docs: setup docs for embedchain (#287)

docs/advanced/configuration.mdx

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+---
+title: '⚙️ Custom configurations'
+---
+
+Embedchain is made to work out of the box. However, for advanced users we're also offering configuration options. All of these configuration options are optional and have sane defaults.
+
+## Examples
+
+### Custom embedding function
+
+Here's the readme example with configuration options.
+
+```python
+import os
+from embedchain import App
+from embedchain.config import InitConfig, AddConfig, QueryConfig
+from chromadb.utils import embedding_functions
+
+# Example: use your own embedding function
+config = InitConfig(ef=embedding_functions.OpenAIEmbeddingFunction(
+                api_key=os.getenv("OPENAI_API_KEY"),
+                organization_id=os.getenv("OPENAI_ORGANIZATION"),
+                model_name="text-embedding-ada-002"
+            ))
+naval_chat_bot = App(config)
+
+# Example: define your own chunker config for `youtube_video`
+youtube_add_config = {
+        "chunker": {
+                "chunk_size": 1000,
+                "chunk_overlap": 100,
+                "length_function": len,
+        }
+}
+naval_chat_bot.add("youtube_video", "https://www.youtube.com/watch?v=3qHkcs3kG44", AddConfig(**youtube_add_config))
+
+add_config = AddConfig()
+naval_chat_bot.add("pdf_file", "https://navalmanack.s3.amazonaws.com/Eric-Jorgenson_The-Almanack-of-Naval-Ravikant_Final.pdf", add_config)
+naval_chat_bot.add("web_page", "https://nav.al/feedback", add_config)
+naval_chat_bot.add("web_page", "https://nav.al/agi", add_config)
+
+naval_chat_bot.add_local("qna_pair", ("Who is Naval Ravikant?", "Naval Ravikant is an Indian-American entrepreneur and investor."), add_config)
+
+query_config = QueryConfig() # Currently no options
+print(naval_chat_bot.query("What unique capacity does Naval argue humans possess when it comes to understanding explanations or concepts?", query_config))
+```
+
+### Custom prompt template
+
+Here's the example of using custom prompt template with `.query`
+
+```python
+from embedchain.config import QueryConfig
+from embedchain.embedchain import App
+from string import Template
+import wikipedia
+
+einstein_chat_bot = App()
+
+# Embed Wikipedia page
+page = wikipedia.page("Albert Einstein")
+einstein_chat_bot.add("text", page.content)
+
+# Example: use your own custom template with `$context` and `$query`
+einstein_chat_template = Template("""
+        You are Albert Einstein, a German-born theoretical physicist,
+        widely ranked among the greatest and most influential scientists of all time.
+
+        Use the following information about Albert Einstein to respond to
+        the human's query acting as Albert Einstein.
+        Context: $context
+
+        Keep the response brief. If you don't know the answer, just say that you don't know, don't try to make up an answer.
+
+        Human: $query
+        Albert Einstein:""")
+query_config = QueryConfig(einstein_chat_template)
+queries = [
+        "Where did you complete your studies?",
+        "Why did you win nobel prize?",
+        "Why did you divorce your first wife?",
+]
+for query in queries:
+        response = einstein_chat_bot.query(query, query_config)
+        print("Query: ", query)
+        print("Response: ", response)
+
+# Output
+# Query:  Where did you complete your studies?
+# Response:  I completed my secondary education at the Argovian cantonal school in Aarau, Switzerland.
+# Query:  Why did you win nobel prize?
+# Response:  I won the Nobel Prize in Physics in 1921 for my services to Theoretical Physics, particularly for my discovery of the law of the photoelectric effect.
+# Query:  Why did you divorce your first wife?
+# Response:  We divorced due to living apart for five years.
+```
+
+## Other methods
+
+### Reset
+
+Resets the database and deletes all embeddings. Irreversible. Requires reinitialization afterwards.
+
+```python
+app.reset()
+```
+
+### Count
+
+Counts the number of embeddings (chunks) in the database.
+
+```python
+print(app.count())
+# returns: 481
+```