Merge branch 'main' into patch-1

.github/workflows/contrib-tests.yml

@@ -91,6 +91,17 @@ jobs:
         image: mongodb/mongodb-atlas-local:latest
         ports:
           - 27017:27017
+      couchbase:
+        image: couchbase:enterprise-7.6.3
+        ports:
+          - "8091-8095:8091-8095"
+          - "11210:11210"
+          - "9102:9102"
+        healthcheck: # checks couchbase server is up
+          test: ["CMD", "curl", "-v", "http://localhost:8091/pools"]
+          interval: 20s
+          timeout: 20s
+          retries: 5
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }}
@@ -111,6 +122,9 @@ jobs:
       - name: Install mongodb when on linux
         run: |
           pip install -e .[retrievechat-mongodb]
+      - name: Install couchbase when on linux
+        run: |
+          pip install -e .[retrievechat-couchbase]
       - name: Install unstructured when python-version is 3.9 and on linux
         if: matrix.python-version == '3.9'
         run: |
@@ -120,6 +134,9 @@ jobs:
       - name: Install packages and dependencies for RetrieveChat
         run: |
           pip install -e .[retrievechat]
+      - name: Install packages and dependencies for WebSurfer and browser_utils
+        run: |
+          pip install -e .[test,websurfer]
       - name: Set AUTOGEN_USE_DOCKER based on OS
         shell: bash
         run: |
@@ -261,7 +278,7 @@ jobs:
           fi
       - name: Coverage
         run: |
-          pytest test/test_browser_utils.py test/agentchat/contrib/test_web_surfer.py --skip-openai
+          pytest test/browser_utils test/agentchat/contrib/test_web_surfer.py --skip-openai
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v3
         with:

.github/workflows/deploy-website.yml

@@ -17,7 +17,8 @@ on:
   merge_group:
     types: [checks_requested]
 permissions:
-  contents: write
+  id-token: write
+  pages: write
 jobs:
   checks:
     if: github.event_name != 'push'
@@ -113,9 +114,10 @@ jobs:
           npm i --legacy-peer-deps
           npm run build
           fi
-      - name: Deploy to GitHub Pages
-        uses: peaceiris/actions-gh-pages@v3
+      - name: Upload artifact
+        uses: actions/upload-pages-artifact@v3
         with:
-          github_token: ${{ secrets.GITHUB_TOKEN }}
-          # Build output to publish to the `gh-pages` branch:
-          publish_dir: ./website/build
+          path: "website/build"
+      - name: Deploy to GitHub Pages
+        id: deployment
+        uses: actions/deploy-pages@v4

.pre-commit-config.yaml

@@ -46,7 +46,8 @@ repos:
               website/docs/tutorial/code-executors.ipynb |
               website/docs/topics/code-execution/custom-executor.ipynb |
               website/docs/topics/non-openai-models/cloud-gemini.ipynb |
-              notebook/.*
+              notebook/.* |
+              test/browser_utils/test_files/.*
             )$
   # See https://jaredkhan.com/blog/mypy-pre-commit
   - repo: local

autogen/agentchat/contrib/gpt_assistant_agent.py

@@ -209,10 +209,12 @@ def _invoke_assistant(
         for message in pending_messages:
             if message["content"].strip() == "":
                 continue
+            # Convert message roles to 'user' or 'assistant', by calling _map_role_for_api, to comply with OpenAI API spec
+            api_role = self._map_role_for_api(message["role"])
             self._openai_client.beta.threads.messages.create(
                 thread_id=assistant_thread.id,
                 content=message["content"],
-                role=message["role"],
+                role=api_role,
             )
 
         # Create a new run to get responses from the assistant
@@ -240,6 +242,28 @@ def _invoke_assistant(
         self._unread_index[sender] = len(self._oai_messages[sender]) + 1
         return True, response
 
+    def _map_role_for_api(self, role: str) -> str:
+        """
+        Maps internal message roles to the roles expected by the OpenAI Assistant API.
+
+        Args:
+            role (str): The role from the internal message.
+
+        Returns:
+            str: The mapped role suitable for the API.
+        """
+        if role in ["function", "tool"]:
+            return "assistant"
+        elif role == "system":
+            return "system"
+        elif role == "user":
+            return "user"
+        elif role == "assistant":
+            return "assistant"
+        else:
+            # Default to 'assistant' for any other roles not recognized by the API
+            return "assistant"
+
     def _get_run_response(self, thread, run):
         """
         Waits for and processes the response of a run from the OpenAI assistant.

autogen/agentchat/contrib/retrieve_user_proxy_agent.py

@@ -178,7 +178,7 @@ def __init__(
                     vector db. Default is None, SentenceTransformer with the given `embedding_model`
                     will be used. If you want to use OpenAI, Cohere, HuggingFace or other embedding
                     functions, you can pass it here,
-                    follow the examples in `https://docs.trychroma.com/embeddings`.
+                    follow the examples in `https://docs.trychroma.com/guides/embeddings`.
                 - `customized_prompt` (Optional, str) - the customized prompt for the retrieve chat.
                     Default is None.
                 - `customized_answer_prefix` (Optional, str) - the customized answer prefix for the

autogen/agentchat/contrib/vectordb/base.py

@@ -201,7 +201,7 @@ class VectorDBFactory:
     Factory class for creating vector databases.
     """
 
-    PREDEFINED_VECTOR_DB = ["chroma", "pgvector", "mongodb", "qdrant"]
+    PREDEFINED_VECTOR_DB = ["chroma", "pgvector", "mongodb", "qdrant", "couchbase"]
 
     @staticmethod
     def create_vector_db(db_type: str, **kwargs) -> VectorDB:
@@ -231,6 +231,10 @@ def create_vector_db(db_type: str, **kwargs) -> VectorDB:
             from .qdrant import QdrantVectorDB
 
             return QdrantVectorDB(**kwargs)
+        if db_type.lower() in ["couchbase", "couchbasedb", "capella"]:
+            from .couchbase import CouchbaseVectorDB
+
+            return CouchbaseVectorDB(**kwargs)
         else:
             raise ValueError(
                 f"Unsupported vector database type: {db_type}. Valid types are {VectorDBFactory.PREDEFINED_VECTOR_DB}."