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66 lines
2.1 KiB
Python
66 lines
2.1 KiB
Python
"""Implement a GPT-3 driven browser."""
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from typing import Dict, List
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from pydantic import BaseModel, Extra
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from langchain.chains.base import Chain
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from langchain.chains.llm import LLMChain
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from langchain.chains.natbot.prompt import PROMPT
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from langchain.llms.base import LLM
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from langchain.llms.openai import OpenAI
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class NatBotChain(Chain, BaseModel):
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"""Implement a GPT-3 driven browser."""
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llm: LLM
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objective: str
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input_url_key: str = "url"
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input_browser_content_key: str = "browser_content"
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previous_command: str = ""
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output_key: str = "command"
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class Config:
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"""Configuration for this pydantic object."""
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extra = Extra.forbid
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arbitrary_types_allowed = True
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@classmethod
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def from_default(cls, objective: str) -> "NatBotChain":
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"""Load with default LLM."""
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llm = OpenAI(temperature=0.5, best_of=10, n=3, max_tokens=50)
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return cls(llm=llm, objective=objective)
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@property
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def input_keys(self) -> List[str]:
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"""Expect url and browser content."""
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return [self.input_url_key, self.input_browser_content_key]
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@property
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def output_keys(self) -> List[str]:
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"""Return command."""
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return [self.output_key]
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def _run(self, inputs: Dict[str, str]) -> Dict[str, str]:
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llm_executor = LLMChain(prompt=PROMPT, llm=self.llm)
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url = inputs[self.input_url_key]
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browser_content = inputs[self.input_browser_content_key]
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llm_cmd = llm_executor.predict(
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objective=self.objective,
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url=url[:100],
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previous_command=self.previous_command,
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browser_content=browser_content[:4500],
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)
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llm_cmd = llm_cmd.strip()
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self.previous_command = llm_cmd
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return {self.output_key: llm_cmd}
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def run(self, url: str, browser_content: str) -> str:
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"""More user-friendly interface for interfacing with natbot."""
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_inputs = {
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self.input_url_key: url,
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self.input_browser_content_key: browser_content,
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}
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return self(_inputs)[self.output_key]
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