extend server/public_simplechat with simple minded interactive browser-client side based toolcalling - base logic #16563
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Enable streaming by default, to check the handshake before going on to change the code, given that havent looked into this for more than a year now and have been busy with totally different stuff. Also updated the user messages used for testing a bit
Define the meta that needs to be passed to the GenAi Engine. Define the logic that implements the tool call, if called. Implement the flow/structure such that a single tool calls implementation file can define multiple tool calls.
Make tooljs structure and flow more generic Add a simple_calculator tool/function call logic Add initial skeleton wrt the main tools.mjs file.
Changed latestResponse type to an object instead of a string. Inturn it contains entries for content, toolname and toolargs. Added a custom clear logic due to the same and used it to replace the previously simple assigning of empty string to latestResponse. For now in all places where latestReponse is used, I have replaced with latestReponse.content. Next need to handle identifying the field being streamed and inturn append to it. Also need to add logic to call tool, when tool_call triggered by genai.
Update response_extract_stream to check for which field is being currently streamed ie is it normal content or tool call func name or tool call func args and then return the field name and extracted value. Previously it was always assumed that only normal content will be returned. Currently it is assumed that the server will only stream one of the 3 supported fields at any time and not more than one of them at the same time. TODO: Have to also add logic to extract the reasoning field later, ie wrt gen ai models which give out their thinking. Have updated append_response to expect both the key and the value wrt the latestResponse object, which it will be manipualted. Previously it was always assumed that content is what will be got and inturn appended.
I was wrongly checking for finish_reason to be non null, before trying to extract the genai content/toolcalls, have fixed this oversight with the new flow in progress. I had added few debug logs to identify the above issue, need to remove them later. Note: given that debug logs are disabled by replacing the debug function during this program's initialisation, which I had forgotten about, I didnt get the debug messages and had to scratch my head a bit, before realising this and the other issue ;) Also either when I had originally implemented simplechat 1+ years back, or later due to changes on the server end, the streaming flow sends a initial null wrt the content, where it only sets the role. This was not handled in my flow on the client side, so a null was getting prepended to the chat messages/responses from the server. This has been fixed now in the new generic flow.
Make latestResponse into a new class based type instance wrt ai assistant response, which is what it represents. Move clearing, appending fields' values and getting assistant's response info (irrespective of a content or toolcall response) into this new class and inturn use the same.
Switch oneshot handler to use AssistantResponse, inturn currenlty only handle the normal content in the response. TODO: If any tool_calls in the oneshot response, it is currently not handled. Inturn switch the generic/toplevel handle response logic to use AssistantResponse class, given that both oneshot and the multipart/streaming flows use/return it. Inturn add trimmedContent member to AssistantResponse class and make the generic handle response logic to save the trimmed content into this. Update users of trimmed to work with this structure.
As there could be failure wrt getting the response from the ai server some where in between a long response spread over multiple parts, the logic uses the latestResponse to cache the response as it is being received. However once the full response is got, one needs to transfer it to a new instance of AssistantResponse class, so that latestResponse can be cleared, while the new instance can be used in other locations in the flow as needed. Achieve the same now.
Previously if content was empty, it would have always sent the toolcall info related version even if there was no toolcall info in it. Fixed now to return empty string, if both content and toolname are empty.
The implementations of javascript and simple_calculator now use provided helpers to trap console.log messages when they execute the code / expression provided by GenAi and inturn store the captured log messages in the newly added result key in tc_switch This should help trap the output generated by the provided code or expression as the case maybe and inturn return the same to the GenAi, for its further processing.
Checks for toolname to be defined or not in the GenAi's response If toolname is set, then check if a corresponding tool/func exists, and if so call the same by passing it the GenAi provided toolargs as a object. Inturn the text generated by the tool/func is captured and put into the user input entry text box, with tool_response tag around it.
As output generated by any tool/function call is currently placed into the TextArea provided for End user (for their queries), bcas the GenAi (engine/LLM) may be expecting the tool response to be sent as a user role data with tool_response tag surrounding the results from the tool call. So also now at the end of submit btn click handling, the end user input text area is not cleared, if there was a tool call handled, for above reasons. Also given that running a simple arithmatic expression in itself doesnt generate any output, so wrap them in a console.log, to help capture the result using the console.log trapping flow that is already setup.
and inform the GenAi/LLM about the same
Should hopeful ensure that the GenAi/LLM will generate appropriate code/expression as the argument to pass to these tool calls, to some extent.
ie in vs code with ts-check
Move tool calling logic into tools module. Try trap async promise failures by awaiting results of tool calling and putting full thing in an outer try catch. Have forgotten the nitty gritties of JS flow, this might help, need to check.
So that when tool handler writes the result to the tc_switch, it can make use of the same, to write to the right location. NOTE: This also fixes the issue with I forgetting to rename the key in js_run wrt writing of result.
to better describe how it will be run, so that genai/llm while creating the code to run, will hopefully take care of any naunces required.
Also as part of same, wrap the request details in the assistant block using a similar tagging format as the tool_response in user block.
Instead of automatically calling the requested tool with supplied arguments, rather allow user to verify things before triggering the tool. NOTE: User already provided control over tool_response before submitting it to the ai assistant.
Instead of automatically calling any requested tool by the GenAi / llm, that is from the tail end of the handle user submit btn click, Now if the GenAi/LLM has requested any tool to be called, then enable the Tool Run related UI elements and fill them with the tool name and tool args. In turn the user can verify if they are ok with the tool being called and the arguments being passed to it. Rather they can even fix any errors in the tool usage like the arithmatic expr to calculate that is being passed to simple_calculator or the javascript code being passed to run_javascript_function_code If user is ok with the tool call being requested, then trigger the same. The results if any will be automatically placed into the user query text area. User can cross verify if they are ok with the result and or modify it suitabley if required and inturn submit the same to the GenAi/LLM.
Also avoid showing Tool calling UI elements, when not needed to be shown.
Dont forget to map members of got entity from fetch to things from saved original promise, bcas remember what is got is a promise. also add some comments around certain decisions and needed exploration
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Code/flow has been updated to ensure to trap promises including those from fetch in the generated code if any |
A basic go at it
Declare the result of UrlReq as a DataClass, so that one doesnt goof up wrt updating and accessing members. Duplicate UrlRaw into UrlText, need to add Text extracting from html next for UrlText
As _UrlopenRet not exposed for use outside urllib, so decode and encode the data. Add skeleton to try get the html/xml tree top elements
As html can be malformed, xml ElementTree XMLParser cant handle the same properly, so switch to the HtmlParser helper class that is provided by python and try extend it. Currently a minimal skeleton to just start it out, which captures only the body contents.
First identify lines which have only whitespace and replace them with lines with only newline char in them. Next strip out adjacent lines, if they have only newlines
Ensures that if the url being requested as any query strings in them then things dont get messed up, when the url to get inc its query is extracted from the proxy request's query string
also now track header, footer and nav so that they arent captured
Add a new send headers common helper and use the same wrt the overridden send_error as well as do_OPTIONS This ensures that if there is any error during proxy opertions, the send_error propogates to the fetch from any browser properly without browser intercepting it with a CORS error
So that the same error path is used for logical error wrt http req also, without needing a different path for it. Dont forget to return the resp text/json/..., so that the contents are passed along the promise then chain
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Extends my earlier simple minded tools/server/public_simplechat web/browser ui for llama.cpp to include support for a simple minded interactive tool calling which uses the javascript environment of the browser to provide some basic tool / function calls.
Currently it provides simple_calculator and run_javascript_function_code tool calls.
If ToolCalling is enabled in ui settings, meta data about these tools is handshaked with the GenAi/LLM model. Inturn if the ai model used is aware of tool calling and makes a tool_calls request, the user is shown the tool name and the argument being passed to it. User can verify the same and trigger the tool call as is or make changes as needed before triggering the tool call.
The result of the tool call is automatically placed into the user query chat area, with tool_response tag surrounding it. The user can submit the response as is or make suitable changes to the tool response contents before submitting the same to the ai model.
NOTE: This is for a simple minded exploration of tool calling support in newer ai models and some fun along the way as well as occasional practical use like verifying mathematical or logical statements/reasoning made by the ai model during chat sessions by getting it to also create and execute code to verify such stuff and so.
[[OLD NOTE: The ai model created code is currently run in the browser's global scope, so always cross check the tool call before allowing/running it. In a later version will be updating the logic so that the generated tool call is run within a web worker scope, to limit its powers a little bit, but always be careful when using this. OLD]]
The ai model created code is run from within a web worker context in the browser, to try and isolate it from the main browser context. However any shared web worker context, if any, is not isolated. Always cross check the tool call before allowing/running it.
Bit more details about this feature is in the updated readme.md within public_simplechat.
NOTE: The tool calling has been implemented for the chat streaming mode for now. Will add support for oneshot mode later. Tool calling with this logics current simple minded ideosynchronusy (noted in readme.md) has been tested with Gemma3N model for now.