mirror of
https://github.com/langchain-ai/agent-inbox-langgraph-example.git
synced 2026-07-01 20:44:06 -04:00
William Fu-Hinthorn
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
"""Define the configurable parameters for the agent."""
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from __future__ import annotations
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from dataclasses import dataclass, field, fields
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from typing import Annotated, Optional
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from langchain_core.runnables import RunnableConfig, ensure_config
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from agent import prompts
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@dataclass(kw_only=True)
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class Configuration:
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"""The configuration for the agent."""
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system_prompt: str = field(default=prompts.SYSTEM_PROMPT)
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"""The system prompt to use for the agent's interactions.
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This prompt sets the context and behavior for the agent.
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"""
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model_name: Annotated[str, {"__template_metadata__": {"kind": "llm"}}] = (
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"anthropic/claude-3-5-sonnet-20240620"
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)
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"""The name of the language model to use for the agent's main interactions.
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Should be in the form: provider/model-name.
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"""
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scraper_tool_model_name: Annotated[
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str, {"__template_metadata__": {"kind": "llm"}}
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] = "accounts/fireworks/models/firefunction-v2"
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"""The name of the language model to use for the web scraping tool.
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This model is specifically used for summarizing and extracting information from web pages.
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"""
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max_search_results: int = 10
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"""The maximum number of search results to return for each search query."""
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@classmethod
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def from_runnable_config(
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cls, config: Optional[RunnableConfig] = None
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) -> Configuration:
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"""Create a Configuration instance from a RunnableConfig object."""
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config = ensure_config(config)
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configurable = config.get("configurable") or {}
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_fields = {f.name for f in fields(cls) if f.init}
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return cls(**{k: v for k, v in configurable.items() if k in _fields})
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