agent learn with pipeline input ok

rootfs/knowledge_pipelines/JarvisPlus/pipeline.toml

@@ -0,0 +1,8 @@
+name = "JarvisPlus"
+input.module = "scan_local"
+input.params.workspace = "${myai_dir}/workspace/JarvisPlus"
+input.params.path = "${myai_dir}/data"
+parser.module = "parse_local"
+parser.params.workspace = "${myai_dir}/workspace/JarvisPlus"
+parser.params.assign_to = "JarvisPlus"
+

rootfs/knowledge_pipelines/Mia/input.py

@@ -3,8 +3,7 @@ import aiofiles
 import chardet
 import logging
 import string
-from knowledge import ImageObjectBuilder, DocumentObjectBuilder, KnowledgePipelineEnvironment, KnowledgePipelineJournal
-from aios_kernel.storage import AIStorage
+from aios import AIStorage,ImageObjectBuilder, DocumentObjectBuilder, KnowledgePipelineEnvironment, KnowledgePipelineJournal
 
 class KnowledgeDirSource:
     def __init__(self, env: KnowledgePipelineEnvironment, config):

rootfs/knowledge_pipelines/Mia/parser.py

@@ -1,8 +1,7 @@
 # define a knowledge base class
 import json
 import string
-from aios_kernel import ComputeKernel, AIStorage
-from knowledge import *
+from aios import *
 
 
 class EmbeddingParser:

rootfs/knowledge_pipelines/Mia/query.py

@@ -1,12 +1,11 @@
 import os
 import logging
 import json
-from aios_kernel import *
-from knowledge import *
+from aios import *
 
-class KnowledgeEnvironment(Environment):
-    def __init__(self, env_id: str) -> None:
-        super().__init__(env_id)
+class EmbeddingEnvironment(SimpleEnvironment):
+    def __init__(self, workspace: str) -> None:
+        super().__init__(workspace)
         self.path = os.path.join(AIStorage.get_instance().get_myai_dir(), "knowledge/indices/embedding")
         self._default_text_model = "all-MiniLM-L6-v2"
         self._default_image_model = "clip-ViT-B-32"
@@ -93,5 +92,5 @@ class KnowledgeEnvironment(Environment):
             content = "*** I have provided the following known information for your reference with json format:\n"
             return content + self.tokens_from_objects(object_ids[index:index+1])
 
-def init() -> KnowledgeEnvironment:
-    return KnowledgeEnvironment("embedding")
+def init(workspace: str) -> EmbeddingEnvironment:
+    return EmbeddingEnvironment(workspace)

rootfs/knowledge_pipelines/pipelines.toml

@@ -1,3 +1,3 @@
 pipelines = [
-    "Mail/Sync"
+    "JarvisPlus"
 ]