LanceDB Assistant Bot With Swarm

Assistant Bot With Swarm

agentsllmsassistance-bot-with-swarmvector-databaselancedbgptopenaiAImultimodal-aimachine-learningembeddingsfine-tuningexamplesdeep-learninggpt-4-visionllama-indexragmultimodallangchainlancedb-recipes

alph-notebooks/lancedb-recipes / assistant_bot_with_swarm.ipynb

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Assistant bot with OpenAI's Swarm

This example shows a customer service bot that has two parts: one for interacting with users and another for providing help. It includes tools to assist in these tasks. The run_demo_loop function helps us create an interactive demo session.

Overview

The support bot has two main parts:

User Interface Agent: This part interacts with users at first and directs them to the help center based on what they need.
Help Center Agent: This part offers detailed help and support using various tools and is connected to a LanceDB VectorDB to retrieve documents.

Screenshot from 2024-10-24 11-47-07.png

Install requirements

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ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.
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set OPENAI Key as Env variable

[2]

Prepare and Ingest dataset

[3]

/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: 
The secret `HF_TOKEN` does not exist in your Colab secrets.
To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.
You will be able to reuse this secret in all of your notebooks.
Please note that authentication is recommended but still optional to access public models or datasets.
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Swarm Agents Implementation

[ ]

Starting Swarm CLI 🐝
User: What is the pricing of OpenAI API key?
User Interface Agent: OpenAI API pricing varies based on the specific API product and usage. Here are some general details:

1. **GPT-3.5 and GPT-4 API:**
   - These models are typically priced based on the number of tokens (words or word parts) processed in requests to the API.
   - The pricing might differ between tokens used in input and output.
   - Specific prices can be found on OpenAI's official pricing page or by contacting their sales team.

2. **Fine-Tuning:**
   - The costs for training custom models may involve additional fees, and variable pricing based on the model and data used for fine-tuning.

3. **Other Services:**
   - Other AI models and services provided by OpenAI might have different pricing structures.

Pricing can also depend on the level of access purchased (e.g., pay-as-you-go vs. committed use) and any relevant discounts for high volume usage or non-profit/educational purposes.

For exact, up-to-date pricing, you should consult OpenAI’s official website or directly reach out to their sales team.