Improve docs and nbs (#120)

automata/core/tools/builders/context_oracle.py

@@ -6,6 +6,7 @@
 from automata.core.agent.agent import AgentToolkitBuilder, AgentToolkitNames
 from automata.core.agent.providers import OpenAIAgentToolkitBuilder
 from automata.core.embedding.base import EmbeddingSimilarityCalculator
+from automata.core.experimental.search.symbol_search import SymbolSearch
 from automata.core.llm.providers.openai import OpenAITool
 from automata.core.memory_store.symbol_code_embedding import SymbolCodeEmbeddingHandler
 from automata.core.memory_store.symbol_doc_embedding import SymbolDocEmbeddingHandler
@@ -22,11 +23,13 @@ class ContextOracleToolkitBuilder(AgentToolkitBuilder):
 
     def __init__(
         self,
+        symbol_search: SymbolSearch,
         symbol_doc_embedding_handler: SymbolDocEmbeddingHandler,
         symbol_code_embedding_handler: SymbolCodeEmbeddingHandler,
         embedding_similarity_calculator: EmbeddingSimilarityCalculator,
         **kwargs,
     ) -> None:
+        self.symbol_search = symbol_search
         self.symbol_doc_embedding_handler = symbol_doc_embedding_handler
         self.symbol_code_embedding_handler = symbol_code_embedding_handler
         self.embedding_similarity_calculator = embedding_similarity_calculator
@@ -43,7 +46,7 @@ def build(self) -> List[Tool]:
             )
         ]
 
-    def _get_context(self, query: str, max_related_symbols=1) -> str:
+    def _get_context(self, query: str, max_related_symbols=10) -> str:
         """
         Retrieves the context corresponding to a given query.
 
@@ -55,24 +58,10 @@ def _get_context(self, query: str, max_related_symbols=1) -> str:
         results when populated for the relevant query. Thus, selecting the maximum will factor in documentation
         when populated.
         """
-        doc_embeddings = self.symbol_doc_embedding_handler.get_ordered_embeddings()
-        doc_search_results = self.embedding_similarity_calculator.calculate_query_similarity_dict(
-            doc_embeddings, query
-        )
-        code_embeddings = self.symbol_code_embedding_handler.get_ordered_embeddings()
-        code_search_results = self.embedding_similarity_calculator.calculate_query_similarity_dict(
-            code_embeddings, query
-        )
-        combined_results = {
-            key: max(doc_search_results.get(key, 0), code_search_results.get(key, 0))
-            for key in set(doc_search_results).union(code_search_results)
-        }
 
-        most_similar_symbols = [
-            ele[0] for ele in sorted(combined_results.items(), key=lambda x: -x[1])
-        ]
+        symbol_rank_search_results = self.symbol_search.symbol_rank_search(query)
 
-        most_similar_symbol = most_similar_symbols[0]
+        most_similar_symbol = symbol_rank_search_results[0][0]
 
         most_similar_code_embedding = self.symbol_code_embedding_handler.get_embedding(
             most_similar_symbol
@@ -84,7 +73,7 @@ def _get_context(self, query: str, max_related_symbols=1) -> str:
             most_similar_doc_embedding = self.symbol_doc_embedding_handler.get_embedding(
                 most_similar_symbol
             )
-            result += f"Documentation Summary:\n\n{most_similar_doc_embedding.summary}"
+            result += f"Documentation:\n\n{most_similar_doc_embedding.input_object}"
         except Exception as e:
             logger.error(
                 "Failed to get embedding for symbol %s with error: %s",
@@ -96,7 +85,7 @@ def _get_context(self, query: str, max_related_symbols=1) -> str:
 
             counter = 0
 
-            for symbol in most_similar_symbols:
+            for symbol in [symbol for symbol, _ in symbol_rank_search_results]:
                 if symbol == most_similar_symbol:
                     continue
                 if counter >= max_related_symbols:
@@ -114,7 +103,7 @@ def _get_context(self, query: str, max_related_symbols=1) -> str:
                         e,
                     )
                     continue
-
+        print("result = ", result)
         return result
 
 

automata/core/tools/factory.py

@@ -23,6 +23,7 @@ class AgentToolFactory:
         AgentToolkitNames.PY_WRITER: [("py_writer", PyWriter)],
         AgentToolkitNames.SYMBOL_SEARCH: [("symbol_search", SymbolSearch)],
         AgentToolkitNames.CONTEXT_ORACLE: [
+            ("symbol_search", SymbolSearch),
             ("symbol_doc_embedding_handler", SymbolDocEmbeddingHandler),
             ("symbol_code_embedding_handler", SymbolCodeEmbeddingHandler),
             ("embedding_similarity_calculator", EmbeddingSimilarityCalculator),

automata/docs/agent_guide.rst

@@ -0,0 +1,63 @@
+=================
+Agent Guide
+=================
+
+OpenAIAutomataAgentConfigBuilder
+================================
+
+Overview
+--------
+
+The OpenAIAutomataAgentConfigBuilder is used to build instances of AutomataAgents. It provides a flexible way to set different properties of the agent before instantiation. This class is a subclass of AgentConfigBuilder and belongs to the `automata.config.openai_agent` module.
+
+The builder takes an OpenAIAutomataAgentConfig object as an attribute, which holds various configuration settings for the agent. These settings can include the model, instruction version, system template formatter, etc. 
+
+You can use the `create_config` and `create_from_args` static methods to instantiate the OpenAIAutomataAgentConfig class. Individual properties of the agent can be set using the `with_*` methods. 
+
+Example
+-------
+
+.. code-block:: python
+
+   from automata.config.openai_agent import OpenAIAutomataAgentConfigBuilder
+   from automata.config.base import AgentConfigName
+
+   # Create an instance of OpenAIAutomataAgentConfig using create_config method
+   config = OpenAIAutomataAgentConfigBuilder.create_config(config_name=AgentConfigName.DEFAULT)
+
+   # Create an instance of OpenAIAutomataAgentConfigBuilder using with_model method
+   builder = OpenAIAutomataAgentConfigBuilder.with_model("gpt-4")
+
+
+OpenAIAutomataAgent
+===================
+
+Overview
+--------
+
+OpenAIAutomataAgent is an autonomous agent designed to execute instructions and report the results back to the main system. It uses the OpenAI API to generate responses based on given instructions and manages interactions with various tools.
+
+The agent operates in iterations and stops when it completes its task or exceeds the maximum iterations set in the configuration. OpenAIAutomataAgent uses tools that are instances of OpenAITool.
+
+Usage
+-----
+
+.. code-block:: python
+
+   from automata.core.agent.providers import OpenAIAutomataAgent
+   from automata.config.openai_agent import OpenAIAutomataAgentConfig
+
+   # Create OpenAIAutomataAgentConfig
+   config = OpenAIAutomataAgentConfig()
+
+   # Initialize OpenAIAutomataAgent
+   agent = OpenAIAutomataAgent('your_instructions', config)
+
+   # Run the agent
+   result = agent.run()
+
+Limitations
+-----------
+
+OpenAIAutomataAgent's full functionality depends on the integration with OpenAI API requirements and limitations. Improvements might be needed in logging and exception handling. It currently does not support multiple assistants.
+

automata/docs/conf.py

@@ -14,7 +14,7 @@
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
 
-extensions = []
+extensions = ["sphinx_panels", "sphinx_rtd_dark_mode"]
 
 templates_path = ["_templates"]
 exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
@@ -23,7 +23,8 @@
 
 
 # -- Options for HTML output -------------------------------------------------
-# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
+# https://www.sphinx-doc.org/en/master/usage/configurat3ion.html#options-for-html-output
+
+html_theme = "sphinx-rtd-dark-mode"
 
-html_theme = "sphinx_rtd_theme"
 html_static_path = ["_static"]

automata/docs/config/base/index.rst

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automata/docs/config/index.rst

@@ -1,11 +1,19 @@
-Config Modules
+Config Classes
 ==============
 
 **Automata** is a Python library for autonomous providers.
 
 Check out the :doc:`usage` section for further information, including
 how to :ref:`installation` the project.
 
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automata/docs/config/openai_agent/index.rst

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automata/docs/core/agent/agent/index.rst

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automata/docs/core/agent/index.rst

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automata/docs/core/agent/instances/index.rst

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automata/docs/core/base/database/index.rst

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automata/docs/core/base/index.rst

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automata/docs/core/base/patterns/index.rst

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automata/docs/core/code_handling/index.rst

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automata/docs/core/code_handling/py/index.rst

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automata/docs/core/code_handling/py/writer/index.rst

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automata/docs/core/context_providers/index.rst

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automata/docs/core/embedding/index.rst

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