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Dockerfile

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+# read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.9
+
+RUN useradd -m -u 1000 user
+
+WORKDIR /app
+
+COPY --chown=user ./requirements.txt requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+COPY --chown=user . /app
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI, Request
+from fastapi.responses import PlainTextResponse
+import requests
+
+app = FastAPI()
+
+# Dicionário para armazenar o histórico de conversas
+conversation_histories = {}
+
+API_URL = "https://fabiosantos-ia.hf.space/api/v1/prediction/a953ea1b-ee34-4ae3-9b25-b82c814dd871"
+
+def query(payload):
+    response = requests.post(API_URL, json=payload) #envia a pergunta pelo url da api para a IA
+    return response.json() #guarda a resposta
+
+@app.post("/whatsapp") #endpoint do twilio
+async def reply_whatsapp(request: Request): #recebe a mensagem do usuario
+    form = await request.form()
+    incoming_msg = form.get('Body', '').lower() #guarda a mensagem do usuario
+    from_number = form.get('From')
+    
+    print(incoming_msg)
+    print(from_number)
+
+    # Get the user's conversation history, if it exists
+    user_history = conversation_histories.get(from_number, [])
+
+    output = query({
+        "question": incoming_msg, #leva o que usuario falou para IA pela função query
+    })
+                                
+    
+    return PlainTextResponse(output['text'], status_code=200)

requirements.txt

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+fastapi
+uvicorn[standard]
+twilio