ivam2 0.3 review

by rbytes.net on

ivam2 is an automatic phone answering machine software for ISDN and Linux

License: GPL (GNU General Public License)
File size: 299K
Developer: Lennart Poettering
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ivam2 is an automatic phone answering machine software for ISDN and Linux. It is the completely rewritten successor of ivam featuring many additions.

ivam2 is seperated in two parts: the core daemon written in C and the automate logic coded in Python. The latter is pluggable and may be replaced by different implementations on a per phone number basis (both caller and callee). This makes ivam2 a very powerful application server for telephony services.

The software is very scalable, multiple ISDN channels may be controlled from a single daemon. To write telephony applications for ivam2 is not complicated. In fact, they are simple executables which read audio data of the caller from STDIN and write audio data for the caller to STDOUT.

DTMF sequences may be read from a FIFO special file. A framework for writing telephony applications in Python is provided, a simple answering machine script based on this framework as well. You are free to write applications in other languages such as Perl or C.

A current Linux kernel with isdn4linux and a compatible and configured (active or passive) ISDN card is required.
ivam2 relies on a current version of Python. It was developed on Python 2.3, but there are user reports that it works on Python 2.2 without changes.
ivam2 needs libdaemon (>= 0.4) and liboop (>= 1.0).
Please note: the current liboop-dev package in Debian unstable (1.0-1) is broken as the pkg-config file contained in the upstream distribution is missing. ivam2's configure script requires that file. Thus you have to compile your own version of liboop in order to use ivam2. Please beg the Debian maintainer of liboop so that he fixes this. For more information see Debian bug report #227061.
If you plan to use the message notification feature of ivam2 you need metamail, sox and oggenc installed on the local system.

ivam2 0.3 keywords