Outputs rag pipeline as a yaml config file

data/.gitignore

@@ -15,3 +15,4 @@
 /eval.png
 /eidc_rag_testset.csv
 /eidc_rag_test_set.csv
+/rag-pipeline.yml

dvc.yaml

@@ -22,7 +22,14 @@ stages:
     outs:
     - ${files.extracted}
   chunk-data:
-    cmd: python scripts/chunk_data.py -o ${files.chunked} -c ${hp.chunk-size} -ol ${hp.overlap} ${files.extracted} ${files.supporting-docs} -m ${max-length}
+    cmd: >-
+      python scripts/chunk_data.py 
+      -o ${files.chunked} 
+      -c ${hp.chunk-size} 
+      -ol ${hp.overlap} 
+      ${files.extracted} 
+      ${files.supporting-docs} 
+      -m ${max-length}
     deps:
     - ${files.extracted}
     - ${files.supporting-docs}
@@ -37,7 +44,12 @@ stages:
     outs:
     - ${files.embeddings}
   upload-to-docstore:
-    cmd: python scripts/upload_to_docstore.py ${files.embeddings} -o ${doc-store.files} -em ${hp.embeddings-model} -c ${doc-store.collection}
+    cmd: >-
+      python scripts/upload_to_docstore.py 
+      ${files.embeddings} 
+      -o ${doc-store.files} 
+      -em ${hp.embeddings-model} 
+      -c ${doc-store.collection}
     deps:
     - ${files.embeddings}
     - scripts/upload_to_docstore.py
@@ -48,13 +60,21 @@ stages:
     outs: 
     - ${files.test-set}
   run-rag-pipeline:
-    cmd: python scripts/run_rag_pipeline.py -i ${files.test-set} -o ${files.eval-set} -ds ${files.doc-store} -c ${doc-store.collection} -m ${rag.model}
+    cmd: >-
+      python scripts/run_rag_pipeline.py 
+      -i ${files.test-set} 
+      -o ${files.eval-set} 
+      -ds ${files.doc-store} 
+      -c ${doc-store.collection} 
+      -m ${rag.model} 
+      -p ${files.pipeline}
     deps:
     - ${files.test-set}
     - ${files.doc-store}
     - scripts/run_rag_pipeline.py
     outs: 
     - ${files.eval-set}
+    - ${files.pipeline}
   evaluate:
     cmd: python scripts/evaluate.py ${files.eval-set} -m ${files.metrics} -img ${files.eval-plot}
     deps:

scripts/run_rag_pipeline.py

@@ -1,9 +1,7 @@
 import shutil
 from argparse import ArgumentParser
 from typing import Any, Dict, List, Tuple
-__import__("pysqlite3")
-import sys
-sys.modules["sqlite3"] = sys.modules.pop("pysqlite3")
+
 import pandas as pd
 from haystack import Pipeline
 from haystack.components.builders import PromptBuilder
@@ -90,11 +88,15 @@ def main(
     doc_store_path: str,
     collection_name: str,
     model: str,
+    pipeline_file: str,
 ) -> None:
     shutil.copytree(doc_store_path, TMP_DOC_PATH)
 
     rag_pipe = build_rag_pipeline(model, collection_name)
 
+    with open(pipeline_file, "w") as f:
+        rag_pipe.dump(f)
+
     df = pd.read_csv(test_data_file)
     df.drop(columns=["rating", "contexts"], inplace=True)
 
@@ -136,5 +138,18 @@ def main(
         help="Model to use in RAG pipeline.",
         default="llama3.1",
     )
+    parser.add_argument(
+        "-p",
+        "--pipeline_file",
+        help="File to save the built RAG pipeline to.",
+        default="pipeline.yml",
+    )
     args = parser.parse_args()
-    main(args.input, args.output, args.doc_store, args.collection, args.model)
+    main(
+        args.input,
+        args.output,
+        args.doc_store,
+        args.collection,
+        args.model,
+        args.pipeline_file,
+    )

scripts/upload_to_docstore.py

@@ -4,10 +4,6 @@
 import uuid
 from argparse import ArgumentParser
 
-__import__("pysqlite3")
-import sys
-
-sys.modules["sqlite3"] = sys.modules.pop("pysqlite3")
 import chromadb
 from chromadb.utils import embedding_functions
 from chromadb.utils.batch_utils import create_batches