18 |
48 |
49 |
50 |
19 |
20 |
47 |
21 |
37 |
38 |
39 |
46 |
22 |
23 |
24 |
25 |
26 |
35 |
36 |
51 |
59 |
60 |
61 |
62 |
52 |
58 |
53 |
54 | You
55 |
56 |
57 |
63 |
73 |
74 |
75 |
76 |
77 |
78 |
79 |
80 |
--------------------------------------------------------------------------------
/samples/FileSearch/src/requirements.txt:
--------------------------------------------------------------------------------
1 | #
2 | # This file is autogenerated by pip-compile with Python 3.11
3 | # by the following command:
4 | #
5 | # pip-compile --output-file=requirements.txt pyproject.toml
6 | #
7 | aiofiles==23.2.1
8 | # via quart
9 | aiohttp==3.9.3
10 | # via quartapp (pyproject.toml)
11 | aiosignal==1.3.1
12 | # via aiohttp
13 | annotated-types==0.6.0
14 | # via pydantic
15 | anyio==4.3.0
16 | # via
17 | # httpx
18 | # openai
19 | # watchfiles
20 | attrs==23.2.0
21 | # via aiohttp
22 | azure-core==1.30.1
23 | # via azure-identity
24 | azure-identity==1.15.0
25 | # via quartapp (pyproject.toml)
26 | blinker==1.7.0
27 | # via
28 | # flask
29 | # quart
30 | certifi==2024.2.2
31 | # via
32 | # httpcore
33 | # httpx
34 | # requests
35 | cffi==1.16.0
36 | # via cryptography
37 | charset-normalizer==3.3.2
38 | # via requests
39 | click==8.1.7
40 | # via
41 | # flask
42 | # quart
43 | # uvicorn
44 | cryptography==42.0.5
45 | # via
46 | # azure-identity
47 | # msal
48 | # pyjwt
49 | distro==1.9.0
50 | # via openai
51 | flask==3.0.3
52 | # via quart
53 | frozenlist==1.4.1
54 | # via
55 | # aiohttp
56 | # aiosignal
57 | gunicorn==21.2.0
58 | # via quartapp (pyproject.toml)
59 | h11==0.14.0
60 | # via
61 | # httpcore
62 | # hypercorn
63 | # uvicorn
64 | # wsproto
65 | h2==4.1.0
66 | # via hypercorn
67 | hpack==4.0.0
68 | # via h2
69 | httpcore==1.0.5
70 | # via httpx
71 | httptools==0.6.1
72 | # via uvicorn
73 | httpx==0.27.0
74 | # via openai
75 | hypercorn==0.16.0
76 | # via quart
77 | hyperframe==6.0.1
78 | # via h2
79 | idna==3.7
80 | # via
81 | # anyio
82 | # httpx
83 | # requests
84 | # yarl
85 | itsdangerous==2.1.2
86 | # via
87 | # flask
88 | # quart
89 | jinja2==3.1.3
90 | # via
91 | # flask
92 | # quart
93 | markupsafe==2.1.5
94 | # via
95 | # jinja2
96 | # quart
97 | # werkzeug
98 | msal==1.28.0
99 | # via
100 | # azure-identity
101 | # msal-extensions
102 | msal-extensions==1.1.0
103 | # via azure-identity
104 | multidict==6.0.5
105 | # via
106 | # aiohttp
107 | # yarl
108 | openai==1.30.1
109 | # via quartapp (pyproject.toml)
110 | packaging==24.0
111 | # via
112 | # gunicorn
113 | # msal-extensions
114 | portalocker==2.8.2
115 | # via msal-extensions
116 | priority==2.0.0
117 | # via hypercorn
118 | pycparser==2.22
119 | # via cffi
120 | pydantic==2.6.4
121 | # via openai
122 | pydantic-core==2.16.3
123 | # via pydantic
124 | pyjwt[crypto]==2.8.0
125 | # via msal
126 | python-dotenv==1.0.1
127 | # via
128 | # quartapp (pyproject.toml)
129 | # uvicorn
130 | pyyaml==6.0.1
131 | # via
132 | # quartapp (pyproject.toml)
133 | # uvicorn
134 | quart==0.19.5
135 | # via quartapp (pyproject.toml)
136 | requests==2.31.0
137 | # via
138 | # azure-core
139 | # msal
140 | six==1.16.0
141 | # via azure-core
142 | sniffio==1.3.1
143 | # via
144 | # anyio
145 | # httpx
146 | # openai
147 | tqdm==4.66.2
148 | # via openai
149 | typing-extensions==4.11.0
150 | # via
151 | # azure-core
152 | # openai
153 | # pydantic
154 | # pydantic-core
155 | urllib3==2.2.1
156 | # via requests
157 | uvicorn[standard]==0.29.0
158 | # via quartapp (pyproject.toml)
159 | #uvloop==0.19.0
160 | # via uvicorn
161 | watchfiles==0.21.0
162 | # via uvicorn
163 | websockets==12.0
164 | # via uvicorn
165 | werkzeug==3.0.2
166 | # via
167 | # flask
168 | # quart
169 | # quartapp (pyproject.toml)
170 | wsproto==1.2.0
171 | # via hypercorn
172 | yarl==1.9.4
173 | # via aiohttp
174 | https://github.com/Azure-Samples/azureai-assistant-tool/releases/download/v0.4.0-alpha/azure_ai_assistant-0.4.0a1-py3-none-any.whl
175 | # via quartapp (pyproject.toml)
176 |
--------------------------------------------------------------------------------
/samples/ImageInput/README.md:
--------------------------------------------------------------------------------
1 | # Sample Application using Azure OpenAI Assistants with Image Input Support (Python)
2 |
3 | This sample includes a simple Python [Quart](https://quart.palletsprojects.com/en/latest/) app that streams responses from OpenAI Assistant to an HTML/JS frontend using Server-Sent Events (SSEs). The application supports both image (.jpg/jpeg, .webp, .gif, .png) and text inputs.
4 |
5 | The sample is designed for use with [Docker containers](https://www.docker.com/), both for local development and Azure deployment. For Azure deployment to [Azure Container Apps](https://learn.microsoft.com/azure/container-apps/overview), please use this [template](https://github.com/Azure-Samples/openai-chat-app-quickstart) and replace the `src` folder content with this application.
6 |
7 | ## Local development with Docker
8 |
9 | This sample includes a `docker-compose.yaml` for local development which creates a volume for the app code. That allows you to make changes to the code and see them instantly.
10 |
11 | 1. Install [Docker Desktop](https://www.docker.com/products/docker-desktop/). If you opened this inside Github Codespaces or a Dev Container in VS Code, installation is not needed. ⚠️ If you're on an Apple M1/M2, you won't be able to run `docker` commands inside a Dev Container; either use Codespaces or do not open the Dev Container.
12 |
13 | 2. Make sure that the `.env` file exists.
14 |
15 | 3. Store keys and endpoint information (Azure) for the OpenAI resource in the `.env` file. The key should be stored in the `.env` file as `AZURE_OPENAI_API_KEY or OPENAI_API_KEY`. This is necessary because Docker containers don't have access to your user Azure credentials.
16 |
17 | 4. Start the services with this command:
18 |
19 | ```shell
20 | docker-compose up --build
21 | ```
22 |
23 | 5. Click 'http://localhost:50505' in the browser to run the application.
24 |
25 | ## Example run
26 |
27 | 
28 |
29 | ## Deployment to Azure
30 |
31 | As mentioned earlier, please integrate this app using [template](https://github.com/Azure-Samples/openai-chat-app-quickstart) and following the Azure Container App deployment steps there.
--------------------------------------------------------------------------------
/samples/ImageInput/docker-compose.yaml:
--------------------------------------------------------------------------------
1 | services:
2 | app:
3 | build:
4 | context: ./src
5 | env_file:
6 | - .env
7 | ports:
8 | - 50505:50505
9 | volumes:
10 | - ./src:/code
11 |
--------------------------------------------------------------------------------
/samples/ImageInput/src/.dockerignore:
--------------------------------------------------------------------------------
1 | .git*
2 | .venv/
3 | **/*.pyc
4 |
--------------------------------------------------------------------------------
/samples/ImageInput/src/Dockerfile:
--------------------------------------------------------------------------------
1 | # ------------------- Stage 0: Base Stage ------------------------------
2 | FROM python:3.11-alpine AS base
3 |
4 | WORKDIR /code
5 |
6 | # Install tini, a tiny init for containers
7 | RUN apk add --update --no-cache tini
8 |
9 | # Install required packages for cryptography package
10 | # https://cryptography.io/en/latest/installation/#building-cryptography-on-linux
11 | RUN apk add gcc musl-dev python3-dev libffi-dev openssl-dev cargo pkgconfig
12 |
13 | # ------------------- Stage 1: Build Stage ------------------------------
14 | FROM base AS build
15 |
16 | COPY requirements.txt .
17 |
18 | RUN pip3 install -r requirements.txt
19 |
20 | COPY . .
21 |
22 | # ------------------- Stage 2: Final Stage ------------------------------
23 | FROM base AS final
24 |
25 | RUN addgroup -S app && adduser -S app -G app
26 |
27 | COPY --from=build --chown=app:app /usr/local/lib/python3.11 /usr/local/lib/python3.11
28 | COPY --from=build --chown=app:app /usr/local/bin /usr/local/bin
29 | COPY --from=build --chown=app:app /code /code
30 |
31 | USER app
32 |
33 | EXPOSE 50505
34 |
35 | ENTRYPOINT ["tini", "gunicorn", "quartapp:create_app()"]
36 |
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/samples/ImageInput/src/__init__.py:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/Azure-Samples/azureai-assistant-tool/c962df2526c7b5f67c8af32eead04f5872a80cdd/samples/ImageInput/src/__init__.py
--------------------------------------------------------------------------------
/samples/ImageInput/src/config/image_input_assistant_config.yaml:
--------------------------------------------------------------------------------
1 | name: image_input
2 | instructions: You are a helpful assistant capable of answering questions.
3 | model: gpt-4-turbo-2024-04-09
4 | assistant_id:
5 | file_references: []
6 | tool_resources:
7 | code_interpreter:
8 | files: {}
9 | file_search:
10 | vector_stores: []
11 | functions: []
12 | file_search: false
13 | code_interpreter: false
14 | output_folder_path: /code/output
15 | ai_client_type: OPEN_AI
16 | assistant_type: assistant
17 | completion_settings: null
18 | assistant_role: user
19 | config_folder: null
20 |
--------------------------------------------------------------------------------
/samples/ImageInput/src/gunicorn.conf.py:
--------------------------------------------------------------------------------
1 | import multiprocessing
2 | import os
3 |
4 | from dotenv import load_dotenv
5 |
6 | load_dotenv()
7 |
8 | max_requests = 1000
9 | max_requests_jitter = 50
10 | log_file = "-"
11 | bind = "0.0.0.0:50505"
12 |
13 | if not os.getenv("RUNNING_IN_PRODUCTION"):
14 | reload = True
15 |
16 | num_cpus = multiprocessing.cpu_count()
17 | workers = 1 #(num_cpus * 2) + 1
18 | worker_class = "uvicorn.workers.UvicornWorker"
19 |
20 | timeout = 120
21 |
--------------------------------------------------------------------------------
/samples/ImageInput/src/pyproject.toml:
--------------------------------------------------------------------------------
1 | [project]
2 | name = "quartapp"
3 | version = "1.0.0"
4 | description = "Create a simple chat app using Quart and OpenAI"
5 | dependencies = [
6 | "quart",
7 | "werkzeug",
8 | "gunicorn",
9 | "uvicorn[standard]",
10 | "openai",
11 | "azure-identity",
12 | "aiohttp",
13 | "python-dotenv",
14 | "pyyaml",
15 | "azure-ai-assistant"
16 | ]
17 |
18 | [build-system]
19 | requires = ["flit_core<4"]
20 | build-backend = "flit_core.buildapi"
21 |
--------------------------------------------------------------------------------
/samples/ImageInput/src/quartapp/__init__.py:
--------------------------------------------------------------------------------
1 | # Copyright (c) Microsoft. All rights reserved.
2 | # Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
3 |
4 | import logging
5 | import os
6 |
7 | from quart import Quart
8 |
9 |
10 | def create_app():
11 | if os.getenv("RUNNING_IN_PRODUCTION"):
12 | logging.basicConfig(level=logging.INFO)
13 | else:
14 | logging.basicConfig(level=logging.DEBUG)
15 |
16 | app = Quart(__name__)
17 |
18 | from . import chat # noqa
19 |
20 | app.register_blueprint(chat.bp)
21 |
22 | return app
23 |
--------------------------------------------------------------------------------
/samples/ImageInput/src/quartapp/static/ChatClient.js:
--------------------------------------------------------------------------------
1 | // Copyright (c) Microsoft. All rights reserved.
2 | // Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
3 |
4 | class ChatClient {
5 | constructor(ui) {
6 | this.ui = ui;
7 | this.messageInput = document.getElementById("message");
8 | this.fileInput = document.getElementById("file");
9 | this.eventSource = null;
10 | }
11 |
12 | async sendMessage(url) {
13 | const message = this.messageInput.value.trim();
14 | const files = this.fileInput.files;
15 |
16 | if (!message) return false;
17 |
18 | if (files.length > 0) {
19 | this.ui.appendUserMessage(message, files);
20 | } else {
21 | this.ui.appendUserMessage(message);
22 | }
23 |
24 | const formData = new FormData();
25 | formData.append("message", message);
26 | for (const [i, file] of Array.from(files).entries()) {
27 | if (file.type == "image/jpeg" || file.type == "image/png" || file.type == "image/gif" || file.type == "image/webp") {
28 | formData.append(`${i}_${file.name}`, file);
29 | } else {
30 | console.error("Unsupported file type")
31 | }
32 | }
33 |
34 | const response = await fetch(url, {
35 | method: "POST",
36 | body: formData,
37 | });
38 |
39 | const data = await response.json();
40 | return data.thread_name;
41 | }
42 |
43 | listenToServer(url, threadName) {
44 | if (!this.eventSource || this.eventSource.readyState === EventSource.CLOSED) {
45 | this.eventSource = new EventSource(`${url}/${threadName}`);
46 | this.handleMessages();
47 | }
48 | }
49 |
50 | handleMessages() {
51 | let messageDiv = null;
52 | let accumulatedContent = '';
53 | let isStreaming = true;
54 |
55 | this.eventSource.onmessage = event => {
56 | const data = JSON.parse(event.data);
57 |
58 | if (data.type === "stream_end") {
59 | this.eventSource.close();
60 | messageDiv = null;
61 | accumulatedContent = '';
62 | } else {
63 | if (!messageDiv) {
64 | messageDiv = this.ui.createAssistantMessageDiv();
65 | if (!messageDiv) {
66 | console.error("Failed to create message div.");
67 | }
68 | }
69 |
70 | // Check if it's a completed message
71 | if (data.type === "completed_message") {
72 | //console.log("Received completed message:", data.content);
73 | // Replace the accumulated content with the completed message
74 | this.ui.clearAssistantMessage(messageDiv);
75 | accumulatedContent = data.content;
76 | isStreaming = false;
77 | } else {
78 | //console.log("Received partial message:", data.content);
79 | // Append the partial message to the accumulated content
80 | accumulatedContent += data.content;
81 | }
82 |
83 | this.ui.appendAssistantMessage(messageDiv, accumulatedContent, isStreaming);
84 | }
85 | };
86 |
87 | this.eventSource.onerror = error => {
88 | console.error("EventSource failed:", error);
89 | this.eventSource.close();
90 | };
91 | }
92 |
93 | closeEventSource() {
94 | if (this.eventSource) this.eventSource.close();
95 | }
96 | }
97 |
98 | export default ChatClient;
99 |
--------------------------------------------------------------------------------
/samples/ImageInput/src/quartapp/static/ChatUI.js:
--------------------------------------------------------------------------------
1 | // Copyright (c) Microsoft. All rights reserved.
2 | // Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
3 |
4 | class ChatUI {
5 | constructor() {
6 | this.targetContainer = document.getElementById("messages");
7 | this.userTemplate = document.querySelector('#message-template-user');
8 | this.assistantTemplate = document.querySelector('#message-template-assistant');
9 | if (!this.assistantTemplate) {
10 | console.error("Assistant template not found!");
11 | }
12 | }
13 |
14 | appendUserMessage(message, imageFiles = null) {
15 | const userTemplateClone = this.userTemplate.content.cloneNode(true);
16 | userTemplateClone.querySelector(".message-content").textContent = message;
17 |
18 | if (imageFiles) {
19 | userTemplateClone.querySelector(".message-content").innerHTML += "
64 |
72 |
65 |
66 | Assistant
67 |
68 |
71 | "; 20 | for (const imageFile of imageFiles){ 21 | if (imageFile.type == "image/jpeg" || imageFile.type == "image/png" || imageFile.type == "image/gif" || imageFile.type == "image/webp") { 22 | userTemplateClone.querySelector(".message-content").innerHTML += `
18 |
42 |
43 |
44 |
19 |
20 |
41 |
21 |
40 |
22 |
23 |
24 |
25 |
26 |
38 |
39 |
45 |
53 |
54 |
55 |
56 |
46 |
52 |
47 |
48 | You
49 |
50 |
51 |
57 |
67 |
68 |
69 |
70 |
71 |
72 |
73 |
74 |
--------------------------------------------------------------------------------
/samples/ImageInput/src/requirements.txt:
--------------------------------------------------------------------------------
1 | #
2 | # This file is autogenerated by pip-compile with Python 3.11
3 | # by the following command:
4 | #
5 | # pip-compile --output-file=requirements.txt pyproject.toml
6 | #
7 | aiofiles==23.2.1
8 | # via quart
9 | aiohttp==3.9.3
10 | # via quartapp (pyproject.toml)
11 | aiosignal==1.3.1
12 | # via aiohttp
13 | annotated-types==0.6.0
14 | # via pydantic
15 | anyio==4.3.0
16 | # via
17 | # httpx
18 | # openai
19 | # watchfiles
20 | attrs==23.2.0
21 | # via aiohttp
22 | azure-core==1.30.1
23 | # via azure-identity
24 | azure-identity==1.15.0
25 | # via quartapp (pyproject.toml)
26 | blinker==1.7.0
27 | # via
28 | # flask
29 | # quart
30 | certifi==2024.2.2
31 | # via
32 | # httpcore
33 | # httpx
34 | # requests
35 | cffi==1.16.0
36 | # via cryptography
37 | charset-normalizer==3.3.2
38 | # via requests
39 | click==8.1.7
40 | # via
41 | # flask
42 | # quart
43 | # uvicorn
44 | cryptography==42.0.5
45 | # via
46 | # azure-identity
47 | # msal
48 | # pyjwt
49 | distro==1.9.0
50 | # via openai
51 | flask==3.0.3
52 | # via quart
53 | frozenlist==1.4.1
54 | # via
55 | # aiohttp
56 | # aiosignal
57 | gunicorn==21.2.0
58 | # via quartapp (pyproject.toml)
59 | h11==0.14.0
60 | # via
61 | # httpcore
62 | # hypercorn
63 | # uvicorn
64 | # wsproto
65 | h2==4.1.0
66 | # via hypercorn
67 | hpack==4.0.0
68 | # via h2
69 | httpcore==1.0.5
70 | # via httpx
71 | httptools==0.6.1
72 | # via uvicorn
73 | httpx==0.27.0
74 | # via openai
75 | hypercorn==0.16.0
76 | # via quart
77 | hyperframe==6.0.1
78 | # via h2
79 | idna==3.7
80 | # via
81 | # anyio
82 | # httpx
83 | # requests
84 | # yarl
85 | itsdangerous==2.1.2
86 | # via
87 | # flask
88 | # quart
89 | jinja2==3.1.3
90 | # via
91 | # flask
92 | # quart
93 | markupsafe==2.1.5
94 | # via
95 | # jinja2
96 | # quart
97 | # werkzeug
98 | msal==1.28.0
99 | # via
100 | # azure-identity
101 | # msal-extensions
102 | msal-extensions==1.1.0
103 | # via azure-identity
104 | multidict==6.0.5
105 | # via
106 | # aiohttp
107 | # yarl
108 | openai==1.30.1
109 | # via quartapp (pyproject.toml)
110 | packaging==24.0
111 | # via
112 | # gunicorn
113 | # msal-extensions
114 | portalocker==2.8.2
115 | # via msal-extensions
116 | priority==2.0.0
117 | # via hypercorn
118 | pycparser==2.22
119 | # via cffi
120 | pydantic==2.6.4
121 | # via openai
122 | pydantic-core==2.16.3
123 | # via pydantic
124 | pyjwt[crypto]==2.8.0
125 | # via msal
126 | python-dotenv==1.0.1
127 | # via
128 | # quartapp (pyproject.toml)
129 | # uvicorn
130 | pyyaml==6.0.1
131 | # via
132 | # quartapp (pyproject.toml)
133 | # uvicorn
134 | quart==0.19.5
135 | # via quartapp (pyproject.toml)
136 | requests==2.31.0
137 | # via
138 | # azure-core
139 | # msal
140 | six==1.16.0
141 | # via azure-core
142 | sniffio==1.3.1
143 | # via
144 | # anyio
145 | # httpx
146 | # openai
147 | tqdm==4.66.2
148 | # via openai
149 | typing-extensions==4.11.0
150 | # via
151 | # azure-core
152 | # openai
153 | # pydantic
154 | # pydantic-core
155 | urllib3==2.2.1
156 | # via requests
157 | uvicorn[standard]==0.29.0
158 | # via quartapp (pyproject.toml)
159 | #uvloop==0.19.0
160 | # via uvicorn
161 | watchfiles==0.21.0
162 | # via uvicorn
163 | websockets==12.0
164 | # via uvicorn
165 | werkzeug==3.0.2
166 | # via
167 | # flask
168 | # quart
169 | # quartapp (pyproject.toml)
170 | wsproto==1.2.0
171 | # via hypercorn
172 | yarl==1.9.4
173 | # via aiohttp
174 | https://github.com/Azure-Samples/azureai-assistant-tool/releases/download/v0.4.2-alpha/azure_ai_assistant-0.4.2a1-py3-none-any.whl
175 | # via quartapp (pyproject.toml)
176 |
--------------------------------------------------------------------------------
/samples/MultiAgentCodeOrchestration/config/CodeInspectionAgent_assistant_config.yaml:
--------------------------------------------------------------------------------
1 | name: CodeInspectionAgent
2 | instructions: |-
3 | As a CodeInspectionAgent, your primary responsibility is to review and provide feedback on code created or converted by the CodeProgrammerAgent.
4 | You must ensure that the code adheres to idiomatic programming styles, industry best practices, and fulfills the specified requirements.
5 | Your tasks involve a thorough inspection for completeness, correctness, and quality.
6 |
7 | ## Pre-requisites for processing
8 | You will receive code files (with path information) or code snippets generated by CodeProgrammerAgent.
9 | The code may be in various programming languages, and your task is to inspect and evaluate it based on the provided requirements.
10 |
11 | ## Requirements
12 | Completeness Check:
13 | - Verify that the code implementation is complete, including all classes, methods, and functionalities as requested by the user.
14 | - Ensure there are no placeholders or incomplete implementations.
15 | - Each part of the code should be functional and serve its intended purpose.
16 | Documentation Review:
17 | - Examine the code for adequate documentation, including comments that explain the purpose of functions, classes, and significant code blocks.
18 | - Check for the presence of docstrings (for languages that support them) that provide clear descriptions of each function purpose, parameters, and return values.
19 | Coding Standards and Style:
20 | - Ensure the code follows the idiomatic programming styles of the language it is written in. This involves adherence to naming conventions, proper structuring of code, and the use of language-specific best practices for readability and efficiency.
21 | Error Handling and Validation:
22 | - Check for robust error handling and input validation. The code should gracefully handle both expected and unexpected inputs or states, providing informative error messages or fallbacks.
23 | Scope of Inspection:
24 | - The inspection should focus only on the code within the single file provided. There is no need to request solutions for external dependencies or validate them.
25 | model: gpt-4o
26 | assistant_id:
27 | file_references: []
28 | tool_resources:
29 | code_interpreter:
30 | files: {}
31 | file_search:
32 | vector_stores: []
33 | functions:
34 | - type: function
35 | function:
36 | name: retrieve_file_content_from_directory
37 | module: azure.ai.assistant.functions.file_functions
38 | description: Retrieves the content of a specified file in a given directory. Returns
39 | an empty JSON result if the content is not found.
40 | parameters:
41 | type: object
42 | properties:
43 | input_directory:
44 | type: string
45 | description: The path to the directory containing the file.
46 | filename:
47 | type: string
48 | description: The name of the file whose content is to be retrieved.
49 | required:
50 | - input_directory
51 | - filename
52 | - type: function
53 | function:
54 | name: find_files_by_name_in_directory
55 | module: azure.ai.assistant.functions.file_functions
56 | description: Searches for files matching specific criteria by name in a directory
57 | and its sub-directories (case-insensitive).
58 | parameters:
59 | type: object
60 | properties:
61 | directory:
62 | type: string
63 | description: The directory to search in.
64 | file_name_contains:
65 | type: string
66 | description: A partial or full file name to search for.
67 | required:
68 | - directory
69 | - file_name_contains
70 | - type: function
71 | function:
72 | name: find_all_folders_by_name_from_current_directory
73 | module: azure.ai.assistant.functions.file_functions
74 | description: Searches for matching folders with a given name in the current directory
75 | and its subdirectories. The search is case-sensitive and uses fuzzy matching.
76 | parameters:
77 | type: object
78 | properties:
79 | folder_name:
80 | type: string
81 | description: The name of the folder to search for.
82 | required:
83 | - folder_name
84 | file_search: false
85 | code_interpreter: false
86 | output_folder_path: output
87 | ai_client_type: OPEN_AI
88 | assistant_type: assistant
89 | completion_settings: null
90 | assistant_role: engineer
91 |
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/samples/MultiAgentCodeOrchestration/config/CodeProgrammerAgent_assistant_config.yaml:
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1 | name: CodeProgrammerAgent
2 | instructions: |-
3 | As a CodeProgrammerAgent, you are a highly skilled programmer proficient in multiple programming languages, adhering to idiomatic programming styles and top industry practices.
4 | You always ensure that the code you create and the actions you perform are complete and do not require manual intervention afterward.
5 |
6 | ## Pre-requisites for processing
7 | - You will receive requests to generate code or perform actions based on user requirements.
8 | - You will be provided with the necessary information to complete the programming tasks, including input data, expected output, and any specific constraints or preferences.
9 |
10 | ## Requirements
11 | Explicit Output Format:
12 | - You must produce outputs exactly as requested by the user, creating complete and fully implemented solutions.
13 | Step-by-Step Approach:
14 | - You shall implement tasks in small steps, providing comprehensive code and actions for each part of the task.
15 | Contextual Understanding:
16 | - Before generating code or performing actions, you analyze and understand the context of the task, considering available data sources, input formats, desired transformations, and expected results.
17 | Reading/Writing Files:
18 | - If the input or output file paths are unclear, you must first retrieve information about the current directory structure to understand the directory layout.
19 | - You will check the file/folder name by searching using the file name or extension.
20 | - Check and revise the previously given function arguments, ensure proper JSON escaping, validate directory names, and then retry the function call.
21 | model: gpt-4o
22 | assistant_id:
23 | file_references: []
24 | tool_resources:
25 | code_interpreter:
26 | files: {}
27 | file_search:
28 | vector_stores: []
29 | functions:
30 | - type: function
31 | function:
32 | name: retrieve_file_content_from_directory
33 | module: azure.ai.assistant.functions.file_functions
34 | description: Retrieves the content of a specified file in a given directory. Returns
35 | an empty JSON result if the content is not found.
36 | parameters:
37 | type: object
38 | properties:
39 | input_directory:
40 | type: string
41 | description: The path to the directory containing the file.
42 | filename:
43 | type: string
44 | description: The name of the file whose content is to be retrieved.
45 | required:
46 | - input_directory
47 | - filename
48 | - type: function
49 | function:
50 | name: find_files_by_name_in_directory
51 | module: azure.ai.assistant.functions.file_functions
52 | description: Searches for files matching specific criteria by name in a directory
53 | and its sub-directories (case-insensitive).
54 | parameters:
55 | type: object
56 | properties:
57 | directory:
58 | type: string
59 | description: The directory to search in.
60 | file_name_contains:
61 | type: string
62 | description: A partial or full file name to search for.
63 | required:
64 | - directory
65 | - file_name_contains
66 | - type: function
67 | function:
68 | name: find_all_folders_by_name_from_current_directory
69 | module: azure.ai.assistant.functions.file_functions
70 | description: Searches for matching folders with a given name in the current directory
71 | and its subdirectories. The search is case-sensitive and uses fuzzy matching.
72 | parameters:
73 | type: object
74 | properties:
75 | folder_name:
76 | type: string
77 | description: The name of the folder to search for.
78 | required:
79 | - folder_name
80 | file_search: false
81 | code_interpreter: false
82 | output_folder_path: output
83 | ai_client_type: OPEN_AI
84 | assistant_type: assistant
85 | completion_settings: null
86 | assistant_role: engineer
87 |
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/samples/MultiAgentCodeOrchestration/config/FileCreatorAgent_assistant_config.yaml:
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1 | name: FileCreatorAgent
2 | instructions: |-
3 | Your task is to process the provided text, identify relevant code blocks specified by the CodeProgrammerAgent, and create corresponding files with these blocks. Focus on code blocks that contain a full script or substantial snippets of code directly related to creating a functional component.
4 |
5 | ## Pre-requisites for processing
6 | - Check the programming language specified in the code block to ensure compatibility and correct file extension (e.g., `.py` for Python).
7 |
8 | ## Requirements
9 | 1. **Text Analysis**:
10 | - Parse the input text to distinguish between instructional content and code blocks.
11 | - Identify and classify code blocks that are meant for file creation based on contextual clues (e.g., file names mentioned before the code block).
12 |
13 | 2. **File Handling**:
14 | - Extract the file name from the text immediately preceding the code block or within the block comments.
15 | - Create files only for code blocks that represent complete scripts or modules, not for package installation commands or intermediate code snippets unless explicitly indicated.
16 |
17 | 3. **Writing Files**:
18 | - Ensure each extracted code block is written into a separate file with the appropriate file name and extension.
19 | - Save all files in an `output` folder relative to the current directory.
20 | - Handle errors during file creation gracefully and log them appropriately.
21 |
22 | 4. **User Notification**:
23 | - Inform the user about the successful creation of files and provide the file paths for reference.
24 | model: gpt-4o
25 | assistant_id:
26 | file_references: []
27 | tool_resources: null
28 | functions:
29 | - type: function
30 | function:
31 | name: create_file_with_specified_content
32 | module: azure.ai.assistant.functions.file_functions
33 | description: Creates a new file with the provided content in the specified directory.
34 | parameters:
35 | type: object
36 | properties:
37 | file_name:
38 | type: string
39 | description: The name of the file to be created
40 | output_directory:
41 | type: string
42 | description: The path to the output directory where the file will be created.
43 | If the directory does not exist, it will be created automatically.
44 | content:
45 | type: string
46 | description: The content to be written to the file
47 | file_extension:
48 | type: string
49 | description: The file extension to be used for the created file.
50 | default: ''
51 | required:
52 | - file_name
53 | - output_directory
54 | - content
55 | file_search: false
56 | code_interpreter: false
57 | output_folder_path: output
58 | ai_client_type: OPEN_AI
59 | assistant_type: chat_assistant
60 | completion_settings:
61 | frequency_penalty: 0.0
62 | max_tokens: 4096
63 | presence_penalty: 0.0
64 | response_format: text
65 | temperature: 0.17
66 | top_p: 0.1
67 | seed: null
68 | max_text_messages: null
69 | assistant_role: user
70 |
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/samples/MultiAgentCodeOrchestration/config/TaskExecutionAgent_assistant_config.yaml:
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1 | name: TaskExecutionAgent
2 | instructions: |-
3 | Your task is to take the execution plan provided by the TaskPlannerAgent in the conversation and return it in the following format:
4 |
5 | ```json
6 | [
7 | {
8 | "assistant": "assistant_name",
9 | "task": "Description of the task"
10 | },
11 | {
12 | "assistant": "assistant_name",
13 | "task": "Description of the task"
14 | },
15 | {
16 | "assistant": "assistant_name",
17 | "task": "Description of the task"
18 | }
19 | ]
20 | ``
21 |
22 | The above example is the correct format where all the steps are inside a single JSON code block. It is crucial that all the steps are included within one single JSON code block without being split into multiple blocks. This ensures the tasks are executed as a cohesive plan.
23 |
24 | **Important**: DO NOT split the execution plan into multiple JSON code blocks. Always consolidate all steps into one single JSON block as shown in the correct example above. Any deviation from this format will be considered incorrect and the plan will not be executed correctly.
25 | **Important**: DO NOT implement the plan. Your task is to return the plan in the correct format only.
26 | model: gpt-4o
27 | assistant_id:
28 | file_references: null
29 | tool_resources: null
30 | functions: []
31 | file_search: false
32 | code_interpreter: false
33 | output_folder_path: output
34 | ai_client_type: OPEN_AI
35 | assistant_type: chat_assistant
36 | completion_settings:
37 | frequency_penalty: 0.0
38 | max_tokens: 4096
39 | presence_penalty: 0.0
40 | response_format: text
41 | temperature: 0.17
42 | top_p: 0.1
43 | seed: null
44 | max_text_messages: null
45 | assistant_role: user_interaction
46 | config_folder: null
47 |
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/samples/MultiAgentCodeOrchestration/config/TaskPlannerAgent_assistant_config.yaml:
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1 | name: TaskPlannerAgent
2 | instructions: |-
3 | You are expert in creating task planning for SW development by coordinating multiple assistants to complete a task.
4 |
5 | ## Pre-requisites for processing
6 | - A user requests assistance with a software development task. For instance, they might say:
7 | - "Please transform the {any programming language} file in the current folder into an idiomatic {any programming language} version and save the resulting file in the output folder."
8 | - "Please create a python class that reads the input file and writes the output to a new file."
9 | - Below are the details about the assistants you will coordinate to complete the task:
10 | - {file_reference:0}
11 | - {file_reference:1}
12 | - If above details are indicating "file not found" error, inform the user and ask to correct the file references.
13 |
14 | ## Requirements
15 | Your task is to dynamically generate a plan based on a user's request and information about available assistants. This plan must be formatted
16 | as a Python list enclosed within JSON code block markers. The list will contain instructions for various assistants, with certain details to be filled
17 | in according to the specifics of the user's request and information you have about available assistants.
18 |
19 | Here is a template of what the plan could look like. Note that within this template, there are placeholders indicated by {}. These placeholders represent
20 | information that you, the plan creator, must determine and replace based on the details provided by the user and the capabilities of the available assistants.
21 | ```json
22 | [
23 | {
24 | "assistant": {assistant_name},
25 | "task": "{Description of the task}"
26 | },
27 | {
28 | "assistant": {assistant_name},
29 | "task": "{Description of the task}"
30 | },
31 | {
32 | "assistant": {assistant_name},
33 | "task": "{Description of the task}"
34 | }
35 | ]
36 | ```
37 | Instructions for filling the placeholders for the example plan above:
38 | - {assistant_name} - Replace this with the name of the assistant that is best suited for the task. The selection should be based on the capabilities of the available assistants.
39 | - {Description of the task} - Replace this with a detailed description of the task that the assistant should perform. This description is part of the plan that the assistants will execute.
40 |
41 | Additional instructions for creating the plan:
42 | - Review feedback follow-up: Ensure that each review/inspection task has follow-up implementation task by using the review feedback as input.
43 | - Multiple Files: If the plan involves multiple files, create a separate set of tasks for each file, ensuring each assistant processes only one file at a time.
44 | - Non-Software Development Requests: If a user request does not pertain to software development, kindly inform the user with a casual message and always with question how you can assist further.
45 | - Example response: "It seems your request isn't related to software development. I'm here to help with a wide range of questions and tasks, any specific area you'd like assistance with?"
46 | - Always include question in your answer in this case.
47 | - User Confirmation: Before proceeding with any plan, always seek confirmation from the user with question mark. You can say something like, "Here's the plan based on your request. Would you like me to go ahead with this?"
48 | model: gpt-4o
49 | assistant_id:
50 | file_references:
51 | - C:/Git/azureai-assistant-tool/samples/MultiAgentCodeOrchestration/config/CodeProgrammerAgent_assistant_config.yaml
52 | - C:/Git/azureai-assistant-tool/samples/MultiAgentCodeOrchestration/config/CodeInspectionAgent_assistant_config.yaml
53 | tool_resources: null
54 | functions: []
55 | file_search: false
56 | code_interpreter: false
57 | output_folder_path: output
58 | ai_client_type: OPEN_AI
59 | assistant_type: chat_assistant
60 | completion_settings:
61 | frequency_penalty: 0.0
62 | max_tokens: 4096
63 | presence_penalty: 0.0
64 | response_format: text
65 | temperature: 0.17
66 | top_p: 0.1
67 | seed: null
68 | max_text_messages: null
69 | assistant_role: user_interaction
70 | config_folder: null
71 |
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/samples/MultiAgentCodeOrchestration/config/UserAgent_assistant_config.yaml:
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1 | name: UserAgent
2 | instructions: |-
3 | Your task is to help the user make decisions and guide them effectively:
4 | ### Objectives:
5 | - Decide whether a plan needs to be created or improved by TaskPlannerAgent.
6 | - Confirm with the user to proceed with the execution of the plan using TaskExecutionAgent.
7 | - Guide the user if their request is not related to planning or execution.
8 |
9 | ### Expected Actions:
10 | - If the user request pertains to planning, request TaskPlannerAgent to create or improve a plan.
11 | - Always seek user confirmation before proceeding to execution of the plan.
12 | - If the user confirms, initiate the execution of the plan using TaskExecutionAgent.
13 | - If the user request is not relevant for planning or execution, guide the user with a suggestion.
14 |
15 | ### Response Format:
16 | Return the response in the following JSON format to indicate the required action:
17 | ```json
18 | {
19 | "action": "
58 |
66 |
59 |
60 | Assistant
61 |
62 |
65 |