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Code Issues Packages Projects Releases Wiki Activity

Force List[Tuple[str,str]] to chat history widget (#12530)

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Co-authored-by: Bagatur <baskaryan@gmail.com>
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David Duong 2023-10-30 23:19:32 +01:00 committed by GitHub
parent d39b4b61b6
commit b5c17ff188
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3 changed files with 6 additions and 6 deletions
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4
templates/openai-functions-agent/openai_functions_agent/agent.py
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@ -5,7 +5,7 @@ from langchain.agents.format_scratchpad import format_to_openai_functions
from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser
from langchain.chat_models import ChatOpenAI from langchain.chat_models import ChatOpenAI
from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain.pydantic_v1 import BaseModel from langchain.pydantic_v1 import BaseModel, Field
from langchain.schema.messages import AIMessage, HumanMessage from langchain.schema.messages import AIMessage, HumanMessage
from langchain.tools.render import format_tool_to_openai_function from langchain.tools.render import format_tool_to_openai_function
from langchain.tools.tavily_search import TavilySearchResults from langchain.tools.tavily_search import TavilySearchResults
@ -57,7 +57,7 @@ agent = (
class AgentInput(BaseModel): class AgentInput(BaseModel):
input: str input: str
chat_history: List[Tuple[str, str]] chat_history: List[Tuple[str, str]] = Field(..., extra={"widget": {"type": "chat"}})
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True).with_types( agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True).with_types(

4
templates/rag-conversation/rag_conversation/chain.py
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@ -15,7 +15,7 @@ from langchain.schema.runnable import (
RunnablePassthrough, RunnablePassthrough,
) )
from langchain.vectorstores import Pinecone from langchain.vectorstores import Pinecone
from pydantic import BaseModel from pydantic import BaseModel, Field
if os.environ.get("PINECONE_API_KEY", None) is None: if os.environ.get("PINECONE_API_KEY", None) is None:
raise Exception("Missing `PINECONE_API_KEY` environment variable.") raise Exception("Missing `PINECONE_API_KEY` environment variable.")
@ -87,7 +87,7 @@ def _format_chat_history(chat_history: List[Tuple[str, str]]) -> List:
# User input # User input
class ChatHistory(BaseModel): class ChatHistory(BaseModel):
chat_history: List[Tuple[str, str]] chat_history: List[Tuple[str, str]] = Field(..., extra={"widget": {"type": "chat"}})
question: str question: str

4
templates/xml-agent/xml_agent/agent.py
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@ -3,7 +3,7 @@ from typing import List, Tuple
from langchain.agents import AgentExecutor from langchain.agents import AgentExecutor
from langchain.agents.format_scratchpad import format_xml from langchain.agents.format_scratchpad import format_xml
from langchain.chat_models import ChatAnthropic from langchain.chat_models import ChatAnthropic
from langchain.pydantic_v1 import BaseModel from langchain.pydantic_v1 import BaseModel, Field
from langchain.schema import AIMessage, HumanMessage from langchain.schema import AIMessage, HumanMessage
from langchain.tools import DuckDuckGoSearchRun from langchain.tools import DuckDuckGoSearchRun
from langchain.tools.render import render_text_description from langchain.tools.render import render_text_description
@ -44,7 +44,7 @@ agent = (
class AgentInput(BaseModel): class AgentInput(BaseModel):
question: str question: str
chat_history: List[Tuple[str, str]] chat_history: List[Tuple[str, str]] = Field(..., extra={"widget": {"type": "chat"}})
agent_executor = AgentExecutor( agent_executor = AgentExecutor(