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Fix LangChainDeprecationWarning: The class LLMChain was deprecated #4828

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Fix LangChainDeprecationWarning: The class LLMChain was deprecated #4828

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109 changes: 58 additions & 51 deletions bugbug/tools/code_review.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@
from typing import Iterable, Literal, Optional

import tenacity
from langchain.chains import ConversationChain, LLMChain
from langchain.chains import ConversationChain, RunnableSequence
from langchain.memory import ConversationBufferMemory
from langchain.prompts import PromptTemplate
from langchain_openai import OpenAIEmbeddings
Expand Down Expand Up @@ -1043,44 +1043,54 @@ def __init__(
else ""
)

self.summarization_chain = LLMChain(
prompt=PromptTemplate.from_template(
PROMPT_TEMPLATE_SUMMARIZATION,
partial_variables={
"experience_scope": (
f"the {self.target_software} source code"
if self.target_software
else "a software project"
)
},
),
llm=self.llm,
verbose=verbose,
summarization_chain_prompt = PromptTemplate.from_template(
PROMPT_TEMPLATE_SUMMARIZATION,
partial_variables={
"experience_scope": (
f"the {self.target_software} source code"
if self.target_software
else "a software project"
)
},
)
self.filtering_chain = LLMChain(
prompt=PromptTemplate.from_template(
PROMPT_TEMPLATE_FILTERING_ANALYSIS,
partial_variables={
"target_code_consistency": self.target_software or "rest of the"
},
),
llm=self.llm,
verbose=verbose,

self.summarization_chain = RunnableSequence(
[summarization_chain_prompt, self.llm], verbose=verbose
)

filtering_chain_prompt = PromptTemplate.from_template(
PROMPT_TEMPLATE_FILTERING_ANALYSIS,
partial_variables={
"target_code_consistency": self.target_software or "rest of the"
},
)

self.filtering_chain = RunnableSequence(
[filtering_chain_prompt, self.llm], verbose=verbose
)

deduplicating_chain_prompt = PromptTemplate.from_template(
PROMPT_TEMPLATE_DEDUPLICATE
)

self.deduplicating_chain = RunnableSequence(
[deduplicating_chain_prompt, self.llm], verbose=verbose
)
self.deduplicating_chain = LLMChain(
prompt=PromptTemplate.from_template(PROMPT_TEMPLATE_DEDUPLICATE),
llm=self.llm,
verbose=verbose,

further_context_prompt = PromptTemplate.from_template(
PROMPT_TEMPLATE_FURTHER_CONTEXT_LINES
)
self.further_context_chain = LLMChain(
prompt=PromptTemplate.from_template(PROMPT_TEMPLATE_FURTHER_CONTEXT_LINES),
llm=self.llm,
verbose=verbose,

self.further_context_chain = RunnableSequence(
[further_context_prompt, self.llm], verbose=verbose
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can verbose used here?

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I don't think so; you could check the documentation and test it.

)

further_info_chain_prompt = PromptTemplate.from_template(
PROMPT_TEMPLATE_FURTHER_INFO
)
self.further_info_chain = LLMChain(
prompt=PromptTemplate.from_template(PROMPT_TEMPLATE_FURTHER_INFO),
llm=self.llm,
verbose=verbose,

self.further_info_chain = RunnableSequence(
[further_info_chain_prompt, self.llm], verbose=verbose
)

self.function_search = function_search
Expand All @@ -1107,17 +1117,17 @@ def run(self, patch: Patch) -> list[InlineComment] | None:
return None

output_summarization = self.summarization_chain.invoke(
{"patch": formatted_patch},
return_only_outputs=True,
)["text"]
{"patch": formatted_patch}
)

if self.verbose:
GenerativeModelTool._print_answer(output_summarization)

if self.function_search is not None:
line_code_list = self.further_context_chain.run(
patch=formatted_patch, summarization=output_summarization
).split("\n")
output_further_context = self.further_context_chain.invoke(
{"patch": formatted_patch, "summarization": output_summarization}
)
line_code_list = output_further_context.split("\n")

if self.verbose:
GenerativeModelTool._print_answer(line_code_list)
Expand All @@ -1129,11 +1139,12 @@ def run(self, patch: Patch) -> list[InlineComment] | None:
formatted_patch,
)

output_further_info = self.further_info_chain.invoke(
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@theoniko theoniko Feb 23, 2025 •
edited
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Is it returning a string, JSON or something else?

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One way to determine this is by running it.

{"patch": formatted_patch, "summarization": output_summarization}
)
function_list = [
function_name.strip()
for function_name in self.further_info_chain.run(
patch=formatted_patch, summarization=output_summarization
).split("\n")
for function_name in output_further_info.split("\n")
]

if self.verbose:
Expand Down Expand Up @@ -1221,10 +1232,7 @@ def run(self, patch: Patch) -> list[InlineComment] | None:
memory.clear()

if len(self.comment_gen_llms) > 1:
output = self.deduplicating_chain.invoke(
{"review": output},
return_only_outputs=True,
)["text"]
output = self.deduplicating_chain.invoke({"review": output})

if self.verbose:
GenerativeModelTool._print_answer(output)
Expand All @@ -1245,9 +1253,8 @@ def run(self, patch: Patch) -> list[InlineComment] | None:
"review": output,
"patch": patch.raw_diff,
"rejected_examples": rejected_examples,
},
return_only_outputs=True,
)["text"]
}
)

if self.verbose:
GenerativeModelTool._print_answer(raw_output)
Expand Down