Revert "Feature/configure flows (#345)"

This reverts commit a9197d11ee.

trustgraph-embeddings-hf/trustgraph/embeddings/hf/hf.py

@@ -4,37 +4,89 @@ Embeddings service, applies an embeddings model selected from HuggingFace.
 Input is text, output is embeddings vector.
 """
 
-from ... base import EmbeddingsService
-
 from langchain_huggingface import HuggingFaceEmbeddings
 
-default_ident = "embeddings"
+from trustgraph.schema import EmbeddingsRequest, EmbeddingsResponse, Error
+from trustgraph.schema import embeddings_request_queue
+from trustgraph.schema import embeddings_response_queue
+from trustgraph.log_level import LogLevel
+from trustgraph.base import ConsumerProducer
 
+module = ".".join(__name__.split(".")[1:-1])
+
+default_input_queue = embeddings_request_queue
+default_output_queue = embeddings_response_queue
+default_subscriber = module
 default_model="all-MiniLM-L6-v2"
 
-class Processor(EmbeddingsService):
+class Processor(ConsumerProducer):
 
     def __init__(self, **params):
 
+        input_queue = params.get("input_queue", default_input_queue)
+        output_queue = params.get("output_queue", default_output_queue)
+        subscriber = params.get("subscriber", default_subscriber)
         model = params.get("model", default_model)
 
         super(Processor, self).__init__(
-            **params | { "model": model }
+            **params | {
+                "input_queue": input_queue,
+                "output_queue": output_queue,
+                "subscriber": subscriber,
+                "input_schema": EmbeddingsRequest,
+                "output_schema": EmbeddingsResponse,
+            }
         )
 
-        print("Get model...", flush=True)
         self.embeddings = HuggingFaceEmbeddings(model_name=model)
 
-    async def on_embeddings(self, text):
+    async def handle(self, msg):
 
-        embeds = self.embeddings.embed_documents([text])
-        print("Done.", flush=True)
-        return embeds
+        v = msg.value()
+
+        # Sender-produced ID
+        id = msg.properties()["id"]
+
+        print(f"Handling input {id}...", flush=True)
+
+        try:
+
+            text = v.text
+            embeds = self.embeddings.embed_documents([text])
+
+            print("Send response...", flush=True)
+            r = EmbeddingsResponse(vectors=embeds, error=None)
+            await self.send(r, properties={"id": id})
+
+            print("Done.", flush=True)
+
+
+        except Exception as e:
+
+            print(f"Exception: {e}")
+
+            print("Send error response...", flush=True)
+
+            r = EmbeddingsResponse(
+                error=Error(
+                    type = "llm-error",
+                    message = str(e),
+                ),
+                response=None,
+            )
+
+            await self.send(r, properties={"id": id})
+
+            self.consumer.acknowledge(msg)
+            
 
     @staticmethod
     def add_args(parser):
 
-        EmbeddingsService.add_args(parser)
+        ConsumerProducer.add_args(
+            parser, default_input_queue, default_subscriber,
+            default_output_queue,
+        )
 
         parser.add_argument(
             '-m', '--model',
@@ -44,5 +96,5 @@ class Processor(EmbeddingsService):
 
 def run():
 
-    Processor.launch(default_ident, __doc__)
+    Processor.launch(module, __doc__)