Repository: gradio-app/gradio
Pull request: Use updated component in `postprocess()`
This fixes: https://github.com/gradio-app/gradio/issues/7382 but if this fix is correct, I don't know how anything was working before. It seems we were using the original component instead of the updated component when running `.postprocess()`

Am I missing something @aliabid94 @freddyaboulton?

In particular, it seems like the example below was working on `main` (no error was being raised when submitting the `Number` component), but I don't see how it could have been working since we were using the old `Number` component internally so the old value of `minimum` should have raised an error:

```py
import gradio as gr

def update_number_minimum():
  d2 = gr.Number(minimum=0)
  return d2

with gr.Blocks() as iface:
    number = gr.Number(minimum=10)
    number2 = gr.Number()
    number.submit(lambda x:x, number, number2)
    iface.load(update_number_minimum, None, number)

iface.launch()
```

Problem statement:
Setting Dropdown value to an updated (but valid) choice produces warning
### Describe the bug

# The bug is as follows
#A dropdown object is filled with a list
# a hidden Textbox is filled with a string variable of the first list item in the dropbox to carry over the variable. It is also filled if the dropdown selects another variable from the list. One could use a statev. I use a hidden textbox.
# When this process is reversed the warning message appears. Even converting the textbox. value to string does not help.
# A warning is given that the new string transferred from the textbox is not in the dropdown list
# "UserWarning: The value passed into gr.Dropdown() is not in the list of choices. Please update the list of choices to include: Option 1 or set allow_custom_value=True."
#When printing out the type of the textbox and the dropdown, both are 'str'.

### Have you searched existing issues?  🔎

- [X] I have searched and found no existing issues

### Reproduction

```python
import gradio as gr

# Define choices for the dropdown
my_choices = ["Option 1", "Option 2", "Option 3"]


def select_first_value(dummy_var):
  # This function sets the first value found in the sub_dirs Dropdown
  selected_dropdown=dummy_var
  #print("selected_sub_dir:", selected_sub_dir)
  return selected_dropdown 

def Update_variable_textbox(dropdown_list):
  # A dummy textbox is used to pass variables between events.
  # This function updates the dummy textbox. One can also use the State gradio option
  selected_list_item=dropdown_list
  return selected_list_item 

def update_Dropdown_choices():
  # This function updates the choices of a Dropdown object
  d2 = gr.Dropdown(my_choices)
  return d2

with gr.Blocks() as iface:
   
    # Create and populate Dropdown  
    dropdown_list = gr.Dropdown(label="list", choices=[],interactive=True)
    # Create dummy hidden textbox to transfer variables globally
    dummy_var=gr.Textbox(value="", visible=True)
    #button to start all
    my_btn=gr.Button(value="Start")

    my_btn.click(update_Dropdown_choices,None,dropdown_list)
    dummy_var.change(select_first_value,dummy_var,dropdown_list)

    # If a different value is selected update dummy textbox: sub_dirs_first_choice
    dropdown_list.change(Update_variable_textbox,dropdown_list,dummy_var)



iface.launch()

```


### Screenshot

_No response_

### Logs

```shell
NO Logs
```


### System Info

```shell
Linux mint 21.2, Visual Studio. Python 10, conda, 
Gradio Environment Information:
------------------------------
Operating System: Linux
gradio version: 4.16.0
gradio_client version: 0.8.1

------------------------------------------------
gradio dependencies in your environment:

aiofiles: 23.2.1
altair: 5.2.0
fastapi: 0.109.0
ffmpy: 0.3.1
gradio-client==0.8.1 is not installed.
httpx: 0.26.0
huggingface-hub: 0.20.3
importlib-resources: 6.1.1
jinja2: 3.1.3
markupsafe: 2.1.4
matplotlib: 3.8.2
numpy: 1.26.3
orjson: 3.9.12
packaging: 23.2
pandas: 2.2.0
pillow: 10.2.0
pydantic: 2.5.3
pydub: 0.25.1
python-multipart: 0.0.6
pyyaml: 6.0.1
ruff: 0.1.14
semantic-version: 2.10.0
tomlkit==0.12.0 is not installed.
typer: 0.9.0
typing-extensions: 4.9.0
uvicorn: 0.27.0
authlib; extra == 'oauth' is not installed.
itsdangerous; extra == 'oauth' is not installed.


gradio_client dependencies in your environment:

fsspec: 2023.12.2
httpx: 0.26.0
huggingface-hub: 0.20.3
packaging: 23.2
typing-extensions: 4.9.0
websockets: 11.0.3
```


### Severity

I can work around it

Hints from issue discussion:
I've been wracking my brains over this issue @DRomatzki. Providing a simpler repro as I continue to look into it:

```py
import gradio as gr

# Define choices for the dropdown
my_choices = ["Option 1", "Option 2", "Option 3"]


def update_dropdown_choices():
  d2 = gr.Dropdown(choices=my_choices)
  print(d2.choices)
  return d2

with gr.Blocks() as iface:
    dropdown = gr.Dropdown(label="list", choices=[], interactive=True)
    textbox = gr.Textbox(value="")

    textbox.submit(lambda x:x, textbox, dropdown)
    dropdown.change(lambda x:x, dropdown, textbox)

    iface.load(update_dropdown_choices, None, dropdown)


iface.launch()
```

Commit message: lint

Patch to review:
diff --git a/.changeset/blue-walls-flash.md b/.changeset/blue-walls-flash.md
new file mode 100644
index 0000000000..d08fb044c1
--- /dev/null
+++ b/.changeset/blue-walls-flash.md
@@ -0,0 +1,5 @@
+---
+"gradio": patch
+---
+
+fix:Use updated component in `postprocess()`
diff --git a/gradio/blocks.py b/gradio/blocks.py
index d73bca17b3..489a2ec0d5 100644
--- a/gradio/blocks.py
+++ b/gradio/blocks.py
@@ -1449,7 +1449,10 @@ def postprocess_data(
                         raise InvalidComponentError(
                             f"{block.__class__} Component with id {output_id} not a valid output component."
                         )
+                    if output_id in state:
+                        block = state[output_id]
                     prediction_value = block.postprocess(prediction_value)
+
                 outputs_cached = processing_utils.move_files_to_cache(
                     prediction_value,
                     block,  # type: ignore
diff --git a/test/test_blocks.py b/test/test_blocks.py
index 0c7eb6374e..8eea228427 100644
--- a/test/test_blocks.py
+++ b/test/test_blocks.py
@@ -823,6 +823,31 @@ def run(min, num):
             "error" not in session_1.json()
         )  # no error because sesssion 1 block config was lost when session 3 was added
 
+    def test_state_holder_is_used_in_postprocess(self):
+        with gr.Blocks() as demo:
+            dropdown = gr.Dropdown(label="list", choices=["Choice 1"], interactive=True)
+            button = gr.Button("Get dropdown value")
+            button2 = gr.Button("Convert dropdown to multiselect")
+            button.click(lambda x: x, inputs=dropdown, outputs=dropdown)
+            button2.click(lambda: gr.Dropdown(multiselect=True), outputs=dropdown)
+
+        app, _, _ = demo.launch(prevent_thread_lock=True)
+        client = TestClient(app)
+
+        response = client.post(
+            "/api/predict/",
+            json={"data": ["Choice 1"], "session_hash": "1", "fn_index": 0},
+        )
+        assert response.json()["data"][0] == "Choice 1"
+        response = client.post(
+            "/api/predict/", json={"data": [], "session_hash": "1", "fn_index": 1}
+        )
+        response = client.post(
+            "/api/predict/",
+            json={"data": ["Choice 1"], "session_hash": "1", "fn_index": 0},
+        )
+        assert response.json()["data"][0] == ["Choice 1"]
+
 
 class TestCallFunction:
     @pytest.mark.asyncio


Code review comments:
diff_hunk: @@ -823,6 +823,31 @@ def run(min, num):
             "error" not in session_1.json()
         )  # no error because sesssion 1 block config was lost when session 3 was added
 
+    def test_state_holder_is_used_in_postprocess(self):
path: test/test_blocks.py
text: @user1:
Looks good! Just wondering why we can't use the connect context manager here.

@author:
Good point, I had forgotten about that -- will refactor