txtchat is a framework for building conversational search and workflows. txtchat is open source under Apache 2.0 license and available on GitHub.

A set of intelligent agents are available to integrate with messaging platforms. These agents or personas are associated with an automated account and respond to messages with AI-powered responses. Workflows can use large language models (LLMs), small models or both.

https://preview.redd.it/uhypbdu0wbka1.png?width=1301&format=png&auto=webp&v=enabled&s=ccdfc7063cfc5a26086c869a7f539fa82c6fea73

A persona is a combination of a chat agent and workflow that determines the type of responses. Each agent is tied to an account in the messaging platform. Persona workflows are messaging-platform agnostic.

Examples

The following is a list of YouTube videos that shows how txtchat works. These videos run a series of queries with the Wikitalk persona. Wikitalk is a combination of a Wikipedia embeddings index and a LLM prompt to answer questions.

Every answer shows an associated reference with where the data came from. Wikitalk will say "I don't have data on that" when it doesn't have an answer.

History

Conversation with Wikitalk about history.

https://www.youtube.com/watch?v=ROyess8dLoA

Sports

Talk about sports.

https://youtube.com/watch?v=LXRB-iruKSc

Culture

Arts and culture questions.

https://www.youtube.com/watch?v=OkObkNhJIgk

Science

Let's quiz Wikitalk on science.

https://youtube.com/watch?v=-rsYDsZc9Wo

Summary

Not all workflows need a LLM. There are plenty of great small models available to perform a specific task. The Summary persona simply reads the input URL and summarizes the text.

https://youtube.com/watch?v=PBJm9aDqkn0

Mr. French

Like the summary persona, Mr. French is a simple persona that translates input text to French.

https://youtube.com/watch?v=4x8pOIm4rbo

Comments

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visarga t1_j9y7624 wrote on February 25, 2023 at 12:48 PM

#1,992,117

Does it do only one round of retrieval?

davidmezzetti OP t1_j9y7tmq wrote on February 25, 2023 at 12:55 PM

#1,992,252

Replying to visarga (#1,992,117)

With the current version, yes it runs an embeddings query for each message. I plan to handle threaded conversations shortly. In that scenario, the chat history will be provided to the prompt.

dancingnightly t1_ja2lfup wrote on February 26, 2023 at 11:00 AM

#2,020,329

Replying to davidmezzetti (#1,992,252)

Is this current version mostly RAG + WebGPT semantic search to GPT answer, then?

Big fan of your recent work.

SatoshiNotMe t1_ja2swra wrote on February 26, 2023 at 12:33 PM

#2,021,578

This is very interesting. Ignore the down-voters. Thank you for sharing 🙏

davidmezzetti OP t1_ja345mn wrote on February 26, 2023 at 2:20 PM

#2,023,773

Replying to dancingnightly (#2,020,329)

Thank you.

This application is RAG with a local vector index combined with a LLM from the FLAN-T5 series of models.

The whole solution can be locally hosted with no remote runtime API dependencies.

davidmezzetti OP t1_ja34bm6 wrote on February 26, 2023 at 2:22 PM

#2,023,802

Replying to SatoshiNotMe (#2,021,578)

Thanks, appreciate it. Not much I can do with down votes unless someone provides their rationale, which no one ever does.

SatoshiNotMe t1_ja3z3f2 wrote on February 26, 2023 at 5:53 PM

#2,029,558

Replying to davidmezzetti (#2,023,802)

You may get better discussion on HN. Speaking of which, I have a trove of HN discussion links bookmarked, and these are a goldmine of info. Would something like your approach work for “chatting” with these and getting useful answers?

davidmezzetti OP t1_ja44q0n wrote on February 26, 2023 at 6:30 PM

#2,030,606

Replying to SatoshiNotMe (#2,029,558)

Yes, the HN "chat" approach would work. There is a section in the README covering this. https://github.com/neuml/txtchat#connect-your-own-data

You would need to extract those comments and then load them into an Embeddings index.