LLM Pico Car: How I Built a Voice-Controlled Toy Car Using Generative AI, Gradio, and Raspberry Pi Pico

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import gradio as gr ... with gr.Blocks() as demo: ...
with gr.Tab("Audio Instructions"): # Define components audio_input = gr.Audio( sources=["microphone"], type="filepath", format="wav") with gr.Row(): audio_send_button = gr.Button("Submit", variant="primary") audio_reset_button = gr.Button("Reset", variant="secondary") ... # Define click event handlers audio_send_button.click(handler_audio_input, inputs=audio_input, outputs=[audio_transcript_output, audio_commands_output, audio_status_output, progress_lamps,],) ... # Launch the server demo.launch(server_name="0.0.0.0", share=True) HS"VEJP HS#VUUPO HS#VUUPO HS5FYUCPY HS5FYUCPY HS+40/ TUSVDUVSFEBDUJPOT $PEF(SBEJPCMPDLT 4UFQ*OQVUWPJDFWJBBXFCBQQ HS)5.-

with gr.Tab("Voice Input"): # Define components audio_input = gr.Audio( sources=["microphone"], type="filepath", format="wav") with gr.Row(): audio_send_button = gr.Button("Submit", variant="primary") audio_reset_button = gr.Button("Reset", variant="secondary") audio_transcript_output = gr.Textbox(label="Transcription Result") audio_status_output = gr.Textbox(label="Processing Status") audio_commands_output = gr.JSON(label=“Generated Commandas") # Define click event handlers ... # Launch the server demo.launch(server_name="0.0.0.0", share=True) 4UFQ*OQVUWPJDFWJBBXFCBQQ $PEF6*MBZPVU 7PJDFJOQVU DPNQPOFOU #VUUPOT 3FTVMU DPNQPOFOUT HS"VEJP HS#VUUPO HS#VUUPO HS5FYUCPY HS5FYUCPY HS+40/ TUSVDUVSFEBDUJPOT HS)5.-

with gr.Tab("Voice Input"): # Define components ... # Define click event handlers audio_send_button.click(handler_audio_input, inputs=audio_input, outputs=[audio_transcript_output, audio_commands_output, audio_status_output, progress_lamps,],) audio_reset_button.click(...) audio_input.start_recording(...) audio_input.stop_recording(...) # Launch the server demo.launch(server_name="0.0.0.0", share=True) $PEF&WFOUIBOEMJOH 4UFQ*OQVUWPJDFWJBBXFCBQQ $MJDL

with gr.Tab("Voice Input"): # Define components ... # Define click event handlers audio_send_button.click(handler_audio_input, inputs=audio_input, outputs=[audio_transcript_output, audio_commands_output, audio_status_output, progress_lamps,],) audio_reset_button.click(...) audio_input.start_recording(...) audio_input.stop_recording(...) # Launch the server demo.launch(server_name="0.0.0.0", share=True) $PEF&WFOUIBOEMJOH 4UFQ*OQVUWPJDFWJBBXFCBQQ *OQVU 0VUQVUT $MJDL

with gr.Tab("Voice Input"): # Define components ... # Define click event handlers audio_send_button.click(handler_audio_input, inputs=audio_input, outputs=[audio_transcript_output, audio_commands_output, audio_status_output, progress_lamps,],) audio_reset_button.click(...) audio_input.start_recording(...) audio_input.stop_recording(...) # Launch the server demo.launch(server_name="0.0.0.0", share=True) $PEF&WFOUIBOEMJOH 4UFQ*OQVUWPJDFWJBBXFCBQQ .click(handler, inputs=..., outputs=...) audio_transcript_output 'VODUJPOFYFDVUFEXIFODMJDLFE w TQFFDISFDPHOJUJPO w --.QSPDFTTJOH w TFOEDPNNBOETUPUIF1JDPDBS w ʜ audio_status_output audio_commands_output audio_input

with gr.Tab("Voice Input"): # Define components ... # Define click event handlers audio_send_button.click(handler_audio_input, inputs=audio_input, outputs=[audio_transcript_output, audio_commands_output, audio_status_output, progress_lamps,],) audio_reset_button.click(...) audio_input.start_recording(...) audio_input.stop_recording(...) # Launch the server demo.launch(server_name="0.0.0.0", share=True) $PEF-BVODIUIFTFSWFS 4UFQ*OQVUWPJDFWJBBXFCBQQ

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audio_send_button.click(handler_audio_input, inputs=audio_input, outputs=[audio_transcript_output, audio_commands_output, audio_status_output, progress_lamps]) def handler_audio_input(audio_file): success, text
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model = WhisperModel(model_size, device="cpu", compute_type="float32") ... segments, _ = model.transcribe(tmp_audio_path, language=None) text = "".join([segment.text for segment in segments]) ᶃ-PBEUIFNPEFM ᶄ3VOUSBOTDSJQUJPO "VEJPˠ5FYU 5SBOTDSJQUJPO 4UFQ5SBOTDSJCFWPJDFBOEHFOFSBUFTUSVDUVSFEBDUJPOT

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from langchain.chat_models import init_chat_model from langchain_core.prompts import ChatPromptTemplate ... prompt
= ChatPromptTemplate( [ ("system", TEXT_TO_COMMAND_PROMPT), ("human", "ࢦࣔ: {text}"), ] ) llm = init_chat_model(model="gpt-4.1", temperature=0) chain = prompt | llm result = chain.invoke({"text": text}) instructions = result.content # Add RGB color info based on the LED color name (CSS color name) in the generated data instructions = _add_led_rgb(instructions) instructions = json.loads(instructions) ᶃ#VJMEUIFQSPNQUUFNQMBUF ᶄ*OJUJBMJ[FUIFNPEFM ᶅ$POOFDUUIFQSPNQUBOENPEFM $PEF-BOH$IBJOQJQFMJOF 4UFQ5SBOTDSJCFWPJDFBOEHFOFSBUFTUSVDUVSFEBDUJPOT ᶆ*OWPLFUIFNPEFMUPHFOFSBUFBDUJPOT

= ChatPromptTemplate( [ ("system", TEXT_TO_COMMAND_PROMPT), ("human", "ࢦࣔ: {text}"), ] ) llm = init_chat_model(model="gpt-4.1", temperature=0) chain = prompt | llm result = chain.invoke({"text": text}) instructions = result.content # Add RGB color info based on the LED color name (CSS color name) in the generated data instructions = _add_led_rgb(instructions) instructions = json.loads(instructions) Please convert the given instruction text into a JSON array of motion commands for the Pico Car. If the input text is not an instruction (for example, “Good morning!” or “Idiot!”), convert it into a command array that expresses the car’s emotion in response. Output only the command array — do not include any explanations or additional text. Each command should follow the format below: … 1SPNQUT 4UFQ5SBOTDSJCFWPJDFBOEHFOFSBUFTUSVDUVSFEBDUJPOT 1SPNQU

= ChatPromptTemplate( [ ("system", TEXT_TO_COMMAND_PROMPT), ("human", "ࢦࣔ: {text}"), ] ) llm = init_chat_model(model="gpt-4.1", temperature=0) chain = prompt | llm result = chain.invoke({"text": text}) instructions = result.content # Add RGB color info based on the LED color name (CSS color name) in the generated data instructions = _add_led_rgb(instructions) instructions = json.loads(instructions) Please convert the given Japanese instruction text into a JSON array of motion commands for the Pico Car. If the input text is not an instruction (for example, “Good morning!” or “Idiot!”), convert it into a command array that expresses the car’s emotion in response. Output only the command array — do not include any explanations or additional text. Each command should follow the format below: … 1SPNQUT 4UFQ5SBOTDSJCFWPJDFBOEHFOFSBUFTUSVDUVSFEBDUJPOT 1SPNQU

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[ { "action": {"type": "forward", "distance_cm": 20}, "led": {"color": "green"}},
{ "action": {"type": "turn", "direction": "right", "angle": 90}, "led": {"color": "green"}}, ...] BDUJPOUVSOSJHIU MFEHSFFO BDUJPONPWFGPSXBSE DN MFEHSFFO &YBNQMFPGHFOFSBUFEBDUJPOEBUB TUDPNNBOE 4UFQ5SBOTDSJCFWPJDFBOEHFOFSBUFTUSVDUVSFEBDUJPOT OEDPNNBOE

[ { "action": {"type": "forward", "distance_cm": 20}, "led": {"color": "green",
"rgb": (0, 255, 0) }}, { "action": {"type": "turn", "direction": "right", "angle": 90}, "led": {"color": "green", "rgb": (0, 255, 0)}}, ...] 1PTUQSPDFTTJOH$PMPSOBNFˠ3(# 4UFQ5SBOTDSJCFWPJDFBOEHFOFSBUFTUSVDUVSFEBDUJPOT $POWFSU$44DPMPSOBNFTUP3(# VTJOHTUBOEBSE$44SVMFT w 5IFNPEFMPVUQVUTPOMZDPMPSOBNFT3(#WBMVFTBSFBEEFEMBUFSJO1ZUIPO w $PMPSOBNFTBSFFBTJFSGPSUIF"*UPFYQSFTTFNPUJPOT TP*MFUUIFNPEFMPVUQVU$44DPMPSOBNFTPOMZ w 3(#DPOWFSTJPOJTEPOFJO1ZUIPOUPLFFQUIJOHTTJNQMFBOEDPSSFDU

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from microdot import Microdot from pico_car import Car, RealCar car
= Car() if settings.USE_MOCK else RealCar() app = Microdot() ... @app.route("/command", methods=["POST"]) async def handle_command(request): try: car.sound_freq(1000, 0.1) car.sound_freq(1200, 0.1) command_list = request.json car.run_commands(command_list) return {"status": "ok"} except Exception as e: handle_buggy_error() print_exception(e) return {"status": "error", "message": str(e)}, 500 ... app.run(port=5001) ᶃ1MBZBOPUJ fi DBUJPOTPVOE $SFBUFBOJOTUBODFPGUIFDVTUPN1JDP$BSDMBTT ᶄ&YFDVUFDPNNBOET )BOEMFFSSPST FH QMBZFSSPSTPVOE TUPQNPUPST -BVODIUIFTFSWFS $PEF.JDSPEPU4FSWFSPOUIF1JDP 4UFQ3FDFJWFBOEFYFDVUFDPNNBOET %F fi OFBO"1*UPSFDFJWFBOE FYFDVUFDPNNBOET $SFBUFB.JDSPEPUBQQ

= Car() if settings.USE_MOCK else RealCar() app = Microdot() ... @app.route("/command", methods=["POST"]) async def handle_command(request): try: car.sound_freq(1000, 0.1) car.sound_freq(1200, 0.1) command_list = request.json car.run_commands(command_list) return {"status": "ok"} except Exception as e: handle_buggy_error() print_exception(e) return {"status": "error", "message": str(e)}, 500 ... app.run(port=5001) ᶃ1MBZBOPUJ fi DBUJPOTPVOE 4XJUDICFUXFFONPDL BOESFBMIBSEXBSF GPSFBTZUFTUJOH $SFBUFBOJOTUBODFPGUIFDVTUPN1JDP$BSDMBTT ᶄ&YFDVUFDPNNBOET )BOEMFFSSPST FH QMBZFSSPSTPVOE TUPQNPUPST -BVODIUIFTFSWFS $PEF.JDSPEPU4FSWFSPOUIF1JDP 4UFQ3FDFJWFBOEFYFDVUFDPNNBOET %F fi OFBO"1*UPSFDFJWFBOE FYFDVUFDPNNBOET $SFBUFB.JDSPEPUBQQ

= Car() if settings.USE_MOCK else RealCar() app = Microdot() ... @app.route("/command", methods=["POST"]) async def handle_command(request): try: car.sound_freq(1000, 0.1) car.sound_freq(1200, 0.1) command_list = request.json car.run_commands(command_list) return {"status": "ok"} except Exception as e: handle_buggy_error() print_exception(e) return {"status": "error", "message": str(e)}, 500 ... app.run(port=5001) ᶃ1MBZBOPUJ fi DBUJPOTPVOE 4XJUDICFUXFFONPDL BOESFBMIBSEXBSF GPSFBTZUFTUJOH $SFBUFBOJOTUBODFPGUIFDVTUPN1JDP$BSDMBTT $SFBUFB.JDSPEPUBQQ ᶄ&YFDVUFDPNNBOET )BOEMFFSSPST FH QMBZFSSPSTPVOE TUPQNPUPST -BVODIUIFTFSWFS $PEF.JDSPEPU4FSWFSPOUIF1JDP 4UFQ3FDFJWFBOEFYFDVUFDPNNBOET %F fi OFBO"1*UPSFDFJWFBOE FYFDVUFDPNNBOET

= Car() if settings.USE_MOCK else RealCar() app = Microdot() ... @app.route("/command", methods=["POST"]) async def handle_command(request): try: car.sound_freq(1000, 0.1) car.sound_freq(1200, 0.1) command_list = request.json car.run_commands(command_list) return {"status": "ok"} except Exception as e: handle_buggy_error() print_exception(e) return {"status": "error", "message": str(e)}, 500 ... app.run(port=5001) ᶃ1MBZBOPUJ fi DBUJPOTPVOE $SFBUFBOJOTUBODFPGUIFDVTUPN1JDP$BSDMBTT ᶄ&YFDVUFDPNNBOET )BOEMFFSSPST FH QMBZFSSPSTPVOE TUPQNPUPST -BVODIUIFTFSWFS $PEF.JDSPEPU4FSWFSPOUIF1JDP 4UFQ3FDFJWFBOEFYFDVUFDPNNBOET %F fi OFBO"1*UPSFDFJWFBOE FYFDVUFDPNNBOET $SFBUFB.JDSPEPUBQQ 'MBTLMJLFTZOUBY

= Car() if settings.USE_MOCK else RealCar() app = Microdot() ... @app.route("/command", methods=["POST"]) async def handle_command(request): try: car.sound_freq(1000, 0.1) car.sound_freq(1200, 0.1) command_list = request.json car.run_commands(command_list) return {"status": "ok"} except Exception as e: handle_buggy_error() print_exception(e) return {"status": "error", "message": str(e)}, 500 ... app.run(port=5001) ᶃ1MBZBOPUJ fi DBUJPOTPVOE $SFBUFBOJOTUBODFPGUIFDVTUPN1JDP$BSDMBTT ᶄ&YFDVUFDPNNBOET )BOEMFFSSPST FH QMBZFSSPSTPVOE TUPQNPUPST -BVODIUIFTFSWFS $PEF.JDSPEPU4FSWFSPOUIF1JDP 4UFQ3FDFJWFBOEFYFDVUFDPNNBOET %F fi OFBO"1*UPSFDFJWFBOE FYFDVUFDPNNBOET $SFBUFB.JDSPEPUBQQ

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LLM Pico Car: How I Built a Voice-Controlled To...

LLM Pico Car: How I Built a Voice-Controlled Toy Car Using Generative AI, Gradio, and Raspberry Pi Pico

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