simplify summarize endpoint by removing dynamic length adjustments and setting fixed parameters for summary generation

main.py

@@ -5,47 +5,16 @@ from transformers import pipeline
 app = FastAPI()
 summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 
+
 class TextInput(BaseModel):
     text: str
 
+
 @app.get("/")
 async def root():
     return {"message": "Welcome to the Text Summarization API!"}
 
 @app.post("/summarize")
 async def summarize_text(input: TextInput):
-    # Count approximate number of words (could be improved with tokenizer count in the future)
-    word_count = len(input.text.split())
-    
-
-    if word_count < 50:
-        max_length = max(10, word_count // 2)  
-        min_length = max(3, word_count // 4)   
-    elif word_count < 200:
-        max_length = max(50, word_count // 3)
-        min_length = max(15, word_count // 6)
-    else:
-        max_length = max(100, word_count // 4)
-        min_length = max(30, word_count // 8)
-    
-    # Prevent max_length from being too large (BART has token limits)
-    max_length = min(max_length, 1024)
-    
-    # Generate summary with dynamic parameters
-    summary = summarizer(
-        input.text, 
-        max_length=max_length, 
-        min_length=min_length, 
-        do_sample=True,
-        temperature=0.7,
-        num_beams=4
-    )
-    
-    return {
-        "summary": summary[0]["summary_text"],
-        "parameters_used": {
-            "input_word_count": word_count,
-            "max_length": max_length,
-            "min_length": min_length
-        }
-    }
+    summary = (summarizer(input.text, max_length=200, min_length=30, do_sample=False ))
+    return {"summary": summary[0]['summary_text']}