fix: patch api routes (#2374)

examples/docs/agent_advanced.py

@@ -27,7 +27,7 @@
         ),
     ],
     # LLM model & endpoint configuration
-    llm="openai/gpt-4",
+    model="openai/gpt-4",
     context_window_limit=8000,
     # embedding model & endpoint configuration (cannot be changed)
     embedding="openai/text-embedding-ada-002",

examples/docs/agent_basic.py

@@ -18,7 +18,7 @@
         ),
     ],
     # set automatic defaults for LLM/embedding config
-    llm="openai/gpt-4",
+    model="openai/gpt-4",
     embedding="openai/text-embedding-ada-002",
 )
 print(f"Created agent with name {agent_state.name} and unique ID {agent_state.id}")

examples/docs/rest_client.py

@@ -31,7 +31,7 @@ def main():
                 value="I am a friendly AI",
             ),
         ],
-        llm=llm_configs[0].handle,
+        model=llm_configs[0].handle,
         embedding=embedding_configs[0].handle,
     )
     print(f"Created agent: {agent_state.name} with ID {str(agent_state.id)}")

examples/docs/tools.py

@@ -45,7 +45,7 @@ def roll_d20() -> str:
         ),
     ],
     # set automatic defaults for LLM/embedding config
-    llm="openai/gpt-4",
+    model="openai/gpt-4",
     embedding="openai/text-embedding-ada-002",
     # create the agent with an additional tool
     tool_ids=[tool.id],
@@ -88,7 +88,7 @@ def roll_d20() -> str:
             value="username: sarah",
         ),
     ],
-    llm="openai/gpt-4",
+    model="openai/gpt-4",
     embedding="openai/text-embedding-ada-002",
     include_base_tools=False, 
     tool_ids=[tool.id, send_message_tool],

examples/notebooks/Agentic RAG with Letta.ipynb

@@ -118,7 +118,7 @@
     "            value=\"Name: Sarah\",\n",
     "        ),\n",
     "    ],\n",
-    "    llm=\"openai/gpt-4\",\n",
+    "    model=\"openai/gpt-4\",\n",
     "    embedding=\"openai/text-embedding-ada-002\",\n",
     ")"
    ]
@@ -305,7 +305,7 @@
     "        ),\n",
     "    ],\n",
     "    # set automatic defaults for LLM/embedding config\n",
-    "    llm=\"openai/gpt-4\",\n",
+    "    model=\"openai/gpt-4\",\n",
     "    embedding=\"openai/text-embedding-ada-002\",\n",
     ")\n",
     "normal_agent.tools"
@@ -345,7 +345,7 @@
     "        ),\n",
     "    ],\n",
     "    # set automatic defaults for LLM/embedding config\n",
-    "    llm=\"openai/gpt-4\",\n",
+    "    model=\"openai/gpt-4\",\n",
     "    embedding=\"openai/text-embedding-ada-002\",\n",
     "    tools=['send_message'], \n",
     "    include_base_tools=False\n",
@@ -422,7 +422,7 @@
     "            + \"that you use to lookup information about users' birthdays.\"\n",
     "        ),\n",
     "    ],\n",
-    "    llm=\"openai/gpt-4\",\n",
+    "    model=\"openai/gpt-4\",\n",
     "    embedding=\"openai/text-embedding-ada-002\"\n",
     ")"
    ]
@@ -852,7 +852,7 @@
     "        ),\n",
     "    ],\n",
     "    tool_ids=[search_tool.id], \n",
-    "    llm=\"openai/gpt-4\",\n",
+    "    model=\"openai/gpt-4\",\n",
     ")"
    ]
   },

examples/notebooks/Multi-agent recruiting workflow.ipynb

@@ -182,7 +182,7 @@
     "    ],\n",
     "    block_ids=[org_block.id],\n",
     "    tool_ids=[read_resume_tool.id, submit_evaluation_tool.id]\n",
-    "    llm=\"openai/gpt-4\",\n",
+    "    model=\"openai/gpt-4\",\n",
     "    embedding=\"openai/text-embedding-ada-002\",\n",
     ")\n"
    ]
@@ -251,7 +251,7 @@
     "    ],\n",
     "    block_ids=[org_block.id],\n",
     "    tool_ids=[email_candidate_tool.id]\n",
-    "    llm=\"openai/gpt-4\",\n",
+    "    model=\"openai/gpt-4\",\n",
     "    embedding=\"openai/text-embedding-ada-002\",\n",
     ")"
    ]
@@ -623,7 +623,7 @@
     "    ],\n",
     "    block_ids=[org_block.id],\n",
     "    tool_ids=[read_resume_tool.id, submit_evaluation_tool.id]\n",
-    "    llm=\"openai/gpt-4\",\n",
+    "    model=\"openai/gpt-4\",\n",
     "    embedding=\"openai/text-embedding-ada-002\",\n",
     ")\n",
     "\n",
@@ -637,7 +637,7 @@
     "    ],\n",
     "    block_ids=[org_block.id],\n",
     "    tool_ids=[email_candidate_tool.id]\n",
-    "    llm=\"openai/gpt-4\",\n",
+    "    model=\"openai/gpt-4\",\n",
     "    embedding=\"openai/text-embedding-ada-002\",\n",
     ")"
    ]
@@ -740,7 +740,7 @@
     "    ],\n",
     "    block_ids=[org_block.id],\n",
     "    tool_ids=[search_candidate_tool.id, consider_candidate_tool.id],\n",
-    "    llm=\"openai/gpt-4\",\n",
+    "    model=\"openai/gpt-4\",\n",
     "    embedding=\"openai/text-embedding-ada-002\"\n",
     ")\n",
     "    \n"

letta/client/client.py

@@ -776,7 +776,7 @@ def get_in_context_memory(self, agent_id: str) -> Memory:
         Returns:
             memory (Memory): In-context memory of the agent
         """
-        response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/memory", headers=self.headers)
+        response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core_memory", headers=self.headers)
         if response.status_code != 200:
             raise ValueError(f"Failed to get in-context memory: {response.text}")
         return Memory(**response.json())
@@ -797,7 +797,7 @@ def update_in_context_memory(self, agent_id: str, section: str, value: Union[Lis
         """
         memory_update_dict = {section: value}
         response = requests.patch(
-            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/memory", json=memory_update_dict, headers=self.headers
+            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core_memory", json=memory_update_dict, headers=self.headers
         )
         if response.status_code != 200:
             raise ValueError(f"Failed to update in-context memory: {response.text}")
@@ -814,10 +814,10 @@ def get_archival_memory_summary(self, agent_id: str) -> ArchivalMemorySummary:
             summary (ArchivalMemorySummary): Summary of the archival memory
 
         """
-        response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/memory/archival", headers=self.headers)
+        response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/context", headers=self.headers)
         if response.status_code != 200:
             raise ValueError(f"Failed to get archival memory summary: {response.text}")
-        return ArchivalMemorySummary(**response.json())
+        return ArchivalMemorySummary(size=response.json().get("num_archival_memory", 0))
 
     def get_recall_memory_summary(self, agent_id: str) -> RecallMemorySummary:
         """
@@ -829,10 +829,10 @@ def get_recall_memory_summary(self, agent_id: str) -> RecallMemorySummary:
         Returns:
             summary (RecallMemorySummary): Summary of the recall memory
         """
-        response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/memory/recall", headers=self.headers)
+        response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/context", headers=self.headers)
         if response.status_code != 200:
             raise ValueError(f"Failed to get recall memory summary: {response.text}")
-        return RecallMemorySummary(**response.json())
+        return RecallMemorySummary(size=response.json().get("num_recall_memory", 0))
 
     def get_in_context_messages(self, agent_id: str) -> List[Message]:
         """
@@ -844,10 +844,10 @@ def get_in_context_messages(self, agent_id: str) -> List[Message]:
         Returns:
             messages (List[Message]): List of in-context messages
         """
-        response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/memory/messages", headers=self.headers)
+        response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/context", headers=self.headers)
         if response.status_code != 200:
-            raise ValueError(f"Failed to get in-context messages: {response.text}")
-        return [Message(**message) for message in response.json()]
+            raise ValueError(f"Failed to get recall memory summary: {response.text}")
+        return [Message(**message) for message in response.json().get("messages", "")]
 
     # agent interactions
 
@@ -889,7 +889,9 @@ def get_archival_memory(
             params["before"] = str(before)
         if after:
             params["after"] = str(after)
-        response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{str(agent_id)}/archival", params=params, headers=self.headers)
+        response = requests.get(
+            f"{self.base_url}/{self.api_prefix}/agents/{str(agent_id)}/archival_memory", params=params, headers=self.headers
+        )
         assert response.status_code == 200, f"Failed to get archival memory: {response.text}"
         return [Passage(**passage) for passage in response.json()]
 
@@ -906,7 +908,7 @@ def insert_archival_memory(self, agent_id: str, memory: str) -> List[Passage]:
         """
         request = CreateArchivalMemory(text=memory)
         response = requests.post(
-            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/archival", headers=self.headers, json=request.model_dump()
+            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/archival_memory", headers=self.headers, json=request.model_dump()
         )
         if response.status_code != 200:
             raise ValueError(f"Failed to insert archival memory: {response.text}")
@@ -920,7 +922,7 @@ def delete_archival_memory(self, agent_id: str, memory_id: str):
             agent_id (str): ID of the agent
             memory_id (str): ID of the memory
         """
-        response = requests.delete(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/archival/{memory_id}", headers=self.headers)
+        response = requests.delete(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/archival_memory/{memory_id}", headers=self.headers)
         assert response.status_code == 200, f"Failed to delete archival memory: {response.text}"
 
     # messages (recall memory)
@@ -1463,12 +1465,14 @@ def get_tool_id(self, tool_name: str):
         Returns:
             id (str): ID of the tool (`None` if not found)
         """
-        response = requests.get(f"{self.base_url}/{self.api_prefix}/tools/name/{tool_name}", headers=self.headers)
-        if response.status_code == 404:
-            return None
-        elif response.status_code != 200:
+        response = requests.get(f"{self.base_url}/{self.api_prefix}/tools", headers=self.headers)
+        if response.status_code != 200:
             raise ValueError(f"Failed to get tool: {response.text}")
-        return response.json()
+
+        tools = [tool for tool in [Tool(**tool) for tool in response.json()] if tool.name == tool_name]
+        if not tools:
+            return None
+        return tools[0].id
 
     def upsert_base_tools(self) -> List[Tool]:
         response = requests.post(f"{self.base_url}/{self.api_prefix}/tools/add-base-tools/", headers=self.headers)
@@ -1852,7 +1856,7 @@ def add_agent_memory_block(self, agent_id: str, create_block: CreateBlock) -> Me
             memory (Memory): The updated memory
         """
         response = requests.post(
-            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/memory/block",
+            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core_memory/blocks",
             headers=self.headers,
             json=create_block.model_dump(),
         )
@@ -1893,14 +1897,14 @@ def remove_agent_memory_block(self, agent_id: str, block_label: str) -> Memory:
             memory (Memory): The updated memory
         """
         response = requests.delete(
-            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/memory/block/{block_label}",
+            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core_memory/blocks/{block_label}",
             headers=self.headers,
         )
         if response.status_code != 200:
             raise ValueError(f"Failed to remove agent memory block: {response.text}")
         return Memory(**response.json())
 
-    def get_agent_memory_blocks(self, agent_id: str) -> List[Block]:
+    def list_agent_memory_blocks(self, agent_id: str) -> List[Block]:
         """
         Get all the blocks in the agent's core memory
 
@@ -1910,7 +1914,7 @@ def get_agent_memory_blocks(self, agent_id: str) -> List[Block]:
         Returns:
             blocks (List[Block]): The blocks in the agent's core memory
         """
-        response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/memory/block", headers=self.headers)
+        response = requests.get(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core_memory/blocks", headers=self.headers)
         if response.status_code != 200:
             raise ValueError(f"Failed to get agent memory blocks: {response.text}")
         return [Block(**block) for block in response.json()]
@@ -1927,7 +1931,7 @@ def get_agent_memory_block(self, agent_id: str, label: str) -> Block:
             block (Block): The block corresponding to the label
         """
         response = requests.get(
-            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/memory/block/{label}",
+            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core_memory/blocks/{label}",
             headers=self.headers,
         )
         if response.status_code != 200:
@@ -1960,7 +1964,7 @@ def update_agent_memory_block(
         if limit:
             data["limit"] = limit
         response = requests.patch(
-            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/memory/block/{label}",
+            f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/core_memory/blocks/{label}",
             headers=self.headers,
             json=data,
         )
@@ -3523,7 +3527,7 @@ def remove_agent_memory_block(self, agent_id: str, block_label: str) -> Memory:
         """
         return self.server.agent_manager.detach_block_with_label(agent_id=agent_id, block_label=block_label, actor=self.user)
 
-    def get_agent_memory_blocks(self, agent_id: str) -> List[Block]:
+    def list_agent_memory_blocks(self, agent_id: str) -> List[Block]:
         """
         Get all the blocks in the agent's core memory
 

letta/schemas/agent.py

@@ -123,7 +123,7 @@ class CreateAgent(BaseModel, validate_assignment=True):  #
     )
     description: Optional[str] = Field(None, description="The description of the agent.")
     metadata_: Optional[Dict] = Field(None, description="The metadata of the agent.", alias="metadata_")
-    llm: Optional[str] = Field(
+    model: Optional[str] = Field(
         None,
         description="The LLM configuration handle used by the agent, specified in the format "
         "provider/model-name, as an alternative to specifying llm_config.",
@@ -139,7 +139,7 @@ class CreateAgent(BaseModel, validate_assignment=True):  #
     tool_exec_environment_variables: Optional[Dict[str, str]] = Field(
         None, description="The environment variables for tool execution specific to this agent."
     )
-    variables: Optional[Dict[str, str]] = Field(None, description="The variables that should be set for the agent.")
+    memory_variables: Optional[Dict[str, str]] = Field(None, description="The variables that should be set for the agent.")
 
     @field_validator("name")
     @classmethod
@@ -166,26 +166,26 @@ def validate_name(cls, name: str) -> str:
 
         return name
 
-    @field_validator("llm")
+    @field_validator("model")
     @classmethod
-    def validate_llm(cls, llm: Optional[str]) -> Optional[str]:
-        if not llm:
-            return llm
+    def validate_model(cls, model: Optional[str]) -> Optional[str]:
+        if not model:
+            return model
 
-        provider_name, model_name = llm.split("/", 1)
+        provider_name, model_name = model.split("/", 1)
         if not provider_name or not model_name:
             raise ValueError("The llm config handle should be in the format provider/model-name")
 
-        return llm
+        return model
 
     @field_validator("embedding")
     @classmethod
     def validate_embedding(cls, embedding: Optional[str]) -> Optional[str]:
         if not embedding:
             return embedding
 
-        provider_name, model_name = embedding.split("/", 1)
-        if not provider_name or not model_name:
+        provider_name, embedding_name = embedding.split("/", 1)
+        if not provider_name or not embedding_name:
             raise ValueError("The embedding config handle should be in the format provider/model-name")
 
         return embedding