Files
coyote/src/rag/providers/qdrant.rs
T

493 lines
17 KiB
Rust

use crate::rag::provider::RagProvider;
use crate::rag::{DocumentId, RagData};
use anyhow::{Context, Result, bail};
use async_trait::async_trait;
use reqwest::header::{HeaderMap, HeaderValue};
use reqwest::{Client, Response, StatusCode};
use serde_json::Value;
use std::collections::HashMap;
/// Render Qdrant's error envelope into a human-readable message.
///
/// `body` is the raw response text. Two shapes have to be tolerated:
/// * application-level errors carry `{"status": {"error": "..."}, "time": 0.0}`,
/// while successful responses carry a bare string `{"status": "ok", ...}` — so
/// `status` is string-or-object and a struct with `status: String` fails to
/// parse every error body;
/// * routing-level 404s (a wrong HTTP verb) return an EMPTY body with no JSON at
/// all, which without the length check surfaces as "EOF while parsing a value"
/// instead of the actual 404.
fn format_error_body(status: StatusCode, body: &str) -> String {
if body.is_empty() {
return format!("HTTP {status} (empty body — check the HTTP verb and path)");
}
serde_json::from_str::<Value>(body)
.ok()
.and_then(|v| v["status"]["error"].as_str().map(str::to_string))
.unwrap_or_else(|| format!("HTTP {status}: {body}"))
}
/// Read the vector dimension out of a parsed `GET /collections/{name}` response.
fn vector_dimension_from_collection(body: &Value) -> Result<u64> {
let params = &body["result"]["config"]["params"];
params["vectors"]["size"]
.as_u64()
.or_else(|| {
params["vectors"]
.as_object()
.and_then(|m| m.values().next())
.and_then(|v| v["size"].as_u64())
})
.context("Could not determine vector dimension from collection config")
}
/// True if a parsed `GET /collections/{name}` response describes a NAMED
/// (multi-vector) collection.
///
/// `vector_search` posts an unnamed vector, which a named-vector collection
/// rejects with HTTP 400 on every query, so attaching one yields a RAG that is
/// silently 100% broken. A named collection holding a SINGLE vector is
/// structurally a map, identical in kind to the multi-named case, and rejects
/// the same way; testing for a numeric `size` directly under `vectors` catches
/// it, whereas counting keys (`len() > 1`) would wrongly accept it.
fn is_multi_vector_config(body: &Value) -> bool {
body["result"]["config"]["params"]["vectors"]["size"]
.as_u64()
.is_none()
}
/// Query-only client for an external Qdrant collection.
///
/// Attach-only: this provider never writes to the remote collection. Coyote does
/// not own the data, and `rebuild_indexes` refuses rather than pretending to.
pub struct QdrantProvider {
client: Client,
base_url: String,
collection: String,
}
impl QdrantProvider {
fn make_client(api_key: Option<&str>) -> Result<Client> {
let mut headers = HeaderMap::new();
if let Some(key) = api_key {
let mut value =
HeaderValue::from_str(key).context("api-key header value is not valid ASCII")?;
value.set_sensitive(true);
headers.insert("api-key", value);
}
Client::builder()
.default_headers(headers)
.build()
.context("Failed to build reqwest client")
}
pub(crate) fn normalize_base_url(host: &str) -> String {
if host.starts_with("http://") || host.starts_with("https://") {
host.to_string()
} else {
format!("http://{host}")
}
}
async fn error_message(resp: Response) -> String {
let status = resp.status();
let body = resp.text().await.unwrap_or_default();
format_error_body(status, &body)
}
/// Shared `GET /collections/{name}` fetch. Both the dimension and the
/// multi-vector probe discriminate on this same response.
async fn fetch_collection(
host: &str,
collection: &str,
api_key: Option<&str>,
) -> Result<Value> {
let base_url = Self::normalize_base_url(host);
let client = Self::make_client(api_key)?;
let resp = client
.get(format!("{base_url}/collections/{collection}"))
.send()
.await
.with_context(|| format!("Failed to connect to {host}"))?;
if !resp.status().is_success() {
bail!(
"Failed to read collection '{collection}': {}",
Self::error_message(resp).await
);
}
Ok(resp.json().await?)
}
pub async fn new(host: &str, collection: &str, api_key: Option<&str>) -> Result<Self> {
let base_url = Self::normalize_base_url(host);
let client = Self::make_client(api_key)?;
let resp = client
.get(format!("{base_url}/collections/{collection}"))
.send()
.await
.with_context(|| format!("Failed to connect to {host}"))?;
if !resp.status().is_success() {
bail!(
"Collection '{collection}' not accessible at {host}: {}",
Self::error_message(resp).await
);
}
Ok(Self {
client,
base_url,
collection: collection.to_string(),
})
}
pub async fn list_collections(host: &str, api_key: Option<&str>) -> Result<Vec<String>> {
let base_url = Self::normalize_base_url(host);
let client = Self::make_client(api_key)?;
let resp = client
.get(format!("{base_url}/collections"))
.send()
.await
.with_context(|| format!("Failed to connect to {host}"))?;
if !resp.status().is_success() {
bail!(
"Failed to list collections: {}",
Self::error_message(resp).await
);
}
let body: Value = resp.json().await?;
let names = body["result"]["collections"]
.as_array()
.context("Unexpected /collections response shape")?
.iter()
.filter_map(|v| v["name"].as_str().map(str::to_string))
.collect();
Ok(names)
}
pub async fn get_vector_dimension(
host: &str,
collection: &str,
api_key: Option<&str>,
) -> Result<u64> {
let body = Self::fetch_collection(host, collection, api_key).await?;
vector_dimension_from_collection(&body)
}
pub async fn is_multi_vector(
host: &str,
collection: &str,
api_key: Option<&str>,
) -> Result<bool> {
let body = Self::fetch_collection(host, collection, api_key).await?;
Ok(is_multi_vector_config(&body))
}
pub async fn sample_point_id(
host: &str,
collection: &str,
api_key: Option<&str>,
) -> Result<Option<String>> {
let base_url = Self::normalize_base_url(host);
let client = Self::make_client(api_key)?;
let url = format!("{base_url}/collections/{collection}/points/scroll");
let body = serde_json::json!({ "limit": 1, "with_payload": false });
let resp = client
.post(&url)
.json(&body)
.send()
.await
.with_context(|| format!("Failed to connect to {host}"))?;
if !resp.status().is_success() {
bail!(
"Failed to sample a point from '{collection}': {}",
Self::error_message(resp).await
);
}
let data: Value = resp.json().await?;
let id_val = data["result"]["points"]
.as_array()
.and_then(|pts| pts.first())
.map(|pt| pt["id"].to_string());
Ok(id_val)
}
}
#[async_trait]
impl RagProvider for QdrantProvider {
async fn vector_search(
&self,
embedding: &[f32],
top_k: usize,
min_score: f32,
) -> Result<Vec<(DocumentId, f32)>> {
let url = format!(
"{}/collections/{}/points/search",
self.base_url, self.collection
);
// `score_threshold` is deliberately NOT sent. It is metric-aware: on Cosine
// collections 0.0 means "no floor" as expected, but Euclid collections score
// by negative distance, where 0.0 filters everything out. The attach wizard
// does not pin the distance metric, so filter locally instead.
let body = serde_json::json!({
"vector": embedding,
"limit": top_k,
"with_payload": false,
});
let resp = self.client.post(&url).json(&body).send().await?;
if !resp.status().is_success() {
bail!(
"Qdrant search on '{}' failed: {}",
self.collection,
Self::error_message(resp).await
);
}
let data: Value = resp.json().await?;
let results = data["result"]
.as_array()
.context("Unexpected /points/search response shape")?
.iter()
.filter_map(|pt| {
// String (UUID) IDs yield None here and are dropped. The attach
// wizard rejects such collections up front so this cannot silently
// become "zero results, no error".
let id = pt["id"].as_u64()? as usize;
let score = pt["score"].as_f64()? as f32;
Some((DocumentId(id), score))
})
.filter(|(_, score)| *score > min_score)
.collect();
Ok(results)
}
async fn fetch_content(&self, ids: &[DocumentId]) -> Result<Vec<(DocumentId, String)>> {
if ids.is_empty() {
return Ok(vec![]);
}
let url = format!("{}/collections/{}/points", self.base_url, self.collection);
let id_list: Vec<u64> = ids.iter().map(|d| d.0 as u64).collect();
let body = serde_json::json!({
"ids": id_list,
"with_payload": true,
});
let resp = self.client.post(&url).json(&body).send().await?;
if !resp.status().is_success() {
bail!(
"Qdrant point fetch on '{}' failed: {}",
self.collection,
Self::error_message(resp).await
);
}
let data: Value = resp.json().await?;
let mut rows: Vec<(DocumentId, String)> = data["result"]
.as_array()
.context("Unexpected /points response shape")?
.iter()
.filter_map(|pt| {
let id = pt["id"].as_u64()? as usize;
let text = pt["payload"]["page_content"].as_str()?.to_string();
Some((DocumentId(id), text))
})
.collect();
// `/points` does not guarantee response order matches request order, and the
// caller's RRF ranking is carried by that order. Restore it.
let position: HashMap<DocumentId, usize> =
ids.iter().enumerate().map(|(i, id)| (*id, i)).collect();
rows.sort_by_key(|(id, _)| position.get(id).copied().unwrap_or(usize::MAX));
Ok(rows)
}
async fn rebuild_indexes(&mut self, data: &RagData, _full_rebuild: bool) -> Result<()> {
// Both arms refuse. A silent `Ok(())` would make `.rebuild rag` and
// `.edit rag-docs` look like they worked while writing nothing to the
// remote, leaving the user believing the collection was updated.
if data.attached {
bail!(
"This RAG is attached to an external Qdrant collection. Coyote does not own \
its documents and cannot rebuild it. Manage the collection directly, or \
create a Coyote-owned RAG with `.rag <name>`."
);
}
bail!("Writing to Qdrant is not supported yet (attach-only).");
}
fn duplicate(&self, _data: &RagData) -> Box<dyn RagProvider> {
// Cloning the client shares the connection pool and the injected api-key
// header. Sharing is correct: both handles address the same remote
// collection, and neither of them writes to it.
Box::new(Self {
client: self.client.clone(),
base_url: self.base_url.clone(),
collection: self.collection.clone(),
})
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn error_message_reads_the_object_status_envelope() {
let body =
r#"{"status": {"error": "Wrong input: Not existing vector name error:"}, "time": 0.0}"#;
let msg = format_error_body(StatusCode::BAD_REQUEST, body);
assert!(msg.contains("Not existing vector name"), "got: {msg}");
assert!(
!msg.contains("EOF"),
"must not fall through to a parse error"
);
}
#[test]
fn error_message_survives_the_string_status_and_the_empty_body() {
let ok = format_error_body(StatusCode::OK, r#"{"status": "ok", "time": 0.0}"#);
assert!(
ok.contains("200"),
"no `status.error` present → fall back to status+body: {ok}"
);
let empty = format_error_body(StatusCode::NOT_FOUND, "");
assert!(empty.contains("empty body"), "got: {empty}");
assert!(
empty.contains("verb"),
"the message must point at the likely cause: {empty}"
);
}
#[test]
fn vector_dimension_handles_both_collection_shapes() {
let unnamed = serde_json::json!({
"result": {"config": {"params": {"vectors": {"size": 1536, "distance": "Cosine"}}}}
});
assert_eq!(vector_dimension_from_collection(&unnamed).unwrap(), 1536);
let named = serde_json::json!({
"result": {"config": {"params": {"vectors": {"text": {"size": 768, "distance": "Cosine"}}}}}
});
assert_eq!(vector_dimension_from_collection(&named).unwrap(), 768);
let junk = serde_json::json!({"result": {"config": {"params": {}}}});
assert!(vector_dimension_from_collection(&junk).is_err());
}
#[test]
fn is_multi_vector_rejects_the_named_single_collection() {
let unnamed = serde_json::json!({
"result": {"config": {"params": {"vectors": {"size": 1536, "distance": "Cosine"}}}}
});
assert!(!is_multi_vector_config(&unnamed));
let named_single = serde_json::json!({
"result": {"config": {"params": {"vectors": {"text": {"size": 1536}}}}}
});
assert!(
is_multi_vector_config(&named_single),
"named-single must be rejected too"
);
let named_multi = serde_json::json!({
"result": {"config": {"params": {"vectors": {"text": {"size": 1536}, "image": {"size": 512}}}}}
});
assert!(is_multi_vector_config(&named_multi));
}
#[test]
fn normalize_base_url_only_adds_a_scheme_when_missing() {
assert_eq!(
QdrantProvider::normalize_base_url("qdrant.example.com:6333"),
"http://qdrant.example.com:6333"
);
assert_eq!(
QdrantProvider::normalize_base_url("https://xyz.cloud.qdrant.io"),
"https://xyz.cloud.qdrant.io"
);
assert_eq!(
QdrantProvider::normalize_base_url("http://localhost:6333"),
"http://localhost:6333"
);
}
#[tokio::test]
async fn rebuild_indexes_refuses_for_attached_and_unattached_alike() {
let mut provider = QdrantProvider {
client: Client::new(),
base_url: "http://localhost:6333".to_string(),
collection: "c".to_string(),
};
let attached = RagData {
driver: "qdrant".to_string(),
attached: true,
..Default::default()
};
let err = provider
.rebuild_indexes(&attached, true)
.await
.expect_err("an attached qdrant RAG must never report a successful rebuild");
assert!(err.to_string().contains("cannot rebuild"), "got: {err}");
// `attached: false` is reserved for the (unimplemented) write path. It must
// also refuse: silently succeeding would run a full paid embedding pass and
// then discard every vector.
let owned = RagData {
driver: "qdrant".to_string(),
attached: false,
..Default::default()
};
let err = provider
.rebuild_indexes(&owned, true)
.await
.expect_err("writing to qdrant is unimplemented and must fail loudly");
assert!(err.to_string().contains("not supported yet"), "got: {err}");
}
#[tokio::test]
async fn fetch_content_short_circuits_on_an_empty_id_list() {
let provider = QdrantProvider {
client: Client::new(),
base_url: "http://127.0.0.1:1".to_string(),
collection: "c".to_string(),
};
assert!(provider.fetch_content(&[]).await.unwrap().is_empty());
}
#[tokio::test]
#[ignore]
async fn qdrant_list_collections_requires_running_instance() {
let collections = QdrantProvider::list_collections("http://localhost:6333", None)
.await
.unwrap();
assert!(!collections.is_empty());
}
#[tokio::test]
#[ignore]
async fn qdrant_vector_search_returns_results() {
let provider = QdrantProvider::new("http://localhost:6333", "test-collection", None)
.await
.unwrap();
let embedding = vec![0.0f32; 1536];
let results = provider.vector_search(&embedding, 5, 0.0).await.unwrap();
assert!(results.len() <= 5);
}
}