chore: migrate examples to use latest sdk ver (#690)

examples/docs/agent_advanced.py

@@ -1,29 +1,36 @@
-from letta import ChatMemory, EmbeddingConfig, LLMConfig, create_client
+from letta_client import CreateBlock, Letta, MessageCreate
+
 from letta.prompts import gpt_system
 
-client = create_client()
+"""
+Make sure you run the Letta server before running this example.
+```
+letta server
+```
+"""
+
+client = Letta(base_url="http://localhost:8283")
 
 # create a new agent
-agent_state = client.create_agent(
+agent_state = client.agents.create(
     # agent's name (unique per-user, autogenerated if not provided)
     name="agent_name",
     # in-context memory representation with human/persona blocks
-    memory=ChatMemory(human="Name: Sarah", persona="You are a helpful assistant that loves emojis"),
+    memory_blocks=[
+        CreateBlock(
+            label="human",
+            value="Name: Sarah",
+        ),
+        CreateBlock(
+            label="persona",
+            value="You are a helpful assistant that loves emojis",
+        ),
+    ],
     # LLM model & endpoint configuration
-    llm_config=LLMConfig(
-        model="gpt-4",
-        model_endpoint_type="openai",
-        model_endpoint="https://api.openai.com/v1",
-        context_window=8000,  # set to <= max context window
-    ),
+    llm="openai/gpt-4",
+    context_window_limit=8000,
     # embedding model & endpoint configuration (cannot be changed)
-    embedding_config=EmbeddingConfig(
-        embedding_endpoint_type="openai",
-        embedding_endpoint="https://api.openai.com/v1",
-        embedding_model="text-embedding-ada-002",
-        embedding_dim=1536,
-        embedding_chunk_size=300,
-    ),
+    embedding="openai/text-embedding-ada-002",
     # system instructions for the agent (defaults to `memgpt_chat`)
     system=gpt_system.get_system_text("memgpt_chat"),
     # whether to include base letta tools (default: True)
@@ -34,14 +41,30 @@ agent_state = client.create_agent(
 print(f"Created agent with name {agent_state.name} and unique ID {agent_state.id}")
 
 # message an agent as a user
-response = client.send_message(agent_id=agent_state.id, role="user", message="hello")
+response = client.agents.messages.send(
+    agent_id=agent_state.id, 
+    messages=[
+        MessageCreate(
+            role="user",
+            text="hello",
+        )
+    ],
+)
 print("Usage", response.usage)
 print("Agent messages", response.messages)
 
 # message a system message (non-user)
-response = client.send_message(agent_id=agent_state.id, role="system", message="[system] user has logged in. send a friendly message.")
+response = client.agents.messages.send(
+    agent_id=agent_state.id, 
+    messages=[
+        MessageCreate(
+            role="system",
+            text="[system] user has logged in. send a friendly message.",
+        )
+    ],
+)
 print("Usage", response.usage)
 print("Agent messages", response.messages)
 
 # delete the agent
-client.delete_agent(agent_id=agent_state.id)
+client.agents.delete(agent_id=agent_state.id)

examples/docs/agent_basic.py

@@ -1,29 +1,49 @@
-from letta import EmbeddingConfig, LLMConfig, create_client
+from letta_client import CreateBlock, Letta, MessageCreate
 
-client = create_client()
+"""
+Make sure you run the Letta server before running this example.
+```
+letta server
+```
+"""
 
-# set automatic defaults for LLM/embedding config
-client.set_default_llm_config(LLMConfig.default_config(model_name="gpt-4"))
-client.set_default_embedding_config(EmbeddingConfig.default_config(model_name="text-embedding-ada-002"))
+client = Letta(base_url="http://localhost:8283")
 
 # create a new agent
-agent_state = client.create_agent()
+agent_state = client.agents.create(
+    memory_blocks=[
+        CreateBlock(
+            label="human",
+            value="Name: Sarah",
+        ),
+    ],
+    # set automatic defaults for LLM/embedding config
+    llm="openai/gpt-4",
+    embedding="openai/text-embedding-ada-002",
+)
 print(f"Created agent with name {agent_state.name} and unique ID {agent_state.id}")
 
 # Message an agent
-response = client.send_message(agent_id=agent_state.id, role="user", message="hello")
+response = client.agents.messages.send(
+    agent_id=agent_state.id,
+    messages=[
+        MessageCreate(
+            role="user",
+            text="hello",
+        )
+    ],
+)
 print("Usage", response.usage)
 print("Agent messages", response.messages)
 
 # list all agents
-agents = client.list_agents()
+agents = client.agents.list()
 
 # get the agent by ID
-agent_state = client.get_agent(agent_id=agent_state.id)
+agent_state = client.agents.get(agent_id=agent_state.id)
 
 # get the agent by name
-agent_id = client.get_agent_id(agent_name=agent_state.name)
-agent_state = client.get_agent(agent_id=agent_id)
+agent_state = client.agents.list(name=agent_state.name)[0]
 
 # delete an agent
-client.delete_agent(agent_id=agent_state.id)
+client.agents.delete(agent_id=agent_state.id)

examples/docs/rest_client.py

@@ -1,5 +1,4 @@
-from letta import create_client
-from letta.schemas.memory import ChatMemory
+from letta_client import CreateBlock, Letta, MessageCreate
 
 """
 Make sure you run the Letta server before running this example.
@@ -11,30 +10,47 @@ letta server
 
 def main():
     # Connect to the server as a user
-    client = create_client(base_url="http://localhost:8283")
+    client = Letta(base_url="http://localhost:8283")
 
     # list available configs on the server
-    llm_configs = client.list_llm_configs()
+    llm_configs = client.models.list_llms()
     print(f"Available LLM configs: {llm_configs}")
-    embedding_configs = client.list_embedding_configs()
+    embedding_configs = client.models.list_embedding_models()
     print(f"Available embedding configs: {embedding_configs}")
 
     # Create an agent
-    agent_state = client.create_agent(
+    agent_state = client.agents.create(
         name="my_agent",
-        memory=ChatMemory(human="My name is Sarah.", persona="I am a friendly AI."),
-        embedding_config=embedding_configs[0],
-        llm_config=llm_configs[0],
+        memory_blocks=[
+            CreateBlock(
+                label="human",
+                value="My name is Sarah",
+            ),
+            CreateBlock(
+                label="persona",
+                value="I am a friendly AI",
+            ),
+        ],
+        llm=llm_configs[0].handle,
+        embedding=embedding_configs[0].handle,
     )
     print(f"Created agent: {agent_state.name} with ID {str(agent_state.id)}")
 
     # Send a message to the agent
     print(f"Created agent: {agent_state.name} with ID {str(agent_state.id)}")
-    response = client.user_message(agent_id=agent_state.id, message="Whats my name?")
+    response = client.agents.messages.send(
+        agent_id=agent_state.id, 
+        messages=[
+            MessageCreate(
+                role="user",
+                text="Whats my name?",
+            )
+        ],
+    )
     print(f"Received response:", response.messages)
 
     # Delete agent
-    client.delete_agent(agent_id=agent_state.id)
+    client.agents.delete(agent_id=agent_state.id)
     print(f"Deleted agent: {agent_state.name} with ID {str(agent_state.id)}")
 
 

examples/docs/tools.py

@@ -1,11 +1,14 @@
-from letta import EmbeddingConfig, LLMConfig, create_client
-from letta.schemas.tool_rule import TerminalToolRule
+from letta_client import CreateBlock, Letta, MessageCreate
+from letta_client.types import TerminalToolRule
 
-client = create_client()
-# set automatic defaults for LLM/embedding config
-client.set_default_llm_config(LLMConfig.default_config(model_name="gpt-4"))
-client.set_default_embedding_config(EmbeddingConfig.default_config(model_name="text-embedding-ada-002"))
+"""
+Make sure you run the Letta server before running this example.
+```
+letta server
+```
+"""
 
+client = Letta(base_url="http://localhost:8283")
 
 # define a function with a docstring
 def roll_d20() -> str:
@@ -30,43 +33,78 @@ def roll_d20() -> str:
 
 
 # create a tool from the function
-tool = client.create_or_update_tool(roll_d20)
+tool = client.tools.upsert_from_function(func=roll_d20, name="roll_d20")
 print(f"Created tool with name {tool.name}")
 
 # create a new agent
-agent_state = client.create_agent(
+agent_state = client.agents.create(
+    memory_blocks=[
+        CreateBlock(
+            label="human",
+            value="Name: Sarah",
+        ),
+    ],
+    # set automatic defaults for LLM/embedding config
+    llm="openai/gpt-4",
+    embedding="openai/text-embedding-ada-002",
     # create the agent with an additional tool
     tool_ids=[tool.id],
-    # add tool rules that terminate execution after specific tools
     tool_rules=[
         # exit after roll_d20 is called
         TerminalToolRule(tool_name=tool.name),
         # exit after send_message is called (default behavior)
         TerminalToolRule(tool_name="send_message"),
-    ],
+    ]
 )
 print(f"Created agent with name {agent_state.name} with tools {[t.name for t in agent_state.tools]}")
 
 # Message an agent
-response = client.send_message(agent_id=agent_state.id, role="user", message="roll a dice")
+response = client.agents.messages.send(
+    agent_id=agent_state.id, 
+    messages=[
+        MessageCreate(
+            role="user",
+            text="roll a dice",
+        )
+    ],
+)
 print("Usage", response.usage)
 print("Agent messages", response.messages)
 
 # remove a tool from the agent
-client.remove_tool_from_agent(agent_id=agent_state.id, tool_id=tool.id)
+client.agents.tools.remove(agent_id=agent_state.id, tool_id=tool.id)
 
 # add a tool to the agent
-client.add_tool_to_agent(agent_id=agent_state.id, tool_id=tool.id)
+client.agents.tools.add(agent_id=agent_state.id, tool_id=tool.id)
 
-client.delete_agent(agent_id=agent_state.id)
+client.agents.delete(agent_id=agent_state.id)
 
 # create an agent with only a subset of default tools
-send_message_tool = client.get_tool_id("send_message")
-agent_state = client.create_agent(include_base_tools=False, tool_ids=[tool.id, send_message_tool])
+send_message_tool = client.tools.get_by_name(tool_name="send_message")
+agent_state = client.agents.create(
+    memory_blocks=[
+        CreateBlock(
+            label="human",
+            value="username: sarah",
+        ),
+    ],
+    llm="openai/gpt-4",
+    embedding="openai/text-embedding-ada-002",
+    include_base_tools=False, 
+    tool_ids=[tool.id, send_message_tool],
+)
 
 # message the agent to search archival memory (will be unable to do so)
-response = client.send_message(agent_id=agent_state.id, role="user", message="search your archival memory")
+client.agents.messages.send(
+    agent_id=agent_state.id,
+    messages=[
+        MessageCreate(
+            role="user",
+            text="search your archival memory",
+        )
+    ],
+)
 print("Usage", response.usage)
 print("Agent messages", response.messages)
 
-client.delete_agent(agent_id=agent_state.id)
+client.agents.delete(agent_id=agent_state.id)