Feature/configure flows (#345)

- Keeps processing in different flows separate so that data can go to different stores / collections etc.
- Potentially supports different processing flows
- Tidies the processing API with common base-classes for e.g. LLMs, and automatic configuration of 'clients' to use the right queue names in a flow

trustgraph-base/trustgraph/base/graph_embeddings_query_service.py

@@ -0,0 +1,84 @@
+
+"""
+Graph embeddings query service.  Input is vectors.  Output is list of
+embeddings.
+"""
+
+from .. schema import GraphEmbeddingsRequest, GraphEmbeddingsResponse
+from .. schema import Error, Value
+
+from . flow_processor import FlowProcessor
+from . consumer_spec import ConsumerSpec
+from . producer_spec import ProducerSpec
+
+default_ident = "ge-query"
+
+class GraphEmbeddingsQueryService(FlowProcessor):
+
+    def __init__(self, **params):
+
+        id = params.get("id")
+
+        super(GraphEmbeddingsQueryService, self).__init__(
+            **params | { "id": id }
+        )
+
+        self.register_specification(
+            ConsumerSpec(
+                name = "request",
+                schema = GraphEmbeddingsRequest,
+                handler = self.on_message
+            )
+        )
+
+        self.register_specification(
+            ProducerSpec(
+                name = "response",
+                schema = GraphEmbeddingsResponse,
+            )
+        )
+
+    async def on_message(self, msg, consumer, flow):
+
+        try:
+
+            request = msg.value()
+
+            # Sender-produced ID
+            id = msg.properties()["id"]
+
+            print(f"Handling input {id}...", flush=True)
+
+            entities = await self.query_graph_embeddings(request)
+
+            print("Send response...", flush=True)
+            r = GraphEmbeddingsResponse(entities=entities, error=None)
+            await flow("response").send(r, properties={"id": id})
+
+            print("Done.", flush=True)
+
+        except Exception as e:
+
+            print(f"Exception: {e}")
+
+            print("Send error response...", flush=True)
+
+            r = GraphEmbeddingsResponse(
+                error=Error(
+                    type = "graph-embeddings-query-error",
+                    message = str(e),
+                ),
+                response=None,
+            )
+
+            await flow("response").send(r, properties={"id": id})
+
+    @staticmethod
+    def add_args(parser):
+
+        FlowProcessor.add_args(parser)
+
+def run():
+
+    Processor.launch(default_ident, __doc__)
+