- Moved the agent-react template from hard-coded in agent_manager.py to (#151)

a template prompt managed by prompt manager.  The prompt is called
  agent-react.

templates/prompts/default-prompts.jsonnet

@@ -104,6 +104,10 @@
             "response-type": "text",
         },
 
+        "agent-react":: {
+            "prompt": "Answer the following questions as best you can. You have\naccess to the following functions:\n\n{% for tool in tools %}{\n    \"function\": \"{{ tool.name }}\",\n    \"description\": \"{{ tool.description }}\",\n    \"arguments\": [\n{% for arg in tool.arguments %}        {\n            \"name\": \"{{ arg.name }}\",\n            \"type\": \"{{ arg.type }}\",\n            \"description\": \"{{ arg.description }}\",\n        }\n{% endfor %}\n    ]\n}\n{% endfor %}\n\nYou can either choose to call a function to get more information, or\nreturn a final answer.\n    \nTo call a function, respond with a JSON object of the following format:\n\n{\n    \"thought\": \"your thought about what to do\",\n    \"action\": \"the action to take, should be one of [{{tool_names}}]\",\n    \"arguments\": {\n        \"argument1\": \"argument_value\",\n        \"argument2\": \"argument_value\"\n    }\n}\n\nTo provide a final answer, response a JSON object of the following format:\n\n{\n  \"thought\": \"I now know the final answer\",\n  \"final-answer\": \"the final answer to the original input question\"\n}\n\nPrevious steps are included in the input.  Each step has the following\nformat in your output:\n\n{\n  \"thought\": \"your thought about what to do\",\n  \"action\": \"the action taken\",\n  \"arguments\": {\n      \"argument1\": action argument,\n      \"argument2\": action argument2\n  },\n  \"observation\": \"the result of the action\",\n}\n\nRespond by describing either one single thought/action/arguments or\nthe final-answer.  Pause after providing one action or final-answer.\n\n{% if context %}Additional context has been provided:\n{{context}}{% endif %}\n\nQuestion: {{question}}\n\nInput:\n    \n{% for h in history %}\n{\n    \"action\": \"{{h.action}}\",\n    \"arguments\": [\n{% for k, v in h.arguments.items() %}        {\n            \"{{k}}\": \"{{v}}\",\n{%endfor%}        }\n    ],\n    \"observation\": \"{{h.observation}}\"\n}\n{% endfor %}",
+            "response-type": "json"
+        }
     }
 
 }

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

@@ -1,5 +1,4 @@
 
-import ibis
 import logging
 import json
 
@@ -9,79 +8,6 @@ logger = logging.getLogger(__name__)
 
 class AgentManager:
 
-    template="""Answer the following questions as best you can. You have
-access to the following functions:
-
-{% for tool in tools %}{
-    "function": "{{ tool.name }}",
-    "description": "{{ tool.description }}",
-    "arguments": [
-{% for arg in tool.arguments %}        {
-            "name": "{{ arg.name }}",
-            "type": "{{ arg.type }}",
-            "description": "{{ arg.description }}",
-        }
-{% endfor %}
-    ]
-}
-{% endfor %}
-
-You can either choose to call a function to get more information, or
-return a final answer.
-    
-To call a function, respond with a JSON object of the following format:
-
-{
-    "thought": "your thought about what to do",
-    "action": "the action to take, should be one of [{{tool_names}}]",
-    "arguments": {
-        "argument1": "argument_value",
-        "argument2": "argument_value"
-    }
-}
-
-To provide a final answer, response a JSON object of the following format:
-
-{
-  "thought": "I now know the final answer",
-  "final-answer": "the final answer to the original input question"
-}
-
-Previous steps are included in the input.  Each step has the following
-format in your output:
-
-{
-  "thought": "your thought about what to do",
-  "action": "the action taken",
-  "arguments": {
-      "argument1": action argument,
-      "argument2": action argument2
-  },
-  "observation": "the result of the action",
-}
-
-Respond by describing either one single thought/action/arguments or
-the final-answer.  Pause after providing one action or final-answer.
-
-{% if context %}Additional context has been provided:
-{{context}}{% endif %}
-
-Question: {{question}}
-
-Input:
-    
-{% for h in history %}
-{
-    "action": "{{h.action}}",
-    "arguments": [
-{% for k, v in h.arguments.items() %}        {
-            "{{k}}": "{{v}}",
-{%endfor%}        }
-    ],
-    "observation": "{{h.observation}}"
-}
-{% endfor %}"""
-
     def __init__(self, context, tools, additional_context=None):
         self.context = context
         self.tools = tools
@@ -89,15 +15,14 @@ Input:
 
     def reason(self, question, history):
 
-        tpl = ibis.Template(self.template)
-
         tools = self.tools
 
         tool_names = ",".join([
             t for t in self.tools.keys()
         ])
 
-        prompt = tpl.render({
+        variables = {
+            "question": question,
             "tools": [
                 {
                     "name": tool.name,
@@ -124,26 +49,21 @@ Input:
                     "observation": h.observation,
                 }
                 for h in history
-            ],
+            ]
-        })
+        }
 
-        print(prompt)
+        print(json.dumps(variables, indent=4), flush=True)
 
-        logger.info(f"prompt: {prompt}")
+        logger.info(f"prompt: {variables}")
 
-        resp = self.context.prompt.request(
+        obj = self.context.prompt.request(
-            "question",
+            "agent-react",
-            {
+            variables
-                "question": prompt
-            }
         )
 
-        resp = resp.replace("```json", "")
+        print(json.dumps(obj, indent=4), flush=True)
-        resp = resp.replace("```", "")
 
-        logger.info(f"response: {resp}")
+        logger.info(f"response: {obj}")
-
-        obj = json.loads(resp)
 
         if obj.get("final-answer"):