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@ -1,10 +1,11 @@
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"""Chain that first uses an LLM to generate multiple items then loops over them."""
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from typing import Any, Dict, List
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from typing import Dict, List, Any
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from pydantic import BaseModel, Extra, root_validator
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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.base import Chain
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from langchain.chains.llm import LLMChain
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from langchain.chains.llm import LLMChain
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from langchain.prompts.base import ListOutputParser
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class LLMForLoopChain(Chain, BaseModel):
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class LLMForLoopChain(Chain, BaseModel):
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@ -38,6 +39,17 @@ class LLMForLoopChain(Chain, BaseModel):
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"""
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"""
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return [self.output_key]
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return [self.output_key]
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@root_validator()
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def validate_output_parser(cls, values: Dict) -> Dict:
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"""Validate that the correct inputs exist for all chains."""
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chain = values["llm_chain"]
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if not isinstance(chain.prompt.output_parser, ListOutputParser):
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raise ValueError(
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f"The OutputParser on the base prompt should be of type "
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f"ListOutputParser, got {type(chain.prompt.output_parser)}"
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)
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return values
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def run_list(self, **kwargs: Any) -> List[str]:
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def run_list(self, **kwargs: Any) -> List[str]:
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"""Get list from LLM chain and then run chain on each item."""
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"""Get list from LLM chain and then run chain on each item."""
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output_items = self.llm_chain.predict_and_parse(**kwargs)
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output_items = self.llm_chain.predict_and_parse(**kwargs)
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"""BasePrompt schema definition."""
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"""BasePrompt schema definition."""
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from abc import ABC, abstractmethod
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from abc import ABC, abstractmethod
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from typing import Any, Dict, List, Union, Optional
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from typing import Any, Dict, List, Optional, Union
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from pydantic import BaseModel, Field, root_validator, Extra
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from pydantic import BaseModel, Extra, root_validator
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from langchain.formatting import formatter
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from langchain.formatting import formatter
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@ -37,6 +37,13 @@ class BaseOutputParser(ABC):
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"""Parse the output of an LLM call."""
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"""Parse the output of an LLM call."""
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class ListOutputParser(ABC):
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"""Class to parse the output of an LLM call to a list."""
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@abstractmethod
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def parse(self, text: str) -> List[str]:
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"""Parse the output of an LLM call."""
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class BasePromptTemplate(BaseModel, ABC):
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class BasePromptTemplate(BaseModel, ABC):
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"""Base prompt should expose the format method, returning a prompt."""
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"""Base prompt should expose the format method, returning a prompt."""
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