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Added ClickHouse vector sotre support
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Valery Denisov
parent
c1802e7cf0
commit
117a548117
@ -1,7 +1,7 @@
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## Vectorstores
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PrivateGPT supports [Qdrant](https://qdrant.tech/), [Chroma](https://www.trychroma.com/) and [PGVector](https://github.com/pgvector/pgvector) as vectorstore providers. Qdrant being the default.
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PrivateGPT supports [Qdrant](https://qdrant.tech/), [Chroma](https://www.trychroma.com/), [PGVector](https://github.com/pgvector/pgvector) and [ClickHouse](https://github.com/ClickHouse/ClickHouse) as vectorstore providers. Qdrant being the default.
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In order to select one or the other, set the `vectorstore.database` property in the `settings.yaml` file to `qdrant`, `chroma` or `postgres`.
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In order to select one or the other, set the `vectorstore.database` property in the `settings.yaml` file to `qdrant`, `chroma`, `postgres` and `clickhouse`.
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```yaml
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vectorstore:
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@ -101,3 +101,69 @@ Indexes:
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postgres=#
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```
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The dimensions of the embeddings columns will be set based on the `embedding.embed_dim` value. If the embedding model changes this table may need to be dropped and recreated to avoid a dimension mismatch.
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### ClickHouse
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To utilize ClickHouse as the vector store, a [ClickHouse](https://github.com/ClickHouse/ClickHouse) database must be employed.
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To enable ClickHouse, set the `vectorstore.database` property in the `settings.yaml` file to `clickhouse` and install the `vector-stores-clickhouse` extra.
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```bash
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poetry install --extras vector-stores-clickhouse
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```
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ClickHouse settings can be configured by setting values to the `clickhouse` property in the `settings.yaml` file.
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The available configuration options are:
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| Field | Description |
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|----------------------|----------------------------------------------------------------|
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| **host** | The server hosting the ClickHouse database. Default is `localhost` |
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| **port** | The port on which the ClickHouse database is accessible. Default is `8123` |
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| **username** | The username for database access. Default is `default` |
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| **password** | The password for database access. (Optional) |
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| **database** | The specific database to connect to. Default is `__default__` |
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| **secure** | Use https/TLS for secure connection to the server. Default is `false` |
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| **interface** | The protocol used for the connection, either 'http' or 'https'. (Optional) |
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| **settings** | Specific ClickHouse server settings to be used with the session. (Optional) |
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| **connect_timeout** | Timeout in seconds for establishing a connection. (Optional) |
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| **send_receive_timeout** | Read timeout in seconds for http connection. (Optional) |
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| **verify** | Verify the server certificate in secure/https mode. (Optional) |
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| **ca_cert** | Path to Certificate Authority root certificate (.pem format). (Optional) |
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| **client_cert** | Path to TLS Client certificate (.pem format). (Optional) |
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| **client_cert_key** | Path to the private key for the TLS Client certificate. (Optional) |
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| **http_proxy** | HTTP proxy address. (Optional) |
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| **https_proxy** | HTTPS proxy address. (Optional) |
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| **server_host_name** | Server host name to be checked against the TLS certificate. (Optional) |
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For example:
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```yaml
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vectorstore:
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database: clickhouse
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clickhouse:
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host: localhost
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port: 8443
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username: admin
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password: <PASSWORD>
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database: embeddings
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secure: false
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```
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The following table will be created in the database:
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```
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clickhouse-client
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:) \d embeddings.llama_index
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Table "llama_index"
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№ | name | type | default_type | default_expression | comment | codec_expression | ttl_expression
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----|-----------|----------------------------------------------|--------------|--------------------|---------|------------------|---------------
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1 | id | String | | | | |
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2 | doc_id | String | | | | |
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3 | text | String | | | | |
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4 | vector | Array(Float32) | | | | |
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5 | node_info | Tuple(start Nullable(UInt64), end Nullable(UInt64)) | | | | |
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6 | metadata | String | | | | |
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clickhouse-client
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```
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The dimensions of the embeddings columns will be set based on the `embedding.embed_dim` value. If the embedding model changes, this table may need to be dropped and recreated to avoid a dimension mismatch.
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@ -121,6 +121,25 @@ class VectorStoreComponent:
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collection_name="make_this_parameterizable_per_api_call",
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), # TODO
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)
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case "clickhouse":
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try:
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from llama_index.vector_stores.clickhouse import ClickHouseVectorStore
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from clickhouse_connect import get_client
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except ImportError as e:
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raise ImportError(
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"ClickHouse dependencies not found, install with `poetry install --extras vector-stores-clickhouse`"
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) from e
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if settings.clickhouse is None:
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raise ValueError("ClickHouse settings not found. Please provide settings.")
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clickhouse_client = get_client(
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host=settings.clickhouse.host,
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port=settings.clickhouse.port,
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username=settings.clickhouse.username,
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password=settings.clickhouse.password,
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)
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self.vector_store = ClickHouseVectorStore(clickhouse_client=clickhouse_client)
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case _:
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# Should be unreachable
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# The settings validator should have caught this
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@ -1,4 +1,4 @@
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from typing import Literal
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from typing import Literal, Optional, Dict, Any, Union
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from pydantic import BaseModel, Field
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@ -107,7 +107,7 @@ class LLMSettings(BaseModel):
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class VectorstoreSettings(BaseModel):
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database: Literal["chroma", "qdrant", "postgres"]
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database: Literal["chroma", "qdrant", "postgres", "clickhouse"]
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class NodeStoreSettings(BaseModel):
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@ -323,6 +323,77 @@ class RagSettings(BaseModel):
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rerank: RerankSettings
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class ClickHouseSettings(BaseModel):
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host: str = Field(
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"localhost",
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description="The server hosting the ClickHouse database",
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)
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port: int = Field(
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8123,
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description="The port on which the ClickHouse database is accessible",
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)
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username: str = Field(
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"default",
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description="The username to use to connect to the ClickHouse database",
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)
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password: str = Field(
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"",
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description="The password to use to connect to the ClickHouse database",
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)
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database: str = Field(
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"__default__",
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description="The default database to use for connections",
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)
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secure: Union[bool, str] = Field(
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False,
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description="Use https/TLS for secure connection to the server",
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)
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interface: Optional[str] = Field(
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None,
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description="Must be either 'http' or 'https'. Determines the protocol to use for the connection",
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)
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settings: Optional[Dict[str, Any]] = Field(
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None,
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description="Specific ClickHouse server settings to be used with the session",
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)
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connect_timeout: Optional[int] = Field(
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None,
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description="Timeout in seconds for establishing a connection",
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)
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send_receive_timeout: Optional[int] = Field(
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None,
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description="Read timeout in seconds for http connection",
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)
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verify: Optional[bool] = Field(
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None,
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description="Verify the server certificate in secure/https mode",
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)
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ca_cert: Optional[str] = Field(
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None,
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description="Path to Certificate Authority root certificate (.pem format)",
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)
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client_cert: Optional[str] = Field(
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None,
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description="Path to TLS Client certificate (.pem format)",
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)
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client_cert_key: Optional[str] = Field(
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None,
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description="Path to the private key for the TLS Client certificate",
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)
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http_proxy: Optional[str] = Field(
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None,
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description="HTTP proxy address",
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)
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https_proxy: Optional[str] = Field(
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None,
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description="HTTPS proxy address",
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)
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server_host_name: Optional[str] = Field(
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None,
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description="Server host name to be checked against the TLS certificate",
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)
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class PostgresSettings(BaseModel):
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host: str = Field(
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"localhost",
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@ -421,6 +492,7 @@ class Settings(BaseModel):
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rag: RagSettings
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qdrant: QdrantSettings | None = None
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postgres: PostgresSettings | None = None
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clickhouse: ClickHouseSettings | None = None
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"""
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@ -31,12 +31,16 @@ llama-index-embeddings-azure-openai = {version ="^0.1.6", optional = true}
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llama-index-vector-stores-qdrant = {version ="^0.1.3", optional = true}
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llama-index-vector-stores-chroma = {version ="^0.1.4", optional = true}
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llama-index-vector-stores-postgres = {version ="^0.1.2", optional = true}
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llama-index-vector-stores-clickhouse = {version ="^0.1.3", optional = true}
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llama-index-storage-docstore-postgres = {version ="^0.1.2", optional = true}
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llama-index-storage-index-store-postgres = {version ="^0.1.2", optional = true}
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# Postgres
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psycopg2-binary = {version ="^2.9.9", optional = true}
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asyncpg = {version="^0.29.0", optional = true}
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# ClickHouse
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clickhouse-connect = {version = "^0.7.8", optional = true}
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# Optional Sagemaker dependency
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boto3 = {version ="^1.34.51", optional = true}
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@ -61,6 +65,7 @@ embeddings-openai = ["llama-index-embeddings-openai"]
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embeddings-sagemaker = ["boto3"]
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embeddings-azopenai = ["llama-index-embeddings-azure-openai"]
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vector-stores-qdrant = ["llama-index-vector-stores-qdrant"]
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vector-stores-clickhouse = ["llama-index-vector-stores-clickhouse", "clickhouse_connect"]
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vector-stores-chroma = ["llama-index-vector-stores-chroma"]
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vector-stores-postgres = ["llama-index-vector-stores-postgres"]
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storage-nodestore-postgres = ["llama-index-storage-docstore-postgres","llama-index-storage-index-store-postgres","psycopg2-binary","asyncpg"]
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@ -52,6 +52,13 @@ rag:
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model: cross-encoder/ms-marco-MiniLM-L-2-v2
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top_n: 1
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clickhouse:
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host: localhost
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port: 8443
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username: admin
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password: clickhouse
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database: embeddings
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llamacpp:
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prompt_style: "mistral"
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llm_hf_repo_id: TheBloke/Mistral-7B-Instruct-v0.2-GGUF
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