How to Make a POST Request to an External API in a flow

[peterjacksonwonka]

Hi.
I'm in need of some guidance on how to execute a POST request to an external API within a LangFlow flow.
Could you provide me with the steps?
Could you advise me on which component would be best to use for making a POST request to an external API within a LangFlow flow?
Thank you for your support

[dosubot[bot]]

Hey @peterjacksonwonka! Great to see you back. Hope you're doing well.

To make a POST request to an external API within a LangFlow flow, you can use the PostRequest component. Here are the steps you can follow:

1. Instantiate the PostRequest Component: First, you need to create an instance of the PostRequest component. This component is specifically designed to make POST requests to a given URL with optional headers.

from langchain_core.documents import Document
post_request_component = PostRequest()

2. Prepare the Document: Make sure you have a Document object or a list of Document objects that you want to send in the POST request. The Document should contain the data you wish to send in its page_content.

document = Document(page_content="Your request data here")

3. Set the URL and Headers: Define the URL to which the POST request should be made. Optionally, you can also define headers as a dictionary if the API requires them.

url = "https://example.com/api/endpoint"
headers = {"Content-Type": "application/json"}

4. Call the build Method: Use the build method of the PostRequest component, passing the Document (or list of Document objects), the URL, and optionally the headers. The build method will handle the creation of a session, making the POST request(s), and returning the response(s) as Document object(s).

response_documents = post_request_component.build(document, url, headers=headers)

5. Handle the Response: The build method returns a list of Document objects containing the responses from the API. Each Document in the list will have its page_content set to the response from the API, and its metadata will include the original request URL, headers, and the status code.

for response_document in response_documents:
    print(response_document.page_content)  # The API response
    print(response_document.metadata)  # Additional metadata including the status code

This example demonstrates how to use the PostRequest component to make a POST request to an external API, handle headers, and process the response. You can find more details about the PostRequest component in the source code.

Please note that the build method in the PostRequest component accepts a Document or a list of Document objects, a URL string, and an optional dictionary of headers. It returns a list of Document objects containing the responses from the API.

I hope this helps! If you have any more questions, feel free to ask.

Sources

• src/backend/langflow/components/utilities/PostRequest.py

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[peterjacksonwonka]

@dusobot
There is no component called 'postrequest.'
There is only 'requestposttool.'
Why can't I see it?
The langflow version is 0.6.7

[LIJUN-XU]

hello, could you tell me how to use parameters about document . i want to use user input word as param. Then Adding some props(eg:{query: input word, fetchCount:5,page:4}). last , the object as request's body send http request. if you could tell me ,appreciate it. 🙏

[vinz-deloitte]

hi, i face the same issue with posting a call to external api, i can use post request component, but how do you manage the trigger. in my case, i need to call the post request component, once the chat conversation ends and the summary of this conversation needs to be passed as body to the external api .. im finding it hard to figure out the triggering part. any help would be highly appreciated.

[Cristhianzl]

Hi! 👋

We are using other channels as our official means of communication with users. We apologize for the delayed response.
For faster assistance, please direct your questions to our Discord channel or open a GitHub issue, as we are much more active on these platforms.

Langflow Discord Server

Thank you for your understanding.

Best regards,
The Langflow Team