Update Chat templates and examples to use chatlas

Author: cpsievert

shiny/templates/chat/enterprise/aws-bedrock-anthropic/app.py

@@ -4,16 +4,17 @@
 # To get started, follow the instructions at https://aws.amazon.com/bedrock/claude/
 # as well as https://github.com/anthropics/anthropic-sdk-python#aws-bedrock
 # ------------------------------------------------------------------------------------
-from anthropic import AnthropicBedrock
 from app_utils import load_dotenv
+from chatlas import ChatBedrockAnthropic
 
 from shiny.express import ui
 
 # Either explicitly set the AWS environment variables before launching the app, or set
 # them in a file named `.env`. The `python-dotenv` package will load `.env` as
 # environment variables which can be read by `os.getenv()`.
 load_dotenv()
-llm = AnthropicBedrock(
+chat_model = ChatBedrockAnthropic(
+    model="anthropic.claude-3-sonnet-20240229-v1:0",
     # aws_secret_key=os.getenv("AWS_SECRET_KEY"),
     # aws_access_key=os.getenv("AWS_ACCESS_KEY"),
     # aws_region=os.getenv("AWS_REGION"),
@@ -34,15 +35,6 @@
 
 # Define a callback to run when the user submits a message
 @chat.on_user_submit
-async def _():
-    # Get messages currently in the chat
-    messages = chat.messages(format="anthropic")
-    # Create a response message stream
-    response = llm.messages.create(
-        model="anthropic.claude-3-5-sonnet-20241022-v2:0",
-        messages=messages,
-        stream=True,
-        max_tokens=1000,
-    )
-    # Append the response stream into the chat
+async def handle_user_input(user_input):
+    response = chat_model.stream(user_input)
     await chat.append_message_stream(response)

shiny/templates/chat/enterprise/aws-bedrock-anthropic/requirements.txt

@@ -1,4 +1,5 @@
 shiny
 python-dotenv
 tokenizers
-anthropic
+chatlas
+anthropic[bedrock]

shiny/templates/chat/enterprise/azure-openai/app.py

@@ -1,58 +1,41 @@
 # ------------------------------------------------------------------------------------
 # A basic Shiny Chat example powered by OpenAI running on Azure.
-# To run it, you'll need OpenAI API key.
-# To get setup, follow the instructions at https://learn.microsoft.com/en-us/azure/ai-services/openai/quickstart?tabs=command-line%2Cpython-new&pivots=programming-language-python#create-a-new-python-application
 # ------------------------------------------------------------------------------------
 import os
 
 from app_utils import load_dotenv
-from openai import AzureOpenAI
+from chatlas import ChatAzureOpenAI
 
 from shiny.express import ui
 
-# Either explicitly set the AZURE_OPENAI_API_KEY and AZURE_OPENAI_ENDPOINT environment
-# variables before launching the app, or set them in a file named `.env`. The
-# `python-dotenv` package will load `.env` as environment variables which can later be
-# read by `os.getenv()`.
+# ChatAzureOpenAI() requires an API key from Azure OpenAI.
+# See the docs for more information on how to obtain one.
+# https://posit-dev.github.io/chatlas/reference/ChatAzureOpenAI.html
 load_dotenv()
-
-llm = AzureOpenAI(
+chat_model = ChatAzureOpenAI(
     api_key=os.getenv("AZURE_OPENAI_API_KEY"),
-    api_version="2024-02-01",
-    azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),  # type: ignore
+    endpoint="https://my-endpoint.openai.azure.com",
+    deployment_id="gpt-4o-mini",
+    api_version="2024-08-01-preview",
 )
 
-deployment_name = "REPLACE_WITH_YOUR_DEPLOYMENT_NAME"
-
 # Set some Shiny page options
 ui.page_opts(
-    title="Hello OpenAI Chat",
+    title="Hello Azure OpenAI Chat",
     fillable=True,
     fillable_mobile=True,
 )
 
 # Create a chat instance, with an initial message
 chat = ui.Chat(
     id="chat",
-    messages=[
-        {"content": "Hello! How can I help you today?", "role": "assistant"},
-    ],
+    messages=["Hello! How can I help you today?"],
 )
-
-# Display the chat
 chat.ui()
 
 
 # Define a callback to run when the user submits a message
 @chat.on_user_submit
-async def _():
-    # Get messages currently in the chat
-    messages = chat.messages(format="openai")
-    # Create a response message stream
-    response = llm.chat.completions.create(
-        model=deployment_name,
-        messages=messages,
-        stream=True,
-    )
-    # Append the response stream into the chat
+async def handle_user_input(user_input):
+    response = chat_model.stream(user_input)
     await chat.append_message_stream(response)

shiny/templates/chat/enterprise/azure-openai/requirements.txt

@@ -1,4 +1,5 @@
 shiny
 python-dotenv
 tokenizers
+chatlas
 openai

shiny/templates/chat/hello-providers/anthropic/app.py

@@ -1,20 +1,23 @@
 # ------------------------------------------------------------------------------------
 # A basic Shiny Chat example powered by Anthropic's Claude model.
-# To run it, you'll need an Anthropic API key.
-# To get one, follow the instructions at https://docs.anthropic.com/en/api/getting-started
 # ------------------------------------------------------------------------------------
 import os
 
-from anthropic import AsyncAnthropic
 from app_utils import load_dotenv
+from chatlas import ChatAnthropic
 
 from shiny.express import ui
 
-# Either explicitly set the ANTHROPIC_API_KEY environment variable before launching the
-# app, or set them in a file named `.env`. The `python-dotenv` package will load `.env`
-# as environment variables which can later be read by `os.getenv()`.
+# ChatAnthropic() requires an API key from Anthropic.
+# See the docs for more information on how to obtain one.
+# https://posit-dev.github.io/chatlas/reference/ChatAnthropic.html
 load_dotenv()
-llm = AsyncAnthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"))
+chat_model = ChatAnthropic(
+    api_key=os.environ.get("ANTHROPIC_API_KEY"),
+    model="claude-3-5-sonnet-latest",
+    system_prompt="You are a helpful assistant.",
+)
+
 
 # Set some Shiny page options
 ui.page_opts(
@@ -23,22 +26,16 @@
     fillable_mobile=True,
 )
 
-# Create and display empty chat
-chat = ui.Chat(id="chat")
+# Create and display a Shiny chat component
+chat = ui.Chat(
+    id="chat",
+    messages=["Hello! How can I help you today?"],
+)
 chat.ui()
 
 
-# Define a callback to run when the user submits a message
+# Generate a response when the user submits a message
 @chat.on_user_submit
-async def _():
-    # Get messages currently in the chat
-    messages = chat.messages(format="anthropic")
-    # Create a response message stream
-    response = await llm.messages.create(
-        model="claude-3-5-sonnet-latest",
-        messages=messages,
-        stream=True,
-        max_tokens=1000,
-    )
-    # Append the response stream into the chat
+async def handle_user_input(user_input):
+    response = chat_model.stream(user_input)
     await chat.append_message_stream(response)

shiny/templates/chat/hello-providers/anthropic/requirements.txt

@@ -1,4 +1,5 @@
 shiny
 python-dotenv
 tokenizers
+chatlas
 anthropic

shiny/templates/chat/hello-providers/google/_template.json

@@ -0,0 +1,5 @@
+{
+  "type": "app",
+  "id": "chat-ai-gemini",
+  "title": "Chat AI using Google Gemini"
+}

shiny/templates/chat/hello-providers/google/app.py

@@ -0,0 +1,37 @@
+# ------------------------------------------------------------------------------------
+# A basic Shiny Chat example powered by Google's Gemini model.
+# ------------------------------------------------------------------------------------
+import os
+
+from app_utils import load_dotenv
+from chatlas import ChatGoogle
+
+from shiny.express import ui
+
+# ChatGoogle() requires an API key from Google.
+# See the docs for more information on how to obtain one.
+# https://posit-dev.github.io/chatlas/reference/ChatGoogle.html
+load_dotenv()
+chat_model = ChatGoogle(
+    api_key=os.environ.get("GOOGLE_API_KEY"),
+    system_prompt="You are a helpful assistant.",
+    model="gemini-1.5-flash",
+)
+
+# Set some Shiny page options
+ui.page_opts(
+    title="Hello Google Gemini Chat",
+    fillable=True,
+    fillable_mobile=True,
+)
+
+# Create and display empty chat
+chat = ui.Chat(id="chat")
+chat.ui()
+
+
+# Generate a response when the user submits a message
+@chat.on_user_submit
+async def handle_user_input(user_input):
+    response = chat_model.stream(user_input)
+    await chat.append_message_stream(response)

shiny/templates/chat/hello-providers/google/app_utils.py

@@ -0,0 +1,26 @@
+import os
+from pathlib import Path
+from typing import Any
+
+app_dir = Path(__file__).parent
+env_file = app_dir / ".env"
+
+
+def load_dotenv(dotenv_path: os.PathLike[str] = env_file, **kwargs: Any) -> None:
+    """
+    A convenience wrapper around `dotenv.load_dotenv` that warns if `dotenv` is not installed.
+    It also returns `None` to make it easier to ignore the return value.
+    """
+    try:
+        import dotenv
+
+        dotenv.load_dotenv(dotenv_path=dotenv_path, **kwargs)
+    except ImportError:
+        import warnings
+
+        warnings.warn(
+            "Could not import `dotenv`. If you want to use `.env` files to "
+            "load environment variables, please install it using "
+            "`pip install python-dotenv`.",
+            stacklevel=2,
+        )

shiny/templates/chat/hello-providers/google/requirements.txt

@@ -0,0 +1,5 @@
+shiny
+python-dotenv
+tokenizers
+chatlas
+google-generativeai