@avcodes/harbor - npm Package Compare versions

Comparing version 0.3.10 to 0.3.12

airweave/override.env

+# This file can be used for additional environment variables
+# specifically for the 'airweave' service.
+# You can also use the "harbor env" command to set these variables.
+
+# .env.example - Template for local development environment
+# Copy to .env for local debugging with VS Code
+
+# Application settings
+PROJECT_NAME=Airweave
+
+# Database settings - will connect to Docker services via localhost
+POSTGRES_DB=airweave
+POSTGRES_PASSWORD=airweave1234!
+POSTGRES_USER=airweave
+
+# Vector database settings
+QDRANT_PORT=6333
+
+# Embedding model settings
+TEXT2VEC_INFERENCE_URL=http://airweave-embeddings:9878
+
+# Feature flags
+RUN_DB_SYNC=true
+RUN_ALEMBIC_MIGRATIONS=true
+LOCAL_CURSOR_DEVELOPMENT=true
+
+# Default admin user
+FIRST_SUPERUSER=[e-mail]
+FIRST_SUPERUSER_PASSWORD=changeme123!
+
+# Security - will be auto-generated if not provided
+
+# DO NOT add real keys to this example file
+ENCRYPTION_KEY="j+3mpBC2702TKIpQcKfYy6pqZqCEbhXsTrxpAhkcRSk="
+
+# API Keys - required for certain features
+# DO NOT add real keys to this example file
+OPENAI_API_KEY=
+MISTRAL_API_KEY=

compose.airweave.yml

+services:
+  airweave:
+    container_name: ${HARBOR_CONTAINER_PREFIX}.airweave
+    build:
+      context: ${HARBOR_AIRWEAVE_GIT_REF}:frontend
+      dockerfile: Dockerfile
+    ports:
+      - ${HARBOR_AIRWEAVE_HOST_PORT}:8080
+    environment:
+      - API_URL=http://localhost:${HARBOR_AIRWEAVE_BACKEND_HOST_PORT}
+      - ENABLE_AUTH=false
+    depends_on:
+      airweave-backend:
+        condition: service_healthy
+    healthcheck:
+      test: [ "CMD", "wget", "--spider", "-q", "http://localhost:8080" ]
+      interval: 1s
+      timeout: 10s
+      retries: 10
+    env_file:
+      - ./.env
+      - ./airweave/override.env
+    networks:
+      - harbor-network
+
+  airweave-backend:
+    container_name: ${HARBOR_CONTAINER_PREFIX}.airweave-backend
+    build:
+      context: ${HARBOR_AIRWEAVE_GIT_REF}:backend
+      dockerfile: Dockerfile
+    ports:
+      - ${HARBOR_AIRWEAVE_BACKEND_HOST_PORT}:8001
+    environment:
+      - POSTGRES_HOST=airweave-postgres
+      - REDIS_HOST=airweave-redis
+      - QDRANT_HOST=airweave-qdrant
+      - QDRANT_PORT=6333
+      - TEXT2VEC_INFERENCE_URL=http://airweave-embeddings:8080
+      - FRONTEND_LOCAL_DEVELOPMENT_PORT=${HARBOR_AIRWEAVE_HOST_PORT}
+      - API_FULL_URL=http://localhost:${HARBOR_AIRWEAVE_BACKEND_HOST_PORT}
+      - LOCAL_DEVELOPMENT=false
+      - ADDITIONAL_CORS_ORIGINS=http://localhost:${HARBOR_AIRWEAVE_HOST_PORT}
+    depends_on:
+      airweave-postgres:
+        condition: service_healthy
+      airweave-redis:
+        condition: service_healthy
+      airweave-qdrant:
+        condition: service_healthy
+    healthcheck:
+      test: [ "CMD", "curl", "-f", "http://localhost:8001/health" ]
+      interval: 1s
+      timeout: 10s
+      retries: 10
+    env_file:
+      - ./.env
+      - ./airweave/override.env
+    networks:
+      - harbor-network
+
+  airweave-postgres:
+    container_name: ${HARBOR_CONTAINER_PREFIX}.airweave-postgres
+    image: postgres:16
+    ports:
+      - ${HARBOR_AIRWEAVE_POSTGRES_HOST_PORT}:5432
+    environment:
+      - POSTGRES_DB=airweave
+      - POSTGRES_USER=airweave
+      - POSTGRES_PASSWORD=airweave1234!
+    healthcheck:
+      test: [ "CMD", "pg_isready", "-U", "airweave" ]
+      interval: 1s
+      timeout: 10s
+      retries: 10
+    volumes:
+      - ${HARBOR_AIRWEAVE_WORKSPACE}/pg:/var/lib/postgresql/data
+    env_file:
+      - ./.env
+      - ./airweave/override.env
+    networks:
+      - harbor-network
+
+  airweave-redis:
+    container_name: ${HARBOR_CONTAINER_PREFIX}.airweave-redis
+    image: redis:7-alpine
+    ports:
+      - ${HARBOR_AIRWEAVE_REDIS_HOST_PORT}:6379
+    healthcheck:
+      test: [ "CMD", "redis-cli", "ping" ]
+      interval: 1s
+      timeout: 10s
+      retries: 10
+    volumes:
+      - ${HARBOR_AIRWEAVE_WORKSPACE}/redis:/data
+    env_file:
+      - ./.env
+      - ./airweave/override.env
+    networks:
+      - harbor-network
+
+  airweave-embeddings:
+    container_name: ${HARBOR_CONTAINER_PREFIX}.airweave-embeddings
+    image: semitechnologies/transformers-inference:sentence-transformers-all-MiniLM-L6-v2
+    ports:
+      - ${HARBOR_AIRWEAVE_EMBEDDINGS_HOST_PORT}:8080
+    environment:
+      ENABLE_CUDA: 0
+      WORKERS_PER_NODE: 1
+    healthcheck:
+      test: [ "CMD", "wget", "--spider", "-q", "http://localhost:8080/health" ]
+      interval: 1s
+      timeout: 10s
+      retries: 20
+    env_file:
+      - ./.env
+      - ./airweave/override.env
+    networks:
+      - harbor-network
+
+  airweave-qdrant:
+    container_name: ${HARBOR_CONTAINER_PREFIX}.airweave-qdrant
+    image: qdrant/qdrant:latest
+    command: bash -c "apt-get update && apt-get install -y curl && ./entrypoint.sh"
+    ports:
+      - ${HARBOR_AIRWEAVE_QDRANT_HOST_PORT}:6333
+    healthcheck:
+      test: [ "CMD", "curl", "-f", "http://localhost:6333/collections" ]
+      interval: 1s
+      timeout: 10s
+      retries: 10
+    volumes:
+      - ${HARBOR_AIRWEAVE_WORKSPACE}/qdrant:/qdrant/storage
+    env_file:
+      - ./.env
+      - ./airweave/override.env
+    networks:
+      - harbor-network

docs/2.3.48-Satellite-Airweave.md

+### [Airweave](https://github.com/airweave-ai/airweave)
+
+> Handle: `airweave`<br/>
+> URL: [http://localhost:34481](http://localhost:34481)
+
+![Airweave Screenshot](./harbor-airweave.png)
+
+A lightweight, fast, and extensible vector database for AI applications. Airweave provides persistent storage and efficient similarity search for embeddings, making it ideal for RAG, chat history, and knowledge base use cases.
+
+#### Starting
+
+```bash
+# [Optional] Pre-build the image
+harbor build airweave
+
+# Start the service
+# --open is optional, to open in browser
+harbor up airweave --open
+```
+
+- Airweave exposes a REST API and a web UI for managing collections and documents
+  - Run `harbor url airweave-backend` to get API URL
+- Data is persisted in the `airweave/data` folder by default, configurable via `airweave.workspace`
+
+#### Usage
+
+You will mostly interact with Airweave via its Web UI or API. Run [`harbor open`](./3.-Harbor-CLI-Reference#harbor-open-service) to access the UI.
+
+```bash
+# Open Airweave Web UI in the browser
+harbor open airweave
+
+# Get a URL
+harbor url airweave
+
+# Get a QR for the phone
+harbor qr airweave
+```
+
+#### Configuration
+
+See the [official documentation](https://github.com/av/airweave#configuration) for more details.
+
+Following options can be set via [`harbor config`](./3.-Harbor-CLI-Reference.md#harbor-config):
+
+```bash
+# The port on the host where Airweave endpoint will be available
+AIRWEAVE_HOST_PORT             34481
+
+# Ports on the host for other services in Airweave group
+AIRWEAVE_BACKEND_HOST_PORT     34482
+AIRWEAVE_POSTGRES_HOST_PORT    34483
+AIRWEAVE_REDIS_HOST_PORT       34484
+AIRWEAVE_QDRANT_HOST_PORT      34485
+AIRWEAVE_EMBEDDINGS_HOST_PORT  34486
+
+# Git ref to build the image from
+# You can adjust the branch/tag/commit to use by adjusting part after the #
+AIRWEAVE_GIT_REF               https://github.com/airweave-ai/airweave.git#main
+
+# Location of the Airweave workspace on the host
+# This is where service data is stored
+# Should be either relative to $(harbor home) or an absolute path
+AIRWEAVE_WORKSPACE             ./airweave/data
+```
+
+See [environment configuration guide](./1.-Harbor-User-Guide.md#environment-variables) to set arbitrary environment variables for the service.

.scripts/seed.ts

@@ -9,3 +9,3 @@ // deno run -A ./.scripts/seed.ts
 
-const VERSION = "0.3.10";
+const VERSION = "0.3.12";
 
@@ -12,0 +12,0 @@ type ValueSeed = {

app/package.json

 {
   "name": "@avcodes/harbor-app",
   "private": true,
-  "version": "0.3.10",
+  "version": "0.3.12",
   "type": "module",
@@ -6,0 +6,0 @@ "scripts": {

app/src-tauri/Cargo.toml

 
 [package]
 name = "harbor-app"
-version = "0.3.10"
+version = "0.3.12"
 description = "A companion app for Harbor LLM toolkit"
@@ -6,0 +6,0 @@ authors = ["av"]

app/src-tauri/tauri.conf.json

 {
   "$schema": "https://schema.tauri.app/config/2.4.0",
   "productName": "Harbor",
-  "version": "0.3.10",
+  "version": "0.3.12",
   "identifier": "com.harbor.app",
@@ -6,0 +6,0 @@ "build": {

app/src/serviceMetadata.ts

@@ -537,3 +537,9 @@
         tooltip: 'MAX is a platform from Modular (creators of Mojo) for running LLMs.'
+    },
+    airweave: {
+        name: 'Airweave',
+        tags: [HST.satellite],
+        wikiUrl: `${wikiUrl}/2.3.48-Satellite-Airweave`,
+        tooltip: 'Airweave lets agents search any app by transforming its contents into agent-ready knowledge.'
     }
 };

boost/src/chat.py

@@ -116,3 +116,4 @@ from typing import Optional
     response = await self.llm.chat_completion(chat=self)
-    self.assistant(self.llm.get_response_content(response))
+    params = await self.llm.resolve_request_params()
+    self.assistant(self.llm.get_response_content(params, response))
     return response
@@ -119,0 +120,0 @@

boost/src/config.py

@@ -199,3 +199,3 @@ from typing import Optional, Generic, TypeVar, List, Union, Type, Dict
   type=ConfigDict,
-  default='temperature=0',
+  default='temperature=0.35',
   description='Extra parameters to always add to the LLM API requests for the downstream APIs (subset of chat completion payload)'
@@ -202,0 +202,0 @@ )

boost/src/custom_modules/polyglot.py

@@ -5,19 +5,19 @@ import asyncio
 import llm
+import log
 
+logger = log.setup_logger(__name__)
+
 ID_PREFIX = "polyglot"
 
 translate_query_prompt = """
-<instruction>
 Translate the following message into {language} language.
-Do not do literal translation, but rather adapt the message to the cultural context of the target language, however keep the original meaning.
+Focus on keeping original meaning and context unchanged.
 Do not address any part of the message, only translate it.
-</instruction>
 
-<input name="message">
+<message>
 {message}
-</input>
+</message>
 """
 
 synthesis_prompt = """
-<instruction>
 Read through the "solutions" to the "query".
@@ -27,11 +27,10 @@ Combine ideas from the "solutions" into a single coherent response to the "query".
 Your reply will be in the language of the "query" input.
-</instruction>
 
-<input name="query">
+<query>
 {query}
-</input>
+</query>
 
-<input name="solutions">
+<solutions>
 {solutions}
-</input>
+</solutions>
 """
@@ -90,3 +89,5 @@
     query=query,
-    solutions=solutions,
+    solutions="\n\n".join(
+      [f"# Solution No. {i+1}:\n{solution}" for i, solution in enumerate(solutions)]
+    ),
   )

compose.ldr.yml

 services:
   ldr:
-    build:
-      context: https://github.com/LearningCircuit/local-deep-research.git
-      dockerfile: Dockerfile
+    image: ${HARBOR_LDR_IMAGE}:${HARBOR_LDR_VERSION}
+    # build:
+    #   context: https://github.com/LearningCircuit/local-deep-research.git
+    #   dockerfile: Dockerfile
     container_name: ${HARBOR_CONTAINER_PREFIX}.ldr
@@ -7,0 +8,0 @@ ports:

compose.x.ldr.ollama.yml

@@ -5,2 +5,4 @@ services:
       - LDR_LLM__PROVIDER=ollama
-      - OLLAMA_BASE_URL=${HARBOR_OLLAMA_INTERNAL_URL}
+      - OLLAMA_BASE_URL=${HARBOR_OLLAMA_INTERNAL_URL}
+      - LDR_LLM_PROVIDER=ollama
+      - LDR_LLM_OLLAMA_URL=${HARBOR_OLLAMA_INTERNAL_URL}

compose.x.ldr.searxng.yml

@@ -5,2 +5,3 @@ services:
       - LDR_SEARCH__TOOL=searxng
+      - LDR_SEARCH_TOOL=searxng
       - SEARXNG_INSTANCE=${HARBOR_SEARXNG_INTERNAL_URL}

docs/2.-Services.md

@@ -124,2 +124,5 @@
 
+- [Airweave](https://github.com/av/harbor/wiki/2.3.48-Satellite-Airweave) <span style="opacity: 0.5;">`Satellite`</span><br/>
+Airweave lets agents search any app by transforming its contents into agent-ready knowledge.
+
 - [autogpt](https://github.com/av/harbor/wiki/2.3.15-Satellite:-AutoGPT) <span style="opacity: 0.5;">`Satellite`, `Partial Support`</span><br/>
@@ -126,0 +129,0 @@ Create, deploy, and manage continuous AI agents that automate complex workflows.

docs/2.3.45-Satellite-Local-Deep-Research.md

@@ -13,4 +13,4 @@ ### [Local Deep Research](https://github.com/LearningCircuit/local-deep-research)
 ```bash
-# [Optional] pre-build the image
-harbor build ldr
+# [Optional] pre-pull the image (~7GB)
+harbor pull ldr
 
@@ -38,2 +38,9 @@ # It makes little sense to run ldr without a
 LDR_WORKSPACE                  ./ldr/data
+
+# Docker image to use for this service
+LDR_IMAGE                      localdeepresearch/local-deep-research
+
+# Docker tag to use for this service
+# Should be one of the tags for the image above
+LDR_VERSION                    latest
 ```

docs/2.3.5-Satellite&colon-LiteLLM.md

 ### [🚅 LiteLLM](https://docs.litellm.ai/docs/)
 
-> Handle: `litellm`
+> Handle: `litellm`<br/>
 > URL: [http://localhost:33841/](http://localhost:33841/)
@@ -65,2 +65,6 @@
 
+- After changing the `config.yaml` - you will need to restart the service `harbor restart litellm`
+- URLs must be internal to Docker network, can be obtained with [`harbor url -i <service>`](./3.-Harbor-CLI-Reference.md#harbor-url-service)
+- You can use `harbor env litellm <name> <value>` to set environment variables to reference in the `config.yaml` file
+
 Please see [official LiteLLM documentation](https://docs.litellm.ai/docs/) for plenty of additional examples.

ollama/override.env

@@ -5,1 +5,2 @@ # This file can be used for additional environment variables
 OLLAMA_CONTEXT_LENGTH="4096"
+OLLAMA_NUM_PARALLEL="4"

package.json

 {
   "name": "@avcodes/harbor",
-  "version": "0.3.10",
+  "version": "0.3.12",
   "description": "Effortlessly run LLM backends, APIs, frontends, and services with one command.",
@@ -5,0 +5,0 @@ "private": false,

profiles/default.env

@@ -602,2 +602,4 @@ # ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
 HARBOR_LDR_WORKSPACE="./ldr/data"
+HARBOR_LDR_IMAGE="localdeepresearch/local-deep-research"
+HARBOR_LDR_VERSION="latest"
 
@@ -625,2 +627,12 @@ # LocalAI
 
+# AirWeave
+HARBOR_AIRWEAVE_HOST_PORT=34481
+HARBOR_AIRWEAVE_BACKEND_HOST_PORT=34482
+HARBOR_AIRWEAVE_POSTGRES_HOST_PORT=34483
+HARBOR_AIRWEAVE_REDIS_HOST_PORT=34484
+HARBOR_AIRWEAVE_QDRANT_HOST_PORT=34485
+HARBOR_AIRWEAVE_EMBEDDINGS_HOST_PORT=34486
+HARBOR_AIRWEAVE_GIT_REF="https://github.com/airweave-ai/airweave.git#main"
+HARBOR_AIRWEAVE_WORKSPACE="./airweave/data"
+
 # ============================================
@@ -627,0 +639,0 @@ # Service Configuration.

pyproject.toml

 
 [tool.poetry]
 name = "llm-harbor"
-version = "0.3.10"
+version = "0.3.12"
 description = "Effortlessly run LLM backends, APIs, frontends, and services with one command."
@@ -12,3 +12,3 @@ repository = "https://github.com/av/harbor"
 classifiers = ["Topic :: Utilities","Topic :: Scientific/Engineering :: Artificial Intelligence","Environment :: Console","License :: OSI Approved :: Apache Software License"]
-include = 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
@@ -15,0 +15,0 @@ [[tool.poetry.packages]]

New alerts

Network access

Supply chain risk

This module accesses the network.

Found 5 instances in 1 package

Uses eval

Supply chain risk

Package uses dynamic code execution (e.g., eval()), which is a dangerous practice. This can prevent the code from running in certain environments and increases the risk that the code may contain exploits or malicious behavior.

Found 1 instance in 1 package

Environment variable access

Supply chain risk

Package accesses environment variables, which may be a sign of credential stuffing or data theft.

Found 12 instances in 1 package

Filesystem access

Supply chain risk

Accesses the file system, and could potentially read sensitive data.

Found 1 instance in 1 package

AI-detected potential code anomaly

Supply chain risk

AI has identified unusual behaviors that may pose a security risk.

Found 2 instances in 1 package

Long strings

Supply chain risk

Contains long string literals, which may be a sign of obfuscated or packed code.

Found 1 instance in 1 package

URL strings

Supply chain risk

Package contains fragments of external URLs or IP addresses, which the package may be accessing at runtime.

Found 1 instance in 1 package

Fixed alerts

Network access

Supply chain risk

This module accesses the network.

Found 5 instances in 1 package

Uses eval

Supply chain risk

Package uses dynamic code execution (e.g., eval()), which is a dangerous practice. This can prevent the code from running in certain environments and increases the risk that the code may contain exploits or malicious behavior.

Found 1 instance in 1 package

Environment variable access

Supply chain risk

Package accesses environment variables, which may be a sign of credential stuffing or data theft.

Found 12 instances in 1 package

Filesystem access

Supply chain risk

Accesses the file system, and could potentially read sensitive data.

Found 1 instance in 1 package

AI-detected potential code anomaly

Supply chain risk

AI has identified unusual behaviors that may pose a security risk.

Found 2 instances in 1 package

Long strings

Supply chain risk

Contains long string literals, which may be a sign of obfuscated or packed code.

Found 1 instance in 1 package

URL strings

Supply chain risk

Package contains fragments of external URLs or IP addresses, which the package may be accessing at runtime.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

28027555

0.85%

Number of package files

1160

0.35%

Lines of code

21424

0.03%

No dependency changes