fix interface handling with generic model

refactor HTTP Client initialization

introduce a "Generic" model

This is basically an OpenAI implementation, which then can be reused by
most other providers since they usually implement a somewhat compatible
API. The API URL can be se

introduce a "Generic" model

This is basically an OpenAI implementation, which then can be reused by
most other providers since they usually implement a somewhat compatible
API. The API URL can be set manually so it should be easy to add new
unsupported providers.

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add remote component to ask questions to the bot

The endpoint allows to override model and language settings on demand.

Adjust OpenAI API calls. fixes #34

* max_token has been replaced by max_completion_tokens
* temperature setting is not suported by reasoning models

some model updates

still not 100% uptodate

updated model definitions

updated model lists

This adds a CLI tool to fetch some model data from @BerriAI/litellm

added gpt-4o

gpt-4-turbo is no longer in preview

added Voyage AI for embeddings

added model command to CLI

This prints info about the available models

clean up of the config options

Emojis are used to make the different options easier to distinguish

added Mistral to the list of models

move model configuration into json files

This removes the use of individual classes for each model in favor of
more general client classes that only get a model name passed. The meta
info about pric

move model configuration into json files

This removes the use of individual classes for each model in favor of
more general client classes that only get a model name passed. The meta
info about price and token limits is configured in a json file

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more refactoring on chat and embed model support

* differentiate between input and output tokens
* make use of much larger input contexts

first tries with Anthropic

Use interfaces for Chat and Embedding classes

This way it's easier to have a base OpenAI class. This also moves much
of the statistics and http handling into the base class making model
implementati

Use interfaces for Chat and Embedding classes

This way it's easier to have a base OpenAI class. This also moves much
of the statistics and http handling into the base class making model
implementations even leaner

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First start on refactoring the class hierarchy

This splits embedding models from chat completion models.

�� Automatic code style fixes

�� Automatic code style fixes

support GPT4

added helper to quickly check the available models

refactoring to make models selectable

This makes it much easier to add new models. Models can now be selected
via the configuration