mirror of
https://github.com/hwchase17/langchain
synced 2024-11-18 09:25:54 +00:00
72 lines
2.1 KiB
Python
72 lines
2.1 KiB
Python
import os
|
|
|
|
from git import Repo
|
|
from langchain_community.document_loaders.generic import GenericLoader
|
|
from langchain_community.document_loaders.parsers import LanguageParser
|
|
from langchain_community.embeddings import GPT4AllEmbeddings
|
|
from langchain_community.llms.fireworks import Fireworks
|
|
from langchain_community.vectorstores import Chroma
|
|
from langchain_core.output_parsers import StrOutputParser
|
|
from langchain_core.prompts import ChatPromptTemplate
|
|
from langchain_core.pydantic_v1 import BaseModel
|
|
from langchain_core.runnables import RunnableParallel, RunnablePassthrough
|
|
from langchain_text_splitters import Language, RecursiveCharacterTextSplitter
|
|
|
|
# Check API key
|
|
if os.environ.get("FIREWORKS_API_KEY", None) is None:
|
|
raise Exception("Missing `FIREWORKS_API_KEY` environment variable.")
|
|
|
|
# Load codebase
|
|
# Set local path
|
|
repo_path = "/Users/rlm/Desktop/tmp_repo"
|
|
# Use LangChain as an example
|
|
repo = Repo.clone_from("https://github.com/langchain-ai/langchain", to_path=repo_path)
|
|
loader = GenericLoader.from_filesystem(
|
|
repo_path + "/libs/langchain/langchain",
|
|
glob="**/*",
|
|
suffixes=[".py"],
|
|
parser=LanguageParser(language=Language.PYTHON, parser_threshold=500),
|
|
)
|
|
documents = loader.load()
|
|
|
|
# Split
|
|
python_splitter = RecursiveCharacterTextSplitter.from_language(
|
|
language=Language.PYTHON, chunk_size=2000, chunk_overlap=200
|
|
)
|
|
texts = python_splitter.split_documents(documents)
|
|
|
|
# Add to vectorDB
|
|
vectorstore = Chroma.from_documents(
|
|
documents=texts,
|
|
collection_name="codebase-rag",
|
|
embedding=GPT4AllEmbeddings(),
|
|
)
|
|
retriever = vectorstore.as_retriever()
|
|
|
|
# RAG prompt
|
|
template = """Answer the question based only on the following context:
|
|
{context}
|
|
|
|
Question: {question}
|
|
"""
|
|
prompt = ChatPromptTemplate.from_template(template)
|
|
|
|
# Initialize a Fireworks model
|
|
model = Fireworks(model="accounts/fireworks/models/llama-v2-34b-code-instruct")
|
|
|
|
# RAG chain
|
|
chain = (
|
|
RunnableParallel({"context": retriever, "question": RunnablePassthrough()})
|
|
| prompt
|
|
| model
|
|
| StrOutputParser()
|
|
)
|
|
|
|
|
|
# Add typing for input
|
|
class Question(BaseModel):
|
|
__root__: str
|
|
|
|
|
|
chain = chain.with_types(input_type=Question)
|