chore: Merge for release

docs/framework/ai-module.mdx

@@ -138,7 +138,7 @@ graph.add_file(file)
 
 # Remove the file from the graph
 graph.remove_file(file)
-````
+```
 
 #### Applying Graphs to Conversation completion
 
@@ -228,10 +228,10 @@ response = conversation.complete(tools=tool, max_tool_depth=7)
 You can pass either a single tool or a list of tools to the `complete()` or `stream_complete()` methods. The tools can be a combination of FunctionTool, Graph, or JSON-defined tools.
 
 ```python
-from writer.ai import FunctionTool, retrieve_graph
+from writer.ai import create_function_tool, retrieve_graph
 
 # Define a function tool
-tool1 = FunctionTool(
+tool1 = create_function_tool(
     name="get_data",
     callable=lambda x: f"Data for {x}",
     parameters={"x": {"type": "string", "description": "Input value"}}
@@ -245,7 +245,9 @@ response = conversation.complete(tools=[tool1, graph])
 ```
 
 ## Text generation without a conversation state
-These `complete` and `stream_complete` methods are designed for one-off text generation without the need to manage a conversation state. They return the model's response as a string. Each function accepts a `config` dictionary allowing call-specific configurations.
+
+### Text generation against a string prompt
+`complete` and `stream_complete` methods are designed for one-off text generation without the need to manage a conversation state. They return the model's response as a string. Each function accepts a `config` dictionary allowing call-specific configurations.
 
 <CodeGroup>
 ```python complete
@@ -260,4 +262,81 @@ for text_chunk in stream_complete("Explore the benefits of AI.", config={'temper
 ```
 </CodeGroup>
 
+### Text generation against graphs
+The `ask` and `stream_ask` methods allow you to query one or more graphs to generate responses from the information stored within them.
+
+#### Two approaches to questioning graphs
+
+There are two ways to query graphs, depending on your needs:
+1.	**Graph-Level Methods** (`Graph.ask`, `Graph.stream_ask`): Used when working with a single graph instance. These methods are tied directly to the Graph object, encapsulating operations within that instance.
+2.	**Module-Level Methods** (`writer.ai.ask`, `writer.ai.stream_ask`): Designed for querying multiple graphs simultaneously. These methods operate on a broader scale, allowing mixed inputs of graph objects and IDs.
+
+<Note>
+•	Use graph-level methods when working with a single graph instance.
+•	Use module-level methods when querying multiple graphs or when graph IDs are your primary input.
+</Note>
+
+#### Parameters
+
+Both methods include:
+	• `question: str`: The main query for the LLM.
+	• *Optional* `subqueries: bool` (default: `False`): Allows the LLM to generate additional questions during response preparation for more detailed answers. Enabling this might increase response time.
+
+Method-level methods require:
+    • `graphs_or_graph_ids: list[Graph | str]`: A list of graphs to use for the question. You can pass `Graph` objects directly into the list, use graph IDs in string form, or a mix of both.
+
+#### Graph-level methods
+
+The graph-level methods, `Graph.ask` and `Graph.stream_ask`, are designed for interacting with a single graph. By calling these methods on a specific `Graph` instance, you can easily pose questions and retrieve answers tailored to that graph’s content.
+
+<CodeGroup>
+```python ask
+# Retrieve a specific graph
+graph = retrieve_graph("f47ac10b-58cc-4372-a567-0e02b2c3d479")
+
+# Pose a question to the graph and get a complete response
+response = graph.ask("What are the benefits of renewable energy?")
+print(response)
+```
+```python stream_ask
+# Retrieve a specific graph
+graph = retrieve_graph("f47ac10b-58cc-4372-a567-0e02b2c3d479")
+
+# Pose a question and stream the response in chunks
+for chunk in graph.stream_ask("Explain the history of solar energy."):
+    print(chunk)
+```
+</CodeGroup>
+
+#### Module-level methods
+The module-level methods, `writer.ai.ask` and `writer.ai.stream_ask`, are designed for querying multiple graphs simultaneously. They are useful when you need to aggregate or compare data across multiple graphs.
+
+<CodeGroup>
+```python ask
+from writer.ai import ask
+
+# Pose a question to multiple graphs
+response = ask(
+    question="What are the latest advancements in AI?",
+    graphs_or_graph_ids=[
+        "550e8400-e29b-41d4-a716-446655440000",
+        "123e4567-e89b-12d3-a456-426614174000"
+        ]
+)
+print(response)
+```
+```python stream_ask
+from writer.ai import stream_ask
+
+# Stream responses from multiple graphs
+for chunk in stream_ask(
+    question="Describe the key features of renewable energy sources.",
+    graphs_or_graph_ids=[
+        "550e8400-e29b-41d4-a716-446655440000",
+        "123e4567-e89b-12d3-a456-426614174000"
+        ]
+):
+    print(chunk)
+```
+</CodeGroup>
 

docs/framework/seo.mdx

@@ -1,5 +1,5 @@
 ---
-title: "SEO"
+title: "Seo and social sharing"
 mode: "wide"
 ---
 
@@ -41,6 +41,7 @@ writer.serve.configure_webpage_metadata(
 
 You can also use a function to generate the meta tags dynamically.
 
+*./server_setup.py*
 ```python
 def _meta():
 	last_news = db.get_last_news()
@@ -57,6 +58,7 @@ writer.serve.configure_webpage_metadata(meta=_meta)
 
 When you share a link on social networks, they will try to fetch the metadata of the page to display a preview.
 
+*./server_setup.py*
 ```python
 writer.serve.configure_webpage_metadata(
     opengraph_tags= {
@@ -66,9 +68,11 @@ writer.serve.configure_webpage_metadata(
     	"og:url": "https://myapp.com"
     }
 )
+```
 
 You can also use a function to generate the opengraph tags dynamically.
 
+*./server_setup.py*
 ```python
 def _opengraph_tags():
 	last_news = db.get_last_news()

docs/mint.json

@@ -32,23 +32,20 @@
 				"framework/introduction",
 				"framework/quickstart",
 				"framework/ai-module",
-				"framework/cloud-deploy",
-				"framework/sample-apps"
+				"framework/sample-apps",
+				"framework/component-list-link"
 			]
 		},
 		{
 			"group": "Guides",
 			"pages": [
 				"framework/application-state",
-				"framework/event-handlers",
+				"framework/backend-initiated-actions",
 				"framework/builder-basics",
+				"framework/event-handlers",
 				"framework/handling-inputs",
-				"framework/dataframe",
-				"framework/backend-driven-ui",
-				"framework/stylesheets",
-				"framework/frontend-scripts",
-				"framework/custom-components",
-				"framework/authentication"
+			  	"framework/dataframe",
+				"framework/repeater"
 			]
 		},
 		{
@@ -64,19 +61,23 @@
 			"group": "Deployment",
 			"pages": [
 				"framework/cloud-deploy",
-				"framework/deploy-with-docker",
-				"framework/testing"
+				"framework/deploy-with-docker"
 			]
 		},
 		{
 			"group": "Advanced",
 			"pages": [
-				"framework/repeater",
-				"framework/backend-initiated-actions",
+				"framework/authentication",
+				"framework/backend-driven-ui",
+				"framework/custom-components",
+				"framework/custom-server",
+				"framework/frontend-scripts",
 				"framework/page-routes",
 				"framework/sessions",
-				"framework/custom-server",
-				"framework/state-schema"
+				"framework/state-schema",
+				"framework/stylesheets",
+				"framework/testing",
+				"framework/seo"
 			]
 		},
 		{

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "writer"
-version = "0.8.3rc1"
+version = "0.8.3rc2"
 description = "An open-source, Python framework for building feature-rich apps that are fully integrated with the Writer platform."
 authors = ["Writer, Inc."]
 readme = "README.md"

src/ui/src/components/core/base/BaseInputWrapper.vue

@@ -4,16 +4,16 @@
 		class="BaseInputWrapper"
 		:class="{ horizontal: isHorizontal }"
 	>
-		<label v-if="props.label">{{ props.label }}</label>
+		<label v-if="label">{{ label }}</label>
 		<slot></slot>
 	</div>
 </template>
 
 <script setup lang="ts">
-const props = defineProps<{
-	label: string;
-	isHorizontal?: boolean;
-}>();
+defineProps({
+	label: { type: String, required: false, default: undefined },
+	isHorizontal: { type: Boolean, required: false },
+});
 </script>
 
 <style scoped>