haystack

Source#

• Repository: deepset-ai/haystack
• Last source update: 2026-08-09
• Last verified: 2026-08-09

Tags#

Integration notes#

Repository is focused on tool/server interoperability; wrap in bounded worker contracts for production use.

worker.md example#

Starter worker.md contract mapped from this registry entry. Copy this file and adapt schemas, constraints, and statuses for your task.

---
id: haystack-repo-derived-worker
name: haystack Repo-Derived Worker
version: 1.0.0
source_registry_url: https://worker.md/registry/haystack/
source_repository: https://github.com/deepset-ai/haystack
repository_default_branch: main
repository_language: Python
repository_license: Apache-2.0
repository_updated_at: 2026-08-09
worker_mode: agent-orchestration-worker
derivation_method: github_repository_metadata_plus_raw_readme
derivation_confidence: 0.95
derived_on: 2026-08-09
tags:
  - agent-framework
  - agentic-ai
  - agentic-rag
  - agents
  - ai
  - ai-agents
---

# haystack Repo-Derived Worker

## Repo-derived summary
- Registry summary: Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing...
- Repository description: Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
- Stars (snapshot): 26,150
- Primary language: Python
- Worker mode classification: agent-orchestration-worker

## Extracted from
- https://github.com/deepset-ai/haystack
- https://github.com/deepset-ai/haystack/blob/main/README.md
- https://github.com/deepset-ai/haystack/actions/workflows/tests.yml/badge.svg
- https://raw.githubusercontent.com/deepset-ai/haystack/python-coverage-comment-action-data/badge.svg
- https://img.shields.io/website?label=documentation&up_message=online&url=https%3A%2F%2Fdocs.haystack.deepset.ai

## Evidence notes (from repository text)
- README summary paragraph: ### Read the announcement https://haystack.deepset.ai/blog/haystack-3-release!
- https://haystack.deepset.ai/ is an open-source AI orchestration framework for building production-ready LLM applications in Python.
- One `Pipeline` runs synchronously or asynchronously and streams token by token. `Agent` can run concurrent tool calls.

## Installation hints found in README
- `pip install haystack-ai`
- `pip install --pre haystack-ai`

## worker.md contract (derived starter)
Purpose: Execute one orchestrated agent task as a bounded worker step.

### Input schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "run_id",
    "task",
    "context"
  ],
  "properties": {
    "run_id": {
      "type": "string"
    },
    "task": {
      "type": "string"
    },
    "context": {
      "type": "object"
    }
  }
}
```

### Output schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "run_id",
    "status",
    "result"
  ],
  "properties": {
    "run_id": {
      "type": "string"
    },
    "status": {
      "type": "string",
      "enum": [
        "ok",
        "retryable_error",
        "invalid_request",
        "invalid_output"
      ]
    },
    "result": {
      "type": "object"
    }
  }
}
```

### Constraints
- timeout_seconds: 30
- max_attempts: 2
- idempotency_key: run_id
- status_enum: [ok, retryable_error, invalid_request, invalid_output]
- notes: adapt to concrete APIs/classes documented in this repository before production use

## How this should be used
1. Treat this file as a repo-derived starter profile, not a claim of an official repository API contract.
2. Replace schemas with exact interfaces from code/docs you adopt.
3. Keep execution bounded and auditable using worker protocol constraints.

How to use#

• Save this as a worker spec file (for example: haystack-my-task.worker.md).
• Replace the input/output schemas and purpose with your real bounded task.
• Enforce schema validation + timeout + retry policy in your runtime before production use.

Citation#

Reference URL: https://worker.md/registry/haystack/

Source URL: https://github.com/deepset-ai/haystack