Merge branch 'master' into lyh_tool_token

Author: Wendong-Fan

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -1,7 +1,7 @@
 name: 🐛 Bug Report
 description: File an issue about a bug.
 title: "[BUG] "
-labels: [bug]
+labels: [bug, Needs Triage]
 body:
   - type: markdown
     attributes:
@@ -26,7 +26,7 @@ body:
     attributes:
       label: What version of camel are you using?
       description: Run command `python3 -c 'print(__import__("camel").__version__)'` in your shell and paste the output here.
-      placeholder: E.g., 0.2.78
+      placeholder: E.g., 0.2.79a0
     validations:
       required: true
 

.github/ISSUE_TEMPLATE/feature_request.yml

@@ -1,7 +1,7 @@
 name: ✨ Feature Request
 description: Suggest an idea for this project.
 title: "[Feature Request] "
-labels: [enhancement]
+labels: [Needs Triage]
 body:
   - type: checkboxes
     id: steps

.github/ISSUE_TEMPLATE/questions.yml

@@ -1,7 +1,7 @@
 name: 🤔 Questions / Help / Support
 description: Do you need support?
 title: "[Question] "
-labels: [question]
+labels: [question, Needs Triage]
 body:
   - type: checkboxes
     id: steps

.github/workflows/pr-label-automation.yml

@@ -0,0 +1,24 @@
+name: PR Label Automation
+
+on:
+  pull_request:
+    types: [opened]
+
+permissions:
+  pull-requests: write
+
+jobs:
+  add-labels:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Add Review Required label
+        uses: actions/github-script@v7
+        with:
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+          script: |
+            github.rest.issues.addLabels({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.issue.number,
+              labels: ['Review Required']
+            })

.pre-commit-config.yaml

@@ -4,7 +4,7 @@ repos:
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix, --show-fixes]
-        exclude: ^(docs/cookbooks/|examples/usecases/)  # Ignore files under docs/cookbooks and examples/usecases
+        exclude: ^(docs/cookbooks/|examples/usecases/|examples/custom_client_usage\.py)  # Ignore files under docs/cookbooks and examples/usecases
       - id: ruff-format
         exclude: ^(docs/cookbooks/|examples/usecases/)  # Ignore files under docs/cookbooks and examples/usecases
 

camel/__init__.py

@@ -14,7 +14,7 @@
 
 from camel.logger import disable_logging, enable_logging, set_log_level
 
-__version__ = '0.2.78'
+__version__ = '0.2.79a0'
 
 __all__ = [
     '__version__',

camel/models/aws_bedrock_model.py

@@ -13,17 +13,11 @@
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
 
 import os
-from typing import Any, Dict, List, Optional, Type, Union
-
-from openai import AsyncStream
-from pydantic import BaseModel
+from typing import Any, Dict, Optional, Union
 
 from camel.configs import BedrockConfig
-from camel.messages import OpenAIMessage
 from camel.models.openai_compatible_model import OpenAICompatibleModel
 from camel.types import (
-    ChatCompletion,
-    ChatCompletionChunk,
     ModelType,
 )
 from camel.utils import BaseTokenCounter, api_keys_required
@@ -93,13 +87,3 @@ def __init__(
             max_retries=max_retries,
             **kwargs,
         )
-
-    async def _arun(
-        self,
-        messages: List[OpenAIMessage],
-        response_format: Optional[Type[BaseModel]] = None,
-        tools: Optional[List[Dict[str, Any]]] = None,
-    ) -> Union[ChatCompletion, AsyncStream[ChatCompletionChunk]]:
-        raise NotImplementedError(
-            "AWS Bedrock does not support async inference."
-        )

camel/models/azure_openai_model.py

@@ -88,8 +88,19 @@ class AzureOpenAIModel(BaseModelBackend):
             (default: :obj:`None`)
         max_retries (int, optional): Maximum number of retries for API calls.
             (default: :obj:`3`)
+        client (Optional[Any], optional): A custom synchronous AzureOpenAI
+            client instance. If provided, this client will be used instead of
+            creating a new one. Useful for RL frameworks like AReaL or rLLM
+            that provide Azure OpenAI-compatible clients. The client should
+            implement the AzureOpenAI client interface with
+            `.chat.completions.create()` and `.beta.chat.completions.parse()`
+            methods. (default: :obj:`None`)
+        async_client (Optional[Any], optional): A custom asynchronous
+            AzureOpenAI client instance. If provided, this client will be
+            used instead of creating a new one. The client should implement
+            the AsyncAzureOpenAI client interface. (default: :obj:`None`)
         **kwargs (Any): Additional arguments to pass to the client
-            initialization.
+            initialization. Ignored if custom clients are provided.
 
     References:
         https://learn.microsoft.com/en-us/azure/ai-services/openai/
@@ -108,6 +119,8 @@ def __init__(
         azure_ad_token_provider: Optional["AzureADTokenProvider"] = None,
         azure_ad_token: Optional[str] = None,
         max_retries: int = 3,
+        client: Optional[Any] = None,
+        async_client: Optional[Any] = None,
         **kwargs: Any,
     ) -> None:
         if model_config_dict is None:
@@ -138,56 +151,72 @@ def __init__(
                 "or `AZURE_DEPLOYMENT_NAME` environment variable."
             )
 
-        if is_langfuse_available():
-            from langfuse.openai import AsyncAzureOpenAI as LangfuseAsyncOpenAI
-            from langfuse.openai import AzureOpenAI as LangfuseOpenAI
-
-            self._client = LangfuseOpenAI(
-                azure_endpoint=str(self._url),
-                azure_deployment=self._azure_deployment_name,
-                api_version=self.api_version,
-                api_key=self._api_key,
-                azure_ad_token=self._azure_ad_token,
-                azure_ad_token_provider=self.azure_ad_token_provider,
-                timeout=self._timeout,
-                max_retries=max_retries,
-                **kwargs,
-            )
-            self._async_client = LangfuseAsyncOpenAI(
-                azure_endpoint=str(self._url),
-                azure_deployment=self._azure_deployment_name,
-                api_version=self.api_version,
-                api_key=self._api_key,
-                azure_ad_token=self._azure_ad_token,
-                azure_ad_token_provider=self.azure_ad_token_provider,
-                timeout=self._timeout,
-                max_retries=max_retries,
-                **kwargs,
-            )
+        # Use custom clients if provided, otherwise create new ones
+        if client is not None:
+            # Use the provided custom sync client
+            self._client = client
         else:
-            self._client = AzureOpenAI(
-                azure_endpoint=str(self._url),
-                azure_deployment=self._azure_deployment_name,
-                api_version=self.api_version,
-                api_key=self._api_key,
-                azure_ad_token=self._azure_ad_token,
-                azure_ad_token_provider=self.azure_ad_token_provider,
-                timeout=self._timeout,
-                max_retries=max_retries,
-                **kwargs,
-            )
+            # Create default sync client
+            if is_langfuse_available():
+                from langfuse.openai import AzureOpenAI as LangfuseOpenAI
+
+                self._client = LangfuseOpenAI(
+                    azure_endpoint=str(self._url),
+                    azure_deployment=self._azure_deployment_name,
+                    api_version=self.api_version,
+                    api_key=self._api_key,
+                    azure_ad_token=self._azure_ad_token,
+                    azure_ad_token_provider=self.azure_ad_token_provider,
+                    timeout=self._timeout,
+                    max_retries=max_retries,
+                    **kwargs,
+                )
+            else:
+                self._client = AzureOpenAI(
+                    azure_endpoint=str(self._url),
+                    azure_deployment=self._azure_deployment_name,
+                    api_version=self.api_version,
+                    api_key=self._api_key,
+                    azure_ad_token=self._azure_ad_token,
+                    azure_ad_token_provider=self.azure_ad_token_provider,
+                    timeout=self._timeout,
+                    max_retries=max_retries,
+                    **kwargs,
+                )
 
-            self._async_client = AsyncAzureOpenAI(
-                azure_endpoint=str(self._url),
-                azure_deployment=self._azure_deployment_name,
-                api_version=self.api_version,
-                api_key=self._api_key,
-                azure_ad_token=self._azure_ad_token,
-                azure_ad_token_provider=self.azure_ad_token_provider,
-                timeout=self._timeout,
-                max_retries=max_retries,
-                **kwargs,
-            )
+        if async_client is not None:
+            # Use the provided custom async client
+            self._async_client = async_client
+        else:
+            # Create default async client
+            if is_langfuse_available():
+                from langfuse.openai import (
+                    AsyncAzureOpenAI as LangfuseAsyncOpenAI,
+                )
+
+                self._async_client = LangfuseAsyncOpenAI(
+                    azure_endpoint=str(self._url),
+                    azure_deployment=self._azure_deployment_name,
+                    api_version=self.api_version,
+                    api_key=self._api_key,
+                    azure_ad_token=self._azure_ad_token,
+                    azure_ad_token_provider=self.azure_ad_token_provider,
+                    timeout=self._timeout,
+                    max_retries=max_retries,
+                    **kwargs,
+                )
+            else:
+                self._async_client = AsyncAzureOpenAI(
+                    azure_endpoint=str(self._url),
+                    azure_deployment=self._azure_deployment_name,
+                    api_version=self.api_version,
+                    api_key=self._api_key,
+                    azure_ad_token=self._azure_ad_token,
+                    azure_ad_token_provider=self.azure_ad_token_provider,
+                    timeout=self._timeout,
+                    max_retries=max_retries,
+                    **kwargs,
+                )
 
     @property
     def token_counter(self) -> BaseTokenCounter:

camel/models/model_factory.py

@@ -13,7 +13,7 @@
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
 import json
 import os
-from typing import ClassVar, Dict, Optional, Type, Union
+from typing import Any, ClassVar, Dict, Optional, Type, Union
 
 from camel.models.aiml_model import AIMLModel
 from camel.models.amd_model import AMDModel
@@ -119,6 +119,8 @@ def create(
         url: Optional[str] = None,
         timeout: Optional[float] = None,
         max_retries: int = 3,
+        client: Optional[Any] = None,
+        async_client: Optional[Any] = None,
         **kwargs,
     ) -> BaseModelBackend:
         r"""Creates an instance of `BaseModelBackend` of the specified type.
@@ -145,6 +147,14 @@ def create(
                 for API calls. (default: :obj:`None`)
             max_retries (int, optional): Maximum number of retries
                 for API calls. (default: :obj:`3`)
+            client (Optional[Any], optional): A custom synchronous client
+                instance. Supported by models that use OpenAI-compatible APIs
+                . The client should implement the appropriate client interface
+                for the platform. (default: :obj:`None`)
+            async_client (Optional[Any], optional): A custom asynchronous
+                client instance. Supported by models that use OpenAI-compatible
+                APIs. The client should implement the appropriate async client
+                interface for the platform. (default: :obj:`None`)
             **kwargs: Additional model-specific parameters that will be passed
                 to the model constructor. For example, Azure OpenAI models may
                 require `api_version`, `azure_deployment_name`,
@@ -190,6 +200,12 @@ def create(
         if model_class is None:
             raise ValueError(f"Unknown model platform `{model_platform}`")
 
+        # Pass client and async_client via kwargs if provided
+        if client is not None:
+            kwargs['client'] = client
+        if async_client is not None:
+            kwargs['async_client'] = async_client
+
         return model_class(
             model_type=model_type,
             model_config_dict=model_config_dict,