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Overview

Wait for all queued semantic processing and vectorization tasks to complete. This ensures that resources and skills are fully processed and indexed before you query them.
After adding resources or skills, OpenViking processes them asynchronously. Use this method to wait for completion before searching or retrieving content.

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Method Signature

client.wait_processed(
    timeout: Optional[float] = None
) -> Dict[str, Any]

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Parameters

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timeout
float
Maximum time to wait in seconds. If not provided, waits indefinitely until all processing completes.

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Response

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semantic_queue
object
Status of the semantic processing queue (L0/L1 generation)
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vector_queue
object
Status of the vectorization queue

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Examples

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Basic Usage

import openviking as ov

client = ov.OpenViking(path="./data")
client.initialize()

# Add resource without waiting
result = client.add_resource("./docs/guide.md")

# Wait for processing to complete
status = client.wait_processed()
print(f"Processed: {status['semantic_queue']['processed']} items")

{
  "status": "ok",
  "result": {
    "semantic_queue": {
      "processed": 12,
      "error_count": 0,
      "errors": []
    },
    "vector_queue": {
      "processed": 12,
      "error_count": 0,
      "errors": []
    }
  },
  "time": 2.4
}

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With Timeout

try:
    status = client.wait_processed(timeout=30.0)
    print("Processing complete!")
except Exception as e:
    print(f"Timeout or error: {e}")

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Batch Processing Pattern

# Add multiple resources without waiting
files = [
    "./docs/intro.md",
    "./docs/api.md",
    "./docs/examples.md"
]

for file in files:
    client.add_resource(file, wait=False)
    print(f"Queued: {file}")

# Wait for all to complete
print("Waiting for processing...")
status = client.wait_processed()

print(f"✓ Processed {status['semantic_queue']['processed']} items")
if status['semantic_queue']['error_count'] > 0:
    print(f"⚠ Errors: {status['semantic_queue']['errors']}")

# Add resource and wait
client.add_resource(
    "https://raw.githubusercontent.com/volcengine/OpenViking/refs/heads/main/README.md",
    wait=False
)

# Wait for processing
client.wait_processed()

# Now safe to search
results = client.find("what is openviking")
for r in results.resources:
    print(f"Found: {r.uri} (score: {r.score:.4f})")

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Processing Queues

OpenViking uses two asynchronous queues for resource processing:

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1. Semantic Queue

Processes resources to generate:
  • L0 (Abstract): High-level summary of the resource
  • L1 (Overview): Detailed overview with key points

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2. Vector Queue

Indexes resources for semantic search:
  • Generates embeddings for content chunks
  • Stores vectors in the vector database
  • Enables semantic similarity search
Both queues must complete before resources are fully searchable.

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Best Practices

Use wait_processed() when:
  • You need to search resources immediately after adding them
  • You’re adding resources in a script or initialization phase
  • You need to verify processing completed successfully
  • You’re running tests that depend on resource availability
For better performance when adding multiple resources:
# Add all resources first (fast)
for resource in resources:
    client.add_resource(resource, wait=False)

# Wait once for all to complete
client.wait_processed()
This is more efficient than waiting after each individual resource.
Set appropriate timeouts based on resource size:
  • Small files (< 1MB): 10-30 seconds
  • Medium files (1-100MB): 1-5 minutes
  • Large files or directories: 5-30 minutes
try:
    client.wait_processed(timeout=300.0)  # 5 minutes
except TimeoutError:
    # Handle timeout - processing continues in background
    print("Still processing, check back later")
Check for processing errors:
status = client.wait_processed()

if status['semantic_queue']['error_count'] > 0:
    for error in status['semantic_queue']['errors']:
        print(f"Error: {error['message']}")

if status['vector_queue']['error_count'] > 0:
    for error in status['vector_queue']['errors']:
        print(f"Vectorization error: {error['message']}")

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Response Examples

{
  "status": "ok",
  "result": {
    "semantic_queue": {
      "processed": 15,
      "error_count": 0,
      "errors": []
    },
    "vector_queue": {
      "processed": 15,
      "error_count": 0,
      "errors": []
    }
  },
  "time": 3.2
}
  • add_resource - Add resources (supports wait parameter)
  • add_skill - Add skills (supports wait parameter)
  • find - Search resources after processing
  • abstract - Get L0 abstract (requires processing)
  • overview - Get L1 overview (requires processing)