project added

Dockerfile

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+# Use the official Python image
+FROM python:3.9
+
+# Set the working directory inside the container
+WORKDIR /app
+
+# Copy and install dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the app code
+COPY . .
+
+# Expose the API on port 7860
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+import os
+import re
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Initialize FastAPI app
+app = FastAPI()
+
+# Enable CORS (Allow all origins)
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Allow all origins
+    allow_credentials=True,
+    allow_methods=["*"],  # Allow all methods
+    allow_headers=["*"],  # Allow all headers
+)
+
+# Load the model
+MODEL_ID = "mzman123/musa-chef-gpt"
+tokenizer = AutoTokenizer.from_pretrained("auhide/chef-gpt-en")
+chef_gpt = AutoModelForCausalLM.from_pretrained(MODEL_ID)
+print("Model Loaded")
+
+
+# Define request body structure
+class IngredientsRequest(BaseModel):
+    ingredients: str
+
+
+@app.get("/")
+def home():
+    return {"message": "Hello World"}
+
+
+@app.post("/generate")
+def generate_from_model(request: IngredientsRequest):
+    """Generate a recipe from the given ingredients."""
+    
+    ingredients = request.ingredients.split(", ")
+    print("at backend:", ingredients)
+
+    if isinstance(ingredients, list):
+        prompt_text = f"ingredients>> {', '.join(ingredients)} ; recipe>>"
+        prompt_tokens = tokenizer(prompt_text, return_tensors="pt")
+
+        print("Prompt =", prompt_text)
+
+        output_test = chef_gpt.generate(
+            prompt_tokens.input_ids,
+            do_sample=True,
+            max_length=1000,
+            top_p=0.95,
+            attention_mask=prompt_tokens.attention_mask
+        )
+
+        recipe = tokenizer.batch_decode(output_test)[0]
+        print("Recipe before regex =", recipe)
+
+        # Extract recipe part
+        pattern = r"recipe>>([\s\S]*?)"
+        match = re.search(pattern, recipe)
+        if match:
+            recipe = recipe[match.end():].strip()
+        else:
+            print("Recipe section not found.")
+
+        # Clean unwanted text
+        unwanted_phrases = ['<|endoftext|>', '']
+        for phrase in unwanted_phrases:
+            recipe = recipe.replace(phrase, '')
+
+        recipe_lines = recipe.split("\n")
+
+        return {"recipe": recipe_lines}
+
+    else:
+        raise HTTPException(status_code=400, detail="Input data should be a comma-separated string of ingredients")
+
+
+# Run the FastAPI app (only when executing locally)
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=int(os.getenv("PORT", 7860)))

requirements.txt

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+fastapi
+uvicorn
+transformers
+torch