To expand on the last point, previously agents were allowed to potentially loop forever, whether caused maliciously or not Now you can specify a max_iterations parameter, which stops it after that many iterations https://
langchain.readthedocs.io/en/latest/exam
ples/agents/max_iterations.html
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AI
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LangChain Agents Max Iterations Parameter Implementation
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LangChain v0.052 Adds Watch Mode Tests Agent Security
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v0.052 Add watch mode for tests – @nfcampos Add schema property to SQL DB class – @diwanksingh Propagate verbose flag to combine-document chains – @parth_29 Add max_iterations kwarg to agent executor, in part to stop attacks like the below
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Displaying Intermediate Steps in Streamlit UI
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this is great! how did you get the intermediate steps to be printed to the streamlit UI? someone in the discord was just asking about this – i think its a great UX https://
discord.com/channels/10380
97195422978059/1057934201049055232/1058021225399582720
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Google’s PaLM: A 540B Parameter Language Model Explained
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— AI Breakfast (@AiBreakfast) 29 décembre 2022
You've heard a lot about ChatGPT But in the next few weeks, you'll start to hear about another model that could be 3x more powerful than ChatGPT: PaLM Google's Pathways Language Model (PaLM) a 540-billion parameter model trained with the Pathways system Here's what we know
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Visual Expression Evolution Told Through Artificial Intelligence
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WOOOOOW! La Evolución de la Expresión Visual, una historia contada con inteligencia artificial. Brutal. https://t.co/DN2gk54bbT
— Carlos Santana (@DotCSV) 29 décembre 2022WOOOOOW! La Evolución de la Expresión Visual, una historia contada con inteligencia artificial. Brutal.
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Get a complex SQL query from a simple natural request
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— Defend Intelligence (Anis Ayari) (@DFintelligence) 29 décembre 2022
And the best part is that I can just ask it naturally, queries like "yes give me the table of all PlayStations sold in the Netherlands to customers who have a loyalty card". And poof, 30 minutes of work saved with the right SQL query.
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Human becomes the machine’s debugger, paradox
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Well, of course he is sometimes mistaken (often he doesn't understand directly) but I clarify and give him an example and it's fine. So he must know what I do and debug his code. The human becomes a bit of the machine's debugger. That's paradoxical.
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Save 30 minutes of work by simply asking for an SQL query
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Et le must c’est que je peux juste lui demander naturellement après, les requêtes genre “oui donne moi la table de toutes les PlayStations vendu aux paybas à des clients qui ont la carte de fidélité”. Et pouf 30min de taff d’économiser avec la requête sql qui va bien. pic.twitter.com/IgOK0sYZkt
— Defend Intelligence (Anis Ayari) (@DFintelligence) 29 décembre 2022And the best part is that I can just naturally ask it afterwards, queries like 'yes give me the table of all PlayStations sold to the Netherlands to customers who have a loyalty card'. And poof, 30 minutes of work saved with the right SQL query.
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Magic SQL: queries generated from database schema
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For SQL it's magic. I give it the schema of my database (with descriptions). And it gives me everything I ask for. It remade my morning. No more deadly copy-pasting or checking column descriptions every two seconds.
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PaLM 540B Architecture Code Released Open Source
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Mola, pero… ¿quién tiene capacidad de entrenar un PaLM de 540 billions (x3 el tamaño de GPT-3)? Aquí están compartiendo el código de la arquitectura y no un modelo pre-entrenado. Con lo que es un entrénalo-tú-mismo de ChatGPT.