Dataherald · aazo11 · Sep 8, 2023 · Sep 14, 2023
diff --git a/docs/conf.py b/docs/conf.py
@@ -11,10 +11,11 @@
 
 sys.path.insert(0, os.path.abspath(".."))
 
-project = "Dataherald"
+project = "Dataherald AI"
 copyright = "2023, Dataherald"
 author = "Dataherald"
-release = "0.0.1"
+release = "main"
+html_title = project
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

diff --git a/docs/contributing.projects.rst b/docs/contributing.projects.rst
@@ -0,0 +1,2 @@
+Contributing
+====================
diff --git a/docs/envars.rst b/docs/envars.rst
@@ -0,0 +1,33 @@
+Environment Variables
+=======================
+
+
+# Openai info. All these fields are required for the engine to work.
+OPENAI_API_KEY = #This field is required for the engine to work.
+ORG_ID =
+LLM_MODEL = 'gpt-4-32k' #the openAI llm model that you want to use. possible values: gpt-4-32k, gpt-4, gpt-3.5-turbo, gpt-3.5-turbo-16k
+
+
+GOLDEN_RECORD_COLLECTION = 'my-golden-records'
+#Pinecone info. These fields are required if the vector store used is Pinecone
+PINECONE_API_KEY =
+PINECONE_ENVIRONMENT =
+
+# Module implementations to be used names for each required component. You can use the default ones or create your own
+API_SERVER = "dataherald.api.fastapi.FastAPI"
+SQL_GENERATOR = "dataherald.sql_generator.dataherald_sqlagent.DataheraldSQLAgent"
+EVALUATOR = "dataherald.eval.simple_evaluator.SimpleEvaluator"
+DB = "dataherald.db.mongo.MongoDB"
+VECTOR_STORE = 'dataherald.vector_store.chroma.Chroma' 
+CONTEXT_STORE = 'dataherald.context_store.default.DefaultContextStore' # Set a context store class, the default one is DefaultContextStore
+DB_SCANNER = 'dataherald.db_scanner.sqlalchemy.SqlAlchemyScanner'
+
+# mongo database information
+MONGODB_URI = "mongodb://admin:admin@mongodb:27017"
+MONGODB_DB_NAME = 'dataherald'
+MONGODB_DB_USERNAME = 'admin'
+MONGODB_DB_PASSWORD = 'admin'
+
+
+# The enncryption key is used to encrypt database connection info before storing in Mongo. Please refer to the README on how to set it.
+ENCRYPT_KEY = 
diff --git a/docs/getting_started.rst b/docs/getting_started.rst
diff --git a/docs/index.rst b/docs/index.rst
@@ -7,14 +7,45 @@ Dataherald AI
 ========================================
 Welcome to the official documentation page of the Dataherald AI engine. This documentation is intended for developers who want to:
 
-* Use the Dataherald AI engine to set up Natural Language interfaces from structured data in their own projects.
-* Contribute to the Dataherald AI engine.
+* 🖥️ Use the Dataherald AI engine to set up Natural Language interfaces from structured data in their own projects.
+* 🏍️ Contribute to the Dataherald AI engine.
 
 These documents will cover how to get started, how to set up an API from your database that can answer questions in plain English and how to extend the core engine's functionality.
 
+We also have an active Discord community you can join
+
+.. toctree::
+   :maxdepth: 1
+   :caption: Getting Started
+   :hidden:
+
+   introduction
+   quickstart
+
+
 .. toctree::
+   :caption: References
    :hidden:
 
-   getting_started
    api
-   modules
+   envars
+   modules
+
+.. toctree::
+   :caption: Tutorials
+   :hidden:
+
+   tutorial.sample_database
+   tutorial.finetune_sql_generator
+   tutorial.chatgpt_plugin
+
+
+.. toctree::
+   :caption: Contributing
+   :hidden:
+
+   contributing.projects
+
+
+
+
diff --git a/docs/introduction.rst b/docs/introduction.rst
@@ -12,8 +12,8 @@ You can use Dataherald to:
 
 Dataherald is built to:
 
-* Be modular, allowing different implementations of core modules to be plugged-in
-* Come batteries included: Have best-in-class implementations for modules like text to SQL, evaluation   
-* Be easy to set-up and use with major data warehouses
-* Allow for Active Learning, allowing you to improve the performance with usage
-* Be fast
+* 🔌 Be modular, allowing different implementations of core modules to be plugged-in
+* 🔋 Come batteries included: Have best-in-class implementations for modules like text to SQL, evaluation   
+* 📀 Be easy to set-up and use with major data warehouses 
+* 👨‍🏫 Allow for Active Learning, allowing you to improve the performance with usage 
+* 🏎️ Be fast 
diff --git a/docs/tutorial.chatgpt_plugin.rst b/docs/tutorial.chatgpt_plugin.rst
@@ -0,0 +1,4 @@
+Create a ChatGPT plug-in from your structured data
+=====================================================
+
+Coming soon ...
diff --git a/docs/tutorial.finetune_sql_generator.rst b/docs/tutorial.finetune_sql_generator.rst
@@ -0,0 +1,4 @@
+Using a Custom Text to SQL Engine
+==================================
+
+Coming soon ...
diff --git a/docs/tutorial.sample_database.rst b/docs/tutorial.sample_database.rst
@@ -0,0 +1,4 @@
+Setting up a sample Database for accurate NL-to-SQL
+====================================================
+
+Coming soon ...