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github.com/coleam00/ottomator-agents
/ functions
Functions
1,846 in github.com/coleam00/ottomator-agents
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Functions
1,846
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Types & classes
402
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Endpoints
53
↓ 2 callers
Function
initialize_db
Initialize database connection pool.
docling-rag-agent/rag_agent.py:27
↓ 2 callers
Function
initialize_db
Initialize database connection pool.
docling-rag-agent/cli.py:43
↓ 2 callers
Function
initialize_db
Initialize database connection pool.
all-rag-strategies/implementation/rag_agent.py:27
↓ 2 callers
Function
initialize_db
Initialize database connection pool.
all-rag-strategies/implementation/cli.py:43
↓ 2 callers
Function
initialize_graph
Initialize graph client.
agentic-rag-knowledge-graph/agent/graph_utils.py:360
↓ 2 callers
Function
is_an_url
Returns True if the string is an URL
genericsuite-app-maker-agent/lib/codegen_utilities.py:110
↓ 2 callers
Function
list_documents_tool
List available documents. Args: input_data: Listing parameters Returns: List of document metadata
agentic-rag-knowledge-graph/agent/tools.py:241
↓ 2 callers
Method
load_servers
Load server configuration from a JSON file (typically mcp_config.json) and creates an instance of each server (no active connection until 'sta
pydantic-ai-mcp-agent/extras/experimental_mcp_client.py:28
↓ 2 callers
Function
log_memory
(prefix: str = "")
crawl4AI-agent-v2/crawl4AI-examples/3-crawl_sitemap_in_parallel.py:23
↓ 2 callers
Method
process_file
Process a document file, extract text, generate chunks and embeddings. Args: file_path: Path to the document fil
foundational-rag-agent/document_processing/ingestion.py:62
↓ 2 callers
Function
process_files_to_string
Convert a list of files with base64 content into a formatted string.
file-agent/file_agent.py:95
↓ 2 callers
Function
process_files_to_string
Convert a list of files with base64 content into a formatted string using MarkItDown.
ottomarkdown-agent/file_agent.py:193
↓ 2 callers
Method
prompt_enhancer
Perform a prompt enhancement request
genericsuite-app-maker-agent/lib/codegen_ai_abstracts.py:182
↓ 2 callers
Method
query
Abstract method for querying the LLM
genericsuite-app-maker-agent/lib/codegen_ai_abstracts.py:121
↓ 2 callers
Method
query
Abstract method for querying the LLM
genericsuite-app-maker-agent/lib/codegen_ai_utilities.py:53
↓ 2 callers
Method
query_custom_llm
(self, prompt: str, **kwargs: Any)
genericsuite-app-maker-agent/lib/codegen_llamaindex_abstraction.py:78
↓ 2 callers
Method
query_from_text_model
( self, prompt: str, question: str, prompt_enhancement_text: str = None,
genericsuite-app-maker-agent/lib/codegen_ai_abstracts.py:164
↓ 2 callers
Method
receive_messages
Receive streaming messages from the Claude SDK. Yields: Messages from the SDK (AssistantMessage, ToolUseBlock, etc.)
claude-agent-sdk-demos/PRPs/examples/ai_docs/claude_sdk_wrapper.py:145
↓ 2 callers
Method
reset_suggestions_prompt
Reset the suggestions prompt
genericsuite-app-maker-agent/lib/codegen_streamlit_lib.py:244
↓ 2 callers
Function
run_agent
Run the agent with streaming text for the user_input prompt, while maintaining the entire conversation in `st.session_state.messages`.
genericsuite-app-maker-agent/gsam_ottomator_agent/gsam_agent_lib.py:140
↓ 2 callers
Function
save_conversation_turn
Save a conversation turn to the database. Args: session_id: Session ID user_message: User's message assistant_me
agentic-rag-knowledge-graph/agent/api.py:253
↓ 2 callers
Method
save_item
Save the item in the database
genericsuite-app-maker-agent/lib/codegen_db.py:46
↓ 2 callers
Method
save_result
Saves the final result to a file
genericsuite-app-maker-agent/lib/codegen_schema_generator.py:482
↓ 2 callers
Function
save_session
Save session ID for a conversation.
claude-agent-sdk-demos/obsidian_integration/api_server.py:89
↓ 2 callers
Method
set_new_id
Set the new id global variable
genericsuite-app-maker-agent/lib/codegen_streamlit_lib.py:61
↓ 2 callers
Method
show_button_of_type
Show a button based on the button_config Args: button_config (dict): button configuration {
genericsuite-app-maker-agent/lib/codegen_streamlit_lib.py:761
↓ 2 callers
Method
show_cloud_resource
(self, url: str, resource_type: str)
genericsuite-app-maker-agent/lib/codegen_streamlit_lib.py:526
↓ 2 callers
Method
show_conversation_content
Show the conversation content
genericsuite-app-maker-agent/lib/codegen_streamlit_lib.py:553
↓ 2 callers
Method
show_conversation_question
(self, id: str)
genericsuite-app-maker-agent/lib/codegen_streamlit_lib.py:636
↓ 2 callers
Method
show_gallery
Show the gallery of videos or images
genericsuite-app-maker-agent/lib/codegen_streamlit_lib.py:1591
↓ 2 callers
Method
show_one_suggestion
Show one suggestion in the main section
genericsuite-app-maker-agent/lib/codegen_streamlit_lib.py:320
↓ 2 callers
Method
start
Starts each MCP server and returns the tools for each server formatted for Pydantic AI.
pydantic-ai-mcp-agent/extras/experimental_mcp_client.py:40
↓ 2 callers
Method
store_document_chunk
Store a document chunk with its embedding in Supabase. Args: url: Source URL or identifier for the document
foundational-rag-agent/database/setup.py:45
↓ 2 callers
Function
store_message
Store a message in the database.
TinyDM-agent/database.py:20
↓ 2 callers
Function
store_message
Store a message in the messages table.
genericsuite-app-maker-agent/gsam_ottomator_agent/gsam_postgres_agent.py:107
↓ 2 callers
Function
store_message
Store a message in the Supabase messages table.
nba-agent/agent_trial/nba_agent_1.py:848
↓ 2 callers
Function
store_message
Store a message in the messages table.
~sample-python-agent~/sample_postgres_agent.py:92
↓ 2 callers
Function
store_message
(session_id: str, message_type: str, content: str, data: Optional[dict] = None)
youtube-summary-agent/main.py:60
↓ 2 callers
Function
summarize_text
Summarizes the transcript using OpenAI GPT, with video metadata for context.
youtube-summary-agent/main.py:182
↓ 2 callers
Function
test_connection
Test database connection. Returns: True if connection successful
agentic-rag-knowledge-graph/agent/db_utils.py:500
↓ 2 callers
Function
test_graph_connection
Test graph database connection. Returns: True if connection successful
agentic-rag-knowledge-graph/agent/graph_utils.py:434
↓ 2 callers
Method
toggle_server_status
Enable or disable specific MCP servers. Args: server_names (List[str]): List of server names to toggle. enab
thirdbrain-mcp-openai-agent/mcp_client.py:446
↓ 2 callers
Method
video_gen
Perform a video generation request
genericsuite-app-maker-agent/lib/codegen_ai_utilities.py:151
↓ 2 callers
Method
video_gen_followup
Perform a video generation request check
genericsuite-app-maker-agent/lib/codegen_ai_utilities.py:175
↓ 2 callers
Method
video_generation
( self, question: str = None, previous_response: dict = None, settings: dict =
genericsuite-app-maker-agent/lib/codegen_general_lib.py:774
↓ 1 callers
Method
_check_file
Validate file exists and is within size limits. Args: file_path: Path to the document file
foundational-rag-agent/document_processing/ingestion.py:39
↓ 1 callers
Method
_clean_databases
Clean existing data from databases.
agentic-rag-knowledge-graph/ingestion/ingest.py:386
↓ 1 callers
Method
_clean_databases
Clean existing data from databases.
ag-ui-rag-agent/agent/ingestion/ingest.py:347
↓ 1 callers
Method
_clean_databases
Clean existing data from databases.
docling-rag-agent/ingestion/ingest.py:446
↓ 1 callers
Method
_clean_databases
Clean existing data from databases.
all-rag-strategies/implementation/ingestion/ingest.py:467
↓ 1 callers
Method
_create_mock_update
Helper to create mock Telegram update.
claude-agent-sdk-demos/telegram_integration/tests/test_sentry_monitoring.py:240
↓ 1 callers
Method
_estimate_tokens
Rough estimate of token count (4 chars per token).
agentic-rag-knowledge-graph/ingestion/graph_builder.py:192
↓ 1 callers
Method
_extract_companies
Extract company names from text.
agentic-rag-knowledge-graph/ingestion/graph_builder.py:271
↓ 1 callers
Method
_extract_document_metadata
Extract metadata from document content.
agentic-rag-knowledge-graph/ingestion/ingest.py:307
↓ 1 callers
Method
_extract_document_metadata
Extract metadata from document content.
ag-ui-rag-agent/agent/ingestion/ingest.py:268
↓ 1 callers
Method
_extract_document_metadata
Extract metadata from document content.
docling-rag-agent/ingestion/ingest.py:367
↓ 1 callers
Method
_extract_document_metadata
Extract metadata from document content.
all-rag-strategies/implementation/ingestion/ingest.py:388
↓ 1 callers
Method
_extract_locations
Extract location names from text.
agentic-rag-knowledge-graph/ingestion/graph_builder.py:335
↓ 1 callers
Method
_extract_people
Extract person names from text.
agentic-rag-knowledge-graph/ingestion/graph_builder.py:316
↓ 1 callers
Method
_extract_technologies
Extract technology terms from text.
agentic-rag-knowledge-graph/ingestion/graph_builder.py:294
↓ 1 callers
Method
_extract_title
Extract title from document content or filename.
agentic-rag-knowledge-graph/ingestion/ingest.py:295
↓ 1 callers
Method
_extract_title
Extract title from document content or filename.
ag-ui-rag-agent/agent/ingestion/ingest.py:256
↓ 1 callers
Method
_extract_title
Extract title from document content or filename.
docling-rag-agent/ingestion/ingest.py:355
↓ 1 callers
Method
_extract_title
Extract title from document content or filename.
all-rag-strategies/implementation/ingestion/ingest.py:376
↓ 1 callers
Method
_find_document_files
Find all supported document files in the documents folder.
docling-rag-agent/ingestion/ingest.py:233
↓ 1 callers
Method
_find_document_files
Find all supported document files in the documents folder.
all-rag-strategies/implementation/ingestion/ingest.py:254
↓ 1 callers
Method
_find_markdown_files
Find all markdown files in the documents folder.
agentic-rag-knowledge-graph/ingestion/ingest.py:271
↓ 1 callers
Method
_find_markdown_files
Find all markdown files in the documents folder.
ag-ui-rag-agent/agent/ingestion/ingest.py:232
↓ 1 callers
Method
_format_betting_lines
Format betting lines for display.
nba-agent/agent_trial/nba_agent_1.py:494
↓ 1 callers
Method
_generate_parlay_prediction
Generate a parlay prediction based on highest confidence picks.
nba-agent/agent_trial/nba_agent_1.py:564
↓ 1 callers
Method
_generate_prediction
Generate prediction with consistent format.
nba-agent/nba_agent.py:313
↓ 1 callers
Method
_get_current_nba_season
Get the NBA season based on the game date. For the 2024-25 season, use 2024.
nba-agent/nba_agent.py:79
↓ 1 callers
Method
_get_default_system_prompt
Get the default system prompt for Obsidian integration. Returns: str: Default system prompt
claude-agent-sdk-demos/PRPs/examples/ai_docs/claude_sdk_wrapper.py:100
↓ 1 callers
Method
_get_season_averages
Get player's season averages for the current season.
nba-agent/nba_agent.py:106
↓ 1 callers
Method
_get_season_averages
Get player's season averages for the current season.
nba-agent/agent_trial/nba_agent_1.py:108
↓ 1 callers
Method
_ingest_single_document
Ingest a single document. Args: file_path: Path to the document file Returns: Inges
agentic-rag-knowledge-graph/ingestion/ingest.py:161
↓ 1 callers
Method
_ingest_single_document
Ingest a single document. Args: file_path: Path to the document file Returns: Inges
ag-ui-rag-agent/agent/ingestion/ingest.py:153
↓ 1 callers
Method
_ingest_single_document
Ingest a single document. Args: file_path: Path to the document file Returns: Ingestion result
docling-rag-agent/ingestion/ingest.py:153
↓ 1 callers
Method
_ingest_single_document
Ingest a single document. Args: file_path: Path to the document file Returns: Ingestion result
all-rag-strategies/implementation/ingestion/ingest.py:155
↓ 1 callers
Method
_prepare_episode_content
Prepare episode content with minimal context to avoid token limits. Args: chunk: Document chunk docu
agentic-rag-knowledge-graph/ingestion/graph_builder.py:146
↓ 1 callers
Method
_read_document
Read document content from file.
agentic-rag-knowledge-graph/ingestion/ingest.py:285
↓ 1 callers
Method
_read_document
Read document content from file.
ag-ui-rag-agent/agent/ingestion/ingest.py:246
↓ 1 callers
Method
_read_document
Read document content from file - supports multiple formats via Docling. Returns: Tuple of (markdown_content, docling_do
docling-rag-agent/ingestion/ingest.py:256
↓ 1 callers
Method
_read_document
Read document content from file - supports multiple formats via Docling. Returns: Tuple of (markdown_content, docling_do
all-rag-strategies/implementation/ingestion/ingest.py:277
↓ 1 callers
Method
_save_to_postgres
Save document and chunks to PostgreSQL.
agentic-rag-knowledge-graph/ingestion/ingest.py:337
↓ 1 callers
Method
_save_to_postgres
Save document and chunks to PostgreSQL.
ag-ui-rag-agent/agent/ingestion/ingest.py:298
↓ 1 callers
Method
_save_to_postgres
Save document and chunks to PostgreSQL.
docling-rag-agent/ingestion/ingest.py:397
↓ 1 callers
Method
_save_to_postgres
Save document and chunks to PostgreSQL.
all-rag-strategies/implementation/ingestion/ingest.py:418
↓ 1 callers
Method
_semantic_chunk
Perform semantic chunking using LLM. Args: content: Content to chunk Returns: List
agentic-rag-knowledge-graph/ingestion/chunker.py:127
↓ 1 callers
Method
_semantic_chunk
Perform semantic chunking using LLM. Args: content: Content to chunk Returns: List
ag-ui-rag-agent/agent/ingestion/chunker.py:127
↓ 1 callers
Method
_semantic_chunk
Perform semantic chunking using LLM. Args: content: Content to chunk Returns: List
docling-rag-agent/ingestion/chunker_no_docling.py:127
↓ 1 callers
Method
_semantic_chunk
Perform semantic chunking using LLM. Args: content: Content to chunk Returns: List
all-rag-strategies/implementation/ingestion/chunker_no_docling.py:127
↓ 1 callers
Method
_simple_chunk
Simple rule-based chunking. Args: content: Content to chunk base_metadata: Base metadata for chunks
agentic-rag-knowledge-graph/ingestion/chunker.py:279
↓ 1 callers
Method
_simple_chunk
Simple rule-based chunking. Args: content: Content to chunk base_metadata: Base metadata for chunks
ag-ui-rag-agent/agent/ingestion/chunker.py:279
↓ 1 callers
Method
_simple_chunk
Simple rule-based chunking. Args: content: Content to chunk base_metadata: Base metadata for chunks
docling-rag-agent/ingestion/chunker_no_docling.py:279
↓ 1 callers
Method
_simple_chunk
Simple rule-based chunking. Args: content: Content to chunk base_metadata: Base metadata for chunks
all-rag-strategies/implementation/ingestion/chunker_no_docling.py:279
↓ 1 callers
Method
_split_long_section
Split a long section using LLM for semantic boundaries. Args: section: Section to split Returns
ag-ui-rag-agent/agent/ingestion/chunker.py:202
↓ 1 callers
Method
_split_long_section
Split a long section using LLM for semantic boundaries. Args: section: Section to split Returns
docling-rag-agent/ingestion/chunker_no_docling.py:202
↓ 1 callers
Method
_split_long_section
Split a long section using LLM for semantic boundaries. Args: section: Section to split Returns
all-rag-strategies/implementation/ingestion/chunker_no_docling.py:202
↓ 1 callers
Method
_split_on_structure
Split content on structural boundaries. Args: content: Content to split Returns: Li
ag-ui-rag-agent/agent/ingestion/chunker.py:170
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