autogen/python/uv.lock

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version = 1
requires-python = ">=3.10, <3.13"
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2024-09-30 10:54:41 -04:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
version = "24.1.0"
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2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
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chromadb = [
{ name = "chromadb" },
]
diskcache = [
{ name = "diskcache" },
]
docker = [
{ name = "asyncio-atexit" },
{ name = "docker" },
]
file-surfer = [
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{ name = "autogen-agentchat" },
{ name = "markitdown" },
]
gemini = [
{ name = "google-genai" },
]
Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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graphrag = [
{ name = "graphrag" },
]
grpc = [
{ name = "grpcio" },
]
http-tool = [
{ name = "httpx" },
{ name = "json-schema-to-pydantic" },
]
jupyter-executor = [
{ name = "ipykernel" },
{ name = "nbclient" },
]
langchain = [
{ name = "langchain-core" },
]
Feature add Add LlamaCppChatCompletionClient and llama-cpp (#5326) This pull request introduces the integration of the `llama-cpp` library into the `autogen-ext` package, with significant changes to the project dependencies and the implementation of a new chat completion client. The most important changes include updating the project dependencies, adding a new module for the `LlamaCppChatCompletionClient`, and implementing the client with various functionalities. ### Project Dependencies: * [`python/packages/autogen-ext/pyproject.toml`](diffhunk://#diff-095119d4420ff09059557bd25681211d1772c2be0fbe0ff2d551a3726eff1b4bR34-R38): Added `llama-cpp-python` as a new dependency under the `llama-cpp` section. ### New Module: * [`python/packages/autogen-ext/src/autogen_ext/models/llama_cpp/__init__.py`](diffhunk://#diff-42ae3ba17d51ca917634c4ea3c5969cf930297c288a783f8d9c126f2accef71dR1-R8): Introduced the `LlamaCppChatCompletionClient` class and handled import errors with a descriptive message for missing dependencies. ### Implementation of `LlamaCppChatCompletionClient`: * `python/packages/autogen-ext/src/autogen_ext/models/llama_cpp/_llama_cpp_completion_client.py`: - Added the `LlamaCppChatCompletionClient` class with methods to initialize the client, create chat completions, detect and execute tools, and handle streaming responses. - Included detailed logging for debugging purposes and implemented methods to count tokens, track usage, and provide model information.…d chat capabilities <!-- 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. --> ## Related issue number <!-- For example: "Closes #1234" --> ## Checks - [X ] 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. - [X ] I've added tests (if relevant) corresponding to the changes introduced in this PR. - [ X] I've made sure all auto checks have passed. --------- Co-authored-by: aribornstein <x@x.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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llama-cpp = [
{ name = "llama-cpp-python" },
]
magentic-one = [
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{ name = "autogen-agentchat" },
{ name = "markitdown" },
{ name = "pillow" },
{ name = "playwright" },
]
mcp = [
{ name = "json-schema-to-pydantic" },
{ name = "mcp" },
]
5663 ollama client host (#5674) @ekzhu should likely be assigned as reviewer ## Why are these changes needed? These changes address the bug reported in #5663. Prevents TypeError from being thrown at inference time by ollama AsyncClient when `host` (and other) kwargs are passed to autogen OllamaChatCompletionClient constructor. It also adds ollama as a named optional extra so that the ollama requirements can be installed alongside autogen-ext (e.g. `pip install autogen-ext[ollama]` @ekzhu, I will need some help or guidance to ensure that the associated test (which requires ollama and tiktoken as dependencies of the OllamaChatCompletionClient) can run successfully in autogen's test execution environment. I have also left the "I've made sure all auto checks have passed" check below unchecked as this PR is coming from my fork. (UPDATE: auto checks appear to have passed after opening PR, so I have checked box below) ## Related issue number Intended to close #5663 ## Checks - [x] I've included any doc changes needed for <https://microsoft.github.io/autogen/>. See <https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to build and test documentation locally. - [x] I've added tests (if relevant) corresponding to the changes introduced in this PR. - [x] I've made sure all auto checks have passed. --------- Co-authored-by: Ryan Stewart <ryanstewart@Ryans-MacBook-Pro.local> Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com> Co-authored-by: peterychang <49209570+peterychang@users.noreply.github.com>
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ollama = [
{ name = "ollama" },
{ name = "tiktoken" },
]
openai = [
{ name = "aiofiles" },
{ name = "openai" },
{ name = "tiktoken" },
]
redis = [
{ name = "redis" },
]
rich = [
{ name = "rich" },
]
semantic-kernel-all = [
{ name = "semantic-kernel", extra = ["anthropic", "aws", "dapr", "google", "hugging-face", "mistralai", "ollama", "onnx", "pandas", "usearch"] },
]
semantic-kernel-anthropic = [
{ name = "semantic-kernel", extra = ["anthropic"] },
]
semantic-kernel-aws = [
{ name = "semantic-kernel", extra = ["aws"] },
]
semantic-kernel-core = [
{ name = "semantic-kernel" },
]
semantic-kernel-dapr = [
{ name = "semantic-kernel", extra = ["dapr"] },
]
semantic-kernel-google = [
{ name = "semantic-kernel", extra = ["google"] },
]
semantic-kernel-hugging-face = [
{ name = "semantic-kernel", extra = ["hugging-face"] },
]
semantic-kernel-mistralai = [
{ name = "semantic-kernel", extra = ["mistralai"] },
]
semantic-kernel-ollama = [
{ name = "semantic-kernel", extra = ["ollama"] },
]
semantic-kernel-onnx = [
{ name = "semantic-kernel", extra = ["onnx"] },
]
semantic-kernel-pandas = [
{ name = "semantic-kernel", extra = ["pandas"] },
]
Task-Centric Memory (#5227) _(EXPERIMENTAL, RESEARCH IN PROGRESS)_ In 2023 AutoGen introduced [Teachable Agents](https://microsoft.github.io/autogen/0.2/blog/2023/10/26/TeachableAgent/) that users could teach new facts, preferences and skills. But teachable agents were limited in several ways: They could only be `ConversableAgent` subclasses, they couldn't learn a new skill unless the user stated (in a single turn) both the task and how to solve it, and they couldn't learn on their own. **Task-Centric Memory** overcomes these limitations, allowing users to teach arbitrary agents (or teams) more flexibly and reliably, and enabling agents to learn from their own trial-and-error experiences. This PR is large and complex. All of the files are new, and most of the added components depend on the others to run at all. But the review process can be accelerated if approached in the following order. 1. Start with the [Task-Centric Memory README](https://github.com/microsoft/autogen/tree/agentic_memory/python/packages/autogen-ext/src/autogen_ext/task_centric_memory). 1. Install the memory extension locally, since it won't be in pypi until it's merged. In the `agentic_memory` branch, and the `python/packages` directory: - `pip install -e autogen-agentchat` - `pip install -e autogen-ext[openai]` - `pip install -e autogen-ext[task-centric-memory]` 2. Run the Quickstart sample code, then immediately open the `./pagelogs/quick/0 Call Tree.html` file in a browser to view the work in progress. 3. Click through the web page links to see the details. 2. Continue through the rest of the main README to get a high-level overview of the architecture. 3. Read through the [code samples README](https://github.com/microsoft/autogen/tree/agentic_memory/python/samples/task_centric_memory), running each of the 4 code samples while viewing their page logs. 4. Skim through the 4 code samples, along with their corresponding yaml config files: 1. `chat_with_teachable_agent.py` 2. `eval_retrieval.py` 3. `eval_teachability.py` 4. `eval_learning_from_demonstration.py` 5. `eval_self_teaching.py` 6. Read `task_centric_memory_controller.py`, referring back to the previously generated page logs as needed. This is the most important and complex file in the PR. 7. Read the remaining core files. 1. `_task_centric_memory_bank.py` 2. `_string_similarity_map.py` 3. `_prompter.py` 8. Read the supporting files in the utils dir. 1. `teachability.py` 2. `apprentice.py` 3. `grader.py` 4. `page_logger.py` 5. `_functions.py`
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task-centric-memory = [
{ name = "chromadb" },
]
video-surfer = [
{ name = "autogen-agentchat" },
{ name = "ffmpeg-python" },
{ name = "openai-whisper" },
{ name = "opencv-python" },
]
web-surfer = [
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{ name = "autogen-agentchat" },
{ name = "markitdown" },
{ name = "pillow" },
{ name = "playwright" },
]
[package.dev-dependencies]
dev = [
{ name = "autogen-test-utils" },
{ name = "httpx" },
{ name = "langchain-experimental" },
Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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{ name = "pandas-stubs" },
]
[package.metadata]
requires-dist = [
{ name = "aiofiles", marker = "extra == 'openai'" },
{ name = "asyncio-atexit", marker = "extra == 'docker'", specifier = ">=1.0.1" },
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{ name = "autogen-agentchat", marker = "extra == 'file-surfer'", editable = "packages/autogen-agentchat" },
{ name = "autogen-agentchat", marker = "extra == 'magentic-one'", editable = "packages/autogen-agentchat" },
{ name = "autogen-agentchat", marker = "extra == 'video-surfer'", editable = "packages/autogen-agentchat" },
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{ name = "autogen-agentchat", marker = "extra == 'web-surfer'", editable = "packages/autogen-agentchat" },
{ name = "autogen-core", editable = "packages/autogen-core" },
{ name = "azure-ai-inference", marker = "extra == 'azure'", specifier = ">=1.0.0b7" },
{ name = "azure-core", marker = "extra == 'azure'" },
{ name = "azure-identity", marker = "extra == 'azure'" },
Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
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{ name = "chromadb", marker = "extra == 'chromadb'" },
{ name = "chromadb", marker = "extra == 'task-centric-memory'", specifier = ">=0.6.3" },
{ name = "diskcache", marker = "extra == 'diskcache'", specifier = ">=5.6.3" },
{ name = "docker", marker = "extra == 'docker'", specifier = "~=7.0" },
{ name = "ffmpeg-python", marker = "extra == 'video-surfer'" },
{ name = "google-genai", marker = "extra == 'gemini'", specifier = ">=1.0.0" },
Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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{ name = "graphrag", marker = "extra == 'graphrag'", specifier = ">=1.0.1" },
{ name = "grpcio", marker = "extra == 'grpc'", specifier = "~=1.70.0" },
{ name = "httpx", marker = "extra == 'http-tool'", specifier = ">=0.27.0" },
{ name = "ipykernel", marker = "extra == 'jupyter-executor'", specifier = ">=6.29.5" },
{ name = "json-schema-to-pydantic", marker = "extra == 'http-tool'", specifier = ">=0.2.0" },
{ name = "json-schema-to-pydantic", marker = "extra == 'mcp'", specifier = ">=0.2.2" },
{ name = "langchain-core", marker = "extra == 'langchain'", specifier = "~=0.3.3" },
{ name = "llama-cpp-python", marker = "extra == 'llama-cpp'", specifier = ">=0.3.8" },
{ name = "markitdown", marker = "extra == 'file-surfer'", specifier = "~=0.0.1" },
{ name = "markitdown", marker = "extra == 'magentic-one'", specifier = "~=0.0.1" },
{ name = "markitdown", marker = "extra == 'web-surfer'", specifier = "~=0.0.1" },
{ name = "mcp", marker = "extra == 'mcp'", specifier = ">=1.5.0" },
{ name = "nbclient", marker = "extra == 'jupyter-executor'", specifier = ">=0.10.2" },
5663 ollama client host (#5674) @ekzhu should likely be assigned as reviewer ## Why are these changes needed? These changes address the bug reported in #5663. Prevents TypeError from being thrown at inference time by ollama AsyncClient when `host` (and other) kwargs are passed to autogen OllamaChatCompletionClient constructor. It also adds ollama as a named optional extra so that the ollama requirements can be installed alongside autogen-ext (e.g. `pip install autogen-ext[ollama]` @ekzhu, I will need some help or guidance to ensure that the associated test (which requires ollama and tiktoken as dependencies of the OllamaChatCompletionClient) can run successfully in autogen's test execution environment. I have also left the "I've made sure all auto checks have passed" check below unchecked as this PR is coming from my fork. (UPDATE: auto checks appear to have passed after opening PR, so I have checked box below) ## Related issue number Intended to close #5663 ## Checks - [x] I've included any doc changes needed for <https://microsoft.github.io/autogen/>. See <https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to build and test documentation locally. - [x] I've added tests (if relevant) corresponding to the changes introduced in this PR. - [x] I've made sure all auto checks have passed. --------- Co-authored-by: Ryan Stewart <ryanstewart@Ryans-MacBook-Pro.local> Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com> Co-authored-by: peterychang <49209570+peterychang@users.noreply.github.com>
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{ name = "ollama", marker = "extra == 'ollama'", specifier = ">=0.4.7" },
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{ name = "openai-whisper", marker = "extra == 'video-surfer'" },
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5663 ollama client host (#5674) @ekzhu should likely be assigned as reviewer ## Why are these changes needed? These changes address the bug reported in #5663. Prevents TypeError from being thrown at inference time by ollama AsyncClient when `host` (and other) kwargs are passed to autogen OllamaChatCompletionClient constructor. It also adds ollama as a named optional extra so that the ollama requirements can be installed alongside autogen-ext (e.g. `pip install autogen-ext[ollama]` @ekzhu, I will need some help or guidance to ensure that the associated test (which requires ollama and tiktoken as dependencies of the OllamaChatCompletionClient) can run successfully in autogen's test execution environment. I have also left the "I've made sure all auto checks have passed" check below unchecked as this PR is coming from my fork. (UPDATE: auto checks appear to have passed after opening PR, so I have checked box below) ## Related issue number Intended to close #5663 ## Checks - [x] I've included any doc changes needed for <https://microsoft.github.io/autogen/>. See <https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to build and test documentation locally. - [x] I've added tests (if relevant) corresponding to the changes introduced in this PR. - [x] I've made sure all auto checks have passed. --------- Co-authored-by: Ryan Stewart <ryanstewart@Ryans-MacBook-Pro.local> Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com> Co-authored-by: peterychang <49209570+peterychang@users.noreply.github.com>
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Feature add Add LlamaCppChatCompletionClient and llama-cpp (#5326) This pull request introduces the integration of the `llama-cpp` library into the `autogen-ext` package, with significant changes to the project dependencies and the implementation of a new chat completion client. The most important changes include updating the project dependencies, adding a new module for the `LlamaCppChatCompletionClient`, and implementing the client with various functionalities. ### Project Dependencies: * [`python/packages/autogen-ext/pyproject.toml`](diffhunk://#diff-095119d4420ff09059557bd25681211d1772c2be0fbe0ff2d551a3726eff1b4bR34-R38): Added `llama-cpp-python` as a new dependency under the `llama-cpp` section. ### New Module: * [`python/packages/autogen-ext/src/autogen_ext/models/llama_cpp/__init__.py`](diffhunk://#diff-42ae3ba17d51ca917634c4ea3c5969cf930297c288a783f8d9c126f2accef71dR1-R8): Introduced the `LlamaCppChatCompletionClient` class and handled import errors with a descriptive message for missing dependencies. ### Implementation of `LlamaCppChatCompletionClient`: * `python/packages/autogen-ext/src/autogen_ext/models/llama_cpp/_llama_cpp_completion_client.py`: - Added the `LlamaCppChatCompletionClient` class with methods to initialize the client, create chat completions, detect and execute tools, and handle streaming responses. - Included detailed logging for debugging purposes and implemented methods to count tokens, track usage, and provide model information.…d chat capabilities <!-- 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. --> ## Related issue number <!-- For example: "Closes #1234" --> ## Checks - [X ] 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. - [X ] I've added tests (if relevant) corresponding to the changes introduced in this PR. - [ X] I've made sure all auto checks have passed. --------- Co-authored-by: aribornstein <x@x.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-11 01:53:53 +02:00
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Feature add Add LlamaCppChatCompletionClient and llama-cpp (#5326) This pull request introduces the integration of the `llama-cpp` library into the `autogen-ext` package, with significant changes to the project dependencies and the implementation of a new chat completion client. The most important changes include updating the project dependencies, adding a new module for the `LlamaCppChatCompletionClient`, and implementing the client with various functionalities. ### Project Dependencies: * [`python/packages/autogen-ext/pyproject.toml`](diffhunk://#diff-095119d4420ff09059557bd25681211d1772c2be0fbe0ff2d551a3726eff1b4bR34-R38): Added `llama-cpp-python` as a new dependency under the `llama-cpp` section. ### New Module: * [`python/packages/autogen-ext/src/autogen_ext/models/llama_cpp/__init__.py`](diffhunk://#diff-42ae3ba17d51ca917634c4ea3c5969cf930297c288a783f8d9c126f2accef71dR1-R8): Introduced the `LlamaCppChatCompletionClient` class and handled import errors with a descriptive message for missing dependencies. ### Implementation of `LlamaCppChatCompletionClient`: * `python/packages/autogen-ext/src/autogen_ext/models/llama_cpp/_llama_cpp_completion_client.py`: - Added the `LlamaCppChatCompletionClient` class with methods to initialize the client, create chat completions, detect and execute tools, and handle streaming responses. - Included detailed logging for debugging purposes and implemented methods to count tokens, track usage, and provide model information.…d chat capabilities <!-- 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. --> ## Related issue number <!-- For example: "Closes #1234" --> ## Checks - [X ] 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. - [X ] I've added tests (if relevant) corresponding to the changes introduced in this PR. - [ X] I've made sure all auto checks have passed. --------- Co-authored-by: aribornstein <x@x.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-11 01:53:53 +02:00
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Feature add Add LlamaCppChatCompletionClient and llama-cpp (#5326) This pull request introduces the integration of the `llama-cpp` library into the `autogen-ext` package, with significant changes to the project dependencies and the implementation of a new chat completion client. The most important changes include updating the project dependencies, adding a new module for the `LlamaCppChatCompletionClient`, and implementing the client with various functionalities. ### Project Dependencies: * [`python/packages/autogen-ext/pyproject.toml`](diffhunk://#diff-095119d4420ff09059557bd25681211d1772c2be0fbe0ff2d551a3726eff1b4bR34-R38): Added `llama-cpp-python` as a new dependency under the `llama-cpp` section. ### New Module: * [`python/packages/autogen-ext/src/autogen_ext/models/llama_cpp/__init__.py`](diffhunk://#diff-42ae3ba17d51ca917634c4ea3c5969cf930297c288a783f8d9c126f2accef71dR1-R8): Introduced the `LlamaCppChatCompletionClient` class and handled import errors with a descriptive message for missing dependencies. ### Implementation of `LlamaCppChatCompletionClient`: * `python/packages/autogen-ext/src/autogen_ext/models/llama_cpp/_llama_cpp_completion_client.py`: - Added the `LlamaCppChatCompletionClient` class with methods to initialize the client, create chat completions, detect and execute tools, and handle streaming responses. - Included detailed logging for debugging purposes and implemented methods to count tokens, track usage, and provide model information.…d chat capabilities <!-- 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. --> ## Related issue number <!-- For example: "Closes #1234" --> ## Checks - [X ] 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. - [X ] I've added tests (if relevant) corresponding to the changes introduced in this PR. - [ X] I've made sure all auto checks have passed. --------- Co-authored-by: aribornstein <x@x.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-11 01:53:53 +02:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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Add ChromaDBVectorMemory in Extensions (#5308) <!-- 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.
2025-03-01 07:41:01 -08:00
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2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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Graphrag integration (#4612) * add initial global search draft * add graphrag dep * fix local search embedding * linting * add from config constructor * remove draft notebook * update config factory and add docstrings * add graphrag sample * add sample prompts * update readme * update deps * Add API docs * Update python/samples/agentchat_graphrag/requirements.txt * Update python/samples/agentchat_graphrag/requirements.txt * update docstrings with snippet and doc ref * lint * improve set up instructions in docstring * lint * update lock * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * add unit tests * update lock * update uv lock * add docstring newlines * stubs and typing on graphrag tests * fix docstrings * fix mypy error * + linting and type fixes * type fix graphrag sample * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_global_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/packages/autogen-ext/src/autogen_ext/tools/graphrag/_local_search.py Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * Update python/samples/agentchat_graphrag/requirements.txt Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com> * update overrides * fix docstring client imports * additional docstring fix * add docstring missing import * use openai and fix db path * use console for displaying messages * add model config and gitignore * update readme * lint * Update python/samples/agentchat_graphrag/README.md * Update python/samples/agentchat_graphrag/README.md * Comment remaining azure config --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com> Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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2025-01-15 21:04:17 +10:00
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