towhee
litellm
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towhee | litellm | |
---|---|---|
26 | 28 | |
2,989 | 8,225 | |
2.4% | 30.4% | |
8.6 | 10.0 | |
3 months ago | 4 days ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
towhee
- FLaNK Stack Weekly for 14 Aug 2023
- Welcome to generate your embeddings with Towhee
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Vector database built for scalable similarity search
As another commenter noted, Milvus is overkill and a "bit much" if you're learning/playing.
A good intro to the field with progression towards a full Milvus implementation could be starting with towhee[0] (which is also supported by Milvus).
towhee has an example to do exactly what you want with CLIP[1].
[0] - https://towhee.io/
[1] - https://github.com/towhee-io/examples/tree/main/image/text_i...
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What Is DocArray?
The description of this is kind of confusing but I think the easiest way to understand it is that it is a data processing pipeline of sorts. Take unstructured data and apply transformation and computation. A similar project to this is Towhee (https://github.com/towhee-io/towhee). This project tries to simplify unstructured data processing and provides pretrained models and pipelines from their hub.
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[P] My co-founder and I quit our engineering jobs at AWS to build “Tensor Search”. Here is why.
Milvus also has incredible flexibility when it comes to choosing an indexing strategy, and we also have a library specifically meant to help vectorize a variety of data called Towhee (https://github.com/towhee-io/towhee).
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Deep Dive into Real-World Image Search Engine with Python
Benchmarking the models with towhee is as simple as:
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A quick tip on DataFrame.apply
The project's homepage is https://github.com/towhee-io/towhee, and you can find more about towhee by going through the documents.
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Build an Image Search Engine in Minutes
I made a tutorial for building an image search engine with python. The code example is as simple as 10 lines of code, using Towhee and Milvus To put images into the search engine:
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Any good libraries for feature extraction?
Traditionally, I've done this through PyTorch by adding a hook, but this requires knowledge of the model itself (i.e. model arch and layer names). I found https://github.com/Hironsan/awesome-embedding-models but it didn't provide many CV-focused open-source projects. There's also https://github.com/towhee-io/towhee which is great but more targeted towards application development.
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A python framework for unstructured data processing
You can check the result from the tutorial.
litellm
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Anthropic launches Tool Use (function calling)
There are a few libs that already abstract this away, for example:
- https://github.com/BerriAI/litellm
- https://jxnl.github.io/instructor/
- langchain
It's not hard for me to imagine a future where there is something like the CNCF for AI models, tools, and infra.
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Ask HN: Python Meta-Client for OpenAI, Anthropic, Gemini LLM and other API-s?
Hey, are you just looking for litellm - https://github.com/BerriAI/litellm
context - i'm the repo maintainer
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Voxos.ai – An Open-Source Desktop Voice Assistant
It should be possible using LiteLLM and a patch or a proxy.
https://github.com/BerriAI/litellm
- Show HN: Talk to any ArXiv paper just by changing the URL
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Integrate LLM Frameworks
This article will demonstrate how txtai can integrate with llama.cpp, LiteLLM and custom generation methods. For custom generation, we'll show how to run inference with a Mamba model.
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Is there any open source app to load a model and expose API like OpenAI?
I use this with ollama and works perfectly https://github.com/BerriAI/litellm
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OpenAI Switch Kit: Swap OpenAI with any open-source model
Another abstraction layer library is: https://github.com/BerriAI/litellm
For me the killer feature of a library like this would be if it implemented function calling. Even if it was for a very restricted grammar - like the traditional ReAct prompt:
Solve a question answering task with interleaving Thought, Action, Observation usteps. Thought can reason about the current situation, and Action can be three types:
- LibreChat
- LM Studio – Discover, download, and run local LLMs
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Please!!! Help me!!!! Open Interpreter. Chatgpt-4. Mac, Terminals.
Welcome to Open Interpreter. ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── ▌ OpenAI API key not found To use GPT-4 (recommended) please provide an OpenAI API key. To use Code-Llama (free but less capable) press enter. ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── OpenAI API key: [the API Key I inputed] Tip: To save this key for later, run export OPENAI_API_KEY=your_api_key on Mac/Linux or setx OPENAI_API_KEY your_api_key on Windows. ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── ▌ Model set to GPT-4 Open Interpreter will require approval before running code. Use interpreter -y to bypass this. Press CTRL-C to exit. > export OPENAI_API_KEY=your_api_key Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True'. Traceback (most recent call last): File "/Library/Frameworks/Python.framework/Versions/3.12/bin/interpreter", line 8, in sys.exit(cli()) ^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/core.py", line 22, in cli cli(self) File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/cli/cli.py", line 254, in cli interpreter.chat() File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/core.py", line 76, in chat for _ in self._streaming_chat(message=message, display=display): File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/core.py", line 97, in _streaming_chat yield from terminal_interface(self, message) File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/terminal_interface/terminal_interface.py", line 62, in terminal_interface for chunk in interpreter.chat(message, display=False, stream=True): File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/core.py", line 105, in _streaming_chat yield from self._respond() File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/core.py", line 131, in _respond yield from respond(self) File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/core/respond.py", line 61, in respond for chunk in interpreter._llm(messages_for_llm): File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/interpreter/llm/setup_openai_coding_llm.py", line 94, in coding_llm response = litellm.completion(**params) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/utils.py", line 792, in wrapper raise e File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/utils.py", line 751, in wrapper result = original_function(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/timeout.py", line 53, in wrapper result = future.result(timeout=local_timeout_duration) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 456, in result return self.__get_result() ^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result raise self._exception File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/timeout.py", line 42, in async_func return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/main.py", line 1183, in completion raise exception_type( ^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/utils.py", line 2959, in exception_type raise e File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/utils.py", line 2355, in exception_type raise original_exception File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/main.py", line 441, in completion raise e File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/litellm/main.py", line 423, in completion response = openai.ChatCompletion.create( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/openai/api_resources/chat_completion.py", line 25, in create return super().create(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/openai/api_resources/abstract/engine_api_resource.py", line 155, in create response, _, api_key = requestor.request( ^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/openai/api_requestor.py", line 299, in request resp, got_stream = self._interpret_response(result, stream) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/openai/api_requestor.py", line 710, in _interpret_response self._interpret_response_line( File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/openai/api_requestor.py", line 775, in _interpret_response_line raise self.handle_error_response( openai.error.InvalidRequestError: The model `gpt-4` does not exist or you do not have access to it. Learn more: https://help.openai.com/en/articles/7102672-how-can-i-access-gpt-4.
What are some alternatives?
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
Milvus - A cloud-native vector database, storage for next generation AI applications
FastChat - An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
examples - Analyze the unstructured data with Towhee, such as reverse image search, reverse video search, audio classification, question and answer systems, molecular search, etc.
LocalAI - :robot: The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. It allows to generate Text, Audio, Video, Images. Also with voice cloning capabilities.
PySceneDetect - :movie_camera: Python and OpenCV-based scene cut/transition detection program & library.
dify - Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
AI - Artificial Intelligence Projects
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
pgvector - Open-source vector similarity search for Postgres
libsql - libSQL is a fork of SQLite that is both Open Source, and Open Contributions.