trying fast api again

app.py

@@ -1,6 +1,8 @@
-import gradio as gr
+from fastapi import FastAPI
+from pydantic import BaseModel
 from transformers import pipeline
 from typing import Dict, Any
+import uvicorn
 
 INTENT_MODEL = "rasouzadev/medgo-intent-classifier"
 HATE_MODEL = "unitary/unbiased-toxic-roberta"
@@ -8,7 +10,19 @@ HATE_MODEL = "unitary/unbiased-toxic-roberta"
 print("Loading pipelines (this may take a minute)...")
 
 intent_pipe = pipeline("text-classification", model=INTENT_MODEL, truncation=True)
-hate_pipe = pipeline("text-classification", model=HATE_MODEL, truncation=True, return_all_scores=True)
+hate_pipe = pipeline("text-classification", model=HATE_MODEL, truncation=True, top_k=None)
+
+app = FastAPI(title="MedGo - Intent & Hate Detector API")
+
+class InputText(BaseModel):
+    text: str
+
+class PredictionResponse(BaseModel):
+    intent: str
+    intent_score: float
+    hate_label: str | None
+    hate_score: float
+    note: str | None
 
 def unify_scores(pipe_output):
     if not pipe_output:
@@ -17,10 +31,25 @@ def unify_scores(pipe_output):
         return pipe_output[0]
     return pipe_output
 
-def classify(text: str) -> Dict[str, Any]:
-    """
-    Classifica o texto e detecta hate speech
-    """
+@app.get("/")
+def root():
+    return {
+        "message": "MedGo API - Intent & Hate Detector",
+        "endpoints": {
+            "predict": "/predict",
+            "health": "/health",
+            "docs": "/docs"
+        }
+    }
+
+@app.get("/health")
+def health():
+    return {"status": "ok"}
+
+@app.post("/predict", response_model=PredictionResponse)
+def classify(input_data: InputText) -> Dict[str, Any]:
+    text = input_data.text
+
     hate_raw = hate_pipe(text)
     hate_scores = unify_scores(hate_raw)
     best_hate = max(hate_scores, key=lambda x: x.get("score", 0.0), default=None)
@@ -51,32 +80,5 @@ def classify(text: str) -> Dict[str, Any]:
         "note": None
     }
 
-with gr.Blocks(title="MedGo - Intent & Hate Detector API") as demo:
-    gr.Markdown("# MedGo - Intent & Hate Detector API")
-    gr.Markdown("API para classificação de intenção e detecção de hate speech")
-    
-    with gr.Row():
-        with gr.Column():
-            text_input = gr.Textbox(
-                label="Texto para classificar", 
-                placeholder="Digite o texto aqui...",
-                lines=3
-            )
-            submit_btn = gr.Button("Classificar", variant="primary")
-        
-        with gr.Column():
-            output_json = gr.JSON(label="Resultado")
-    
-    gr.Examples(
-        examples=[
-            ["Preciso marcar uma consulta"],
-            ["Qual é o horário de atendimento?"],
-            ["Você é um idiota!"],
-        ],
-        inputs=text_input
-    )
-    
-    submit_btn.click(fn=classify, inputs=text_input, outputs=output_json, api_name="predict")
-
 if __name__ == "__main__":
-    demo.launch()
+    uvicorn.run(app, host="0.0.0.0", port=7860)