Initial Commit

app/api/v1/translate.py

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+from fastapi import APIRouter
+from app.models.translation import TranslationRequest, TranslationResponse
+from app.services.translator import translate_text
+
+router = APIRouter()
+
+@router.post("/", response_model=TranslationResponse)
+async def translate(request: TranslationRequest):
+    translated_text = await translate_text(request.text, request.target_language)
+    return TranslationResponse(translated_text=translated_text)

app/core/config.py

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+import os
+from dotenv import load_dotenv
+
+# Load .env variables
+load_dotenv()
+
+# Read environment variables with defaults
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
+OPENAI_MODEL = os.getenv("OPENAI_MODEL", "gpt-3.5-turbo")
+OPENAI_API_BASE = os.getenv("OPENAI_API_BASE", "https://api.openai.com/v1")

app/core/deepseek_client.py

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+# app/services/openai_service.py
+import openai
+from openai import OpenAI
+from app.core.config import OPENAI_API_KEY, OPENAI_MODEL
+from app.core.config import OPENAI_API_BASE
+
+# Set OpenAI API key from the environment
+openai.api_key = OPENAI_API_KEY
+openai.api_base = OPENAI_API_BASE
+
+print(openai.api_key)
+print(OPENAI_MODEL)
+print(OPENAI_API_BASE)
+
+async def chat_with_openai(messages: list):
+    # Use the model from environment variable or fallback to default
+    model = OPENAI_MODEL
+    client = OpenAI(api_key=openai.api_key, base_url=openai.api_base)
+
+    response = client.chat.completions.create(
+        model="deepseek-chat",  # Or the model you want
+        messages=messages,  # Update this according to the new API syntax
+        max_tokens=100,  # Example parameter
+        stream=False
+    )
+    
+    return response.choices[0].message.content

app/main.py

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+from fastapi import FastAPI
+from app.api.v1 import translate
+
+app = FastAPI()
+
+# Include your routes
+app.include_router(translate.router, prefix="/api/v1/translate", tags=["translate"])

app/models/translation.py

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+from pydantic import BaseModel
+
+class TranslationRequest(BaseModel):
+    text: str
+    target_language: str  # Example: 'id' for Indonesian, 'en' for English, etc.
+
+class TranslationResponse(BaseModel):
+    translated_text: str

app/services/translator.py

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+from app.core.deepseek_client import chat_with_openai
+
+async def translate_text(text: str, target_language: str) -> str:
+    messages = [
+        {"role": "system", "content": f"Translate the following text into {target_language}. Output only the translated text without explanation."},
+        {"role": "user", "content": text},
+    ]
+    translated_text = await chat_with_openai(messages)
+    return translated_text