Chat example using structured output from openai

examples/chat/structured-output/app.py

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+import json
+from typing import List
+
+import shinyswatch
+from dotenv import load_dotenv
+from openai import AsyncOpenAI
+from pydantic import BaseModel
+
+from shiny import App, reactive, render, ui
+
+load_dotenv()
+
+# Initialize AsyncOpenAI client
+client = AsyncOpenAI()
+
+
+# Define the recipe schema using Pydantic
+class Ingredient(BaseModel):
+    name: str
+    amount: str
+    unit: str
+
+
+class RecipeStep(BaseModel):
+    step_number: int
+    instruction: str
+
+
+class Recipe(BaseModel):
+    name: str
+    description: str
+    ingredients: List[Ingredient]
+    steps: List[RecipeStep]
+    prep_time: str
+    cook_time: str
+    servings: int
+
+
+app_ui = ui.page_fillable(
+    ui.layout_sidebar(
+        ui.sidebar(
+            ui.input_action_button("clear", "New Chat"),
+            ui.accordion(
+                ui.accordion_panel("Recipe Summary", ui.output_ui("recipe_display")),
+                ui.accordion_panel("JSON View", ui.output_code("json_view")),
+            ),
+            id="sidebar",
+            open="closed",
+            width="500px",
+        ),
+        ui.chat_ui("chat"),
+    ),
+    title="Recipe Assistant",
+    theme=shinyswatch.theme.minty,
+)
+
+
+def server(input, output, session):
+    welcome_message = {
+        "content": "Hello! I'm your Recipe Assistant. Ask me about any recipe, and I'll help you find and understand it. When you're ready for a structured summary, just say 'Summarize recipe'.",
+        "role": "assistant",
+    }
+    chat = ui.Chat(id="chat", messages=[welcome_message])
+    recipe = reactive.Value(None)
+
+    @chat.on_user_submit
+    async def _():
+        user_message = chat.messages()[-1]["content"]
+
+        if "summarize recipe" in user_message.lower():
+            # Use Structured Outputs to get recipe details
+            completion = await client.beta.chat.completions.parse(
+                model="gpt-4o-2024-08-06",
+                messages=[
+                    {
+                        "role": "system",
+                        "content": "You are a helpful recipe assistant. Provide recipe details based on the previous conversation.",
+                    },
+                    *chat.messages(format="openai"),
+                ],
+                response_format=Recipe,
+            )
+
+            recipe.set(completion.choices[0].message.parsed)
+
+            await chat.append_message(
+                {
+                    "role": "assistant",
+                    "content": "I've summarized the recipe for you. You can see the structured details and JSON view in the sidebar.",
+                }
+            )
+
+            ui.update_sidebar("sidebar", show=True)
+
+        else:
+            # Continue the conversation normally
+            response = await client.chat.completions.create(
+                model="gpt-4o-2024-08-06",
+                messages=chat.messages(format="openai"),
+                stream=True,
+            )
+            await chat.append_message_stream(response)
+
+    @output
+    @render.ui
+    def recipe_display():
+        if recipe() is None:
+            return ui.p("No recipe summary available yet.")
+
+        r = recipe()
+        return ui.div(
+            ui.h3(r.name),
+            ui.p(r.description),
+            ui.h4("Ingredients:"),
+            ui.tags.ul(
+                [
+                    ui.tags.li(f"{ing.amount} {ing.unit} {ing.name}")
+                    for ing in r.ingredients
+                ]
+            ),
+            ui.h4("Instructions:"),
+            ui.tags.ol([ui.tags.li(step.instruction) for step in r.steps]),
+            ui.p(f"Prep time: {r.prep_time}"),
+            ui.p(f"Cook time: {r.cook_time}"),
+            ui.p(f"Servings: {r.servings}"),
+            style="border: 1px solid #ccc; padding: 10px; margin-top: 20px;",
+        )
+
+    @output
+    @render.code
+    def json_view():
+        if recipe() is None:
+            return "No recipe JSON available yet."
+
+        json_str = json.dumps(recipe().dict(), indent=2)
+        return json_str
+
+    @reactive.Effect
+    @reactive.event(input.clear)
+    async def _():
+        await chat.clear_messages()
+        await chat.append_message(welcome_message)
+        recipe.set(None)
+
+
+app = App(app_ui, server)

examples/chat/structured-output/requirements.txt

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+shiny
+shinyswatch
+python-dotenv
+openai
+pydantic