Merge branch 'main' into memory_path

crewAIInc · Jan 17, 2025 · c3bb84a · c3bb84a
2 parents b418cb5 + 30d0271
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diff --git a/docs/concepts/knowledge.mdx b/docs/concepts/knowledge.mdx
@@ -93,6 +93,12 @@ result = crew.kickoff(inputs={"question": "What city does John live in and how o
 
 Here's another example with the `CrewDoclingSource`. The CrewDoclingSource is actually quite versatile and can handle multiple file formats including TXT, PDF, DOCX, HTML, and more. 
 
+<Note>
+  You need to install `docling` for the following example to work: `uv add docling`
+</Note>
+
+
+
 ```python Code
 from crewai import LLM, Agent, Crew, Process, Task
 from crewai.knowledge.source.crew_docling_source import CrewDoclingSource
@@ -282,6 +288,7 @@ The `embedder` parameter supports various embedding model providers that include
 - `ollama`: Local embeddings with Ollama
 - `vertexai`: Google Cloud VertexAI embeddings
 - `cohere`: Cohere's embedding models
+- `voyageai`: VoyageAI's embedding models
 - `bedrock`: AWS Bedrock embeddings
 - `huggingface`: Hugging Face models
 - `watson`: IBM Watson embeddings

diff --git a/docs/concepts/memory.mdx b/docs/concepts/memory.mdx
@@ -293,6 +293,26 @@ my_crew = Crew(
     }
 )
 ```
+### Using VoyageAI embeddings
+
+```python Code
+from crewai import Crew, Agent, Task, Process
+
+my_crew = Crew(
+    agents=[...],
+    tasks=[...],
+    process=Process.sequential,
+    memory=True,
+    verbose=True,
+    embedder={
+        "provider": "voyageai",
+        "config": {
+            "api_key": "YOUR_API_KEY",
+            "model_name": "<model_name>"
+        }
+    }
+)
+```
 ### Using HuggingFace embeddings
 
 ```python Code

diff --git a/docs/how-to/llm-connections.mdx b/docs/how-to/llm-connections.mdx
@@ -23,6 +23,7 @@ LiteLLM supports a wide range of providers, including but not limited to:
 - Azure OpenAI
 - AWS (Bedrock, SageMaker)
 - Cohere
+- VoyageAI
 - Hugging Face
 - Ollama
 - Mistral AI

diff --git a/src/crewai/agents/agent_builder/utilities/base_output_converter.py b/src/crewai/agents/agent_builder/utilities/base_output_converter.py
@@ -25,7 +25,7 @@ class OutputConverter(BaseModel, ABC):
     llm: Any = Field(description="The language model to be used to convert the text.")
     model: Any = Field(description="The model to be used to convert the text.")
     instructions: str = Field(description="Conversion instructions to the LLM.")
-    max_attempts: Optional[int] = Field(
+    max_attempts: int = Field(
         description="Max number of attempts to try to get the output formatted.",
         default=3,
     )

diff --git a/src/crewai/agents/agent_builder/utilities/base_token_process.py b/src/crewai/agents/agent_builder/utilities/base_token_process.py
@@ -2,11 +2,12 @@
 
 
 class TokenProcess:
-    total_tokens: int = 0
-    prompt_tokens: int = 0
-    cached_prompt_tokens: int = 0
-    completion_tokens: int = 0
-    successful_requests: int = 0
+    def __init__(self):
+        self.total_tokens: int = 0
+        self.prompt_tokens: int = 0
+        self.cached_prompt_tokens: int = 0
+        self.completion_tokens: int = 0
+        self.successful_requests: int = 0
 
     def sum_prompt_tokens(self, tokens: int):
         self.prompt_tokens = self.prompt_tokens + tokens