# Running Pipelines
Execute deployed pipelines via CLI, HTTP API, or programmatically.
## Quick Reference
=== "HayhooksCLI"
```bash
hayhooks pipeline run my_pipeline --param 'query="What is Haystack?"'
```
=== "Hayhooks HTTP API"
```bash
curl -X POST http://localhost:1416/my_pipeline/run \
-H 'Content-Type: application/json' \
-d '{"query":"What is Haystack?"}'
```
=== "Python"
```python
import requests
resp = requests.post(
"http://localhost:1416/my_pipeline/run",
json={"query": "What is Haystack?"}
)
print(resp.json())
```
=== "Async Python"
```python
import httpx
import asyncio
async def main():
async with httpx.AsyncClient() as client:
r = await client.post(
"http://localhost:1416/my_pipeline/run",
json={"query": "What is Haystack?"}
)
print(r.json())
asyncio.run(main())
```
=== "OpenAI Chat Completion (`curl`)"
```bash
curl -X POST http://localhost:1416/v1/chat/completions \
-H 'Content-Type: application/json' \
-d '{
"model": "my_pipeline",
"messages": [{"role": "user", "content": "What is Haystack?"}]
}'
```
=== "Open WebUI"
See [Open WebUI Integration](../features/openwebui-integration.md) for setup details.
For more CLI examples, see [CLI Commands](../features/cli-commands.md).
## File Uploads
### CLI
```bash
# Single file
hayhooks pipeline run my_pipeline --file document.pdf --param 'query="Summarize"'
# Multiple files
hayhooks pipeline run my_pipeline --file doc1.pdf --file doc2.txt
# Directory
hayhooks pipeline run my_pipeline --dir ./documents
```
### HTTP
```bash
curl -X POST http://localhost:1416/my_pipeline/run \
-F 'files=@document.pdf' \
-F 'query="Summarize this document"'
```
See [File Upload Support](../features/file-upload-support.md) for implementation details.
## Python Integration
### Requests
```python
import requests
resp = requests.post(
"http://localhost:1416/my_pipeline/run",
json={"query": "What is Haystack?"}
)
print(resp.json())
```
### Async (httpx)
```python
import httpx
import asyncio
async def main():
async with httpx.AsyncClient() as client:
r = await client.post(
"http://localhost:1416/my_pipeline/run",
json={"query": "What is Haystack?"}
)
print(r.json())
asyncio.run(main())
```
## Streaming
Implement `run_chat_completion` or `run_chat_completion_async` in your wrapper. See [OpenAI Compatibility](../features/openai-compatibility.md) for details.
## Error Handling & Retry Logic
```python
import requests
from requests.exceptions import RequestException
import time
def run_with_retry(pipeline_name, params, max_retries=3):
url = f"http://localhost:1416/{pipeline_name}/run"
for attempt in range(max_retries):
try:
response = requests.post(url, json=params)
response.raise_for_status()
return response.json()
except RequestException as e:
if attempt == max_retries - 1:
raise
time.sleep(2 ** attempt) # Exponential backoff
```
## Logging
Add logging to your pipeline wrappers:
```python
from hayhooks import log
class PipelineWrapper(BasePipelineWrapper):
def run_api(self, query: str) -> str:
log.info("Processing query: {}", query)
result = self.pipeline.run({"prompt": {"query": query}})
log.info("Pipeline completed")
return result["llm"]["replies"][0]
```
See [Logging Reference](../reference/logging.md) for details.
## Next Steps
- [CLI Commands](../features/cli-commands.md) - Complete CLI reference
- [Examples](../examples/overview.md) - Working examples
