mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-07-29 15:23:51 +00:00
flesh out memory banks API
This commit is contained in:
parent
31289e3f47
commit
77d6055d9f
11 changed files with 1792 additions and 974 deletions
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@ -10,13 +10,13 @@ from typing import Any, Dict, List, Literal, Optional, Union
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from llama_models.schema_utils import json_schema_type
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from pydantic import BaseModel, ConfigDict, Field, validator
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from pydantic import BaseModel, ConfigDict, Field
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from typing_extensions import Annotated
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from llama_toolchain.common.deployment_types import * # noqa: F403
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from llama_toolchain.inference.api import * # noqa: F403
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from llama_toolchain.safety.api.datatypes import * # noqa: F403
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from llama_toolchain.memory.api.datatypes import * # noqa: F403
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from llama_toolchain.safety.api import * # noqa: F403
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from llama_toolchain.memory.api import * # noqa: F403
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@json_schema_type
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@ -25,31 +25,81 @@ class Attachment(BaseModel):
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mime_type: str
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class AgenticSystemBuiltinTool(BuiltinTool):
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class AgenticSystemTool(Enum):
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brave_search = "brave_search"
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wolfram_alpha = "wolfram_alpha"
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photogen = "photogen"
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code_interpreter = "code_interpreter"
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function_call = "function_call"
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memory = "memory"
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@json_schema_type
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class AgenticSystemToolDefinition(BaseModel):
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tool_name: Union[AgenticSystemBuiltinTool, str]
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description: Optional[str] = None
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parameters: Optional[Dict[str, ToolParamDefinition]] = None
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@validator("tool_name", pre=True)
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@classmethod
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def validate_field(cls, v):
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if isinstance(v, str):
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try:
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return AgenticSystemBuiltinTool(v)
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except ValueError:
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return v
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return v
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execution_config: Optional[RestAPIExecutionConfig] = None
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class ToolDefinitionCommon(BaseModel):
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input_shields: Optional[List[ShieldDefinition]] = Field(default_factory=list)
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output_shields: Optional[List[ShieldDefinition]] = Field(default_factory=list)
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@json_schema_type
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class BraveSearchToolDefinition(ToolDefinitionCommon):
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type: Literal[AgenticSystemTool.brave_search.value] = (
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AgenticSystemTool.brave_search.value
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)
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remote_execution: Optional[RestAPIExecutionConfig] = None
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@json_schema_type
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class WolframAlphaToolDefinition(ToolDefinitionCommon):
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type: Literal[AgenticSystemTool.wolfram_alpha.value] = (
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AgenticSystemTool.wolfram_alpha.value
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)
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remote_execution: Optional[RestAPIExecutionConfig] = None
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@json_schema_type
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class PhotogenToolDefinition(ToolDefinitionCommon):
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type: Literal[AgenticSystemTool.photogen.value] = AgenticSystemTool.photogen.value
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remote_execution: Optional[RestAPIExecutionConfig] = None
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@json_schema_type
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class CodeInterpreterToolDefinition(ToolDefinitionCommon):
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type: Literal[AgenticSystemTool.code_interpreter.value] = (
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AgenticSystemTool.code_interpreter.value
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)
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enable_inline_code_execution: bool = True
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remote_execution: Optional[RestAPIExecutionConfig] = None
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@json_schema_type
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class FunctionCallToolDefinition(ToolDefinitionCommon):
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type: Literal[AgenticSystemTool.function_call.value] = (
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AgenticSystemTool.function_call.value
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)
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description: str
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parameters: Dict[str, ToolParamDefinition]
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remote_execution: Optional[RestAPIExecutionConfig] = None
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@json_schema_type
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class MemoryToolDefinition(ToolDefinitionCommon):
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type: Literal[AgenticSystemTool.memory.value] = AgenticSystemTool.memory.value
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memory_banks: List[MemoryBank] = Field(default_factory=list)
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AgenticSystemToolDefinition = Annotated[
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Union[
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BraveSearchToolDefinition,
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WolframAlphaToolDefinition,
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PhotogenToolDefinition,
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CodeInterpreterToolDefinition,
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FunctionCallToolDefinition,
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MemoryToolDefinition,
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],
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Field(discriminator="type"),
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]
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class StepCommon(BaseModel):
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turn_id: str
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step_id: str
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@ -136,27 +186,45 @@ class Session(BaseModel):
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started_at: datetime
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@json_schema_type
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class MemoryConfig(BaseModel):
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memory_bank_id: str
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class MemoryBankConfigCommon(BaseModel):
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bank_id: str
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# this configuration can hold other information we may want to configure
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# how will the agent use the memory bank API?
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#
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#
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class VectorMemoryBankConfig(MemoryBankConfigCommon):
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type: Literal[MemoryBankType.vector.value] = MemoryBankType.vector.value
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class KeyValueMemoryBankConfig(MemoryBankConfigCommon):
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type: Literal[MemoryBankType.keyvalue.value] = MemoryBankType.keyvalue.value
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keys: List[str] # what keys to focus on
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class KeywordMemoryBankConfig(MemoryBankConfigCommon):
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type: Literal[MemoryBankType.keyword.value] = MemoryBankType.keyword.value
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class GraphMemoryBankConfig(MemoryBankConfigCommon):
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type: Literal[MemoryBankType.graph.value] = MemoryBankType.graph.value
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entities: List[str] # what entities to focus on
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MemoryBankConfig = Annotated[
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Union[
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VectorMemoryBankConfig,
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KeyValueMemoryBankConfig,
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KeywordMemoryBankConfig,
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GraphMemoryBankConfig,
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],
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Field(discriminator="type"),
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]
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class AgentConfigCommon(BaseModel):
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sampling_params: Optional[SamplingParams] = SamplingParams()
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memory_configs: Optional[List[MemoryConfig]] = Field(default_factory=list)
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input_shields: Optional[List[ShieldDefinition]] = Field(default_factory=list)
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output_shields: Optional[List[ShieldDefinition]] = Field(default_factory=list)
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# if you completely want to replace the messages prefixed by the system,
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# this is debug only
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debug_prefix_messages: Optional[List[Message]] = Field(default_factory=list)
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tools: Optional[List[AgenticSystemToolDefinition]] = Field(default_factory=list)
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tool_choice: Optional[ToolChoice] = Field(default=ToolChoice.auto)
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tool_prompt_format: Optional[ToolPromptFormat] = Field(
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@ -168,6 +236,7 @@ class AgentConfigCommon(BaseModel):
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class AgentConfig(AgentConfigCommon):
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model: str
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instructions: str
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memory_bank_configs: Optional[List[MemoryBankConfig]] = Field(default_factory=list)
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class AgentConfigOverridablePerTurn(AgentConfigCommon):
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@ -10,21 +10,9 @@ from typing import Protocol
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from llama_models.schema_utils import json_schema_type, webmethod
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@json_schema_type
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class AgenticSystemCreateRequest(BaseModel):
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agent_config: AgentConfig
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@json_schema_type
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class AgenticSystemCreateResponse(BaseModel):
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# TODO: rename this to agent_id
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system_id: str
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@json_schema_type
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class AgenticSystemSessionCreateRequest(BaseModel):
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system_id: str
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session_name: str
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agent_id: str
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@json_schema_type
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@ -33,8 +21,8 @@ class AgenticSystemSessionCreateResponse(BaseModel):
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@json_schema_type
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class AgenticSystemTurnCreateRequest(BaseModel, AgentConfigOverridablePerTurn):
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system_id: str
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class AgenticSystemTurnCreateRequest(AgentConfigOverridablePerTurn):
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agent_id: str
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session_id: str
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# TODO: figure out how we can simplify this and make why
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@ -67,7 +55,7 @@ class AgenticSystem(Protocol):
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@webmethod(route="/agentic_system/create")
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async def create_agentic_system(
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self,
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request: AgenticSystemCreateRequest,
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agent_config: AgentConfig,
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) -> AgenticSystemCreateResponse: ...
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@webmethod(route="/agentic_system/turn/create")
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@ -91,7 +79,8 @@ class AgenticSystem(Protocol):
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@webmethod(route="/agentic_system/session/create")
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async def create_agentic_system_session(
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self,
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request: AgenticSystemSessionCreateRequest,
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agent_id: str,
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session_name: str,
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) -> AgenticSystemSessionCreateResponse: ...
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@webmethod(route="/agentic_system/session/get")
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@ -26,9 +26,7 @@ from llama_toolchain.agentic_system.event_logger import EventLogger
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from .api import (
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AgentConfig,
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AgenticSystem,
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AgenticSystemCreateRequest,
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AgenticSystemCreateResponse,
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AgenticSystemSessionCreateRequest,
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AgenticSystemSessionCreateResponse,
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AgenticSystemToolDefinition,
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AgenticSystemTurnCreateRequest,
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@ -127,27 +125,23 @@ async def run_main(host: str, port: int):
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),
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]
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create_request = AgenticSystemCreateRequest(
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agent_config = AgentConfig(
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model="Meta-Llama3.1-8B-Instruct",
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agent_config=AgentConfig(
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instructions="You are a helpful assistant",
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sampling_params=SamplingParams(),
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available_tools=tool_definitions,
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input_shields=[],
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output_shields=[],
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debug_prefix_messages=[],
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tool_prompt_format=ToolPromptFormat.json,
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),
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instructions="You are a helpful assistant",
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sampling_params=SamplingParams(),
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tools=tool_definitions,
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input_shields=[],
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output_shields=[],
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debug_prefix_messages=[],
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tool_prompt_format=ToolPromptFormat.json,
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)
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create_response = await api.create_agentic_system(create_request)
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create_response = await api.create_agentic_system(agent_config)
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print(create_response)
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session_response = await api.create_agentic_system_session(
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AgenticSystemSessionCreateRequest(
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system_id=create_response.system_id,
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session_name="test_session",
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)
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agent_id=create_response.agent_id,
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session_name="test_session",
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)
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print(session_response)
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@ -162,7 +156,7 @@ async def run_main(host: str, port: int):
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cprint(f"User> {content}", color="blue")
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iterator = api.create_agentic_system_turn(
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AgenticSystemTurnCreateRequest(
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system_id=create_response.system_id,
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agent_id=create_response.agent_id,
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session_id=session_response.session_id,
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messages=[
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UserMessage(content=content),
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@ -8,7 +8,7 @@
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import copy
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import uuid
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from datetime import datetime
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from typing import AsyncGenerator, List, Optional
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from typing import AsyncGenerator, List
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from llama_models.llama3.api.datatypes import ToolPromptFormat
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@ -326,7 +326,7 @@ class ChatAgent(ShieldRunnerMixin):
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req = ChatCompletionRequest(
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model=self.agent_config.model,
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messages=input_messages,
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tools=self.agent_config.available_tools,
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tools=self.agent_config.tools,
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tool_prompt_format=self.agent_config.tool_prompt_format,
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stream=True,
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sampling_params=sampling_params,
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@ -24,7 +24,7 @@ from llama_toolchain.tools.builtin import (
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)
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from llama_toolchain.tools.safety import with_safety
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from .agent_instance import AgentInstance, ChatAgent
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from .agent_instance import ChatAgent
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from .config import MetaReferenceImplConfig
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@ -71,11 +71,11 @@ class MetaReferenceAgenticSystemImpl(AgenticSystem):
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self,
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request: AgenticSystemCreateRequest,
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) -> AgenticSystemCreateResponse:
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system_id = str(uuid.uuid4())
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agent_id = str(uuid.uuid4())
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builtin_tools = []
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cfg = request.agent_config
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for dfn in cfg.available_tools:
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for dfn in cfg.tools:
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if isinstance(dfn.tool_name, BuiltinTool):
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if dfn.tool_name == BuiltinTool.wolfram_alpha:
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key = self.config.wolfram_api_key
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@ -102,7 +102,7 @@ class MetaReferenceAgenticSystemImpl(AgenticSystem):
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)
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)
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AGENT_INSTANCES_BY_ID[system_id] = ChatAgent(
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AGENT_INSTANCES_BY_ID[agent_id] = ChatAgent(
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agent_config=cfg,
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inference_api=self.inference_api,
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safety_api=self.safety_api,
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@ -111,16 +111,16 @@ class MetaReferenceAgenticSystemImpl(AgenticSystem):
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)
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return AgenticSystemCreateResponse(
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system_id=system_id,
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agent_id=agent_id,
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)
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async def create_agentic_system_session(
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self,
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request: AgenticSystemSessionCreateRequest,
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) -> AgenticSystemSessionCreateResponse:
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system_id = request.system_id
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assert system_id in AGENT_INSTANCES_BY_ID, f"System {system_id} not found"
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agent = AGENT_INSTANCES_BY_ID[system_id]
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agent_id = request.agent_id
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assert agent_id in AGENT_INSTANCES_BY_ID, f"System {agent_id} not found"
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agent = AGENT_INSTANCES_BY_ID[agent_id]
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session = agent.create_session(request.session_name)
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return AgenticSystemSessionCreateResponse(
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@ -131,9 +131,9 @@ class MetaReferenceAgenticSystemImpl(AgenticSystem):
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self,
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request: AgenticSystemTurnCreateRequest,
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) -> AsyncGenerator:
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system_id = request.system_id
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assert system_id in AGENT_INSTANCES_BY_ID, f"System {system_id} not found"
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agent = AGENT_INSTANCES_BY_ID[system_id]
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agent_id = request.agent_id
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assert agent_id in AGENT_INSTANCES_BY_ID, f"System {agent_id} not found"
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agent = AGENT_INSTANCES_BY_ID[agent_id]
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assert (
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request.session_id in agent.sessions
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|
|
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@ -19,7 +19,7 @@ from llama_toolchain.inference.api import Message
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async def execute_with_custom_tools(
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system: AgenticSystem,
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system_id: str,
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agent_id: str,
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session_id: str,
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messages: List[Message],
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custom_tools: List[Any],
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@ -35,7 +35,7 @@ async def execute_with_custom_tools(
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n_iter += 1
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request = AgenticSystemTurnCreateRequest(
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system_id=system_id,
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agent_id=agent_id,
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session_id=session_id,
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messages=current_messages,
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stream=stream,
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|
|
|
@ -14,12 +14,7 @@ from llama_models.llama3.api.datatypes import (
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ToolPromptFormat,
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)
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from llama_toolchain.agentic_system.api import (
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AgentConfig,
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AgenticSystemCreateRequest,
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AgenticSystemSessionCreateRequest,
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AgenticSystemToolDefinition,
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)
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from llama_toolchain.agentic_system.api import AgentConfig, AgenticSystemToolDefinition
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from llama_toolchain.agentic_system.client import AgenticSystemClient
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from llama_toolchain.agentic_system.meta_reference.execute_with_custom_tools import (
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|
@ -32,9 +27,9 @@ from llama_toolchain.safety.api.datatypes import BuiltinShield, ShieldDefinition
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|
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class AgenticSystemClientWrapper:
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def __init__(self, api, system_id, custom_tools):
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def __init__(self, api, agent_id, custom_tools):
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self.api = api
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self.system_id = system_id
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self.agent_id = agent_id
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self.custom_tools = custom_tools
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self.session_id = None
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|
@ -43,10 +38,8 @@ class AgenticSystemClientWrapper:
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name = f"Session-{uuid.uuid4()}"
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response = await self.api.create_agentic_system_session(
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AgenticSystemSessionCreateRequest(
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system_id=self.system_id,
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session_name=name,
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)
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agent_id=self.agent_id,
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session_name=name,
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)
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self.session_id = response.session_id
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return self.session_id
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|
@ -54,7 +47,7 @@ class AgenticSystemClientWrapper:
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async def run(self, messages: List[Message], stream: bool = True):
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async for chunk in execute_with_custom_tools(
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self.api,
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self.system_id,
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self.agent_id,
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self.session_id,
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messages,
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self.custom_tools,
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|
@ -98,29 +91,27 @@ async def get_agent_system_instance(
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ShieldDefinition(shield_type=BuiltinShield.injection_shield),
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]
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create_request = AgenticSystemCreateRequest(
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agent_config = AgentConfig(
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model=model,
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agent_config=AgentConfig(
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instructions="You are a helpful assistant",
|
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available_tools=tool_definitions,
|
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input_shields=(
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[]
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if disable_safety
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else [
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ShieldDefinition(shield_type=BuiltinShield.llama_guard),
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ShieldDefinition(shield_type=BuiltinShield.jailbreak_shield),
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]
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),
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output_shields=(
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[]
|
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if disable_safety
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else [
|
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ShieldDefinition(shield_type=BuiltinShield.llama_guard),
|
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]
|
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),
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sampling_params=SamplingParams(),
|
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tool_prompt_format=tool_prompt_format,
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||||
instructions="You are a helpful assistant",
|
||||
tools=tool_definitions,
|
||||
input_shields=(
|
||||
[]
|
||||
if disable_safety
|
||||
else [
|
||||
ShieldDefinition(shield_type=BuiltinShield.llama_guard),
|
||||
ShieldDefinition(shield_type=BuiltinShield.jailbreak_shield),
|
||||
]
|
||||
),
|
||||
output_shields=(
|
||||
[]
|
||||
if disable_safety
|
||||
else [
|
||||
ShieldDefinition(shield_type=BuiltinShield.llama_guard),
|
||||
]
|
||||
),
|
||||
sampling_params=SamplingParams(),
|
||||
tool_prompt_format=tool_prompt_format,
|
||||
)
|
||||
create_response = await api.create_agentic_system(create_request)
|
||||
return AgenticSystemClientWrapper(api, create_response.system_id, custom_tools)
|
||||
create_response = await api.create_agentic_system(agent_config)
|
||||
return AgenticSystemClientWrapper(api, create_response.agent_id, custom_tools)
|
||||
|
|
|
@ -3,23 +3,3 @@
|
|||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
from typing import Any, Dict
|
||||
|
||||
from llama_models.schema_utils import json_schema_type
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
@json_schema_type
|
||||
class MemoryBank(BaseModel):
|
||||
memory_bank_id: str
|
||||
memory_bank_name: str
|
||||
|
||||
|
||||
@json_schema_type
|
||||
class MemoryBankDocument(BaseModel):
|
||||
document_id: str
|
||||
content: bytes
|
||||
metadata: Dict[str, Any]
|
||||
mime_type: str
|
||||
|
|
|
@ -6,76 +6,132 @@
|
|||
|
||||
from typing import List, Protocol
|
||||
|
||||
from llama_models.llama3.api.datatypes import InterleavedTextMedia
|
||||
from pydantic import BaseModel, Field
|
||||
from typing_extensions import Annotated
|
||||
|
||||
from llama_models.llama3.api.datatypes import * # noqa: F403
|
||||
|
||||
from llama_models.schema_utils import webmethod
|
||||
from .datatypes import * # noqa: F403
|
||||
|
||||
|
||||
@json_schema_type
|
||||
class RetrieveMemoryDocumentsRequest(BaseModel):
|
||||
query: InterleavedTextMedia
|
||||
bank_ids: str
|
||||
class MemoryBankDocument(BaseModel):
|
||||
document_id: str
|
||||
content: InterleavedTextMedia | URL
|
||||
mime_type: str
|
||||
metadata: Dict[str, Any]
|
||||
|
||||
|
||||
class Chunk(BaseModel):
|
||||
content: InterleavedTextMedia
|
||||
token_count: int
|
||||
|
||||
|
||||
@json_schema_type
|
||||
class RetrieveMemoryDocumentsResponse(BaseModel):
|
||||
documents: List[MemoryBankDocument]
|
||||
class QueryDocumentsResponse(BaseModel):
|
||||
chunks: List[Chunk]
|
||||
scores: List[float]
|
||||
|
||||
|
||||
@json_schema_type
|
||||
class MemoryBankType(Enum):
|
||||
vector = "vector"
|
||||
keyvalue = "keyvalue"
|
||||
keyword = "keyword"
|
||||
graph = "graph"
|
||||
|
||||
|
||||
class VectorMemoryBankConfig(BaseModel):
|
||||
type: Literal[MemoryBankType.vector.value] = MemoryBankType.vector.value
|
||||
embedding_model: str
|
||||
|
||||
|
||||
class KeyValueMemoryBankConfig(BaseModel):
|
||||
type: Literal[MemoryBankType.keyvalue.value] = MemoryBankType.keyvalue.value
|
||||
|
||||
|
||||
class KeywordMemoryBankConfig(BaseModel):
|
||||
type: Literal[MemoryBankType.keyword.value] = MemoryBankType.keyword.value
|
||||
|
||||
|
||||
class GraphMemoryBankConfig(BaseModel):
|
||||
type: Literal[MemoryBankType.graph.value] = MemoryBankType.graph.value
|
||||
|
||||
|
||||
MemoryBankConfig = Annotated[
|
||||
Union[
|
||||
VectorMemoryBankConfig,
|
||||
KeyValueMemoryBankConfig,
|
||||
KeywordMemoryBankConfig,
|
||||
GraphMemoryBankConfig,
|
||||
],
|
||||
Field(discriminator="type"),
|
||||
]
|
||||
|
||||
|
||||
@json_schema_type
|
||||
class MemoryBank(BaseModel):
|
||||
bank_id: str
|
||||
name: str
|
||||
config: MemoryBankConfig
|
||||
# if there's a pre-existing store which obeys the MemoryBank REST interface
|
||||
url: Optional[URL] = None
|
||||
|
||||
|
||||
class Memory(Protocol):
|
||||
@webmethod(route="/memory_banks/create")
|
||||
def create_memory_bank(
|
||||
self,
|
||||
bank_id: str,
|
||||
bank_name: str,
|
||||
embedding_model: str,
|
||||
documents: List[MemoryBankDocument],
|
||||
) -> None: ...
|
||||
name: str,
|
||||
config: MemoryBankConfig,
|
||||
url: Optional[URL] = None,
|
||||
) -> MemoryBank: ...
|
||||
|
||||
@webmethod(route="/memory_banks/list")
|
||||
def get_memory_banks(self) -> List[MemoryBank]: ...
|
||||
@webmethod(route="/memory_banks/list", method="GET")
|
||||
def list_memory_banks(self) -> List[MemoryBank]: ...
|
||||
|
||||
@webmethod(route="/memory_banks/get")
|
||||
def get_memory_bank(self, bank_id: str) -> List[MemoryBank]: ...
|
||||
def get_memory_bank(self, bank_id: str) -> MemoryBank: ...
|
||||
|
||||
@webmethod(route="/memory_banks/drop")
|
||||
def delete_memory_bank(
|
||||
@webmethod(route="/memory_banks/drop", method="DELETE")
|
||||
def drop_memory_bank(
|
||||
self,
|
||||
bank_id: str,
|
||||
) -> str: ...
|
||||
|
||||
@webmethod(route="/memory_bank/insert")
|
||||
def insert_memory_documents(
|
||||
def insert_documents(
|
||||
self,
|
||||
bank_id: str,
|
||||
documents: List[MemoryBankDocument],
|
||||
) -> None: ...
|
||||
|
||||
@webmethod(route="/memory_bank/update")
|
||||
def update_memory_documents(
|
||||
def update_documents(
|
||||
self,
|
||||
bank_id: str,
|
||||
documents: List[MemoryBankDocument],
|
||||
) -> None: ...
|
||||
|
||||
@webmethod(route="/memory_bank/get")
|
||||
def retrieve_memory_documents(
|
||||
self,
|
||||
request: RetrieveMemoryDocumentsRequest,
|
||||
) -> List[MemoryBankDocument]: ...
|
||||
|
||||
@webmethod(route="/memory_bank/get")
|
||||
def get_memory_documents(
|
||||
@webmethod(route="/memory_bank/query")
|
||||
def query_documents(
|
||||
self,
|
||||
bank_id: str,
|
||||
document_uuids: List[str],
|
||||
) -> List[MemoryBankDocument]: ...
|
||||
query: InterleavedTextMedia,
|
||||
params: Optional[Dict[str, Any]] = None,
|
||||
) -> QueryDocumentsResponse: ...
|
||||
|
||||
@webmethod(route="/memory_bank/delete")
|
||||
def delete_memory_documents(
|
||||
@webmethod(route="/memory_bank/documents/get")
|
||||
def get_documents(
|
||||
self,
|
||||
bank_id: str,
|
||||
document_uuids: List[str],
|
||||
) -> List[str]: ...
|
||||
document_ids: List[str],
|
||||
) -> List[MemoryBankDocument]: ...
|
||||
|
||||
@webmethod(route="/memory_bank/documents/delete")
|
||||
def delete_documents(
|
||||
self,
|
||||
bank_id: str,
|
||||
document_ids: List[str],
|
||||
) -> None: ...
|
||||
|
|
File diff suppressed because it is too large
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File diff suppressed because it is too large
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Add table
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Reference in a new issue