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bc7e56e8df
Supporting asyncio in langchain primitives allows for users to run them concurrently and creates more seamless integration with asyncio-supported frameworks (FastAPI, etc.) Summary of changes: **LLM** * Add `agenerate` and `_agenerate` * Implement in OpenAI by leveraging `client.Completions.acreate` **Chain** * Add `arun`, `acall`, `_acall` * Implement them in `LLMChain` and `LLMMathChain` for now **Agent** * Refactor and leverage async chain and llm methods * Add ability for `Tools` to contain async coroutine * Implement async SerpaPI `arun` Create demo notebook. Open questions: * Should all the async stuff go in separate classes? I've seen both patterns (keeping the same class and having async and sync methods vs. having class separation) |
1 year ago | |
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| .. | ||
| api | 1 year ago | |
| chat_vector_db | 1 year ago | |
| combine_documents | 1 year ago | |
| conversation | 1 year ago | |
| hyde | 1 year ago | |
| llm_bash | 1 year ago | |
| llm_checker | 1 year ago | |
| llm_math | 1 year ago | |
| natbot | 1 year ago | |
| pal | 1 year ago | |
| qa_with_sources | 1 year ago | |
| question_answering | 1 year ago | |
| sql_database | 1 year ago | |
| summarize | 1 year ago | |
| vector_db_qa | 1 year ago | |
| __init__.py | 1 year ago | |
| base.py | 1 year ago | |
| llm.py | 1 year ago | |
| llm_requests.py | 1 year ago | |
| loading.py | 1 year ago | |
| mapreduce.py | 1 year ago | |
| moderation.py | 1 year ago | |
| sequential.py | 1 year ago | |
| transform.py | 2 years ago | |