Add human message as input variable to chat agent prompt creation (#4542

)

# Add human message as input variable to chat agent prompt creation

This PR adds human message and system message input to
`CHAT_ZERO_SHOT_REACT_DESCRIPTION` agent, similar to [conversational
chat
agent](https://github.com/hwchase17/langchain/blob/7bcf238a1acf40aef21a5a198cf0e62d76f93c15/langchain/agents/conversational_chat/base.py#L64-L71).

I met this issue trying to use `create_prompt` function when using the
[BabyAGI agent with tools
notebook](https://python.langchain.com/en/latest/use_cases/autonomous_agents/baby_agi_with_agent.html),
since BabyAGI uses “task” instead of “input” input variable. For normal
zero shot react agent this is fine because I can manually change the
suffix to “{input}/n/n{agent_scratchpad}” just like the notebook, but I
cannot do this with conversational chat agent, therefore blocking me to
use BabyAGI with chat zero shot agent.

I tested this in my own project
[Chrome-GPT](https://github.com/richardyc/Chrome-GPT) and this fix
worked.

## Request for review
Agents / Tools / Toolkits
- @vowelparrot

langchain/agents/chat/base.py

@@ -4,7 +4,12 @@
 
 from langchain.agents.agent import Agent, AgentOutputParser
 from langchain.agents.chat.output_parser import ChatOutputParser
-from langchain.agents.chat.prompt import FORMAT_INSTRUCTIONS, PREFIX, SUFFIX
+from langchain.agents.chat.prompt import (
+    FORMAT_INSTRUCTIONS,
+    HUMAN_MESSAGE,
+    SYSTEM_MESSAGE_PREFIX,
+    SYSTEM_MESSAGE_SUFFIX,
+)
 from langchain.agents.utils import validate_tools_single_input
 from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.base import BaseCallbackManager
@@ -64,18 +69,26 @@ def _stop(self) -> List[str]:
     def create_prompt(
         cls,
         tools: Sequence[BaseTool],
-        prefix: str = PREFIX,
-        suffix: str = SUFFIX,
+        system_message_prefix: str = SYSTEM_MESSAGE_PREFIX,
+        system_message_suffix: str = SYSTEM_MESSAGE_SUFFIX,
+        human_message: str = HUMAN_MESSAGE,
         format_instructions: str = FORMAT_INSTRUCTIONS,
         input_variables: Optional[List[str]] = None,
     ) -> BasePromptTemplate:
         tool_strings = "\n".join([f"{tool.name}: {tool.description}" for tool in tools])
         tool_names = ", ".join([tool.name for tool in tools])
         format_instructions = format_instructions.format(tool_names=tool_names)
-        template = "\n\n".join([prefix, tool_strings, format_instructions, suffix])
+        template = "\n\n".join(
+            [
+                system_message_prefix,
+                tool_strings,
+                format_instructions,
+                system_message_suffix,
+            ]
+        )
         messages = [
             SystemMessagePromptTemplate.from_template(template),
-            HumanMessagePromptTemplate.from_template("{input}\n\n{agent_scratchpad}"),
+            HumanMessagePromptTemplate.from_template(human_message),
         ]
         if input_variables is None:
             input_variables = ["input", "agent_scratchpad"]
@@ -88,8 +101,9 @@ def from_llm_and_tools(
         tools: Sequence[BaseTool],
         callback_manager: Optional[BaseCallbackManager] = None,
         output_parser: Optional[AgentOutputParser] = None,
-        prefix: str = PREFIX,
-        suffix: str = SUFFIX,
+        system_message_prefix: str = SYSTEM_MESSAGE_PREFIX,
+        system_message_suffix: str = SYSTEM_MESSAGE_SUFFIX,
+        human_message: str = HUMAN_MESSAGE,
         format_instructions: str = FORMAT_INSTRUCTIONS,
         input_variables: Optional[List[str]] = None,
         **kwargs: Any,
@@ -98,8 +112,9 @@ def from_llm_and_tools(
         cls._validate_tools(tools)
         prompt = cls.create_prompt(
             tools,
-            prefix=prefix,
-            suffix=suffix,
+            system_message_prefix=system_message_prefix,
+            system_message_suffix=system_message_suffix,
+            human_message=human_message,
             format_instructions=format_instructions,
             input_variables=input_variables,
         )

langchain/agents/chat/prompt.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-PREFIX = """Answer the following questions as best you can. You have access to the following tools:"""
+SYSTEM_MESSAGE_PREFIX = """Answer the following questions as best you can. You have access to the following tools:"""
 FORMAT_INSTRUCTIONS = """The way you use the tools is by specifying a json blob.
 Specifically, this json should have a `action` key (with the name of the tool to use) and a `action_input` key (with the input to the tool going here).
 
@@ -26,4 +26,5 @@
 ... (this Thought/Action/Observation can repeat N times)
 Thought: I now know the final answer
 Final Answer: the final answer to the original input question"""
-SUFFIX = """Begin! Reminder to always use the exact characters `Final Answer` when responding."""
+SYSTEM_MESSAGE_SUFFIX = """Begin! Reminder to always use the exact characters `Final Answer` when responding."""
+HUMAN_MESSAGE = "{input}\n\n{agent_scratchpad}"