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78ef148c88
<!-- Thank you for your contribution! Please review https://microsoft.github.io/autogen/docs/Contribute before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? <!-- Please give a short summary of the change and the problem this solves. --> Shows an example of how to use the `Memory` interface to implement a just-in-time vector memory based on chromadb. ```python import os from pathlib import Path from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.ui import Console from autogen_core.memory import MemoryContent, MemoryMimeType from autogen_ext.memory.chromadb import ChromaDBVectorMemory, PersistentChromaDBVectorMemoryConfig from autogen_ext.models.openai import OpenAIChatCompletionClient # Initialize ChromaDB memory with custom config chroma_user_memory = ChromaDBVectorMemory( config=PersistentChromaDBVectorMemoryConfig( collection_name="preferences", persistence_path=os.path.join(str(Path.home()), ".chromadb_autogen"), k=2, # Return top k results score_threshold=0.4, # Minimum similarity score ) ) # a HttpChromaDBVectorMemoryConfig is also supported for connecting to a remote ChromaDB server # Add user preferences to memory await chroma_user_memory.add( MemoryContent( content="The weather should be in metric units", mime_type=MemoryMimeType.TEXT, metadata={"category": "preferences", "type": "units"}, ) ) await chroma_user_memory.add( MemoryContent( content="Meal recipe must be vegan", mime_type=MemoryMimeType.TEXT, metadata={"category": "preferences", "type": "dietary"}, ) ) # Create assistant agent with ChromaDB memory assistant_agent = AssistantAgent( name="assistant_agent", model_client=OpenAIChatCompletionClient( model="gpt-4o", ), tools=[get_weather], memory=[user_memory], ) stream = assistant_agent.run_stream(task="What is the weather in New York?") await Console(stream) await user_memory.close() ``` ```txt ---------- user ---------- What is the weather in New York? ---------- assistant_agent ---------- [MemoryContent(content='The weather should be in metric units', mime_type='MemoryMimeType.TEXT', metadata={'category': 'preferences', 'mime_type': 'MemoryMimeType.TEXT', 'type': 'units', 'score': 0.4342913043162201, 'id': '8a8d683c-5866-41e1-ac17-08c4fda6da86'}), MemoryContent(content='The weather should be in metric units', mime_type='MemoryMimeType.TEXT', metadata={'category': 'preferences', 'mime_type': 'MemoryMimeType.TEXT', 'type': 'units', 'score': 0.4342913043162201, 'id': 'f27af42c-cb63-46f0-b26b-ffcc09955ca1'})] ---------- assistant_agent ---------- [FunctionCall(id='call_a8U3YEj2dxA065vyzdfXDtNf', arguments='{"city":"New York","units":"metric"}', name='get_weather')] ---------- assistant_agent ---------- [FunctionExecutionResult(content='The weather in New York is 23 °C and Sunny.', call_id='call_a8U3YEj2dxA065vyzdfXDtNf', is_error=False)] ---------- assistant_agent ---------- The weather in New York is 23 °C and Sunny. ``` Note that MemoryContent object in the MemoryQuery events have useful metadata like the score and id retrieved memories. ## Related issue number <!-- For example: "Closes #1234" --> ## Checks - [ ] I've included any doc changes needed for https://microsoft.github.io/autogen/. See https://microsoft.github.io/autogen/docs/Contribute#documentation to build and test documentation locally. - [ ] I've added tests (if relevant) corresponding to the changes introduced in this PR. - [ ] I've made sure all auto checks have passed.
175 lines
3.5 KiB
TOML
175 lines
3.5 KiB
TOML
[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[project]
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name = "autogen-ext"
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version = "0.4.8"
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license = {file = "LICENSE-CODE"}
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description = "AutoGen extensions library"
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readme = "README.md"
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requires-python = ">=3.10"
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classifiers = [
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"Programming Language :: Python :: 3",
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"License :: OSI Approved :: MIT License",
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"Operating System :: OS Independent",
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]
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dependencies = [
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"autogen-core==0.4.8",
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]
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[project.optional-dependencies]
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langchain = ["langchain_core~= 0.3.3"]
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azure = [
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"azure-ai-inference>=1.0.0b7",
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"azure-core",
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"azure-identity",
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]
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docker = ["docker~=7.0", "asyncio_atexit>=1.0.1"]
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ollama = ["ollama>=0.4.7", "tiktoken>=0.8.0"]
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openai = ["openai>=1.52.2", "tiktoken>=0.8.0", "aiofiles"]
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file-surfer = [
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"autogen-agentchat==0.4.8",
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"markitdown>=0.0.1a2",
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]
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graphrag = ["graphrag>=1.0.1"]
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chromadb = ["chromadb"]
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web-surfer = [
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"autogen-agentchat==0.4.8",
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"playwright>=1.48.0",
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"pillow>=11.0.0",
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"markitdown>=0.0.1a2",
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]
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magentic-one = [
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"autogen-agentchat==0.4.8",
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"markitdown>=0.0.1a2",
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"playwright>=1.48.0",
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"pillow>=11.0.0",
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]
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video-surfer = [
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"autogen-agentchat==0.4.8",
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"opencv-python>=4.5",
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"ffmpeg-python",
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"openai-whisper",
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]
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diskcache = [
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"diskcache>=5.6.3"
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]
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redis = [
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"redis>=5.2.1"
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]
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grpc = [
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"grpcio~=1.70.0",
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]
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jupyter-executor = [
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"ipykernel>=6.29.5",
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"nbclient>=0.10.2",
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]
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semantic-kernel-core = [
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"semantic-kernel>=1.17.1",
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]
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gemini = [
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"google-genai>=1.0.0",
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]
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semantic-kernel-google = [
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"semantic-kernel[google]>=1.17.1",
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]
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semantic-kernel-hugging-face = [
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"semantic-kernel[hugging_face]>=1.17.1",
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]
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semantic-kernel-mistralai = [
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"semantic-kernel[mistralai]>=1.17.1",
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]
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semantic-kernel-ollama = [
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"semantic-kernel[ollama]>=1.17.1",
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]
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semantic-kernel-onnx = [
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"semantic-kernel[onnx]>=1.17.1",
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]
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semantic-kernel-anthropic = [
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"semantic-kernel[anthropic]>=1.17.1",
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]
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semantic-kernel-pandas = [
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"semantic-kernel[pandas]>=1.17.1",
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]
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semantic-kernel-aws = [
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"semantic-kernel[aws]>=1.17.1",
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]
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semantic-kernel-dapr = [
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"semantic-kernel[dapr]>=1.17.1",
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]
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http-tool = [
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"httpx>=0.27.0",
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"json-schema-to-pydantic>=0.2.0"
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]
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semantic-kernel-all = [
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"semantic-kernel[google,hugging_face,mistralai,ollama,onnx,anthropic,usearch,pandas,aws,dapr]>=1.17.1",
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]
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rich = ["rich>=13.9.4"]
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mcp = [
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"mcp>=1.1.3",
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"json-schema-to-pydantic>=0.2.2"
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]
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[tool.hatch.build.targets.wheel]
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packages = ["src/autogen_ext"]
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[dependency-groups]
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dev = [
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"autogen_test_utils",
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"langchain-experimental",
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"pandas-stubs>=2.2.3.241126",
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"httpx>=0.28.1",
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]
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[tool.ruff]
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extend = "../../pyproject.toml"
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include = ["src/**", "tests/*.py"]
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exclude = ["src/autogen_ext/agents/web_surfer/*.js", "src/autogen_ext/runtimes/grpc/protos", "tests/protos"]
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[tool.pyright]
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extends = "../../pyproject.toml"
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include = ["src", "tests"]
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exclude = ["src/autogen_ext/runtimes/grpc/protos", "tests/protos"]
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[tool.pytest.ini_options]
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minversion = "6.0"
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testpaths = ["tests"]
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markers = [
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"grpc",
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]
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[tool.poe]
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include = "../../shared_tasks.toml"
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[tool.poe.tasks]
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test.sequence = [
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"playwright install",
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"pytest -n 1 --cov=src --cov-report=term-missing --cov-report=xml",
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]
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test.default_item_type = "cmd"
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test-grpc = "pytest -n 1 --cov=src --cov-report=term-missing --cov-report=xml --grpc"
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mypy = "mypy --config-file ../../pyproject.toml --exclude src/autogen_ext/runtimes/grpc/protos --exclude tests/protos src tests"
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[tool.mypy]
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[[tool.mypy.overrides]]
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module = "docker.*"
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ignore_missing_imports = true
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