Wrap all create/update connectors with generic tools #49
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plutasnyy
changed the title
always game for manual testing, but checking: do we not have anything automated in place that will catch issues? |
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Unfortunately, there is no such thing :( We probably should add some |
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TODO: |
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| "databricks_volumes": create_databricks_volumes_destination, | ||
| "mongodb": create_mongodb_destination, | ||
| "neo4j": create_neo4j_destination, | ||
| "pinecone": create_pinecone_destination, | ||
| "s3": create_s3_destination, | ||
| "weaviate": create_weaviate_destination, | ||
| } | ||
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| if destination_type in destination_functions: | ||
| destination_function = destination_functions[destination_type] | ||
| return await destination_function(ctx=ctx, name=name, **type_specific_config) | ||
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| return ( | ||
| f"Unsupported destination type: {destination_type}. " | ||
| f"Please use a supported destination type {list(destination_functions.keys())}." | ||
| ) | ||
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| async def update_destination_connector( | ||
| ctx: Context, | ||
| destination_id: str, | ||
| destination_type: Literal[ | ||
| "astradb", | ||
| "databricks_delta_table", | ||
| "databricks_volumes", | ||
| "mongodb", | ||
| "neo4j", | ||
| "pinecone", | ||
| "s3", | ||
| "weaviate", | ||
| ], | ||
| type_specific_config: dict[str, Any], | ||
| ) -> str: | ||
| """Update a destination connector based on type. | ||
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| Args: | ||
| ctx: Context object with the request and lifespan context | ||
| destination_id: ID of the destination connector to update | ||
| destination_type: The type of destination being updated | ||
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| type_specific_config: | ||
| astradb: | ||
| collection_name: (Optional[str]): The AstraDB collection name | ||
| keyspace: (Optional[str]): The AstraDB keyspace | ||
| batch_size: (Optional[int]) The batch size for inserting documents | ||
| databricks_delta_table: | ||
| catalog: (Optional[str]): Name of the catalog in Databricks Unity Catalog | ||
| database: (Optional[str]): The database in Unity Catalog | ||
| http_path: (Optional[str]): The cluster’s or SQL warehouse’s HTTP Path value | ||
| server_hostname: (Optional[str]): The Databricks cluster’s or SQL warehouse’s | ||
| Server Hostname value | ||
| table_name: (Optional[str]): The name of the table in the schema | ||
| volume: (Optional[str]): Name of the volume associated with the schema. | ||
| schema: (Optional[str]) Name of the schema associated with the volume | ||
| volume_path: (Optional[str]) Any target folder path within the volume, starting | ||
| from the root of the volume. | ||
| databricks_volumes: | ||
| catalog: (Optional[str]): Name of the catalog in Databricks | ||
| host: (Optional[str]): The Databricks host URL | ||
| volume: (Optional[str]): Name of the volume associated with the schema | ||
| schema: (Optional[str]) Name of the schema associated with the volume. The default | ||
| value is "default". | ||
| volume_path: (Optional[str]) Any target folder path within the volume, | ||
| starting from the root of the volume. | ||
| mongodb: | ||
| database: (Optional[str]): The name of the MongoDB database | ||
| collection: (Optional[str]): The name of the MongoDB collection | ||
| neo4j: | ||
| database: (Optional[str]): The Neo4j database, e.g. "neo4j" | ||
| uri: (Optional[str]): The Neo4j URI | ||
| e.g. neo4j+s://<neo4j_instance_id>.databases.neo4j.io | ||
| batch_size: (Optional[int]) The batch size for the connector | ||
| pinecone: | ||
| index_name: (Optional[str]): The Pinecone index name | ||
| namespace: (Optional[str]) The pinecone namespace, a folder inside the | ||
| pinecone index | ||
| batch_size: (Optional[int]) The batch size | ||
| s3: | ||
| remote_url: (Optional[str]): The S3 URI to the bucket or folder | ||
| weaviate: | ||
| cluster_url: (Optional[str]): URL of the Weaviate cluster | ||
| collection: (Optional[str]): Name of the collection in the Weaviate cluster | ||
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| Returns: | ||
| String containing the updated destination connector information | ||
| """ | ||
| update_functions = { | ||
| "astradb": update_astradb_destination, | ||
| "databricks_delta_table": update_databricks_delta_table_destination, | ||
| "databricks_volumes": update_databricks_volumes_destination, | ||
| "mongodb": update_mongodb_destination, | ||
| "neo4j": update_neo4j_destination, | ||
| "pinecone": update_pinecone_destination, | ||
| "s3": update_s3_destination, | ||
| "weaviate": update_weaviate_destination, | ||
| } | ||
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| if destination_type in update_functions: | ||
| update_function = update_functions[destination_type] | ||
| return await update_function(ctx=ctx, destination_id=destination_id, **type_specific_config) |
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what's the long term vision? are we going to keep extending across all destinations? this does feel great as far as scaling out, but no need to block here.
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To be honest, I don't know if we would scale drastically with something, I think the crucial thing to add would be to select a subset of tools. Then we could split them across different dimensions, e.g., s3_connector, which can perform CRUD on s3 sources and destinations.
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or for example expose only tools that have credentials provided
ryannikolaidis
approved these changes
Apr 7, 2025
Yea, agree, feels like table stakes. Maybe stub a ticket just as a reminder/placeholder? |
plutasnyy
deleted the
pluto/reduce_prompt_length_4_unify_source_and_destination
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This PR wraps create update tools into generic tools. It reduces the amount of tokens in the context by 5k:
I have verified running all notebooks and in debug mode invalid usage, and LGTM. I encourage reviewers for extra testing ;)