Feat: update api with props for frontend. Add on frontend validations

Feat: update api with props for frontend. Add on frontend validations…

backend/src/api.py

@@ -1,6 +1,6 @@
 import os
 
-from fastapi import FastAPI, File, UploadFile
+from fastapi import FastAPI, File, Request, UploadFile
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import FileResponse
 
@@ -28,7 +28,7 @@ async def healthcheck():
 
 
 @app.post("/process-audio/", response_model=UploadResponse)
-async def create_upload_file(audio_file: UploadFile = File(..., description="arquivo .mp3 ou .wav")):
+async def create_upload_file(request: Request, audio_file: UploadFile = File(..., description="arquivo .mp3 ou .wav")):
     lang_chain = LangChain(api_key=OPEN_AI_TOKEN)
     service = DeepDive(llm_engine=lang_chain)
     service.validate_api_token()
@@ -40,7 +40,7 @@ async def create_upload_file(audio_file: UploadFile = File(..., description="arq
     response = service.speech_to_text(response)
     response = service.summarize_text(response=response)
     response = service.create_audio_from_summary(response=response)
-    response = service.create_link_to_summary(response=response)
+    response = service.create_link_to_summary(request=request, response=response)
 
     return UploadResponse(**response)
 

backend/src/services/models.py

@@ -5,5 +5,4 @@ class UploadResponse(BaseModel):
     file_id: str
     original_context: str = None
     summary_context: str = None
-    audio_summarize: str = None
     summary_url: str = None

backend/src/services/services.py

@@ -1,7 +1,7 @@
 from uuid import uuid4
 
 import speech_recognition as sr
-from fastapi import UploadFile
+from fastapi import Request, UploadFile
 from gtts import gTTS
 from pydub import AudioSegment as Asegment
 from src.summarization.engines import LangChain
@@ -95,6 +95,7 @@ def create_audio_from_summary(self, response: dict):
             print(f"Erro ao criar arquivo de áudio: {exc}")
             raise
 
-    def create_link_to_summary(self, response: dict):
-        response["summary_url"] = f"/download/{response.get('file_id')}"
+    def create_link_to_summary(self, request: Request, response: dict):
+        base_url = str(request.base_url)
+        response["summary_url"] = f"{base_url}download/{response.get('file_id')}"
         return response

backend/src/settings/development.py

@@ -8,4 +8,4 @@
 }
 
 
-OPEN_AI_TOKEN = "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"
+OPEN_AI_TOKEN = "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"

backend/src/summarization/engines.py

@@ -12,11 +12,11 @@ def __init__(self, api_key: str):
         self.api_key = api_key
 
     def summarize(self, text: str) -> str:
-        prompt = f"Por favor, analise o seguinte texto e crie um resumo breve, \
-                  focando nas ideias principais e informações mais relevantes. \
+        prompt = f"Por favor, analise o seguinte texto e crie um resumo muito breve, \
+                  apenas com as informações mais relevantes. \
                   O resumo deve ser conciso, com poucas palavras, \
                   destacando apenas os aspectos mais importantes do texto. \
-                  Aqui está o texto para análise: :\n\n{text}\n\n Sumário:"
+                  Aqui está o texto para análise: \n\n{text}\n\n Sumário:"
         return self.llm.predict(prompt)
 
     def token_is_valid(self):