Refactor tokenize endpoint to use Pydantic model for request validation and update README.md examples to reflect changes in API usage

README.md

@@ -15,9 +15,10 @@ A simple API for tokenizing text using spaCy.
 
 ### Using curl
 ```bash
-curl -X POST "https://theirstory-tokenizer.hf.space:7860/tokenize" \
+curl -X POST "https://theirstory-tokenizer.hf.space/tokenize" \
      -H "Content-Type: application/json" \
-     -d '{"text": "Hello world!"}'
+     -H "accept: application/json" \
+     -d '{"text": "Hello world"}'
 ```
 
 ### Using Python
@@ -25,8 +26,9 @@ curl -X POST "https://theirstory-tokenizer.hf.space:7860/tokenize" \
 import requests
 
 response = requests.post(
-    "https://theirstory-tokenizer.hf.space:7860/tokenize",
-    json={"text": "Hello world!"}
+    "https://theirstory-tokenizer.hf.space/tokenize",
+    json={"text": "Hello world"},
+    headers={"accept": "application/json"}
 )
 tokens = response.json()
 print(tokens)
@@ -34,13 +36,14 @@ print(tokens)
 
 ### Using JavaScript
 ```javascript
-const response = await fetch('https://theirstory-tokenizer.hf.space:7860/tokenize', {
+const response = await fetch('https://theirstory-tokenizer.hf.space/tokenize', {
     method: 'POST',
     headers: {
         'Content-Type': 'application/json',
+        'accept': 'application/json'
     },
     body: JSON.stringify({
-        text: 'Hello world!'
+        text: 'Hello world'
     })
 });
 const tokens = await response.json();

app.py

@@ -1,12 +1,16 @@
 from fastapi import FastAPI
+from pydantic import BaseModel
 import spacy
 
 app = FastAPI()
 nlp = spacy.blank("en")
 
+class TokenizeRequest(BaseModel):
+    text: str
+
 @app.post("/tokenize")
-async def tokenize_text(text: str):
-    doc = nlp(text)
+async def tokenize_text(request: TokenizeRequest):
+    doc = nlp(request.text)
     tokens = []
     for token in doc:
         tokens.append({

requirements.txt

@@ -1,4 +1,5 @@
 fastapi
 uvicorn[standard]
 supervision
-spacy
+spacy
+pydantic