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Author	SHA1	Message	Date
ccurme	7a922f3e48	core, openai: support custom token encoders (#20762 )	2024-04-23 13:57:05 +00:00
balloonio	e7b1a44c5b	community[patch]: Invoke callback prior to yielding token fix for Llamafile (#20365 ) - [x] PR title: community[patch]: Invoke callback prior to yielding token fix for Llamafile - [x] PR message: - Description: Invoke callback prior to yielding token in stream method in community llamafile.py - Issue: https://github.com/langchain-ai/langchain/issues/16913 - Dependencies: None - Twitter handle: @bolun_zhang If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17.	2024-04-12 19:26:12 +00:00
Kate Silverstein	0bc4a9b3fc	community[minor]: Adds Llamafile as an LLM (#17431 ) * Description: Adds a simple LLM implementation for interacting with [llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models. * Dependencies: N/A * Issue: N/A Detail [llamafile](https://github.com/Mozilla-Ocho/llamafile) lets you run LLMs locally from a single file on most computers without installing any dependencies. To use the llamafile LLM implementation, the user needs to: 1. Download a llamafile e.g. https://huggingface.co/jartine/TinyLlama-1.1B-Chat-v1.0-GGUF/resolve/main/TinyLlama-1.1B-Chat-v1.0.Q5_K_M.llamafile?download=true 2. Make the file executable. 3. Run the llamafile in 'server mode'. (All llamafiles come packaged with a lightweight server; by default, the server listens at `http://localhost:8080`.) ```bash wget https://url/of/model.llamafile chmod +x model.llamafile ./model.llamafile --server --nobrowser ``` Now, the user can invoke the LLM via the LangChain client: ```python from langchain_community.llms.llamafile import Llamafile llm = Llamafile() llm.invoke("Tell me a joke.") ```	2024-02-14 11:15:24 -08:00

Author

SHA1

Message

Date

ccurme

7a922f3e48

core, openai: support custom token encoders (#20762 )

2024-04-23 13:57:05 +00:00

balloonio

e7b1a44c5b

community[patch]: Invoke callback prior to yielding token fix for Llamafile (#20365 )

- [x] **PR title**: community[patch]: Invoke callback prior to yielding
token fix for Llamafile


- [x] **PR message**: 
- **Description:** Invoke callback prior to yielding token in stream
method in community llamafile.py
    - **Issue:** https://github.com/langchain-ai/langchain/issues/16913
    - **Dependencies:** None
    - **Twitter handle:** @bolun_zhang

If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.

2024-04-12 19:26:12 +00:00

Kate Silverstein

0bc4a9b3fc

community[minor]: Adds Llamafile as an LLM (#17431 )

* **Description:** Adds a simple LLM implementation for interacting with
[llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models.
* **Dependencies:** N/A
* **Issue:** N/A

**Detail**
[llamafile](https://github.com/Mozilla-Ocho/llamafile) lets you run LLMs
locally from a single file on most computers without installing any
dependencies.

To use the llamafile LLM implementation, the user needs to:

1. Download a llamafile e.g.
https://huggingface.co/jartine/TinyLlama-1.1B-Chat-v1.0-GGUF/resolve/main/TinyLlama-1.1B-Chat-v1.0.Q5_K_M.llamafile?download=true
2. Make the file executable.
3. Run the llamafile in 'server mode'. (All llamafiles come packaged
with a lightweight server; by default, the server listens at
`http://localhost:8080`.)


```bash
wget https://url/of/model.llamafile
chmod +x model.llamafile
./model.llamafile --server --nobrowser
```

Now, the user can invoke the LLM via the LangChain client:

```python
from langchain_community.llms.llamafile import Llamafile

llm = Llamafile()

llm.invoke("Tell me a joke.")
```

2024-02-14 11:15:24 -08:00

3 Commits