create_structured_chat_agent

Prompt:

The prompt must have input keys: * tools: contains descriptions and arguments for each tool. * tool_names: contains all tool names. * agent_scratchpad: contains previous agent actions and tool outputs as a string.

Here's an example:

from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder

system = '''Respond to the human as helpfully and accurately as possible. You have access to the following tools:

{tools}

Use a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).

Valid "action" values: "Final Answer" or {tool_names}

Provide only ONE action per $JSON_BLOB, as shown:

```txt
{{
    "action": $TOOL_NAME,
    "action_input": $INPUT
}}

Follow this format:

Question: input question to answer Thought: consider previous and subsequent steps Action:

$JSON_BLOB

Observation: action result ... (repeat Thought/Action/Observation N times) Thought: I know what to respond Action:

{{
    "action": "Final Answer",
    "action_input": "Final response to human"
}}

Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use tools if necessary. Respond directly if appropriate. Format is Action:```$JSON_BLOB```then Observation'''

human = '''{input}

{agent_scratchpad}

(reminder to respond in a JSON blob no matter what)'''

prompt = ChatPromptTemplate.from_messages(
    [
        ("system", system),
        MessagesPlaceholder("chat_history", optional=True),
        ("human", human),
    ]
)