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Introduce Nebula LLM to LangChain (#8876) ## Description This PR adds Nebula to the available LLMs in LangChain. Nebula is an LLM focused on conversation understanding and enables users to extract conversation insights from video, audio, text, and chat-based conversations. These conversations can occur between any mix of human or AI participants. Examples of some questions you could ask Nebula from a given conversation are: - What could be the customer’s pain points based on the conversation? - What sales opportunities can be identified from this conversation? - What best practices can be derived from this conversation for future customer interactions? You can read more about Nebula here: https://symbl.ai/blog/extract-insights-symbl-ai-generative-ai-recall-ai-meetings/ #### Integration Test An integration test is added, but it requires network access. Since Nebula is fully managed like OpenAI, network access is required to exercise the integration test. #### Linting - [x] make lint - [x] make test (TODO: there seems to be a failure in another non-related test??? Need to check on this.) - [x] make format ### Dependencies No new dependencies were introduced. ### Twitter handle [@symbldotai](https://twitter.com/symbldotai) [@dvonthenen](https://twitter.com/dvonthenen) If you have any questions, please let me know. cc: @hwchase17, @baskaryan --------- Co-authored-by: dvonthenen <david.vonthenen@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>
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# Nebula
This page covers how to use [Nebula](https://symbl.ai/nebula), [Symbl.ai](https://symbl.ai/)'s LLM, ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific Nebula wrappers.
## Installation and Setup
Improvements in Nebula LLM (#9226) - Description: Added improvements in Nebula LLM to perform auto-retry; more generation parameters supported. Conversation is no longer required to be passed in the LLM object. Examples are updated. - Issue: N/A - Dependencies: N/A - Tag maintainer: @baskaryan - Twitter handle: symbldotai --------- Co-authored-by: toshishjawale <toshish@symbl.ai>
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- Get an [Nebula API Key](https://info.symbl.ai/Nebula_Private_Beta.html) and set as environment variable `NEBULA_API_KEY`
- Please see the [Nebula documentation](https://docs.symbl.ai/docs/nebula-llm) for more details.
- No time? Visit the [Nebula Quickstart Guide](https://docs.symbl.ai/docs/nebula-quickstart).
Introduce Nebula LLM to LangChain (#8876) ## Description This PR adds Nebula to the available LLMs in LangChain. Nebula is an LLM focused on conversation understanding and enables users to extract conversation insights from video, audio, text, and chat-based conversations. These conversations can occur between any mix of human or AI participants. Examples of some questions you could ask Nebula from a given conversation are: - What could be the customer’s pain points based on the conversation? - What sales opportunities can be identified from this conversation? - What best practices can be derived from this conversation for future customer interactions? You can read more about Nebula here: https://symbl.ai/blog/extract-insights-symbl-ai-generative-ai-recall-ai-meetings/ #### Integration Test An integration test is added, but it requires network access. Since Nebula is fully managed like OpenAI, network access is required to exercise the integration test. #### Linting - [x] make lint - [x] make test (TODO: there seems to be a failure in another non-related test??? Need to check on this.) - [x] make format ### Dependencies No new dependencies were introduced. ### Twitter handle [@symbldotai](https://twitter.com/symbldotai) [@dvonthenen](https://twitter.com/dvonthenen) If you have any questions, please let me know. cc: @hwchase17, @baskaryan --------- Co-authored-by: dvonthenen <david.vonthenen@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>
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### LLM
Improvements in Nebula LLM (#9226) - Description: Added improvements in Nebula LLM to perform auto-retry; more generation parameters supported. Conversation is no longer required to be passed in the LLM object. Examples are updated. - Issue: N/A - Dependencies: N/A - Tag maintainer: @baskaryan - Twitter handle: symbldotai --------- Co-authored-by: toshishjawale <toshish@symbl.ai>
2023-08-15 22:33:07 +00:00
There exists an Nebula LLM wrapper, which you can access with
Introduce Nebula LLM to LangChain (#8876) ## Description This PR adds Nebula to the available LLMs in LangChain. Nebula is an LLM focused on conversation understanding and enables users to extract conversation insights from video, audio, text, and chat-based conversations. These conversations can occur between any mix of human or AI participants. Examples of some questions you could ask Nebula from a given conversation are: - What could be the customer’s pain points based on the conversation? - What sales opportunities can be identified from this conversation? - What best practices can be derived from this conversation for future customer interactions? You can read more about Nebula here: https://symbl.ai/blog/extract-insights-symbl-ai-generative-ai-recall-ai-meetings/ #### Integration Test An integration test is added, but it requires network access. Since Nebula is fully managed like OpenAI, network access is required to exercise the integration test. #### Linting - [x] make lint - [x] make test (TODO: there seems to be a failure in another non-related test??? Need to check on this.) - [x] make format ### Dependencies No new dependencies were introduced. ### Twitter handle [@symbldotai](https://twitter.com/symbldotai) [@dvonthenen](https://twitter.com/dvonthenen) If you have any questions, please let me know. cc: @hwchase17, @baskaryan --------- Co-authored-by: dvonthenen <david.vonthenen@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>
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```python
from langchain.llms import Nebula
Improvements in Nebula LLM (#9226) - Description: Added improvements in Nebula LLM to perform auto-retry; more generation parameters supported. Conversation is no longer required to be passed in the LLM object. Examples are updated. - Issue: N/A - Dependencies: N/A - Tag maintainer: @baskaryan - Twitter handle: symbldotai --------- Co-authored-by: toshishjawale <toshish@symbl.ai>
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llm = Nebula()
Introduce Nebula LLM to LangChain (#8876) ## Description This PR adds Nebula to the available LLMs in LangChain. Nebula is an LLM focused on conversation understanding and enables users to extract conversation insights from video, audio, text, and chat-based conversations. These conversations can occur between any mix of human or AI participants. Examples of some questions you could ask Nebula from a given conversation are: - What could be the customer’s pain points based on the conversation? - What sales opportunities can be identified from this conversation? - What best practices can be derived from this conversation for future customer interactions? You can read more about Nebula here: https://symbl.ai/blog/extract-insights-symbl-ai-generative-ai-recall-ai-meetings/ #### Integration Test An integration test is added, but it requires network access. Since Nebula is fully managed like OpenAI, network access is required to exercise the integration test. #### Linting - [x] make lint - [x] make test (TODO: there seems to be a failure in another non-related test??? Need to check on this.) - [x] make format ### Dependencies No new dependencies were introduced. ### Twitter handle [@symbldotai](https://twitter.com/symbldotai) [@dvonthenen](https://twitter.com/dvonthenen) If you have any questions, please let me know. cc: @hwchase17, @baskaryan --------- Co-authored-by: dvonthenen <david.vonthenen@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>
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```
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