fix readme

README.md

@@ -14,61 +14,73 @@ With Synthesizer, users can:
 
 ---
 
-## Documentation
-
-For more detailed information, tutorials, and API references, please visit the official [Synthesizer Documentation](https://sciphi.readthedocs.io/en/latest/).
-
 ## Fast Setup
 
 ```bash
 pip install sciphi-synthesizer
 ```
-## Features
+
+### Using Synthesizer
+
+1. **Generate synthetic question-answer pairs**
+
+   ```bash
+   export SCIPHI_API_KEY=MY_SCIPHI_API_KEY
+   python -m synthesizer.scripts.data_augmenter run --dataset="wiki_qa"
+   ```
+
+   ```bash
+   tail augmented_output/config_name_eq_answer_question__dataset_name_eq_wiki_qa.jsonl
+   ```
+
+2. **Evaluate RAG pipeline performance**
+
+   ```bash
+   export SCIPHI_API_KEY=MY_SCIPHI_API_KEY
+   python -m synthesizer.scripts.rag_harness --rag_provider="agent-search" --llm_provider_name="sciphi" --n_samples=25
+   ```
+
+### Documentation
+
+For more detailed information, tutorials, and API references, please visit the official [Synthesizer Documentation](https://sciphi.readthedocs.io/en/latest/).
 
 ### Community & Support
 
 - Engage with our vibrant community on [Discord](https://discord.gg/j9GxfbxqAe).
 - For tailored inquiries or feedback, please [email us](mailto:[email protected]).
 
+### Developing with Synthesizer
 
-### Example
-
-The following example demonstrates how to construct a connection to the AgentSearch API with the synthesizer RAG interface. Then, the example goes on to use the RAG interface to generate a response with an OpenAI hosted LLM.
+Quickly set up RAG augmented generation with your choice of provider, from OpenAI, Anhtropic, vLLM, and SciPhi:
 
 ```python
-
-   from synthesizer.core import LLMProviderName, RAGProviderName
-   from synthesizer.interface import (
-      LLMInterfaceManager,
-      RAGInterfaceManager,
-   )
-   from synthesizer.llm import GenerationConfig
-
-   # RAG Provider Settings
-   rag_interface = RAGInterfaceManager.get_interface_from_args(
-      RAGProviderName(rag_provider_name),
-      api_base=rag_api_base,
-      limit_hierarchical_url_results=rag_limit_hierarchical_url_results,
-      limit_final_pagerank_results=rag_limit_final_pagerank_results,
-   )
-   rag_context = rag_interface.get_rag_context(query)
-
-   # LLM Provider Settings
-   llm_interface = LLMInterfaceManager.get_interface_from_args(
-      LLMProviderName(llm_provider_name),
-   )
-
-   generation_config = GenerationConfig(
-      model_name=llm_model_name,
-      max_tokens_to_sample=llm_max_tokens_to_sample,
-      temperature=llm_temperature,
-      top_p=llm_top_p,
-      # other generation params here ...
-   )
-
-   formatted_prompt = rag_prompt.format(rag_context=rag_context)
-   completion = llm_interface.get_completion(
-      formatted_prompt, generation_config
-   )
-   print(completion)
-```
+# Requires SCIPHI_API_KEY in env
+
+from synthesizer.core import LLMProviderName, RAGProviderName
+from synthesizer.interface import LLMInterfaceManager, RAGInterfaceManager
+from synthesizer.llm import GenerationConfig
+
+# RAG Provider Settings
+rag_interface = RAGInterfaceManager.get_interface_from_args(
+    RAGProviderName("agent-search"),
+    limit_hierarchical_url_results=rag_limit_hierarchical_url_results,
+    limit_final_pagerank_results=rag_limit_final_pagerank_results,
+)
+rag_context = rag_interface.get_rag_context(query)
+
+# LLM Provider Settings
+llm_interface = LLMInterfaceManager.get_interface_from_args(
+    LLMProviderName("openai"),
+)
+
+generation_config = GenerationConfig(
+    model_name=llm_model_name,
+    max_tokens_to_sample=llm_max_tokens_to_sample,
+    temperature=llm_temperature,
+    top_p=llm_top_p,
+    # other generation params here ...
+)
+
+formatted_prompt = raw_prompt.format(rag_context=rag_context)
+completion = llm_interface.get_completion(formatted_prompt, generation_config)
+```