Argument parsing (agent manager is broken)

trustgraph-base/trustgraph/base/base_processor.py

@@ -39,8 +39,9 @@ class BaseProcessor:
 
     def __del__(self):
 
-        if self.client:
+        if hasattr(self, "client"):
-            self.client.close()
+            if self.client:
+                self.client.close()
 
     @staticmethod
     def add_args(parser):

trustgraph-flow/trustgraph/agent/react/README.md

@@ -0,0 +1,16 @@
+
+agent-manager-react \
+    -p pulsar://localhost:6650 \
+    --tool-type \
+        shuttle=knowledge-base:query \
+        cats=knowledge-base:query \
+        compute=text-completion:computation \
+    --tool-description \
+        shuttle="Query a knowledge base with information about the space shuttle.  The query should be a simple natural language question" \
+        cats="Query a knowledge base with information about Mark's cats.  The query should be a simple natural language question" \
+        compute="A computation engine which can answer questions about maths and computation" \
+    --tool-argument \
+        cats="query:string:The search query string" \
+        shuttle="query:string:The search query string" \
+        compute="computation:string:The computation to solve"
+

trustgraph-flow/trustgraph/agent/react/service.py

@@ -4,6 +4,7 @@ Simple agent infrastructure broadly implements the ReAct flow.
 
 import json
 import re
+import sys
 
 from pulsar.schema import JsonSchema
 
@@ -35,6 +36,73 @@ class Processor(ConsumerProducer):
 
     def __init__(self, **params):
 
+        tool_base = {}
+
+        # Parsing the prompt information to the prompt configuration
+        # structure
+        tool_type_arg = params.get("tool_type", [])
+        if tool_type_arg:
+            for t in tool_type_arg:
+                toks = t.split("=", 1)
+                if len(toks) < 2:
+                    raise RuntimeError(
+                        f"Tool-type string not well-formed: {t}"
+                    )
+                ttoks = toks[1].split(":", 1)
+                if len(ttoks) == 1:
+                    tool_base[toks[0]] = {
+                        "type": ttoks[0],
+                        "input-arg": "query",
+                        "arguments": {},
+                    }
+                else:
+                    tool_base[toks[0]] = {
+                        "type": ttoks[0],
+                        "input-arg": ttoks[1],
+                        "arguments": {},
+                    }
+
+        # Parsing the prompt information to the prompt configuration
+        # structure
+        tool_desc_arg = params.get("tool_description", [])
+        if tool_desc_arg:
+            for t in tool_desc_arg:
+                toks = t.split("=", 1)
+                if len(toks) < 2:
+                    raise RuntimeError(
+                        f"Tool-type string not well-formed: {t}"
+                    )
+                if toks[0] not in tool_base:
+                    raise RuntimeError(f"Description, tool {toks[0]} not known")
+                tool_base[toks[0]]["description"] = toks[1]
+
+        # Parsing the prompt information to the prompt configuration
+        # structure
+        tool_arg_arg = params.get("tool_argument", [])
+        if tool_arg_arg:
+            for t in tool_arg_arg:
+                toks = t.split("=", 1)
+                if len(toks) < 2:
+                    raise RuntimeError(
+                        f"Tool-type string not well-formed: {t}"
+                    )
+                ttoks = toks[1].split(":", 2)
+                if len(ttoks) != 3:
+                    raise RuntimeError(
+                        f"Tool argument string not well-formed: {t}"
+                    )
+                if toks[0] not in tool_base:
+                    raise RuntimeError(f"Description, tool {toks[0]} not known")
+                tool_base[toks[0]]["arguments"][ttoks[0]] = {
+                    "name": ttoks[0],
+                    "type": ttoks[1],
+                    "description": ttoks[2],
+                }
+
+        print(json.dumps(tool_base, indent=4))
+
+        sys.exit(0)
+
         input_queue = params.get("input_queue", default_input_queue)
         output_queue = params.get("output_queue", default_output_queue)
         subscriber = params.get("subscriber", default_subscriber)
@@ -275,6 +343,35 @@ class Processor(ConsumerProducer):
             help=f'Graph RAG response queue (default: {gr_response_queue})',
         )
 
+        parser.add_argument(
+            '--tool-type', nargs='*',
+            help=f'''Specifies the type of an agent tool.  Takes the form
+<id>=<specifier>.  <id> is the name of the tool.  <specifier> is one of
+knowledge-base, text-completion.  Additional parameters are specified
+for different tools which are tool-specific. e.g. knowledge-query:<arg>
+which specifies the name of the arg whose content is fed into the knowledge
+query as a question.  text-completion:<arg> specifies the name of the arg
+whose content is fed into the text-completion service as a prompt'''
+        )
+
+        parser.add_argument(
+            '--tool-description', nargs='*',
+            help=f'''Specifies the textual description of a tool.  Takes
+the form <id>=<description>.  The description is important, it teaches the
+LLM how to use the tool.  It should describe what it does and how to
+use the arguments.  This is specified in natural language.'''
+        )
+
+        parser.add_argument(
+            '--tool-argument', nargs='*',
+            help=f'''Specifies argument usage for a tool.  Takes
+the form <id>=<arg>:<type>:<description>.  The description is important,
+it is read by the LLM and used to determine how to use the argument.
+<id> can be specified multiple times to give a tool multiple arguments.
+<type> is one of string, number.  <description> is a natural language
+description.'''
+        )
+
 def run():
 
     Processor.start(module, __doc__)