o UQ{im/ @sddlZddlZddlZddlZddlZddlZddlZddlZ ddl Z ddl Z ddl Z ddl mZmZmZejejdedZdZdZdedefd d Zd edeeeffd d Z d4dedededeedeeeff ddZedkriddlZddlZejddZej deddej deddej deddej deddd ej d!ed"de!Z"e"j#Z$e"j%Z&e"j'Z(e"j)Z*e"j+r"z?ej,-e"j+re.e"j+d# Z/e0e/Z1Wdn1swYne2e"j+Z1e13dZ$e13d$Z&e13d%Z(e13d&Z*Wne4y!Z5ze6d'e5e7d(WYdZ5[5ndZ5[5wwe$r+e&r+e(s7e6d)d*Z$d+Z&d,Z(dZ*e6d-e6d.e$e6d/e(e*rSe6d0e*ee$e&e(e*Z8e6d1e6ej9e8d2d3dSdS)5N)DictAnyOptional)levelresponse_iq_analysisz#http://localhost:11434/api/generatez llama3.1:8b voice_inputreturnc Cs\z|sWdS|ds|dr`tj|dd}|d}d|dd vr4d|dd dd }tjd |d }|jd d D]}||qB|j WdWS1sXwYWdSd|vrk|dd}t |}tjd dd }|||j WdWS1swYWdSt y}zt d|WYd}~dSd}~ww)zEHandles both URL and Base64 audio inputs, saving to a temporary file.zhttp://zhttps://T)streamz.mpeg./F)deletesuffixi ) chunk_sizeN,z.wavzFailed to process audio input: ) startswithrequestsgetraise_for_statussplittempfileNamedTemporaryFile iter_contentwritenamebase64 b64decode Exceptionloggererror)rresponsertmp_filechunk audio_dataer'D/var/www/eduai.edurigo.com/response_iq_kunal/response_iq_analysis.pydownload_or_save_audios4 (  (r) file_pathc CsZz tj|dd\}}tj||d\}}||t|k}t|dkr(t|nd}t|dkr5t|nd}tjj ||d}tj j ||d} t| dkrQ| dnd} tj j |dd} t| } t| } tj j||dd}t|}tj j|dd}t|}tj j|dd}t|}tj j||dd}tj|d d }g}| d kr|d n| d kr|dn|d|dkr|dn |dkr|d| | ddkr|dn|d|dkr|dd|t|t|t| t| t| t|t|t|ddWSty,}ztd|didWYd}~Sd}~ww)zX Extracts advanced acoustic features using librosa for improved tonal analysis. N)sr)yr+r)onset_enveloper+)r, )r,r+n_mfccr)axisz,Fast speaking pace (high energy or nervous).Pz,Slow speaking pace (measured or low energy).zNormal/Moderate speaking pace.<z*High pitch variation (expressive/excited).z'Low pitch variation (monotone/robotic).gư>g?zKSignificant energy fluctuations (might indicate hesitation or shaky voice).z,Stable vocal energy (suggesting confidence).g?zBreathy or noisy vocal texture. ) avg_pitch_hz pitch_std tempo_bpm avg_energyenergy_fluctuation avg_centroid avg_flatnessavg_zcr)summarystatszAudio analysis failed: z"Technical audio extraction failed.)librosaloadpiptracknpmedianlenmeanstdonsetonset_strengthbeattempofeaturermsspectral_centroidspectral_flatnesszero_crossing_ratemfccappendjoinfloatrr r!)r*r,r+pitches magnitudespitches_masked avg_pitchr7 onset_envrK avg_temporMr9 energy_stdrNr;flatnessr<zcrr=rQ mfcc_means descriptionr&r'r'r(analyze_audio_features:sZ        r`questionpredefined_answer user_answeruser_voice_urlc Csd}d}d}|r(tdt|}|r(tdt|}zt|WnYd}d}|r>d|ddt|dd }d |d |d |d |d } t| |ddddddd} zftdtdt j t | dd} | j dkrt dtdddtdtd iWS| | } | d!d} d"| vr| d"d#d$d%} nd$| vr| d$d#d$d%} t| }|WStjyt d&d'| d(YSt jy}zt d)|dd*t|iWYd}~Sd}~ww)+Nr zProcessing audio input...z%Extracting advanced audio features...a#You are a world-class communication expert, behavioral psychologist, and tonal analyst. Your goal is to provide a deep, professional evaluation of a candidate's response. Analyze the text for semantic accuracy AND the voice for emotional nuance. Return the result ONLY in strict JSON format.z Voice Tonal Metadata: r>z" Detailed Acoustic Stats: r?z (Interpreting stats: Low pitch_std = monotone, High energy_fluctuation = shaky/hesitant, High avg_flatness = breathy/unclear, Moderate tempo = confident/composed). zf Evaluate the following interview response with high precision. INPUT DATA: - Question: "z"" - Ideal/Predefined Answer: "z" - User's Actual Answer: "z" a REQUIRED ANALYSIS: 1. Match Score (0-100): Quantify how well the user's answer covers the core concepts of the ideal answer. Be strict but fair. 2. Comparison: A professional summary of why the score was given. 3. Behavioral Analysis: Analyze the user's communication style. Are they assertive, analytical, empathetic, or vague? Check for logical flow and vocabulary choice. 4. Tonal Analysis: - If voice metadata is present: Provide a detailed breakdown of the user's delivery (confidence, pace, emotional stability). - If voice metadata is NOT present: Base this on the 'tone' of the written text (formal, casual, apologetic). 5. Visuals: Exactly 3 professional keywords summarizing the vibe (e.g., "Precise", "Authoritative", "Strategic"). OUTPUT FORMAT (Strict JSON): { "matchScore": , "comparison": "", "behavioralAnalysis": "", "tonalAnalysis": "", "visuals": ["", "", ""] } Fjsong?ii) temperaturenum_ctx num_predict)modelpromptsystemr formatoptionsz&Sending request to Ollama using model z...)retimeoutiz Model ID 'z' not found (404).r!zModel 'z:' not found via Ollama. Please pull it using 'ollama pull 'r"z```jsonrz```rzFailed to parse JSON from LLMzLLM returned invalid JSON)r! raw_responsezOllama connection error: zCould not connect to LLM: )r infor)r`osremoveredumps OLLAMA_MODELrpostOLLAMA_API_URL status_coder!rrrstriploadsJSONDecodeErrorRequestExceptionstr)rarbrcrdaudio_analysis_textaudio_file_pathaudio_features system_prompt audio_contextrjpayloadr"resultllm_response_text parsed_jsonr&r'r'r(analyze_responses        r__main__z&Run Response IQ Analysis from Terminal)r_z --questionzThe interview question)typehelpz --predefinedzThe correct/ideal answerz--userzThe user's answerz--voicezURL to user's voice recording)rrdefaultz --json_inputzHJSON string with keys: question, predefinedAnswer, userAnswer, userVoicerpredefinedAnswer userAnswer userVoicezError parsing JSON input: rz6No input provided. Running with DEFAULT DEMO values...zthis is the questionzthis is the predefined answerzthis is the user answerz --- Starting Analysis ---z Question: z User Answer: z Voice URL: z --- Analysis Result ---)indent)N):rsrreloggingrr@numpyrC soundfilesfrioretypingrrr basicConfigINFO getLoggerr rxrvr~r)r`r__name__argparsesysArgumentParserparser add_argument parse_argsargsraq predefinedpauseruavoiceuv json_inputpathisfileopenfrAdatar{rrr&printexitrrur'r'r'r(s $N  y