Merge branch 'main' into issue/3538-chroma-embeddings-hyperlink

autogen/agentchat/contrib/vectordb/chromadb.py

@@ -14,6 +14,11 @@
 except ImportError:
     raise ImportError("Please install chromadb: `pip install chromadb`")
 
+try:
+    from chromadb.errors import ChromaError
+except ImportError:
+    ChromaError = Exception
+
 CHROMADB_MAX_BATCH_SIZE = os.environ.get("CHROMADB_MAX_BATCH_SIZE", 40000)
 logger = get_logger(__name__)
 
@@ -84,7 +89,7 @@ def create_collection(
                 collection = self.active_collection
             else:
                 collection = self.client.get_collection(collection_name, embedding_function=self.embedding_function)
-        except ValueError:
+        except (ValueError, ChromaError):
             collection = None
         if collection is None:
             return self.client.create_collection(

notebook/agentchat_RetrieveChat.ipynb

@@ -31,6 +31,8 @@
     "pip install pyautogen[retrievechat] flaml[automl]\n",
     "```\n",
     "\n",
+    "*You'll need to install `chromadb<=0.5.0` if you see issue like [#3551](https://github.com/microsoft/autogen/issues/3551).*\n",
+    "\n",
     "For more information, please refer to the [installation guide](/docs/installation/).\n",
     ":::\n",
     "````"
@@ -2785,7 +2787,7 @@
    ]
   },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "autogen312",
    "language": "python",
    "name": "python3"
   },

test/agentchat/contrib/vectordb/test_chromadb.py

@@ -15,6 +15,11 @@
 else:
     skip = False
 
+try:
+    from chromadb.errors import ChromaError
+except ImportError:
+    ChromaError = Exception
+
 
 @pytest.mark.skipif(skip, reason="dependency is not installed")
 def test_chromadb():
@@ -26,12 +31,14 @@ def test_chromadb():
 
     # test_delete_collection
     db.delete_collection(collection_name)
-    pytest.raises(ValueError, db.get_collection, collection_name)
+    pytest.raises((ValueError, ChromaError), db.get_collection, collection_name)
 
     # test more create collection
     collection = db.create_collection(collection_name, overwrite=False, get_or_create=False)
     assert collection.name == collection_name
-    pytest.raises(ValueError, db.create_collection, collection_name, overwrite=False, get_or_create=False)
+    pytest.raises(
+        (ValueError, ChromaError), db.create_collection, collection_name, overwrite=False, get_or_create=False
+    )
     collection = db.create_collection(collection_name, overwrite=True, get_or_create=False)
     assert collection.name == collection_name
     collection = db.create_collection(collection_name, overwrite=False, get_or_create=True)

website/blog/2023-10-18-RetrieveChat/index.mdx

@@ -4,7 +4,7 @@ authors: thinkall
 tags: [LLM, RAG]
 ---
 
-*Last update: August 14, 2024; AutoGen version: v0.2.35*
+*Last update: September 23, 2024; AutoGen version: v0.2.35*
 
 ![RAG Architecture](img/retrievechat-arch.png)
 
@@ -57,6 +57,8 @@ Please install pyautogen with the [retrievechat] option before using RAG agents.
 pip install "pyautogen[retrievechat]"
 ```
 
+*You'll need to install `chromadb<=0.5.0` if you see issue like [#3551](https://github.com/microsoft/autogen/issues/3551).*
+
 RetrieveChat can handle various types of documents. By default, it can process
 plain text and PDF files, including formats such as 'txt', 'json', 'csv', 'tsv',
 'md', 'html', 'htm', 'rtf', 'rst', 'jsonl', 'log', 'xml', 'yaml', 'yml' and 'pdf'.

website/blog/2024-06-24-AltModels-Classes/index.mdx

@@ -146,7 +146,7 @@ assistant = AssistantAgent(
 
 ```py
 
-user_proxy.intiate_chat(assistant, message="Write python code to print Hello World!")
+user_proxy.initiate_chat(assistant, message="Write python code to print Hello World!")
 
 ```
 

website/docs/installation/Optional-Dependencies.md

@@ -49,6 +49,7 @@ Example notebooks:
 ```bash
 pip install "pyautogen[retrievechat]"
 ```
+*You'll need to install `chromadb<=0.5.0` if you see issue like [#3551](https://github.com/microsoft/autogen/issues/3551).*
 
 Alternatively `pyautogen` also supports PGVector and Qdrant which can be installed in place of ChromaDB, or alongside it.
 

website/docs/topics/retrieval_augmentation.md

@@ -56,6 +56,7 @@ ragproxyagent.initiate_chat(
     assistant, message=ragproxyagent.message_generator, problem=code_problem, search_string="spark"
 )  # search_string is used as an extra filter for the embeddings search, in this case, we only want to search documents that contain "spark".
 ```
+*You'll need to install `chromadb<=0.5.0` if you see issue like [#3551](https://github.com/microsoft/autogen/issues/3551).*
 
 ## Example Setup: RAG with Retrieval Augmented Agents with PGVector
 The following is an example setup demonstrating how to create retrieval augmented agents in AutoGen: