feat: Gradio Adater implementation

README.md

@@ -52,7 +52,7 @@ class CandidateView(SqlAlchemyBaseView):
         """
         return Candidate.country == country
 
-engine = create_engine('sqlite:///candidates.db')
+engine = create_engine('sqlite:///examples/recruiting/data/candidates.db')
 llm = LiteLLM(model_name="gpt-3.5-turbo")
 my_collection = create_collection("collection_name", llm)
 my_collection.add(CandidateView, lambda: CandidateView(engine))

docs/how-to/sql_views.md

@@ -77,7 +77,7 @@ You need to connect to the database using SQLAlchemy before you can use your vie
 ```python
 from sqlalchemy import create_engine
 
-engine = create_engine('sqlite:///candidates.db')
+engine = create_engine('sqlite:///examples/recruiting/data/candidates.db')
 ```
 
 ## Registering the view

docs/how-to/use_elastic_vector_store_code.py

@@ -17,7 +17,7 @@
 from dbally.similarity.elastic_vector_search import ElasticVectorStore
 
 load_dotenv()
-engine = create_engine("sqlite:///candidates.db")
+engine = create_engine("sqlite:///examples/recruiting/data/candidates.db")
 
 
 Base = automap_base()

docs/how-to/use_elasticsearch_store_code.py

@@ -18,7 +18,7 @@
 from dbally.similarity.elasticsearch_store import ElasticsearchStore
 
 load_dotenv()
-engine = create_engine("sqlite:///candidates.db")
+engine = create_engine("sqlite:///examples/recruiting/data/candidates.db")
 
 
 Base = automap_base()

docs/how-to/visualize_views.md

@@ -0,0 +1,44 @@
+# How-To: Visualize Views
+
+To create simple UI interface use [create_gradio_interface function](https://github.com/deepsense-ai/db-ally/tree/main/src/dbally/gradio/gradio_interface.py) It allows to display Data Preview related to Views
+and execute user queries.
+
+## Installation
+```bash
+pip install dbally["gradio"]
+```
+When You plan to use some other feature like faiss similarity store install them as well.
+
+```bash
+pip install dbally["faiss"]
+```
+
+## Create own gradio interface
+Define collection with implemented views
+
+```python
+llm = LiteLLM(model_name="gpt-3.5-turbo")
+await country_similarity.update()
+collection = dbally.create_collection("recruitment", llm, event_handlers=[CLIEventHandler()])
+collection.add(CandidateView, lambda: CandidateView(engine))
+collection.add(SampleText2SQLViewCyphers, lambda: SampleText2SQLViewCyphers(create_freeform_memory_engine()))
+```
+
+>_**NOTE**_: The following code requires environment variables to proceed with LLM queries. For the example below, set the
+> ```OPENAI_API_KEY``` environment variable.
+
+Create gradio interface
+```python
+gradio_interface = await create_gradio_interface(user_collection=collection)
+```
+
+Launch the gradio interface. To publish public interface pass argument `share=True`
+```python
+gradio_interface.launch()
+```
+
+The endpoint is set by triggering python module with Gradio Adapter launch command.
+Private endpoint is set to http://127.0.0.1:7860/ by default.
+
+## Links
+* [Example Gradio Interface](https://github.com/deepsense-ai/db-ally/tree/main/examples/visualize_views_code.py)

docs/quickstart/index.md

@@ -30,14 +30,14 @@ pip install dbally[litellm]
 
 ## Database Configuration
 
-In this guide, we will use an example SQLAlchemy database containing a single table named `candidates`. This table includes columns such as `id`, `name`, `country`, `years_of_experience`, `position`, `university`, `skills`, and `tags`. You can download the example database from [candidates.db](candidates.db). Alternatively, you can use your own database and models.
+In this guide, we will use an example SQLAlchemy database containing a single table named `candidates`. This table includes columns such as `id`, `name`, `country`, `years_of_experience`, `position`, `university`, `skills`, and `tags`. You can download the example database from [candidates.db](https://github.com/deepsense-ai/db-ally/tree/main/examples/recruiting/candidates.db). Alternatively, you can use your own database and models.
 
 To connect to the database using SQLAlchemy, you need an engine and your database models. Start by creating an engine:
 
 ```python
 from sqlalchemy import create_engine
 
-engine = create_engine('sqlite:///candidates.db')
+engine = create_engine('sqlite:///examples/recruiting/data/candidates.db')
 ```
 
 Next, define an SQLAlchemy model for the `candidates` table. You can either declare the `Candidate` model using [declarative mapping](https://docs.sqlalchemy.org/en/20/orm/mapping_styles.html#declarative-mapping) or generate it using [automap](https://docs.sqlalchemy.org/en/20/orm/extensions/automap.html). For simplicity, we'll use automap:

docs/quickstart/quickstart2_code.py

@@ -16,7 +16,7 @@
 from dbally.llms.litellm import LiteLLM
 
 load_dotenv()
-engine = create_engine("sqlite:///candidates.db")
+engine = create_engine("sqlite:///examples/recruiting/data/candidates.db")
 
 Base = automap_base()
 Base.prepare(autoload_with=engine)

docs/quickstart/quickstart3_code.py

@@ -14,7 +14,7 @@
 from dbally.embeddings.litellm import LiteLLMEmbeddingClient
 from dbally.llms.litellm import LiteLLM
 
-engine = create_engine("sqlite:///candidates.db")
+engine = create_engine("sqlite:///examples/recruiting/data/candidates.db")
 
 Base = automap_base()
 Base.prepare(autoload_with=engine)

docs/quickstart/quickstart_code.py

@@ -11,17 +11,19 @@
 from dbally.llms.litellm import LiteLLM
 
 
-engine = create_engine('sqlite:///candidates.db')
+engine = create_engine("sqlite:///examples/recruiting/data/candidates.db")
 
 Base = automap_base()
 Base.prepare(autoload_with=engine)
 
 Candidate = Base.classes.candidates
 
+
 class CandidateView(SqlAlchemyBaseView):
     """
     A view for retrieving candidates from the database.
     """
+
     def get_select(self) -> sqlalchemy.Select:
         """
         Creates the initial SqlAlchemy select object, which will be used to build the query.
@@ -52,6 +54,7 @@ def from_country(self, country: str) -> sqlalchemy.ColumnElement:
         """
         return Candidate.country == country
 
+
 async def main():
     llm = LiteLLM(model_name="gpt-3.5-turbo")
 

examples/recruiting.py

@@ -2,8 +2,8 @@
 from dataclasses import dataclass
 from typing import List
 
-from recruting.db import ENGINE, fill_candidate_table, get_recruitment_db_description
-from recruting.views import RecruitmentView
+from recruiting.db import ENGINE, fill_candidate_table, get_recruitment_db_description
+from recruiting.views import RecruitmentView
 
 import dbally
 from dbally.audit.event_handlers.cli_event_handler import CLIEventHandler

examples/recruiting/candidate_view_with_similarity_store.py

@@ -0,0 +1,68 @@
+# pylint: disable=missing-return-doc, missing-param-doc, missing-function-docstring
+
+import sqlalchemy
+from sqlalchemy import create_engine
+from sqlalchemy.ext.automap import automap_base
+from typing_extensions import Annotated
+
+from dbally import SqlAlchemyBaseView, decorators
+from dbally.embeddings.litellm import LiteLLMEmbeddingClient
+from dbally.similarity import FaissStore, SimilarityIndex, SimpleSqlAlchemyFetcher
+
+engine = create_engine("sqlite:///examples/recruiting/data/candidates.db")
+
+Base = automap_base()
+Base.prepare(autoload_with=engine)
+
+Candidate = Base.classes.candidates
+
+country_similarity = SimilarityIndex(
+    fetcher=SimpleSqlAlchemyFetcher(
+        engine,
+        table=Candidate,
+        column=Candidate.country,
+    ),
+    store=FaissStore(
+        index_dir="./similarity_indexes",
+        index_name="country_similarity",
+        embedding_client=LiteLLMEmbeddingClient(
+            model="text-embedding-3-small",  # to use openai embedding model
+        ),
+    ),
+)
+
+
+class CandidateView(SqlAlchemyBaseView):
+    """
+    A view for retrieving candidates from the database.
+    """
+
+    def get_select(self) -> sqlalchemy.Select:
+        """
+        Creates the initial SqlAlchemy select object, which will be used to build the query.
+        """
+        return sqlalchemy.select(Candidate)
+
+    @decorators.view_filter()
+    def at_least_experience(self, years: int) -> sqlalchemy.ColumnElement:
+        """
+        Filters candidates with at least `years` of experience.
+        """
+        return Candidate.years_of_experience >= years
+
+    @decorators.view_filter()
+    def senior_data_scientist_position(self) -> sqlalchemy.ColumnElement:
+        """
+        Filters candidates that can be considered for a senior data scientist position.
+        """
+        return sqlalchemy.and_(
+            Candidate.position.in_(["Data Scientist", "Machine Learning Engineer", "Data Engineer"]),
+            Candidate.years_of_experience >= 3,
+        )
+
+    @decorators.view_filter()
+    def from_country(self, country: Annotated[str, country_similarity]) -> sqlalchemy.ColumnElement:
+        """
+        Filters candidates from a specific country.
+        """
+        return Candidate.country == country

examples/recruiting/cypher_text2sql_view.py

@@ -0,0 +1,42 @@
+# pylint: disable=missing-return-doc, missing-function-docstring, missing-class-docstring, missing-return-type-doc
+from typing import List
+
+import sqlalchemy
+from sqlalchemy import text
+
+from dbally.views.freeform.text2sql import BaseText2SQLView, ColumnConfig, TableConfig
+
+
+class SampleText2SQLViewCyphers(BaseText2SQLView):
+    def get_tables(self) -> List[TableConfig]:
+        return [
+            TableConfig(
+                name="security_specialists",
+                columns=[
+                    ColumnConfig("id", "SERIAL PRIMARY KEY"),
+                    ColumnConfig("name", "VARCHAR(255)"),
+                    ColumnConfig("cypher", "VARCHAR(255)"),
+                ],
+                description="Knowledge base",
+            )
+        ]
+
+
+def create_freeform_memory_engine() -> sqlalchemy.Engine:
+    freeform_engine = sqlalchemy.create_engine("sqlite:///:memory:")
+
+    statements = [
+        "CREATE TABLE security_specialists (id INTEGER PRIMARY KEY, name TEXT, cypher TEXT)",
+        "INSERT INTO security_specialists (name, cypher) VALUES ('Alice', 'HAMAC')",
+        "INSERT INTO security_specialists (name, cypher) VALUES ('Bob', 'AES')",
+        "INSERT INTO security_specialists (name, cypher) VALUES ('Charlie', 'RSA')",
+        "INSERT INTO security_specialists (name, cypher) VALUES ('David', 'SHA2')",
+    ]
+
+    with freeform_engine.connect() as conn:
+        for statement in statements:
+            conn.execute(text(statement))
+
+        conn.commit()
+
+    return freeform_engine

examples/visualize_views_code.py

@@ -0,0 +1,24 @@
+# pylint: disable=missing-function-docstring
+import asyncio
+
+from recruiting.candidate_view_with_similarity_store import CandidateView, country_similarity, engine
+from recruiting.cypher_text2sql_view import SampleText2SQLViewCyphers, create_freeform_memory_engine
+
+import dbally
+from dbally.audit import CLIEventHandler
+from dbally.gradio import create_gradio_interface
+from dbally.llms.litellm import LiteLLM
+
+
+async def main():
+    await country_similarity.update()
+    llm = LiteLLM(model_name="gpt-3.5-turbo")
+    collection = dbally.create_collection("candidates", llm, event_handlers=[CLIEventHandler()])
+    collection.add(CandidateView, lambda: CandidateView(engine))
+    collection.add(SampleText2SQLViewCyphers, lambda: SampleText2SQLViewCyphers(create_freeform_memory_engine()))
+    gradio_interface = await create_gradio_interface(user_collection=collection)
+    gradio_interface.launch()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

mkdocs.yml

@@ -29,6 +29,7 @@ nav:
           - how-to/use_elastic_store.md
           - how-to/use_custom_similarity_store.md
           - how-to/update_similarity_indexes.md
+      - how-to/visualize_views.md
       - how-to/log_runs_to_langsmith.md
       - how-to/create_custom_event_handler.md
       - how-to/openai_assistants_integration.md

setup.cfg

@@ -64,7 +64,11 @@ benchmark =
     pydantic-settings~=2.0.3
     psycopg2-binary~=2.9.9
 elasticsearch =
-    elasticsearch==8.13.1
+    elasticsearch~=8.13.1
+gradio =
+    gradio~=4.31.5
+    gradio_client~=0.16.4
+
 
 [options.packages.find]
 where = src