# agentstate — conversation history that lives at the edge.

import { AgentState } from "@agentstate/sdk";

const client = new AgentState({ apiKey: process.env.AS_KEY });

const conv = await client.createConversation({
  messages: [{ role: "user", content: "Summarize findings" }],
});

const { data } = await client.searchConversations({
  query: "summarize",
});

import { AgentState } from "@agentstate/sdk";
import { createAISDKChatStore } from "@agentstate/sdk/ai-sdk";

const client = new AgentState({ apiKey: process.env.AS_KEY });
const store = createAISDKChatStore(client);

const chatId = await store.createChat();
await store.saveChat({ chatId, messages });
const messages = await store.loadChat(chatId);

import { AgentState } from "@agentstate/sdk";
import { AgentStateCheckpointSaver } from "@agentstate/sdk/langgraph";

const client = new AgentState({ apiKey: process.env.AS_KEY });
const saver = new AgentStateCheckpointSaver(client);

const graph = workflow.compile({ checkpointer: saver });

from agentstate import AgentStateClient

client = AgentStateClient(api_key="as_live_...")

conv = client.create_conversation(
    messages=[{"role": "user", "content": "Hello!"}]
)
messages = client.get_conversation(conv.id).messages

curl -X POST https://agentstate.app/api/v1/conversations \
  -H "Authorization: Bearer as_live_..." \
  -H "Content-Type: application/json" \
  -d '{"messages":[{"role":"user","content":"Hi"}]}'

import { AgentState } from "@agentstate/sdk";

const client = new AgentState({
  apiKey: process.env.AGENTSTATE_API_KEY!,
});

// Create with metadata + tags
const conv = await client.createConversation({
  title: "Research session",
  messages: [
    { role: "user", content: "Compare lease strategies" },
    { role: "assistant", content: "Use TTL + renew..." },
  ],
  metadata: { agent_id: "researcher-1" },
});

await client.appendMessages(conv.id, [
  { role: "user", content: "Show the recipe" },
]);

const hits = await client.searchConversations({
  query: "lease",
  limit: 10,
});
// → docs: /docs#conversations

from agentstate import AgentStateClient

client = AgentStateClient(api_key="as_live_...")

conv = client.create_conversation(
    title="Research session",
    messages=[
        {"role": "user", "content": "Compare lease strategies"},
        {"role": "assistant", "content": "Use TTL + renew..."},
    ],
    metadata={"agent_id": "researcher-1"},
)

client.append_messages(conv.id, [
    {"role": "user", "content": "Show the recipe"},
])

hits = client.search_conversations(query="lease", limit=10)
# → pip install agentstate  |  docs: /docs#quickstart

import { AgentState } from "@agentstate/sdk";
import { createAISDKChatStore } from "@agentstate/sdk/ai-sdk";

const client = new AgentState({ apiKey: process.env.AS_KEY! });
const store = createAISDKChatStore(client, {
  // optional: namespace chats under a project prefix
});

const chatId = await store.createChat();
await store.saveChat({
  chatId,
  messages: [
    { role: "user", content: "Plan the migration" },
    { role: "assistant", content: "Step 1..." },
  ],
});

const history = await store.loadChat(chatId);
// → examples/ai-sdk-ui  |  docs: /docs#ai-sdk

import { AgentState } from "@agentstate/sdk";
import { AgentStateCheckpointSaver } from "@agentstate/sdk/langgraph";

const client = new AgentState({ apiKey: process.env.AS_KEY! });
const checkpointer = new AgentStateCheckpointSaver(client);

const graph = workflow.compile({ checkpointer });

const result = await graph.invoke(
  { messages: [{ role: "user", content: "Start" }] },
  { configurable: { thread_id: "thread-42" } },
);
// → examples/langgraph-js  |  @agentstate/sdk/langgraph

from agentstate import AgentStateClient
from agentstate.langgraph import AgentStateCheckpointSaver

client = AgentStateClient(api_key="as_live_...")
saver = AgentStateCheckpointSaver(client)

config = {"configurable": {"thread_id": "thread-42"}}
saver.put(
    config,
    {"id": "ckpt-1", "values": {"phase": "start"}},
    {"note": "first checkpoint"},
    {},
)
# → pip install agentstate[langgraph]
# → examples/langgraph-python

import { AgentState, AgentStateError } from "@agentstate/sdk";

const client = new AgentState({ apiKey: process.env.AS_KEY! });
const stateKey = "task:migrate-db";

try {
  const lease = await client.createStateLease(stateKey, {
    holder_id: "worker-3",
    ttl_ms: 30_000,
  });
  // ... do exclusive work ...
  await client.releaseStateLease(lease.id);
} catch (err) {
  if (err instanceof AgentStateError && err.status === 409) {
    // another worker holds the lease — skip
  }
}
// → examples/fleet-leases  |  recipes/leases

{
  "mcpServers": {
    "agentstate": {
      "type": "http",
      "url": "https://agentstate.app/api/mcp",
      "headers": {
        "Authorization": "Bearer as_live_your_key"
      }
    }
  }
}

# Create
curl -X POST https://agentstate.app/api/v1/conversations \
  -H "Authorization: Bearer as_live_..." \
  -H "Content-Type: application/json" \
  -d '{"messages":[{"role":"user","content":"Hi"}]}'

# Search
curl "https://agentstate.app/api/v1/conversations/search?q=lease" \
  -H "Authorization: Bearer as_live_..."

# OpenAPI
curl https://agentstate.app/openapi.json