cr

langchain/chains/hyde/base.py

@@ -7,7 +7,7 @@ from __future__ import annotations
 from typing import Any, Dict, List, Optional
 
 import numpy as np
-from pydantic import Extra
+from pydantic import Extra, Field
 
 from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.manager import CallbackManagerForChainRun
@@ -23,7 +23,7 @@ class HypotheticalDocumentEmbedder(Chain, Embeddings):
     Based on https://arxiv.org/abs/2212.10496
     """
 
-    base_embeddings: Embeddings
+    base_embeddings: Embeddings = Field(exclude=True)
     llm_chain: LLMChain
 
     class Config:

langchain/chains/llm_bash/base.py

@@ -30,13 +30,12 @@ class LLMBashChain(Chain):
     """
 
     llm_chain: LLMChain
-    llm: Optional[BaseLanguageModel] = None
-    """[Deprecated] LLM wrapper to use."""
     input_key: str = "question"  #: :meta private:
     output_key: str = "answer"  #: :meta private:
-    prompt: BasePromptTemplate = PROMPT
     """[Deprecated]"""
-    bash_process: BashProcess = Field(default_factory=BashProcess)  #: :meta private:
+    bash_process: BashProcess = Field(
+        default_factory=BashProcess, exclude=True
+    )  #: :meta private:
 
     class Config:
         """Configuration for this pydantic object."""
@@ -51,9 +50,13 @@ class LLMBashChain(Chain):
                 "Directly instantiating an LLMBashChain with an llm is deprecated. "
                 "Please instantiate with llm_chain or using the from_llm class method."
             )
-            if "llm_chain" not in values and values["llm"] is not None:
-                prompt = values.get("prompt", PROMPT)
-                values["llm_chain"] = LLMChain(llm=values["llm"], prompt=prompt)
+            llm = values.pop("llm")
+            if "llm_chain" not in values and llm is not None:
+                if "prompt" in values:
+                    prompt = values.pop("prompt")
+                else:
+                    prompt = PROMPT
+                values["llm_chain"] = LLMChain(llm=llm, prompt=prompt)
         return values
 
     @root_validator

langchain/chains/llm_bash/prompt.py

@@ -1,11 +1,8 @@
 # flake8: noqa
 from __future__ import annotations
 
-import re
-from typing import List
-
+from langchain.output_parsers.bash import BashOutputParser
 from langchain.prompts.prompt import PromptTemplate
-from langchain.schema import BaseOutputParser, OutputParserException
 
 _PROMPT_TEMPLATE = """If someone asks you to perform a task, your job is to come up with a series of bash commands that will perform the task. There is no need to put "#!/bin/bash" in your answer. Make sure to reason step by step, using this format:
 
@@ -25,38 +22,6 @@ That is the format. Begin!
 
 Question: {question}"""
 
-
-class BashOutputParser(BaseOutputParser):
-    """Parser for bash output."""
-
-    def parse(self, text: str) -> List[str]:
-        if "```bash" in text:
-            return self.get_code_blocks(text)
-        else:
-            raise OutputParserException(
-                f"Failed to parse bash output. Got: {text}",
-            )
-
-    @staticmethod
-    def get_code_blocks(t: str) -> List[str]:
-        """Get multiple code blocks from the LLM result."""
-        code_blocks: List[str] = []
-        # Bash markdown code blocks
-        pattern = re.compile(r"```bash(.*?)(?:\n\s*)```", re.DOTALL)
-        for match in pattern.finditer(t):
-            matched = match.group(1).strip()
-            if matched:
-                code_blocks.extend(
-                    [line for line in matched.split("\n") if line.strip()]
-                )
-
-        return code_blocks
-
-    @property
-    def _type(self) -> str:
-        return "bash"
-
-
 PROMPT = PromptTemplate(
     input_variables=["question"],
     template=_PROMPT_TEMPLATE,

langchain/chains/loading.py

@@ -138,19 +138,14 @@ def _load_map_reduce_documents_chain(
 
 
 def _load_llm_bash_chain(config: dict, **kwargs: Any) -> LLMBashChain:
-    if "llm" in config:
-        llm_config = config.pop("llm")
-        llm = load_llm_from_config(llm_config)
-    elif "llm_path" in config:
-        llm = load_llm(config.pop("llm_path"))
+    if "llm_chain" in config:
+        llm_chain_config = config.pop("llm_chain")
+        llm_chain = load_chain_from_config(llm_chain_config)
+    elif "llm_chain_path" in config:
+        llm_chain = load_chain(config.pop("llm_chain_path"))
     else:
-        raise ValueError("One of `llm` or `llm_path` must be present.")
-    if "prompt" in config:
-        prompt_config = config.pop("prompt")
-        prompt = load_prompt_from_config(prompt_config)
-    elif "prompt_path" in config:
-        prompt = load_prompt(config.pop("prompt_path"))
-    return LLMBashChain(llm=llm, prompt=prompt, **config)
+        raise ValueError("One of `llm_chain` or `llm_chain_config` must be present.")
+    return LLMBashChain(llm_chain=llm_chain, **config)
 
 
 def _load_llm_checker_chain(config: dict, **kwargs: Any) -> LLMCheckerChain:

langchain/output_parsers/bash.py

@@ -0,0 +1,37 @@
+from __future__ import annotations
+
+import re
+from typing import List
+
+from langchain.schema import BaseOutputParser, OutputParserException
+
+
+class BashOutputParser(BaseOutputParser):
+    """Parser for bash output."""
+
+    def parse(self, text: str) -> List[str]:
+        if "```bash" in text:
+            return self.get_code_blocks(text)
+        else:
+            raise OutputParserException(
+                f"Failed to parse bash output. Got: {text}",
+            )
+
+    @staticmethod
+    def get_code_blocks(t: str) -> List[str]:
+        """Get multiple code blocks from the LLM result."""
+        code_blocks: List[str] = []
+        # Bash markdown code blocks
+        pattern = re.compile(r"```bash(.*?)(?:\n\s*)```", re.DOTALL)
+        for match in pattern.finditer(t):
+            matched = match.group(1).strip()
+            if matched:
+                code_blocks.extend(
+                    [line for line in matched.split("\n") if line.strip()]
+                )
+
+        return code_blocks
+
+    @property
+    def _type(self) -> str:
+        return "bash"

langchain/prompts/loading.py

@@ -7,10 +7,12 @@ from typing import Union
 
 import yaml
 
+from langchain.output_parsers.bash import BashOutputParser
 from langchain.output_parsers.regex import RegexParser
 from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.few_shot import FewShotPromptTemplate
 from langchain.prompts.prompt import PromptTemplate
+from langchain.schema import BaseOutputParser
 from langchain.utilities.loading import try_load_from_hub
 
 URL_BASE = "https://raw.githubusercontent.com/hwchase17/langchain-hub/master/prompts/"
@@ -78,7 +80,9 @@ def _load_output_parser(config: dict) -> dict:
         _config = config.pop("output_parser")
         output_parser_type = _config.pop("_type")
         if output_parser_type == "regex_parser":
-            output_parser = RegexParser(**_config)
+            output_parser: BaseOutputParser = RegexParser(**_config)
+        elif output_parser_type == "bash":
+            output_parser = BashOutputParser(**config)
         else:
             raise ValueError(f"Unsupported output parser {output_parser_type}")
         config["output_parser"] = output_parser

tests/unit_tests/chains/test_llm_bash.py

@@ -4,7 +4,8 @@ import sys
 import pytest
 
 from langchain.chains.llm_bash.base import LLMBashChain
-from langchain.chains.llm_bash.prompt import _PROMPT_TEMPLATE, BashOutputParser
+from langchain.chains.llm_bash.prompt import _PROMPT_TEMPLATE
+from langchain.output_parsers.bash import BashOutputParser
 from langchain.schema import OutputParserException
 from tests.unit_tests.llms.fake_llm import FakeLLM