Create app.py

app.py

@@ -0,0 +1,230 @@
+import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch, re, json
+from datetime import datetime
+
+device = "cuda"  # the device to load the model onto
+
+# Load model and tokenizer
+model = AutoModelForCausalLM.from_pretrained(
+    "Qwen/Qwen1.5-0.5B-Chat",
+    torch_dtype="auto",
+    device_map="auto",
+).to(device)
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen1.5-0.5B-Chat")
+
+if 'recipe' not in st.session_state:
+    st.session_state.recipe = None
+
+if 'recipe_saved' not in st.session_state:
+    st.session_state.recipe_saved = None
+
+if 'user_direction' not in st.session_state:
+    st.session_state.user_direction = None
+
+if 'serving_size' not in st.session_state:
+    st.session_state.serving_size = 2
+
+if 'selected_difficulty' not in st.session_state:
+    st.session_state.selected_difficulty = "Quick & Easy"
+
+if 'exclusions' not in st.session_state:
+    st.session_state.exclusions = None
+    
+def create_detailed_prompt(user_direction, exclusions, serving_size, difficulty):
+    if difficulty == "Quick & Easy":
+        prompt = (
+            f"Provide a 'Quick and Easy' recipe for {user_direction} that excludes {exclusions} and has a serving size of {serving_size}. "
+            f"It should require as few ingredients as possible and should be ready in as little time as possible. "
+            f"The steps should be simple, and the ingredients should be commonly found in a household pantry. "
+            f"Provide a detailed ingredient list and step-by-step guide that explains the instructions to prepare in detail."
+        )
+    elif difficulty == "Intermediate":
+        prompt = (
+            f"Provide a classic recipe for {user_direction} that excludes {exclusions} and has a serving size of {serving_size}. "
+            f"The recipe should offer a bit of a cooking challenge but should not require professional skills. "
+            f"The recipe should feature traditional ingredients and techniques that are authentic to its cuisine. "
+            f"Provide a detailed ingredient list and step-by-step guide that explains the instructions to prepare in detail."
+        )
+    elif difficulty == "Professional":
+        prompt = (
+            f"Provide a advanced recipe for {user_direction} that excludes {exclusions} and has a serving size of {serving_size}. "
+            f"The recipe should push the boundaries of culinary arts, integrating unique ingredients, advanced cooking techniques, and innovative presentations. "
+            f"The recipe should be able to be served at a high-end restaurant or would impress at a gourmet food competition. "
+            f"Provide a detailed ingredient list and step-by-step guide that explains the instructions to prepare in detail."
+        )
+    return prompt
+
+def generate_recipe(user_inputs):
+    with st.spinner('Building the perfect recipe...'):
+        functions = [
+          {
+            "name": "provide_recipe",
+            "description": "Provides a detailed recipe strictly adhering to the user input/specifications, especially ingredient exclusions and the recipe difficulty",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "name": {
+                        "type": "string",
+                        "description": "A creative name for the recipe"
+                    },
+                    "description": {
+                        "type": "string",
+                        "description": "a brief one-sentence description of the provided recipe"
+                    },
+                    "ingredients": {
+                        "type": "array",
+                        "items": {
+                            "type": "object",
+                            "properties": {
+                                "name": {
+                                    "type": "string",
+                                    "description": "Quantity and name of the ingredient"
+                                }
+                            }
+                        }
+                    },
+                    "instructions": {
+                        "type": "array",
+                        "items": {
+                            "type": "object",
+                            "properties": {
+                                "step_number": {
+                                    "type": "number",
+                                    "description": "The sequence number of this step"
+                                },
+                                "instruction": {
+                                    "type": "string",
+                                    "description": "Detailed description of what to do in this step"
+                                }
+                            }
+                        }
+                    }
+                },
+                "required": [
+                    "name",
+                    "description",
+                    "ingredients",
+                    "instructions"
+                    ],
+            },
+          }
+        ]
+        prompt = create_detailed_prompt(user_inputs['user_direction'], user_inputs['exclusions'], user_inputs['serving_size'], user_inputs['difficulty'])
+        messages = [{"role": "user", "content": prompt}]
+        text = tokenizer.apply_chat_template(
+            messages,
+            tokenize=False,
+            add_generation_prompt=True,
+            tools=functions
+        )
+
+        # Tokenize and move to the correct device
+        model_inputs = tokenizer([text], return_tensors="pt").to(device)
+        torch.cuda.empty_cache()
+        with torch.no_grad():
+            generated_ids = model.generate(
+                model_inputs.input_ids,
+                max_new_tokens=64  # Reduced value for memory management
+            )
+
+        generated_ids = [
+            output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+        ]
+
+        st.session_state.recipe = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+        st.session_state.recipe_saved = False
+        
+def clear_inputs():
+    st.session_state.user_direction = None
+    st.session_state.exclusions = None
+    st.session_state.serving_size = 2
+    st.session_state.selected_difficulty = "Quick & Easy"
+    
+st.title("Let's get cooking")
+st.session_state.user_direction = st.text_area(
+    "What do you want to cook? Describe anything - a dish, cuisine, event, or vibe.",
+    value = st.session_state.user_direction,
+    placeholder="quick snack, asian style bowl with either noodles or rice, something italian",
+    )
+
+st.session_state.serving_size = st.number_input(
+    "How many servings would you like to cook?",
+    min_value=1,
+    max_value=100,
+    value=st.session_state.serving_size,
+    step=1
+)
+
+difficulty_dictionary = {
+    "Quick & Easy": {
+        "description": "Easy recipes with straightforward instructions. Ideal for beginners or those seeking quick and simple cooking.",
+    },
+    "Intermediate": {
+        "description": "Recipes with some intricate steps that invite a little challenge. Perfect for regular cooks wanting to expand their repertoire with new ingredients and techniques.",
+    },
+    "Professional": {
+        "description": "Complex recipes that demand a high level of skill and precision. Suited for seasoned cooks aspiring to professional-level sophistication and creativity.",
+    }
+}
+
+st.session_state.selected_difficulty = st.radio(
+    "Choose a difficulty level for your recipe.",
+    [
+        list(difficulty_dictionary.keys())[0], 
+        list(difficulty_dictionary.keys())[1], 
+        list(difficulty_dictionary.keys())[2]
+    ],
+    captions = [
+        difficulty_dictionary["Quick & Easy"]["description"], 
+        difficulty_dictionary["Intermediate"]["description"],
+        difficulty_dictionary["Professional"]["description"]
+    ],
+    index=list(difficulty_dictionary).index(st.session_state.selected_difficulty)
+)
+
+st.session_state.exclusions = st.text_area(
+    "Any ingredients you want to exclude?",
+    value = st.session_state.exclusions,
+    placeholder="gluten, dairy, nuts, cilantro",
+    )
+
+fancy_exclusions =""
+
+if st.session_state.selected_difficulty == "Professional":
+    exclude_fancy = st.checkbox(
+        "Exclude cliche professional ingredients? (gold leaf, truffle, edible flowers, microgreens)", 
+        value=True)
+    fancy_exclusions = "gold leaf, truffle, edible flowers, microgreens, gold dust"
+      
+
+user_inputs = {
+    "user_direction" : st.session_state.user_direction,
+    "exclusions": f"{st.session_state.exclusions}, {fancy_exclusions}",
+    "serving_size": st.session_state.serving_size,
+    "difficulty": st.session_state.selected_difficulty
+}
+button_cols_submit = st.columns([1, 1, 4])
+with button_cols_submit[0]:
+    st.button(label='Submit', on_click=generate_recipe, kwargs=dict(user_inputs=user_inputs), type="primary", use_container_width=True)
+with button_cols_submit[1]:
+    st.button(label='Reset', on_click=clear_inputs, type="secondary", use_container_width=True)
+with button_cols_submit[2]:
+    st.empty()
+    
+if st.session_state.recipe is not None:
+    st.divider()
+    recipe = json.loads(st.session_state.recipe)
+    recipe_md = ''
+    recipe_md += f'# {recipe["name"]} \n\n'
+    recipe_md += f'{recipe["description"]} \n\n'
+    recipe_md += '## Ingredients: \n'
+    for ingredient in recipe['ingredients']:
+        recipe_md += f"- {ingredient['name']} \n"
+    recipe_md += '\n## Instructions:\n'
+    for instruction in recipe['instructions']:
+        recipe_md += f"{instruction['step_number']}. {instruction['instruction']} \n"
+    recipe['md'] = recipe_md
+    recipe['timestamp'] = str(datetime.now())
+    st.markdown(recipe_md)
+    st.write("")