Create app.py

app.py

@@ -0,0 +1,516 @@
+from fastapi import FastAPI, HTTPException, UploadFile, File, Form, Depends
+from typing import Optional
+from fastapi.responses import StreamingResponse, JSONResponse, HTMLResponse
+from fastapi.staticfiles import StaticFiles
+from fastapi.templating import Jinja2Templates
+from huggingface_hub import InferenceClient
+from pydantic import BaseModel, ConfigDict
+import os
+from base64 import b64encode
+from io import BytesIO
+from PIL import Image, ImageEnhance
+import logging
+import pytesseract
+import time
+
+# Set Tesseract CMD path for Windows
+pytesseract.pytesseract.tesseract_cmd = r"F:\Python-files\tesseract\tesseract.exe"
+
+app = FastAPI()
+
+# Configure logging
+logging.basicConfig(level=logging.DEBUG)
+logger = logging.getLogger(__name__)
+
+
+# Default model
+DEFAULT_MODEL = "meta-llama/Meta-Llama-3-8B-Instruct"
+
+# Initialize Jinja2 templates
+templates = Jinja2Templates(directory="templates")
+
+class TextRequest(BaseModel):
+    model_config = ConfigDict(protected_namespaces=())
+    query: str
+    stream: bool = False
+    model_name: Optional[str] = None
+
+class ImageTextRequest(BaseModel):
+    model_config = ConfigDict(protected_namespaces=())
+    query: str
+    stream: bool = False
+    model_name: Optional[str] = None
+    
+    @classmethod
+    def as_form(
+        cls,
+        query: str = Form(...),
+        stream: bool = Form(False),
+        model_name: Optional[str] = Form(None),
+        image: UploadFile = File(...)  # Make image required for i2t2t
+    ):
+        return cls(
+            query=query,
+            stream=stream,
+            model_name=model_name
+        ), image
+
+def get_client(model_name: Optional[str] = None):
+    """Get inference client for specified model or default model"""
+    try:
+        model_path = model_name if model_name and model_name.strip() else DEFAULT_MODEL
+        return InferenceClient(
+            model=model_path
+        )
+    except Exception as e:
+        raise HTTPException(
+            status_code=400, 
+            detail=f"Error initializing model {model_path}: {str(e)}"
+        )
+
+def generate_text_response(query: str, model_name: Optional[str] = None):
+    messages = [{
+        "role": "user",
+        "content": f"[SYSTEM] You are ASSISTANT who answer question asked by user in short and concise manner. [USER] {query}"
+    }]
+
+    try:
+        client = get_client(model_name)
+        for message in client.chat_completion(
+            messages,
+            max_tokens=2048,
+            stream=True
+        ):
+            token = message.choices[0].delta.content
+            yield token
+    except Exception as e:
+        yield f"Error generating response: {str(e)}"
+
+def generate_image_text_response(query: str, image_data: str, model_name: Optional[str] = None):
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": f"[SYSTEM] You are ASSISTANT who answer question asked by user in short and concise manner. [USER] {query}"},
+                {"type": "image_url", "image_url": {"url": f"data:image/*;base64,{image_data}"}}
+            ]
+        }
+    ]
+    
+    logger.debug(f"Messages sent to API: {messages}")
+    
+    try:
+        client = get_client(model_name)
+        for message in client.chat_completion(messages, max_tokens=2048, stream=True):
+            logger.debug(f"Received message chunk: {message}")
+            token = message.choices[0].delta.content
+            yield token
+    except Exception as e:
+        logger.error(f"Error in generate_image_text_response: {str(e)}")
+        yield f"Error generating response: {str(e)}"
+
+def preprocess_image(img):
+    """Enhance image for better OCR results"""
+    # Convert to grayscale
+    img = img.convert('L')
+    
+    # Enhance contrast
+    enhancer = ImageEnhance.Contrast(img)
+    img = enhancer.enhance(2.0)
+    
+    # Enhance sharpness
+    enhancer = ImageEnhance.Sharpness(img)
+    img = enhancer.enhance(1.5)
+    
+    return img
+
+@app.get("/")
+async def root():
+    return {"message": "Welcome to FastAPI server!"}
+
+@app.post("/t2t")
+async def text_to_text(request: TextRequest):
+    try:
+        if request.stream:
+            return StreamingResponse(
+                generate_text_response(request.query, request.model_name),
+                media_type="text/event-stream"
+            )
+        else:
+            response = ""
+            for chunk in generate_text_response(request.query, request.model_name):
+                response += chunk
+            return {"response": response}
+    except Exception as e:
+        logger.error(f"Error in /t2t endpoint: {str(e)}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.post("/i2t2t")
+async def image_text_to_text(form_data: tuple[ImageTextRequest, UploadFile] = Depends(ImageTextRequest.as_form)):
+    form, image = form_data
+    try:
+        # Process image
+        contents = await image.read()
+        try:
+            logger.debug("Attempting to open image")
+            img = Image.open(BytesIO(contents))
+            if img.mode != 'RGB':
+                img = img.convert('RGB')
+            
+            buffer = BytesIO()
+            img.save(buffer, format="PNG")
+            image_data = b64encode(buffer.getvalue()).decode('utf-8')
+            logger.debug("Image processed and encoded to base64")
+        except Exception as img_error:
+            logger.error(f"Error processing image: {str(img_error)}")
+            raise HTTPException(
+                status_code=422,
+                detail=f"Error processing image: {str(img_error)}"
+            )
+        
+        if form.stream:
+            return StreamingResponse(
+                generate_image_text_response(form.query, image_data, form.model_name),
+                media_type="text/event-stream"
+            )
+        else:
+            response = ""
+            for chunk in generate_image_text_response(form.query, image_data, form.model_name):
+                response += chunk
+            return {"response": response}
+    except Exception as e:
+        logger.error(f"Error in /i2t2t endpoint: {str(e)}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.post("/tes")
+async def ocr_endpoint(image: UploadFile = File(...)):
+    try:
+        # Read and process the image
+        contents = await image.read()
+        img = Image.open(BytesIO(contents))
+        
+        # Preprocess the image
+        img = preprocess_image(img)
+        
+        # Perform OCR with timeout and retries
+        max_retries = 3
+        text = ""
+        
+        for attempt in range(max_retries):
+            try:
+                text = pytesseract.image_to_string(
+                    img,
+                    timeout=30,  # 30 second timeout
+                    config='--oem 3 --psm 6'
+                )
+                break
+            except Exception as e:
+                if attempt == max_retries - 1:
+                    raise HTTPException(
+                        status_code=500,
+                        detail=f"Error extracting text: {str(e)}"
+                    )
+                time.sleep(1)  # Wait before retry
+        
+        return {"text": text}
+        
+    except Exception as e:
+        raise HTTPException(
+            status_code=500,
+            detail=f"Error processing image: {str(e)}"
+        )
+
+@app.get("/docs/guide", response_class=HTMLResponse)
+async def api_guide():
+    html_content = '''
+    <!DOCTYPE html>
+    <html lang="en">
+    <head>
+        <meta charset="UTF-8">
+        <meta name="viewport" content="width=device-width, initial-scale=1.0">
+        <title>API Documentation</title>
+        <link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/tailwind.min.css" rel="stylesheet">
+        <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/prism/1.24.1/themes/prism-tomorrow.min.css">
+        <style>
+            .copy-button {
+                position: absolute;
+                top: 8px;
+                right: 8px;
+                padding: 4px 8px;
+                background: #2d3748;
+                border: 1px solid #4a5568;
+                border-radius: 4px;
+                color: #cbd5e0;
+                font-size: 12px;
+                cursor: pointer;
+                transition: all 0.2s;
+            }
+            .copy-button:hover {
+                background: #4a5568;
+            }
+            .code-block {
+                position: relative;
+                margin: 1rem 0;
+            }
+            .endpoint-card {
+                background: #1a202c;
+                border-radius: 8px;
+                margin-bottom: 2rem;
+                padding: 1.5rem;
+            }
+            .language-tab {
+                cursor: pointer;
+                padding: 0.5rem 1rem;
+                border-radius: 4px 4px 0 0;
+            }
+            .language-tab.active {
+                background: #2d3748;
+                color: #fff;
+            }
+        </style>
+    </head>
+    <body class="bg-gray-900 text-gray-100 min-h-screen p-8">
+        <div class="max-w-6xl mx-auto">
+            <h1 class="text-4xl font-bold mb-8">API Documentation</h1>
+            
+            <!-- T2T Endpoint -->
+            <div class="endpoint-card">
+                <h2 class="text-2xl font-semibold mb-4">Text-to-Text Endpoint</h2>
+                <p class="mb-4 text-gray-400">Endpoint for general text queries</p>
+                <p class="mb-2 text-gray-300"><span class="font-mono bg-gray-800 px-2 py-1 rounded">POST /t2t</span></p>
+                
+                <div class="code-block">
+                    <div class="flex mb-2">
+                        <div class="language-tab active" data-lang="curl">cURL</div>
+                        <div class="language-tab" data-lang="python">Python</div>
+                        <div class="language-tab" data-lang="javascript">JavaScript</div>
+                        <div class="language-tab" data-lang="node">Node.js</div>
+                    </div>
+                    <pre><code class="language-bash">curl -X POST "http://localhost:8000/t2t" \
+-H "Content-Type: application/json" \
+-d '{"query": "What is FastAPI?", "stream": false}'</code></pre>
+                    <button class="copy-button">Copy</button>
+                </div>
+            </div>
+
+            <!-- I2T2T Endpoint -->
+            <div class="endpoint-card">
+                <h2 class="text-2xl font-semibold mb-4">Image and Text to Text Endpoint</h2>
+                <p class="mb-4 text-gray-400">Endpoint for queries about images</p>
+                <p class="mb-2 text-gray-300"><span class="font-mono bg-gray-800 px-2 py-1 rounded">POST /i2t2t</span></p>
+                
+                <div class="code-block">
+                    <div class="flex mb-2">
+                        <div class="language-tab active" data-lang="curl">cURL</div>
+                        <div class="language-tab" data-lang="python">Python</div>
+                        <div class="language-tab" data-lang="javascript">JavaScript</div>
+                        <div class="language-tab" data-lang="node">Node.js</div>
+                    </div>
+                    <pre><code class="language-bash">curl -X POST "http://localhost:8000/i2t2t" \
+-F "query=Describe this image" \
+-F "stream=false" \
+-F "image=@/path/to/your/image.jpg"</code></pre>
+                    <button class="copy-button">Copy</button>
+                </div>
+            </div>
+
+            <!-- TES Endpoint -->
+            <div class="endpoint-card">
+                <h2 class="text-2xl font-semibold mb-4">OCR Endpoint</h2>
+                <p class="mb-4 text-gray-400">Extract text from images using OCR</p>
+                <p class="mb-2 text-gray-300"><span class="font-mono bg-gray-800 px-2 py-1 rounded">POST /tes</span></p>
+                
+                <div class="code-block">
+                    <div class="flex mb-2">
+                        <div class="language-tab active" data-lang="curl">cURL</div>
+                        <div class="language-tab" data-lang="python">Python</div>
+                        <div class="language-tab" data-lang="javascript">JavaScript</div>
+                        <div class="language-tab" data-lang="node">Node.js</div>
+                    </div>
+                    <pre><code class="language-bash">curl -X POST "http://localhost:8000/tes" \
+-F "image=@/path/to/your/image.jpg"</code></pre>
+                    <button class="copy-button">Copy</button>
+                </div>
+            </div>
+        </div>
+
+        <script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.24.1/prism.min.js"></script>
+        <script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.24.1/components/prism-python.min.js"></script>
+        <script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.24.1/components/prism-javascript.min.js"></script>
+        <script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.24.1/components/prism-bash.min.js"></script>
+        <script>
+            const codeExamples = {
+                't2t': {
+                    'curl': `curl -X POST "http://localhost:8000/t2t" \\
+-H "Content-Type: application/json" \\
+-d '{"query": "What is FastAPI?", "stream": false}'`,
+                    'python': `import requests
+
+url = "http://localhost:8000/t2t"
+payload = {
+    "query": "What is FastAPI?",
+    "stream": False
+}
+response = requests.post(url, json=payload)
+print(response.json())`,
+                    'javascript': `// Using fetch
+fetch("http://localhost:8000/t2t", {
+    method: "POST",
+    headers: {
+        "Content-Type": "application/json",
+    },
+    body: JSON.stringify({
+        query: "What is FastAPI?",
+        stream: false
+    })
+})
+.then(response => response.json())
+.then(data => console.log(data));`,
+                    'node': `const axios = require('axios');
+
+async function makeRequest() {
+    try {
+        const response = await axios.post('http://localhost:8000/t2t', {
+            query: "What is FastAPI?",
+            stream: false
+        });
+        console.log(response.data);
+    } catch (error) {
+        console.error(error);
+    }
+}
+
+makeRequest();`
+                },
+                'i2t2t': {
+                    'curl': `curl -X POST "http://localhost:8000/i2t2t" \\
+-F "query=Describe this image" \\
+-F "stream=false" \\
+-F "image=@/path/to/your/image.jpg"`,
+                    'python': `import requests
+
+url = "http://localhost:8000/i2t2t"
+files = {
+    'image': ('image.jpg', open('path/to/image.jpg', 'rb')),
+}
+data = {
+    'query': 'Describe this image',
+    'stream': 'false'
+}
+response = requests.post(url, files=files, data=data)
+print(response.json())`,
+                    'javascript': `const formData = new FormData();
+formData.append('image', imageFile);
+formData.append('query', 'Describe this image');
+formData.append('stream', 'false');
+
+fetch("http://localhost:8000/i2t2t", {
+    method: "POST",
+    body: formData
+})
+.then(response => response.json())
+.then(data => console.log(data));`,
+                    'node': `const axios = require('axios');
+const FormData = require('form-data');
+const fs = require('fs');
+
+async function makeRequest() {
+    try {
+        const formData = new FormData();
+        formData.append('image', fs.createReadStream('path/to/image.jpg'));
+        formData.append('query', 'Describe this image');
+        formData.append('stream', 'false');
+
+        const response = await axios.post('http://localhost:8000/i2t2t', formData, {
+            headers: formData.getHeaders()
+        });
+        console.log(response.data);
+    } catch (error) {
+        console.error(error);
+    }
+}
+
+makeRequest();`
+                },
+                'tes': {
+                    'curl': `curl -X POST "http://localhost:8000/tes" \\
+-F "image=@/path/to/your/image.jpg"`,
+                    'python': `import requests
+
+url = "http://localhost:8000/tes"
+files = {
+    'image': ('image.jpg', open('path/to/image.jpg', 'rb'))
+}
+response = requests.post(url, files=files)
+print(response.json())`,
+                    'javascript': `const formData = new FormData();
+formData.append('image', imageFile);
+
+fetch("http://localhost:8000/tes", {
+    method: "POST",
+    body: formData
+})
+.then(response => response.json())
+.then(data => console.log(data));`,
+                    'node': `const axios = require('axios');
+const FormData = require('form-data');
+const fs = require('fs');
+
+async function makeRequest() {
+    try {
+        const formData = new FormData();
+        formData.append('image', fs.createReadStream('path/to/image.jpg'));
+
+        const response = await axios.post('http://localhost:8000/tes', formData, {
+            headers: formData.getHeaders()
+        });
+        console.log(response.data);
+    } catch (error) {
+        console.error(error);
+    }
+}
+
+makeRequest();`
+                }
+            };
+
+            // Handle language tab switching
+            document.querySelectorAll('.language-tab').forEach(tab => {
+                tab.addEventListener('click', () => {
+                    const lang = tab.dataset.lang;
+                    const codeBlock = tab.closest('.endpoint-card');
+                    const endpoint = codeBlock.querySelector('h2').textContent.toLowerCase().includes('ocr') ? 'tes' : 
+                                   codeBlock.querySelector('h2').textContent.toLowerCase().includes('image') ? 'i2t2t' : 't2t';
+                    
+                    // Update active tab
+                    codeBlock.querySelectorAll('.language-tab').forEach(t => t.classList.remove('active'));
+                    tab.classList.add('active');
+                    
+                    // Update code content
+                    const code = codeBlock.querySelector('code');
+                    code.textContent = codeExamples[endpoint][lang];
+                    code.className = `language-${lang === 'curl' ? 'bash' : lang}`;
+                    Prism.highlightElement(code);
+                });
+            });
+
+            // Handle copy buttons
+            document.querySelectorAll('.copy-button').forEach(button => {
+                button.addEventListener('click', () => {
+                    const code = button.previousElementSibling.textContent;
+                    navigator.clipboard.writeText(code);
+                    
+                    // Show feedback
+                    const originalText = button.textContent;
+                    button.textContent = 'Copied!';
+                    setTimeout(() => {
+                        button.textContent = originalText;
+                    }, 2000);
+                });
+            });
+        </script>
+    </body>
+    </html>
+    '''
+    return HTMLResponse(content=html_content)
+