# Parsing NDJSON stream

For example, the endpoint [Agent Graph Invoke ](/agent-graph/agent-graph-api/invoke-stream.md)returns a stream of sequential JSON objects. If you try to parse the raw response as a JSON, it will fail:

```python
import requests
response = requests.post("https://api.connectly.ai/external/v1/ai/agent_graph/invoke", ...)
data = response.json()  # <- fails with JSON parse error
```

This happens because internally we stream the events to allow a smoother user experience.

To properly parse the response, you can use this logic:

```python
import requests
import json

url = "https://api.connectly.ai/external/v1/ai/agent_graph/invoke"
payload = json.dumps(
    {
        "clientKey": "***",
        "businessId": "***",
        "sessionId": "b6bed81c-5fda-486d-b96c-1ff3af36219a",
        "inputEvents": [
            {
                "messageEvent": {
                    "role": "USER",
                    "content": {"textContent": {"text": "Hi"}},
                }
            }
        ],
    }
)
headers = {"Content-Type": "application/json"}
response = requests.request("POST", url, headers=headers, data=payload, stream=True)

for raw_line in response.iter_lines():  # <- parse each line as a JSON
    if raw_line:
        line = raw_line.decode("utf-8")
        data = json.loads(line)
        print(data)
```


---

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Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.connectly.ai/parsing-ndjson-stream.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.