add all need file

Dockerfile

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+FROM python:3.9-slim
+
+# Install system dependencies
+RUN apt-get update && \
+    apt-get install -y build-essential libffi-dev git && \
+    rm -rf /var/lib/apt/lists/*
+
+# Create non-root user
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+# Copy requirements and install
+COPY --chown=user requirements.txt requirements.txt
+RUN python -m pip install --upgrade pip
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy app and model
+COPY --chown=user . /app
+
+# Expose port
+EXPOSE 7860
+
+# Run FastAPI app
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

TextAPI.py

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+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+MT_PRETRAINED_MODEL_NAME = "shhossain/opus-mt-en-to-bn"
+DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+MAX_LENGTH = 128
+
+tokenizer = AutoTokenizer.from_pretrained(MT_PRETRAINED_MODEL_NAME)
+model = AutoModelForSeq2SeqLM.from_pretrained(MT_PRETRAINED_MODEL_NAME)
+state_dict = torch.load("mt_model_weights.pt", map_location=DEVICE)
+model.load_state_dict(state_dict, strict=False)
+model.to(DEVICE)
+model.eval()
+
+def call_translate_api(text: str) -> dict:
+    try:
+        input_ids = tokenizer(text, return_tensors="pt", padding="max_length",
+                              truncation=True, max_length=MAX_LENGTH).input_ids.to(DEVICE)
+        with torch.no_grad():
+            output_tokens = model.generate(input_ids, max_length=MAX_LENGTH,
+                                           num_beams=4, early_stopping=True)
+        translation = tokenizer.decode(output_tokens[0], skip_special_tokens=True)
+        return {"status": "success", "translation": translation, "raw_response": output_tokens.tolist()}
+    except Exception as e:
+        return {"status": "error", "error": str(e)}
+
+if __name__ == "__main__":
+    print("===== English → Bangla Translator =====")
+    while True:
+        text = input("\nEnter English text: ")
+        if text.strip().lower() == "exit":
+            print("Exiting translator. Goodbye!")
+            break
+
+        result = call_translate_api(text)
+        if result["status"] == "success":
+            print(f"Bangla Translation: {result['translation']}")
+        else:
+            print(f"Error: {result['error']}")

app.py

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+import torch
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+# ---------------- CONFIG ---------------- #
+mt_pretrained_model_name = "shhossain/opus-mt-en-to-bn"  # base architecture
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+MAX_LENGTH = 128
+
+# ---------------- LOAD TOKENIZER ---------------- #
+tokenizer = AutoTokenizer.from_pretrained(mt_pretrained_model_name)
+
+# ---------------- LOAD MODEL + YOUR WEIGHTS ---------------- #
+# Load the base pretrained model
+model = AutoModelForSeq2SeqLM.from_pretrained(mt_pretrained_model_name)
+
+# Load your fine-tuned weights (must be in the same folder as app.py)
+state_dict = torch.load("mt_model.pth", map_location=device)
+model.load_state_dict(state_dict, strict=False)  # strict=False = ignore extra keys
+model.to(device)
+model.eval()
+
+# ---------------- TRANSLATION FUNCTION ---------------- #
+def translate_english_to_bangla(sentence: str) -> str:
+    input_ids = tokenizer(
+        sentence,
+        return_tensors="pt",
+        padding="max_length",
+        truncation=True,
+        max_length=MAX_LENGTH
+    ).input_ids.to(device)
+
+    with torch.no_grad():
+        output_tokens = model.generate(
+            input_ids,
+            max_length=MAX_LENGTH,
+            num_beams=4,
+            early_stopping=True
+        )
+
+    return tokenizer.decode(output_tokens[0], skip_special_tokens=True)
+
+# ---------------- GRADIO INTERFACE ---------------- #
+gr.Interface(
+    fn=translate_english_to_bangla,
+    inputs=gr.Textbox(lines=3, placeholder="Enter your English sentence...", label="English Text"),
+    outputs=gr.Textbox(label="Bangla Translation"),
+    title="English to Bangla Translator(Fine Tuning)",
+    description=""
+).launch(server_name="0.0.0.0", server_port=7860)

mt_model.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e664f12133a2750bdaa0075dcb39ce2a710a3f8fde1f7e15341bd758e16d3995
+size 305476421

requirements.txt

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+torch
+transformers
+gradio
+pydantic
+sentencepiece
+numpy
+fastapi
+uvicorn
+sacremoses
+
+