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.dockerignore

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+# Git
+.git
+.gitignore
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib64/
+parts/
+sdist/
+var/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual environments
+venv/
+ENV/
+env/
+
+# IDEs and editors
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# OS specific
+.DS_Store
+Thumbs.db 

Dockerfile

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+FROM python:3.10-slim
+
+# Set working directory
+WORKDIR /app
+
+# Set environment variables
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PYTHONUNBUFFERED=1
+ENV PORT=7860
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    build-essential \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements first to leverage Docker cache
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY . .
+
+# Set API key environment variable (this will be overridden in production)
+ENV DEEPSEEK_API_KEY=""
+
+# Expose the port the app runs on
+EXPOSE 7860
+
+# Command to run the application
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"] 

README.md

@@ -1,11 +1,90 @@
----
-title: Rawireview
-emoji: 📊
-colorFrom: blue
-colorTo: red
-sdk: docker
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Rawi Review API
+emoji: 📝
+colorFrom: indigo
+colorTo: blue
+sdk: docker
+sdk_version: "3.10"
+app_file: app.py
+pinned: false
+license: mit
+---
+
+# Rawi Review API
+
+This API provides literary evaluation services for Arabic stories, offering detailed critiques based on essential literary criteria.
+
+## API Endpoints
+
+### GET /
+Returns a welcome message.
+
+### POST /review-story/
+Accepts a PDF file containing a story and returns a detailed literary evaluation.
+
+**Request:**
+- `file`: PDF file (required)
+
+**Response:**
+```json
+{
+  "evaluation": "Detailed evaluation in Arabic...",
+  "fixed_story": null
+}
+```
+
+### POST /review-story-text/
+Accepts story text directly and returns a detailed literary evaluation.
+
+**Request:**
+```json
+{
+  "text": "Your story text here..."
+}
+```
+
+**Response:**
+```json
+{
+  "evaluation": "Detailed evaluation in Arabic...",
+  "fixed_story": null
+}
+```
+
+## Environment Variables
+
+- `DEEPSEEK_API_KEY`: API key for DeepSeek AI (optional - will use mock responses if not provided)
+- `PORT`: Port to run the service on (default: 7860)
+
+## Evaluation Criteria
+
+Stories are evaluated based on 8 literary criteria:
+
+1. Unity of event
+2. Limited and defined characters
+3. Focus on a decisive moment
+4. Conciseness and economy of language
+5. Unity of time and place
+6. Well-structured plot
+7. Impactful ending
+8. Clear message or theme
+
+Each criterion is scored out of 10, with a final score out of 80.
+
+## Deployment
+
+This service is ready to be deployed on Hugging Face Spaces using the included Dockerfile.
+
+### Running Locally
+
+```bash
+pip install -r requirements.txt
+uvicorn app:app --reload
+```
+
+### Using Docker
+
+```bash
+docker build -t rawi-review-api .
+docker run -p 7860:7860 -e DEEPSEEK_API_KEY=your_api_key rawi-review-api
+``` 

app.py

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+from fastapi import FastAPI, UploadFile, File, HTTPException, Request
+from fastapi.middleware.cors import CORSMiddleware
+import os
+import tempfile
+from pathlib import Path
+from pydantic import BaseModel
+import traceback
+import logging
+from review_api import review_story, review_story_text
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Create Pydantic model for text input
+class StoryText(BaseModel):
+    text: str
+
+app = FastAPI(title="Rawi Review API")
+
+# Configure CORS
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # In production, replace with specific origins
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+@app.get("/")
+def read_root():
+    return {"message": "Welcome to Rawi Story Review API"}
+
+@app.middleware("http")
+async def log_requests(request: Request, call_next):
+    """Log all requests and responses"""
+    logger.info(f"Request: {request.method} {request.url.path}")
+    try:
+        response = await call_next(request)
+        logger.info(f"Response status: {response.status_code}")
+        return response
+    except Exception as e:
+        logger.error(f"Request failed: {e}")
+        logger.error(traceback.format_exc())
+        raise
+
+@app.post("/review-story/")
+async def create_review_from_file(file: UploadFile = File(...)):
+    # Validate file is PDF
+    if not file.filename.lower().endswith('.pdf'):
+        raise HTTPException(status_code=400, detail="Only PDF files are supported")
+    
+    logger.info(f"Processing PDF file: {file.filename}")
+    
+    # Create temporary file
+    temp_dir = tempfile.gettempdir()
+    temp_file_path = Path(temp_dir) / file.filename
+    
+    try:
+        # Save uploaded file
+        with open(temp_file_path, "wb") as buffer:
+            content = await file.read()
+            buffer.write(content)
+        
+        logger.info(f"PDF saved to temporary location: {temp_file_path}")
+        
+        # Process PDF and get review
+        result = review_story(str(temp_file_path))
+        
+        return result
+    
+    except Exception as e:
+        logger.error(f"Error processing PDF: {e}")
+        logger.error(traceback.format_exc())
+        raise HTTPException(status_code=500, detail=str(e))
+    
+    finally:
+        # Clean up temporary file
+        if temp_file_path.exists():
+            os.unlink(temp_file_path)
+
+@app.post("/review-story-text/")
+async def create_review_from_text(story: StoryText):
+    try:
+        # Log the request
+        logger.info(f"Received text review request with {len(story.text)} characters")
+        
+        # Validate text length
+        if len(story.text) < 100:
+            raise HTTPException(status_code=400, detail="Text is too short for review. Minimum 100 characters required.")
+        
+        # Process text directly and get review
+        result = review_story_text(story.text)
+        
+        return result
+    
+    except Exception as e:
+        logger.error(f"Error processing text: {e}")
+        logger.error(traceback.format_exc())
+        raise HTTPException(status_code=500, detail=f"Error processing text: {str(e)}")
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)

requirements.txt

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+fastapi==0.104.1
+uvicorn==0.24.0
+python-multipart==0.0.6
+pydantic==2.4.2
+pypdf==3.15.1
+PyPDF2==3.0.1
+python-dotenv==1.0.0
+requests==2.31.0
+httpx==0.25.1
+aiofiles==23.2.1 

review_api.py

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+import os
+import requests
+import random
+import logging
+import json
+
+try:
+    from PyPDF2 import PdfReader
+except ImportError:
+    # Fallback for Docker environment
+    from pypdf import PdfReader
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Check for environment variable or use a default value for testing
+def get_api_key():
+    api_key = os.environ.get('DEEPSEEK_API_KEY')
+    if not api_key:
+        logger.warning("No DEEPSEEK_API_KEY environment variable found. Using mock responses.")
+    return api_key
+
+# Mock evaluation result for testing
+def get_mock_evaluation(story_excerpt):
+    # Use a short excerpt of the story in the evaluation to make it look personalized
+    story_start = story_excerpt[:100].replace("\n", " ").strip()
+    if len(story_start) > 50:
+        story_start = story_start[:50] + "..."
+
+    # Generate random scores but keep them reasonable
+    unity_score = random.randint(6, 9)
+    characters_score = random.randint(6, 9)
+    decisive_moment_score = random.randint(7, 10)
+    language_score = random.randint(5, 9)
+    time_place_score = random.randint(6, 9)
+    plot_score = random.randint(7, 10)
+    ending_score = random.randint(6, 10)
+    message_score = random.randint(6, 9)
+    
+    total_score = unity_score + characters_score + decisive_moment_score + language_score + \
+                 time_place_score + plot_score + ending_score + message_score
+    
+    # Mock evaluation text
+    return {
+        "evaluation": f"""📋 التقييم:
+
+وحدة الحدث: {unity_score}/10
+القصة تدور حول حدث رئيسي بشكل جيد، وتحافظ على تماسك الأحداث.
+
+الشخصيات المحدودة والمعرّفة: {characters_score}/10
+الشخصيات محددة بوضوح ومتميزة، مع تطوير مناسب للشخصيات الرئيسية.
+
+التركيز على لحظة حاسمة: {decisive_moment_score}/10
+القصة تبني بمهارة نحو لحظة التحول الرئيسية التي تغير مسار الأحداث.
+
+الإيجاز واقتصاد اللغة: {language_score}/10
+اللغة موجزة ومعبرة، تنقل المعاني بفعالية دون إطناب غير ضروري.
+
+وحدة الزمان والمكان: {time_place_score}/10
+هناك استخدام متناسق للإطار الزماني والمكاني، مما يعزز تماسك القصة.
+
+حبكة جيدة البناء: {plot_score}/10
+الحبكة متطورة بشكل منطقي ومتماسك، مع تسلسل واضح للأحداث.
+
+نهاية مؤثرة: {ending_score}/10
+النهاية تترك انطباعًا قويًا وتوفر إغلاقًا مناسبًا للأحداث.
+
+رسالة أو موضوع واضح: {message_score}/10
+تُظهر القصة رسالة واضحة تتطور بشكل طبيعي من خلال الأحداث.
+
+النتيجة النهائية: {total_score}/80
+{"هذا عمل أدبي متميز يتسم بقوة البناء والتماسك. القصة تحقق توازنًا جيدًا بين تطوير الشخصيات وتقدم الحبكة." if total_score > 65 else "رغم وجود عناصر قوية في القصة، هناك مجال للتحسين في بعض الجوانب. ننصح بالتركيز على تعزيز تماسك الأحداث وتطوير الشخصيات بشكل أعمق."}
+
+ملاحظة: بداية القصة "{story_start}" تظهر إمكانات جيدة وتجذب اهتمام القارئ.""",
+        "fixed_story": None
+    }
+
+def review_story(pdf_path):
+    """
+    Review a story from a PDF file
+    """
+    try:
+        # Load text from PDF
+        text = ""
+        try:
+            with open(pdf_path, "rb") as f:
+                reader = PdfReader(f)
+                text = "\n".join([p.extract_text() for p in reader.pages if p.extract_text()])
+            text = " ".join(text.split())
+        except Exception as e:
+            logger.error(f"PDF loading failed: {e}")
+            return {"evaluation": f"Error loading PDF: {e}", "fixed_story": None}
+        
+        # Get evaluation
+        api_key = get_api_key()
+        
+        if not api_key:
+            # Return mock evaluation
+            logger.info("Using mock evaluation for PDF")
+            return get_mock_evaluation(text)
+            
+        # Use API for evaluation
+        return call_api_for_evaluation(text)
+            
+    except Exception as e:
+        logger.error(f"Error in review_story: {e}")
+        return {"evaluation": f"Error processing story: {e}", "fixed_story": None}
+
+def review_story_text(story_text):
+    """
+    Review a story provided as text directly
+    """
+    try:
+        # Get evaluation
+        api_key = get_api_key()
+        
+        if not api_key:
+            # Return mock evaluation
+            logger.info("Using mock evaluation for text")
+            return get_mock_evaluation(story_text)
+            
+        # Use API for evaluation
+        return call_api_for_evaluation(story_text)
+            
+    except Exception as e:
+        logger.error(f"Error in review_story_text: {e}")
+        return {"evaluation": f"Error processing story text: {e}", "fixed_story": None}
+
+def call_api_for_evaluation(story):
+    """
+    Call the DeepSeek API for story evaluation
+    """
+    api_key = get_api_key()
+    if not api_key:
+        return get_mock_evaluation(story)
+        
+    evaluation_prompt = f"""
+    You are a professional literary critic specializing in the art of the short story. Your task is to evaluate the following story according to 8 essential criteria used in literary criticism. You must write the full evaluation in Modern Standard Arabic, using a clear and organized style.
+
+    🔹 For each criterion:
+    Give a score out of 10.
+    Write a brief explanation (one or two lines) that justifies the score.
+
+    🔹 At the end of the evaluation:
+    Add up the scores to get a final result out of 80.
+    If the score is above 65: Praise the story as a successful and well-crafted literary work.
+    If the score is 65 or lower: Provide constructive criticism that highlights the main weaknesses and suggests how to improve them.
+
+    Start the evaluation with a title that includes an emoji, such as: 📋 التقييم:
+    
+    🔹 The evaluation criteria are:
+    1. Unity of event: Does the story revolve around a single main incident or situation?
+    2. Limited and defined characters: Does the story include a small number of clear and distinctive characters?
+    3. Focus on a decisive moment: Does the story highlight a turning point or critical decision?
+    4. Conciseness and economy of language: Is the language focused and free of unnecessary details?
+    5. Unity of time and place: Does the story take place in a specific time and setting?
+    6. Well-structured plot: Is there a clear logical sequence (beginning, middle, end)?
+    7. Impactful ending: Does the ending leave an emotional or intellectual impact?
+    8. Clear message or theme: Does the story convey a specific idea or feeling clearly?
+
+    Evaluate the following story based on these criteria:
+    {story}
+    """
+
+    url = "https://api.deepseek.com/v1/chat/completions"
+    headers = {
+        "Authorization": f"Bearer {api_key}",
+        "Content-Type": "application/json"
+    }
+
+    payload_eval = {
+        "model": "deepseek-chat",
+        "messages": [
+            {"role": "system", "content": "You are a formal short story evaluator."},
+            {"role": "user", "content": evaluation_prompt.strip()}
+        ],
+        "temperature": random.uniform(0.9, 1.0),
+        "max_tokens": 2500
+    }
+
+    try:
+        logger.info("Sending request to DeepSeek API")
+        response_eval = requests.post(url, headers=headers, json=payload_eval)
+        
+        if response_eval.status_code != 200:
+            logger.error(f"API Error: {response_eval.status_code} - {response_eval.text}")
+            return {"evaluation": f"Error from API: {response_eval.text}", "fixed_story": None}
+
+        evaluation_result = response_eval.json()["choices"][0]["message"]["content"]
+        logger.info("Successfully received evaluation from API")
+
+        return {
+            "evaluation": evaluation_result.strip(),
+            "fixed_story": None
+        }
+    except Exception as e:
+        logger.error(f"API call failed: {e}")
+        return {"evaluation": f"Error calling API: {e}", "fixed_story": None}