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This guide provides examples and detailed information on using the gam-afs command-line tools.
Installation and Setup
Ensure you have installed the package:
pip install -e ".[all]"
Configure environment variables for convenience. GAM Agent and Chat Agent can be configured independently:
# GAM Agent (memory building)export GAM_API_KEY="sk-your-api-key"export GAM_MODEL="gpt-4o-mini"export GAM_API_BASE="https://api.openai.com/v1"# Chat Agent (Q&A) — falls back to GAM Agent config when not setexport GAM_CHAT_API_KEY="sk-your-chat-api-key"export GAM_CHAT_MODEL="gpt-4o"export GAM_CHAT_API_BASE="https://api.openai.com/v1"
Commands Overview
The primary commands are gam-add (for building memory) and gam-request (for querying memory). Use the --type text/video flag to switch between modalities.
gam-add — Building Memory
Text Mode (--type text)
# Add a single file
gam-add --type text --gam-dir ./my_gam --input paper.pdf
# Add multiple files
gam-add --type text --gam-dir ./my_gam --input paper1.pdf --input paper2.txt
# Add direct text content
gam-add --type text --gam-dir ./my_gam --content "Some text to memorize"# Disable chunking (treat input as a single memory)
gam-add --type text --gam-dir ./my_gam --input paper.pdf --no-chunking
Video Mode (--type video)
# Build memory from a video directory (should contain video.mp4 + optional subtitles.srt)
gam-add --type video --gam-dir ./my_video_gam --input ./video_dir
# Use specific models
gam-add --type video --gam-dir ./my_video_gam --input ./video_dir \
--model gpt-4o --api-key sk-xxx
gam-request — Querying Memory
Text Mode (--type text)
# Basic query
gam-request --type text --gam-dir ./my_gam --question "What is the main conclusion?"# Custom system prompt + JSON output
gam-request --type text --gam-dir ./my_gam -q "Summarize the paper" \
--system-prompt "You are a research assistant." --json
Video Mode (--type video)
# Video query
gam-request --type video --gam-dir ./my_video_gam --question "What happens in the video?"# Use a specific multimodal vision model
gam-request --type video --gam-dir ./my_video_gam -q "Describe the scene" \
--video-model gpt-4o
CLI Reference
Common Parameters (gam-add / gam-request):
Parameter
Default
Description
--type, -t
(Required)
GAM type: text or video
--gam-dir
(Required)
Path to GAM directory (created automatically)
--model
gpt-4o-mini
GAM Agent LLM model name (Env: GAM_MODEL)
--api-base
https://api.openai.com/v1
GAM Agent API base URL (Env: GAM_API_BASE)
--api-key
—
GAM Agent API key (Env: GAM_API_KEY or OPENAI_API_KEY)
--max-tokens
4096
Maximum tokens to generate
--temperature
0.3
Sampling temperature
--verbose / --no-verbose
--verbose
Print detailed logs
gam-add --type text Specific:
Parameter
Description
--input, -i
Path to input files (can be repeated)
--content, -c
Input text content directly (can be repeated)
--context
Optional context/description for the input
--chunking / --no-chunking
Enable intelligent chunking (default: on)
--output-dir
Directory to save raw chunks
--force-reorganize
Force reorganization of the directory structure
--memory-workers
Parallel memory generation workers (default: 4)
gam-add --type video Specific:
Parameter
Description
--input, -i
Path to video directory (must contain video.mp4)
--segmentor-model
LLM model for segment descriptions
--segmentor-api-base
API base for the segmentor model
--segmentor-api-key
API key for the segmentor model
--caption-subtitles
Include subtitles in descriptions (default: on)
gam-request Specific:
Parameter
Description
--question, -q
User question (Required)
--system-prompt, -s
Custom system prompt
--max-iter
Maximum iterations for the exploratory agent (default: 10)
--json
Output result in JSON format
--chat-model
Chat Agent LLM model name (Env: GAM_CHAT_MODEL, default: same as --model)
--chat-api-base
Chat Agent API base URL (Env: GAM_CHAT_API_BASE, default: same as --api-base)
--chat-api-key
Chat Agent API key (Env: GAM_CHAT_API_KEY, default: same as --api-key)