o !œ6inóã@s0ddlZddlZddlZddlZddlZddlZddlZddlZddlZddl m Z ddl Z ddl ZddlZddlZddlZddlZddlmZmZmZmZmZddlmZddlmZddl m!Z!ddl"m#Z#m$Z$ddl%m&Z&e&ƒe 'd¡Z(e 'd d ¡Z)e 'd ¡Z*e 'd d ¡Z+e 'dd¡Z,dZ-e 'd¡Z.ej/ej0dde 1e2¡Z3ej4e.deZ5e 'dd¡Z6ej7e(dZ8e)Z9e!e*e,dZ Gdd„dƒZ:dd„Z;d@dd„Zd"d#„Z?d@d$d%„Z@d&d'„ZAd(d)„ZBd*d+„ZCd,d-„ZDd@d.d/„ZEd0d1„ZFd2d3„ZGd4d5„ZHd6d7„ZId8d9„ZJd:d;„ZKdd?„ZMdS)AéN)ÚPath)ÚDictÚListÚAnyÚOptionalÚTuple)Ú content_types)ÚOpenAI)Ú!extract_documents_text_compatibleÚcreate_document_extractor)Ú load_dotenvÚANTHROPIC_API_KEYÚANTHROPIC_MODELzclaude-3-5-haiku-latestÚOPENAI_API_KEYÚ OPENAI_MODELz Qwen/Qwen3-Next-80B-A3B-InstructÚ OPENAI_URLz#https://api.deepinfra.com/v1/openaiz/Path/to/Company/Info/summaryÚGEMINI_API_KEYz4%(asctime)s - %(name)s - %(levelname)s - %(message)s)ÚlevelÚformat)Úapi_keyÚ GENAI_ENGINEÚclaude)rÚbase_urlc@s4eZdZdZdZdZdZdZdZdZ dZ d Z d Z d S) ÚcolorzzzzzzzzzzN) Ú__name__Ú __module__Ú __qualname__ÚPURPLEÚCYANÚDARKCYANÚBLUEÚGREENÚYELLOWÚREDÚBOLDÚ UNDERLINEÚEND©r'r'ú.find_disclaimer_infocSs2zd|vr|d}t|dƒWSWdSYdS)z¼ Get the Y-coordinate of an annotation from its rectangle. Returns Y position or None if not available. In PDF coordinates, Y increases from bottom to top. z/Rectr+N)Úfloat)Úannotation_objÚrectr'r'r(Úget_annotation_y_positionksüþz9extract_links_from_pdf..get_annotation_y_positioncSsRz"|j}t|jƒ}t|ƒ}|dkr ||}|d|d}|WSWdSYdS)z“ Estimate the Y-coordinate where the disclaimer text appears. This is approximate since we're working with extracted text. rr+g333333÷?N)Úmediaboxr>ÚheightÚlen)r6r7Údisclaimer_positionrBÚ page_heightÚ text_lengthÚfractionÚ estimated_yr'r'r(Úestimate_disclaimer_y_position{s ûþz>extract_links_from_pdf..estimate_disclaimer_y_positionc sH|durdS||kr dS||krdSd|vr8d|dvr8|dd}||vr-t d¡dS||vr8t d¡dSˆ|ƒ} ˆ|||ƒ} | durn| durn| | kr^t d| d ›d | d ›d ¡dSt d| d ›d | d ›d ¡dSdD]&} | |vr–t|| ƒ} | r–| |vrŠt d¡dS| |vr–t d¡dSqpt d|d›d¡dS)zH Determine if a URL appears before the disclaimer text. NTFú/Aú/URIz(URI found before disclaimer (text match)z'URI found after disclaimer (text match)zAnnotation Y (z.1fz) > Disclaimer Y (z) - before disclaimerz) <= Disclaimer Y (z) - after disclaimer)z /Contentsz/Tz/TUz$Display text found before disclaimerz#Display text found after disclaimerz&Cannot determine URL position on Page r+z - skipping to be safe)r1Údebugr2Ústr) r?r5r6r7Údisclaimer_pageÚdisclaimer_char_posÚtext_before_disclaimerÚtext_after_disclaimerÚuriÚ annotation_yÚ disclaimer_yÚkeyÚ context_text©rJrAr'r(Úis_url_before_disclaimer”sF       €z8extract_links_from_pdf..is_url_before_disclaimerÚrbNz3No disclaimer section found - will extract all URLsz"Disclaimer section starts on Page r+z at character position z?Will include URLs before disclaimer, skip URLs after disclaimerzPage z&: Skipping (entirely after disclaimer)z/Annotsz/Subtypez/LinkrKrL)Úurlr6u: ✓ Extracted URL: u&: ✗ Skipped URL (after disclaimer): zError processing annotation: r[u: ✗ Skipped URL: z1No embedded links found, using text extraction...z'https?://(?:[-\w.]|(?:%[\da-fA-F]{2}))+z: Extracted URL from text: z/: Extracted URL from text (before disclaimer): Ú z<============================================================zSUMMARY: Total URLs extracted: z"No links found in the PDF documentcSóg|]}|d‘qS)r[r')Ú.0Úlinkr'r'r(Ú Fóz*extract_links_from_pdf..zError: z!Error extracting links from PDF: )ÚopenÚPyPDF2Ú PdfReaderr1r2Úsetr,r-r.Ú get_objectÚgetÚ isinstancerNÚappendÚaddÚ ExceptionrMÚ get_linksÚhasattrr[ÚAttributeErrorÚ TypeErrorÚreÚfindallÚrangerDÚerror)Úpdf_pathr=rYÚfiler3rOrPr;r<Ú all_linksÚ seen_urlsr5r6r7Ú annotationsÚ annotationÚannotation_objectrSÚeÚ page_linksr_Úurlsr[r'rXr(Úextract_links_from_pdfKsÚ?    þþ € €þ þ €ÿ     €üý    €ü   €  r*Žt€þr~c Cs¸|durt} g}|D]A}z | d|›¡t ||¡}| d|›d|›¡| |¡Wq tyL}z| d|›dt|ƒ›¡WYd}~q d}~ww| dt|ƒ›d|›¡|S)NzDownloading file from link: zDownloaded file from link z and saved to path zError downloading ú: zTotal downloaded files z at paths )r1r2ÚfdrÚdownload_file_mainrirkrNrD)Úbid_dirÚlinksÚprocess_loggerÚdownloaded_filesr_Ú file_pathr{r'r'r(Údownload_linked_documentsLs   &€ÿr‡csbt ¡}t|dƒ‰t‡fdd„dƒD]}| |¡qWdƒ| ¡S1s(wY| ¡S)z² Calculate SHA-256 hash of file content Args: file_path (Path): Path to the file Returns: str: Hexadecimal hash of the file content rZcs ˆ d¡S)Ni)Úreadr'©Úfr'r(Úus z%calculate_file_hash..óN)ÚhashlibÚsha256rbÚiterÚupdateÚ hexdigest)r†Ú sha256_hashÚ byte_blockr'r‰r(Úcalculate_file_hashgs  ÿ ÿür”c Cspt d|›¡tt|ƒ d¡ƒ}|st d¡ggfSi}|D] }t d|j›¡t|ƒ}||vr;|| |¡q |g||<q g}g}| ¡D]P\}}|d}| |¡|dd…D]<} zt   | ¡| | ¡t d| j›d |j›d ¡Wq\t y˜} zt d | j›d t | ƒ›¡WYd} ~ q\d} ~ wwqIt d t |ƒ›dt |ƒ›d¡dd„|Dƒdd„|DƒfS)aH Remove duplicate PDF files from a directory based on content. For each set of identical files, the first one found is kept and others are removed. Args: directory_path (str): Path to directory containing PDF files Returns: tuple: (kept_files, removed_files) lists of filenames u%🔠Checking for duplicate PDFs in: z*.pdfzNo PDF files foundz Analyzing: rr+NzRemoved duplicate: z (same as ú)zError removing rzKept z unique files, removed z duplicatescSsg|]}|j‘qSr')Úname)r^rŠr'r'r(r`¯sz)remove_duplicate_pdfs..)r1r2ÚlistrÚglobr–r”riÚitemsÚosÚremoverkrNrD) Údirectory_pathÚ pdf_filesÚhash_mapr†Ú file_hashÚ kept_filesÚ removed_filesÚ file_pathsÚ kept_fileÚ duplicater{r'r'r(Úremove_duplicate_pdfszs:       (€ÿû r¥cCsŠt|ƒ}| ¡st d|›¡gS| ¡s t d|›¡gSg}| ¡D]}| ¡r5| t|  ¡ƒ¡q&t dt |ƒ›d|›¡|S)zö Create a list of all files in the specified directory with their full paths. Args: directory_path (str): Path to the directory to scan Returns: list: List of full paths to all files in the directory zDirectory does not exist: zPath is not a directory: zFound z files in ) rÚexistsr1r2Úis_dirÚiterdirÚis_filerirNÚabsoluterD)rœÚdir_pathr¢Úitemr'r'r(Úlist_files_in_directory±s  €r­c sȇfdd„}‡fdd„}‡fdd„}gd¢}i}|D] }dgdd œ||<qtd d „| ¡Dƒƒ} |d | ›d ƒg} |dt|ƒ›dƒ| ¡D]î\} } tj | ¡} |d| ›dt| ƒ›dƒ|  ¡sk|d| ›ƒqHt| ƒ}d}t | ||ƒ}|dt|ƒ›dƒt |ƒD]°\}}|d}|d}t | |dt|ƒ|||ƒ}zst dkr·t jjd|gtjddddd }|j}n6t d!krÑtjjtdd"d#d$|d%œgd&}|jd"j}nt d'krítjjjtd(d#d%œd$|d%œgd)}|jd"jj}t|| ||ƒ}|  | ||||d*œ¡|d+|d›d,t|ƒ›d-| ›ƒWq…t y5}z|d.|d›d-| ›d/t!|ƒ›ƒWYd0}~q…d0}~wwqH|d1t| ƒ›ƒ|d2ƒt"|| |ƒ|d3ƒt#|ƒ|gdd"gd4œ|d5<|d6ƒ|| fS)7a Analyze tender documents with Claude LLM Args: documents_text (dict): Dictionary mapping file paths to their text content process_logger: Optional process logger for detailed logging Returns: dict: Extracted information from tender documents có t |¡ˆrˆ |¡dSdS©N©r1r2©Úmsg©r„r'r(Úlog_infoéó ÿz)analyze_tender_with_LLM..log_infocr®r¯©r1rsr±r³r'r(Ú log_errorîrµz*analyze_tender_with_LLM..log_errorcr®r¯)r1Úwarningr±r³r'r(Ú log_warningórµz,analyze_tender_with_LLM..log_warning) ú;Eligibility/Qualification Criteria or conditions for bidderzPre-bid meetingzEvaluation criteria or methodz"Documents needed to submit the bidz"Scope of work of the whole projectzAmount of EMD feeú?Relaxation or preference given to any kind of company or bidderz Payment termszBOQ requirementsÚRisksÚ RedliningÚ)ÚcontentÚ citationsÚsummarycss|]}t|ƒVqdSr¯)rD)r^Útextr'r'r(Ú s€z*analyze_tender_with_LLM..z&Total text size across all documents: ú characterszStarting LLM analysis of z documentszAnalyzing document: z (z characters)zSkipping empty document: i0uzSplit document into z chunksrÂÚ page_ranger+Úgeminizgemini-2.5-flashz\You are an expert in analyzing tender documents. Extract information with precise citations.i@çš™™™™™¹?©Úsystem_instructionÚmax_output_tokensÚ temperature©ÚmodelÚcontentsÚconfigrrzyYou are an expert in analyzing tender documents. Extract information with precise citations in the specified JSON format.Úuser©Úroler¿©rÍÚ max_tokensrËÚsystemÚmessagesÚopen_llmrÕ©rÍrÖ)Údoc_nameÚ chunk_idxrÅÚresponseÚ parsed_datazSuccessfully analyzed chunk ú/z of zError analyzing chunk z with LLM: Nz.)rV) rpÚfinditerÚ IGNORECASEÚintÚgroupÚstartriÚsortrerj) rrÚpatternsÚpatternÚmatchr5ÚpositionÚ seen_pagesÚunique_markersr'r'r(rås$ ÿý  €råc Csâg}t|ƒ|krtdt|ƒ|ƒ}| ||dt|ƒdœ¡|Sd}|t|ƒkro||}|t|ƒkrS| d||¡}|||dkrB|}n| d||¡}|||dkrS|}t|||ƒ}| |||…|||dœ¡|}|t|ƒks&|S)a7 Create text chunks while tracking which pages each chunk spans Args: doc_text (str): Document text chunk_size (int): Maximum chunk size page_markers (list): List of page markers with positions Returns: list: List of chunk dictionaries with text and page range r)rÂrÅÚ start_posÚend_posz gffffffæ?r\gš™™™™™é?)rDÚget_page_range_for_textriÚrfind) rrrÚchunksrÅrÚendÚ paragraph_endÚline_endr'r'r(ræ£s< ü    ü éræc Cs¢|sddgdœSd}d}t|ƒD] \}\}}||kr|}qt|ƒD] \}\}}||kr/|}q"g}|durD|durDtt||dƒƒ}n|durK|g}|||dœS)zþ Determine which pages a text span covers Args: start_pos (int): Start position in text end_pos (int): End position in text page_markers (list): List of page markers Returns: dict: Page range information N)Ú start_pageÚend_pager-r+)r,r—rr) rrrr r!Úir5rr-r'r'r(rØs* ýrc Cs`d dd„t|ƒDƒ¡}d}|drd|d›}d|›d|›d |›d|›d |›d |›d }|S) z‘ Create a balanced prompt that extracts all categories with equal attention while providing category-specific guidance where needed. r\cSs"g|] \}}|d›d|›‘qS)r+z. r')r^r"r¬r'r'r(r` s"z*create_citation_prompt..r¾r-zThis chunk spans pages: zt You are analyzing tender/RFP documents for comprehensive information extraction with precise citations. Document: z Chunk: rÝuL â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â• TASK: Extract ALL of the following information categories from this chunk diligently. â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â• CATEGORIES TO EXTRACT: uG2 â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â• SECTION 1: UNIVERSAL RULES (Apply to ALL categories) â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â• ã€CITATION RULES】- Apply to EVERY category extracted: • Extract the EXACT text span that contains the relevant information • Use page numbers from "--- Doc Page Number: X ---" markers in the document • If no specific page number found, use null • Confidence ratings: - high: Direct, unambiguous information - medium: Implied or partially stated information - low: Inferred or unclear information ã€FORMATTING RULES】- Apply to EVERY category's content: • Clean up and rephrase content - don't copy verbatim. Summarize and rephrase information. • Use markdown: **bold headings**, *italics for emphasis*, bullet points • Use proper paragraph breaks and logical organization with clear spacing • Make content user-friendly and easy to understand ã€OUTPUT FORMAT】- Required JSON structure: { "extracted_data": [ { "category": "Category name", "found": true/false, "content": "Well-formatted, rephrased information with proper structure and line breaks", "citations": [ { "text_span": "Exact text from document that supports this information", "page_number": page_number_or_null, "confidence": "high/medium/low" } ] } ] } â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â• SECTION 2: CATEGORY-SPECIFIC GUIDANCE â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â• Below are specific instructions for categories that need additional clarity. For categories not listed here, apply standard extraction using the universal rules above. ┌─────────────────────────────────────────────────────────────────────────────┠│ CATEGORY: Eligibility/Qualification Criteria │ └─────────────────────────────────────────────────────────────────────────────┘ Extract ALL criteria bidders must meet: • Financial criteria (turnover, net worth requirements) • Technical criteria (experience, past work orders, certifications) • Legal criteria (registration requirements, not blacklisted) • Capacity criteria (equipment, manpower) • Any minimum/maximum thresholds specified Include specific values, percentages, and time periods mentioned. ┌─────────────────────────────────────────────────────────────────────────────┠│ CATEGORY: Pre-bid meeting │ └─────────────────────────────────────────────────────────────────────────────┘ Extract if any information is given: • Date and time of the meeting • Mode (online/offline/hybrid) • Venue or online meeting link • Contact details for queries ┌─────────────────────────────────────────────────────────────────────────────┠│ CATEGORY: Evaluation criteria or method │ └─────────────────────────────────────────────────────────────────────────────┘ Extract the complete evaluation methodology: • Scoring criteria and weightages • Technical vs commercial evaluation split • Minimum qualifying marks/scores • Complete scoring tables if specified • L1/lowest bid selection criteria ┌─────────────────────────────────────────────────────────────────────────────┠│ CATEGORY: Documents needed to submit the bid │ └─────────────────────────────────────────────────────────────────────────────┘ Focus on documents that bidders should submit with their bids, such as certificates, experience letters, financial documents, compliance statements etc. If a document is mentioned as 'Additional Doc 1 (Requested in ATC) or Additional Document 2 (Requested in ATC) etc' in the RFP/Tender, it needs to be ignored. These are documents with generic description like 'Additional document format as specified in ATC'. These documents should not be included in the final list of documents. *Also DO NOT include any annexures, forms, proformas given in the RFP document chunk in this list.* Annexures will be taken care of separately. ┌─────────────────────────────────────────────────────────────────────────────┠│ CATEGORY: Amount of EMD fee │ └─────────────────────────────────────────────────────────────────────────────┘ Extract: • Exact EMD amount • Mode of payment (DD, BG, online, etc.) • Bank details if specified ┌─────────────────────────────────────────────────────────────────────────────┠│ CATEGORY: Relaxation or preference │ └─────────────────────────────────────────────────────────────────────────────┘ Extract any preferences given to: • MSE/MSME bidders • Startups (DIPP registered) • SC/ST owned enterprises • Local suppliers • Make in India preferences • Any turnover/experience relaxations • Any EMD Fee relaxations ┌─────────────────────────────────────────────────────────────────────────────┠│ CATEGORY: Payment terms │ └─────────────────────────────────────────────────────────────────────────────┘ Extract complete payment structure: • Payment milestones and percentages • Advance payment provisions • Running bill/monthly payment terms • Final payment conditions • Payment timeline after bill submission • Any deductions (retention, taxes) ┌─────────────────────────────────────────────────────────────────────────────┠│ CATEGORY: BOQ requirements │ └─────────────────────────────────────────────────────────────────────────────┘ Extract: • Bill of Quantities structure • How rates should be quoted (per unit, lump sum, percentage) • Any specific BOQ filling instructions • Price variation clauses • Quantity variation limits ┌─────────────────────────────────────────────────────────────────────────────┠│ CATEGORY: Scope of work │ └─────────────────────────────────────────────────────────────────────────────┘ Extract: • Main deliverables and activities • Work location/site details • Duration/timeline • Key milestones • Contractor's responsibilities • Items/services included and excluded ┌─────────────────────────────────────────────────────────────────────────────┠│ CATEGORY: Risks │ └─────────────────────────────────────────────────────────────────────────────┘ Extract all risky clauses: • Penalty clauses • Liquidated Damages (LD) / Mutually Agreed Damages (MAD) • Indemnification requirements • Termination conditions • Forfeiture conditions • Liability caps or unlimited liability • Force majeure exclusions ┌─────────────────────────────────────────────────────────────────────────────┠│ CATEGORY: Redlining │ └─────────────────────────────────────────────────────────────────────────────┘ Identify potential queries/clarifications for: • Ambiguous terms or conditions • One-sided or unfair clauses • Missing information that should be clarified • Terms that could be negotiated in pre-bid meeting • Inconsistencies in the document â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â• SECTION 3: FINAL REMINDERS â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â• ✦ Extract ALL 12 categories - do not skip any ✦ If a category is not found in this chunk, mark found: false and content: "Not found in this chunk" ✦ Apply CITATION RULES to every extraction ✦ Apply FORMATTING RULES to all content ✦ Each category deserves equal attention and thoroughness â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â• DOCUMENT CHUNK TO ANALYZE: â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â• u­ â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â• Return ONLY the JSON response with all 12 categories. No additional text. Use proper markdown formatting (**bold**, *italic*, bullet points, proper spacing, line breaks) in content fields. )Újoinr,) rÙrÚÚ total_chunksrrûrÅÚcategories_listÚ page_inforr'r'r(rçs*ýüüû ô<ÄCrçcCsØzt |¡WStjyYnwz*| dd¡}| dd¡}| dd¡}| dd¡}| d d¡}| d d ¡}t |¡WStjyEYnwz | dd ¡}t |¡WStjy\Ynwt d |dd…›d¡|S)z3Safely parse JSON with multiple fallback strategiesú\z\\z\\nz\nz\\tz\tz\\rz\rz\\\\z\\"z\"r¾zCould not parse JSON: Nédú...)ÚjsonÚloadsÚJSONDecodeErrorÚreplaceÚloggingr¸)Ú json_stringÚdefaultÚ fixed_stringÚcleaned_stringr'r'r(Úsafe_json_parseÕs0 ÿ       ÿ  ÿr3c Cs¶z2t d|tj¡}|r| d¡}nt d|tj¡}|r!| d¡}ntdƒ‚t|ƒ}t||||ƒ}|WStyZ}zt  d|›d|›dt |ƒ›¡t |||ƒWYd }~Sd }~ww) a, Parse LLM response and extract structured data with citations Args: response_text (str): Raw LLM response doc_name (str): Document name chunk_idx (int): Chunk index chunk_text (str): Original chunk text Returns: dict: Parsed structured data z```json\s*(.*?)\s*```r+z\{.*\}rzNo JSON found in responsezError parsing LLM response for z chunk rN) rpÚsearchÚDOTALLrÚ ValueErrorr3Úvalidate_and_enhance_citationsrkr1r2rNÚfallback_text_parsing) rrÙrÚrÚ json_matchÚjson_strrÜÚ enhanced_datar{r'r'r(rö÷s$   ÿ €ýröc Csìdgi}d|vr |S|dD]e}| dd¡sq| dd¡d| dd¡gd œ}| d g¡D];}|| d d¡| d ¡|| d d¡dœ}|d } | r`|  ¡| ¡vr`| ¡ |  ¡¡} | dkr`| |d<|d  |¡q,|d rs|d |¡q|S)a+ Validate and enhance citation data from LLM response Args: parsed_data (dict): Parsed JSON data from LLM doc_name (str): Document name chunk_idx (int): Chunk index chunk_text (str): Original chunk text Returns: dict: Enhanced citation data Úextracted_dataÚfoundFÚcategoryÚUnknownTr¿r¾)r>r=r¿rÀrÀÚ text_spanÚ page_numberÚ confidenceÚmedium)Ú document_namer@rAÚ chunk_indexrBr*Ú text_position)rgr/r0ri) rÜrÙrÚrr;r¬Ú enhanced_itemÚcitationÚenhanced_citationr@Ú span_positionr'r'r(r7s8     ü  û €r7cCs dgi}|S)zû Fallback method to parse text when JSON parsing fails Args: response_text (str): Raw response text doc_name (str): Document name chunk_idx (int): Chunk index Returns: dict: Basic parsed data structure r<r')rrÙrÚr<r'r'r(r8Us r8c Cs|D]†}d|vr q|d}|d}|d}| dg¡D]l}| dd¡}d} |D]} | ¡|  ¡vs9|  ¡| ¡vr=| } nq'| sAq| dd¡} | r‡|  ¡r‡|| dri|| dd |›d |d ›d | ›7<nd |›d |d ›d | ›|| d<|| d | dg¡¡qqdS)a  Combine all chunk analyses into final structured output with citations Args: extracted_info_with_citations (dict): Final output dictionary doc_analyses (list): List of chunk analyses info_to_extract (list): Categories to extract rÜrÙrÚr<r>r¾Nr¿z --- From z (chunk r+z) --- z --- From rÀ)rgr/räÚextend) rürþrûÚanalysisrÜrÙrÚr¬r>Úmatching_categoryÚextract_categoryr¿r'r'r(r÷gs6   þ   ,"  ÿ€êør÷cCs²| ¡D]R\}}|d}|d}|r| ¡dkrd|d<n&| d¡}t|ƒdkr;t|ƒdkr6|d d…d n||d<n|d d|d<t|ƒ|d <ttd d„|Dƒƒƒ|d<qd S)zŒ Generate summaries for each category Args: extracted_info_with_citations (dict): Extracted information with citations r¿rÀr¾zNo information foundrÁÚ.ééÈNr)rrÞcSr])rDr')r^Úcr'r'r(r`ªraz/generate_category_summaries..rß)r™räÚsplitrDr—re)rür>Údatar¿rÀÚ sentencesr'r'r(rø“s   & ðrøc Cs4tj |d¡}tj|ddtj |d¡}tj |d¡}t|dƒ}tj||ddWd ƒn1s4wYt|dd d F}| d ¡| d ¡| ¡D]/\}}| |›d¡| dt |ƒd¡| |  ¡pmd¡| d¡d|vr~|d  ¡} qOWd ƒn1s‰wYt   d|›¡|| fS)zé Save extracted information to a file Args: bid_dir (str): Directory to save the file to extracted_info (dict): Extracted information to save Returns: str: Path to the saved file Útender_analysisT)Úexist_okztender_analysis.txtztender_analysis.jsonÚwé)ÚindentNzutf-8)ÚencodingzTENDER ANALYSIS REPORT z4================================================== r\Ú-zNot found in the documentsz6 ================================================== Ú Eligibilityr¿zSaved extracted information to ) ršrâr#Úmakedirsrbr*ÚdumpÚwriter™rDrär1r2) r‚Úextracted_infoÚ output_pathÚoutput_text_fileÚoutput_json_filerurŠr>r2Ú eligibilityr'r'r(Úsave_extracted_info¬s,  ÿ    €úü rfcCst dt›¡dS)zj Get company information from Google Docs Returns: str: Company information text z!Getting company information from uh Yugasa Company Information for Government tendering: Company Name: Yugasa Software Labs Pvt Ltd Office addresses: Gurgaon Address: Yugasa Software Labs, 3rd floor, Tower B, Unitech Cyber Park, Sector 39, Gurgaon 122001, Haryana Lucknow Address: Yugasa Software Labs, 3rd floor, TC-14, Vibhuti Khand, Gomti Nagar, Lucknow, Uttar Pradesh 226010 US Address: Yugasa Software LLC, 370 Campus Drive, Somerset, New Jersey 08873 Company registration: Yugasa Software Labs Pvt Ltd is a legal entity in India registered under Indian Companies Act, 2013. Registered as Private Limited Company with Registrar of Companies, Delhi. The CIN of the company is U72900HR2015PTC056837 Company website: www.yugasa.com Company Phone: +918800522257 Company Email: contact@yugasa.com Contact Person: Dharmesh Jaggi Person Authorized to sign Bid Documents: Dharmesh Jaggi PAN of Yugasa: AAACY7582J Certifications: CMMI 3 ISO 27001:2022 ISO 9001:2015 Valid GST registration. GST Number of Yugasa: 06AAACY7582J1ZU Yugasa is the official Meta Business Partner as ISV solution provider for WhatsApp. Turnover of previous years: 2024-25: INR 3.52 Crores 2023-24: INR 3.29 Crores 2022-23: INR 3.19 Crores 2021-22: INR 3.35 Crores 2020-21: INR 2.18 Crores Yugasa software Labs Pvt Ltd is not barred or blacklisted by any PSU, government department, or private sector entity. Yugasa software labs pvt ltd is an MSME and registered Startup Manpower on Yugasa’s payroll: Currently Yugasa has 40 employees on its payroll. Some previously done projects of Yugasa: Project 1 Client Name: Narayana Hospitals Project Title: Development and Implementation of WhatsApp Business API Solution and AI-enabled Chatbot for support automation Project Scope: - Integration of WhatsApp Business API with NH's existing systems - Development of AI-enabled chatbot for patient interaction and support management - Multi-language support including English and regional languages - Real-time response and query resolution for patients - Continuous support and maintenance of the chatbot system Project Value: The total value of the project till date is INR 30,35,605, and the project is ongoing. Project Duration: September 30th, 2022 to Present (Ongoing) Project 2 Client Name: NSC Guwahati NSC Guwahati is a Ministry of Culture organization Project Title: Cashless ticket booking chatbot on WhatsApp. Project Value: INR 14 lakhs )r1r2ÚCOMPANY_INFO_DOCr'r'r'r(Úget_company_infoÐs rhc sê‡fdd„}‡fdd„}|dƒ| dd¡d}| d d¡d}|d t|ƒ›d ƒ|d t|ƒ›d ƒd |›d|›d|›d}z|dt›dƒtdkratjjd|gtjddddd}|j} n6tdkr{t j j t dddd|dœgd}|j dj} ntdkr—tjjj td ddœd|dœgd!}|jdjj } |d"t| ƒ›d ƒ|d#| ›ƒd$|  ¡v} t d%| tj¡} | r¿|  d&¡ ¡nd'} |d(| rÇd)nd*›ƒ| | fWStyô} z|d+t| ƒ›ƒd,d-t| ƒ›fWYd.} ~ Sd.} ~ ww)/a% Check if the company is eligible for the bid Args: extracted_info (dict): Extracted tender information company_info (str): Company information process_logger: Optional process logger for detailed logging Returns: tuple: (is_eligible, reason) cr®r¯r°r±r³r'r(r´1rµz#check_eligibility..log_infocr®r¯r¶r±r³r'r(r·6rµz$check_eligibility..log_errorzStarting eligibility check...rºr¾r¿r»zEligibility criteria length: rÄzExemptions length: zÞ You need to determine if the company is eligible to apply for a tender based on the eligibility criteria, exemptions to some special type of companies (if any), and company information. Eligibility Criteria: z Exemptions: z Company Information: a3 Please analyze if the company meets all the eligibility criteria. Return your answer in the following format: Eligible: [Yes/No] Reason: [Detailed explanation of why the company is eligible or not] Missing Requirements: [List any requirements the company doesn't meet, if applicable] z Calling LLM (z) for eligibility assessment...rÆzgemini-2.5-flash-preview-04-17z^You are an expert in tender eligibility assessment. Be thorough and accurate in your analysis.iÐrÇrÈrÌrrrÐrÑrÓr×rÕrØzEligibility response received: zEligibility response: z eligible: yesz!Reason:\s*(.*?)(?:\n\n|\n[A-Z]|$)r+zNo detailed reason providedz%Eligibility check completed. Result: ÚEligiblez Not Eligiblez%Error checking eligibility with LLM: Fz Error during eligibility check: N)rgrDrèrérêrërìrírÂrîrÖrïrðr¿rñròrórrôrõr/rpr4r5rrärkrN)raÚ company_infor„r´r·Úeligibility_criteriaÚ exemptionsrrÛrÚ is_eligibleÚ reason_matchÚreasonr{r'r³r(Úcheck_eligibility$sr üù öýý ÿû þþ  €þrpr¯)NršÚshutilÚtimerpÚrequestsrcÚ anthropicrr.ÚpathlibrÚbid_prep_automationÚbpaÚ bid_queriesÚbqÚfile_download_robustr€ÚargparseÚsysr*ÚtypingrrrrrÚgoogle.generativeaiÚ generativeaiÚgenaiÚgoogle.generativeai.typesrrìrñr Údocument_extractorr r Údotenvr Úgetenvr rrrrrgrÚ basicConfigÚINFOÚ getLoggerrr1Ú configurerérèÚ Anthropicrîrðrr~r‡r”r¥r­r rårærrçr3rör7r8r÷rørfrhrpr'r'r'r(Ús‚               þ  7 ,#$5- Q"(6,$T