Templates (#12294)

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>

templates/self-query-supabase/self_query_supabase/chain.py

@@ -0,0 +1,64 @@
+import os
+from langchain.llms.openai import OpenAI
+from langchain.retrievers.self_query.base import SelfQueryRetriever
+from langchain.chat_models import ChatOpenAI
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.schema.output_parser import StrOutputParser
+from langchain.schema.runnable import RunnablePassthrough, RunnableParallel
+from langchain.chains.query_constructor.base import AttributeInfo
+
+from supabase.client import create_client
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores.supabase import SupabaseVectorStore
+
+supabase_url = os.environ.get("SUPABASE_URL")
+supabase_key = os.environ.get("SUPABASE_SERVICE_KEY")
+supabase = create_client(supabase_url, supabase_key)
+
+embeddings = OpenAIEmbeddings()
+
+vectorstore = SupabaseVectorStore(
+    client=supabase,
+    embedding=embeddings,
+    table_name="documents",
+    query_name="match_documents"
+)
+
+# Adjust this based on the metadata you store in the `metadata` JSON column
+metadata_field_info = [
+    AttributeInfo(
+        name="genre",
+        description="The genre of the movie",
+        type="string or list[string]",
+    ),
+    AttributeInfo(
+        name="year",
+        description="The year the movie was released",
+        type="integer",
+    ),
+    AttributeInfo(
+        name="director",
+        description="The name of the movie director",
+        type="string",
+    ),
+    AttributeInfo(
+        name="rating", description="A 1-10 rating for the movie", type="float"
+    ),
+]
+
+# Adjust this based on the type of documents you store
+document_content_description = "Brief summary of a movie"
+llm = OpenAI(temperature=0)
+
+retriever = SelfQueryRetriever.from_llm(
+    llm,
+    vectorstore,
+    document_content_description,
+    metadata_field_info,
+    verbose=True
+)
+
+chain = (
+    RunnableParallel({"query": RunnablePassthrough()})
+    | retriever
+)