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app.py

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+import gradio as gr
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import warnings
+import json
+import re
+import ast
+from typing import List, Dict, Any
+warnings.filterwarnings("ignore")
+
+# F-1 Model Configuration
+MODEL_NAME = "Sheikh-F1/F1"
+FALLBACK_MODEL = "microsoft/DialoGPT-medium"
+
+class F1MultilingualCoder:
+    """F-1 Multilingual Coding Assistant"""
+    
+    def __init__(self):
+        self.model = None
+        self.tokenizer = None
+        self.device = "cuda" if torch.cuda.is_available() else "cpu"
+        self.model_loaded = False
+        
+        # Multilingual code templates
+        self.code_templates = {
+            "factorial": {
+                "en": "def factorial(n):\n    if n <= 1:\n        return 1\n    return n * factorial(n-1)",
+                "bn": "def factorial(n):\n    if n <= 1:\n        return 1\n    return n * factorial(n-1)",
+                "banglish": "def factorial(n):\n    if n <= 1:\n        return 1\n    return n * factorial(n-1)"
+            },
+            "fibonacci": {
+                "en": "def fibonacci(n):\n    if n <= 1:\n        return n\n    return fibonacci(n-1) + fibonacci(n-2)",
+                "bn": "def fibonacci(n):\n    if n <= 1:\n        return n\n    return fibonacci(n-1) + fibonacci(n-2)",
+                "banglish": "def fibonacci(n):\n    if n <= 1:\n        return n\n    return fibonacci(n-1) + fibonacci(n-2)"
+            },
+            "binary_search": {
+                "en": "def binary_search(arr, target):\n    left, right = 0, len(arr) - 1\n    while left <= right:\n        mid = (left + right) // 2\n        if arr[mid] == target:\n            return mid\n        elif arr[mid] < target:\n            left = mid + 1\n        else:\n            right = mid - 1\n    return -1",
+                "bn": "def binary_search(arr, target):\n    left, right = 0, len(arr) - 1\n    while left <= right:\n        mid = (left + right) // 2\n        if arr[mid] == target:\n            return mid\n        elif arr[mid] < target:\n            left = mid + 1\n        else:\n            right = mid - 1\n    return -1",
+                "banglish": "def binary_search(arr, target):\n    left, right = 0, len(arr) - 1\n    while left <= right:\n        mid = (left + right) // 2\n        if arr[mid] == target:\n            return mid\n        elif arr[mid] < target:\n            left = mid + 1\n        else:\n            right = mid - 1\n    return -1"
+            }
+        }
+    
+    def load_model(self):
+        """Load F-1 model with fallback"""
+        try:
+            print("Loading F-1 model...")
+            self.tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, padding_side="left")
+            self.model = AutoModelForCausalLM.from_pretrained(MODEL_NAME).to(self.device)
+            
+            if self.tokenizer.pad_token is None:
+                self.tokenizer.pad_token = self.tokenizer.eos_token
+                
+            self.model_loaded = True
+            print("F-1 model loaded successfully!")
+            return True
+            
+        except Exception as e:
+            print(f"F-1 model failed to load: {e}")
+            print("Loading fallback model...")
+            try:
+                self.tokenizer = AutoTokenizer.from_pretrained(FALLBACK_MODEL, padding_side="left")
+                self.model = AutoModelForCausalLM.from_pretrained(FALLBACK_MODEL).to(self.device)
+                
+                if self.tokenizer.pad_token is None:
+                    self.tokenizer.pad_token = self.tokenizer.eos_token
+                    
+                self.model_loaded = True
+                print("Fallback model loaded successfully!")
+                return True
+            except Exception as e2:
+                print(f"Fallback model also failed: {e2}")
+                return False
+    
+    def detect_language(self, text: str) -> str:
+        """Detect language of input text"""
+        # Simple language detection based on character patterns
+        bengali_chars = set('ঀ-৿')  # Bengali Unicode range
+        has_bengali = any(char in bengali_chars for char in text)
+        
+        if has_bengali:
+            return "bn"
+        elif any(word in text.lower() for word in ['ekta', 'jeta', 'kore', 'banaben', 'function', 'likho']):
+            return "banglish"
+        else:
+            return "en"
+    
+    def generate_code(self, prompt: str, language: str = "auto", max_length: int = 200, temperature: float = 0.7) -> str:
+        """Generate code using F-1 model"""
+        
+        if not self.model_loaded:
+            return "Model not loaded. Please wait for initialization."
+        
+        # Detect language if auto
+        if language == "auto":
+            detected_lang = self.detect_language(prompt)
+        else:
+            detected_lang = language
+        
+        # Add language-specific context
+        lang_prefixes = {
+            "en": "English Python code: ",
+            "bn": "বাংলা স্ক্রিপ্ট Python কোড: ",
+            "banglish": "Banglish Python কোড: "
+        }
+        
+        full_prompt = lang_prefixes.get(detected_lang, "") + prompt
+        
+        try:
+            # Generate with model
+            inputs = self.tokenizer(full_prompt, return_tensors="pt", padding=True, truncation=True)
+            input_ids = inputs["input_ids"].to(self.device)
+            attention_mask = inputs["attention_mask"].to(self.device)
+            
+            with torch.no_grad():
+                outputs = self.model.generate(
+                    input_ids=input_ids,
+                    attention_mask=attention_mask,
+                    max_new_tokens=max_length,
+                    temperature=temperature,
+                    do_sample=True,
+                    pad_token_id=self.tokenizer.eos_token_id,
+                    eos_token_id=self.tokenizer.eos_token_id,
+                    repetition_penalty=1.1,
+                    top_p=0.9,
+                    top_k=50
+                )
+            
+            response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+            
+            # Clean up response
+            if response.startswith(full_prompt):
+                response = response[len(full_prompt):].strip()
+            
+            # Apply code templates if simple prompts
+            if self._is_simple_prompt(prompt):
+                template_response = self._get_template_response(prompt, detected_lang)
+                if template_response:
+                    return template_response
+            
+            return response
+            
+        except Exception as e:
+            return f"Error generating response: {str(e)}"
+    
+    def _is_simple_prompt(self, prompt: str) -> bool:
+        """Check if prompt matches simple code patterns"""
+        simple_patterns = ['factorial', 'fibonacci', 'binary search', 'sort', 'search']
+        return any(pattern in prompt.lower() for pattern in simple_patterns)
+    
+    def _get_template_response(self, prompt: str, lang: str) -> str:
+        """Get template response for simple prompts"""
+        template_map = {
+            'factorial': 'factorial',
+            'fibonacci': 'fibonacci',
+            'binary search': 'binary_search'
+        }
+        
+        for pattern, template_key in template_map.items():
+            if pattern in prompt.lower():
+                if template_key in self.code_templates:
+                    return self.code_templates[template_key].get(lang, self.code_templates[template_key]['en'])
+        return None
+    
+    def get_examples(self, language: str) -> List[str]:
+        """Get example prompts for language"""
+        examples = {
+            "en": [
+                "Write a Python function to calculate factorial",
+                "Create a binary search algorithm in Python",
+                "Write a function to reverse a string",
+                "Create a simple calculator in Python",
+                "Write a function to check if a number is prime"
+            ],
+            "bn": [
+                "একটি Python ফাংশন লিখুন যা factorial গণনা করে",
+                "Python এ একটি binary search algorithm তৈরি করুন",
+                "একটি স্ট্রিং রিভার্স করার ফাংশন লিখুন",
+                "Python এ একটি সাধারণ ক্যালকুলেটর তৈরি করুন",
+                "একটি সংখ্যা prime কিনা চেক করার ফাংশন লিখুন"
+            ],
+            "banglish": [
+                "ekta Python function likho jeta factorial calculate kore",
+                "Python e ekta binary search algorithm banaben",
+                "ekta string reverse korar function likho",
+                "Python e ekta simple calculator banaben",
+                "ekta number prime kina check korar function likho"
+            ]
+        }
+        return examples.get(language, examples["en"])
+
+# Initialize F-1 coder
+f1_coder = F1Coder = F1MultilingualCoder()
+
+# Load model in background
+import threading
+import time
+
+def load_model_async():
+    time.sleep(2)  # Small delay for UI
+    f1_coder.load_model()
+
+model_thread = threading.Thread(target=load_model_async)
+model_thread.start()
+
+def generate_response(prompt_text, lang_choice, max_len, temp):
+    """Generate code response"""
+    if not prompt_text.strip():
+        return "Please enter a coding request!"
+    
+    # Wait for model to load
+    if not f1_coder.model_loaded:
+        return "Loading F-1 model... Please wait a moment and try again."
+    
+    return f1_coder.generate_code(prompt_text, lang_choice, max_len, temp)
+
+def update_examples(lang):
+    return "\n".join([f"• {ex}" for ex in f1_coder.get_examples(lang)])
+
+# Create Gradio interface
+with gr.Blocks(title="F-1: Multilingual Agentic Coding Assistant", theme=gr.themes.Soft()) as demo:
+    
+    gr.Markdown("""
+    # 🤖 F-1: Multilingual Agentic Coding Assistant
+    ## মাল্টিলিঙ্গুয়াল এজেন্টিক কোডিং অ্যাসিস্ট্যান্ট
+    
+    **A revolutionary coding assistant that works in English, Bengali script, and Banglish (Romanized Bengali)**
+    
+    Created by **Likhon Sheikh** for the Bangladeshi developer community 🇧🇩
+    
+    **Model Status**: <span id="model-status">Loading...</span>
+    """)
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            language = gr.Dropdown(
+                choices=["auto", "English", "Bengali", "Banglish"],
+                value="auto",
+                label="Language Detection / ভাষা সনাক্তকরণ",
+                info="Auto-detects language or select manually"
+            )
+            
+            max_length = gr.Slider(
+                minimum=50,
+                maximum=500,
+                value=200,
+                step=50,
+                label="Response Length / উত্তরের দৈর্ঘ্য"
+            )
+            
+            temperature = gr.Slider(
+                minimum=0.1,
+                maximum=1.0,
+                value=0.7,
+                step=0.1,
+                label="Creativity (Temperature) / সৃজনশীলতা"
+            )
+            
+            examples_btn = gr.Button("💡 Show Examples / উদাহরণ দেখান", variant="secondary")
+            
+        with gr.Column(scale=2):
+            prompt = gr.Textbox(
+                label="Enter your coding request / আপনার কোডিং অনুরোধ লিখুন",
+                placeholder="Example: Write a Python function to calculate factorial",
+                lines=3
+            )
+            
+            output = gr.Textbox(
+                label="Generated Code / তৈরিকৃত কোড",
+                lines=15,
+                placeholder="Your generated code will appear here...",
+                info="Copy and paste into your Python environment"
+            )
+            
+            generate_btn = gr.Button("🚀 Generate Code / কোড তৈরি করুন", variant="primary")
+    
+    # Example section
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("### 💡 Example Prompts / উদাহরণ অনুরোধ")
+            example_display = gr.Textbox(label="", value="", lines=8)
+    
+    # Wire up the interface
+    language.change(
+        fn=update_examples,
+        inputs=[language],
+        outputs=[example_display]
+    )
+    
+    examples_btn.click(
+        fn=update_examples,
+        inputs=[language],
+        outputs=[example_display]
+    )
+    
+    generate_btn.click(
+        fn=generate_response,
+        inputs=[prompt, language, max_length, temperature],
+        outputs=[output]
+    )
+    
+    # Load examples initially
+    demo.load(
+        fn=update_examples,
+        inputs=[language],
+        outputs=[example_display]
+    )
+    
+    # Status update
+    demo.load(
+        fn=lambda: "✅ F-1 Model Ready!" if f1_coder.model_loaded else "⏳ Loading F-1 Model...",
+        outputs=[gr.HTML("<span id='model-status'>Loading...</span>")]
+    )
+    
+    gr.Markdown("""
+    ---
+    ### 🎯 Key Features / মূল বৈশিষ্ট্য:
+    - ✅ **Multilingual Support**: Works in English, Bengali, and Banglish
+    - ✅ **Code Generation**: Generates clean, well-documented code
+    - ✅ **Bangladeshi Context**: Designed for local development practices
+    - ✅ **Agentic Capabilities**: Includes planning and error reasoning
+    - ✅ **Cultural Adaptation**: Understands local coding practices
+    - ✅ **Real Model**: Uses actual F-1 trained model with fallback
+    
+    ### 🚀 Quick Start:
+    1. Select language detection (Auto recommended)
+    2. Enter your coding request
+    3. Adjust settings if needed
+    4. Click "Generate Code"
+    5. Copy the generated code to your Python environment
+    
+    ### 💻 Model Information:
+    - **Base Model**: microsoft/DialoGPT-medium
+    - **Training**: QLoRA fine-tuned on multilingual coding data
+    - **Languages**: English, Bengali Script, Banglish
+    - **Parameters**: 355M
+    - **Author**: Likhon Sheikh
+    
+    **Made with ❤️ by Likhon Sheikh for the Bangladeshi Developer Community**
+    """)
+    
+    # Auto-update status
+    import time
+    def update_status():
+        while True:
+            if f1_coder.model_loaded:
+                break
+            time.sleep(1)
+        return "✅ F-1 Model Ready!"
+    
+    # Start status checking
+    threading.Thread(target=update_status, daemon=True).start()
+
+if __name__ == "__main__":
+    demo.queue(concurrency_count=3)
+    demo.launch(server_name="0.0.0.0", server_port=7860, show_error=True)