Delete old folders (#21286)

Author: logan-markewich

README.md

@@ -8,13 +8,13 @@
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-LlamaIndex OSS (by [LlamaIndex](https://llamaindex.ai)) is an open-source framework to build agentic applications. **[Parse](https://cloud.llamaindex.ai)** is our enterprise platform for agentic OCR, parsing, extraction, indexing and more. You can use LlamaParse with this framework or on its own; see [LlamaParse](#llamacloud-document-agent-platform) below for signup and product links.
+LlamaIndex OSS (by [LlamaIndex](https://llamaindex.ai?utm_medium=li_github&utm_source=github&utm_campaign=2026--)) is an open-source framework to build agentic applications. **[Parse](https://cloud.llamaindex.ai?utm_medium=li_github&utm_source=github&utm_campaign=2026--)** is our enterprise platform for agentic OCR, parsing, extraction, indexing and more. You can use LlamaParse with this framework or on its own; see [LlamaParse](#llamacloud-document-agent-platform) below for signup and product links.
 
 > ### 📚 **Documentation:**
 >
-> - [LlamaParse](https://developers.llamaindex.ai/python/cloud/llamaparse/)
-> - [LlamaIndex OSS](https://developers.llamaindex.ai/python/framework/)
-> - [LlamaAgents](https://developers.llamaindex.ai/python/llamaagents/overview/)
+> - [LlamaParse](https://developers.llamaindex.ai/python/cloud/llamaparse/?utm_medium=li_github&utm_source=github&utm_campaign=2026--)
+> - [LlamaIndex OSS](https://developers.llamaindex.ai/python/framework/?utm_medium=li_github&utm_source=github&utm_campaign=2026--)
+> - [LlamaAgents](https://developers.llamaindex.ai/python/llamaagents/overview/?utm_medium=li_github&utm_source=github&utm_campaign=2026--)
 
 Building with LlamaIndex typically involves working with LlamaIndex core and a chosen set of integrations (or plugins). There are two ways to start building with LlamaIndex in
 Python:
@@ -46,16 +46,16 @@ from llama_index.llms.openai import OpenAI
 
 **LlamaParse** is its own platform—focused on document agents and agentic OCR. It includes **Parse** (parsing), **LlamaAgents** (deployed document agents), **Extract** (structured extraction), and **Index** (ingest and RAG). You can use it with the LlamaIndex framework or standalone.
 
-- **[Sign up for LlamaParse](https://cloud.llamaindex.ai/login)** — Create an account and get your API key.
-- **Parse** — Agentic OCR and document parsing (130+ formats). [Docs](https://developers.llamaindex.ai/python/cloud/llamaparse/) · [Parse in the cloud](https://cloud.llamaindex.ai/parse)
-- **Extract** — Structured data extraction from documents. [Docs](https://developers.llamaindex.ai/python/cloud/llamaextract/)
-- **Index** — Ingest, index, and RAG pipelines. [Docs](https://developers.llamaindex.ai/python/cloud/llamacloud/) · [Web UI](https://cloud.llamaindex.ai/)
-- **Split** — Split large documents into subcategories. [Docs](https://developers.llamaindex.ai/python/cloud/split/getting_started/)
-- **Agents** — Build end-to-end document agents with `Workflows` and Agent Builder. [Docs](https://developers.llamaindex.ai/python/llamaagents/overview/)
+- **[Sign up for LlamaParse](https://cloud.llamaindex.ai?utm_medium=li_github&utm_source=github&utm_campaign=2026--)** — Create an account and get your API key.
+- **Parse** — Agentic OCR and document parsing (130+ formats). [Docs](https://developers.llamaindex.ai/python/cloud/llamaparse/?utm_medium=li_github&utm_source=github&utm_campaign=2026--)
+- **Extract** — Structured data extraction from documents. [Docs](https://developers.llamaindex.ai/python/cloud/llamaextract/?utm_medium=li_github&utm_source=github&utm_campaign=2026--)
+- **Index** — Ingest, index, and RAG pipelines. [Docs](https://developers.llamaindex.ai/python/cloud/llamacloud/?utm_medium=li_github&utm_source=github&utm_campaign=2026--)
+- **Split** — Split large documents into subcategories. [Docs](https://developers.llamaindex.ai/python/cloud/split/getting_started/?utm_medium=li_github&utm_source=github&utm_campaign=2026--)
+- **Agents** — Build end-to-end document agents with `Workflows` and Agent Builder. [Docs](https://developers.llamaindex.ai/python/llamaagents/overview/?utm_medium=li_github&utm_source=github&utm_campaign=2026--)
 
 ### Important Links
 
-[Documentation](https://docs.llamaindex.ai/en/stable/)
+[Documentation](https://developers.llamaindex.ai/python/framework/?utm_medium=li_github&utm_source=github&utm_campaign=2026--)
 
 [X (formerly Twitter)](https://x.com/llama_index)
 
@@ -65,11 +65,6 @@ from llama_index.llms.openai import OpenAI
 
 [Discord](https://discord.gg/dGcwcsnxhU)
 
-### Ecosystem
-
-- LlamaHub [(community library of data loaders)](https://llamahub.ai)
-- LlamaLab [(cutting-edge AGI projects using LlamaIndex)](https://github.com/run-llama/llama-lab)
-
 ## 🚀 Overview
 
 **NOTE**: This README is not updated as frequently as the documentation. Please check out the documentation above for the latest updates!
@@ -103,7 +98,7 @@ New integrations should meaningfully integrate with existing LlamaIndex framewor
 
 ## 📄 Documentation
 
-Full documentation can be found [here](https://docs.llamaindex.ai/en/latest/)
+Full documentation can be found [here](https://developers.llamaindex.ai/python/framework/?utm_medium=li_github&utm_source=github&utm_campaign=2026--)
 
 Please check it out for the most up-to-date tutorials, how-to guides, references, and other resources!
 
@@ -113,7 +108,7 @@ Please check it out for the most up-to-date tutorials, how-to guides, references
 # custom selection of integrations to work with core
 pip install llama-index-core
 pip install llama-index-llms-openai
-pip install llama-index-llms-replicate
+pip install llama-index-llms-ollama
 pip install llama-index-embeddings-huggingface
 ```
 
@@ -132,29 +127,23 @@ documents = SimpleDirectoryReader("YOUR_DATA_DIRECTORY").load_data()
 index = VectorStoreIndex.from_documents(documents)
 ```
 
-To build a simple vector store index using non-OpenAI LLMs, e.g. Llama 2 hosted on [Replicate](https://replicate.com/), where you can easily create a free trial API token:
+To build a simple vector store index using non-OpenAI LLMs, e.g. LLMs hosted through Ollama:
 
 ```python
-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 llama_index.llms.ollama import Ollama
 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},
+Settings.llm = Ollama(
+    model="llama-3.1:latest",
+    request_timeout=360.0,
 )
 
 # set tokenizer to match LLM
 Settings.tokenizer = AutoTokenizer.from_pretrained(
-    "NousResearch/Llama-2-7b-chat-hf"
+    "meta-llama/Llama-3.1-8B-Instruct"
 )
 
 # set the embed model
@@ -193,18 +182,6 @@ storage_context = StorageContext.from_defaults(persist_dir="./storage")
 index = load_index_from_storage(storage_context)
 ```
 
-## 🔧 Dependencies
-
-We use poetry as the package manager for all Python packages. As a result, the
-dependencies of each Python package can be found by referencing the `pyproject.toml`
-file in each of the package's folders.
-
-```bash
-cd <desired-package-folder>
-pip install poetry
-poetry install --with dev
-```
-
 ## A note on Verification of Build Assets
 
 By default, `llama-index-core` includes a `_static` folder that contains the nltk and tiktoken cache that is included with the package installation. This ensures that you can easily run `llama-index` in environments with restrictive disk access permissions at runtime.