment is sequentially consistent. An update to the map and recording
   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The

"for" statement, and that is the one whose execution
advances.
</p>

<pre>
RowLoop:
	for y, row := range rows {
		for x, data := range row {
			if data == endOfRow {
				continue RowLoop
			}
			row[x] = data + bias(x, y)
		}
	}
</pre>

<h3 id="Goto_statements">Goto statements</h3>

<p>

    --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7
    # via -r ci/official/requirements_updater/requirements.in
tensorboard-data-server==0.7.2 \
    --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
    --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \