Add and prepare rust worker management system for file information processing and knowledge base framework

rust-engine/src/vector_db.rs

@@ -0,0 +1,87 @@
+use anyhow::Result;
+use reqwest::Client;
+use serde_json::json;
+use serde::Deserialize;
+
+#[derive(Clone)]
+pub struct QdrantClient {
+    base: String,
+    client: Client,
+}
+
+impl QdrantClient {
+    pub fn new(base: &str) -> Self {
+        Self {
+            base: base.trim_end_matches('/').to_string(),
+            client: Client::new(),
+        }
+    }
+
+    /// Upsert a point into collection `files` with id and vector
+    pub async fn upsert_point(&self, id: &str, vector: Vec<f32>) -> Result<()> {
+        let url = format!("{}/collections/files/points", self.base);
+        let body = json!({
+            "points": [{
+                "id": id,
+                "vector": vector,
+                "payload": {"type": "file"}
+            }]
+        });
+
+        let resp = self.client.post(&url).json(&body).send().await?;
+        let status = resp.status();
+        if status.is_success() {
+            Ok(())
+        } else {
+            let t = resp.text().await.unwrap_or_default();
+            Err(anyhow::anyhow!("qdrant upsert failed: {} - {}", status, t))
+        }
+    }
+
+    /// Ensure the 'files' collection exists with the given dimension and distance metric
+    pub async fn ensure_files_collection(&self, dim: usize) -> Result<()> {
+        let url = format!("{}/collections/files", self.base);
+        let body = json!({
+            "vectors": {"size": dim, "distance": "Cosine"}
+        });
+        let resp = self.client.put(&url).json(&body).send().await?;
+        // 200 OK or 201 Created means ready; 409 Conflict means already exists
+        if resp.status().is_success() || resp.status().as_u16() == 409 {
+            Ok(())
+        } else {
+            let status = resp.status();
+            let t = resp.text().await.unwrap_or_default();
+            Err(anyhow::anyhow!("qdrant ensure collection failed: {} - {}", status, t))
+        }
+    }
+
+    /// Search top-k nearest points from 'files'
+    pub async fn search_top_k(&self, vector: Vec<f32>, k: usize) -> Result<Vec<String>> {
+        let url = format!("{}/collections/files/points/search", self.base);
+        let body = json!({
+            "vector": vector,
+            "limit": k
+        });
+        let resp = self.client.post(&url).json(&body).send().await?;
+        let status = resp.status();
+        if !status.is_success() {
+            let t = resp.text().await.unwrap_or_default();
+            return Err(anyhow::anyhow!("qdrant search failed: {} - {}", status, t));
+        }
+        #[derive(Deserialize)]
+        struct Hit { id: serde_json::Value }
+        #[derive(Deserialize)]
+        struct Data { result: Vec<Hit> }
+        let data: Data = resp.json().await?;
+        let mut ids = Vec::new();
+        for h in data.result {
+            // id can be string or number; handle string
+            if let Some(s) = h.id.as_str() {
+                ids.push(s.to_string());
+            } else {
+                ids.push(h.id.to_string());
+            }
+        }
+        Ok(ids)
+    }
+}