ms per token,    88.13 tokens per second)    llama_print_timings:        eval time =  4772.57 ms /    93 runs   (   51.32 ms per token,    19.49 tokens per second)    llama_print_timings:       total time = 20959.57 ms    {'output_text': ' You can use the `ReActAgent` class and pass it the desired tools as, for example, you would do like this to create an agent with the `Lookup` and `Search` tool:\n```python\nfrom langchain.agents.react import ReActAgent\nfrom langchain.tools.lookup import Lookup\nfrom langchain.tools.search import Search\nReActAgent(Lookup(), Search())\n```'}Here's the trace RAG, showing the retrieved docs.PreviousRetrieval-augmented generation (RAG)NextUsing a RetrieverUse caseOverviewQuickstartLoadingSplittingRetrievalQAChatOpen source LLMsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
Open In Collab
Open In Collab ->: ms per token,    88.13 tokens per second)    llama_print_timings:        eval time =  4772.57 ms /    93 runs   (   51.32 ms per token,    19.49 tokens per second)    llama_print_timings:       total time = 20959.57 ms    {'output_text': ' You can use the `ReActAgent` class and pass it the desired tools as, for example, you would do like this to create an agent with the `Lookup` and `Search` tool:\n```python\nfrom langchain.agents.react import ReActAgent\nfrom langchain.tools.lookup import Lookup\nfrom langchain.tools.search import Search\nReActAgent(Lookup(), Search())\n```'}Here's the trace RAG, showing the retrieved docs.PreviousRetrieval-augmented generation (RAG)NextUsing a RetrieverUse caseOverviewQuickstartLoadingSplittingRetrievalQAChatOpen source LLMsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.