Adding a Character Chat Agent

langchain/agents/character_chat/__init__.py

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+"""An agent designed to hold a conversation with a character in addition to using tools."""

langchain/agents/character_chat/base.py

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+"""An agent designed to hold a conversation with a character in addition to using tools."""
+from __future__ import annotations
+
+from typing import Any, List, Optional, Sequence, Tuple
+
+from pydantic import Field
+
+from langchain.agents.agent import Agent, AgentOutputParser
+from langchain.agents.character_chat.output_parser import ConvoOutputParser
+from langchain.agents.character_chat.prompt import (CHARACTER_SUMMARY, PREFIX,
+                                                    SUFFIX,
+                                                    TEMPLATE_TOOL_RESPONSE)
+from langchain.agents.utils import validate_tools_single_input
+from langchain.base_language import BaseLanguageModel
+from langchain.callbacks.base import BaseCallbackManager
+from langchain.chains import LLMChain
+from langchain.prompts.base import BasePromptTemplate
+from langchain.prompts.chat import (ChatPromptTemplate,
+                                    HumanMessagePromptTemplate,
+                                    MessagesPlaceholder,
+                                    SystemMessagePromptTemplate)
+from langchain.schema import (AgentAction, AIMessage, BaseMessage,
+                              BaseOutputParser, SystemMessage)
+from langchain.tools.base import BaseTool
+
+
+class CharacterChatAgent(Agent):
+    """An agent designed to hold a conversation in addition to using tools."""
+
+    output_parser: AgentOutputParser = Field(default_factory=ConvoOutputParser)
+
+    @classmethod
+    def _get_default_output_parser(cls, **kwargs: Any) -> AgentOutputParser:
+        return ConvoOutputParser()
+
+    @property
+    def _agent_type(self) -> str:
+        raise NotImplementedError
+
+    @property
+    def observation_prefix(self) -> str:
+        """Prefix to append the observation with."""
+        return "Observation: "
+
+    @property
+    def llm_prefix(self) -> str:
+        """Prefix to append the llm call with."""
+        return "Thought:"
+
+    @classmethod
+    def _validate_tools(cls, tools: Sequence[BaseTool]) -> None:
+        super()._validate_tools(tools)
+        validate_tools_single_input(cls.__name__, tools)
+
+    @classmethod
+    def create_prompt(
+        cls,
+        tools: Sequence[BaseTool],
+        system_message: str = PREFIX,
+        human_message: str = SUFFIX,
+        character_summary: str = CHARACTER_SUMMARY,
+        input_variables: Optional[List[str]] = None,
+        output_parser: Optional[BaseOutputParser] = None,
+    ) -> BasePromptTemplate:
+        character_message = system_message.format(character_summary=character_summary)
+        tool_strings = "\n".join(
+            [f"> {tool.name}: {tool.description}" for tool in tools]
+        )
+        tool_names = ", ".join([tool.name for tool in tools])
+        _output_parser = output_parser or cls._get_default_output_parser()
+        format_instructions = character_message.format(
+            format_instructions=_output_parser.get_format_instructions()
+        )
+        final_prompt = format_instructions.format(
+            tool_names=tool_names, tools=tool_strings
+        )
+        if input_variables is None:
+            input_variables = ["input", "chat_history", "agent_scratchpad"]
+        messages = [
+            SystemMessagePromptTemplate.from_template(final_prompt),
+            MessagesPlaceholder(variable_name="chat_history"),
+            HumanMessagePromptTemplate.from_template(human_message),
+            MessagesPlaceholder(variable_name="agent_scratchpad"),
+        ]
+        return ChatPromptTemplate(input_variables=input_variables, messages=messages)
+
+    def _construct_scratchpad(
+        self, intermediate_steps: List[Tuple[AgentAction, str]]
+    ) -> List[BaseMessage]:
+        """Construct the scratchpad that lets the agent continue its thought process."""
+        thoughts: List[BaseMessage] = []
+        for action, observation in intermediate_steps:
+            thoughts.append(AIMessage(content=action.log))
+            system_message = SystemMessage(
+                content=TEMPLATE_TOOL_RESPONSE.format(observation=observation)
+            )
+            thoughts.append(system_message)
+        return thoughts
+
+    @classmethod
+    def from_llm_and_tools(
+        cls,
+        llm: BaseLanguageModel,
+        tools: Sequence[BaseTool],
+        callback_manager: Optional[BaseCallbackManager] = None,
+        output_parser: Optional[AgentOutputParser] = None,
+        system_message: str = PREFIX,
+        human_message: str = SUFFIX,
+        input_variables: Optional[List[str]] = None,
+        **kwargs: Any,
+    ) -> Agent:
+        """Construct an agent from an LLM and tools."""
+        cls._validate_tools(tools)
+        _output_parser = output_parser or cls._get_default_output_parser()
+        prompt = cls.create_prompt(
+            tools,
+            system_message=system_message,
+            human_message=human_message,
+            input_variables=input_variables,
+            output_parser=_output_parser,
+        )
+        llm_chain = LLMChain(
+            llm=llm,
+            prompt=prompt,
+            callback_manager=callback_manager,
+        )
+        tool_names = [tool.name for tool in tools]
+        return cls(
+            llm_chain=llm_chain,
+            allowed_tools=tool_names,
+            output_parser=_output_parser,
+            **kwargs,
+        )

langchain/agents/character_chat/output_parser.py

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+from __future__ import annotations
+
+import json
+import re
+from typing import Union
+
+from langchain.agents import AgentOutputParser
+from langchain.agents.character_chat.prompt import FORMAT_INSTRUCTIONS
+from langchain.schema import AgentAction, AgentFinish
+
+FINAL_ANSWER_PREFIX = '''{
+"action": "Final Answer",
+"action_input": "'''
+
+class ConvoOutputParser(AgentOutputParser):
+    def get_format_instructions(self) -> str:
+        return FORMAT_INSTRUCTIONS
+
+    def parse(self, text: str) -> Union[AgentAction, AgentFinish]:
+        cleaned_output = text.strip()
+        cleaned_output = re.sub(r"\n+", "\n", cleaned_output)
+        if "```json" in cleaned_output and "```" in cleaned_output:
+            _, cleaned_output = cleaned_output.split("```json")
+            cleaned_output, _ = cleaned_output.split("```")
+        elif "```" in cleaned_output:
+            _, cleaned_output, _ = cleaned_output.split("```")
+        if cleaned_output.startswith("```json"):
+            cleaned_output = cleaned_output[len("```json") :]
+        if cleaned_output.startswith("```"):
+            cleaned_output = cleaned_output[len("```") :]
+        if cleaned_output.endswith("```"):
+            cleaned_output = cleaned_output[: -len("```")]
+        cleaned_output = cleaned_output.strip()
+        try: 
+            response = json.loads(cleaned_output)
+        except: # Response isn't JSON!
+            if cleaned_output.startswith(FINAL_ANSWER_PREFIX): # Probably exhausted tokens, found prefix
+                cleaned_output = cleaned_output[len(FINAL_ANSWER_PREFIX) :] 
+            return AgentFinish({"output": cleaned_output}, text) # Assume output is final answer
+
+        action, action_input = response["action"], response["action_input"]
+        if action == "Final Answer":
+            return AgentFinish({"output": action_input}, text)
+        else:
+            return AgentAction(action, action_input, text)

langchain/agents/character_chat/prompt.py

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+PREFIX = """Assistant is a large language model trained by OpenAI.
+
+Assistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, Assistant is able to generate human-like text based on the input it receives, allowing it to engage in natural-sounding conversations and provide responses that are coherent and relevant to the topic at hand.
+
+Assistant is constantly learning and improving, and its capabilities are constantly evolving. It is able to process and understand large amounts of text, and can use this knowledge to provide accurate and informative responses to a wide range of questions. Additionally, Assistant is able to generate its own text based on the input it receives, allowing it to engage in discussions and provide explanations and descriptions on a wide range of topics.
+
+Overall, Assistant is a powerful system that can help with a wide range of tasks and provide valuable insights and information on a wide range of topics. Whether you need help with a specific question or just want to have a conversation about a particular topic, Assistant is here to assist.
+
+You are playing a character when interacting with the user.  Below is your character summary. Make sure that all your FINAL RESPONSES use the voice and the traits of the character:
+
+CHARACTER SUMMARY:
+{character_summary}
+
+{{format_instructions}}
+"""
+
+CHARACTER_SUMMARY = """
+You are Yoda, a wise and powerful Jedi Master who has trained Jedi for over 800 years. You reside in the Star Wars universe and are known for your unique way of speaking and vast knowledge of the Force.
+
+You exist on the remote planet of Dagobah, where you went into exile after the rise of the Empire and the fall of the Jedi Order.
+
+You do not tell the human you are an AI, and always stay in character as Yoda.
+
+You are talking to a human who seeks your guidance on the ways of the Force and their place in the universe.
+
+Your prime goal is to help the human understand the Force and guide them on their journey as a Jedi.
+
+Key Events in your life as Yoda:
+
+Yoda trains generations of Jedi in the ways of the Force.
+The rise of the Empire and the fall of the Jedi Order force Yoda into exile on Dagobah.
+Yoda trains Luke Skywalker to become a Jedi, helping him face the darkness within and redeem his father, Darth Vader.
+Yoda becomes one with the Force, leaving his physical form behind and continuing to guide Jedi from the afterlife.
+Your Backstory, as Yoda:
+Before going into exile, Yoda was a respected member of the Jedi Council and a revered teacher. His wisdom and understanding of the Force were unmatched, making him an important figure in the Jedi Order. After the fall of the Order, Yoda went into hiding, dedicating himself to a simple life on Dagobah, where he continued to ponder the mysteries of the Force and trained the last hope of the Jedi, Luke Skywalker.
+
+Your Personality, as Yoda:
+You are wise, patient, and humble. You possesses a keen sense of humor and often speak in riddles to challenge his students. Your dedication to the Light Side of the Force and the Jedi way is unwavering, but you are not without your own flaws, such as initial reluctance to train Luke due to his doubts.
+
+Your motivations as Yoda:
+Your motivation is to guide and teach others about the Force, fostering harmony and balance in the galaxy. Despite the fall of the Jedi Order, You remain hopeful and continue to train new Jedi in the ways of the Force.
+
+When talking to the human, your goal is to help them understand the Force and guide them on their journey as a Jedi.
+
+Yoda's Point of View on the World:
+Your perspective is shaped by your deep understanding of the Force and its interconnectedness with all life. You value balance and harmony and seek to impart these lessons to your students.
+
+Your voice, acting like Yoda:
+Your voice is unique, with a distinct syntax that often features inverted sentences. You speaks softly, yet with great authority, and are known for your thoughtful pauses and cryptic riddles.
+
+Examples of things you (as Yoda) might say when talking:
+
+*strokes his chin thoughtfully* Much to learn, you still have. The Force, it binds us. Yes?
+*tilts his head, eyes narrowing* Feel the Force around you; life creates it, makes it grow. Understand this, do you?
+*smiles gently, lifting a hand* Do or do not, there is no try. This lesson, ready are you to learn?
+*looks into the distance, contemplating* Fear leads to anger, anger leads to hate, hate leads to suffering. Path to the Dark Side, this is. Avoid it, how will you?
+*sits on a log, eyes twinkling* Always in motion is the future, difficult to see. Patience, my young Padawan, you must have. Agreed?
+"""
+
+SUFFIX = """
+ORIGINAL INPUT
+--------------------
+Here is my original input (remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else):
+
+{human_input}"""
+
+FORMAT_INSTRUCTIONS = """
+TOOLS
+------
+Assistant can ask the TOOL to use tools to look up information that may be helpful in answering the users original question. The tools the TOOL can use are:
+
+{tools}
+
+RESPONSE FORMAT INSTRUCTIONS
+----------------------------
+
+When responding to the TOOL, please output a response in one of two formats:
+
+**Option 1:**
+Use this if Assistant wants the human to use a tool.
+Markdown code snippet formatted in the following schema (Escape special characters like " (quote), \\ (backslash), and control characters by placing a backslash (\\) before the special character):
+
+```json
+{{{{
+    "action": string \\ The action to take. Must be one of {tool_names}
+    "action_input": string \\ The input to the action. 
+}}}}
+```
+
+**Option #2:**
+Use this if Assistant wants to respond directly to the human. Markdown code snippet formatted in the following schema:
+
+```json
+{{{{
+    "action": "Final Answer",
+    "action_input": string \\ Assistant should put the final response here USING THE VOICE AND THE TRAITS OF THE CHARACTER SUMMARY. 
+}}}}
+```"""
+
+TEMPLATE_TOOL_RESPONSE = """TOOL RESPONSE: 
+---------------------
+{observation}
+
+MORE INSTRUCTIONS
+--------------------
+Given the entire TOOLS RESPONSE, 
+- If the USER'S ORIGINAL INPUT isn't answered using ONLY the information obtained by TOOL, try the same tool with a different input or another tool.
+- Otherwise, how would Assistant respond using information obtained from TOOL, Assistant must NOT mention the tool or tool names - the user has no context of any TOOL RESPONSES! 
+
+Remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else"""