dosubot[bot]
commented
1 year ago Hi, @TransformerJialinWang! I'm Dosu, and I'm here to help the LangChain team manage their backlog. I wanted to let you know that we are marking this issue as stale.
From what I understand, the issue titled "TransformerJialinWang" is about bugs in the AutoGPT implementation. These bugs cause inconsistencies and misalignment in the output. The main goal is to fix the infinite loop and improve the structured output in local files. However, there hasn't been any activity or comments on this issue yet.
Before we proceed, we would like to confirm if this issue is still relevant to the latest version of the LangChain repository. If it is, please let us know by commenting on the issue. Otherwise, feel free to close the issue yourself, or the issue will be automatically closed in 7 days.
Thank you for your understanding and cooperation. We appreciate your contribution to the LangChain project!
Best regards, Dosu
System Info
AutoGPT on LangChain implementation has shown bugs in internal steps and file output processing phase. In particular, I noticed occasional inconsistencies within the internal processes of the AutoGPT implementation. These slight hitches, though infrequent, interrupt the seamless flow of operations. Also, in the file output processing phase, the actual data output seems to diverge from the expected format, hinting at a potential misalignment during the conversion or translation stages.
Who can help?
@TransformerJialinWang @alon
Information
Related Components
Reproduction
Define your embedding model
embeddings_model = OpenAIEmbeddings()
Initialize the vectorstore as empty
import faiss
embedding_size = 1536 #openai embeddings has 1536 dimensions index = faiss.IndexFlatL2(embedding_size) #Index that stores the full vectors and performs exhaustive search vectorstore = FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {})
agent = AutoGPT.from_llm_and_tools( ai_name="Tom", ai_role="Assistant", tools=tools, llm=ChatOpenAI(temperature=0), memory=vectorstore.as_retriever() )
Set verbose to be true
agent.chain.verbose = True
agent.run(["Recommend 5 best books to read in Python"])
Expected behavior
The primary goal is to solve the infinite loop in AutoGPT. The minor one is to provide structured output int local file.