Merge pull request #421 from Pingdred/better_agent

Reactivated the hook agent_prompt_instructions

core/cat/looking_glass/agent_manager.py

@@ -1,11 +1,6 @@
-import re
-import traceback
-import json
-from copy import copy
-
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
-from langchain.agents import AgentExecutor, LLMSingleActionAgent, AgentOutputParser
+from langchain.agents import AgentExecutor, LLMSingleActionAgent
 
 from cat.looking_glass.prompts import ToolPromptTemplate
 from cat.looking_glass.output_parser import ToolOutputParser
@@ -33,7 +28,7 @@ def execute_tool_agent(self, agent_input, allowed_tools):
         allowed_tools_names = [t.name for t in allowed_tools]
 
         prompt = ToolPromptTemplate(
-            #template= TODO: get from hook,
+            template = self.cat.mad_hatter.execute_hook("agent_prompt_instructions"),
             tools=allowed_tools,
             # This omits the `agent_scratchpad`, `tools`, and `tool_names` variables because those are generated dynamically
             # This includes the `intermediate_steps` variable because it is needed to fill the scratchpad
@@ -109,21 +104,8 @@ def execute_agent(self, agent_input):
             return fast_reply
 
         prompt_prefix = mad_hatter.execute_hook("agent_prompt_prefix")
-        #prompt_format_instructions = mad_hatter.execute_hook("agent_prompt_instructions")
         prompt_suffix = mad_hatter.execute_hook("agent_prompt_suffix")
 
-        #input_variables = [
-        #    "input",
-        #    "chat_history",
-        #    "episodic_memory",
-        #    "declarative_memory",
-        #    "agent_scratchpad",
-        #]
-
-        #input_variables = mad_hatter.execute_hook("before_agent_creates_prompt", input_variables,
-         #                                         " ".join([prompt_prefix, prompt_format_instructions, prompt_suffix]))
-
-
         allowed_tools = mad_hatter.execute_hook("agent_allowed_tools")
 
         # Try to get information from tools if there is some allowed

core/cat/looking_glass/output_parser.py

@@ -1,7 +1,7 @@
 import re
 from langchain.agents import AgentOutputParser
 from langchain.schema import AgentAction, AgentFinish, OutputParserException
-from typing import List, Union
+from typing import Union
 
 
 class ToolOutputParser(AgentOutputParser):

core/cat/looking_glass/prompts.py

@@ -4,34 +4,9 @@
 from langchain.agents.tools import BaseTool
 from langchain.prompts import StringPromptTemplate
 
-# TODO: get by hook
-DEFAULT_TOOL_TEMPLATE = """Answer the following question: `{input}`
-You can only reply using these tools:
-
-{tools}
-none_of_the_others: none_of_the_others(None) - Use this tool if none of the others tools help. Input is always None.
-
-If you want to use tools, use the following format:
-Action: the name of the action to take, should be one of [{tool_names}]
-Action Input: the input to the action
-Observation: the result of the action
-...
-Action: the name of the action to take, should be one of [{tool_names}]
-Action Input: the input to the action
-Observation: the result of the action
-
-When you have a final answer respond with:
-Final Answer: the final answer to the original input question
-
-Begin!
-
-Question: {input}
-{agent_scratchpad}"""
-
-
 class ToolPromptTemplate(StringPromptTemplate):
     # The template to use
-    template: str = DEFAULT_TOOL_TEMPLATE
+    template: str
     # The list of tools available
     tools: List[BaseTool]
 

core/cat/mad_hatter/core_plugin/hooks/prompt.py

@@ -8,7 +8,6 @@
 from typing import List, Dict
 from datetime import timedelta
 from langchain.docstore.document import Document
-from langchain.agents.conversational import prompt
 
 from cat.utils import verbal_timedelta
 from cat.mad_hatter.decorators import hook
@@ -87,13 +86,32 @@ def agent_prompt_instructions(cat) -> str:
 
     """
 
-    # Check if procedural memory is disabled
-    prompt_settings = cat.working_memory["user_message_json"]["prompt_settings"]
-    if not prompt_settings["use_procedural_memory"]:
-        return ""
+    DEFAULT_TOOL_TEMPLATE = """Answer the following question: `{input}`
+    You can only reply using these tools:
+
+    {tools}
+    none_of_the_others: none_of_the_others(None) - Use this tool if none of the others tools help. Input is always None.
+
+    If you want to use tools, use the following format:
+    Action: the name of the action to take, should be one of [{tool_names}]
+    Action Input: the input to the action
+    Observation: the result of the action
+    ...
+    Action: the name of the action to take, should be one of [{tool_names}]
+    Action Input: the input to the action
+    Observation: the result of the action
+
+    When you have a final answer respond with:
+    Final Answer: the final answer to the original input question
+
+    Begin!
+
+    Question: {input}
+    {agent_scratchpad}"""
+
 
     # here we piggy back directly on langchain agent instructions. Different instructions will require a different OutputParser
-    return prompt.FORMAT_INSTRUCTIONS
+    return DEFAULT_TOOL_TEMPLATE
 
 
 @hook(priority=0)