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app.py

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+import gradio as gr
+from langchain_core.output_parsers import JsonOutputParser
+from langchain_core.prompts import PromptTemplate
+from langchain_ollama import ChatOllama
+import json
+
+# Initialize the model and parser
+model = ChatOllama(
+    model="llama3.2",
+    temperature=0.25,
+    base_url="https://alpaca-upright-vulture.ngrok-free.app"
+)
+
+parser = JsonOutputParser()
+prompt = PromptTemplate(
+    template="Answer the user query.\n{format_instructions}\n{query}\n",
+    input_variables=["query"],
+    partial_variables={"format_instructions": parser.get_format_instructions()}
+)
+
+chain = prompt | model | parser
+
+def generate_recipe_json(query):
+    try:
+        results = chain.invoke({"query": query})
+        # Format JSON with indentation for better readability
+        formatted_json = json.dumps(results, indent=2)
+        return formatted_json
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Create Gradio interface
+with gr.Blocks(title="Recipe JSON Generator") as demo:
+    gr.Markdown("# 🍳 Recipe JSON Generator")
+    gr.Markdown("Get recipe information in JSON format!")
+    
+    with gr.Row():
+        query_input = gr.Textbox(
+            label="Your Query",
+            placeholder="Enter your recipe query...",
+            value="how to make gulab jam with ingredients"
+        )
+    
+    generate_btn = gr.Button("Generate Recipe JSON")
+    
+    json_output = gr.Code(
+        label="Recipe JSON",
+        language="json",
+    )
+    
+    generate_btn.click(
+        fn=generate_recipe_json,
+        inputs=[query_input],
+        outputs=[json_output]
+    )
+
+# Launch the interface
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+langchain-ollama
+langchain-core
+gradio