add list endpoint

Author: ishaan-jaff

README.md

@@ -24,7 +24,20 @@ curl -X POST \
   }'
 ```
 
-### 2. Add Single Embedding to Vector Store
+### 2. List Vector Stores
+```bash
+# List all vector stores
+curl -X GET \
+  http://localhost:8000/v1/vector_stores \
+  -H "Authorization: Bearer your-api-key"
+
+# List with pagination (limit and after parameters)
+curl -X GET \
+  "http://localhost:8000/v1/vector_stores?limit=10&after=vs_abc123" \
+  -H "Authorization: Bearer your-api-key"
+```
+
+### 3. Add Single Embedding to Vector Store
 ```bash
 curl -X POST \
   http://localhost:8000/v1/vector_stores/vs_abc123/embeddings \
@@ -41,7 +54,7 @@ curl -X POST \
   }'
 ```
 
-### 3. Add Multiple Embeddings (Batch)
+### 4. Add Multiple Embeddings (Batch)
 ```bash
 curl -X POST \
   http://localhost:8000/v1/vector_stores/vs_abc123/embeddings/batch \
@@ -63,7 +76,7 @@ curl -X POST \
   }'
 ```
 
-### 4. Search Vector Store
+### 5. Search Vector Store
 ```bash
 curl -X POST \
   http://localhost:8000/v1/vector_stores/vs_abc123/search \
@@ -234,6 +247,28 @@ Any embedding model supported by LiteLLM proxy can be used. Examples:
 }
 ```
 
+### Vector Store List Response
+```json
+{
+  "object": "list",
+  "data": [
+    {
+      "id": "vs_abc123",
+      "object": "vector_store",
+      "created_at": 1699024800,
+      "name": "Support FAQ",
+      "usage_bytes": 1024,
+      "file_counts": {"completed": 5, "total": 5},
+      "status": "completed",
+      "metadata": {}
+    }
+  ],
+  "first_id": "vs_abc123",
+  "last_id": "vs_def456",
+  "has_more": false
+}
+```
+
 ### Search Response
 ```json
 {

main.py

@@ -17,7 +17,8 @@
     EmbeddingCreateRequest,
     EmbeddingResponse,
     EmbeddingBatchCreateRequest,
-    EmbeddingBatchCreateResponse
+    EmbeddingBatchCreateResponse,
+    VectorStoreListResponse
 )
 from config import settings
 from embedding_service import embedding_service
@@ -126,6 +127,95 @@ async def create_vector_store(
         raise HTTPException(status_code=500, detail=f"Failed to create vector store: {str(e)}")
 
 
+@app.get("/v1/vector_stores", response_model=VectorStoreListResponse)
+async def list_vector_stores(
+    limit: Optional[int] = 20,
+    after: Optional[str] = None,
+    before: Optional[str] = None,
+    api_key: str = Depends(get_api_key)
+):
+    """
+    List vector stores with optional pagination.
+    """
+    try:
+        limit = min(limit or 20, 100)  # Cap at 100 results
+        
+        vector_store_table = settings.table_names["vector_stores"]
+        
+        # Build base query
+        base_query = f"""
+        SELECT id, name, file_counts, status, usage_bytes, expires_after, expires_at, last_active_at, metadata,
+               EXTRACT(EPOCH FROM created_at)::bigint as created_at_timestamp
+        FROM {vector_store_table}
+        """
+        
+        # Add pagination conditions
+        conditions = []
+        params = []
+        param_count = 1
+        
+        if after:
+            conditions.append(f"id > ${param_count}")
+            params.append(after)
+            param_count += 1
+            
+        if before:
+            conditions.append(f"id < ${param_count}")
+            params.append(before)
+            param_count += 1
+        
+        if conditions:
+            base_query += " WHERE " + " AND ".join(conditions)
+        
+        # Add ordering and limit
+        final_query = base_query + f" ORDER BY created_at DESC LIMIT {limit + 1}"
+        
+        # Execute query
+        results = await db.query_raw(final_query, *params)
+        
+        # Check if there are more results
+        has_more = len(results) > limit
+        if has_more:
+            results = results[:limit]  # Remove extra result
+        
+        # Convert to response format
+        vector_stores = []
+        for row in results:
+            created_at = int(row["created_at_timestamp"])
+            expires_at = int(row["expires_at"].timestamp()) if row.get("expires_at") else None
+            last_active_at = int(row["last_active_at"].timestamp()) if row.get("last_active_at") else None
+            
+            vector_store = VectorStoreResponse(
+                id=row["id"],
+                created_at=created_at,
+                name=row["name"],
+                usage_bytes=row["usage_bytes"] or 0,
+                file_counts=row["file_counts"] or {"in_progress": 0, "completed": 0, "failed": 0, "cancelled": 0, "total": 0},
+                status=row["status"],
+                expires_after=row["expires_after"],
+                expires_at=expires_at,
+                last_active_at=last_active_at,
+                metadata=row["metadata"]
+            )
+            vector_stores.append(vector_store)
+        
+        # Determine first_id and last_id
+        first_id = vector_stores[0].id if vector_stores else None
+        last_id = vector_stores[-1].id if vector_stores else None
+        
+        return VectorStoreListResponse(
+            data=vector_stores,
+            first_id=first_id,
+            last_id=last_id,
+            has_more=has_more
+        )
+        
+    except Exception as e:
+        import traceback
+        traceback.print_exc()
+        raise HTTPException(status_code=500, detail=f"Failed to list vector stores: {str(e)}")
+
+
 @app.post("/v1/vector_stores/{vector_store_id}/search", response_model=VectorStoreSearchResponse)
 async def search_vector_store(
     vector_store_id: str,

models.py

@@ -67,4 +67,12 @@ class EmbeddingBatchCreateRequest(BaseModel):
 class EmbeddingBatchCreateResponse(BaseModel):
     object: str = "embedding.batch"
     data: List[EmbeddingResponse]
-    created: int 
+    created: int
+
+
+class VectorStoreListResponse(BaseModel):
+    object: str = "list"
+    data: List[VectorStoreResponse]
+    first_id: Optional[str] = None
+    last_id: Optional[str] = None
+    has_more: bool = False