Closed iplayfast closed 1 month ago
do mklink "llama/main" C:\Users\User\Desktop\Projects\llama\llama.cpp\build\bin\Release\main.exe in the cmd
remember to create the folder "llama" and copy the file "main.exe" into it.
NOTE: I am a confused idiot and this may be a completely wrong interpretation of what to do, as I have been running into problems with the OPENAI_API_KEY as well
What I did was changing this line cmd = cmd = ["llama/main", "-p", prompt]
to pointing to my llama model.
However, to fully run locally, you also need a embedding model like SBert bacause the default embedding model is OpenAI's ada model (cheap but still costs money).
I haven't been able to run things fully locally, but I think I am very close.
UPDATE: LangChain has updated the solution for babyAGI: https://python.langchain.com/en/latest/use_cases/agents/baby_agi.html
UPDATE2: My very rusty implementation with LangChain+llama+babyAGI https://github.com/ai8hyf/babyagi/blob/main/langChain-llama.py
@ai8hyf it would be great if you could share how you made run fully locally as soon as you get it done :) thx
What I did was changing this line
cmd = cmd = ["llama/main", "-p", prompt]
to pointing to my llama model. However, to fully run locally, you also need a embedding model like SBert bacause the default embedding model is OpenAI's ada model (cheap but still costs money). I haven't been able to run things fully locally, but I think I am very close.
I've already tried error:
raise ApiValueError('Unable to prepare type {} for serialization'.format(obj.class.name)) pinecone.core.client.exceptions.ApiValueError: Unable to prepare type ndarray for serialization
@ai8hyf it would be great if you could share how you made run fully locally as soon as you get it done :) thx
Just check this out: https://python.langchain.com/en/latest/use_cases/agents/baby_agi.html I think it solves all the problems here.
What I did was changing this line
cmd = cmd = ["llama/main", "-p", prompt]
to pointing to my llama model. However, to fully run locally, you also need a embedding model like SBert bacause the default embedding model is OpenAI's ada model (cheap but still costs money). I haven't been able to run things fully locally, but I think I am very close.I've already tried error:
raise ApiValueError('Unable to prepare type {} for serialization'.format(obj.class.name)) pinecone.core.client.exceptions.ApiValueError: Unable to prepare type ndarray for serialization
Check this implementation using LangChain: https://python.langchain.com/en/latest/use_cases/agents/baby_agi.html
@ai8hyf it would be great if you could share how you made run fully locally as soon as you get it done :) thx
Just check this out: https://python.langchain.com/en/latest/use_cases/agents/baby_agi.html I think it solves all the problems here.
Creates more problems because it is still needs the openai api and does not explain to how use local llama models instead.
@ai8hyf it would be great if you could share how you made run fully locally as soon as you get it done :) thx
Just check this out: https://python.langchain.com/en/latest/use_cases/agents/baby_agi.html I think it solves all the problems here.
Creates more problems because it is still needs the openai api and does not explain to how use local llama models instead.
I put together a very rough solution for langchain+llama+babyAGI. See my fork here: https://github.com/ai8hyf/babyagi/blob/main/langChain-llama.py
I'd love to get the llama code updated. The initial hack was based on building/running llama.cpp under Linux, so no support for Windows. Also, the embeddings are still based on OpenAI Ada, so OpenAI key is still needed.
But if you have improvements to fix those, I'd love to get a PR to integrate in.
I'd love to get the llama code updated. The initial hack was based on building/running llama.cpp under Linux, so no support for Windows. Also, the embeddings are still based on OpenAI Ada, so OpenAI key is still needed.
But if you have improvements to fix those, I'd love to get a PR to integrate in.
Sorry I don't have a Windows dev machine right now so I don't really know the situation with Windows. The embeddings are also from local llama cpp model (4096 size). The only 3rd-party API used in my code snippet was the SerpAPIWrapper. I basically used LangChain's official example (https://python.langchain.com/en/latest/use_cases/agents/baby_agi.html) and changed the models and embeddings to llama cpp.
@ai8hyf it would be great if you could share how you made run fully locally as soon as you get it done :) thx
Just check this out: https://python.langchain.com/en/latest/use_cases/agents/baby_agi.html I think it solves all the problems here.
Creates more problems because it is still needs the openai api and does not explain to how use local llama models instead.
I put together a very rough solution for langchain+llama+babyAGI. See my fork here: https://github.com/ai8hyf/babyagi/blob/main/langChain-llama.py
For whatever reason, I had to set embedding_size = 5120 for your script to work
@ai8hyf it would be great if you could share how you made run fully locally as soon as you get it done :) thx
Just check this out: https://python.langchain.com/en/latest/use_cases/agents/baby_agi.html I think it solves all the problems here.
Creates more problems because it is still needs the openai api and does not explain to how use local llama models instead.
I put together a very rough solution for langchain+llama+babyAGI. See my fork here: https://github.com/ai8hyf/babyagi/blob/main/langChain-llama.py
For whatever reason, I had to set embedding_size = 5120 for your script to work
ooof, I think that's because you are using a 13b model? Mine was based on the 7b model.
@ai8hyf it would be great if you could share how you made run fully locally as soon as you get it done :) thx
Just check this out: https://python.langchain.com/en/latest/use_cases/agents/baby_agi.html I think it solves all the problems here.
Creates more problems because it is still needs the openai api and does not explain to how use local llama models instead.
I put together a very rough solution for langchain+llama+babyAGI. See my fork here: https://github.com/ai8hyf/babyagi/blob/main/langChain-llama.py
First I would love to thank you for this implementation.
I have tried it but it didn't generate any response at all. I'm using gpt4all-lora-quantized-ggml.bin model.
Any idea why is that?
Can the readme be updated to explain how to interface with llama? I've tried ./babyagi.py -l llama -m models/ggml-vicuna-13b-4bit.bin Setting the .env OPENAI_API_KEY= OPENAI_API_MODEL=llama
As far as I know there is no OPENAI_API_KEY as it is run locally on my computer.