Fixed a few minor typos

Signed-off-by: Bilgin Ibryam <bibryam@gmail.com>

docs/concepts/arxiv_fetcher.md

@@ -6,10 +6,10 @@ The Arxiv Fetcher module in `Dapr Agents` provides a powerful interface to inter
 
 The Arxiv Fetcher simplifies the process of accessing research papers, offering features like:
 
-* Automated Literature Search: Query arXiv for specific topics, keywords, or authors.
-* Metadata Retrieval: Extract structured metadata, such as titles, abstracts, authors, categories, and submission dates.
-* Precise Filtering: Limit search results by date ranges (e.g., retrieve the latest research in a field).
-* PDF Downloading: Fetch full-text PDFs of papers for offline use.
+* **Automated Literature Search**: Query arXiv for specific topics, keywords, or authors.
+* **Metadata Retrieval**: Extract structured metadata, such as titles, abstracts, authors, categories, and submission dates.
+* **Precise Filtering**: Limit search results by date ranges (e.g., retrieve the latest research in a field).
+* **PDF Downloading**: Fetch full-text PDFs of papers for offline use.
 
 ## How to Use the Arxiv Fetcher
 

docs/concepts/text_splitter.md

@@ -89,7 +89,7 @@ if not local_pdf_path.exists():
 
 ### Step 2: Read the Document
 
-For this example, we use Dapr Agents's `PyPDFReader`.
+For this example, we use Dapr Agents' `PyPDFReader`.
 
 !!! info
     The PyPDF Reader relies on the [pypdf python library](https://pypi.org/project/pypdf/), which is not included in the Dapr Agents core module. This design choice helps maintain modularity and avoids adding unnecessary dependencies for users who may not require this functionality. To use the PyPDF Reader, ensure that you install the library separately.

quickstarts/01-hello-world/03_reason_act.py

@@ -11,7 +11,7 @@ def search_weather(city: str) -> str:
 @tool
 def get_activities(weather: str) -> str:
     """Get activity recommendations."""
-    activities = {"rainy": "Visit museums", "Sunny": "Go hiking"}
+    activities = {"rainy": "Visit museums", "sunny": "Go hiking"}
     return activities.get(weather.lower(), "Stay comfortable")
 
 react_agent = ReActAgent(

quickstarts/02_llm_call_dapr/README.md

@@ -38,7 +38,7 @@ DAPR_LLM_COMPONENT_DEFAULT=echo
 ```
 
 The OpenAI API key is not needed for this example.
-Create a `echo.yaml ` file in the component folder
+Create a `echo.yaml` file in the component folder
 
 ```yaml
 apiVersion: dapr.io/v1alpha1

quickstarts/05-multi-agent-workflow-actors/README.md

@@ -128,7 +128,7 @@ async def main():
             message_bus_name="messagepubsub",
             state_store_name="agenticworkflowstate",
             state_key="workflow_state",
-            agents_registry_store_name="agentsregistrystore",
+            agents_registry_store_name="agentstatestore",
             agents_registry_key="agents_registry",
             service_port=8009,
             daprGrpcPort=50009,
@@ -276,7 +276,7 @@ Dapr Agents supports multiple workflow orchestration patterns:
 1. **Console Logs**: Monitor real-time workflow execution and agent interactions
 2. **Dapr Dashboard**: View components, configurations and service details at http://localhost:8080/
 3. **Zipkin Tracing**: Access distributed tracing at http://localhost:9411/zipkin/
-4**Dapr Metrics**: Access agent performance metrics via (ex: HobbitApp) http://localhost:6001/metrics when configured
+4. **Dapr Metrics**: Access agent performance metrics via (ex: HobbitApp) http://localhost:6001/metrics when configured
 
 ## Troubleshooting
 

quickstarts/05-multi-agent-workflow-dapr-workflows/README.md

@@ -126,7 +126,7 @@ async def main():
             message_bus_name="messagepubsub",
             state_store_name="agenticworkflowstate",
             state_key="workflow_state",
-            agents_registry_store_name="agentsregistrystore",
+            agents_registry_store_name="agentstatestore",
             agents_registry_key="agents_registry",
             service_port=8009,
             daprGrpcPort=50009,
@@ -273,7 +273,7 @@ Dapr Agents supports multiple workflow orchestration patterns:
 1. **Console Logs**: Monitor real-time workflow execution and agent interactions
 2. **Dapr Dashboard**: View components, configurations and service details at http://localhost:8080/
 3. **Zipkin Tracing**: Access distributed tracing at http://localhost:9411/zipkin/
-4**Dapr Metrics**: Access agent performance metrics via (ex: HobbitApp) http://localhost:6001/metrics when configured
+4. **Dapr Metrics**: Access agent performance metrics via (ex: HobbitApp) http://localhost:6001/metrics when configured
 
 ## Troubleshooting