> ## Documentation Index > Fetch the complete documentation index at: https://docs.quivr.thevibecompany.co/llms.txt > Use this file to discover all available pages before exploring further. # First-party plugins > The plugins that ship with Quivr: what each provides, its configuration, and where it runs. These plugins live in the `plugins/` folder of the repository. They use the same public protocol as your own plugins, and none is compiled into the engine. `make dev` runs the default set; optional plugins are pinned explicitly. | Plugin | Id | Type | Provides | | - | - | - | - | | `pdf-text` | `pdf-text` 0.1.0 | Normalizer | `application/pdf`: one Part per page | | `alerts` | `alerts` 0.3.0 | Alert rule | keyword and meaning alerts, alone or combined | | `core-ingest` | `core.ingest` 1.0.0 | Ingestion | token windows embedded with `multilingual-e5-small` | | `hosted-embed` | `hosted.embed` 1.0.0 | Ingestion | a configured hosted or OpenAI-compatible text model | | `core-retrieve` | `core.retrieve` 1.1.0 | Retrieval | `default` and `deep`: keyword, vector or hybrid search, as the index ranks it | | `jev-rerank` | `jev.rerank` 1.0.0 | Retrieval | `deep`: Jev re-ranking of a hybrid shortlist, with an unpaid hybrid fallback | | `rss` | `connector.rss` 1.0.0 | Connector | kind `rss`: RSS, Atom and JSON Feed | | `m365-mail` | `connector.m365_mail` 1.0.0 | Connector | kind `m365_mail`: a Microsoft 365 mailbox folder | | `x-list` | `connector.x_list` 1.1.0 | Connector | kind `x_list`: the posts of an X list | | `push-source` | `push-source` 0.1.0 | Connector | kind `events`: versioned text records received through an instance-token route | ## pdf-text Turns a PDF into one `body` Part per page with text, keyed `page-1`, `page-2`…, plus a `source` Part that references the PDF. The Version's `pdf-text.document` extension holds `page_count` and `text_pages`. Pages without text, such as scans, are skipped with an `empty_pages` warning: there is no OCR. An encrypted or damaged PDF is quarantined with the code `encrypted_pdf` or `corrupt_pdf`. | Configuration | Default | Meaning | | - | - | - | | `max_page_parts` | `64` | Page Parts kept, 1 to 64; later pages join the last one | | `max_text_bytes` | `131072` | UTF-8 bytes of page text kept in total, up to 262144 | | `include_source` | `true` | Add the `source` Part that references the PDF | Pin it with a route for `application/pdf`. See [Add content](/guides/add-content#upload-a-file) to upload a PDF. ## alerts Keyword and local-vector checks need no classifier key. Jev checks need a `TYPESAFE_API_KEY` in the plugin's environment. | Kind | Checks | Sends text to Jev? | | - | - | - | | `keywords` | Boolean query and metadata filters | No | | `meaning` | Local stored vectors; requires `meaning_check: vectors` | No | | `described` | Jev by default, local vectors with `meaning_check: vectors` | Yes, unless `meaning_check: vectors` | | `keywords_or_meaning` / `keywords_and_meaning` | Keyword and meaning checks, with an explicit `meaning_check` | With `meaning_check: jev` | Vector checks embed the description with the deployment's embedding provider, which also embeds every article. With the default `core-ingest` and an embedding server you run, that text stays inside the installation; with a hosted provider, it goes to that provider. The pin's `kinds` lists the alert kinds the deployment accepts. For keyword and local meaning checks without a TypeSafe key, pin `"kinds": ["keywords", "meaning", "keywords_or_meaning", "keywords_and_meaning"]`, as `make dev` does. Use `kind: meaning` for a local description, and `meaning_check: vectors` for every meaning check. This pin excludes `described`, so that kind is refused with `422 invalid_expression` even when it selects vectors. The kind list alone does not prevent a mixed expression from selecting Jev. To offer Jev checks: 1. Put the key in the `alerts` plugin's environment: `TYPESAFE_API_KEY=`. Never put it in Quivr's configuration, in logs or in a repository. 2. Add `described` to the pin's `kinds`, keeping the kinds already offered: `"kinds": ["keywords", "meaning", "keywords_or_meaning", "keywords_and_meaning", "described"]`. A kind missing from the list is refused for new alerts. 3. Restart the plugin and Quivr. The plugin logs at startup whether described alerts are enabled. `make dev` adds `described` only when `TYPESAFE_API_KEY` is set in its environment. Meaning kinds need `alerts` `0.3.0`; existing Subscriptions keep the version they name until you [migrate them](/run-quivr/upgrade-an-alert-rule). | Configuration | Default | Meaning | | - | - | - | | `fields` | `{}` | Filter names mapped to JSON Pointers into article metadata, such as `{"author": "/extensions/example.news/data/author"}` | | `text_roles` | `["title", "body"]` | Part roles that keyword terms search and Jev checks; local meaning checks use all supplied vectors | | `described.threshold` | `0.5` | Default Jev probability threshold, 0.2 to 0.95 | | `vectors.threshold` | `0.8` | Default local-vector cosine similarity threshold, 0.2 to 0.95 | See [How alerts work](/guides/alerts), [Keyword alerts](/guides/keyword-alerts) and [Meaning alerts](/guides/described-alerts). ## core-ingest The default ingestion plugin. It cuts the `title` and `body` Parts of each Version into windows of at most 384 tokens that overlap by 48 and prefer paragraph and sentence ends, then embeds each window in the space `core.ingest.e5-small@1` (384 dimensions, cosine) through a Text Embeddings Inference server. A Version with a title and no body, such as a feed item without a description, gets one segment: its title. It refuses a Version with no title or body text, more than 256 KiB of text, 64 Parts or 256 windows, which is then blocked with `ingestion_refused` and a diagnostic that names the reason, and a query longer than 256 tokens. | Configuration | Meaning | | - | - | | `tei_url` | The Text Embeddings Inference server that serves the pinned E5 model | | `tokenizer` | `python` and `model`: the pinned tokenizer helper and its `tokenizer.json` | ## hosted-embed The optional hosted ingestion plugin selects a model, dimensions and input templates by configuration. It supports OpenAI-compatible `/embeddings` and Cohere v2 `/embed` APIs, with bearer, `api-key` or no authentication. Its key is a declared `AZURE_FOUNDRY_KEY` secret in the plugin process environment. It cuts bounded text windows, batches requests and resumes completed batches after a retryable provider failure. Generate an immutable manifest from the configuration before installing it. Each model, dimension, revision or template change creates a new vector space; evaluation, backfill and promotion use the usual engine operations. Each provider attempt logs input-token usage for cost accounting. See the [configuration examples and package commands](https://github.com/The-Vibe-Company/quivr-v2/blob/main/plugins/hosted-embed/README.md). ## core-retrieve The default retrieval plugin: the search Quivr ran itself before it moved into a plugin, with the same rankings. It asks for one candidate list that follows the search mode, `bm25` on the title and body for `lexical`, `near_vector` in the served space for `semantic`, `hybrid` in the served space with alpha 0.5 and relative score fusion for `hybrid`, and returns it as the ranking. Candidates of exactly equal score rank by segment id. It declares `default` (500 ms, no paid call) and `deep` (3 s, 1 cent). Its `deep` ranks like `default`; to re-rank, install `jev.rerank` and map the short name `deep` to `jev.rerank/deep` in `retrieval.profiles`. See [Re-rank with Jev](/guides/rerank-with-jev) for that configuration. It has no plugin configuration. The api refuses to start without a retrieval plugin. ## jev-rerank The optional `jev.rerank` retrieval plugin declares only `deep`. It asks `core.retrieve/default` for a hybrid shortlist, then scores it in one batch with Jev, TypeSafe's paid model. A `deep` search can make paid calls; usage reports the calls and cost, and each re-ranked hit explains its probability. Without a TypeSafe key, or on errors and deadlines, it returns the original hybrid order without a Jev score. It can shorten passages, drop overlapping hits and cache scores. See [Re-rank with Jev](/guides/rerank-with-jev) for configuration and settings, and [Search profiles](/run-quivr/search-profiles) for how it builds on `core.retrieve/default`. ## rss Polls one feed per Connector Instance, with conditional requests and the feed's `ttl`. Each item becomes a Record keyed by its `guid` or `id`; an edited item becomes a new Version. It refuses private and loopback addresses unless `allow_private_addresses` is `true`, which only a local test deployment should set. See [RSS and Atom feeds](/guides/rss). ## m365-mail Collects one folder of one Microsoft 365 mailbox through Microsoft Graph: subject and body as text, attachments up to 25 MB as stored files. `login_endpoint` and `graph_endpoint` override Microsoft's global endpoints, for a national cloud. See [Microsoft 365 mail](/guides/microsoft-365). ## x-list Polls the posts of one X list, turns edits into corrections, and withdraws posts deleted or made protected on X within a recheck window. It can also receive posts in real time through X webhooks. `api_endpoint` overrides the X API origin, for a test fake only. See [X lists](/guides/x). ## push-source The offline Python sample accepts versioned text records at `POST records`, secured by a Quivr instance token. Its `events` kind maps each record into title and body Parts, preserving the sender's key and revision. It has no upstream credential or configuration, and its scheduled fetch only reports channel health. [Write a push source](/plugins/push-source) explains its route; [Receive and secure pushes](/run-quivr/receive-pushes) walks through access and tokens. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.