refactor(api, sdk-py, sdk-ts, ui, docs): rename send_message to store_message across documentation and codebase (#87)

Author: GenerQAQ

README.md

@@ -325,9 +325,9 @@ client.ping()
 
 Acontext can manage agent sessions and artifacts.
 
-### Save Messages [📖](https://docs.acontext.io/api-reference/session/send-message-to-session)
+### Save Messages [📖](https://docs.acontext.io/api-reference/session/store-message-to-session)
 
-Acontext offers persistent storage for message data. When you call `session.send_message`, Acontext will persist the message and start to monitor this session:
+Acontext offers persistent storage for message data. When you call `session.store_message`, Acontext will persist the message and start to monitor this session:
 
 <details>
 <summary>Code Snippet</summary>
@@ -345,7 +345,7 @@ messages = [
 
 # Save messages
 for msg in messages:
-    client.sessions.send_message(session_id=session.id, blob=msg, format="openai")
+    client.sessions.store_message(session_id=session.id, blob=msg, format="openai")
 ```
 
 > [📖](https://docs.acontext.io/store/messages/multi-modal) We also support multi-modal message storage and anthropic SDK.
@@ -367,7 +367,7 @@ new_msg = r.items
 new_msg.append({"role": "user", "content": "How are you doing?"})
 r = openai_client.chat.completions.create(model="gpt-4.1", messages=new_msg)
 print(r.choices[0].message.content)
-client.sessions.send_message(session_id=session.id, blob=r.choices[0].message)
+client.sessions.store_message(session_id=session.id, blob=r.choices[0].message)
 ```
 
 </details>
@@ -478,9 +478,9 @@ messages = [
     },
 ]
 
-# Send messages in a loop
+# Store messages in a loop
 for msg in messages:
-    client.sessions.send_message(session_id=session.id, blob=msg, format="openai")
+    client.sessions.store_message(session_id=session.id, blob=msg, format="openai")
 
 # Wait for task extraction to complete
 client.sessions.flush(session.id)

docs/api-reference/introduction.mdx

@@ -100,8 +100,8 @@ session = client.sessions.create(
     configs={"mode": "chat"}
 )
 
-# Send a message (OpenAI format)
-response = client.sessions.send_message(
+# Store a message (OpenAI format)
+response = client.sessions.store_message(
     session_id=session.id,
     blob={'role': 'user', 'content': 'How do I reset my password?'},
     format='openai'
@@ -133,8 +133,8 @@ const session = await client.sessions.create({
   configs: { mode: 'chat' }
 });
 
-// Send a message (OpenAI format)
-const response = await client.sessions.sendMessage(
+// Store a message (OpenAI format)
+const response = await client.sessions.storeMessage(
   session.id,
   { role: 'user', content: 'How do I reset my password?' },
   { format: 'openai' }
@@ -204,7 +204,7 @@ Acontext supports multiple message formats for maximum compatibility:
 - **Anthropic** - Compatible with Anthropic Messages format
 - **Acontext** - Native format with extended capabilities
 
-You can convert between formats when retrieving or sending messages using the `format` parameter.
+You can convert between formats when retrieving or storing messages using the `format` parameter.
 
 ## Join the Community
 

docs/api-reference/openapi.json

@@ -899,16 +899,16 @@
         "security" : [ {
           "BearerAuth" : [ ]
         } ],
-        "summary" : "Send message to session",
+        "summary" : "Store message to session",
         "tags" : [ "session" ],
         "x-code-samples" : [ {
           "label" : "Python",
           "lang" : "python",
-          "source" : "from acontext import AcontextClient\nfrom acontext.messages import build_acontext_message\n\nclient = AcontextClient(api_key='sk_project_token')\n\n# Send a message in Acontext format\nmessage = build_acontext_message(role='user', parts=['Hello!'])\nclient.sessions.send_message(\n    session_id='session-uuid',\n    blob=message,\n    format='acontext'\n)\n\n# Send a message in OpenAI format\nopenai_message = {'role': 'user', 'content': 'Hello from OpenAI format!'}\nclient.sessions.send_message(\n    session_id='session-uuid',\n    blob=openai_message,\n    format='openai'\n)\n"
+          "source" : "from acontext import AcontextClient\nfrom acontext.messages import build_acontext_message\n\nclient = AcontextClient(api_key='sk_project_token')\n\n# Store a message in Acontext format\nmessage = build_acontext_message(role='user', parts=['Hello!'])\nclient.sessions.store_message(\n    session_id='session-uuid',\n    blob=message,\n    format='acontext'\n)\n\n# Store a message in OpenAI format\nopenai_message = {'role': 'user', 'content': 'Hello from OpenAI format!'}\nclient.sessions.store_message(\n    session_id='session-uuid',\n    blob=openai_message,\n    format='openai'\n)\n"
         }, {
           "label" : "JavaScript",
           "lang" : "javascript",
-          "source" : "import { AcontextClient, MessagePart } from '@acontext/acontext';\n\nconst client = new AcontextClient({ apiKey: 'sk_project_token' });\n\n// Send a message in Acontext format\nawait client.sessions.sendMessage(\n  'session-uuid',\n  {\n    role: 'user',\n    parts: [MessagePart.textPart('Hello!')]\n  },\n  { format: 'acontext' }\n);\n\n// Send a message in OpenAI format\nawait client.sessions.sendMessage(\n  'session-uuid',\n  {\n    role: 'user',\n    content: 'Hello from OpenAI format!'\n  },\n  { format: 'openai' }\n);\n"
+          "source" : "import { AcontextClient, MessagePart } from '@acontext/acontext';\n\nconst client = new AcontextClient({ apiKey: 'sk_project_token' });\n\n// Store a message in Acontext format\nawait client.sessions.storeMessage(\n  'session-uuid',\n  {\n    role: 'user',\n    parts: [MessagePart.textPart('Hello!')]\n  },\n  { format: 'acontext' }\n);\n\n// Store a message in OpenAI format\nawait client.sessions.storeMessage(\n  'session-uuid',\n  {\n    role: 'user',\n    content: 'Hello from OpenAI format!'\n  },\n  { format: 'openai' }\n);\n"
         } ],
         "x-codegen-request-body-name" : "payload"
       }
@@ -2049,7 +2049,7 @@
         "required" : [ "rename" ],
         "type" : "object"
       },
-      "handler.SendMessageReq" : {
+      "handler.StoreMessageReq" : {
         "properties" : {
           "blob" : {
             "type" : "object"
@@ -2754,7 +2754,7 @@
       "_session__session_id__messages_post_request" : {
         "properties" : {
           "payload" : {
-            "description" : "SendMessage payload (Content-Type: multipart/form-data)",
+            "description" : "StoreMessage payload (Content-Type: multipart/form-data)",
             "type" : "string"
           },
           "file" : {

docs/integrations/agno.mdx

@@ -92,12 +92,12 @@ acontext_client = AcontextClient(
 
 ## How It Works
 
-The Agno integration works by sending conversation messages to Acontext in OpenAI message format. Agno's message format is compatible with Acontext, so no conversion is needed.
+The Agno integration works by storing conversation messages to Acontext in OpenAI message format. Agno's message format is compatible with Acontext, so no conversion is needed.
 
 ### Message Flow
 
 1. **Create session**: Initialize a new Acontext session for your agent
-2. **Send messages**: Append each message (user and assistant) to Acontext as the conversation progresses
+2. **Store messages**: Append each message (user and assistant) to Acontext as the conversation progresses
 3. **Extract tasks**: After the conversation, flush the session and retrieve extracted tasks
 4. **Resume sessions**: Load previous conversation history to continue where you left off
 
@@ -127,19 +127,19 @@ agent = Agent(
 space = acontext_client.spaces.create()
 session = acontext_client.sessions.create(space_id=space.id)
 
-# Build conversation and send to Acontext
+# Build conversation and store to Acontext
 conversation = []
 user_msg = {"role": "user", "content": "Hello!"}
 conversation.append(user_msg)
-acontext_client.sessions.send_message(session_id=session.id, blob=user_msg)
+acontext_client.sessions.store_message(session_id=session.id, blob=user_msg)
 
 # Run agent
 response = agent.run(conversation)
 
-# Send assistant response to Acontext
+# Store assistant response to Acontext
 assistant_msg = {"role": "assistant", "content": response.content}
 conversation.append(assistant_msg)
-acontext_client.sessions.send_message(session_id=session.id, blob=assistant_msg)
+acontext_client.sessions.store_message(session_id=session.id, blob=assistant_msg)
 ```
 
 ## Complete Example
@@ -173,7 +173,7 @@ def create_agno_agent() -> Agent:
 
 def append_message(message: dict, conversation: list[dict], session_id: str):
     conversation.append(message)
-    acontext_client.sessions.send_message(session_id=session_id, blob=message)
+    acontext_client.sessions.store_message(session_id=session_id, blob=message)
     return conversation
 
 async def main():
@@ -279,8 +279,8 @@ message = {
     "content": "Your message here"
 }
 
-# Send directly to Acontext - no conversion needed
-acontext_client.sessions.send_message(session_id=session_id, blob=message)
+# Store directly to Acontext - no conversion needed
+acontext_client.sessions.store_message(session_id=session_id, blob=message)
 ```
 
 <Info>
@@ -290,7 +290,7 @@ Agno's `RunOutput.messages` can be converted to dictionaries using `[m.to_dict()
 ## Best Practices
 
 <Tip>
-**Batch message sending**: For better performance, you can batch multiple messages before sending them to Acontext, but ensure you send them in chronological order.
+**Batch message storing**: For better performance, you can batch multiple messages before storing them to Acontext, but ensure you store them in chronological order.
 </Tip>
 
 <Tip>

docs/integrations/ai-sdk.mdx

@@ -103,14 +103,14 @@ const acontextClient = new AcontextClient({
 
 ## How It Works
 
-The Vercel AI SDK integration works by sending conversation messages to Acontext in OpenAI message format. The SDK uses `generateText` for text generation and requires manual tool execution.
+The Vercel AI SDK integration works by storing conversation messages to Acontext in OpenAI message format. The SDK uses `generateText` for text generation and requires manual tool execution.
 
 ### Message Flow
 
 1. **Create session**: Initialize a new Acontext session for your agent
 2. **Generate text**: Use `generateText` with tools to get model responses
 3. **Handle tool calls**: Manually execute tools when the model requests them
-4. **Send messages**: Append each message (user, assistant, and tool) to Acontext
+4. **Store messages**: Append each message (user, assistant, and tool) to Acontext
 5. **Extract tasks**: After the conversation, flush the session and retrieve extracted tasks
 6. **Resume sessions**: Load previous conversation history to continue where you left off
 
@@ -154,7 +154,7 @@ const session = await acontextClient.sessions.create({ spaceId: space.id });
 let conversation: any[] = [];
 const userMsg = { role: 'user', content: 'Hello!' };
 conversation.push(userMsg);
-await acontextClient.sessions.sendMessage(session.id, userMsg, {
+await acontextClient.sessions.storeMessage(session.id, userMsg, {
   format: 'openai',
 });
 
@@ -164,13 +164,13 @@ const result = await generateText({
   messages: conversation,
 });
 
-// Send assistant response to Acontext
+// Store assistant response to Acontext
 const assistantMsg = {
   role: 'assistant',
   content: result.text,
 };
 conversation.push(assistantMsg);
-await acontextClient.sessions.sendMessage(session.id, assistantMsg, {
+await acontextClient.sessions.storeMessage(session.id, assistantMsg, {
   format: 'openai',
 });
 ```
@@ -227,7 +227,7 @@ async function runAgent(conversation: any[]): Promise<[string, any[]]> {
     iteration += 1;
 
     // Filter messages for Vercel AI SDK (only user and assistant)
-    const messagesToSend = conversation
+    const messagesToStore = conversation
       .filter((msg: any) => {
         const role = msg.role;
         return (role === 'user' || role === 'assistant') && !msg._internal;
@@ -249,7 +249,7 @@ async function runAgent(conversation: any[]): Promise<[string, any[]]> {
     const result = await generateText({
       model,
       system: 'You are a helpful assistant',
-      messages: messagesToSend,
+      messages: messagesToStore,
       tools,
     });
 
@@ -348,9 +348,9 @@ async function runAgent(conversation: any[]): Promise<[string, any[]]> {
 }
 ```
 
-### Send Messages to Acontext
+### Store Messages to Acontext
 
-Send all messages (excluding internal ones) to Acontext:
+Store all messages (excluding internal ones) to Acontext:
 
 ```typescript
 async function appendMessage(
@@ -365,7 +365,7 @@ async function appendMessage(
   }
 
   conversation.push(message);
-  await acontextClient.sessions.sendMessage(sessionId, message, {
+  await acontextClient.sessions.storeMessage(sessionId, message, {
     format: 'openai',
   });
   return conversation;
@@ -443,7 +443,7 @@ async function appendMessage(
     return conversation;
   }
   conversation.push(message);
-  await acontextClient.sessions.sendMessage(sessionId, message, {
+  await acontextClient.sessions.storeMessage(sessionId, message, {
     format: 'openai',
   });
   return conversation;
@@ -463,7 +463,7 @@ async function main(): Promise<void> {
   // Run agent with tool calling
   const [responseContent, newMessages] = await runAgent(conversation);
 
-  // Send all messages to Acontext
+  // Store all messages to Acontext
   for (const msg of newMessages) {
     conversation = await appendMessage(msg, conversation, session.id);
   }
@@ -542,7 +542,7 @@ Vercel AI SDK has specific requirements for message formats:
 
 ```typescript
 // Filter messages for Vercel AI SDK
-const messagesToSend = conversation
+const messagesToStore = conversation
   .filter((msg: any) => {
     // Only user and assistant roles, exclude internal messages
     const role = msg.role;
@@ -582,7 +582,7 @@ const messagesToSend = conversation
 </Tip>
 
 <Tip>
-**Format specification**: Always specify `format: 'openai'` when sending messages to Acontext to ensure proper format handling.
+**Format specification**: Always specify `format: 'openai'` when storing messages to Acontext to ensure proper format handling.
 </Tip>
 
 <Tip>
@@ -608,7 +608,7 @@ Vercel AI SDK v5 only accepts 'user' and 'assistant' roles in messages. Tool res
 </Accordion>
 
 <Accordion title="Content Type Requirements">
-Message content must be a string, not an array. Array content needs to be converted to a string before sending to the SDK.
+Message content must be a string, not an array. Array content needs to be converted to a string before passing to the SDK.
 </Accordion>
 </AccordionGroup>