Update 2024-05-05-AI-Agents.md

_posts/2024-05-05-AI-Agents.md

@@ -6,7 +6,7 @@ category: [Lecture]
 tags: [jekyll, ai]
 ---
 
-Introduction to AI Agents, Langchain, LlamaIndex, SWE.
+Introduction to AI Agents, Langchain, SWE.
 
 ---
 ## AI Agents
@@ -126,53 +126,6 @@ Communicative Agents for “Mind” Exploration of Large Language Model Society<
 ---
 ## Frameworks
 
-### [LlamaIndex](https://www.llamaindex.ai/)
-**Code:** [https://github.com/run-llama/llama_index](https://github.com/run-llama/llama_index)<br>
-**Docs:** [](https://docs.llamaindex.ai/en/stable/)<br>
-![](https://docs.llamaindex.ai/en/stable/_static/getting_started/basic_rag.png)
-```
-import os
-
-os.environ["REPLICATE_API_TOKEN"] = "YOUR_REPLICATE_API_TOKEN"
-
-from llama_index.core import Settings, VectorStoreIndex, SimpleDirectoryReader
-from llama_index.embeddings.huggingface import HuggingFaceEmbedding
-from llama_index.llms.replicate import Replicate
-from transformers import AutoTokenizer
-
-# set the LLM
-llama2_7b_chat = "meta/llama-2-7b-chat:8e6975e5ed6174911a6ff3d60540dfd4844201974602551e10e9e87ab143d81e"
-Settings.llm = Replicate(
-    model=llama2_7b_chat,
-    temperature=0.01,
-    additional_kwargs={"top_p": 1, "max_new_tokens": 300},
-)
-
-# set tokenizer to match LLM
-Settings.tokenizer = AutoTokenizer.from_pretrained(
-    "NousResearch/Llama-2-7b-chat-hf"
-)
-
-# set the embed model
-Settings.embed_model = HuggingFaceEmbedding(
-    model_name="BAAI/bge-small-en-v1.5"
-)
-
-documents = SimpleDirectoryReader("YOUR_DATA_DIRECTORY").load_data()
-index = VectorStoreIndex.from_documents(
-    documents,
-)
-```
-```
-query_engine = index.as_query_engine()
-query_engine.query("YOUR_QUESTION")
-```
-By default, data is stored in-memory. To persist to disk (under ./storage):<br>
-```
-index.storage_context.persist()
-```
-
----
 ### [LangChain](https://github.com/langchain-ai/langchain)
 * [LangChain documents](https://js.langchain.com/docs/get_started/introduction)
 * [LangChain use-cases](https://js.langchain.com/docs/use_cases)