diff --git a/.apolo/__init__.py b/.apolo/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/.apolo/applications.yaml b/.apolo/applications.yaml new file mode 100644 index 00000000..c685b2d2 --- /dev/null +++ b/.apolo/applications.yaml @@ -0,0 +1,55 @@ +- app_type: lightrag + name: lightrag + title: LightRAG + install_type: workflow + helm_path: k8s-deploy/lightrag + app_package_name: apolo_apps_lightrag + inputs: + schema_path: .apolo/src/apolo_apps_lightrag/schemas/LightRAGAppInputs.json + types_name: LightRAGAppInputs + processor: LightRAGInputsProcessor + image: ghcr.io/neuro-inc/app-lightrag + outputs: + schema_path: .apolo/src/apolo_apps_lightrag/schemas/LightRAGAppOutputs.json + types_name: LightRAGAppOutputs + processor: LightRAGOutputsProcessor + image: ghcr.io/neuro-inc/app-lightrag + short_description: Advanced RAG framework with graph-enhanced retrieval capabilities + description: | + LightRAG is a simple and fast Retrieval-Augmented Generation (RAG) system that incorporates + graph structure into text indexing and retrieval processes. Unlike traditional RAG approaches, + LightRAG utilizes both low-level and high-level knowledge discovery to enhance text retrieval. + It supports both naive and local search methods, making it suitable for comprehensive + question-answering tasks. The system includes a user-friendly web interface for document + management and querying, with built-in support for various LLM providers and embedding models. + pub_date: "2025-06-25T00:00:00+00:00" + logo: https://storage.googleapis.com/development-421920-assets/app-logos/lightrag-logo.png + tags: + - "RAG" + - "LightRAG" + - "Knowledge Graph" + - "Vector Search" + - "Document Processing" + - "LLM" + - "Embeddings" + - "PostgreSQL" + - "Graph" + - "AI" + - "NLP" + assets: + - type: image + url: https://storage.googleapis.com/development-421920-assets/app-logos/lightrag-banner.png + - type: video + url: https://www.youtube.com/watch?v=oageL-1I0GE + - type: pdf + url: https://arxiv.org/abs/2410.05779 + urls: + - name: LightRAG GitHub Repository + type: documentation + url: https://github.com/HKUDS/LightRAG + - name: LightRAG DeepWiki Documentation + type: documentation + url: https://deepwiki.com/HKUDS/LightRAG + - name: LightRAG Official Repository + type: external + url: https://github.com/HKUDS/LightRAG diff --git a/.apolo/project.yaml b/.apolo/project.yaml new file mode 100644 index 00000000..2a9d249b --- /dev/null +++ b/.apolo/project.yaml @@ -0,0 +1 @@ +id: lightrag diff --git a/.apolo/scripts/gen_types_schemas.mk b/.apolo/scripts/gen_types_schemas.mk new file mode 100644 index 00000000..2db786c4 --- /dev/null +++ b/.apolo/scripts/gen_types_schemas.mk @@ -0,0 +1,3 @@ +.PHONY: gen-types-schemas +gen-types-schemas: + @.apolo/scripts/gen_types_schemas.sh diff --git a/.apolo/scripts/gen_types_schemas.sh b/.apolo/scripts/gen_types_schemas.sh new file mode 100755 index 00000000..5eeb0e84 --- /dev/null +++ b/.apolo/scripts/gen_types_schemas.sh @@ -0,0 +1,26 @@ +#!/usr/bin/env bash + +set -euo pipefail + +REPO_ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/../.." && pwd)" +APP_PACKAGE_DIR=".apolo/src/apolo_apps_lightrag" + +INPUT_SCHEMA="${APP_PACKAGE_DIR}/schemas/LightRAGAppInputs.json" +OUTPUT_SCHEMA="${APP_PACKAGE_DIR}/schemas/LightRAGAppOutputs.json" + +if command -v poetry >/dev/null 2>&1; then + APP_TYPES_CMD=(poetry run app-types) +elif [[ -x "${REPO_ROOT}/.venv/bin/app-types" ]]; then + APP_TYPES_CMD=("${REPO_ROOT}/.venv/bin/app-types") +elif command -v app-types >/dev/null 2>&1; then + APP_TYPES_CMD=(app-types) +else + echo "app-types CLI not found. Install dependencies via 'poetry install --with dev'." >&2 + exit 1 +fi + +( + cd "${REPO_ROOT}" + "${APP_TYPES_CMD[@]}" dump-types-schema "${APP_PACKAGE_DIR}" LightRAGAppInputs "${INPUT_SCHEMA}" + "${APP_TYPES_CMD[@]}" dump-types-schema "${APP_PACKAGE_DIR}" LightRAGAppOutputs "${OUTPUT_SCHEMA}" +) diff --git a/.apolo/src/apolo_apps_lightrag/__init__.py b/.apolo/src/apolo_apps_lightrag/__init__.py new file mode 100644 index 00000000..5cbe48f3 --- /dev/null +++ b/.apolo/src/apolo_apps_lightrag/__init__.py @@ -0,0 +1,15 @@ +from apolo_apps_lightrag.inputs_processor import ( + LightRAGInputsProcessor, +) +from apolo_apps_lightrag.outputs_processor import ( + LightRAGOutputsProcessor, +) +from apolo_apps_lightrag.types import LightRAGAppInputs, LightRAGAppOutputs + + +__all__ = [ + "LightRAGInputsProcessor", + "LightRAGOutputsProcessor", + "LightRAGAppInputs", + "LightRAGAppOutputs", +] diff --git a/.apolo/src/apolo_apps_lightrag/inputs_processor.py b/.apolo/src/apolo_apps_lightrag/inputs_processor.py new file mode 100644 index 00000000..4c71e615 --- /dev/null +++ b/.apolo/src/apolo_apps_lightrag/inputs_processor.py @@ -0,0 +1,246 @@ +import logging +import typing as t + +from apolo_app_types.app_types import AppType +from apolo_app_types.helm.apps.base import BaseChartValueProcessor +from apolo_app_types.helm.apps.common import gen_extra_values +from apolo_app_types.helm.utils.deep_merging import merge_list_of_dicts +from apolo_app_types.protocols.common.openai_compat import ( + OpenAICompatChatAPI, + OpenAICompatEmbeddingsAPI, +) +from apolo_app_types.protocols.common.secrets_ import serialize_optional_secret + +from .types import ( + AnthropicLLMProvider, + GeminiLLMProvider, + LightRAGAppInputs, + OllamaEmbeddingProvider, + OllamaLLMProvider, + OpenAIEmbeddingProvider, + OpenAILLMProvider, +) + + +logger = logging.getLogger(__name__) + + +class LightRAGInputsProcessor(BaseChartValueProcessor[LightRAGAppInputs]): + def _extract_llm_config(self, llm_config: t.Any) -> dict[str, t.Any]: + """Extract LLM configuration from provider-specific config.""" + if isinstance(llm_config, OpenAICompatChatAPI): + if not llm_config.hf_model: + msg = "OpenAI compatible chat API must have hf_model configured" + raise ValueError(msg) + model = llm_config.hf_model.model_hf_name + host = llm_config.complete_url + return { + "binding": "openai", + "model": model, + "host": host, + "api_key": getattr(llm_config, "api_key", None), + } + if isinstance(llm_config, OpenAILLMProvider): + host = llm_config.complete_url + return { + "binding": "openai", + "model": llm_config.model, + "host": host, + "api_key": llm_config.api_key, + } + if isinstance(llm_config, AnthropicLLMProvider): + host = llm_config.complete_url + return { + "binding": "anthropic", + "model": llm_config.model, + "host": host, + "api_key": llm_config.api_key, + } + if isinstance(llm_config, OllamaLLMProvider): + host = llm_config.complete_url + return { + "binding": "ollama", + "model": llm_config.model, + "host": host, + "api_key": None, + } + if isinstance(llm_config, GeminiLLMProvider): + host = llm_config.complete_url + return { + "binding": "gemini", + "model": llm_config.model, + "host": host, + "api_key": llm_config.api_key, + } + binding = getattr(llm_config, "provider", "openai") + model = getattr(llm_config, "model", "gpt-4o-mini") + api_key = getattr(llm_config, "api_key", None) + host = "" + if hasattr(llm_config, "complete_url"): + host = llm_config.complete_url + elif hasattr(llm_config, "host") and llm_config.host: + protocol = getattr(llm_config, "protocol", "https") + port = getattr(llm_config, "port", 443) + host = f"{protocol}://{llm_config.host}:{port}" + return {"binding": binding, "model": model, "host": host, "api_key": api_key} + + def _extract_embedding_config(self, embedding_config: t.Any) -> dict[str, t.Any]: + """Extract embedding configuration from provider-specific config.""" + if isinstance(embedding_config, OpenAICompatEmbeddingsAPI): + if embedding_config.hf_model is None: + msg = "OpenAI compatible embeddings API must have hf_model configured" + raise ValueError(msg) + model = embedding_config.hf_model.model_hf_name + host = embedding_config.complete_url + return { + "binding": "openai", + "model": model, + "api_key": getattr(embedding_config, "api_key", None), + "dimensions": 1536, + "host": host, + } + if isinstance(embedding_config, OpenAIEmbeddingProvider): + host = embedding_config.complete_url + return { + "binding": "openai", + "model": embedding_config.model, + "api_key": embedding_config.api_key, + "dimensions": 1536, + "host": host, + } + if isinstance(embedding_config, OllamaEmbeddingProvider): + host = embedding_config.complete_url + return { + "binding": "ollama", + "model": embedding_config.model, + "api_key": None, + "dimensions": 1024, + "host": host, + } + binding = getattr(embedding_config, "provider", "openai") + model = getattr(embedding_config, "model", "text-embedding-ada-002") + api_key = getattr(embedding_config, "api_key", None) + dimensions = 1536 + if hasattr(embedding_config, "dimensions"): + dimensions = embedding_config.dimensions + host = "" + if hasattr(embedding_config, "complete_url"): + host = embedding_config.complete_url + elif hasattr(embedding_config, "host") and embedding_config.host: + protocol = getattr(embedding_config, "protocol", "https") + port = getattr(embedding_config, "port", 443) + host = f"{protocol}://{embedding_config.host}:{port}" + return { + "binding": binding, + "model": model, + "api_key": api_key, + "dimensions": dimensions, + "host": host, + } + + async def _get_environment_values( + self, + input_: LightRAGAppInputs, + app_secrets_name: str, + ) -> dict[str, t.Any]: + llm_config = self._extract_llm_config(input_.llm_config) + embedding_config = self._extract_embedding_config(input_.embedding_config) + env_config = { + "HOST": "0.0.0.0", + "PORT": 9621, + "WEBUI_TITLE": "Graph RAG Engine", + "WEBUI_DESCRIPTION": "Simple and Fast Graph Based RAG System", + "LLM_BINDING": llm_config["binding"], + "LLM_MODEL": llm_config["model"], + "LLM_BINDING_HOST": llm_config["host"], + "LLM_BINDING_API_KEY": serialize_optional_secret( + llm_config["api_key"], app_secrets_name + ), + "OPENAI_API_KEY": serialize_optional_secret( + llm_config["api_key"], app_secrets_name + ) + or "", + "EMBEDDING_BINDING": embedding_config["binding"], + "EMBEDDING_MODEL": embedding_config["model"], + "EMBEDDING_DIM": embedding_config["dimensions"], + "EMBEDDING_BINDING_HOST": embedding_config["host"], + "EMBEDDING_BINDING_API_KEY": serialize_optional_secret( + embedding_config["api_key"], app_secrets_name + ) + or "", + "LIGHTRAG_KV_STORAGE": "PGKVStorage", + "LIGHTRAG_VECTOR_STORAGE": "PGVectorStorage", + "LIGHTRAG_DOC_STATUS_STORAGE": "PGDocStatusStorage", + "LIGHTRAG_GRAPH_STORAGE": "NetworkXStorage", + "POSTGRES_HOST": input_.pgvector_user.pgbouncer_host, + "POSTGRES_PORT": input_.pgvector_user.pgbouncer_port, + "POSTGRES_USER": input_.pgvector_user.user, + "POSTGRES_PASSWORD": input_.pgvector_user.password, + "POSTGRES_DATABASE": input_.pgvector_user.dbname, + "POSTGRES_WORKSPACE": "default", + } + return {"env": env_config} + + async def _get_persistence_values( + self, + input_: LightRAGAppInputs, + ) -> dict[str, t.Any]: + return { + "persistence": { + "enabled": True, + "ragStorage": { + "size": f"{input_.persistence.rag_storage_size}Gi", + }, + "inputs": { + "size": f"{input_.persistence.inputs_storage_size}Gi", + }, + } + } + + async def gen_extra_values( + self, + input_: LightRAGAppInputs, + app_name: str, + namespace: str, + app_id: str, + app_secrets_name: str, + *_: t.Any, + **kwargs: t.Any, + ) -> dict[str, t.Any]: + env_values = await self._get_environment_values(input_, app_secrets_name) + persistence_values = await self._get_persistence_values(input_) + platform_values = await gen_extra_values( + apolo_client=self.client, + preset_type=input_.preset, + ingress_http=input_.ingress_http, + ingress_grpc=None, + namespace=namespace, + app_id=app_id, + app_type=AppType.LightRAG, + ) + base_values = { + "replicaCount": 1, + "image": { + "repository": "ghcr.io/hkuds/lightrag", + "tag": "1.3.8", + "pullPolicy": "IfNotPresent", + }, + "service": { + "type": "ClusterIP", + "port": 9621, + }, + "nameOverride": "", + "fullnameOverride": app_name, + } + logger.debug("Generated LightRAG values for app %s", app_name) + return merge_list_of_dicts( + [ + base_values, + env_values, + persistence_values, + platform_values, + ] + ) + + +__all__ = ["LightRAGInputsProcessor"] diff --git a/.apolo/src/apolo_apps_lightrag/outputs_processor.py b/.apolo/src/apolo_apps_lightrag/outputs_processor.py new file mode 100644 index 00000000..cb6f011b --- /dev/null +++ b/.apolo/src/apolo_apps_lightrag/outputs_processor.py @@ -0,0 +1,66 @@ +import logging +import typing as t + +from apolo_app_types.clients.kube import get_service_host_port +from apolo_app_types.outputs.base import BaseAppOutputsProcessor +from apolo_app_types.outputs.common import ( + INSTANCE_LABEL, + get_internal_external_web_urls, +) +from apolo_app_types.outputs.utils.ingress import get_ingress_host_port +from apolo_app_types.protocols.common.networking import HttpApi, ServiceAPI, WebApp + +from .types import LightRAGAppOutputs + + +logger = logging.getLogger(__name__) + + +async def _generate_lightrag_outputs( + helm_values: dict[str, t.Any], + app_instance_id: str, +) -> LightRAGAppOutputs: + labels = {"app.kubernetes.io/name": "lightrag", INSTANCE_LABEL: app_instance_id} + internal_web_app_url, external_web_app_url = await get_internal_external_web_urls( + labels + ) + internal_host, internal_port = await get_service_host_port(match_labels=labels) + internal_server_url = None + if internal_host: + internal_server_url = HttpApi( + host=internal_host, + port=int(internal_port), + protocol="http", + ) + external_server_url = None + ingress_host_port = await get_ingress_host_port(match_labels=labels) + if ingress_host_port: + external_server_url = HttpApi( + host=ingress_host_port[0], + port=int(ingress_host_port[1]), + protocol="https", + ) + return LightRAGAppOutputs( + app_url=ServiceAPI[WebApp]( + internal_url=internal_web_app_url, + external_url=external_web_app_url, + ), + server_url=ServiceAPI[HttpApi]( + internal_url=internal_server_url, + external_url=external_server_url, + ), + ) + + +class LightRAGOutputsProcessor(BaseAppOutputsProcessor[LightRAGAppOutputs]): + async def _generate_outputs( + self, + helm_values: dict[str, t.Any], + app_instance_id: str, + ) -> LightRAGAppOutputs: + outputs = await _generate_lightrag_outputs(helm_values, app_instance_id) + logger.info("Got outputs: %s", outputs) + return outputs + + +__all__ = ["LightRAGOutputsProcessor"] diff --git a/.apolo/src/apolo_apps_lightrag/schemas/LightRAGAppInputs.json b/.apolo/src/apolo_apps_lightrag/schemas/LightRAGAppInputs.json new file mode 100644 index 00000000..ed4120e4 --- /dev/null +++ b/.apolo/src/apolo_apps_lightrag/schemas/LightRAGAppInputs.json @@ -0,0 +1,1292 @@ +{ + "$defs": { + "AnthropicLLMProvider": { + "description": "Anthropic LLM provider configuration.", + "properties": { + "host": { + "default": "api.anthropic.com", + "title": "Host", + "type": "string", + "x-description": "Anthropic API host", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Host" + }, + "port": { + "default": 443, + "title": "Port", + "type": "integer", + "x-description": "Set the port.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Port" + }, + "protocol": { + "const": "https", + "default": "https", + "title": "Protocol", + "type": "string" + }, + "timeout": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "default": 60, + "title": "Timeout", + "x-description": "Set the connection timeout in seconds.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Timeout" + }, + "base_path": { + "default": "/v1", + "title": "Base Path", + "type": "string" + }, + "api_type": { + "const": "rest", + "default": "rest", + "title": "Api Type", + "type": "string" + }, + "provider": { + "const": "anthropic", + "default": "anthropic", + "title": "Provider", + "type": "string" + }, + "model": { + "default": "claude-3-5-sonnet-20241022", + "title": "Model", + "type": "string", + "x-description": "Anthropic Claude model name.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Model" + }, + "api_key": { + "default": "", + "title": "Api Key", + "type": "string", + "x-description": "Anthropic API key.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "API Key" + } + }, + "title": "AnthropicLLMProvider", + "type": "object", + "x-description": "Anthropic Claude API configuration.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Anthropic LLM Provider", + "x-type": "AnthropicLLMProvider" + }, + "ApoloAuth": { + "properties": { + "type": { + "const": "apolo_auth", + "default": "apolo_auth", + "description": "Authentication type identifier", + "title": "Type", + "type": "string" + } + }, + "title": "ApoloAuth", + "type": "object", + "x-description": "Use Apolo platform's built-in authentication and authorization. Requires authenticated user credentials with appropriate permissions.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Apolo Platform Authentication", + "x-type": "ApoloAuth" + }, + "ApoloFilesPath": { + "properties": { + "path": { + "title": "Path", + "type": "string", + "x-description": "Provide the Apolo Storage path starting with `storage:` to locate your files.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Storage Path" + } + }, + "required": [ + "path" + ], + "title": "ApoloFilesPath", + "type": "object", + "x-description": "Specify the path within the Apolo Files application to read from or write to.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Apolo Files Path", + "x-type": "ApoloFilesFile" + }, + "ApoloSecret": { + "properties": { + "key": { + "title": "Key", + "type": "string" + } + }, + "required": [ + "key" + ], + "title": "ApoloSecret", + "type": "object", + "x-description": "Apolo Secret Configuration.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Secret", + "x-type": "ApoloSecret" + }, + "AuthIngressMiddleware": { + "properties": { + "name": { + "pattern": "^platform", + "title": "Name", + "type": "string", + "x-description": "Name of the authentication middleware (with namespace) to apply to ingress traffic.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Middleware Name" + } + }, + "required": [ + "name" + ], + "title": "AuthIngressMiddleware", + "type": "object", + "x-description": "Configure authentication middleware for ingress traffic.", + "x-is-advanced-field": false, + "x-meta-type": "integration", + "x-title": "Authentication Ingress Middleware", + "x-type": "AuthIngressMiddleware" + }, + "CrunchyPostgresUserCredentials": { + "properties": { + "user": { + "title": "User", + "type": "string", + "x-description": "Username for the Postgres user.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Postgres User" + }, + "password": { + "title": "Password", + "type": "string", + "x-description": "Password for the Postgres user.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Postgres Password" + }, + "host": { + "title": "Host", + "type": "string", + "x-description": "Host of the Postgres instance.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Postgres Host" + }, + "port": { + "exclusiveMinimum": 0, + "title": "Port", + "type": "integer", + "x-description": "Port of the Postgres instance.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Postgres Port" + }, + "pgbouncer_host": { + "title": "Pgbouncer Host", + "type": "string", + "x-description": "Host of the PGBouncer instance.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "PGBouncer Host" + }, + "pgbouncer_port": { + "exclusiveMinimum": 0, + "title": "Pgbouncer Port", + "type": "integer", + "x-description": "Port of the PGBouncer instance.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "PGBouncer Port" + }, + "dbname": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Dbname" + }, + "jdbc_uri": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Jdbc Uri" + }, + "pgbouncer_jdbc_uri": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Pgbouncer Jdbc Uri" + }, + "pgbouncer_uri": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Pgbouncer Uri" + }, + "uri": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "title": "Uri" + }, + "postgres_uri": { + "anyOf": [ + { + "$ref": "#/$defs/PostgresURI" + }, + { + "type": "null" + } + ], + "default": null + }, + "user_type": { + "const": "user", + "default": "user", + "title": "User Type", + "type": "string" + } + }, + "required": [ + "user", + "password", + "host", + "port", + "pgbouncer_host", + "pgbouncer_port" + ], + "title": "CrunchyPostgresUserCredentials", + "type": "object", + "x-description": "Configuration for Crunchy Postgres user credentials.", + "x-is-advanced-field": false, + "x-meta-type": "integration", + "x-title": "Postgres User Credentials", + "x-type": "CrunchyPostgresUserCredentials" + }, + "CustomAuth": { + "properties": { + "type": { + "const": "custom_auth", + "default": "custom_auth", + "description": "Authentication type identifier", + "title": "Type", + "type": "string" + }, + "middleware": { + "$ref": "#/$defs/AuthIngressMiddleware", + "x-description": "Custom authentication middleware configuration.", + "x-title": "Authentication Middleware" + } + }, + "required": [ + "middleware" + ], + "title": "CustomAuth", + "type": "object", + "x-description": "Use a custom authentication middleware for this ingress. Allows integration with custom authentication providers.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Custom Authentication", + "x-type": "CustomAuth" + }, + "GeminiLLMProvider": { + "description": "Google Gemini LLM provider configuration.", + "properties": { + "host": { + "default": "generativelanguage.googleapis.com", + "title": "Host", + "type": "string", + "x-description": "Google AI API host", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Host" + }, + "port": { + "default": 443, + "title": "Port", + "type": "integer", + "x-description": "Set the port.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Port" + }, + "protocol": { + "const": "https", + "default": "https", + "title": "Protocol", + "type": "string" + }, + "timeout": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "default": 60, + "title": "Timeout", + "x-description": "Configure connection timeout in seconds.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Timeout" + }, + "base_path": { + "default": "/v1", + "title": "Base Path", + "type": "string" + }, + "api_type": { + "const": "rest", + "default": "rest", + "title": "Api Type", + "type": "string" + }, + "provider": { + "const": "gemini", + "default": "gemini", + "title": "Provider", + "type": "string" + }, + "model": { + "default": "gemini-1.5-flash", + "title": "Model", + "type": "string", + "x-description": "Google Gemini model name.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Model" + }, + "api_key": { + "default": "", + "title": "Api Key", + "type": "string", + "x-description": "Google AI API key.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "API Key" + } + }, + "title": "GeminiLLMProvider", + "type": "object", + "x-description": "Google Gemini API configuration.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Gemini LLM Provider", + "x-type": "GeminiLLMProvider" + }, + "HuggingFaceCache": { + "properties": { + "files_path": { + "$ref": "#/$defs/ApoloFilesPath", + "default": { + "path": "storage:.apps/hugging-face-cache", + "__type__": "ApoloFilesPath" + }, + "x-description": "The path to the Apolo Files directory where Hugging Face artifacts are cached.", + "x-title": "Files Path" + } + }, + "title": "HuggingFaceCache", + "type": "object", + "x-description": "Configuration for the Hugging Face cache.", + "x-is-advanced-field": false, + "x-meta-type": "integration", + "x-title": "Hugging Face Cache", + "x-type": "HuggingFaceCache" + }, + "HuggingFaceModel": { + "properties": { + "model_hf_name": { + "title": "Model Hf Name", + "type": "string", + "x-description": "The name of the Hugging Face model.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Hugging Face Model Name" + }, + "hf_token": { + "anyOf": [ + { + "$ref": "#/$defs/HuggingFaceToken" + }, + { + "type": "null" + } + ], + "default": null, + "x-description": "Provide a Hugging Face API token linked to an account with access to the model specified above. This token will be used to download model files from the Hugging Face Hub, including gated or private repositories where applicable.", + "x-is-advanced-field": false, + "x-meta-type": "integration", + "x-title": "Hugging Face Token" + }, + "hf_cache": { + "anyOf": [ + { + "$ref": "#/$defs/HuggingFaceCache" + }, + { + "type": "null" + } + ], + "default": null, + "x-description": "Enables caching of model files to reduce redundant downloads and speed up load times.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Model Cache" + } + }, + "required": [ + "model_hf_name" + ], + "title": "HuggingFaceModel", + "type": "object", + "x-description": "Configure the Hugging Face model. Ensure it is available on the Hugging Face Hub and provide an API token with access rights if the repository is gated.", + "x-is-advanced-field": false, + "x-meta-type": "integration", + "x-title": "Hugging Face Model", + "x-type": "HuggingFaceModel" + }, + "HuggingFaceToken": { + "properties": { + "token_name": { + "minLength": 0, + "title": "Token Name", + "type": "string", + "x-description": "The name of the Hugging Face token.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Token Name" + }, + "token": { + "$ref": "#/$defs/ApoloSecret", + "x-description": "The Hugging Face API token used to access models.", + "x-title": "Hugging Face Token" + } + }, + "required": [ + "token_name", + "token" + ], + "title": "HuggingFaceToken", + "type": "object", + "x-description": "Provide a Hugging Face API token linked to an account with access to the model specified above. This token will be used to download model files from the Hugging Face Hub, including gated or private repositories where applicable.", + "x-is-advanced-field": false, + "x-meta-type": "integration", + "x-title": "Hugging Face Token", + "x-type": "HuggingFaceToken" + }, + "IngressHttp": { + "properties": { + "auth": { + "anyOf": [ + { + "$ref": "#/$defs/ApoloAuth" + }, + { + "$ref": "#/$defs/NoAuth" + }, + { + "$ref": "#/$defs/CustomAuth" + } + ], + "title": "Auth", + "x-description": "Configure authentication for this ingress. Choose Apolo platform authentication, custom middleware, or no authentication.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Authentication" + } + }, + "title": "IngressHttp", + "type": "object", + "x-description": "Enable access to your application over the internet using HTTPS.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Enable HTTP Ingress", + "x-type": "IngressHttp" + }, + "LightRAGPersistence": { + "properties": { + "rag_storage_size": { + "default": 10, + "exclusiveMinimum": 0, + "title": "Rag Storage Size", + "type": "integer", + "x-description": "Size of the persistent volume for RAG data storage.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "RAG Storage Size (GB)" + }, + "inputs_storage_size": { + "default": 5, + "exclusiveMinimum": 0, + "title": "Inputs Storage Size", + "type": "integer", + "x-description": "Size of the persistent volume for input files.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Inputs Storage Size (GB)" + } + }, + "title": "LightRAGPersistence", + "type": "object", + "x-description": "Configure persistent storage for LightRAG data and inputs.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "LightRAG Persistence" + }, + "NoAuth": { + "properties": { + "type": { + "const": "no_auth", + "default": "no_auth", + "description": "Authentication type identifier", + "title": "Type", + "type": "string" + } + }, + "title": "NoAuth", + "type": "object", + "x-description": "Disable authentication for this ingress. The application will be publicly accessible without any authentication.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "No Authentication", + "x-type": "NoAuth" + }, + "OllamaEmbeddingProvider": { + "description": "Ollama embedding provider configuration.", + "properties": { + "host": { + "title": "Host", + "type": "string", + "x-description": "Ollama server host.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Host" + }, + "port": { + "default": 11434, + "title": "Port", + "type": "integer", + "x-description": "Ollama server port.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Port" + }, + "protocol": { + "default": "http", + "enum": [ + "http", + "https" + ], + "title": "Protocol", + "type": "string", + "x-description": "Ollama server protocol.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Protocol" + }, + "timeout": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "default": 300, + "title": "Timeout", + "x-description": "Configure connection timeout in seconds.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Timeout" + }, + "base_path": { + "default": "/api", + "title": "Base Path", + "type": "string" + }, + "api_type": { + "const": "rest", + "default": "rest", + "title": "Api Type", + "type": "string" + }, + "provider": { + "const": "ollama", + "default": "ollama", + "title": "Provider", + "type": "string" + }, + "model": { + "default": "nomic-embed-text", + "title": "Model", + "type": "string", + "x-description": "Ollama embedding model name.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Model" + } + }, + "required": [ + "host" + ], + "title": "OllamaEmbeddingProvider", + "type": "object", + "x-description": "Ollama local embedding model configuration.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Ollama Embedding Provider", + "x-type": "OllamaEmbeddingProvider" + }, + "OllamaLLMProvider": { + "description": "Ollama LLM provider configuration.", + "properties": { + "host": { + "title": "Host", + "type": "string", + "x-description": "Ollama server host.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Host" + }, + "port": { + "default": 11434, + "title": "Port", + "type": "integer", + "x-description": "Ollama server port.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Port" + }, + "protocol": { + "default": "http", + "enum": [ + "http", + "https" + ], + "title": "Protocol", + "type": "string", + "x-description": "Ollama server protocol.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Protocol" + }, + "timeout": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "default": 300, + "title": "Timeout", + "x-description": "Configure connection timeout in seconds.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Timeout" + }, + "base_path": { + "default": "/api", + "title": "Base Path", + "type": "string" + }, + "api_type": { + "const": "rest", + "default": "rest", + "title": "Api Type", + "type": "string" + }, + "provider": { + "const": "ollama", + "default": "ollama", + "title": "Provider", + "type": "string" + }, + "model": { + "default": "llama3.1:8b-instruct-q4_0", + "title": "Model", + "type": "string", + "x-description": "Ollama model name.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Model" + } + }, + "required": [ + "host" + ], + "title": "OllamaLLMProvider", + "type": "object", + "x-description": "Configuration for a self-hosted Ollama server.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Ollama LLM Provider", + "x-type": "OllamaLLMProvider" + }, + "OpenAICompatChatAPI": { + "properties": { + "host": { + "title": "Host", + "type": "string", + "x-description": "The hostname of the HTTP endpoint.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Hostname" + }, + "port": { + "default": 80, + "exclusiveMinimum": 0, + "title": "Port", + "type": "integer", + "x-description": "The port of the HTTP endpoint.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Port" + }, + "protocol": { + "default": "http", + "title": "Protocol", + "type": "string", + "x-description": "The protocol to use, e.g., http or https.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Protocol" + }, + "timeout": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "default": 30.0, + "title": "Timeout", + "x-description": "Connection timeout in seconds.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Connection Timeout" + }, + "base_path": { + "default": "/", + "title": "Base Path", + "type": "string" + }, + "api_type": { + "const": "rest", + "default": "rest", + "title": "Api Type", + "type": "string" + }, + "api_base_path": { + "default": "/v1", + "title": "Api Base Path", + "type": "string" + }, + "openai_api_type": { + "const": "chat", + "default": "chat", + "title": "Openai Api Type", + "type": "string" + }, + "endpoint_url": { + "const": "/v1/chat", + "default": "/v1/chat", + "title": "Endpoint Url", + "type": "string" + }, + "hf_model": { + "anyOf": [ + { + "$ref": "#/$defs/HuggingFaceModel" + }, + { + "type": "null" + } + ], + "default": null, + "x-description": "Configure the Hugging Face model. Ensure it is available on the Hugging Face Hub and provide an API token with access rights if the repository is gated.", + "x-is-advanced-field": false, + "x-meta-type": "integration", + "x-title": "Hugging Face Model" + } + }, + "required": [ + "host" + ], + "title": "OpenAICompatChatAPI", + "type": "object", + "x-description": "Configuration for OpenAI compatible chat API.", + "x-is-advanced-field": false, + "x-meta-type": "integration", + "x-title": "OpenAI Compatible Chat API", + "x-type": "OpenAICompatChatAPI" + }, + "OpenAICompatEmbeddingsAPI": { + "properties": { + "host": { + "title": "Host", + "type": "string", + "x-description": "The hostname of the HTTP endpoint.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Hostname" + }, + "port": { + "default": 80, + "exclusiveMinimum": 0, + "title": "Port", + "type": "integer", + "x-description": "The port of the HTTP endpoint.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Port" + }, + "protocol": { + "default": "http", + "title": "Protocol", + "type": "string", + "x-description": "The protocol to use, e.g., http or https.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Protocol" + }, + "timeout": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "default": 30.0, + "title": "Timeout", + "x-description": "Connection timeout in seconds.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Connection Timeout" + }, + "base_path": { + "default": "/", + "title": "Base Path", + "type": "string" + }, + "api_type": { + "const": "rest", + "default": "rest", + "title": "Api Type", + "type": "string" + }, + "api_base_path": { + "default": "/v1", + "title": "Api Base Path", + "type": "string" + }, + "openai_api_type": { + "const": "embeddings", + "default": "embeddings", + "title": "Openai Api Type", + "type": "string" + }, + "endpoint_url": { + "const": "/v1/embeddings", + "default": "/v1/embeddings", + "title": "Endpoint Url", + "type": "string" + }, + "hf_model": { + "anyOf": [ + { + "$ref": "#/$defs/HuggingFaceModel" + }, + { + "type": "null" + } + ], + "default": null, + "x-description": "Configure the Hugging Face model. Ensure it is available on the Hugging Face Hub and provide an API token with access rights if the repository is gated.", + "x-is-advanced-field": false, + "x-meta-type": "integration", + "x-title": "Hugging Face Model" + } + }, + "required": [ + "host" + ], + "title": "OpenAICompatEmbeddingsAPI", + "type": "object", + "x-description": "Configuration for OpenAI compatible embeddings API.", + "x-is-advanced-field": false, + "x-meta-type": "integration", + "x-title": "OpenAI Compatible Embeddings API", + "x-type": "OpenAICompatEmbeddingsAPI" + }, + "OpenAIEmbeddingProvider": { + "description": "OpenAI embedding provider configuration.", + "properties": { + "host": { + "default": "api.openai.com", + "title": "Host", + "type": "string", + "x-description": "OpenAI API host", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Host" + }, + "port": { + "default": 443, + "title": "Port", + "type": "integer", + "x-description": "Set the port.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Port" + }, + "protocol": { + "const": "https", + "default": "https", + "title": "Protocol", + "type": "string" + }, + "timeout": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "default": 60, + "title": "Timeout", + "x-description": "Set the connection timeout in seconds.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Timeout" + }, + "base_path": { + "default": "/v1", + "title": "Base Path", + "type": "string" + }, + "api_type": { + "const": "rest", + "default": "rest", + "title": "Api Type", + "type": "string" + }, + "provider": { + "const": "openai", + "default": "openai", + "title": "Provider", + "type": "string" + }, + "model": { + "default": "text-embedding-ada-002", + "title": "Model", + "type": "string", + "x-description": "Embedding model name.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Model" + }, + "api_key": { + "default": "", + "title": "Api Key", + "type": "string", + "x-description": "OpenAI API key.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "API Key" + } + }, + "title": "OpenAIEmbeddingProvider", + "type": "object", + "x-description": "OpenAI embeddings API configuration.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "OpenAI Embedding Provider", + "x-type": "OpenAIEmbeddingProvider" + }, + "OpenAILLMProvider": { + "description": "OpenAI LLM provider configuration.", + "properties": { + "host": { + "default": "api.openai.com", + "title": "Host", + "type": "string", + "x-description": "OpenAI API host", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Host" + }, + "port": { + "default": 443, + "title": "Port", + "type": "integer", + "x-description": "Set the port.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Port" + }, + "protocol": { + "const": "https", + "default": "https", + "title": "Protocol", + "type": "string" + }, + "timeout": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "default": 60, + "title": "Timeout", + "x-description": "Set the connection timeout in seconds.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Timeout" + }, + "base_path": { + "default": "/v1", + "title": "Base Path", + "type": "string" + }, + "api_type": { + "const": "rest", + "default": "rest", + "title": "Api Type", + "type": "string" + }, + "provider": { + "const": "openai", + "default": "openai", + "title": "Provider", + "type": "string" + }, + "model": { + "default": "gpt-4o-mini", + "title": "Model", + "type": "string", + "x-description": "Chat completion model name.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Model" + }, + "api_key": { + "default": "", + "title": "Api Key", + "type": "string", + "x-description": "OpenAI API key.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "API Key" + } + }, + "title": "OpenAILLMProvider", + "type": "object", + "x-description": "OpenAI chat completion API configuration.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "OpenAI LLM Provider", + "x-type": "OpenAILLMProvider" + }, + "PostgresURI": { + "description": "Configuration for the Postgres connection URI.", + "properties": { + "uri": { + "title": "Uri", + "type": "string", + "x-description": "Specify full Postgres connection URI. E.g. 'postgresql://user:pass@host:5432/db'", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "URI" + } + }, + "required": [ + "uri" + ], + "title": "PostgresURI", + "type": "object", + "x-description": "Full Postgres connection URI configuration.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Postgres URI", + "x-type": "PostgresURI" + }, + "Preset": { + "properties": { + "name": { + "title": "Name", + "type": "string", + "x-description": "The name of the preset.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Resource Preset" + } + }, + "required": [ + "name" + ], + "title": "Preset", + "type": "object", + "x-description": "Select the resource preset used per service replica.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Resource Preset", + "x-type": "Preset" + } + }, + "properties": { + "preset": { + "$ref": "#/$defs/Preset" + }, + "ingress_http": { + "$ref": "#/$defs/IngressHttp" + }, + "pgvector_user": { + "$ref": "#/$defs/CrunchyPostgresUserCredentials" + }, + "llm_config": { + "anyOf": [ + { + "$ref": "#/$defs/OpenAICompatChatAPI" + }, + { + "$ref": "#/$defs/OpenAILLMProvider" + }, + { + "$ref": "#/$defs/AnthropicLLMProvider" + }, + { + "$ref": "#/$defs/OllamaLLMProvider" + }, + { + "$ref": "#/$defs/GeminiLLMProvider" + } + ], + "default": { + "host": "", + "port": 443, + "protocol": "https", + "timeout": 30.0, + "base_path": "/", + "api_type": "rest", + "api_base_path": "/v1", + "openai_api_type": "chat", + "endpoint_url": "/v1/chat", + "hf_model": null, + "__type__": "OpenAICompatChatAPI" + }, + "title": "Llm Config", + "x-description": "LLM provider configuration.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "LLM Configuration" + }, + "embedding_config": { + "anyOf": [ + { + "$ref": "#/$defs/OpenAICompatEmbeddingsAPI" + }, + { + "$ref": "#/$defs/OpenAIEmbeddingProvider" + }, + { + "$ref": "#/$defs/OllamaEmbeddingProvider" + } + ], + "default": { + "host": "", + "port": 443, + "protocol": "https", + "timeout": 30.0, + "base_path": "/", + "api_type": "rest", + "api_base_path": "/v1", + "openai_api_type": "embeddings", + "endpoint_url": "/v1/embeddings", + "hf_model": null, + "__type__": "OpenAICompatEmbeddingsAPI" + }, + "title": "Embedding Config", + "x-description": "Embedding provider configuration.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Embedding Configuration" + }, + "persistence": { + "$ref": "#/$defs/LightRAGPersistence", + "x-title": "Persistence Configuration" + } + }, + "required": [ + "preset", + "ingress_http", + "pgvector_user" + ], + "title": "LightRAGAppInputs", + "type": "object" +} diff --git a/.apolo/src/apolo_apps_lightrag/schemas/LightRAGAppOutputs.json b/.apolo/src/apolo_apps_lightrag/schemas/LightRAGAppOutputs.json new file mode 100644 index 00000000..b5130b05 --- /dev/null +++ b/.apolo/src/apolo_apps_lightrag/schemas/LightRAGAppOutputs.json @@ -0,0 +1,245 @@ +{ + "$defs": { + "HttpApi": { + "properties": { + "host": { + "title": "Host", + "type": "string", + "x-description": "The hostname of the HTTP endpoint.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Hostname" + }, + "port": { + "default": 80, + "exclusiveMinimum": 0, + "title": "Port", + "type": "integer", + "x-description": "The port of the HTTP endpoint.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Port" + }, + "protocol": { + "default": "http", + "title": "Protocol", + "type": "string", + "x-description": "The protocol to use, e.g., http or https.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Protocol" + }, + "timeout": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "default": 30.0, + "title": "Timeout", + "x-description": "Connection timeout in seconds.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Connection Timeout" + }, + "base_path": { + "default": "/", + "title": "Base Path", + "type": "string" + } + }, + "required": [ + "host" + ], + "title": "HttpApi", + "type": "object", + "x-description": "HTTP API Configuration.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "HTTP API", + "x-type": "OpenAICompatibleEmbeddingsRestAPI" + }, + "ServiceAPI_HttpApi_": { + "properties": { + "internal_url": { + "anyOf": [ + { + "$ref": "#/$defs/HttpApi" + }, + { + "type": "null" + } + ], + "default": null, + "x-description": "Internal URL to access the service. This route is not protected by platform authorization and only workloads from the same project can access it.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Internal URL" + }, + "external_url": { + "anyOf": [ + { + "$ref": "#/$defs/HttpApi" + }, + { + "type": "null" + } + ], + "default": null, + "x-description": "External URL for accessing the service from outside the cluster. This route might be secured by platform authorization and is accessible from any network with a valid platform authorization token that has appropriate permissions.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "External URL" + } + }, + "title": "ServiceAPI[HttpApi]", + "type": "object", + "x-description": "Service APIs URLs.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Service APIs", + "x-type": "ServiceAPI[GrpcAPI]" + }, + "ServiceAPI_WebApp_": { + "properties": { + "internal_url": { + "anyOf": [ + { + "$ref": "#/$defs/WebApp" + }, + { + "type": "null" + } + ], + "default": null, + "x-description": "Internal URL to access the service. This route is not protected by platform authorization and only workloads from the same project can access it.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Internal URL" + }, + "external_url": { + "anyOf": [ + { + "$ref": "#/$defs/WebApp" + }, + { + "type": "null" + } + ], + "default": null, + "x-description": "External URL for accessing the service from outside the cluster. This route might be secured by platform authorization and is accessible from any network with a valid platform authorization token that has appropriate permissions.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "External URL" + } + }, + "title": "ServiceAPI[WebApp]", + "type": "object", + "x-description": "Service APIs URLs.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Service APIs", + "x-type": "ServiceAPI[GrpcAPI]" + }, + "WebApp": { + "properties": { + "host": { + "title": "Host", + "type": "string", + "x-description": "The hostname of the HTTP endpoint.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Hostname" + }, + "port": { + "default": 80, + "exclusiveMinimum": 0, + "title": "Port", + "type": "integer", + "x-description": "The port of the HTTP endpoint.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Port" + }, + "protocol": { + "default": "http", + "title": "Protocol", + "type": "string", + "x-description": "The protocol to use, e.g., http or https.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Protocol" + }, + "timeout": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "default": 30.0, + "title": "Timeout", + "x-description": "Connection timeout in seconds.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "Connection Timeout" + }, + "base_path": { + "default": "/", + "title": "Base Path", + "type": "string" + }, + "api_type": { + "const": "webapp", + "default": "webapp", + "title": "Api Type", + "type": "string" + } + }, + "required": [ + "host" + ], + "title": "WebApp", + "type": "object", + "x-description": "HTTP API Configuration.", + "x-is-advanced-field": false, + "x-meta-type": "inline", + "x-title": "HTTP API", + "x-type": "OpenAICompatibleEmbeddingsRestAPI" + } + }, + "description": "LightRAG outputs.", + "properties": { + "app_url": { + "anyOf": [ + { + "$ref": "#/$defs/ServiceAPI_WebApp_" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The main application URL for accessing the service. This is the primary endpoint users should use to access the application.", + "title": "Application URL" + }, + "server_url": { + "anyOf": [ + { + "$ref": "#/$defs/ServiceAPI_HttpApi_" + }, + { + "type": "null" + } + ], + "default": null + } + }, + "title": "LightRAGAppOutputs", + "type": "object" +} diff --git a/.apolo/src/apolo_apps_lightrag/types.py b/.apolo/src/apolo_apps_lightrag/types.py new file mode 100644 index 00000000..2b4c08fc --- /dev/null +++ b/.apolo/src/apolo_apps_lightrag/types.py @@ -0,0 +1,426 @@ +from typing import Literal + +from pydantic import BaseModel, ConfigDict, Field, field_validator + +from apolo_app_types import AppInputs, AppOutputs +from apolo_app_types.protocols.common import ( + IngressHttp, + Preset, + SchemaExtraMetadata, + SchemaMetaType, +) +from apolo_app_types.protocols.common.networking import HttpApi, RestAPI, ServiceAPI +from apolo_app_types.protocols.common.openai_compat import ( + OpenAICompatChatAPI, + OpenAICompatEmbeddingsAPI, +) +from apolo_app_types.protocols.postgres import CrunchyPostgresUserCredentials + + +class LightRAGPersistence(BaseModel): + model_config = ConfigDict( + protected_namespaces=(), + json_schema_extra=SchemaExtraMetadata( + title="LightRAG Persistence", + description="Configure persistent storage for LightRAG data and inputs.", + ).as_json_schema_extra(), + ) + + rag_storage_size: int = Field( + default=10, + gt=0, + json_schema_extra=SchemaExtraMetadata( + title="RAG Storage Size (GB)", + description="Size of the persistent volume for RAG data storage.", + ).as_json_schema_extra(), + ) + inputs_storage_size: int = Field( + default=5, + gt=0, + json_schema_extra=SchemaExtraMetadata( + title="Inputs Storage Size (GB)", + description="Size of the persistent volume for input files.", + ).as_json_schema_extra(), + ) + + @field_validator("rag_storage_size", "inputs_storage_size", mode="before") + @classmethod + def validate_storage_size(cls, value: int) -> int: + if value and isinstance(value, int) and value < 1: + error_message = "Storage size must be greater than 1GB." + raise ValueError(error_message) + return value + + +class OpenAILLMProvider(RestAPI): + """OpenAI LLM provider configuration.""" + + model_config = ConfigDict( + protected_namespaces=(), + json_schema_extra=SchemaExtraMetadata( + title="OpenAI LLM Provider", + description="OpenAI chat completion API configuration.", + meta_type=SchemaMetaType.INLINE, + ).as_json_schema_extra(), + ) + + host: str = Field( + default="api.openai.com", + json_schema_extra=SchemaExtraMetadata( + title="Host", + description="OpenAI API host", + ).as_json_schema_extra(), + ) + port: int = Field( + default=443, + json_schema_extra=SchemaExtraMetadata( + title="Port", + description="Set the port.", + ).as_json_schema_extra(), + ) + protocol: Literal["https"] = "https" + timeout: int | None = Field( + default=60, + json_schema_extra=SchemaExtraMetadata( + title="Timeout", + description="Set the connection timeout in seconds.", + ).as_json_schema_extra(), + ) + base_path: str = "/v1" + provider: Literal["openai"] = "openai" + model: str = Field( + default="gpt-4o-mini", + json_schema_extra=SchemaExtraMetadata( + title="Model", + description="Chat completion model name.", + ).as_json_schema_extra(), + ) + api_key: str = Field( + default="", + json_schema_extra=SchemaExtraMetadata( + title="API Key", + description="OpenAI API key.", + ).as_json_schema_extra(), + ) + + +class AnthropicLLMProvider(RestAPI): + """Anthropic LLM provider configuration.""" + + model_config = ConfigDict( + protected_namespaces=(), + json_schema_extra=SchemaExtraMetadata( + title="Anthropic LLM Provider", + description="Anthropic Claude API configuration.", + meta_type=SchemaMetaType.INLINE, + ).as_json_schema_extra(), + ) + + host: str = Field( + default="api.anthropic.com", + json_schema_extra=SchemaExtraMetadata( + title="Host", + description="Anthropic API host", + ).as_json_schema_extra(), + ) + port: int = Field( + default=443, + json_schema_extra=SchemaExtraMetadata( + title="Port", + description="Set the port.", + ).as_json_schema_extra(), + ) + protocol: Literal["https"] = "https" + timeout: int | None = Field( + default=60, + json_schema_extra=SchemaExtraMetadata( + title="Timeout", + description="Set the connection timeout in seconds.", + ).as_json_schema_extra(), + ) + base_path: str = "/v1" + provider: Literal["anthropic"] = "anthropic" + model: str = Field( + default="claude-3-5-sonnet-20241022", + json_schema_extra=SchemaExtraMetadata( + title="Model", + description="Anthropic Claude model name.", + ).as_json_schema_extra(), + ) + api_key: str = Field( + default="", + json_schema_extra=SchemaExtraMetadata( + title="API Key", + description="Anthropic API key.", + ).as_json_schema_extra(), + ) + + +class OllamaLLMProvider(RestAPI): + """Ollama LLM provider configuration.""" + + model_config = ConfigDict( + protected_namespaces=(), + json_schema_extra=SchemaExtraMetadata( + title="Ollama LLM Provider", + description="Configuration for a self-hosted Ollama server.", + meta_type=SchemaMetaType.INLINE, + ).as_json_schema_extra(), + ) + + host: str = Field( + json_schema_extra=SchemaExtraMetadata( + title="Host", + description="Ollama server host.", + ).as_json_schema_extra(), + ) + port: int = Field( + default=11434, + json_schema_extra=SchemaExtraMetadata( + title="Port", + description="Ollama server port.", + ).as_json_schema_extra(), + ) + protocol: Literal["http", "https"] = Field( + default="http", + json_schema_extra=SchemaExtraMetadata( + title="Protocol", + description="Ollama server protocol.", + ).as_json_schema_extra(), + ) + timeout: int | None = Field( + default=300, + json_schema_extra=SchemaExtraMetadata( + title="Timeout", + description="Configure connection timeout in seconds.", + ).as_json_schema_extra(), + ) + base_path: str = "/api" + provider: Literal["ollama"] = "ollama" + model: str = Field( + default="llama3.1:8b-instruct-q4_0", + json_schema_extra=SchemaExtraMetadata( + title="Model", + description="Ollama model name.", + ).as_json_schema_extra(), + ) + + +class GeminiLLMProvider(RestAPI): + """Google Gemini LLM provider configuration.""" + + model_config = ConfigDict( + protected_namespaces=(), + json_schema_extra=SchemaExtraMetadata( + title="Gemini LLM Provider", + description="Google Gemini API configuration.", + meta_type=SchemaMetaType.INLINE, + ).as_json_schema_extra(), + ) + + host: str = Field( + default="generativelanguage.googleapis.com", + json_schema_extra=SchemaExtraMetadata( + title="Host", + description="Google AI API host", + ).as_json_schema_extra(), + ) + port: int = Field( + default=443, + json_schema_extra=SchemaExtraMetadata( + title="Port", + description="Set the port.", + ).as_json_schema_extra(), + ) + protocol: Literal["https"] = "https" + timeout: int | None = Field( + default=60, + json_schema_extra=SchemaExtraMetadata( + title="Timeout", + description="Configure connection timeout in seconds.", + ).as_json_schema_extra(), + ) + base_path: str = "/v1" + provider: Literal["gemini"] = "gemini" + model: str = Field( + default="gemini-1.5-flash", + json_schema_extra=SchemaExtraMetadata( + title="Model", + description="Google Gemini model name.", + ).as_json_schema_extra(), + ) + api_key: str = Field( + default="", + json_schema_extra=SchemaExtraMetadata( + title="API Key", + description="Google AI API key.", + ).as_json_schema_extra(), + ) + + +LLMProvider = ( + OpenAICompatChatAPI + | OpenAILLMProvider + | AnthropicLLMProvider + | OllamaLLMProvider + | GeminiLLMProvider +) + + +class OpenAIEmbeddingProvider(RestAPI): + """OpenAI embedding provider configuration.""" + + model_config = ConfigDict( + protected_namespaces=(), + json_schema_extra=SchemaExtraMetadata( + title="OpenAI Embedding Provider", + description="OpenAI embeddings API configuration.", + meta_type=SchemaMetaType.INLINE, + ).as_json_schema_extra(), + ) + + host: str = Field( + default="api.openai.com", + json_schema_extra=SchemaExtraMetadata( + title="Host", + description="OpenAI API host", + ).as_json_schema_extra(), + ) + port: int = Field( + default=443, + json_schema_extra=SchemaExtraMetadata( + title="Port", + description="Set the port.", + ).as_json_schema_extra(), + ) + protocol: Literal["https"] = "https" + timeout: int | None = Field( + default=60, + json_schema_extra=SchemaExtraMetadata( + title="Timeout", + description="Set the connection timeout in seconds.", + ).as_json_schema_extra(), + ) + base_path: str = "/v1" + provider: Literal["openai"] = "openai" + model: str = Field( + default="text-embedding-ada-002", + json_schema_extra=SchemaExtraMetadata( + title="Model", + description="Embedding model name.", + ).as_json_schema_extra(), + ) + api_key: str = Field( + default="", + json_schema_extra=SchemaExtraMetadata( + title="API Key", + description="OpenAI API key.", + ).as_json_schema_extra(), + ) + + +class OllamaEmbeddingProvider(RestAPI): + """Ollama embedding provider configuration.""" + + model_config = ConfigDict( + protected_namespaces=(), + json_schema_extra=SchemaExtraMetadata( + title="Ollama Embedding Provider", + description="Ollama local embedding model configuration.", + meta_type=SchemaMetaType.INLINE, + ).as_json_schema_extra(), + ) + + host: str = Field( + json_schema_extra=SchemaExtraMetadata( + title="Host", + description="Ollama server host.", + ).as_json_schema_extra(), + ) + port: int = Field( + default=11434, + json_schema_extra=SchemaExtraMetadata( + title="Port", + description="Ollama server port.", + ).as_json_schema_extra(), + ) + protocol: Literal["http", "https"] = Field( + default="http", + json_schema_extra=SchemaExtraMetadata( + title="Protocol", + description="Ollama server protocol.", + ).as_json_schema_extra(), + ) + timeout: int | None = Field( + default=300, + json_schema_extra=SchemaExtraMetadata( + title="Timeout", + description="Configure connection timeout in seconds.", + ).as_json_schema_extra(), + ) + base_path: str = "/api" + provider: Literal["ollama"] = "ollama" + model: str = Field( + default="nomic-embed-text", + json_schema_extra=SchemaExtraMetadata( + title="Model", + description="Ollama embedding model name.", + ).as_json_schema_extra(), + ) + + +EmbeddingProvider = ( + OpenAICompatEmbeddingsAPI | OpenAIEmbeddingProvider | OllamaEmbeddingProvider +) + + +LightRAGLLMConfig = LLMProvider +LightRAGEmbeddingConfig = EmbeddingProvider + + +class LightRAGAppInputs(AppInputs): + preset: Preset + ingress_http: IngressHttp + pgvector_user: CrunchyPostgresUserCredentials + llm_config: LightRAGLLMConfig = Field( + default=OpenAICompatChatAPI(host="", port=443, protocol="https"), + json_schema_extra=SchemaExtraMetadata( + title="LLM Configuration", + description="LLM provider configuration.", + ).as_json_schema_extra(), + ) + embedding_config: LightRAGEmbeddingConfig = Field( + default=OpenAICompatEmbeddingsAPI(host="", port=443, protocol="https"), + json_schema_extra=SchemaExtraMetadata( + title="Embedding Configuration", + description="Embedding provider configuration.", + ).as_json_schema_extra(), + ) + persistence: LightRAGPersistence = Field( + default_factory=LightRAGPersistence, + json_schema_extra=SchemaExtraMetadata( + title="Persistence Configuration", + description="Configure persistent storage for LightRAG data and inputs.", + ).as_json_schema_extra(), + ) + + +class LightRAGAppOutputs(AppOutputs): + """LightRAG outputs.""" + + server_url: ServiceAPI[HttpApi] | None = None + + +__all__ = [ + "LightRAGAppInputs", + "LightRAGAppOutputs", + "LightRAGEmbeddingConfig", + "LightRAGLLMConfig", + "LightRAGPersistence", + "OpenAILLMProvider", + "AnthropicLLMProvider", + "OllamaLLMProvider", + "GeminiLLMProvider", + "OpenAIEmbeddingProvider", + "OllamaEmbeddingProvider", +] diff --git a/.apolo/tests/__init__.py b/.apolo/tests/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/.apolo/tests/conftest.py b/.apolo/tests/conftest.py new file mode 100644 index 00000000..7fc6a562 --- /dev/null +++ b/.apolo/tests/conftest.py @@ -0,0 +1,6 @@ +import pytest + +pytest_plugins = [ + "apolo_app_types_fixtures.apolo_clients", + "apolo_app_types_fixtures.constants", +] diff --git a/.apolo/tests/unit/__init__.py b/.apolo/tests/unit/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/.env.example b/.env.example index e9315aa9..f39b1ba2 100644 --- a/.env.example +++ b/.env.example @@ -23,7 +23,7 @@ LLM_BINDING_API_KEY=sk-your-openai-api-key-here # EMBEDDING_BINDING_HOST=https://api.openai.com/v1 # EMBEDDING_BINDING_API_KEY=sk-your-openai-api-key-here EMBEDDING_BINDING=openai -EMBEDDING_MODEL=gemini-embedding-001 +EMBEDDING_MODEL=gemini-embedding-001 EMBEDDING_DIM=3072 EMBEDDING_BINDING_HOST=https://generativelanguage.googleapis.com/v1beta/openai/ EMBEDDING_BINDING_API_KEY=AI-your-gemini-api-key-here diff --git a/.github/actionlint-matcher.json b/.github/actionlint-matcher.json new file mode 100644 index 00000000..4171e9ef --- /dev/null +++ b/.github/actionlint-matcher.json @@ -0,0 +1,17 @@ +{ + "problemMatcher": [ + { + "owner": "actionlint", + "pattern": [ + { + "code": 5, + "column": 3, + "file": 1, + "line": 2, + "message": 4, + "regexp": "^(?:\\x1b\\[\\d+m)?(.+?)(?:\\x1b\\[\\d+m)*:(?:\\x1b\\[\\d+m)*(\\d+)(?:\\x1b\\[\\d+m)*:(?:\\x1b\\[\\d+m)*(\\d+)(?:\\x1b\\[\\d+m)*: (?:\\x1b\\[\\d+m)*(.+?)(?:\\x1b\\[\\d+m)* \\[(.+?)\\]$" + } + ] + } + ] +} diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml new file mode 100644 index 00000000..312d1d88 --- /dev/null +++ b/.github/workflows/ci.yaml @@ -0,0 +1,106 @@ +name: CI + +on: + push: + branches: [master] + tags: ["v*"] + pull_request: + branches: [master] + schedule: + - cron: 0 4 * * * + +jobs: + test: + name: All checks are passed + uses: ./.github/workflows/test.yaml + secrets: inherit + + approve: + name: Approve bot PR + runs-on: ubuntu-latest + if: endsWith(github.actor, '[bot]') + needs: test + permissions: + contents: write + pull-requests: write + steps: + - name: Checkout + uses: actions/checkout@v4 + - name: metadata + id: metadata + if: github.actor == 'dependabot[bot]' + uses: dependabot/fetch-metadata@v2 + with: + github-token: ${{ secrets.GITHUB_TOKEN }} + - name: Enable auto-merge for bot PRs + run: gh pr merge --auto --squash --delete-branch "$PR_URL" + env: + PR_URL: ${{ github.event.pull_request.html_url }} + GH_TOKEN: ${{ secrets.GITHUB_TOKEN }} + + release-processor-image: + name: Release processor image + runs-on: ubuntu-latest + needs: test + if: github.event_name == 'push' && (startsWith(github.ref, 'refs/tags/v') || github.ref == 'refs/heads/master') + steps: + - name: Checkout commit + uses: actions/checkout@v4 + - name: Purge old artifacts + uses: kolpav/purge-artifacts-action@v1 + with: + token: ${{ github.token }} + expire-in: 30mins + - name: Login to ghcr.io + uses: docker/login-action@v3.5.0 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ github.token }} + - name: Release development image + run: | + make build-hook-image + - name: Release development image + run: | + export IMAGE_TAG=development + make push-hook-image + - name: Release prod image + if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') + run: | + export IMAGE_TAG=${GITHUB_REF#refs/tags/v} + make push-hook-image + + release-processor-image-pr: + name: Release processor image from PR + runs-on: ubuntu-latest + needs: test + if: github.event_name == 'pull_request' + steps: + - name: Checkout commit + uses: actions/checkout@v4 + - name: Purge old artifacts + uses: kolpav/purge-artifacts-action@v1 + with: + token: ${{ github.token }} + expire-in: 30mins + - name: Login to ghcr.io + uses: docker/login-action@v3.5.0 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ github.token }} + - name: Extract metadata (tags, labels) for Docker + id: meta + uses: docker/metadata-action@v5 + with: + images: ghcr.io/neuro-inc/app-lightrag + tags: | + type=ref,event=pr + - name: Build Docker image + run: make build-hook-image + - name: Push release for testing + if: github.actor != 'dependabot[bot]' + run: | + FULL_IMAGE_NAME=${{ steps.meta.outputs.tags }} + export IMAGE_TAG=${FULL_IMAGE_NAME##*:} + make push-hook-image diff --git a/.github/workflows/linting.yaml b/.github/workflows/linting.yaml index aa054369..b861301f 100644 --- a/.github/workflows/linting.yaml +++ b/.github/workflows/linting.yaml @@ -24,7 +24,7 @@ jobs: - name: Install dependencies run: | python -m pip install --upgrade pip - pip install pre-commit + pip install pre-commit apolo-app-types - name: Run pre-commit run: pre-commit run --all-files --show-diff-on-failure diff --git a/.github/workflows/test.yaml b/.github/workflows/test.yaml new file mode 100644 index 00000000..43b2c59d --- /dev/null +++ b/.github/workflows/test.yaml @@ -0,0 +1,74 @@ +on: + workflow_call: {} + +jobs: + lint: + name: Lint + runs-on: ubuntu-latest + steps: + - name: Checkout commit + uses: actions/checkout@v4 + - name: Install python + uses: actions/setup-python@v5 + with: + python-version: 3.12 + - name: Cache pre-commit hooks + uses: actions/cache@v4 + with: + path: ~/.cache/pre-commit + key: pre-commit|py3.12|${{ hashFiles('.pre-commit-config.yaml') }} + - name: Install Poetry + run: pip install poetry + - name: Setup Python dependencies cache + uses: actions/cache@v4 + with: + path: ~/.cache/pypoetry + key: poetry-${{ hashFiles('**/poetry.lock') }} + restore-keys: | + poetry- + - name: Install dependencies + run: make install + - name: Add local venv to PATH + run: echo "${{ github.workspace }}/.venv/bin" >> $GITHUB_PATH + - name: Lint + run: | + echo "::add-matcher::.github/actionlint-matcher.json" + make lint + test-unit: + name: Unit tests + runs-on: ubuntu-latest + steps: + - name: Checkout commit + uses: actions/checkout@v4 + - name: Install python + uses: actions/setup-python@v5 + with: + python-version-file: .python-version + cache: pip + - name: Install Poetry + run: pip install poetry + - name: Setup Python dependencies cache + uses: actions/cache@v4 + with: + path: ~/.cache/pypoetry + key: poetry-${{ hashFiles('**/poetry.lock') }} + restore-keys: | + poetry- + - name: Install dependencies + run: make setup + - name: Add local venv to PATH + run: echo "${{ github.workspace }}/.venv/bin" >> $GITHUB_PATH + - name: Run unit tests + run: make test-unit + + check: + name: Check + needs: + - lint + runs-on: ubuntu-latest + if: always() + steps: + - name: Decide whether the needed jobs succeeded or failed + uses: re-actors/alls-green@release/v1 + with: + jobs: ${{ toJSON(needs) }} diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 0629b743..08b4a3e3 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -26,3 +26,23 @@ repos: - id: check-manifest stages: [manual] exclude: ^lightrag/api/webui/ + + + - repo: https://github.com/mrtazz/checkmake.git + rev: 0.2.2 + hooks: + - id: checkmake + + + - repo: https://github.com/gruntwork-io/pre-commit + rev: v0.1.30 + hooks: + - id: helmlint + + + - repo: local + hooks: + - id: generate-types-schemas + name: Generate types schemas + entry: make -f .apolo/scripts/gen_types_schemas.mk gen-types-schemas + language: system diff --git a/.python-version b/.python-version new file mode 100644 index 00000000..2c073331 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.11 diff --git a/Makefile b/Makefile index 2e580fed..b2cad31e 100644 --- a/Makefile +++ b/Makefile @@ -7,16 +7,7 @@ CHART_PACKAGE_DIR := dist/charts HELM_REGISTRY := ghcr.io/neuro-inc/helm-charts RAW_VERSION := $(if $(VERSION),$(VERSION),$(shell git describe --tags --always --dirty 2>/dev/null)) -SANITIZED_VERSION := $(shell RAW="$(RAW_VERSION)" python - <<'PY' -import os, re -raw = os.environ.get("RAW", "").strip() -if not raw: - raw = "0.0.0" -raw = raw.lstrip("v") -sanitized = re.sub(r"[^0-9A-Za-z\\.\\-]", "-", raw) -print(sanitized or "0.0.0") -PY -) +SANITIZED_VERSION := $(shell python -c 'import re; raw = "$(RAW_VERSION)".strip(); raw = raw[1:] if raw.startswith("v") else raw; raw = raw or "0.0.0"; sanitized = re.sub(r"[^0-9A-Za-z.\-]", "-", raw); print(sanitized or "0.0.0")') CHART_VERSION := $(SANITIZED_VERSION) CHART_PACKAGE := $(CHART_PACKAGE_DIR)/$(CHART_NAME)-$(CHART_VERSION).tgz diff --git a/README_load_docs.md b/README_load_docs.md index 1d5d846f..c53f5548 100644 --- a/README_load_docs.md +++ b/README_load_docs.md @@ -8,7 +8,7 @@ Advanced script to load markdown documentation into LightRAG with flexible refer # Default mode (file path references) python load_docs.py /path/to/your/docs -# URL mode (website link references) +# URL mode (website link references) python load_docs.py /path/to/docs --mode urls --base-url https://docs.example.com/ ``` @@ -28,7 +28,7 @@ python load_docs.py docs/ --mode files - [KG] administration/setup.md ``` -### URLs Mode +### URLs Mode Uses website URLs in query response citations: ```bash python load_docs.py docs/ --mode urls --base-url https://docs.apolo.us/index/ @@ -37,7 +37,7 @@ python load_docs.py docs/ --mode urls --base-url https://my-docs.com/v1/ **Query Response Example:** ``` -### References +### References - [DC] https://docs.apolo.us/index/getting-started/installation - [KG] https://docs.apolo.us/index/administration/setup ``` @@ -68,7 +68,7 @@ docs/ ```bash # Visit your docs site and note the URL patterns: # https://docs.example.com/getting-started/installation -# https://docs.example.com/api/authentication +# https://docs.example.com/api/authentication # https://docs.example.com/guides/deployment ``` @@ -80,7 +80,7 @@ mkdir -p docs/{getting-started,api,guides} **Step 3: Organize Your Markdown Files** ```bash # Match each URL to a file path: -docs/getting-started/installation.md # → /getting-started/installation +docs/getting-started/installation.md # → /getting-started/installation docs/api/authentication.md # → /api/authentication docs/guides/deployment.md # → /guides/deployment docs/guides/README.md # → /guides (overview page) @@ -109,7 +109,7 @@ curl -I https://docs.example.com/api/authentication apolo-docs/ ├── getting-started/ │ ├── first-steps/ -│ │ ├── getting-started.md → /index/getting-started/first-steps/getting-started +│ │ ├── getting-started.md → /index/getting-started/first-steps/getting-started │ │ └── README.md → /index/getting-started/first-steps │ ├── apolo-base-docker-image.md → /index/getting-started/apolo-base-docker-image │ └── faq.md → /index/getting-started/faq @@ -135,14 +135,14 @@ python load_docs.py docs/ --endpoint https://lightrag.example.com # Load to local instance, skip test query python load_docs.py docs/ --no-test -# Files mode with custom endpoint +# Files mode with custom endpoint python load_docs.py docs/ --mode files --endpoint http://localhost:9621 ``` ## Features - **Dual Reference Modes**: File paths or live website URLs in citations -- **Flexible Base URL**: Works with any documentation site structure +- **Flexible Base URL**: Works with any documentation site structure - **Simple dependency**: Only requires `httpx` and Python standard library - **Automatic discovery**: Finds all `.md` files recursively - **Smart metadata**: Adds appropriate title, path/URL, and source information @@ -171,4 +171,4 @@ This loader is perfect for: pip install httpx ``` -**Note**: This script is included with LightRAG deployments and provides a simple way to load any markdown documentation into your LightRAG instance. \ No newline at end of file +**Note**: This script is included with LightRAG deployments and provides a simple way to load any markdown documentation into your LightRAG instance. diff --git a/hooks.Dockerfile b/hooks.Dockerfile new file mode 100644 index 00000000..ad579545 --- /dev/null +++ b/hooks.Dockerfile @@ -0,0 +1,22 @@ +FROM python:3.12-slim + +LABEL org.opencontainers.image.source="https://github.com/neuro-inc/LightRAG" + +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + POETRY_NO_INTERACTION=1 \ + POETRY_VIRTUALENVS_CREATE=0 + +RUN apt-get update && apt-get install -y --no-install-recommends \ + build-essential \ + && apt-get clean && rm -rf /var/lib/apt/lists/* + +WORKDIR /app + +COPY README.md poetry.lock pyproject.toml . +RUN pip --no-cache-dir install poetry && poetry install --no-root --no-cache + +COPY .apolo .apolo +RUN poetry install --only-root --no-cache + +ENTRYPOINT ["app-types"] diff --git a/load_docs.py b/load_docs.py index fd41959f..7482fdd7 100755 --- a/load_docs.py +++ b/load_docs.py @@ -14,8 +14,8 @@ from typing import Dict, List, Optional async def load_document_to_lightrag( - content: str, - title: str, + content: str, + title: str, doc_url: str, endpoint: str = "http://localhost:9621", headers: Optional[Dict[str, str]] = None @@ -34,7 +34,7 @@ async def load_document_to_lightrag( "file_source": doc_url } ) - + if response.status_code == 200: print(f"✅ Loaded: {title}") return True @@ -47,7 +47,7 @@ async def load_document_to_lightrag( except: print(f" Response: {response.text}") return False - + except Exception as e: print(f"❌ Error loading {title}: {e}") return False @@ -58,27 +58,27 @@ def convert_file_path_to_url(relative_path: str, base_url: str) -> str: # Ensure base URL ends with / if not base_url.endswith('/'): base_url += '/' - + # Handle special cases if relative_path in ["README.md", "SUMMARY.md"]: return base_url.rstrip('/') - + # Remove .md extension and convert path url_path = relative_path.replace(".md", "") - + # Handle README files in subdirectories - they map to the directory URL if url_path.endswith("/README"): url_path = url_path[:-7] # Remove "/README" - + # Clean up any double slashes url_path = url_path.strip("/") - + return f"{base_url}{url_path}" def load_markdown_files(docs_path: Path, mode: str = "files", base_url: str = None) -> List[tuple]: """Load all markdown files from directory structure - + Args: docs_path: Path to documentation directory mode: 'files' for file paths, 'urls' for URL references @@ -86,42 +86,42 @@ def load_markdown_files(docs_path: Path, mode: str = "files", base_url: str = No """ if not docs_path.exists(): raise FileNotFoundError(f"Documentation directory not found: {docs_path}") - + if mode == "urls" and not base_url: raise ValueError("base_url is required when mode is 'urls'") - + # Find all markdown files, excluding SUMMARY.md as it's just the table of contents md_files = [f for f in docs_path.rglob("*.md") if f.name != "SUMMARY.md"] print(f"📚 Found {len(md_files)} markdown files") print(f"🔧 Mode: {mode}") if mode == "urls": print(f"🌐 Base URL: {base_url}") - + documents = [] - + for file_path in md_files: try: # Load content with open(file_path, 'r', encoding='utf-8') as f: content = f.read().strip() - + if not content: continue - + # Generate title from filename title = file_path.stem.replace("-", " ").replace("_", " ").title() if title.lower() == "readme": # Use parent directory name for README files title = f"{file_path.parent.name.replace('-', ' ').replace('_', ' ').title()} Overview" - + # Get relative path for metadata relative_path = str(file_path.relative_to(docs_path)) - + if mode == "files": # Use file path as reference reference = relative_path source_info = f"File: {file_path.name}" - + # Prepare content with file metadata content_with_metadata = f""" Title: {title} @@ -134,7 +134,7 @@ Source: {source_info} # Convert file path to documentation URL reference = convert_file_path_to_url(relative_path, base_url) source_info = f"Documentation Site" - + # Prepare content with URL metadata content_with_metadata = f""" Title: {title} @@ -143,13 +143,13 @@ Source: {source_info} {content} """ - + documents.append((content_with_metadata, title, reference)) - + except Exception as e: print(f"⚠️ Error processing {file_path}: {e}") continue - + return documents @@ -189,7 +189,7 @@ async def test_query( headers=request_headers, json={"query": "What is this documentation about?", "mode": "local"} ) - + if response.status_code == 200: result = response.json() print(f"✅ Query successful!") @@ -202,7 +202,7 @@ async def test_query( print(f" Error details: {error_detail}") except: print(f" Response: {response.text}") - + except Exception as e: print(f"❌ Query error: {e}") @@ -216,22 +216,22 @@ async def main(): Examples: # Load with file path references (default mode) python load_docs.py ../apolo-copilot/docs/official-apolo-documentation/docs - + # Load with URL references python load_docs.py docs/ --mode urls --base-url https://docs.apolo.us/index/ - + # Load Apolo docs with URL references (common use case) python load_docs.py ../apolo-copilot/docs/official-apolo-documentation/docs \\ --mode urls --base-url https://docs.apolo.us/index/ - + # Use custom endpoint python load_docs.py docs/ --endpoint https://lightrag.example.com - + # Load with different documentation base URL python load_docs.py docs/ --mode urls --base-url https://my-docs.example.com/docs/ """ ) - + parser.add_argument( "docs_path", nargs="?", @@ -259,7 +259,7 @@ Examples: action="store_true", help="Skip test query after loading" ) - + args = parser.parse_args() api_key = os.getenv("LIGHTRAG_API_KEY") if api_key: @@ -267,7 +267,7 @@ Examples: else: auth_headers = None print("ℹ️ LIGHTRAG_API_KEY not set, continuing without authentication.") - + print("🚀 Loading Documentation into LightRAG") print("=" * 60) print(f"📁 Documentation path: {args.docs_path}") @@ -280,12 +280,12 @@ Examples: sys.exit(1) print(f"🌐 LightRAG endpoint: {args.endpoint}") print() - + # Test LightRAG connectivity if not await test_lightrag_health(args.endpoint, headers=auth_headers): print("❌ Cannot connect to LightRAG. Please ensure it's running and accessible.") sys.exit(1) - + # Load documents docs_path = Path(args.docs_path).resolve() try: @@ -293,24 +293,24 @@ Examples: except (FileNotFoundError, ValueError) as e: print(f"❌ {e}") sys.exit(1) - + if not documents: print("❌ No markdown files found to load") sys.exit(1) - + # Calculate statistics total_content = sum(len(content) for content, _, _ in documents) avg_content = total_content // len(documents) if documents else 0 - + print(f"📊 Total content: {total_content:,} characters") print(f"📊 Average length: {avg_content:,} characters") - + # Load documents successful = 0 failed = 0 - + print(f"\n🔄 Starting to load documents...") - + for i, (content, title, doc_url) in enumerate(documents): success = await load_document_to_lightrag( content, @@ -319,23 +319,23 @@ Examples: args.endpoint, headers=auth_headers ) - + if success: successful += 1 else: failed += 1 - + # Progress update if (i + 1) % 10 == 0: print(f"📈 Progress: {i + 1}/{len(documents)} ({successful} success, {failed} failed)") - + # Small delay to avoid overwhelming the service await asyncio.sleep(0.3) - + print(f"\n✅ Loading complete!") print(f"📊 Successful: {successful}") print(f"📊 Failed: {failed}") - + # Test query unless disabled if not args.no_test and successful > 0: await test_query(args.endpoint, headers=auth_headers) diff --git a/poetry.lock b/poetry.lock new file mode 100644 index 00000000..46dcd61e --- /dev/null +++ b/poetry.lock @@ -0,0 +1,2377 @@ +# This file is automatically @generated by Poetry 2.1.3 and should not be changed by hand. + +[[package]] +name = "aiobotocore" +version = "2.21.1" +description = "Async client for aws services using botocore and aiohttp" +optional = false +python-versions = ">=3.8" +groups = ["main"] +files = [ + {file = "aiobotocore-2.21.1-py3-none-any.whl", hash = "sha256:bd7c49a6d6f8a3d9444b0a94417c8da13813b5c7eec1c4f0ec2db7e8ce8f23e7"}, + {file = "aiobotocore-2.21.1.tar.gz", hash = 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