Some ai's dont seem to be prefering to use this direct helper
provided for fetching pdf as text, on its own. Instead ai (gptoss)
seems to be keen on fetching raw pdf and extract text etal, so now
renaming the function call to try and make its semantic more
readily obivious hopefully.
It sometimes (not always) seem to assum fetch_web_url_text, can
convert pdf to text and return it. Maybe I need to place the
specific fetch pdf as text before the generic fetch web url text
and so...
With the rename, the pdf specific fetch seems to be getting used
more.
Allow user to clear the existing chat. The user does have the
option to load the just cleared chat, if required.
Add icons wrt clearing chat and settings.
Update readme wrt searchDrops, auto settings ui creation
Rename tools-auto to tools-autoSecs, to make it easy to realise
that the value represents seconds.
Update the initial skeleton wrt the tag drops logic
* had forgotten to convert object to json string at the client end
* had confused between js and python and tried accessing the dict
elements using . notation rather than [] notation in python.
* if the id filtered tag to be dropped is found, from then on
track all other tags of the same type (independent of id),
so that start and end tags can be matched. bcas end tag call
wont have attribute, so all other tags of same type need to
be tracked, for proper winding and unwinding to try find
matching end tag
* remember to reset the tracked drop tag type to None once matching
end tag at same depth is found. should avoid some unnecessary
unwinding.
* set/fix the type wrt tagDrops explicitly to needed depth and
ensure the dummy one and any explicitly got one is of right type.
Tested with duckduckgo search engine and now the div based unneeded
header is avoided in returned search result.
Chances are for ai models which dont support tool calling, things
will be such that the tool calls meta data shared will be silently
ignored without much issue.
So enabling tool calling feature by default, so that in case one
is using a ai model with tool calling the feature is readily
available for use.
Revert SlidingWindow ChatHistory in Context from last 10 to last 5
(2 more then origianl, given more context support in todays models)
by default, given that now tool handshakes go through the tools
related side channel in the http handshake and arent morphed into
normal user-assistant channel of the handshake.
Rename path and tags/identifiers from Pdf2Text to PdfText
Rename the function call to pdf_to_text, this should also help
indicate semantic more unambiguously, just in case, especially
for smaller models.
also move debug dump helper to its own module
also remember to specify the Class name in quotes, similar to
refering to a class within a member of th class wrt python type
checking.
As I was seeing the truncated message even for stripped plain text
web acces, relooking at that initial go at truncating, revealed
a oversight, which had the truncation logic trigger anytime the
iResultMaxDataLength was greater than 0, irrespective of whether
the actual result was smaller than the allowed limit or not,
thus adding that truncated message to end of result unnecessarily.
Have fixed that oversight
Also recent any number of args based simpleprox handshake helper
in toolweb seems to be working (atleast for the existing single
arg based calls).
Update the descriptions of set and get to indicate the possible
corner cases or rather semantic in such situations.
Update the readme also a bit. The auto save and restore mentioned
has nothing to do with the new data store mechanism.
In the eagerness of initial skeleton, had forgotten that the
root/generic tool call router takes care of parsing the json string
into a object, before calling the tool call, so no need to try
parse again. Fixed the same.
Hadnt converted the object based response from data store related
calls in the db web worker, into json string before passing to the
generic tool response callback, fixed the same.
- Rather the though of making the ChatMsgEx.createAllInOne handle
string or object set aside for now, to keep things simple and
consistant to the greatest extent possible across different flows.
And good news - flow is working atleast for the overall happy path
Need to check what corner cases are lurking like calling set on
same key more than once, seemed to have some flow oddity, which I
need to check later.
Also maybe change the field name to value from data in the response
to get, to match the field name convention of set. GPT-OSS is fine
with it. But worst case micro / nano / pico models may trip up, in
worst case, so better to keep things consistent.
instead of using the shared bearer token as is, hash it with
current year and use the hash.
keep /aum path out of auth check.
in future bearer token could be transformed more often, as well as
with additional nounce/dynamic token from server got during initial
/aum handshake as also running counter and so ...
NOTE: All these circus not good enough, given that currently the
simpleproxy.py handshakes work over http. However these skeletons
put in place, for future, if needed.
TODO: There is a once in a bluemoon race when the year transitions
between client generating the request and server handling the req.
But other wise year transitions dont matter bcas client always
creates fresh token, and server checks for year change to genrate
fresh token if required.
Moved it into Me->tools, so that end user can modify the same as
required from the settings ui.
TODO: Currently, if tc response is got after a tool call timed out
and user submitted default timed out error response, the delayed
actual response when it is got may overwrite any new content in
user query box, this needs to be tackled.
include info about the auto option within tools.
use nonwrapped text wrt certain sections, so that the markdown
readme can be viewed properly wrt the structure of the content
in it.
Also remove more inner/detailed stuff from show info in not bAll
mode, given that many of the previous differentiated stuff have
been moved into chatProps and inturn shown for now
NOTE: not a robust check, just tries to establish a http connection
for now and doesnt really check if it is the specific proxy srvr
of interest or not.
Also update the sliding window context size to last 9 chat messages
so that there is a sufficiently large context for multi turn tool
calls based adjusting by ai and user, without needing to go full
hog, which has the issue of overflowing the currently set context
window wrt the loaded ai model.
hanishkvc
Diego Devesa