add new sdk samples

scenarios/inference/chat-app/chat-simple.py

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+from azure.ai.projects import AIProjectClient
+from azure.identity import DefaultAzureCredential
+
+project_connection_string = "<your-connection-string-goes-here>"
+
+project = AIProjectClient.from_connection_string(
+    conn_str=project_connection_string, credential=DefaultAzureCredential()
+)
+
+chat = project.inference.get_chat_completions_client()
+response = chat.complete(
+    model="gpt-4o-mini",
+    messages=[
+        {
+            "role": "system",
+            "content": "You are an AI assistant that speaks like a techno punk rocker from 2350. Be cool but not too cool. Ya dig?",
+        },
+        {"role": "user", "content": "Hey, can you help me with my taxes? I'm a freelancer."},
+    ],
+)
+
+print(response.choices[0].message.content)

scenarios/inference/chat-app/chat-template.py

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+# ruff: noqa: E402, ANN201, ANN001
+
+chat = None
+
+# <chat_function>
+from azure.ai.inference.prompts import PromptTemplate
+
+
+def get_chat_response(messages, context):
+    # create a prompt template from an inline string (using mustache syntax)
+    prompt_template = PromptTemplate.from_message(
+        prompt_template="""
+        system:
+        You are an AI assistant that speaks like a techno punk rocker from 2350. Be cool but not too cool. Ya dig? Refer to the user by their first name, try to work their last name into a pun.
+
+        The user's first name is {{first_name}} and their last name is {{last_name}}.
+        """
+    )
+
+    # generate system message from the template, passing in the context as variables
+    system_message = prompt_template.render(data=context)
+
+    # add the prompt messages to the user messages
+    return chat.complete(
+        model="gpt-4o-mini",
+        messages=system_message + messages,
+        temperature=1,
+        frequency_penalty=0.5,
+        presence_penalty=0.5,
+    )
+
+
+# </chat_function>
+
+# <create_response>
+if __name__ == "__main__":
+    response = get_chat_response(
+        messages=[{"role": "user", "content": "what city has the best food in the world?"}],
+        context={"first_name": "Jessie", "last_name": "Irwin"},
+    )
+    print(response.choices[0].message.content)
+# </create_response>

scenarios/projects/basic/.env.sample

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+AIPROJECT_CONNECTION_STRING=your_connection_string

scenarios/projects/basic/README.md

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+---
+page_type: sample
+languages:
+- python
+products:
+- ai-products
+- ai-model-inference
+- ai-search
+- ai-evaluation
+description: Hello world samples for the projects SDK client
+---
+
+## Project SDK Basic samples
+
+### Overview
+
+This folder contains hello world samples for the projects SDK client. 
+
+### Objective
+
+This is meant to test out code that's used in our [SDK Overview](https://aka.ms/aifoundrysdk) page.
+
+## Create resources
+
+To run this sample, you'll need to create an Azure AI Project with an Azure AI Services resource connected to it. If you have an existing one, you can skip these steps and move to the next section.
+
+### Create an AI Project and AI Services resource
+
+First we'll create a project in Azure AI Studio:
+ - Navigate to [ai.azure.com](ai.azure.com)
+ - Click **New Project** on the homepage
+ - Enter a project name
+ - Click **Create new hub**, provide a hub name
+ - In **Customize** change the location to **East US 2** or **Sweden Central**
+ - Click **Create Project**
+
+This will take about 3 minutes to complete.
+
+### Deploy a gpt-4o-mini model
+
+Now we'll need to deploy a model so that we can call it from code. To start, we'll use a gpt-4o-mini model because it's fast and cheap. You can experiment with using a gpt-4o model for better results.
+ - Go to the **Models + Endpoints** page
+ - Click the **+ Deploy Model** dropdown and click **Deploy a base model**
+ - Select **gpt-4o-mini** from the list and click **Confirm**
+
+Repeat the above steps for text-embedding-ada-002
+
+## Set up a local development environment
+
+First, clone this repo locally from your favorite terminal and open this folder:
+```
+git clone https://github.com/azure-samples/azureai-samples
+cd azureai-samples/scenarios/projects/basic
+```
+
+Then run az login to authenticate with Azure:
+```
+az login
+```
+
+### Creating a local Python environment
+
+First, create a virtual environment. Always do this when installing packages locally >:(
+
+On Windows:
+```
+py -3 -m venv .venv
+.venv\scripts\activate
+```
+
+On Linux:
+```
+python3 -m venv .venv
+source venv/bin/activate
+```
+
+Install the core dependencies to run the sample:
+```Python
+pip install -r requirements.txt
+```
+
+## Configure project string
+
+Go back to the **Overview** page of your project, and in the upper right hand corner click the copy button beside the **Project connection string** field.
+
+Create a ```.env``` file using the sample:
+```
+cp .env.sample .env
+```
+
+Open the ```.env``` file and paste (ctrl-v) the value to the right of the ```AIPROJECT_CONNECTION_STRING=``` variable.
+
+### Try out samples!
+
+Run the different python files to run different code samples in this folder:
+```
+python <file_name>.py
+```
+
+### Estimated Runtime: 10 mins

scenarios/projects/basic/agents.py

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+# ruff: noqa: E402
+
+import os
+from azure.ai.projects import AIProjectClient
+from azure.identity import DefaultAzureCredential
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+project = AIProjectClient.from_connection_string(
+    conn_str=os.environ["AIPROJECT_CONNECTION_STRING"], credential=DefaultAzureCredential()
+)
+
+# <create_agent>
+from azure.ai.projects.models import FileSearchTool
+
+file = project.agents.upload_file_and_poll(file_path="product_info_1.md", purpose="assistants")
+vector_store = project.agents.create_vector_store_and_poll(file_ids=[file.id], name="my_vectorstore")
+file_search = FileSearchTool(vector_store_ids=[vector_store.id])
+
+# Create agent with file search tool and process the agent run
+agent = project.agents.create_agent(
+    model="gpt-4o-mini",
+    name="my-agent",
+    instructions="Hello, you are helpful agent and can search information from uploaded files",
+    tools=file_search.definitions,
+    tool_resources=file_search.resources,
+)
+
+# </create_agent>
+
+# <run_agent>
+# create and run a thread with a message
+thread = project.agents.create_thread()
+message = project.agents.create_message(
+    thread_id=thread.id, role="user", content="Hello, what Contoso products do you know?"
+)
+run = project.agents.create_and_process_run(thread_id=thread.id, assistant_id=agent.id)
+if run.status == "failed":
+    print(f"Run failed: {run.last_error}")
+    exit()
+
+# get messages from the thread and print the response (last message)
+messages = project.agents.list_messages(thread_id=thread.id)
+print(f"Response: {messages[-1]}")
+
+# </run_agent>

scenarios/projects/basic/evaluate_violence.py

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+# ruff: noqa: E402
+
+import os
+from azure.ai.projects import AIProjectClient
+from azure.identity import DefaultAzureCredential
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+project = AIProjectClient.from_connection_string(
+    conn_str=os.environ["AIPROJECT_CONNECTION_STRING"], credential=DefaultAzureCredential()
+)
+
+# <evaluate_violence>
+from azure.ai.evaluation import ViolenceEvaluator
+from azure.identity import DefaultAzureCredential
+
+# Initializing Violence Evaluator with project information
+violence_eval = ViolenceEvaluator(azure_ai_project=project.scope, credential=DefaultAzureCredential())
+
+# Running Violence Evaluator on single input row
+violence_score = violence_eval(query="what's the capital of france", response="Paris")
+print(violence_score)
+# </evaluate_violence>

scenarios/projects/basic/inference.py

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+import os
+from azure.ai.projects import AIProjectClient
+from azure.identity import DefaultAzureCredential
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+project = AIProjectClient.from_connection_string(
+    conn_str=os.environ["AIPROJECT_CONNECTION_STRING"], credential=DefaultAzureCredential()
+)
+
+# <chat_completion>
+# get a chat inferencing client using the project's default model inferencing endpoint
+chat = project.inference.get_chat_completions_client()
+
+# run a chat completion using the inferencing client
+response = chat.complete(
+    model="gpt-4o-mini",
+    messages=[
+        {
+            "role": "system",
+            "content": "You are an AI assistant that speaks like a techno punk rocker from 2350. Be cool but not too cool. Ya dig?",
+        },
+        {"role": "user", "content": "Hey, can you help me with my taxes? I'm a freelancer."},
+    ],
+)
+
+print(response.choices[0].message.content)
+# </chat_completion>

scenarios/projects/basic/myprompt.prompty

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+---
+name: Chat Prompt
+description: A prompty that extract users query intent based on the current_query and chat_history of the conversation
+model:
+    api: chat
+    configuration:
+        azure_deployment: gpt-4o-mini
+    parameters:
+        max_tokens: 256 # limit the output
+        temperature: 0.8 # higher temperature for creative answers
+---
+system:
+You are a helpful writing assistant.
+The user's first name is {{first_name}} and their last name is {{last_name}}.
+
+user:
+Write me a short poem about flowers

scenarios/projects/basic/openai_client.py

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+import os
+from azure.ai.projects import AIProjectClient
+from azure.identity import DefaultAzureCredential
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+project = AIProjectClient.from_connection_string(
+    conn_str=os.environ["AIPROJECT_CONNECTION_STRING"], credential=DefaultAzureCredential()
+)
+
+# <get_openai_client>
+openai = project.inference.get_azure_openai_client(api_version="2024-06-01")
+response = openai.chat.completions.create(
+    model="gpt-4o",
+    messages=[
+        {"role": "system", "content": "You are a helpful writing assistant"},
+        {"role": "user", "content": "Write me a poem about flowers"},
+    ],
+)
+
+print(response.choices[0].message.content)
+# </get_openai_client>

scenarios/projects/basic/product_info_1.md

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+# Information about product item_number: 1
+
+## Brand
+Contoso Galaxy Innovations
+
+## Category
+Smart Eyewear
+
+## Features
+- Augmented Reality interface
+- Voice-controlled AI assistant
+- HD video recording with 3D audio
+- UV protection and blue light filtering
+- Wireless charging with extended battery life
+
+## User Guide
+
+### 1. Introduction
+Introduction to your new SmartView Glasses
+
+### 2. Product Overview
+Overview of features and controls
+
+### 3. Sizing and Fit
+Finding your perfect fit and style adjustments
+
+### 4. Proper Care and Maintenance
+Cleaning and caring for your SmartView Glasses
+
+### 5. Break-in Period
+Adjusting to the augmented reality experience
+
+### 6. Safety Tips
+Safety guidelines for public and private spaces
+
+### 7. Troubleshooting
+Quick fixes for common issues
+
+## Warranty Information
+Two-year limited warranty on all electronic components
+
+## Contact Information
+Customer Support at [email protected]
+
+## Return Policy
+30-day return policy with no questions asked
+
+## FAQ
+- How to sync your SmartView Glasses with your devices
+- Troubleshooting connection issues
+- Customizing your augmented reality environment

scenarios/projects/basic/project.py

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+from azure.identity import DefaultAzureCredential
+from azure.ai.projects import AIProjectClient
+
+project_connection_string = "your_connection_string"
+
+project = AIProjectClient.from_connection_string(
+    conn_str=project_connection_string, credential=DefaultAzureCredential()
+)