Create app.py

app.py

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+import os
+from fastapi import FastAPI, File, Form, HTTPException
+from fastapi.responses import JSONResponse
+from pydantic import BaseModel
+from groq import Groq
+import io
+
+# Set up the Groq client
+os.environ["GROQ_API_KEY"] = os.getenv("GROQ_API_KEY")
+client = Groq(api_key=os.environ["GROQ_API_KEY"])
+
+app = FastAPI()
+
+# Pydantic model for the transcription result
+class TranscriptionResponse(BaseModel):
+    transcription: str
+
+class FeedbackResponse(BaseModel):
+    grammar_feedback: str
+    vocabulary_feedback: str
+    grammar_score: int
+    vocabulary_score: int
+
+@app.get("/")
+async def index():
+    return {"message": "Welcome to the Audio Transcription API!"}
+
+@app.post("/transcribe")
+async def transcribe_audio(audio_data: bytes = File(...), language: str = Form(...)):
+    try:
+        # Transcribe the audio based on the selected language
+        transcription = client.audio.transcriptions.create(
+            file=("audio.wav", audio_data),
+            model="whisper-large-v3",
+            prompt="Transcribe the audio accurately based on the selected language.",
+            response_format="text",
+            language=language,
+        )
+        return JSONResponse(content=TranscriptionResponse(transcription=transcription).dict())
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.post("/check_grammar")
+async def check_grammar(transcription: str = Form(...), language: str = Form(...)):
+    if not transcription or not language:
+        raise HTTPException(status_code=400, detail="Missing transcription or language selection")
+
+    try:
+        # Grammar check
+        grammar_prompt = (
+            f"Briefly check the grammar of the following text in {language}: {transcription}. "
+            "Identify any word that does not belong to the selected language and flag it. Based on the number of incorrect words, "
+            "also check the grammar deeply and carefully. Provide a score from 1 to 10 based on the grammar accuracy, reducing points for incorrect words, "
+            "and make sure to output the score on a new line after two line breaks like \"SCORE=\"."
+        )
+
+        grammar_check_response = client.chat.completions.create(
+            model="llama3-groq-70b-8192-tool-use-preview",
+            messages=[{"role": "user", "content": grammar_prompt}]
+        )
+        grammar_feedback = grammar_check_response.choices[0].message.content.strip()
+
+        # Vocabulary check
+        vocabulary_prompt = (
+            f"Check the vocabulary accuracy of the following text in {language}: {transcription}. "
+            "Identify any word that does not belong to the selected language and flag it. Based on the number of incorrect words, "
+            "also check the grammar deeply and carefully. Provide a score from 1 to 10 based on the vocabulary accuracy, reducing points for incorrect words, "
+            "and make sure to output the score on a new line after two line breaks like \"SCORE=\"."
+        )
+
+        vocabulary_check_response = client.chat.completions.create(
+            model="llama-3.1-70b-versatile",
+            messages=[{"role": "user", "content": vocabulary_prompt}]
+        )
+        vocabulary_feedback = vocabulary_check_response.choices[0].message.content.strip()
+
+        # Calculate scores from feedback
+        grammar_score = calculate_score(grammar_feedback)
+        vocabulary_score = calculate_score(vocabulary_feedback)
+
+        return JSONResponse(content=FeedbackResponse(
+            grammar_feedback=grammar_feedback,
+            vocabulary_feedback=vocabulary_feedback,
+            grammar_score=grammar_score,
+            vocabulary_score=vocabulary_score
+        ).dict())
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+def calculate_score(feedback):
+    """
+    Calculate score based on feedback content. 
+    This function searches for the keyword 'SCORE=' or similar variations 
+    (SCORE:, score:, etc.) and extracts the score value.
+    """
+    import re
+    match = re.search(r'(SCORE=|score=|SCORE:|score:|SCORE = )\s*(\d+)', feedback)
+    
+    if match:
+        # Extract and return the score as an integer
+        return int(match.group(2))
+    
+    # Return a default score of 0 if no score is found in the feedback
+    return 0