Merge pull request instructlab#166 from derekhiggins/load-pipes

Load custom pipelines from shared data dir

requirements.txt

@@ -3,6 +3,7 @@ click>=8.1.7,<9.0.0
 httpx>=0.25.0,<1.0.0
 langchain-text-splitters
 openai>=1.13.3,<2.0.0
+platformdirs>=4.2
 # Note: this dependency goes along with langchain-text-splitters and mayt be
 #       removed once that one is removed.
 # do not use 8.4.0 due to a bug in the library

src/instructlab/sdg/generate_data.py

@@ -14,6 +14,7 @@
 from datasets import Dataset
 import httpx
 import openai
+import platformdirs
 
 # First Party
 # pylint: disable=ungrouped-imports
@@ -164,29 +165,48 @@ def _gen_test_data(
             outfile.write("\n")
 
 
+def _check_pipeline_dir(pipeline):
+    for file in ["knowledge.yaml", "freeform_skills.yaml", "grounded_skills.yaml"]:
+        if not os.path.exists(os.path.join(pipeline, file)):
+            raise GenerateException(
+                f"Error: pipeline directory ({pipeline}) does not contain {file}."
+            )
+
+
 def _sdg_init(pipeline, client, model_family, model_id, num_instructions_to_generate):
     pipeline_pkg = None
-    if pipeline == "full":
-        pipeline_pkg = FULL_PIPELINES_PACKAGE
-    elif pipeline == "simple":
-        pipeline_pkg = SIMPLE_PIPELINES_PACKAGE
+
+    # Search for the pipeline in User and Site data directories
+    # then for a package defined pipeline
+    # and finally pipelines referenced by absolute path
+    pd = platformdirs.PlatformDirs(
+        appname=os.path.join("instructlab", "sdg"), multipath=True
+    )
+    for d in pd.iter_data_dirs():
+        if os.path.exists(os.path.join(d, pipeline)):
+            pipeline = os.path.join(d, pipeline)
+            _check_pipeline_dir(pipeline)
+            break
     else:
-        # Validate that pipeline is a valid directory and that it contains the required files
-        if not os.path.exists(pipeline):
-            raise GenerateException(
-                f"Error: pipeline directory ({pipeline}) does not exist."
-            )
-        for file in ["knowledge.yaml", "freeform_skills.yaml", "grounded_skills.yaml"]:
-            if not os.path.exists(os.path.join(pipeline, file)):
+        if pipeline == "full":
+            pipeline_pkg = FULL_PIPELINES_PACKAGE
+        elif pipeline == "simple":
+            pipeline_pkg = SIMPLE_PIPELINES_PACKAGE
+        else:
+            # Validate that pipeline is a valid directory and that it contains the required files
+            if not os.path.exists(pipeline):
                 raise GenerateException(
-                    f"Error: pipeline directory ({pipeline}) does not contain {file}."
+                    f"Error: pipeline directory ({pipeline}) does not exist."
                 )
+            _check_pipeline_dir(pipeline)
 
     ctx = PipelineContext(client, model_family, model_id, num_instructions_to_generate)
 
     def load_pipeline(yaml_basename):
         if pipeline_pkg:
-            with resources.path(pipeline_pkg, yaml_basename) as yaml_path:
+            with resources.as_file(
+                resources.files(pipeline_pkg).joinpath(yaml_basename)
+            ) as yaml_path:
                 return Pipeline.from_file(ctx, yaml_path)
         else:
             return Pipeline.from_file(ctx, os.path.join(pipeline, yaml_basename))
@@ -236,7 +256,8 @@ def generate_data(
     use the SDG library constructs directly, and this function will likely be removed.
 
     Args:
-        pipeline: This argument may be either an alias defined by the sdg library ("simple", "full"),
+        pipeline: This argument may be either an alias defined in a user or site "data directory"
+                  or an alias defined by the sdg library ("simple", "full")(if the data directory has no matches),
                   or an absolute path to a directory containing the pipeline YAML files.
                   We expect three files to be present in this directory: "knowledge.yaml",
                     "freeform_skills.yaml", and "grounded_skills.yaml".