[Question]: Add chat history / GPTIndexChatMemory #8363
Replies: 6 comments
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@sorrentinopasquale Instead of Query Engine, you can use Chat Engine to track the history. Refer https://gpt-index.readthedocs.io/en/latest/core_modules/query_modules/chat_engines/root.html |
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@BharahthyKannan How can we use chatengine along with limiting GPT to the data we provide it only. |
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you can use vectordatabase that you store to the chatbot |
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Any idea how to use history while using graphs? Graphs do not have chat engine option, it only has query engine. |
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🤖 Hi, Thanks for reaching out. To implement chat history in LlamaIndex, you can use the from llama_index.llms.base import LLM
from llama_index.memory import BaseMemory, ChatMemoryBuffer
llm = LLM() # Initialize your LLM
memory = BaseMemory() # Initialize your memory
prefix_messages = [] # Initialize your prefix messages
chat_engine = SimpleChatEngine(llm, memory, prefix_messages) You can use the message = "Hello, world!"
chat_engine.chat(message) And you can retrieve the chat history using the history = chat_engine.chat_history In the provided context, the The Please note that the actual implementation of the If you're interested in more advanced chat history management, you might find these issues helpful:
These issues discuss different ways to manage chat history, including using a I hope this helps! Let me know if you have any other questions. Sources
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research. Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant. If you want to continue the conversation, start your reply with @dosu-bot. |
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🤖 Hi, Thanks for reaching out. To implement chat history in LlamaIndex, you can use the from llama_index.llms.base import LLM
from llama_index.memory import BaseMemory, ChatMemoryBuffer
llm = LLM() # Initialize your LLM
memory = BaseMemory() # Initialize your memory
prefix_messages = [] # Initialize your prefix messages
chat_engine = SimpleChatEngine(llm, memory, prefix_messages) You can use the message = "Hello, world!"
chat_engine.chat(message) And you can retrieve the chat history using the history = chat_engine.chat_history In the provided context, the The Please note that the actual implementation of the If you're interested in more advanced chat history management, you might find these issues helpful:
These issues discuss different ways to manage chat history, including using a I hope this helps! Let me know if you have any other questions. Sources
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research. Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant. If you want to continue the conversation, start your reply with @dosu-bot. |
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Question Validation
Question
Hi all,
I upgraded a couple of weeks ago to llama-index==0.6.37 and I would now like to implement the chat history, can you kindly support me? Do you have any reference or can lead me to docs? I saw some examples but they use OpenAIChat /agent_executor
Thanks
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