github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2025-08-18 09:01:03 +00:00
Code Issues Packages Projects Releases Wiki Activity

experimental[patch], docs: refine notebook for MyScale SelfQueryRetriever (#22016)

Browse Source 
- **Description:** upgrade model to `gpt-4o`
This commit is contained in:
mochi 2024-05-23 05:49:01 +08:00 committed by GitHub
parent d948783a4c
commit 63284ffebf
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 6 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb
View File

@ -162,12 +162,14 @@
"source": [ "source": [
"from langchain.chains.query_constructor.base import AttributeInfo\n", "from langchain.chains.query_constructor.base import AttributeInfo\n",
"from langchain.retrievers.self_query.base import SelfQueryRetriever\n", "from langchain.retrievers.self_query.base import SelfQueryRetriever\n",
"from langchain_openai import OpenAI\n", "from langchain_openai import ChatOpenAI\n",
"\n", "\n",
"metadata_field_info = [\n", "metadata_field_info = [\n",
" AttributeInfo(\n", " AttributeInfo(\n",
" name=\"genre\",\n", " name=\"genre\",\n",
" description=\"The genres of the movie\",\n", " description=\"The genres of the movie. \"\n",
" \"It only supports equal and contain comparisons. \"\n",
" \"Here are some examples: genre = [' A '], genre = [' A ', 'B'], contain (genre, 'A')\",\n",
" type=\"list[string]\",\n", " type=\"list[string]\",\n",
" ),\n", " ),\n",
" # If you want to include length of a list, just define it as a new column\n", " # If you want to include length of a list, just define it as a new column\n",
@ -193,7 +195,7 @@
" ),\n", " ),\n",
"]\n", "]\n",
"document_content_description = \"Brief summary of a movie\"\n", "document_content_description = \"Brief summary of a movie\"\n",
"llm = OpenAI(temperature=0)\n", "llm = ChatOpenAI(temperature=0, model_name=\"gpt-4o\")\n",
"retriever = SelfQueryRetriever.from_llm(\n", "retriever = SelfQueryRetriever.from_llm(\n",
" llm, vectorstore, document_content_description, metadata_field_info, verbose=True\n", " llm, vectorstore, document_content_description, metadata_field_info, verbose=True\n",
")" ")"

2
libs/experimental/langchain_experimental/sql/vector_sql.py
View File

@ -40,7 +40,7 @@ class VectorSQLOutputParser(BaseOutputParser[str]):
@classmethod @classmethod
def from_embeddings( def from_embeddings(
cls, model: Embeddings, distance_func_name: str = "distance", **kwargs: Any cls, model: Embeddings, distance_func_name: str = "distance", **kwargs: Any
) -> BaseOutputParser: ) -> VectorSQLOutputParser:
return cls(model=model, distance_func_name=distance_func_name, **kwargs) return cls(model=model, distance_func_name=distance_func_name, **kwargs)
def parse(self, text: str) -> str: def parse(self, text: str) -> str: