From 2ded37b4c4aca84ff7a793ba93d81ddb8b68e235 Mon Sep 17 00:00:00 2001 From: Ankush Kumar Date: Wed, 5 Aug 2026 11:03:38 +0530 Subject: [PATCH 1/7] fix: prevent useEffect cleanup crash in Chat component --- src/frontend/src/pages/chat/Chat.tsx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/frontend/src/pages/chat/Chat.tsx b/src/frontend/src/pages/chat/Chat.tsx index 9750967..9a6cd32 100644 --- a/src/frontend/src/pages/chat/Chat.tsx +++ b/src/frontend/src/pages/chat/Chat.tsx @@ -146,8 +146,8 @@ const Chat = () => { setIsStreaming(false); }; - useEffect(() => chatMessageStreamEnd.current?.scrollIntoView({ behavior: "smooth" }), [isLoading]); - useEffect(() => chatMessageStreamEnd.current?.scrollIntoView({ behavior: "auto" }), [streamedAnswers]); + useEffect(() => { chatMessageStreamEnd.current?.scrollIntoView({ behavior: "smooth" }); }, [isLoading]); + useEffect(() => { chatMessageStreamEnd.current?.scrollIntoView({ behavior: "auto" }); }, [streamedAnswers]); const onPromptTemplateChange = (_ev?: React.FormEvent, newValue?: string) => { setPromptTemplate(newValue || ""); From c4d4e9595e5b8b14a2bc30929e7923ada99ab821 Mon Sep 17 00:00:00 2001 From: Ankush Kumar Date: Sat, 8 Aug 2026 22:46:57 +0530 Subject: [PATCH 2/7] added cars seed data --- src/backend/fastapi_app/cars_seed_data.json | 11687 ++++++++++++++++++ 1 file changed, 11687 insertions(+) create mode 100644 src/backend/fastapi_app/cars_seed_data.json diff --git a/src/backend/fastapi_app/cars_seed_data.json b/src/backend/fastapi_app/cars_seed_data.json new file mode 100644 index 0000000..5af98db --- /dev/null +++ b/src/backend/fastapi_app/cars_seed_data.json @@ -0,0 +1,11687 @@ +[ + { + "id": 1, + "type": "Sedan", + "brand": "Hyundai", + "name": "Verna", + "description": "A 5-seater capacity, modern safety specifications, and multiple fuel or powertrain choice. 1482 cc to 1497 cc petrol options, including high-performance turbo variants. 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Comes with a 1956 cc diesel engine and optional all-wheel drive. Features a panoramic sunroof, ADAS safety suite, and spacious three-row seating. Mileage: Approx. 16.3 to 19.6 kmpl.", + "price": 2500000, + "embedding_3l": null, + "embedding_nomic": [ + -0.09081098437309265, + 0.06582000851631165, + -0.19087696075439453, + -0.0020289469975978136, + 0.04395698383450508, + 0.00046623722300864756, + 0.02174616977572441, + 0.01560896635055542, + -0.04817064478993416, + 0.006540096364915371, + 0.016747072339057922, + -0.014222203753888607, + 0.08848664909601212, + -0.009284062311053276, + 0.04662349447607994, + -0.034997351467609406, + 0.0013709432678297162, + -0.06453252583742142, + 0.061063848435878754, + 0.05400531366467476, + -0.013965153135359287, + 0.018197868019342422, + -0.06130833551287651, + 0.024608934298157692, + 0.07332582026720047, + 0.04841536656022072, + 0.014755560085177422, + 0.01405730377882719, + 0.03123994544148445, + -0.030417228117585182, + 0.09449551999568939, + -0.03478500247001648, + -0.0062849088571965694, + -0.00026068478473462164, + -0.030775928869843483, + -0.030801836401224136, + 0.08762966096401215, + 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Powered by a 2755 cc diesel engine with 4WD option. Known for its legendary reliability and strong resale value. 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Available with manual and AMT gearboxes. Compact dimensions make it ideal for city driving. Mileage: Approx. 24.8 kmpl.", + "price": 700000, + "embedding_3l": null, + "embedding_nomic": [ + -0.019226547330617905, + 0.028297092765569687, + -0.20085617899894714, + 0.04776565358042717, + 0.013339327648282051, + -0.009239314123988152, + -0.025336410850286484, + -0.00846981443464756, + -0.07943325489759445, + -0.02305709384381771, + 0.026833562180399895, + 0.00700792670249939, + 0.11400501430034637, + 0.0056678010150790215, + 0.02215738408267498, + -0.03371986746788025, + 0.0055305142886936665, + -0.06297531723976135, + 0.011248024180531502, + 0.025233978405594826, + 0.004782167728990316, + 0.033665768802165985, + -0.04719029739499092, + 0.031102720648050308, + 0.10709875822067261, + 0.026123542338609695, + 0.03672288730740547, + -0.02753176912665367, + 0.04231474921107292, + -0.04975153133273125, + 0.08164690434932709, + -0.09085874259471893, + -0.028135910630226135, + -0.03351069241762161, + -0.05308041721582413, + -0.04023751989006996, + 0.0506940521299839, + 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EV", + "description": "A 5-seater electric SUV with a 50.3 kWh battery delivering up to 461 km of range. Equipped with a panoramic sunroof, AI-powered voice assistant, and Level 2 ADAS features. Supports fast DC charging up to 76 kW. Zero tailpipe emissions.", + "price": 2300000, + "embedding_3l": null, + "embedding_nomic": [ + -0.056775808334350586, + 0.05164279043674469, + -0.17852628231048584, + 0.024781985208392143, + 0.058984965085983276, + -0.011267872527241707, + -0.0015754273626953363, + 0.005876987241208553, + -0.02891361340880394, + 0.01836525648832321, + 0.02628157287836075, + 0.039856936782598495, + 0.07365698367357254, + 0.0063894097693264484, + 0.025872306898236275, + -0.016256852075457573, + 0.01519149448722601, + -0.04861246421933174, + 0.045587580651044846, + 0.03178310766816139, + 0.01300183217972517, + -0.052838921546936035, + -0.07167785614728928, + 0.026596728712320328, + 0.08395475894212723, + 0.0717071071267128, + 0.016468066722154617, + -0.01936420612037182, + 0.034594640135765076, + -0.03266661614179611, + 0.07348678261041641, + -0.02461402118206024, + -0.011165983974933624, + 0.012746495194733143, + -0.07962383329868317, + -0.023969655856490135, + 0.07950879633426666, + 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"Sedan", + "brand": "BMW", + "name": "3 Series", + "description": "A luxury 5-seater sports sedan with rear-wheel drive dynamics and a refined 1998 cc turbocharged petrol engine producing 258 bhp. Features a 12.3-inch digital cockpit, Harman Kardon audio, and premium leather interior. Mileage: Approx. 14.5 kmpl.", + "price": 6500000, + "embedding_3l": null, + "embedding_nomic": [ + -0.019672365859150887, + 0.017818696796894073, + -0.1859070062637329, + 0.004150551278144121, + 0.020142117515206337, + -0.00202008755877614, + -0.01593928411602974, + -0.0030139724258333445, + -0.06836965680122375, + 0.022267799824476242, + -0.010338928550481796, + 0.004476865287870169, + 0.04401041939854622, + -0.006517490372061729, + 0.03243422135710716, + -0.04206288233399391, + -0.07436468452215195, + -0.04125106334686279, + 0.027904087677598, + 0.032190244644880295, + -0.0043521057814359665, + 0.006078456528484821, + -0.1359352022409439, + 0.023615941405296326, + 0.09303977340459824, + 0.04556465148925781, + -0.008782797493040562, + -0.03576071187853813, + -0.0031100588385015726, + -0.049861982464790344, + 0.05249423533678055, + -0.01680947095155716, + -0.03580782189965248, + -0.011952107772231102, + -0.028439166024327278, + -0.06355836987495422, + 0.04033093899488449, + 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Features a panoramic roof, ambient lighting, semi-autonomous driving, and a premium Bowers & Wilkins audio system. 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Available in petrol, diesel, and CNG variants with a 1199 cc or 1497 cc engine. Known for its safe monocoque body, plush ride quality, and well-equipped cabin. Mileage: Approx. 19.0 to 25.1 kmpl.", + "price": 850000, + "embedding_3l": null, + "embedding_nomic": [ + -0.043711356818675995, + 0.0390874408185482, + -0.19800347089767456, + 0.014784617349505424, + 0.06268715113401413, + 0.005817560013383627, + -0.00530253117904067, + 0.006046261638402939, + -0.07665283977985382, + -0.01739906519651413, + -0.007682833354920149, + 0.0032435753382742405, + 0.086983822286129, + -0.0018773620249703526, + 0.040199264883995056, + -0.05232485383749008, + -0.030073238536715508, + -0.04314367473125458, + 0.026379572227597237, + 0.03713247552514076, + 0.004771685693413019, + -0.0018829000182449818, + -0.04334382340312004, + 0.014611950144171715, + 0.09464279562234879, + 0.05723908916115761, + -0.013694226741790771, + 0.0037276060320436954, + 0.036542247980833054, + -0.043093521147966385, + 0.09759115427732468, + -0.06401988863945007, + -0.035055045038461685, + -0.014797642827033997, + -0.024849114939570427, + -0.04651400074362755, + 0.04215526580810547, + 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-0.02067096345126629, + 0.003725043497979641, + -0.03525981307029724, + -0.042714498937129974, + -0.08687745034694672, + 0.004977815318852663, + -0.04935681074857712, + -0.0014005749253556132, + 0.053483568131923676, + -0.009722497314214706, + -0.0043065184727311134, + -0.013920657336711884, + -0.019479874521493912, + 0.05963081121444702, + 0.09249204397201538, + -0.037518296390771866, + 0.013203511014580727, + -0.014273406006395817, + -0.02625814639031887, + 0.005172971170395613, + -0.02590871788561344, + 0.06623862683773041, + 0.024113433435559273, + 0.03585394099354744, + 0.062405072152614594, + 0.00725904293358326, + 0.02363041788339615, + -0.02684120088815689, + 0.02658076211810112, + -0.012075589038431644, + -0.01455984078347683, + -0.01308593712747097, + -0.03797909989953041, + -0.02210909128189087 + ] + } +] \ No newline at end of file From 67d5c38a32e2a1e65577a5513106e21e2611e42e Mon Sep 17 00:00:00 2001 From: Ankush Kumar Date: Sat, 8 Aug 2026 22:47:23 +0530 Subject: [PATCH 3/7] added car model --- src/backend/fastapi_app/postgres_models.py | 29 ++++++++++++++++++++++ 1 file changed, 29 insertions(+) diff --git a/src/backend/fastapi_app/postgres_models.py b/src/backend/fastapi_app/postgres_models.py index c2a7e3a..1844727 100644 --- a/src/backend/fastapi_app/postgres_models.py +++ b/src/backend/fastapi_app/postgres_models.py @@ -39,6 +39,35 @@ def to_str_for_embedding(self): return f"Name: {self.name} Description: {self.description} Type: {self.type}" +class Car(Base): + __tablename__ = "cars" + id: Mapped[int] = mapped_column(primary_key=True, autoincrement=True) + type: Mapped[str] = mapped_column() + brand: Mapped[str] = mapped_column() + name: Mapped[str] = mapped_column() + description: Mapped[str] = mapped_column() + price: Mapped[float] = mapped_column() + # Embeddings for different models: + embedding_3l: Mapped[Vector] = mapped_column(Vector(1024), nullable=True) # text-embedding-3-large + embedding_nomic: Mapped[Vector] = mapped_column(Vector(768), nullable=True) # nomic-embed-text + + def to_dict(self, include_embedding: bool = False): + model_dict = {column.name: getattr(self, column.name) for column in self.__table__.columns} + if include_embedding: + model_dict["embedding_3l"] = model_dict.get("embedding_3l", []) + model_dict["embedding_nomic"] = model_dict.get("embedding_nomic", []) + else: + del model_dict["embedding_3l"] + del model_dict["embedding_nomic"] + return model_dict + + def to_str_for_rag(self): + return f"Name:{self.name} Description:{self.description} Price:{self.price} Brand:{self.brand} Type:{self.type}" + + def to_str_for_embedding(self): + return f"Name: {self.name} Brand: {self.brand} Description: {self.description} Type: {self.type}" + + """ **Define HNSW index to support vector similarity search** From bec52d8306ac72bc60673561c4bc21b7d84839f1 Mon Sep 17 00:00:00 2001 From: Ankush Kumar Date: Sat, 8 Aug 2026 22:47:45 +0530 Subject: [PATCH 4/7] added script to generate embeddings --- .../fastapi_app/update_cars_embeddings.py | 65 +++++++++++++++++++ 1 file changed, 65 insertions(+) create mode 100644 src/backend/fastapi_app/update_cars_embeddings.py diff --git a/src/backend/fastapi_app/update_cars_embeddings.py b/src/backend/fastapi_app/update_cars_embeddings.py new file mode 100644 index 0000000..2f5702d --- /dev/null +++ b/src/backend/fastapi_app/update_cars_embeddings.py @@ -0,0 +1,65 @@ +import asyncio +import json +import logging +import os + +from dotenv import load_dotenv + +from fastapi_app.dependencies import common_parameters, get_azure_credential +from fastapi_app.embeddings import compute_text_embedding +from fastapi_app.openai_clients import create_openai_embed_client +from fastapi_app.postgres_models import Car + +logger = logging.getLogger("ragapp") + + +async def update_cars_embeddings(): + azure_credential = await get_azure_credential() + openai_embed_client = await create_openai_embed_client(azure_credential) + common_params = await common_parameters() + + OPENAI_EMBED_HOST = os.getenv("OPENAI_EMBED_HOST") + if OPENAI_EMBED_HOST == "azure": + embedding_column = os.getenv("AZURE_OPENAI_EMBEDDING_COLUMN", "embedding_3l") + elif OPENAI_EMBED_HOST == "ollama": + embedding_column = os.getenv("OLLAMA_EMBEDDING_COLUMN", "embedding_nomic") + else: + embedding_column = os.getenv("OPENAICOM_EMBEDDING_COLUMN", "embedding_3l") + + logger.info(f"Updating car embeddings in column: {embedding_column}") + + current_dir = os.path.dirname(os.path.realpath(__file__)) + seed_file = os.path.join(current_dir, "cars_seed_data.json") + + with open(seed_file) as f: + seed_data_objects = json.load(f) + + rows = [] + for seed_data_object in seed_data_objects: + # Strip any existing embedding keys before constructing the model + attrs = {k: v for k, v in seed_data_object.items() if k not in ("embedding_3l", "embedding_nomic")} + row = Car(**attrs) + + embedding = await compute_text_embedding( + row.to_str_for_embedding(), + openai_client=openai_embed_client, + embed_model=common_params.openai_embed_model, + embed_deployment=common_params.openai_embed_deployment, + embedding_dimensions=common_params.openai_embed_dimensions, + ) + setattr(row, embedding_column, embedding) + rows.append(row) + logger.info(f"Embedded: {row.name}") + + # Write updated seed data (with embeddings) back to the file + with open(seed_file, "w") as f: + json.dump([row.to_dict(include_embedding=True) for row in rows], f, indent=4) + + logger.info(f"Done. Embeddings written to {seed_file}") + + +if __name__ == "__main__": + logging.basicConfig(level=logging.WARNING) + logger.setLevel(logging.INFO) + load_dotenv(override=True) + asyncio.run(update_cars_embeddings()) From c0ac5faed29ab5cb3a05b6a739f160dc62e2ebd4 Mon Sep 17 00:00:00 2001 From: Ankush Kumar Date: Sun, 9 Aug 2026 15:42:06 +0530 Subject: [PATCH 5/7] feat: add cars table HNSW indexes and seed data script --- src/backend/fastapi_app/postgres_models.py | 18 ++++ .../setup_postgres_cars_seeddata.py | 82 +++++++++++++++++++ .../fastapi_app/setup_postgres_seeddata.py | 4 +- 3 files changed, 102 insertions(+), 2 deletions(-) create mode 100644 src/backend/fastapi_app/setup_postgres_cars_seeddata.py diff --git a/src/backend/fastapi_app/postgres_models.py b/src/backend/fastapi_app/postgres_models.py index 1844727..4bdbf5a 100644 --- a/src/backend/fastapi_app/postgres_models.py +++ b/src/backend/fastapi_app/postgres_models.py @@ -95,3 +95,21 @@ def to_str_for_embedding(self): postgresql_with={"m": 16, "ef_construction": 64}, postgresql_ops={"embedding_nomic": "vector_cosine_ops"}, ) + +cars_table_name = Car.__tablename__ + +cars_index_3l = Index( + f"hnsw_index_for_cosine_{cars_table_name}_embedding_3l", + Car.embedding_3l, + postgresql_using="hnsw", + postgresql_with={"m": 16, "ef_construction": 64}, + postgresql_ops={"embedding_3l": "vector_cosine_ops"}, +) + +cars_index_nomic = Index( + f"hnsw_index_for_cosine_{cars_table_name}_embedding_nomic", + Car.embedding_nomic, + postgresql_using="hnsw", + postgresql_with={"m": 16, "ef_construction": 64}, + postgresql_ops={"embedding_nomic": "vector_cosine_ops"}, +) diff --git a/src/backend/fastapi_app/setup_postgres_cars_seeddata.py b/src/backend/fastapi_app/setup_postgres_cars_seeddata.py new file mode 100644 index 0000000..fb75dbf --- /dev/null +++ b/src/backend/fastapi_app/setup_postgres_cars_seeddata.py @@ -0,0 +1,82 @@ +import argparse +import asyncio +import json +import logging +import os + +import numpy as np +import sqlalchemy.exc +from dotenv import load_dotenv +from sqlalchemy import select, text +from sqlalchemy.ext.asyncio import async_sessionmaker + +from fastapi_app.postgres_engine import ( + create_postgres_engine_from_args, + create_postgres_engine_from_env, +) +from fastapi_app.postgres_models import Car + +logger = logging.getLogger("ragapp") + + +async def seed_data(engine): + # Check if cars table exists + async with engine.begin() as conn: + table_name = Car.__tablename__ + result = await conn.execute( + text( + f"SELECT EXISTS (SELECT 1 FROM information_schema.tables WHERE table_schema = 'public' AND table_name = '{table_name}')" # noqa + ) + ) + if not result.scalar(): + logger.error(f"{table_name} table does not exist. Please run the database setup script first.") + return + + async with async_sessionmaker(engine, expire_on_commit=False)() as session: + current_dir = os.path.dirname(os.path.realpath(__file__)) + with open(os.path.join(current_dir, "cars_seed_data.json")) as f: + seed_data_objects = json.load(f) + for seed_data_object in seed_data_objects: + db_car = await session.execute(select(Car).filter(Car.id == seed_data_object["id"])) + if db_car.scalars().first(): + logger.info(f"Car with id {seed_data_object['id']} already exists, skipping.") + continue + attrs = {key: value for key, value in seed_data_object.items()} + attrs["embedding_3l"] = np.array(seed_data_object["embedding_3l"]) if seed_data_object.get("embedding_3l") is not None else None + attrs["embedding_nomic"] = np.array(seed_data_object["embedding_nomic"]) if seed_data_object.get("embedding_nomic") is not None else None + column_names = ", ".join(attrs.keys()) + values = ", ".join([f":{key}" for key in attrs.keys()]) + await session.execute(text(f"INSERT INTO {table_name} ({column_names}) VALUES ({values})"), attrs) + try: + await session.commit() + except sqlalchemy.exc.IntegrityError: + pass + + logger.info(f"{table_name} table seeded successfully.") + + +async def main(): + parser = argparse.ArgumentParser(description="Seed cars data") + parser.add_argument("--host", type=str, help="Postgres host") + parser.add_argument("--username", type=str, help="Postgres username") + parser.add_argument("--password", type=str, help="Postgres password") + parser.add_argument("--database", type=str, help="Postgres database") + parser.add_argument("--sslmode", type=str, help="Postgres sslmode") + parser.add_argument("--tenant-id", type=str, help="Azure tenant ID", default=None) + + args = parser.parse_args() + if args.host is None: + engine = await create_postgres_engine_from_env() + else: + engine = await create_postgres_engine_from_args(args) + + await seed_data(engine) + + await engine.dispose() + + +if __name__ == "__main__": + logging.basicConfig(level=logging.WARNING) + logger.setLevel(logging.INFO) + load_dotenv(override=True) + asyncio.run(main()) diff --git a/src/backend/fastapi_app/setup_postgres_seeddata.py b/src/backend/fastapi_app/setup_postgres_seeddata.py index d943131..8bb5d4a 100644 --- a/src/backend/fastapi_app/setup_postgres_seeddata.py +++ b/src/backend/fastapi_app/setup_postgres_seeddata.py @@ -42,8 +42,8 @@ async def seed_data(engine): if db_item.scalars().first(): continue attrs = {key: value for key, value in seed_data_object.items()} - attrs["embedding_3l"] = np.array(seed_data_object["embedding_3l"]) - attrs["embedding_nomic"] = np.array(seed_data_object["embedding_nomic"]) + attrs["embedding_3l"] = np.array(seed_data_object["embedding_3l"]) if seed_data_object.get("embedding_3l") is not None else None + attrs["embedding_nomic"] = np.array(seed_data_object["embedding_nomic"]) if seed_data_object.get("embedding_nomic") is not None else None column_names = ", ".join(attrs.keys()) values = ", ".join([f":{key}" for key in attrs.keys()]) await session.execute(text(f"INSERT INTO {table_name} ({column_names}) VALUES ({values})"), attrs) From 4bbff43ddb6e7c4f6118f0530f819436378dddb6 Mon Sep 17 00:00:00 2001 From: Ankush Kumar Date: Mon, 10 Aug 2026 11:34:00 +0530 Subject: [PATCH 6/7] feat: add cars table with multi-domain RAG routing --- src/backend/fastapi_app/postgres_searcher.py | 8 ++-- src/backend/fastapi_app/rag_advanced.py | 46 +++++++++++++++++--- src/backend/fastapi_app/routes/api_routes.py | 24 +++++++++- 3 files changed, 69 insertions(+), 9 deletions(-) diff --git a/src/backend/fastapi_app/postgres_searcher.py b/src/backend/fastapi_app/postgres_searcher.py index aa84eaf..f8df386 100644 --- a/src/backend/fastapi_app/postgres_searcher.py +++ b/src/backend/fastapi_app/postgres_searcher.py @@ -7,7 +7,7 @@ from fastapi_app.api_models import Filter from fastapi_app.embeddings import compute_text_embedding -from fastapi_app.postgres_models import Item +from fastapi_app.postgres_models import Base, Item class PostgresSearcher: @@ -19,6 +19,7 @@ def __init__( embed_model: str, embed_dimensions: Optional[int], embedding_column: str, + db_model: type[Base] = Item, # which table to search; defaults to Item for backward compatibility ): self.db_session = db_session self.openai_embed_client = openai_embed_client @@ -26,6 +27,7 @@ def __init__( self.embed_deployment = embed_deployment self.embed_dimensions = embed_dimensions self.embedding_column = embedding_column + self.db_model = db_model def build_filter_clause(self, filters: Optional[list[Filter]]) -> tuple[str, str]: if filters is None: @@ -47,7 +49,7 @@ async def search( filters: Optional[list[Filter]] = None, ): filter_clause_where, filter_clause_and = self.build_filter_clause(filters) - table_name = Item.__tablename__ + table_name = self.db_model.__tablename__ vector_query = f""" SELECT id, RANK () OVER (ORDER BY {self.embedding_column} <=> :embedding) AS rank FROM {table_name} @@ -100,7 +102,7 @@ async def search( # Convert results to SQLAlchemy models row_models = [] for id, _ in results[:top]: - item = await self.db_session.execute(select(Item).where(Item.id == id)) + item = await self.db_session.execute(select(self.db_model).where(self.db_model.id == id)) row_models.append(item.scalar()) return row_models diff --git a/src/backend/fastapi_app/rag_advanced.py b/src/backend/fastapi_app/rag_advanced.py index 26e67c8..c057c18 100644 --- a/src/backend/fastapi_app/rag_advanced.py +++ b/src/backend/fastapi_app/rag_advanced.py @@ -44,11 +44,13 @@ def __init__( messages: list[ResponseInputItemParam], overrides: ChatRequestOverrides, searcher: PostgresSearcher, + cars_searcher: PostgresSearcher, openai_chat_client: AsyncOpenAI, chat_model: str, chat_deployment: Optional[str], # Not needed for non-Azure OpenAI ): self.searcher = searcher + self.cars_searcher = cars_searcher self.chat_params = self.get_chat_params(messages, overrides) self.model_for_thoughts = ( {"model": chat_model, "deployment": chat_deployment} if chat_deployment else {"model": chat_model} @@ -59,7 +61,7 @@ def __init__( self.search_agent = Agent( name="Searcher", instructions=self.query_prompt_template, - tools=[function_tool(self.search_database)], + tools=[function_tool(self.search_items), function_tool(self.search_cars)], tool_use_behavior="stop_on_first_tool", model=openai_agents_model, ) @@ -73,24 +75,24 @@ def __init__( ), ) - async def search_database( + async def search_items( self, search_query: str, price_filter: Optional[PriceFilter] = None, brand_filter: Optional[BrandFilter] = None, ) -> SearchResults: """ - Search PostgreSQL database for relevant products based on user query + Search the items database for products like clothing, footwear, outdoor gear, and accessories. + Use this tool when the user asks about general products, apparel, shoes, or equipment. Args: - search_query: English query string to use for full text search, e.g. 'red shoes'. + search_query: English query string to use for full text search, e.g. 'red hiking boots'. price_filter: Filter search results based on price of the product brand_filter: Filter search results based on brand of the product Returns: List of formatted items that match the search query and filters """ - # Only send non-None filters filters: list[Filter] = [] if price_filter: filters.append(price_filter) @@ -107,6 +109,40 @@ async def search_database( query=search_query, items=[ItemPublic.model_validate(item.to_dict()) for item in results], filters=filters ) + async def search_cars( + self, + search_query: str, + price_filter: Optional[PriceFilter] = None, + brand_filter: Optional[BrandFilter] = None, + ) -> SearchResults: + """ + Search the cars database for vehicles like sedans, SUVs, hatchbacks, crossovers, and electric cars. + Use this tool when the user asks about cars, vehicles, mileage, engine specs, or automobile brands. + + Args: + search_query: English query string to use for full text search, e.g. 'luxury SUV with sunroof'. + price_filter: Filter search results based on price of the car + brand_filter: Filter search results based on car brand (e.g. 'Hyundai', 'Toyota', 'BMW') + + Returns: + List of cars that match the search query and filters + """ + filters: list[Filter] = [] + if price_filter: + filters.append(price_filter) + if brand_filter: + filters.append(brand_filter) + results = await self.cars_searcher.search_and_embed( + search_query, + top=self.chat_params.top, + enable_vector_search=self.chat_params.enable_vector_search, + enable_text_search=self.chat_params.enable_text_search, + filters=filters, + ) + return SearchResults( + query=search_query, items=[ItemPublic.model_validate(item.to_dict()) for item in results], filters=filters + ) + async def prepare_context(self) -> tuple[list[ItemPublic], list[ThoughtStep]]: few_shots: list[ResponseInputItemParam] = json.loads(self.query_fewshots) user_query = f"Find search results for user query: {self.chat_params.original_user_query}" diff --git a/src/backend/fastapi_app/routes/api_routes.py b/src/backend/fastapi_app/routes/api_routes.py index 5821eaf..f497551 100644 --- a/src/backend/fastapi_app/routes/api_routes.py +++ b/src/backend/fastapi_app/routes/api_routes.py @@ -18,7 +18,7 @@ RetrievalResponseDelta, ) from fastapi_app.dependencies import ChatClient, CommonDeps, DBSession, EmbeddingsClient -from fastapi_app.postgres_models import Item +from fastapi_app.postgres_models import Car, Item from fastapi_app.postgres_searcher import PostgresSearcher from fastapi_app.rag_advanced import AdvancedRAGChat from fastapi_app.rag_simple import SimpleRAGChat @@ -117,6 +117,16 @@ async def chat_handler( embed_model=context.openai_embed_model, embed_dimensions=context.openai_embed_dimensions, embedding_column=context.embedding_column, + db_model=Item, + ) + cars_searcher = PostgresSearcher( + db_session=database_session, + openai_embed_client=openai_embed.client, + embed_deployment=context.openai_embed_deployment, + embed_model=context.openai_embed_model, + embed_dimensions=context.openai_embed_dimensions, + embedding_column=context.embedding_column, + db_model=Car, ) rag_flow: Union[SimpleRAGChat, AdvancedRAGChat] if chat_request.context.overrides.use_advanced_flow: @@ -124,6 +134,7 @@ async def chat_handler( messages=chat_request.input, overrides=chat_request.context.overrides, searcher=searcher, + cars_searcher=cars_searcher, openai_chat_client=openai_chat.client, chat_model=context.openai_chat_model, chat_deployment=context.openai_chat_deployment, @@ -164,6 +175,16 @@ async def chat_stream_handler( embed_model=context.openai_embed_model, embed_dimensions=context.openai_embed_dimensions, embedding_column=context.embedding_column, + db_model=Item, + ) + cars_searcher = PostgresSearcher( + db_session=database_session, + openai_embed_client=openai_embed.client, + embed_deployment=context.openai_embed_deployment, + embed_model=context.openai_embed_model, + embed_dimensions=context.openai_embed_dimensions, + embedding_column=context.embedding_column, + db_model=Car, ) rag_flow: Union[SimpleRAGChat, AdvancedRAGChat] @@ -172,6 +193,7 @@ async def chat_stream_handler( messages=chat_request.input, overrides=chat_request.context.overrides, searcher=searcher, + cars_searcher=cars_searcher, openai_chat_client=openai_chat.client, chat_model=context.openai_chat_model, chat_deployment=context.openai_chat_deployment, From 33dca9ec7460a32991751993be5de9c8409bd45d Mon Sep 17 00:00:00 2001 From: Ankush Kumar Date: Sat, 15 Aug 2026 19:19:17 +0530 Subject: [PATCH 7/7] fixed str issue --- src/backend/fastapi_app/rag_advanced.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/backend/fastapi_app/rag_advanced.py b/src/backend/fastapi_app/rag_advanced.py index c057c18..a7d2fb8 100644 --- a/src/backend/fastapi_app/rag_advanced.py +++ b/src/backend/fastapi_app/rag_advanced.py @@ -152,7 +152,9 @@ async def prepare_context(self) -> tuple[list[ItemPublic], list[ThoughtStep]]: run_results = await Runner.run(self.search_agent, input=all_messages) most_recent_response = run_results.new_items[-1] if isinstance(most_recent_response, ToolCallOutputItem): - search_results = most_recent_response.output + output = most_recent_response.output + # The agents SDK serializes Pydantic models to a JSON string — parse it back + search_results = SearchResults.model_validate_json(output) if isinstance(output, str) else output else: raise ValueError("Error retrieving search results, model did not call tool properly")