updated /predict description

app.py

@@ -61,14 +61,23 @@ async def index():
 @app.post("/predict", tags=["Machine Learning"])
 async def predict(predictionFeatures: PredictionFeatures):
     """
-    Predicts whether the provided text contains hate speech.
-    The input is a string with the sentence to be predicted
+    Predict whether the provided text contains hate speech.
 
-    The return is a dictionnary with  : 
-    * the prediction : "offensive" or "not offensive"
-    * the probability : A number between 0 and 1. The higher the bigger the probability for hate speech. The threshold for the prediction is at 0.5
+    ### Input
+    - `predictionFeatures` (PredictionFeatures): An object containing the text to be analyzed.
+      - The input text is provided as a string.
 
-    Use the following request to use it  : 
+    ### Output
+    Returns a dictionary with the following keys:
+    - `prediction` (str): Indicates whether the text is "offensive" or "not offensive".
+    - `probability` (float): A value between 0 and 1, representing the likelihood of hate speech.
+      - Texts with a probability >= 0.5 are classified as "offensive".
+
+    ### Example Usage
+    To use this endpoint, send a POST request as follows:
+
+    ```python
+    import requests
 
     url = "https://llepogam-hate-speech-detection-api.hf.space/predict"
     headers = {
@@ -76,11 +85,13 @@ async def predict(predictionFeatures: PredictionFeatures):
         "Content-Type": "application/json"
     }
 
-    Text_to_predict = {
-        "Text": text
+    data = {
+        "Text": "your text here"
     }
 
-
+    response = requests.post(url, headers=headers, json=data)
+    print(response.json())
+    ```
     """
 
     # Convert input into a DataFrame