fetch-agents
Python client for the AgentsLab AI agent services.
Three agents, one SDK:
- Code Context Agent — slim, map, extract, mark code layers
- Context Doctor — compress, analyze, optimize LLM context windows
- AI Teleporter — teleport, search, merge chat export knowledge bases
Install
pip install fetch-agents
Quick Start
from fetch_agents import FetchAgents
# Register once (free, no email required)
info = FetchAgents.register(name="myapp")
api_key = info["api_key"] # save this
client = FetchAgents(api_key=api_key)
# Slim a code file to only the layers relevant to your task
result = client.slim(
url="https://raw.githubusercontent.com/you/repo/main/app.py",
task="fix the auth handler"
)
print(result["context"])
# Compress LLM context to reduce tokens
result = client.compress(text="...long assistant output...", max_length=200)
print(result["compressed"])
# Teleport a chat export into a searchable knowledge base
with open("chatgpt_export.json") as f:
data = f.read()
index = client.teleport(data)
hits = client.search(index["index_id"], query="how do I fix auth?")
API Key via Environment
export FETCH_API_KEY=fak_xxx
client = FetchAgents() # picks up FETCH_API_KEY automatically
Free Tier
50 requests/day per key, no credit card needed. For higher volume, top up with crypto:
invoice = client.topup(amount_usd=5, currency="btc")
print(invoice["pay_url"]) # pay this address
Supported: BTC, LTC, BCH, DOGE, TRX, ETH, BNB, USDT, USDC, and more.
All Methods
| Method | Agent | Description |
|---|---|---|
register(name) |
— | Self-service registration, returns API key |
me() |
— | Quota + balance |
topup(amount_usd, currency) |
— | Create crypto invoice |
topup_status(invoice_id) |
— | Check invoice status |
currencies() |
— | List supported currencies |
slim(url, task) |
Code Context | Relevant layers only |
map(url) |
Code Context | List all LAYER sections |
extract(url, layer) |
Code Context | Extract one layer |
mark(url) |
Code Context | Auto-insert LAYER markers |
compress(text, max_length) |
Context Doctor | Token-compress text |
analyze(messages) |
Context Doctor | Score messages by importance |
optimize(messages) |
Context Doctor | Remove noise, compress verbose turns |
extract_memory(messages) |
Context Doctor | Extract structured facts |
teleport(data) |
AI Teleporter | Upload chat export, create index |
search(index_id, query, top_k) |
AI Teleporter | Semantic search |
merge(index_ids) |
AI Teleporter | Merge indexes |
formats() |
AI Teleporter | List supported export formats |
Links
- Website & docs: https://agentslab.duckdns.org
- Issues: https://github.com/SoftwareValete/fetch-agents/issues
Metadata
Release files for fetch-agents 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fetch_agents-0.1.0.tar.gz | 5.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fetch_agents-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 12.1 kB
Release files / fetch_agents-0.1.0.tar.gz
| Download URL | fetch_agents-0.1.0.tar.gz |
|---|---|
| Size | 5.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.2.0 CPython/3.12.3
|
Release files / fetch_agents-0.1.0-py3-none-any.whl
| Download URL | fetch_agents-0.1.0-py3-none-any.whl |
|---|---|
| Size | 6.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.3
|