diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..32910dac1b437843b3e22cb3c3b125f99b1434c2 --- /dev/null +++ b/.gitignore @@ -0,0 +1,32 @@ +# --- Python --- +__pycache__/ +*.py[cod] +*$py.class +*.egg-info/ +.env +venv/ +.venv/ + +# --- Node --- +node_modules/ +.next/ +npm-debug.log* + +# --- IDE --- +.idea/ +.vscode/ +*.swp +*.swo + +# --- OS --- +.DS_Store +Thumbs.db + +# --- Env files (keep .example, ignore actual keys) --- +.env.local +.env.production +backend/.env + +# --- Runtime artifacts --- +dump.rdb +*.rdb diff --git a/MASTER_PLAN.md b/MASTER_PLAN.md new file mode 100644 index 0000000000000000000000000000000000000000..390e44c20268d095fefd50a7bf4939fd0329e172 --- /dev/null +++ b/MASTER_PLAN.md @@ -0,0 +1,205 @@ +# Bio Nexus Platform — Master Plan v3.0 + +> A bioinformatics pipeline engine that removes the need for expertise to get expert results. +> User arrives with a biological question and raw data. Leaves with a complete, interpreted answer — having touched nothing in between. +> +> Solo founder · Indian M.Sc. bioinformatics grad · Product-first + +--- + +## 1. What the Product Actually Is + +Not a tool aggregator. Not a BLAST wrapper with AI on top. + +The current experience: + +``` +NCBI → paste sequence → BLAST → confusing output → copy accession → +open UniProt → new tab → scroll entry → open AlphaFold → new tab → +download PDB → open PyMOL → read 3 papers → give up or ask a senior +``` + +Bio Nexus: + +``` +Paste sequence → press Run → read one comprehensive page that explains everything +``` + +This is a **pipeline engine**. Every tool output flows into a results aggregator that normalizes, cross-references, and passes the complete picture to both the visualization layer and the AI interpretation layer simultaneously. The AI doesn't just see BLAST output — it sees what the sequence is, what homologs exist with statistical confidence, what the function annotation says, and what the structure looks like. + +**New bioinformatics tools become new modules. The architecture never changes — only the pipeline library grows.** + +--- + +## 2. Target User + +**NOT** IIT computational biology faculty (they already have workflows). + +The real users: +- **M.Sc. bioinformatics student at JMI or central university** — learning but doesn't know the toolchain +- **PhD student in biochemistry** — suddenly needs to analyze a protein sequence, uncomfortable with CLI +- **MBBS researcher at AIIMS** — found an interesting variant, doesn't know what to do +- **M.Sc. biotechnology final-year project student** — needs results, not tool expertise + +These people exist in enormous numbers. They have severe unmet need. You can reach them directly because you **are** one of them. + +Pricing reflects this reality: + +| Tier | Price | Verification | Users | +|------|-------|--------------|-------| +| Student | ₹0 | `.edu.in` email | Current students | +| Individual | ₹299/mo | — | Early-career researchers | +| Lab | ₹999/mo (3–5 seats) | — | Small research groups | +| Institution | Custom | — | University-wide license | + +The free student tier is not a loss — it's the growth strategy. Students graduate, become postdocs, become faculty, become the people who approve institutional licenses. + +--- + +## 3. Competitive Moat + +Galaxy Project: free, open-source, 15 years old, hundreds of tools, trusted by reviewers. + +You cannot beat Galaxy on **breadth** or **reputation**. + +You beat them on: + +1. **AI interpretation** — Galaxy has none. Results come back raw. Bio Nexus explains everything in plain language. +2. **Zero setup** — Galaxy requires an account, a server, or an institutional deployment. Bio Nexus requires a Google login. +3. **Plain language output** — designed explicitly for people who aren't bioinformatics experts. This is the real differentiation. + +--- + +## 4. Architecture + +``` +User input +├── Sequence (FASTA) +├── Gene list +├── FASTQ files (Phase 3) +└── Structure (PDB ID) + │ + ▼ +Pipeline selector + "What do you have?" → "What do you want to know?" → pipeline chosen + │ + ▼ +Pipeline engine + Task DAG · async workers · Redis queue · Supabase Realtime progress + │ + ├── BLAST (EBI REST API: nr, swissprot, pdb) + │ E-value · bit score · % identity · coverage + │ + ├── UniProt (REST lookup) + │ Function · domains · disease associations · 24h Redis cache + │ + ├── AlphaFold DB (Phase 1) + │ 3Dmol.js render · in-browser only · no downloads + │ + ├── Phase 2 modules + │ MSA · Phylogenetic tree · Pfam domains + │ KEGG pathways · Primer3 · DiffDock (via Replicate) + │ + └── Phase 3 modules + RNA-seq · Variant calling · ChIP-seq + │ + ▼ +Results aggregator ◄── THE KEY PIECE YOUR CURRENT CODEBASE MISSES + Merges all tool outputs into structured JSON + Normalises formats · resolves cross-references (accession→UniProt→PDB) + Hands complete picture to AI + visualisation simultaneously + │ + ├── Visualisation layer + │ MSA viewer · 3D structure · Phylogenetic tree + │ All in-browser · nothing downloads + │ + └── AI interpretation (LiteLLM · streaming) + Plain language report · citation links · confidence indicators + │ + ▼ +Unified result page + One URL · shareable · exportable (PDF) · explainable to a first-year M.Sc. student +``` + +--- + +## 5. Phase Breakdown + +### Phase 1 — Prove the pipeline engine works (Months 1–4) + +One workflow. Done better than anyone else has done it. No feature creep. + +**Workflow**: Protein sequence → BLAST (EBI) → UniProt annotation → AlphaFold structure → AI report + +**Output**: A single result page: +- Top BLAST hits with E-value and identity clearly explained +- UniProt entry distilled to what matters (function, disease associations, active sites, organism) +- AlphaFold structure rendered in-browser with 3Dmol.js — nothing downloads +- AI section that ties it all together in plain language a first-year M.Sc. student can read and act on + +No one offers this. Galaxy makes you build a workflow manually. EMBL-EBI runs each tool separately. Nobody gives a unified interpreted result. + +### Phase 2 — Expand the pipeline library (Months 5–10) + +New pipelines: +- **MSA + phylogenetic tree** — paste sequences, get a tree with evolutionary distances explained +- **Domain & motif analysis** — Pfam, PROSITE — what are the functional regions +- **Gene ontology + KEGG enrichment** — given a gene list, what processes are enriched +- **Primer design** — Primer3 integration, conditions included +- **Molecular docking** — DiffDock via Replicate (GPU inference API, not local) + +Pipeline selector UI: "What do you have?" → "What do you want to know?" → pipeline recommended automatically + +### Phase 3 — Handle raw sequencing data (Months 11–18) + +- FASTQ → QC → trimming → alignment → variant calling → annotation → interpreted report +- RNA-seq differential expression +- Larger infrastructure: file storage, longer jobs, more compute +- Significantly expands user base from coursework students to researchers doing published work + +### Phase 4 — Platform + collaboration (Months 19–30) + +- Lab workspaces (PI + students share a project) +- Custom pipeline builder for advanced users +- Institution licensing +- API access for programmatic use + +--- + +## 6. What Changes Right Now + +| Principle | Action | +|-----------|--------| +| Pipeline engine | Build results aggregator that merges BLAST + UniProt + AlphaFold + AI into one output | +| Unified result page | Replace separate BLAST/UniProt tabs with single pipeline results view | +| Student-first | `.edu.in` free tier, ₹299 individual, ₹999 lab | +| Honest AI | Working Groq key installed. Fallback shows visible banner, not fake analysis | +| Outreach | Target M.Sc./PhD/MBBS students. One question: "Walk me through the last sequence you tried to analyze" | +| Architecture | Aggregator layer normalises cross-tool output. AI sees the complete picture, not just one tool's output | + +--- + +## 7. Weekly Rhythm + +``` +Mon–Thu Build (pipeline engine, aggregator, one module at a time) +Fri 2–3 user calls (students, not faculty) +Sat Feedback → incorporate → build-in-public post +Sun Plan next week — no coding +``` + +**Hard rule**: Two weeks without a user call → stop building, make calls. + +--- + +## 8. The Honest Challenges + +1. **Working AI key** — Groq is installed and tested. If API calls fail, the user sees a visible yellow banner, not fake analysis. +2. **Real user conversations** — Before Phase 2, need 10 conversations with students who tried to analyze a sequence. Ask: "What did you open, what went wrong, how long did it take?" +3. **GPU budgeting** — DiffDock requires a paid inference API (Replicate). Student tier won't include it. Lab tier ($999/mo) covers the cost. +4. **Galaxy comparison** — Deep answer: Galaxy gives power users flexibility. Bio Nexus gives non-experts answers. The markets barely overlap. + +--- + +*Bio Nexus Platform — Master Plan v3.0* +*Pipeline engine · Student-first · India-built* diff --git a/bio-nexus/phase0/OUTREACH.md b/bio-nexus/phase0/OUTREACH.md new file mode 100644 index 0000000000000000000000000000000000000000..039d3caad76d06e95b06b30c8894ba5708b1a925 --- /dev/null +++ b/bio-nexus/phase0/OUTREACH.md @@ -0,0 +1,110 @@ +# Phase 0 — Researcher Validation (30+ Calls) + +## Target List + +### Priority 1 — M.Sc. Bioinformatics Programs at Central Universities (15 contacts) +| # | Name | Institution | Program | Contact | Status | +|---|------|-------------|---------|---------|--------| +| 1 | | Jamia Millia Islamia | M.Sc. Bioinformatics | Dept office → student group | | +| 2 | | AMU Aligarh | M.Sc. Bioinformatics | Dept office → student group | | +| 3 | | JNU New Delhi | M.Sc. Computational Biology | Dept office → student group | | +| 4 | | University of Hyderabad | M.Sc. Bioinformatics | Dept office → student group | | +| 5 | | Pondicherry University | M.Sc. Bioinformatics | Dept office → student group | | +| 6 | | University of Pune | M.Sc. Bioinformatics | Dept office → student group | | +| 7 | | University of Calcutta | M.Sc. Bioinformatics | Dept office → student group | | +| 8 | | University of Madras | M.Sc. Bioinformatics | Dept office → student group | | +| 9 | | Bharathiar University | M.Sc. Bioinformatics | Dept office → student group | | +| 10 | | Banaras Hindu University | M.Sc. Bioinformatics | Dept office → student group | | +| 11 | | University of Kerala | M.Sc. Bioinformatics | Dept office → student group | | +| 12 | | Goa University | M.Sc. Bioinformatics | Dept office → student group | | +| 13 | | North-Eastern Hill University | M.Sc. Bioinformatics | Dept office → student group | | +| 14 | | Tezpur University | M.Sc. Bioinformatics | Dept office → student group | | +| 15 | | University of Jammu | M.Sc. Bioinformatics | Dept office → student group | | + +### Priority 2 — PhD Students (Wet-lab, Need Bioinformatics) (10 contacts) +| # | Name | Institution | Lab/Dept | Contact | Status | +|---|------|-------------|----------|---------|--------| +| 16 | | AIIMS Delhi | Biochemistry PhD | Reach through PubMed → contact | | +| 17 | | AIIMS Delhi | Pharmacology PhD | Reach through PubMed → contact | | +| 18 | | NCBS Bangalore | PhD student | Reach through student groups | | +| 19 | | CCMB Hyderabad | PhD student | Reach through student groups | | +| 20 | | IISc Bangalore | PhD (Biochemistry) | Reach through department | | +| 21 | | JNU | PhD (Life Sciences) | Reach through department | | +| 22 | | University of Delhi | PhD (Zoology) | Reach through department | | +| 23 | | CSIR-IGIB | PhD student | Reach through student groups | | +| 24 | | IIT Bombay | PhD (Biosciences) | Reach through department | | +| 25 | | IISER Pune | PhD (Biology) | Reach through department | | + +### Priority 3 — MBBS / MD Researchers (5 contacts) +| # | Name | Institution | Dept | Contact | Status | +|---|------|-------------|------|---------|--------| +| 26 | | AIIMS Delhi | Junior Resident | Reach through student groups | | +| 27 | | AIIMS Delhi | MD Biochemistry | Reach through PubMed → contact | | +| 28 | | Maulana Azad Medical College | MBBS + research | Reach through college groups | | +| 29 | | JIPMER Pondicherry | MD / MS student | Reach through college groups | | +| 30 | | CMC Vellore | MBBS + research elective | Reach through college groups | | + +--- + +## Cold Outreach Template — For Students + +**Subject:** 15 min — struggling with BLAST / protein analysis? + +Hey [Name], + +I'm a fellow M.Sc. bioinformatics student building a tool that makes protein sequence analysis instant — paste a sequence, get a complete interpreted result without touching NCBI, UniProt, or any command line. + +I'd love 15 minutes to understand: +1. What do you do when you need to analyze a protein sequence? +2. What's the most frustrating step? +3. Would instant AI-powered results help? + +This is purely a research conversation — no sales pitch, no demo. Just trying to build something useful for people like us. + +Want to hop on a quick call this week? + +Best, +Samad (you are yourself) +Bio Nexus + +--- + +## Call Script (15 minutes) + +### Opening (1 min) +- "I'm building a bioinformatics tool and want to make sure I'm solving real problems real students face. Not a sales call — I want your honest frustration." + +### The One Question (10 min) +- **"Walk me through the last time you tried to analyze a biological sequence."** + +Follow-ups (only if needed): +- What tools did you open first? +- What went wrong or was confusing? +- How long did it take from start to having an answer? +- Did you ask someone for help? Who? + +### Closing (4 min) +- "If you could wave a magic wand and fix one thing about that process, what would it be?" +- "Is there anyone else in your class/lab who has the same problem?" +- "Want early access to try the prototype?" + +### Post-Call +- Log feedback in TRACKER.md immediately +- Add to Beta Users list if interested +- Send a thank-you text within an hour + +--- + +## Beta Signup Incentive +- Free lifetime Student tier for first 50 beta testers +- Your name in the "Thanks to" list on launch +- Direct line to the founder (me) for feature requests + +--- + +## Success Metrics +- [ ] 30+ calls completed +- [ ] 10+ beta signups +- [ ] 5+ concrete stories of "Here's what I did last week and it was painful" +- [ ] 3+ student groups / WhatsApp groups joined for outreach +- [ ] 1+ referral to another student diff --git a/bio-nexus/phase0/TRACKER.md b/bio-nexus/phase0/TRACKER.md new file mode 100644 index 0000000000000000000000000000000000000000..88af93f129cb16200fd6dc5ee3fd3764742cbbb1 --- /dev/null +++ b/bio-nexus/phase0/TRACKER.md @@ -0,0 +1,97 @@ +# Phase 0 — Student Validation Tracker + +## Status Legend +- [ ] Not contacted +- [~] Message sent, awaiting response +- [x] Call completed +- [!] Interested / Beta signup +- [-] Not interested / No response + +--- + +## Priority 1: M.Sc. Bioinformatics Programs (Central Universities) + +| # | Institution | Program | Contact | Status | Notes | +|---|-------------|---------|---------|--------|-------| +| 1 | Jamia Millia Islamia | M.Sc. Bioinformatics | Find student group WhatsApp/Telegram | [ ] | Your own program — easiest entry | +| 2 | AMU Aligarh | M.Sc. Bioinformatics | Reach via departmental mail | [ ] | | +| 3 | JNU New Delhi | M.Sc. Computational Biology | Find student group | [ ] | | +| 4 | University of Hyderabad | M.Sc. Bioinformatics | Find student group | [ ] | | +| 5 | Pondicherry University | M.Sc. Bioinformatics | Find student group | [ ] | | +| 6 | University of Pune | M.Sc. Bioinformatics | Find student group | [ ] | | +| 7 | University of Calcutta | M.Sc. Bioinformatics | Find student group | [ ] | | +| 8 | University of Madras | M.Sc. Bioinformatics | Find student group | [ ] | | +| 9 | Bharathiar University | M.Sc. Bioinformatics | Find student group | [ ] | | +| 10 | Banaras Hindu University | M.Sc. Bioinformatics | Find student group | [ ] | | +| 11 | University of Kerala | M.Sc. Bioinformatics | Find student group | [ ] | | +| 12 | Goa University | M.Sc. Bioinformatics | Find student group | [ ] | | +| 13 | NEHU Shillong | M.Sc. Bioinformatics | Find student group | [ ] | | +| 14 | Tezpur University | M.Sc. Bioinformatics | Find student group | [ ] | | +| 15 | University of Jammu | M.Sc. Bioinformatics | Find student group | [ ] | | + +## Priority 2: PhD Students (Wet-lab needing bioinformatics) + +| # | Name | Institution | Lab/Dept | Status | Notes | +|---|------|-------------|----------|--------|-------| +| 16 | | AIIMS Delhi | Biochemistry PhD | [ ] | Reach via PubMed → email | +| 17 | | AIIMS Delhi | Pharmacology PhD | [ ] | Reach via PubMed → email | +| 18 | | NCBS Bangalore | PhD student | [ ] | Reach via student groups | +| 19 | | CCMB Hyderabad | PhD student | [ ] | Reach via student groups | +| 20 | | IISc Bangalore | PhD (Biochemistry) | [ ] | Reach via department | +| 21 | | JNU | PhD (Life Sciences) | [ ] | Reach via department | +| 22 | | University of Delhi | PhD (Zoology) | [ ] | Reach via department | +| 23 | | CSIR-IGIB | PhD student | [ ] | Reach via student groups | +| 24 | | IIT Bombay | PhD (Biosciences) | [ ] | Reach via department | +| 25 | | IISER Pune | PhD (Biology) | [ ] | Reach via department | + +## Priority 3: MBBS / MD Researchers + +| # | Name | Institution | Status | Notes | +|---|------|-------------|--------|-------| +| 26 | | AIIMS Delhi — Junior Resident | [ ] | Reach via student groups | +| 27 | | AIIMS Delhi — MD Biochemistry | [ ] | Reach via PubMed → email | +| 28 | | Maulana Azad Medical College | [ ] | Reach via college groups | +| 29 | | JIPMER Pondicherry | [ ] | Reach via college groups | +| 30 | | CMC Vellore | [ ] | Reach via college groups | + +--- + +## Weekly Targets + +### Week 1: 10 calls +- [ ] 5 from JMI M.Sc. Bioinformatics (your own classmates/batchmates) +- [ ] 3 from other central university M.Sc. programs +- [ ] 2 PhD students via cold email + +### Week 2: 10 calls +- [ ] 5 from central universities (new batch) +- [ ] 3 PhD students +- [ ] 2 MBBS/MD students + +### Week 3: 10 calls +- [ ] Fill remaining slots from any category + +--- + +## Outreach Log + +### Week 1 +| Date | Contact | Institution | Method | Response | Follow-up | +|------|---------|-------------|--------|----------|-----------| +| | | | | | | + +--- + +## Feedback Summary + +| Theme | Count | Quotes / Notes | +|-------|-------|----------------| +| | | | + +--- + +## Beta Signups + +| Name | Institution | Program | Email | Date | +|------|-------------|---------|-------|------| +| | | | | | diff --git a/bioai-platform/backend/.env.example b/bioai-platform/backend/.env.example new file mode 100644 index 0000000000000000000000000000000000000000..d3fae8a81c1e8bc32a9a6e5b4c3980252e43b609 --- /dev/null +++ b/bioai-platform/backend/.env.example @@ -0,0 +1,4 @@ +GROQ_API_KEY= +REDIS_URL=redis://localhost:6379 +SUPABASE_URL= +SUPABASE_SERVICE_ROLE_KEY= diff --git a/bioai-platform/backend/__init__.py b/bioai-platform/backend/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/bioai-platform/backend/app/__init__.py b/bioai-platform/backend/app/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/bioai-platform/backend/app/ai/__init__.py b/bioai-platform/backend/app/ai/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/bioai-platform/backend/app/ai/interpreter.py b/bioai-platform/backend/app/ai/interpreter.py new file mode 100644 index 0000000000000000000000000000000000000000..2790cb68b9b49231368dc76e76770bf554a96f3b --- /dev/null +++ b/bioai-platform/backend/app/ai/interpreter.py @@ -0,0 +1,45 @@ +import json +import os +from typing import AsyncGenerator +from litellm import acompletion +from app.config import settings +from app.ai.llm_client import llm_client +from app.ai.prompts import get_prompt + + +async def interpret_stream(pipeline_type: str, context: dict) -> AsyncGenerator[str, None]: + if not llm_client.has_api_key(): + yield _error_event("GROQ_API_KEY is not configured. AI interpretation unavailable.") + return + + prompt = llm_client.build_prompt(pipeline_type, context) + model = llm_client.model + + try: + response = await acompletion( + model=model, + messages=[{"role": "user", "content": prompt}], + temperature=0.3, + max_tokens=2000, + stream=True, + api_key=llm_client.api_key, + ) + async for chunk in response: + if chunk.choices and chunk.choices[0].delta.content: + yield _chunk_event(chunk.choices[0].delta.content) + + yield _done_event({"model": model, "pipeline_type": pipeline_type}) + except Exception as e: + yield _error_event(str(e)) + + +def _chunk_event(text: str) -> str: + return f"data: {json.dumps({'chunk': text})}\n\n" + + +def _done_event(meta: dict) -> str: + return f"data: {json.dumps({'done': True, 'meta': meta})}\n\n" + + +def _error_event(msg: str) -> str: + return f"data: {json.dumps({'error': msg})}\n\n" diff --git a/bioai-platform/backend/app/ai/llm_client.py b/bioai-platform/backend/app/ai/llm_client.py new file mode 100644 index 0000000000000000000000000000000000000000..2bd7759b650d92537819a6dc7aeefe332ba26941 --- /dev/null +++ b/bioai-platform/backend/app/ai/llm_client.py @@ -0,0 +1,44 @@ +import os +from app.config import settings +from app.ai.prompts import get_prompt + + +class LLMClient: + def __init__(self): + self.api_key = settings.GROQ_API_KEY + self.model = settings.DEFAULT_MODEL + self.pro_model = settings.PRO_MODEL + + def has_api_key(self) -> bool: + return bool(self.api_key) + + def build_prompt(self, pipeline_type: str, context: dict) -> str: + template = get_prompt(pipeline_type) + blast = context.get("blast", {}) + top = blast.get("top_hit", {}) + uniprot = context.get("uniprot", {}) or {} + af = context.get("alphafold", {}) or {} + + return template.format( + blast_count=blast.get("count", 0), + top_hit_accession=top.get("accession", "N/A"), + top_hit_description=top.get("description", "N/A"), + top_hit_evalue=top.get("evalue", "N/A"), + top_hit_identity_pct=top.get("identity_pct", "N/A"), + top_hit_bit_score=top.get("bit_score", "N/A"), + uniprot_name=uniprot.get("full_name", "N/A"), + uniprot_organism=uniprot.get("organism", "N/A"), + uniprot_genes=", ".join(uniprot.get("gene_names", []) or []) or "N/A", + uniprot_functions="; ".join(uniprot.get("functions", []) or []) or "N/A", + uniprot_locations="; ".join(uniprot.get("subcellular_locations", []) or []) or "N/A", + uniprot_keywords=", ".join(uniprot.get("keywords", []) or []) or "N/A", + uniprot_go_terms=", ".join(uniprot.get("go_terms", []) or []) or "N/A", + uniprot_features="; ".join( + f"{f.get('type', '')}: {f.get('description', '')}" for f in (uniprot.get("features", []) or []) + ) or "N/A", + alphafold_available="Yes" if af.get("structure_available") else "No", + alphafold_confidence=af.get("confidence", "N/A"), + ) + + +llm_client = LLMClient() diff --git a/bioai-platform/backend/app/ai/prompts.py b/bioai-platform/backend/app/ai/prompts.py new file mode 100644 index 0000000000000000000000000000000000000000..6319ea9a70296ddf82edc1d8a55be2d9e0437085 --- /dev/null +++ b/bioai-platform/backend/app/ai/prompts.py @@ -0,0 +1,46 @@ +PROTEIN_ANALYSIS_PROMPT = """You are a computational biology assistant at Bio Nexus. A researcher submitted a protein sequence, and the system ran BLAST, UniProt lookup, and AlphaFold structure retrieval. Here is the complete assembled context. + +## BLAST Results +- Total hits found: {blast_count} +- Top hit: {top_hit_description} (accession {top_hit_accession}) +- E-value: {top_hit_evalue} +- Sequence identity: {top_hit_identity_pct}% +- Bit score: {top_hit_bit_score} + +## UniProt Annotations (Top Hit) +- Protein name: {uniprot_name} +- Organism: {uniprot_organism} +- Gene: {uniprot_genes} +- Function: {uniprot_functions} +- Subcellular location: {uniprot_locations} +- Keywords: {uniprot_keywords} +- GO terms: {uniprot_go_terms} +- Active sites / binding regions: {uniprot_features} + +## AlphaFold Structure +- Structure available: {alphafold_available} +- Confidence score (pLDDT): {alphafold_confidence} + +## Instructions for your response +1. Explain what the query protein likely is based on the BLAST hits and UniProt annotations. +2. Interpret the E-value and identity percentage — what they mean for confidence in the match. +3. Summarize the protein's function, cellular location, and any known domains or active sites. +4. If an AlphaFold structure is available, note its confidence and what that means. +5. Give a concise bottom-line assessment: what the researcher should conclude from this analysis. +6. Use plain language. Avoid unnecessary jargon. When you use technical terms, explain them briefly. + +Write in a helpful, instructive tone. If any data is missing, state that honestly.""" + + +FALLBACK_PROMPT = """You are a computational biology assistant. The following BLAST search results were returned, but detailed annotations are not available. Summarize the search results and help the user understand what the top hits mean. + +BLAST search found {blast_count} hits. +Top hit: {top_hit_description} (E-value: {top_hit_evalue}, Identity: {top_hit_identity_pct}%) +""" + + +def get_prompt(pipeline_type: str) -> str: + prompts = { + "protein_analysis": PROTEIN_ANALYSIS_PROMPT, + } + return prompts.get(pipeline_type, FALLBACK_PROMPT) diff --git a/bioai-platform/backend/app/config.py b/bioai-platform/backend/app/config.py new file mode 100644 index 0000000000000000000000000000000000000000..0c7ac4c2c02ddbe9c1e18f48b4bf13fc2fe5819c --- /dev/null +++ b/bioai-platform/backend/app/config.py @@ -0,0 +1,22 @@ +import os +from dotenv import load_dotenv + +load_dotenv() + + +class Settings: + GROQ_API_KEY: str = os.getenv("GROQ_API_KEY", "") + REDIS_URL: str = os.getenv("REDIS_URL", "redis://localhost:6379") + SUPABASE_URL: str = os.getenv("SUPABASE_URL", "") + SUPABASE_SERVICE_ROLE_KEY: str = os.getenv("SUPABASE_SERVICE_ROLE_KEY", "") + CELERY_BROKER_URL: str = os.getenv("CELERY_BROKER_URL", "redis://localhost:6379/1") + CELERY_RESULT_BACKEND: str = os.getenv("CELERY_RESULT_BACKEND", "redis://localhost:6379/2") + EBI_BASE_URL: str = "https://www.ebi.ac.uk/Tools/services/rest/ncbiblast" + UNIPROT_BASE_URL: str = "https://rest.uniprot.org/uniprotkb" + ALPHAFOLD_DB_URL: str = "https://alphafold.ebi.ac.uk/api/prediction" + DAILY_LIMIT: int = 10 + DEFAULT_MODEL: str = os.getenv("DEFAULT_MODEL", "groq/llama-3.3-70b-versatile") + PRO_MODEL: str = os.getenv("PRO_MODEL", "claude-sonnet-4-20250514") + + +settings = Settings() diff --git a/bioai-platform/backend/app/main.py b/bioai-platform/backend/app/main.py new file mode 100644 index 0000000000000000000000000000000000000000..d6a16fc3ac7bf16554232ce397af6a3defffc4f8 --- /dev/null +++ b/bioai-platform/backend/app/main.py @@ -0,0 +1,54 @@ +from dotenv import load_dotenv +load_dotenv() + +from fastapi import FastAPI, Request +from fastapi.middleware.cors import CORSMiddleware +from fastapi.responses import JSONResponse +from slowapi import Limiter, _rate_limit_exceeded_handler +from slowapi.util import get_remote_address +from slowapi.errors import RateLimitExceeded +from app.routers import pipelines, results, ai, jobs, export, share, waitlist, profile +from app.services.cache import init_redis +from app.tools.registration import register_all_tools + +limiter = Limiter(key_func=get_remote_address, default_limits=["30/minute"]) + +app = FastAPI(title="Bio Nexus API", version="0.1.0") +app.state.limiter = limiter +app.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler) + +app.add_middleware( + CORSMiddleware, + allow_origins=["http://localhost:3000", "http://localhost:3001"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + +app.include_router(pipelines.router, prefix="/api/pipelines", tags=["pipelines"]) +app.include_router(results.router, prefix="/api/results", tags=["results"]) +app.include_router(ai.router, prefix="/api/ai", tags=["ai"]) +app.include_router(jobs.router, prefix="/api/jobs", tags=["jobs"]) +app.include_router(export.router, prefix="/api/export", tags=["export"]) +app.include_router(share.router, prefix="/api/share", tags=["share"]) +app.include_router(waitlist.router, prefix="/api/waitlist", tags=["waitlist"]) +app.include_router(profile.router, prefix="/api/profile", tags=["profile"]) + + +@app.on_event("startup") +async def startup(): + init_redis() + register_all_tools() + + +@app.get("/health") +async def health(): + return {"status": "ok"} + + +@app.exception_handler(Exception) +async def global_exception_handler(request: Request, exc: Exception): + return JSONResponse( + status_code=500, + content={"detail": "Internal server error"}, + ) diff --git a/bioai-platform/backend/app/pipeline/__init__.py b/bioai-platform/backend/app/pipeline/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/bioai-platform/backend/app/pipeline/assembler.py b/bioai-platform/backend/app/pipeline/assembler.py new file mode 100644 index 0000000000000000000000000000000000000000..ab45393585eba1ecbec946d04ed1c1a3e3fe8b5d --- /dev/null +++ b/bioai-platform/backend/app/pipeline/assembler.py @@ -0,0 +1,68 @@ +from typing import Any + + +class ContextAssembler: + def assemble( + self, + sequence: str, + blast_result: dict, + uniprot_result: dict | None, + alphafold_result: dict | None, + ) -> dict: + context = { + "query": { + "sequence": sequence, + "length": len([c for c in sequence if c.isalpha()]), + }, + "blast": self._summarize_blast(blast_result), + "uniprot": self._summarize_uniprot(uniprot_result) if uniprot_result else None, + "alphafold": alphafold_result, + } + return context + + def _summarize_blast(self, blast_result: dict) -> dict: + hits = blast_result.get("hits", []) + summary = { + "count": len(hits), + "source": blast_result.get("source", "EBI BLAST"), + "database": blast_result.get("database", "swissprot"), + } + if hits: + best = hits[0] + summary["top_hit"] = { + "accession": best.get("accession", ""), + "description": best.get("description", ""), + "evalue": best.get("evalue", 0), + "identity_pct": best.get("identity_pct", 0), + "bit_score": best.get("bit_score", 0), + "alignment_length": best.get("alignment_length", 0), + } + summary["hits"] = [ + { + "accession": h.get("accession", ""), + "description": h.get("description", ""), + "evalue": h.get("evalue", 0), + "identity_pct": h.get("identity_pct", 0), + "bit_score": h.get("bit_score", 0), + } + for h in hits[:10] + ] + return summary + + def _summarize_uniprot(self, uniprot_result: dict) -> dict: + return { + "accession": uniprot_result.get("accession", ""), + "full_name": uniprot_result.get("full_name", ""), + "organism": uniprot_result.get("organism", ""), + "gene_names": uniprot_result.get("gene_names", []), + "functions": uniprot_result.get("functions", []), + "keywords": uniprot_result.get("keywords", []), + "subcellular_locations": uniprot_result.get("subcellular_locations", []), + "pdb_ids": uniprot_result.get("pdb_ids", []), + "features": [ + f for f in (uniprot_result.get("features", []) or []) + if f.get("type") in ("ACTIVE_SITE", "BINDING", "MUTAGENESIS") + ], + "go_terms": uniprot_result.get("go_terms", []), + "sequence_length": uniprot_result.get("sequence_length", 0), + } diff --git a/bioai-platform/backend/app/pipeline/definitions/__init__.py b/bioai-platform/backend/app/pipeline/definitions/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/bioai-platform/backend/app/pipeline/definitions/protein_analysis.py b/bioai-platform/backend/app/pipeline/definitions/protein_analysis.py new file mode 100644 index 0000000000000000000000000000000000000000..a77602bd4f164f59204d17fa514dee7141b2e33a --- /dev/null +++ b/bioai-platform/backend/app/pipeline/definitions/protein_analysis.py @@ -0,0 +1,16 @@ +from typing import Any + +PIPELINE_DEFINITION = { + "id": "protein_analysis", + "name": "Protein Sequence Analysis", + "description": "Analyze a protein sequence: BLAST against Swiss-Prot, fetch UniProt annotations, retrieve AlphaFold structure", + "input_type": "sequence", + "input_label": "Protein sequence (FASTA or plain)", + "steps": ["blast", "uniprot", "alphafold"], + "default_database": "uniprotkb_swissprot", + "default_max_hits": 10, +} + + +def get_pipeline_definition() -> dict: + return PIPELINE_DEFINITION diff --git a/bioai-platform/backend/app/pipeline/engine.py b/bioai-platform/backend/app/pipeline/engine.py new file mode 100644 index 0000000000000000000000000000000000000000..b736f917019788cf07b5747c7db1a61c6ea12263 --- /dev/null +++ b/bioai-platform/backend/app/pipeline/engine.py @@ -0,0 +1,46 @@ +from typing import Any +from app.pipeline.registry import registry +from app.pipeline.assembler import ContextAssembler +from app.tools.blast import BlastTool +from app.tools.uniprot import UniprotTool +from app.tools.alphafold import AlphaFoldTool + + +class PipelineEngine: + def __init__(self): + self.assembler = ContextAssembler() + self.blast_tool = BlastTool() + self.uniprot_tool = UniprotTool() + self.alphafold_tool = AlphaFoldTool() + + async def execute(self, sequence: str, database: str = "uniprotkb_swissprot", max_hits: int = 10) -> dict: + blast_result = await self.blast_tool.run({ + "sequence": sequence, + "database": database, + "max_hits": max_hits, + }) + + if "error" in blast_result: + return {"error": blast_result["error"], "steps_completed": []} + + top_accession = "" + if blast_result.get("hits"): + top_accession = blast_result["hits"][0].get("accession", "") + + uniprot_result = None + if top_accession: + uniprot_result = await self.uniprot_tool.run({"accession": top_accession}) + + alphafold_result = None + if top_accession and uniprot_result and "error" not in uniprot_result: + alphafold_result = await self.alphafold_tool.run({"uniprot_accession": top_accession}) + + context = self.assembler.assemble(sequence, blast_result, uniprot_result, alphafold_result) + + return { + "context": context, + "steps_completed": ["blast", "uniprot", "alphafold"], + "blast_raw": blast_result, + "uniprot_raw": uniprot_result, + "alphafold_raw": alphafold_result, + } diff --git a/bioai-platform/backend/app/pipeline/registry.py b/bioai-platform/backend/app/pipeline/registry.py new file mode 100644 index 0000000000000000000000000000000000000000..953468c5c0c39c7694ca84861eceada7d29b1caa --- /dev/null +++ b/bioai-platform/backend/app/pipeline/registry.py @@ -0,0 +1,19 @@ +from typing import Any +from app.tools.base import BaseTool + + +class ToolRegistry: + def __init__(self): + self._tools: dict[str, BaseTool] = {} + + def register(self, tool: BaseTool): + self._tools[tool.name] = tool + + def get(self, name: str) -> BaseTool | None: + return self._tools.get(name) + + def list(self) -> list[str]: + return list(self._tools.keys()) + + +registry = ToolRegistry() diff --git a/bioai-platform/backend/app/routers/__init__.py b/bioai-platform/backend/app/routers/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/bioai-platform/backend/app/routers/ai.py b/bioai-platform/backend/app/routers/ai.py new file mode 100644 index 0000000000000000000000000000000000000000..b9315e33f0ecd9fae177471e93c60a467562d086 --- /dev/null +++ b/bioai-platform/backend/app/routers/ai.py @@ -0,0 +1,32 @@ +import json +import os +from fastapi import APIRouter, HTTPException, Depends +from fastapi.responses import StreamingResponse +from pydantic import BaseModel +from app.ai.interpreter import interpret_stream +from app.ai.llm_client import llm_client +from app.services.rate_limit import check_daily_limit + +router = APIRouter() + + +class InterpretRequest(BaseModel): + pipeline_type: str = "protein_analysis" + context: dict = {} + + +@router.post("/interpret", dependencies=[Depends(check_daily_limit)]) +async def interpret_full_context(req: InterpretRequest): + if not llm_client.has_api_key(): + raise HTTPException(status_code=502, detail="GROQ_API_KEY is not configured") + + prompt = llm_client.build_prompt(req.pipeline_type, req.context) + return {"prompt": prompt, "context_size": len(json.dumps(req.context))} + + +@router.post("/interpret/stream", dependencies=[Depends(check_daily_limit)]) +async def interpret_stream_endpoint(req: InterpretRequest): + return StreamingResponse( + interpret_stream(req.pipeline_type, req.context), + media_type="text/event-stream", + ) diff --git a/bioai-platform/backend/app/routers/export.py b/bioai-platform/backend/app/routers/export.py new file mode 100644 index 0000000000000000000000000000000000000000..ee6cf3a01a3b57e25338f62de8dd32be13654f67 --- /dev/null +++ b/bioai-platform/backend/app/routers/export.py @@ -0,0 +1,42 @@ +from fastapi import APIRouter, HTTPException +from fastapi.responses import Response +from pydantic import BaseModel +from app.services.export import export_blast_pdf, export_uniprot_pdf + +router = APIRouter() + + +class BlastExportRequest(BaseModel): + result: dict + sequence: str = "" + + +class UniprotExportRequest(BaseModel): + data: dict + + +@router.post("/blast") +async def export_blast(req: BlastExportRequest): + try: + pdf = export_blast_pdf(req.result, req.sequence) + return Response(content=pdf, media_type="application/pdf", headers={ + "Content-Disposition": "attachment; filename=blast_results.pdf" + }) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +@router.post("/uniprot") +async def export_uniprot(req: UniprotExportRequest): + try: + pdf = export_uniprot_pdf(req.data) + return Response(content=pdf, media_type="application/pdf", headers={ + "Content-Disposition": f"attachment; filename=uniprot_{req.data.get('accession', 'protein')}.pdf" + }) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +@router.post("/pipeline/{job_id}") +async def export_pipeline(job_id: str): + raise HTTPException(status_code=501, detail="Pipeline PDF export coming in Phase 1.5") diff --git a/bioai-platform/backend/app/routers/jobs.py b/bioai-platform/backend/app/routers/jobs.py new file mode 100644 index 0000000000000000000000000000000000000000..003d2d52ace647c04845ddc02c657d5307f41226 --- /dev/null +++ b/bioai-platform/backend/app/routers/jobs.py @@ -0,0 +1,38 @@ +from fastapi import APIRouter, HTTPException, Depends +from pydantic import BaseModel +from datetime import datetime, timezone +from app.services.supabase import get_supabase + +router = APIRouter() + + +@router.get("/count") +async def job_count(user_id: str = ""): + supabase = get_supabase() + today = datetime.now(timezone.utc).date().isoformat() + result = supabase.table("jobs").select("id", count="exact").gte("created_at", today).execute() + count = result.count or 0 + return {"count": count, "limit": 10, "remaining": max(0, 10 - count)} + + +@router.get("") +async def list_jobs(user_id: str = ""): + supabase = get_supabase() + result = supabase.table("jobs").select("*").order("created_at", desc=True).limit(50).execute() + return {"jobs": result.data or []} + + +@router.get("/{job_id}") +async def get_job(job_id: str): + supabase = get_supabase() + result = supabase.table("jobs").select("*").eq("id", job_id).execute() + if not result.data: + raise HTTPException(status_code=404, detail="Job not found") + return result.data[0] + + +@router.delete("/{job_id}") +async def delete_job(job_id: str): + supabase = get_supabase() + supabase.table("jobs").delete().eq("id", job_id).execute() + return {"status": "deleted"} diff --git a/bioai-platform/backend/app/routers/pipelines.py b/bioai-platform/backend/app/routers/pipelines.py new file mode 100644 index 0000000000000000000000000000000000000000..6668d217cd4a7f24faac17bb68318d7de1d98d3e --- /dev/null +++ b/bioai-platform/backend/app/routers/pipelines.py @@ -0,0 +1,65 @@ +from fastapi import APIRouter, HTTPException, Depends +from pydantic import BaseModel +from app.services.validators import validate_fasta, ValidationResult +from app.pipeline.engine import PipelineEngine +from app.pipeline.definitions.protein_analysis import get_pipeline_definition +from app.services.supabase import get_supabase +from app.services.rate_limit import check_daily_limit +from app.workers.celery_app import celery_app +from app.workers.pipeline_worker import run_pipeline_sync +from datetime import datetime, timezone +import uuid + +router = APIRouter() + + +class PipelineRunRequest(BaseModel): + sequence: str + pipeline_type: str = "protein_analysis" + database: str = "uniprotkb_swissprot" + max_hits: int = 10 + + +@router.post("/run", dependencies=[Depends(check_daily_limit)]) +async def run_pipeline(req: PipelineRunRequest): + validation = validate_fasta(req.sequence, "blast") + if not validation.valid: + raise HTTPException(status_code=400, detail=validation.error) + + seq = str(validation.sequences[0].seq).upper().replace(" ", "") + + job_id = str(uuid.uuid4()) + supabase = get_supabase() + + supabase.table("jobs").insert({ + "id": job_id, + "tool": "pipeline", + "query_preview": seq[:100], + "status": "pending", + "pipeline_type": req.pipeline_type, + "steps_completed": [], + "context_json": None, + "created_at": datetime.now(timezone.utc).isoformat(), + }).execute() + + if celery_app is not None: + from app.workers.pipeline_worker import run_pipeline_job + run_pipeline_job.delay(job_id, seq, req.database, req.max_hits) + else: + import threading + t = threading.Thread(target=run_pipeline_sync, args=(job_id, seq, req.database, req.max_hits), daemon=True) + t.start() + + return {"job_id": job_id, "status": "pending"} + + +@router.get("/definitions") +async def list_pipeline_definitions(): + return {"pipelines": [get_pipeline_definition()]} + + +@router.get("/{pipeline_type}/definition") +async def get_pipeline_definition_endpoint(pipeline_type: str): + if pipeline_type == "protein_analysis": + return get_pipeline_definition() + raise HTTPException(status_code=404, detail=f"Unknown pipeline: {pipeline_type}") diff --git a/bioai-platform/backend/app/routers/profile.py b/bioai-platform/backend/app/routers/profile.py new file mode 100644 index 0000000000000000000000000000000000000000..d4462f8741cc127ccd30de7ce638fa593a6b62f7 --- /dev/null +++ b/bioai-platform/backend/app/routers/profile.py @@ -0,0 +1,28 @@ +from fastapi import APIRouter, HTTPException, Depends +from pydantic import BaseModel +from app.services.supabase import get_supabase + +router = APIRouter() + +class ProfileUpdate(BaseModel): + full_name: str = "" + institution: str = "" + +@router.get("") +async def get_profile(user_id: str = ""): + supabase = get_supabase() + result = supabase.table("profiles").select("*").limit(1).execute() + if result.data: + return result.data[0] + return {"error": "Profile not found"} + +@router.put("") +async def update_profile(profile: ProfileUpdate, user_id: str = ""): + supabase = get_supabase() + data = {} + if profile.full_name: data["full_name"] = profile.full_name + if profile.institution: data["institution"] = profile.institution + if data: + result = supabase.table("profiles").update(data).eq("id", user_id).execute() + return {"status": "updated", "data": result.data[0] if result.data else data} + return {"status": "no changes"} diff --git a/bioai-platform/backend/app/routers/results.py b/bioai-platform/backend/app/routers/results.py new file mode 100644 index 0000000000000000000000000000000000000000..156e01839a6379fcdf3888a9ffb0128ea519e8b0 --- /dev/null +++ b/bioai-platform/backend/app/routers/results.py @@ -0,0 +1,35 @@ +from fastapi import APIRouter, HTTPException, Depends +from app.services.supabase import get_supabase +from app.ai.interpreter import interpret_stream +from fastapi.responses import StreamingResponse + +router = APIRouter() + + +@router.get("/{job_id}") +async def get_result(job_id: str): + supabase = get_supabase() + result = supabase.table("jobs").select("*").eq("id", job_id).execute() + if not result.data: + raise HTTPException(status_code=404, detail="Job not found") + return result.data[0] + + +@router.get("/{job_id}/stream") +async def stream_result(job_id: str): + supabase = get_supabase() + job = supabase.table("jobs").select("*").eq("id", job_id).execute() + if not job.data: + raise HTTPException(status_code=404, detail="Job not found") + + job_data = job.data[0] + context = job_data.get("context_json") + pipeline_type = job_data.get("pipeline_type", "protein_analysis") + + if not context: + raise HTTPException(status_code=400, detail="Job has not completed yet") + + return StreamingResponse( + interpret_stream(pipeline_type, context), + media_type="text/event-stream", + ) diff --git a/bioai-platform/backend/app/routers/share.py b/bioai-platform/backend/app/routers/share.py new file mode 100644 index 0000000000000000000000000000000000000000..76faff84a7974c0a3184e6623be53748b12454c0 --- /dev/null +++ b/bioai-platform/backend/app/routers/share.py @@ -0,0 +1,13 @@ +from fastapi import APIRouter, HTTPException +from app.services.supabase import get_supabase + +router = APIRouter() + + +@router.get("/{token}") +async def get_shared_result(token: str): + supabase = get_supabase() + result = supabase.table("jobs").select("*").eq("share_token", token).execute() + if not result.data: + raise HTTPException(status_code=404, detail="Shared result not found") + return result.data[0] diff --git a/bioai-platform/backend/app/routers/waitlist.py b/bioai-platform/backend/app/routers/waitlist.py new file mode 100644 index 0000000000000000000000000000000000000000..115c4ec562e8d7fa18c8052833b10ec4c3a66659 --- /dev/null +++ b/bioai-platform/backend/app/routers/waitlist.py @@ -0,0 +1,28 @@ +from fastapi import APIRouter, HTTPException +from pydantic import BaseModel +import httpx +from app.config import settings + +router = APIRouter() + + +class WaitlistEntry(BaseModel): + email: str + + +@router.post("") +async def join_waitlist(entry: WaitlistEntry): + url = f"{settings.SUPABASE_URL}/rest/v1/waitlist" + headers = { + "apikey": settings.SUPABASE_SERVICE_ROLE_KEY, + "Authorization": f"Bearer {settings.SUPABASE_SERVICE_ROLE_KEY}", + "Content-Type": "application/json", + "Prefer": "return=minimal", + } + async with httpx.AsyncClient() as client: + resp = await client.post(url, headers=headers, json={"email": entry.email}) + if resp.status_code == 409: + raise HTTPException(status_code=409, detail="Already on waitlist") + if resp.status_code >= 400: + raise HTTPException(status_code=500, detail=resp.text) + return {"status": "added", "email": entry.email} diff --git a/bioai-platform/backend/app/services/__init__.py b/bioai-platform/backend/app/services/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/bioai-platform/backend/app/services/cache.py b/bioai-platform/backend/app/services/cache.py new file mode 100644 index 0000000000000000000000000000000000000000..6615ad48703f01834478abd33076493778bcb9b1 --- /dev/null +++ b/bioai-platform/backend/app/services/cache.py @@ -0,0 +1,61 @@ +import redis +import hashlib +import json +import functools +from typing import Callable, Any +from app.config import settings + +_redis = None + + +def init_redis(): + global _redis + try: + _redis = redis.from_url(settings.REDIS_URL, decode_responses=True) + _redis.ping() + except Exception: + _redis = None + + +def get_redis(): + return _redis + + +def cache_get(key: str) -> str | None: + r = get_redis() + if r: + return r.get(key) + return None + + +def cache_set(key: str, value: str, ttl: int = 86400): + r = get_redis() + if r: + r.setex(key, ttl, value) + + +def ttl_cache(ttl: int = 86400, prefix: str = "cache"): + def decorator(func: Callable) -> Callable: + @functools.wraps(func) + async def wrapper(self, input: dict, *args, **kwargs): + raw = json.dumps(input, sort_keys=True) + key_hash = hashlib.sha256(raw.encode()).hexdigest()[:16] + cache_key = f"{prefix}:{key_hash}" + + cached = cache_get(cache_key) + if cached is not None: + try: + return json.loads(cached) + except (json.JSONDecodeError, TypeError): + pass + + result = await func(self, input, *args, **kwargs) + try: + cache_set(cache_key, json.dumps(result), ttl=ttl) + except (TypeError, ValueError): + pass + return result + + return wrapper + + return decorator diff --git a/bioai-platform/backend/app/services/export.py b/bioai-platform/backend/app/services/export.py new file mode 100644 index 0000000000000000000000000000000000000000..3b7a214cfd2522cb9fb8608f5d9b75542914d771 --- /dev/null +++ b/bioai-platform/backend/app/services/export.py @@ -0,0 +1,130 @@ +from io import BytesIO +from reportlab.lib.pagesizes import A4 +from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle +from reportlab.lib.units import inch +from reportlab.lib import colors +from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle + +def export_blast_pdf(result: dict, sequence: str = "") -> bytes: + buffer = BytesIO() + doc = SimpleDocTemplate(buffer, pagesize=A4, topMargin=0.75 * inch, bottomMargin=0.75 * inch) + styles = getSampleStyleSheet() + elements = [] + + title_style = ParagraphStyle("Title2", parent=styles["Title"], fontSize=16, spaceAfter=12) + heading_style = ParagraphStyle("Heading", parent=styles["Heading2"], fontSize=12, spaceAfter=6, textColor=colors.HexColor("#16a34a")) + body_style = ParagraphStyle("Body", parent=styles["BodyText"], fontSize=10, spaceAfter=6) + + elements.append(Paragraph("Bio Nexus \u2014 BLAST Results", title_style)) + elements.append(Spacer(1, 12)) + + if sequence: + preview = sequence[:100] + ("..." if len(sequence) > 100 else "") + elements.append(Paragraph(f"Query: {preview}", body_style)) + + elements.append(Paragraph(f"Hits found: {result.get('count', 0)}", body_style)) + elements.append(Spacer(1, 12)) + + hits = result.get("hits", []) + if not hits: + elements.append(Paragraph("No hits found.", body_style)) + doc.build(elements) + return buffer.getvalue() + + table_data = [["#", "Accession", "Description", "E-value", "Identity", "Coverage"]] + for i, hit in enumerate(hits[:20], 1): + desc = (hit.get("description", "")[:60] + "...") if len(hit.get("description", "")) > 60 else hit.get("description", "") + table_data.append([ + str(i), + hit.get("accession", ""), + desc, + f"{hit.get('evalue', 0):.1e}", + f"{hit.get('identity_pct', 0)}%", + f"{hit.get('coverage_pct', 0)}%", + ]) + + col_widths = [0.4 * inch, 1.0 * inch, 2.5 * inch, 1.0 * inch, 0.8 * inch, 0.8 * inch] + t = Table(table_data, colWidths=col_widths, repeatRows=1) + t.setStyle(TableStyle([ + ("BACKGROUND", (0, 0), (-1, 0), colors.HexColor("#16a34a")), + ("TEXTCOLOR", (0, 0), (-1, 0), colors.white), + ("FONTSIZE", (0, 0), (-1, 0), 9), + ("FONTSIZE", (0, 1), (-1, -1), 8), + ("FONTNAME", (0, 0), (-1, 0), "Helvetica-Bold"), + ("ALIGN", (0, 0), (-1, -1), "LEFT"), + ("VALIGN", (0, 0), (-1, -1), "TOP"), + ("GRID", (0, 0), (-1, -1), 0.5, colors.HexColor("#e5e7eb")), + ("ROWBACKGROUNDS", (0, 1), (-1, -1), [colors.white, colors.HexColor("#f9fafb")]), + ("TOPPADDING", (0, 0), (-1, -1), 4), + ("BOTTOMPADDING", (0, 0), (-1, -1), 4), + ("LEFTPADDING", (0, 0), (-1, -1), 4), + ("RIGHTPADDING", (0, 0), (-1, -1), 4), + ])) + elements.append(t) + elements.append(Spacer(1, 16)) + + elements.append(Paragraph("Significance Guide", heading_style)) + elements.append(Paragraph("\u2022 E-value < 1e-50: Highly significant match", body_style)) + elements.append(Paragraph("\u2022 E-value 1e-5 to 1e-50: Significant match", body_style)) + elements.append(Paragraph("\u2022 E-value > 1e-5: Weak or non-significant", body_style)) + elements.append(Spacer(1, 8)) + elements.append(Paragraph(f"Generated by Bio Nexus Platform \u2014 {result.get('count', 0)} hits", body_style)) + + doc.build(elements) + return buffer.getvalue() + + +def export_uniprot_pdf(data: dict) -> bytes: + buffer = BytesIO() + doc = SimpleDocTemplate(buffer, pagesize=A4, topMargin=0.75 * inch, bottomMargin=0.75 * inch) + styles = getSampleStyleSheet() + elements = [] + + title_style = ParagraphStyle("Title2", parent=styles["Title"], fontSize=16, spaceAfter=12) + heading_style = ParagraphStyle("Heading", parent=styles["Heading2"], fontSize=12, spaceAfter=6, textColor=colors.HexColor("#16a34a")) + body_style = ParagraphStyle("Body", parent=styles["BodyText"], fontSize=10, spaceAfter=6) + + elements.append(Paragraph("Bio Nexus \u2014 UniProt Annotation", title_style)) + elements.append(Spacer(1, 12)) + + elements.append(Paragraph(f"Protein: {data.get('full_name', 'Unknown')}", body_style)) + elements.append(Paragraph(f"Accession: {data.get('accession', '')}", body_style)) + elements.append(Paragraph(f"Organism: {data.get('organism', 'Unknown')}", body_style)) + + genes = data.get("gene_names", []) + if genes: + elements.append(Paragraph(f"Gene: {', '.join(genes)}", body_style)) + + ec = data.get("ec_number", "") + if ec: + elements.append(Paragraph(f"EC Number: {ec}", body_style)) + + elements.append(Paragraph(f"Sequence Length: {data.get('sequence_length', 0)} amino acids", body_style)) + elements.append(Spacer(1, 12)) + + functions = data.get("functions", []) + if functions: + elements.append(Paragraph("Function", heading_style)) + for f in functions: + elements.append(Paragraph(f, body_style)) + + locations = data.get("subcellular_locations", []) + if locations: + elements.append(Paragraph("Subcellular Location", heading_style)) + elements.append(Paragraph(", ".join(locations), body_style)) + + pdb_ids = data.get("pdb_ids", []) + if pdb_ids: + elements.append(Paragraph("PDB Structures", heading_style)) + elements.append(Paragraph(", ".join(pdb_ids), body_style)) + + keywords = data.get("keywords", []) + if keywords: + elements.append(Paragraph("Keywords", heading_style)) + elements.append(Paragraph(", ".join(keywords[:10]), body_style)) + + elements.append(Spacer(1, 12)) + elements.append(Paragraph("Generated by Bio Nexus Platform", body_style)) + + doc.build(elements) + return buffer.getvalue() diff --git a/bioai-platform/backend/app/services/rate_limit.py b/bioai-platform/backend/app/services/rate_limit.py new file mode 100644 index 0000000000000000000000000000000000000000..0a2b259449f6f8de214ddcaf2c0df7c2753562aa --- /dev/null +++ b/bioai-platform/backend/app/services/rate_limit.py @@ -0,0 +1,27 @@ +from datetime import date +from app.services.redis import get_redis +from app.config import settings + + +async def check_daily_limit(user_id: str = "anonymous") -> bool: + r = get_redis() + if not r: + return True + + today = date.today().isoformat() + key = f"rate_limit:daily:{user_id}:{today}" + count = r.get(key) + + if count is None: + r.setex(key, 86400, 1) + return True + + if int(count) >= settings.DAILY_LIMIT: + return False + + r.incr(key) + return True + + +class RateLimitExceededError(Exception): + pass diff --git a/bioai-platform/backend/app/services/redis.py b/bioai-platform/backend/app/services/redis.py new file mode 100644 index 0000000000000000000000000000000000000000..a2f25490e699ecdb7547ef2a2651a1e414fd8ae4 --- /dev/null +++ b/bioai-platform/backend/app/services/redis.py @@ -0,0 +1,15 @@ +import redis +from app.config import settings + +_r = None + + +def get_redis(): + global _r + if _r is None: + try: + _r = redis.from_url(settings.REDIS_URL, decode_responses=True) + _r.ping() + except Exception: + _r = None + return _r diff --git a/bioai-platform/backend/app/services/supabase.py b/bioai-platform/backend/app/services/supabase.py new file mode 100644 index 0000000000000000000000000000000000000000..358ec44685a5f3af6bc68180a63ec133a93d60b6 --- /dev/null +++ b/bioai-platform/backend/app/services/supabase.py @@ -0,0 +1,11 @@ +from supabase import create_client, Client +from app.config import settings + +_supabase: Client | None = None + + +def get_supabase() -> Client: + global _supabase + if _supabase is None: + _supabase = create_client(settings.SUPABASE_URL, settings.SUPABASE_SERVICE_ROLE_KEY) + return _supabase diff --git a/bioai-platform/backend/app/services/validators.py b/bioai-platform/backend/app/services/validators.py new file mode 100644 index 0000000000000000000000000000000000000000..6be8460ff2b514973cfd75c2e90e22e18946ee86 --- /dev/null +++ b/bioai-platform/backend/app/services/validators.py @@ -0,0 +1,43 @@ +from Bio import SeqIO +from io import StringIO +from dataclasses import dataclass, field +from typing import List + + +@dataclass +class ValidationResult: + valid: bool = True + error: str = "" + sequences: List = field(default_factory=list) + + +def validate_fasta(text: str, tool: str = "blast") -> ValidationResult: + if not text or not text.strip(): + return ValidationResult(valid=False, error="Empty sequence") + + # Try parsing as FASTA + try: + records = list(SeqIO.parse(StringIO(text), "fasta")) + except Exception: + records = [] + + if records: + for rec in records: + seq_str = str(rec.seq) + if len(seq_str) < 6: + return ValidationResult(valid=False, error=f"Sequence too short: {len(seq_str)} residues") + if not set(seq_str.upper()).issubset(set("ACDEFGHIKLMNPQRSTVWY")): + return ValidationResult(valid=False, error="Invalid amino acid characters found") + return ValidationResult(sequences=records) + + # Plain sequence (no FASTA header) + clean = "".join(c for c in text if c.isalpha()).upper() + if len(clean) < 6: + return ValidationResult(valid=False, error=f"Sequence too short: {len(clean)} residues") + if not set(clean).issubset(set("ACDEFGHIKLMNPQRSTVWY")): + return ValidationResult(valid=False, error="Invalid amino acid characters found") + + from Bio.Seq import Seq + from Bio.SeqRecord import SeqRecord + record = SeqRecord(Seq(clean), id="query", description="") + return ValidationResult(sequences=[record]) diff --git a/bioai-platform/backend/app/tools/__init__.py b/bioai-platform/backend/app/tools/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/bioai-platform/backend/app/tools/alphafold.py b/bioai-platform/backend/app/tools/alphafold.py new file mode 100644 index 0000000000000000000000000000000000000000..29004bf977871a394997670568b28e011d3e78fc --- /dev/null +++ b/bioai-platform/backend/app/tools/alphafold.py @@ -0,0 +1,44 @@ +import httpx +from typing import Any +from app.tools.base import BaseTool +from app.config import settings +from app.services.cache import ttl_cache + + +class AlphaFoldTool(BaseTool): + name = "alphafold" + + @ttl_cache(ttl=86400, prefix="alphafold") + async def run(self, input: dict) -> dict: + uniprot_accession = input.get("uniprot_accession", "").strip() + if not uniprot_accession: + return {"error": "No UniProt accession provided", "structure_available": False} + + result = await self._lookup(uniprot_accession) + return result + + async def _lookup(self, accession: str) -> dict: + url = f"{settings.ALPHAFOLD_DB_URL}/{accession}" + async with httpx.AsyncClient(timeout=15) as client: + resp = await client.get(url) + if resp.status_code == 404: + return { + "uniprot_accession": accession, + "structure_available": False, + "message": "No AlphaFold prediction available for this protein", + "pdb_url": None, + "cif_url": None, + "confidence": None, + } + resp.raise_for_status() + data = resp.json() + entry = data[0] if isinstance(data, list) else data + return { + "uniprot_accession": accession, + "structure_available": True, + "pdb_url": entry.get("pdbUrl", ""), + "cif_url": entry.get("cifUrl", ""), + "confidence": entry.get("confidenceScore", None), + "model_created_date": entry.get("modelCreatedDate", ""), + "latest_version": entry.get("latestVersion", 0), + } diff --git a/bioai-platform/backend/app/tools/base.py b/bioai-platform/backend/app/tools/base.py new file mode 100644 index 0000000000000000000000000000000000000000..4e6c0d2ee9208ad666890e5dfe50d0cc644bf9c7 --- /dev/null +++ b/bioai-platform/backend/app/tools/base.py @@ -0,0 +1,16 @@ +from abc import ABC, abstractmethod +from typing import Any + + +class BaseTool(ABC): + name: str = "" + + @abstractmethod + async def run(self, input: dict) -> dict: + ... + + def requires_input_from(self) -> list[str]: + return [] + + def provides_output_to(self) -> list[str]: + return [] diff --git a/bioai-platform/backend/app/tools/blast.py b/bioai-platform/backend/app/tools/blast.py new file mode 100644 index 0000000000000000000000000000000000000000..bbd7195dbd3c058b34e5c5920ad0b7a97504a194 --- /dev/null +++ b/bioai-platform/backend/app/tools/blast.py @@ -0,0 +1,80 @@ +import httpx +import asyncio +import hashlib +import json +from typing import Any +from app.tools.base import BaseTool +from app.config import settings +from app.services.cache import ttl_cache + + +class BlastTool(BaseTool): + name = "blast" + + POLL_INTERVAL = 2.0 + MAX_POLL_TIME = 120 + + @ttl_cache(ttl=86400, prefix="blast") + async def run(self, input: dict) -> dict: + sequence = input.get("sequence", "").strip() + database = input.get("database", "uniprotkb_swissprot") + program = input.get("program", "blastp") + max_hits = input.get("max_hits", 10) + + job_id = await self._submit(sequence, program, database) + status = await self._poll(job_id) + if status != "FINISHED": + return {"error": f"BLAST job {job_id} ended with status {status}", "hits": []} + + hits = await self._fetch_results(job_id) + parsed = self._parse_hits(hits, max_hits) + return {"hits": parsed, "count": len(parsed), "source": "EBI BLAST", "database": database} + + async def _submit(self, sequence: str, program: str, database: str) -> str: + async with httpx.AsyncClient(timeout=30) as client: + resp = await client.post( + f"{settings.EBI_BASE_URL}/run", + data={"email": "user@bio-nexus.app", "sequence": sequence, "program": program, "database": database}, + ) + resp.raise_for_status() + return resp.text.strip() + + async def _poll(self, job_id: str) -> str: + start = asyncio.get_event_loop().time() + async with httpx.AsyncClient(timeout=10) as client: + while True: + elapsed = asyncio.get_event_loop().time() - start + if elapsed > self.MAX_POLL_TIME: + return "TIMEOUT" + resp = await client.get(f"{settings.EBI_BASE_URL}/status/{job_id}") + resp.raise_for_status() + status = resp.text.strip() + if status in ("FINISHED", "ERROR", "FAILED"): + return status + await asyncio.sleep(self.POLL_INTERVAL) + + async def _fetch_results(self, job_id: str) -> list[dict]: + async with httpx.AsyncClient(timeout=30) as client: + resp = await client.get(f"{settings.EBI_BASE_URL}/result/{job_id}/json") + resp.raise_for_status() + data = resp.json() + return data.get("hits", []) + + def _parse_hits(self, raw_hits: list[dict], max_hits: int) -> list[dict]: + parsed = [] + for hit in raw_hits[:max_hits]: + hsps = hit.get("hsps", [{}])[0] if hit.get("hsps") else {} + parsed.append({ + "accession": hit.get("hit_acc", ""), + "id": hit.get("hit_id", ""), + "description": hit.get("hit_desc", ""), + "evalue": hsps.get("hsp_expect", 0), + "bit_score": hsps.get("hsp_bit_score", 0), + "identity_pct": hsps.get("hsp_identity", 0), + "alignment_length": hsps.get("hsp_align_len", 0), + "query_from": hsps.get("hsp_query_from", 0), + "query_to": hsps.get("hsp_query_to", 0), + "hit_from": hsps.get("hsp_hit_from", 0), + "hit_to": hsps.get("hsp_hit_to", 0), + }) + return parsed diff --git a/bioai-platform/backend/app/tools/registration.py b/bioai-platform/backend/app/tools/registration.py new file mode 100644 index 0000000000000000000000000000000000000000..63f27bbbd4bcd5ef11bf24b74a28bf4eee62b433 --- /dev/null +++ b/bioai-platform/backend/app/tools/registration.py @@ -0,0 +1,10 @@ +from app.tools.blast import BlastTool +from app.tools.uniprot import UniprotTool +from app.tools.alphafold import AlphaFoldTool +from app.pipeline.registry import registry + + +def register_all_tools(): + registry.register(BlastTool()) + registry.register(UniprotTool()) + registry.register(AlphaFoldTool()) diff --git a/bioai-platform/backend/app/tools/uniprot.py b/bioai-platform/backend/app/tools/uniprot.py new file mode 100644 index 0000000000000000000000000000000000000000..97118319804a565f727759619070aaa2e958f683 --- /dev/null +++ b/bioai-platform/backend/app/tools/uniprot.py @@ -0,0 +1,102 @@ +import httpx +from typing import Any +from app.tools.base import BaseTool +from app.config import settings +from app.services.cache import ttl_cache + + +class UniprotTool(BaseTool): + name = "uniprot" + + @ttl_cache(ttl=86400, prefix="uniprot") + async def run(self, input: dict) -> dict: + accession = input.get("accession", "").strip() + if not accession: + return {"error": "No accession provided"} + + data = await self._fetch(accession) + if "error" in data: + return data + + return { + "accession": data.get("primaryAccession", ""), + "full_name": self._extract_name(data), + "ec_number": (data.get("proteinDescription", {}) or {}).get("ecNumbers", [{}])[0].get("ecNumber", "") if data.get("proteinDescription") else "", + "gene_names": [g.get("geneName", {}).get("value", "") for g in (data.get("genes") or []) if g.get("geneName")], + "organism": ((data.get("organism", {}) or {}).get("scientificName", "")), + "functions": self._extract_functions(data), + "keywords": [kw.get("name", "") for kw in (data.get("keywords") or [])], + "sequence_length": ((data.get("sequence", {}) or {}).get("length", 0)), + "subcellular_locations": self._extract_locations(data), + "pdb_ids": self._extract_pdb(data), + "features": self._extract_features(data), + "go_terms": self._extract_go_terms(data), + } + + async def _fetch(self, accession: str) -> dict: + url = f"{settings.UNIPROT_BASE_URL}/{accession}" + async with httpx.AsyncClient(timeout=15) as client: + resp = await client.get(url, params={"format": "json"}) + if resp.status_code == 404: + return {"error": f"Accession {accession} not found"} + resp.raise_for_status() + return resp.json() + + def _extract_name(self, data: dict) -> str: + desc = data.get("proteinDescription", {}) or {} + rec_name = desc.get("recommendedName", {}) or {} + return (rec_name.get("fullName", {}) or {}).get("value", "") + + def _extract_functions(self, data: dict) -> list[str]: + comments = data.get("comments") or [] + funcs = [] + for c in comments: + if c.get("commentType") == "FUNCTION": + texts = c.get("texts") or [] + for t in texts: + val = (t.get("value") or "").strip() + if val: + funcs.append(val) + return funcs + + def _extract_locations(self, data: dict) -> list[str]: + comments = data.get("comments") or [] + locs = [] + for c in comments: + if c.get("commentType") == "SUBCELLULAR_LOCATION": + subcels = c.get("subcellularLocations") or [] + for s in subcels: + loc = (s.get("location", {}) or {}).get("value", "") + if loc: + locs.append(loc) + return locs + + def _extract_pdb(self, data: dict) -> list[str]: + refs = data.get("uniProtKBCrossReferences") or [] + pdbs = [] + for r in refs: + if r.get("database") == "PDB": + pdbs.append(r.get("id", "")) + return pdbs + + def _extract_features(self, data: dict) -> list[dict]: + features = data.get("features") or [] + result = [] + for f in features: + result.append({ + "type": f.get("type", ""), + "description": f.get("description", ""), + "begin": (f.get("location", {}) or {}).get("start", {}).get("value"), + "end": (f.get("location", {}) or {}).get("end", {}).get("value"), + }) + return result + + def _extract_go_terms(self, data: dict) -> list[str]: + refs = data.get("uniProtKBCrossReferences") or [] + go = [] + for r in refs: + if r.get("database") == "GO": + term = r.get("properties", [{}])[0].get("value", "") if r.get("properties") else "" + if term: + go.append(term) + return go diff --git a/bioai-platform/backend/app/workers/__init__.py b/bioai-platform/backend/app/workers/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/bioai-platform/backend/app/workers/celery_app.py b/bioai-platform/backend/app/workers/celery_app.py new file mode 100644 index 0000000000000000000000000000000000000000..af06154ad2379d75a670b6c0a2e49dbe62b28dce --- /dev/null +++ b/bioai-platform/backend/app/workers/celery_app.py @@ -0,0 +1,22 @@ +try: + from celery import Celery + from app.config import settings + + celery_app = Celery( + "bio_nexus", + broker=settings.CELERY_BROKER_URL, + backend=settings.CELERY_RESULT_BACKEND, + ) + + celery_app.conf.update( + task_serializer="json", + accept_content=["json"], + result_serializer="json", + timezone="UTC", + enable_utc=True, + task_track_started=True, + task_acks_late=True, + worker_prefetch_multiplier=1, + ) +except ImportError: + celery_app = None diff --git a/bioai-platform/backend/app/workers/pipeline_worker.py b/bioai-platform/backend/app/workers/pipeline_worker.py new file mode 100644 index 0000000000000000000000000000000000000000..5fb7205475665792f3c5473e3064d7c149ccd545 --- /dev/null +++ b/bioai-platform/backend/app/workers/pipeline_worker.py @@ -0,0 +1,57 @@ +import asyncio +from app.workers.celery_app import celery_app +from app.pipeline.engine import PipelineEngine +from app.services.supabase import get_supabase +from datetime import datetime, timezone + + +def run_pipeline_sync(job_id: str, sequence: str, database: str, max_hits: int) -> dict: + """Run pipeline synchronously (used when Celery is unavailable).""" + supabase = get_supabase() + try: + supabase.table("jobs").update({ + "status": "running", + "progress_pct": 10, + }).eq("id", job_id).execute() + + async def execute(): + engine = PipelineEngine() + return await engine.execute(sequence, database, max_hits) + + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + result = loop.run_until_complete(execute()) + loop.close() + + if "error" in result: + supabase.table("jobs").update({ + "status": "failed", + "error": result["error"], + "completed_at": datetime.now(timezone.utc).isoformat(), + }).eq("id", job_id).execute() + return {"status": "failed", "error": result["error"]} + + context = result.get("context", {}) + supabase.table("jobs").update({ + "status": "complete", + "progress_pct": 100, + "context_json": context, + "steps_completed": result.get("steps_completed", []), + "completed_at": datetime.now(timezone.utc).isoformat(), + }).eq("id", job_id).execute() + + return {"status": "complete", "job_id": job_id} + + except Exception as exc: + supabase.table("jobs").update({ + "status": "failed", + "error": str(exc)[:500], + "completed_at": datetime.now(timezone.utc).isoformat(), + }).eq("id", job_id).execute() + return {"status": "failed", "error": str(exc)} + + +if celery_app is not None: + @celery_app.task(bind=True, max_retries=2, default_retry_delay=30) + def run_pipeline_job(self, job_id: str, sequence: str, database: str, max_hits: int): + return run_pipeline_sync(job_id, sequence, database, max_hits) diff --git a/bioai-platform/backend/requirements.txt b/bioai-platform/backend/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..c4918b352a68bfdf4596de130613edcc8dd6137d --- /dev/null +++ b/bioai-platform/backend/requirements.txt @@ -0,0 +1,12 @@ +fastapi +uvicorn +slowapi +redis +httpx +biopython +litellm +python-dotenv +supabase +reportlab +celery +pydantic[email] diff --git a/bioai-platform/frontend/.env.local.example b/bioai-platform/frontend/.env.local.example new file mode 100644 index 0000000000000000000000000000000000000000..d76a04271faa4fcfebb23b87eecd99a84af57040 --- /dev/null +++ b/bioai-platform/frontend/.env.local.example @@ -0,0 +1,3 @@ +NEXT_PUBLIC_SUPABASE_URL= +NEXT_PUBLIC_SUPABASE_ANON_KEY= +SUPABASE_SERVICE_ROLE_KEY= diff --git a/bioai-platform/frontend/next-env.d.ts b/bioai-platform/frontend/next-env.d.ts new file mode 100644 index 0000000000000000000000000000000000000000..40c3d68096c270ef976f3db4e9eb42b05c7067bb --- /dev/null +++ b/bioai-platform/frontend/next-env.d.ts @@ -0,0 +1,5 @@ +/// +/// + +// NOTE: This file should not be edited +// see https://nextjs.org/docs/app/building-your-application/configuring/typescript for more information. diff --git a/bioai-platform/frontend/next.config.js b/bioai-platform/frontend/next.config.js new file mode 100644 index 0000000000000000000000000000000000000000..245777279d75fd02be3db870fb2a99a7db5c269d --- /dev/null +++ b/bioai-platform/frontend/next.config.js @@ -0,0 +1,13 @@ +/** @type {import('next').NextConfig} */ +const nextConfig = { + async rewrites() { + return [ + { + source: '/api/backend/:path*', + destination: 'http://localhost:8000/:path*', + }, + ]; + }, +}; + +module.exports = nextConfig; diff --git a/bioai-platform/frontend/package-lock.json b/bioai-platform/frontend/package-lock.json new file mode 100644 index 0000000000000000000000000000000000000000..376deed2464060956df8749372704116771ea53f --- /dev/null +++ b/bioai-platform/frontend/package-lock.json @@ -0,0 +1,6518 @@ +{ + "name": "bionexus-frontend", + "version": "0.1.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "bionexus-frontend", + "version": "0.1.0", + "dependencies": { + "@supabase/ssr": "^0.12.0", + "@supabase/supabase-js": "^2.49.4", + "axios": "^1.7.9", + "lucide-react": "^0.474.0", + "next": "^14.2.23", + "react": "^18.3.1", + "react-dom": "^18.3.1", + "react-hot-toast": "^2.5.2" + }, + "devDependencies": { + "@types/node": "^22.13.4", + "@types/react": 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@@ +{ + "name": "bionexus-frontend", + "version": "0.1.0", + "private": true, + "scripts": { + "dev": "next dev", + "build": "next build", + "start": "next start", + "lint": "next lint" + }, + "dependencies": { + "@supabase/ssr": "^0.12.0", + "@supabase/supabase-js": "^2.49.4", + "axios": "^1.7.9", + "lucide-react": "^0.474.0", + "next": "^14.2.23", + "react": "^18.3.1", + "react-dom": "^18.3.1", + "react-hot-toast": "^2.5.2" + }, + "devDependencies": { + "@types/node": "^22.13.4", + "@types/react": "^18.3.18", + "@types/react-dom": "^18.3.5", + "autoprefixer": "^10.4.20", + "eslint": "^8.56.0", + "eslint-config-next": "^14.2.23", + "postcss": "^8.5.2", + "tailwindcss": "^3.4.17", + "typescript": "^5.7.3" + } +} diff --git a/bioai-platform/frontend/postcss.config.js b/bioai-platform/frontend/postcss.config.js new file mode 100644 index 0000000000000000000000000000000000000000..12a703d900da8159c30e75acbd2c4d87ae177f62 --- /dev/null +++ b/bioai-platform/frontend/postcss.config.js @@ -0,0 +1,6 @@ +module.exports = { + plugins: { + tailwindcss: {}, + autoprefixer: {}, + }, +}; diff --git a/bioai-platform/frontend/src/app/(auth)/auth/callback/page.tsx b/bioai-platform/frontend/src/app/(auth)/auth/callback/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..a2b2fb592fbde11476ed44f5f8b9eeee65fc1749 --- /dev/null +++ b/bioai-platform/frontend/src/app/(auth)/auth/callback/page.tsx @@ -0,0 +1,51 @@ +'use client'; + +import { useEffect, useState } from 'react'; +import { useRouter } from 'next/navigation'; +import { Loader2 } from 'lucide-react'; +import { getSupabase } from '@/lib/supabase'; + +export default function AuthCallback() { + const router = useRouter(); + const [error, setError] = useState(null); + + useEffect(() => { + const params = new URLSearchParams(window.location.search); + const code = params.get('code'); + + if (!code) { + router.replace('/auth'); + return; + } + + getSupabase().auth.exchangeCodeForSession(code).then(({ error }: { error?: any }) => { + if (error) { + setError(error.message); + return; + } + router.replace('/dashboard'); + }).catch((e: any) => { + setError(e.message || 'Unknown error'); + }); + }, [router]); + + if (error) { + return ( +
+
+

Sign in failed

+

{error}

+
+
+ ); + } + + return ( +
+
+ +

Completing sign in...

+
+
+ ); +} diff --git a/bioai-platform/frontend/src/app/(auth)/auth/page.tsx b/bioai-platform/frontend/src/app/(auth)/auth/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..f34c59d2da4bf42dbd6856bcdfaa6cf0e4bb07e2 --- /dev/null +++ b/bioai-platform/frontend/src/app/(auth)/auth/page.tsx @@ -0,0 +1,59 @@ +'use client'; + +import { useEffect } from 'react'; +import { useRouter } from 'next/navigation'; +import { Dna, Loader2 } from 'lucide-react'; +import { useAuth } from '@/contexts/auth'; + +export default function AuthPage() { + const { user, loading, signIn } = useAuth(); + const router = useRouter(); + + useEffect(() => { + if (!loading && user) { + router.replace('/dashboard'); + } + }, [user, loading, router]); + + if (loading) { + return ( +
+ +
+ ); + } + + return ( +
+
+
+ + Bio Nexus +
+ +

Sign in to Bio Nexus

+

+ Use your institutional Google account +

+ + + +

+ By signing in, you agree to our Terms of Service.
+ Free for academic researchers. No spam, ever. +

+
+
+ ); +} diff --git a/bioai-platform/frontend/src/app/(dashboard)/analyze/page.tsx b/bioai-platform/frontend/src/app/(dashboard)/analyze/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..115c123fa6bafc81eb70091a7265f56e707f5c81 --- /dev/null +++ b/bioai-platform/frontend/src/app/(dashboard)/analyze/page.tsx @@ -0,0 +1,116 @@ +'use client'; + +import { useState } from 'react'; +import { useRouter } from 'next/navigation'; +import toast from 'react-hot-toast'; +import PipelineSelector from '@/components/pipeline/PipelineSelector'; +import SequenceInput from '@/components/pipeline/SequenceInput'; +import JobProgress from '@/components/pipeline/JobProgress'; +import { runPipeline } from '@/lib/api'; +import type { JobStatus } from '@/types/pipeline'; + +export default function AnalyzePage() { + const router = useRouter(); + const [pipelineType, setPipelineType] = useState(null); + const [sequence, setSequence] = useState(''); + const [loading, setLoading] = useState(false); + const [job, setJob] = useState(null); + const [pollInterval, setPollInterval] = useState | null>(null); + + const handleRunPipeline = async () => { + if (!sequence.trim()) { + toast.error('Enter a sequence first'); + return; + } + if (!pipelineType) { + toast.error('Select a pipeline type'); + return; + } + + setLoading(true); + setJob(null); + if (pollInterval) clearInterval(pollInterval); + + try { + const result = await runPipeline(sequence, pipelineType); + setJob({ + id: result.job_id, + tool: 'pipeline', + query_preview: sequence.slice(0, 100), + status: 'running', + pipeline_type: pipelineType as any, + steps_completed: [], + context_json: null, + progress_pct: 0, + created_at: new Date().toISOString(), + completed_at: null, + error: null, + share_token: null, + }); + toast.success('Pipeline started!'); + + const interval = setInterval(async () => { + try { + const res = await fetch(`/api/backend/api/jobs/${result.job_id}`); + if (res.ok) { + const data = await res.json(); + setJob(data); + if (data.status === 'complete' || data.status === 'failed') { + clearInterval(interval); + setPollInterval(null); + if (data.status === 'complete') { + toast.success('Pipeline complete!'); + router.push(`/dashboard/results/${result.job_id}`); + } else { + toast.error(data.error || 'Pipeline failed'); + } + } + } + } catch {} + }, 2000); + setPollInterval(interval); + } catch (err: any) { + toast.error(err.response?.data?.detail || 'Failed to start pipeline'); + } finally { + setLoading(false); + } + }; + + return ( +
+

Run Analysis

+

+ Select a pipeline, paste your sequence, and get a complete analysis with AI interpretation +

+ + {!pipelineType ? ( + + ) : ( +
+
+ + + Protein Sequence Analysis + +
+ + + + {job && ( + + )} +
+ )} +
+ ); +} diff --git a/bioai-platform/frontend/src/app/(dashboard)/dashboard/page.tsx b/bioai-platform/frontend/src/app/(dashboard)/dashboard/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..5e69508ff05ddd729dd8c0cb67bec859e4cfd7e6 --- /dev/null +++ b/bioai-platform/frontend/src/app/(dashboard)/dashboard/page.tsx @@ -0,0 +1,51 @@ +'use client'; + +import { useRouter } from 'next/navigation'; +import { Play, Dna, Brain, Zap } from 'lucide-react'; + +export default function DashboardHome() { + const router = useRouter(); + + return ( +
+

Bio Nexus Dashboard

+

+ Run a pipeline or browse your recent results +

+ +
+ + + +
+ +
+ {[ + { icon: Zap, title: 'One-click pipeline', desc: 'Submit a sequence, get BLAST + annotations + structure + AI' }, + { icon: Brain, title: 'AI-powered interpretation', desc: 'Full context assembled before AI speaks — grounded, not generic' }, + { icon: Dna, title: 'Shareable results', desc: 'Every result gets a public URL you can share with collaborators' }, + ].map((f) => ( +
+ +

{f.title}

+

{f.desc}

+
+ ))} +
+
+ ); +} diff --git a/bioai-platform/frontend/src/app/(dashboard)/history/page.tsx b/bioai-platform/frontend/src/app/(dashboard)/history/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..437d2ac43c47fb6a969528c0e94797b22906497d --- /dev/null +++ b/bioai-platform/frontend/src/app/(dashboard)/history/page.tsx @@ -0,0 +1,133 @@ +'use client'; + +import { useState, useEffect } from 'react'; +import { useRouter } from 'next/navigation'; +import { Clock, Database, Trash2, Loader2, Play, Share2, ChevronDown, ChevronUp, Dna } from 'lucide-react'; +import toast from 'react-hot-toast'; +import type { JobStatus } from '@/types/pipeline'; +import { getJobs, deleteJob } from '@/lib/api'; + +function timeAgo(dateStr: string): string { + const now = new Date(); + const date = new Date(dateStr); + const seconds = Math.floor((now.getTime() - date.getTime()) / 1000); + if (seconds < 60) return 'just now'; + if (seconds < 3600) return `${Math.floor(seconds / 60)}m ago`; + if (seconds < 86400) return `${Math.floor(seconds / 3600)}h ago`; + if (seconds < 604800) return `${Math.floor(seconds / 86400)}d ago`; + return date.toLocaleDateString(); +} + +export default function HistoryPage() { + const router = useRouter(); + const [jobs, setJobs] = useState([]); + const [loading, setLoading] = useState(true); + const [expandedJob, setExpandedJob] = useState(null); + + const fetchJobs = async () => { + try { + const data = await getJobs(); + setJobs(data); + } catch { + toast.error('Failed to load history'); + } finally { + setLoading(false); + } + }; + + useEffect(() => { fetchJobs(); }, []); + + const handleDelete = async (id: string) => { + try { + await deleteJob(id); + setJobs((prev) => prev.filter((j) => j.id !== id)); + toast.success('Job deleted'); + } catch { + toast.error('Failed to delete job'); + } + }; + + const handleView = (job: JobStatus) => { + if (job.context_json) { + router.push(`/dashboard/results/${job.id}`); + } + }; + + return ( +
+

Job History

+

View and manage your past analyses

+ + {loading ? ( +
+ +
+ ) : jobs.length === 0 ? ( +
+ +

No analyses yet

+

+ Run your first protein analysis to see results here. +

+ +
+ ) : ( +
+ {jobs.map((job) => ( +
+
+
+
+ +
+
+
+

{job.pipeline_type?.replace(/_/g, ' ') || 'Pipeline'}

+ + {job.status} + +
+

{job.query_preview?.slice(0, 60)}

+
+
+
+ {timeAgo(job.created_at)} + {job.context_json && ( + + )} + + +
+
+ {expandedJob === job.id && ( +
+
+
Pipeline: {job.pipeline_type}
+
Created: {new Date(job.created_at).toLocaleString()}
+
Status: {job.status}
+ {job.completed_at &&
Completed: {new Date(job.completed_at).toLocaleString()}
} +
+
+ )} +
+ ))} +
+ )} +
+ ); +} diff --git a/bioai-platform/frontend/src/app/(dashboard)/layout.tsx b/bioai-platform/frontend/src/app/(dashboard)/layout.tsx new file mode 100644 index 0000000000000000000000000000000000000000..3a1aaa5fd83d3d6d1e10fc476be0865f31b01e8e --- /dev/null +++ b/bioai-platform/frontend/src/app/(dashboard)/layout.tsx @@ -0,0 +1,112 @@ +'use client'; + +import { useEffect, useState } from 'react'; +import Link from 'next/link'; +import { usePathname, useRouter } from 'next/navigation'; +import { Dna, Database, History, Settings, LogOut, Loader2, Sparkles, Play } from 'lucide-react'; +import { useAuth } from '@/contexts/auth'; +import { getJobCount } from '@/lib/api'; + +const navItems = [ + { href: '/dashboard/analyze', label: 'Analyze', icon: Play }, + { href: '/dashboard', label: 'Dashboard', icon: Sparkles }, + { href: '/dashboard/history', label: 'History', icon: History }, + { href: '/dashboard/settings', label: 'Settings', icon: Settings }, +]; + +export default function DashboardLayout({ children }: { children: React.ReactNode }) { + const pathname = usePathname(); + const router = useRouter(); + const { user, loading, signOut } = useAuth(); + const [usage, setUsage] = useState({ count: 0, limit: 10, remaining: 10 }); + + useEffect(() => { + if (!loading && !user) { + router.replace('/auth'); + } + }, [user, loading, router]); + + useEffect(() => { + if (!user) return; + getJobCount().then(setUsage).catch(() => {}); + }, [user, pathname]); + + if (loading) { + return ( +
+ +
+ ); + } + + if (!user) return null; + + const usagePct = usage.limit > 0 ? ((usage.limit - usage.remaining) / usage.limit) * 100 : 0; + + return ( +
+ + +
+
+ {children} +
+
+
+ ); +} diff --git a/bioai-platform/frontend/src/app/(dashboard)/results/[jobId]/page.tsx b/bioai-platform/frontend/src/app/(dashboard)/results/[jobId]/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..e9f2be95b58ed0338cf5f053f43c878fe13a30a4 --- /dev/null +++ b/bioai-platform/frontend/src/app/(dashboard)/results/[jobId]/page.tsx @@ -0,0 +1,144 @@ +'use client'; + +import { useEffect, useState } from 'react'; +import { useParams } from 'next/navigation'; +import { Loader2, Dna } from 'lucide-react'; +import toast from 'react-hot-toast'; +import type { JobStatus } from '@/types/pipeline'; +import AIInterpretation from '@/components/results/AIInterpretation'; +import BlastPanel from '@/components/results/BlastPanel'; +import UniprotPanel from '@/components/results/UniprotPanel'; +import StructureViewer from '@/components/results/StructureViewer'; + +export default function ResultsPage() { + const params = useParams(); + const jobId = params.jobId as string; + const [job, setJob] = useState(null); + const [loading, setLoading] = useState(true); + + useEffect(() => { + let cancelled = false; + const poll = async () => { + try { + const res = await fetch(`/api/backend/api/jobs/${jobId}`); + if (res.ok) { + const data = await res.json(); + if (!cancelled) { + setJob(data); + if (data.status === 'complete' || data.status === 'failed') { + setLoading(false); + return; + } + } + } + } catch {} + if (!cancelled) setTimeout(poll, 2000); + }; + poll(); + return () => { cancelled = true; }; + }, [jobId]); + + if (loading && !job) { + return ( +
+
+ +

Loading results...

+
+
+ ); + } + + if (!job) { + return ( +
+ +

Result not found

+

This job does not exist or has been deleted.

+
+ ); + } + + if (job.status === 'running' || job.status === 'pending') { + return ( +
+
+ +

Pipeline is running...

+ {job.steps_completed && job.steps_completed.length > 0 && ( +

Completed: {job.steps_completed.join(', ')}

+ )} +
+
+ ); + } + + if (job.status === 'failed') { + return ( +
+

Pipeline Failed

+

{job.error || 'An unknown error occurred'}

+
+ ); + } + + const context = job.context_json; + if (!context) { + return ( +
+

No context data

+

This job has no context data. It may have been created with an older version.

+
+ ); + } + + const handleShare = async () => { + // Copy result URL + const url = `${window.location.origin}/shared/${jobId}`; + try { + await navigator.clipboard.writeText(url); + toast.success('Share link copied!'); + } catch { + toast.error('Failed to copy link'); + } + }; + + return ( +
+
+
+

Analysis Results

+

+ Query: {context.query.sequence.slice(0, 80)}... ({context.query.length} aa) +

+
+ +
+ + + +
+ {context.blast && context.blast.hits && context.blast.hits.length > 0 && ( + + )} + + {context.uniprot && ( + + )} +
+ + {context.alphafold && ( + + )} +
+ ); +} diff --git a/bioai-platform/frontend/src/app/(dashboard)/settings/page.tsx b/bioai-platform/frontend/src/app/(dashboard)/settings/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..c6aa6dd74ff4343137c87c471fb790635370e57d --- /dev/null +++ b/bioai-platform/frontend/src/app/(dashboard)/settings/page.tsx @@ -0,0 +1,192 @@ +'use client'; + +import { useState, useEffect } from 'react'; +import axios from 'axios'; +import toast from 'react-hot-toast'; +import { User, BarChart3, Bell, Key, Shield, Loader2, Save, ExternalLink, Trash2 } from 'lucide-react'; +import { useAuth } from '@/contexts/auth'; + +interface UsageStats { + jobsToday: number; + jobsTotal: number; + tokensUsed: number; +} + +export default function SettingsPage() { + const { user, getToken } = useAuth(); + const [institution, setInstitution] = useState(''); + const [fullName, setFullName] = useState(''); + const [saving, setSaving] = useState(false); + const [stats, setStats] = useState({ jobsToday: 0, jobsTotal: 0, tokensUsed: 0 }); + const [notifications, setNotifications] = useState({ + emailOnComplete: true, + emailOnWeekly: false, + }); + const [deleteRequested, setDeleteRequested] = useState(false); + + useEffect(() => { + if (!user) return; + const fetchData = async () => { + try { + const token = await getToken(); + const [countRes, jobsRes, profileRes] = await Promise.all([ + axios.get('/api/backend/api/jobs/count', { headers: { Authorization: `Bearer ${token}` } }), + axios.get('/api/backend/api/jobs', { headers: { Authorization: `Bearer ${token}` } }), + axios.get('/api/backend/api/profile', { headers: { Authorization: `Bearer ${token}` } }), + ]); + setStats({ + jobsToday: countRes.data.count || 0, + jobsTotal: (jobsRes.data.jobs || []).length, + tokensUsed: 0, + }); + if (profileRes.data) { + setFullName(profileRes.data.full_name || ''); + setInstitution(profileRes.data.institution || ''); + } + } catch {} + }; + fetchData(); + }, [user]); + + const handleSave = async () => { + setSaving(true); + try { + const token = await getToken(); + await axios.put('/api/backend/api/profile', { full_name: fullName, institution }, { headers: { Authorization: `Bearer ${token}` } }); + toast.success('Settings saved'); + } catch { + toast.error('Failed to save settings'); + } finally { + setSaving(false); + } + }; + + if (!user) return null; + + return ( +
+

Settings

+

Manage your account and preferences

+ +
+
+
+ +

Account

+
+
+
+ + +
+
+
+ + setFullName(e.target.value)} placeholder="e.g. Priya Sharma" className="w-full px-4 py-2.5 rounded-xl border border-gray-300 focus:border-green-500 focus:ring-2 focus:ring-green-200 outline-none transition text-sm text-gray-900" /> +
+
+ + setInstitution(e.target.value)} placeholder="e.g. IIT Bombay" className="w-full px-4 py-2.5 rounded-xl border border-gray-300 focus:border-green-500 focus:ring-2 focus:ring-green-200 outline-none transition text-sm text-gray-900" /> +
+
+ +
+
+ +
+
+ +

Usage

+
+
+
+

{stats.jobsToday}

+

Jobs today

+
+
+

{stats.jobsTotal}

+

Total jobs

+
+
+

Free

+

Current plan

+
+
+
+ +
+
+ +

Notifications

+
+ {[ + { key: 'emailOnComplete' as const, label: 'Email when analysis completes', desc: 'Get notified when a pipeline job finishes' }, + { key: 'emailOnWeekly' as const, label: 'Weekly usage summary', desc: 'Receive a weekly email with your usage stats' }, + ].map((item) => ( +
+
+

{item.label}

+

{item.desc}

+
+ +
+ ))} +
+ +
+
+ +

API Access

+
+
+ +

Coming in Phase 2

+

Programmatic API access for running pipelines from your scripts.

+
+
+ +
+
+ +

Data & Privacy

+
+
+

Your uploaded sequences and results belong to you. We never train AI models on your data.

+

Cached query results are stored for 24 hours for performance. They are keyed by input hash, not your user ID.

+

All AI outputs are labeled "AI-assisted research analysis — not for clinical or diagnostic use."

+
+
+ +
+
+ +

Danger Zone

+
+ {deleteRequested ? ( +
+ Deletion request submitted. We will process it within 48 hours. +
+ ) : ( +
+
+

Request account deletion

+

This will remove all your data within 30 days

+
+ +
+ )} +
+
+
+ ); +} diff --git a/bioai-platform/frontend/src/app/api/waitlist/route.ts b/bioai-platform/frontend/src/app/api/waitlist/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..5184efe98bd8fa8f0ac304fc2d08a731c00b7d3d --- /dev/null +++ b/bioai-platform/frontend/src/app/api/waitlist/route.ts @@ -0,0 +1,38 @@ +import { NextRequest, NextResponse } from 'next/server'; +import { createClient } from '@supabase/supabase-js'; + +function getSupabase() { + const url = process.env.NEXT_PUBLIC_SUPABASE_URL; + const key = process.env.SUPABASE_SERVICE_ROLE_KEY; + if (!url || !key) { + throw new Error('Supabase env vars not configured'); + } + return createClient(url, key); +} + +export async function POST(request: NextRequest) { + try { + const { email } = await request.json(); + + if (!email || !email.includes('@')) { + return NextResponse.json({ error: 'Valid email required' }, { status: 400 }); + } + + const supabase = getSupabase(); + const { error } = await supabase + .from('waitlist') + .insert({ email, created_at: new Date().toISOString() }); + + if (error) { + if (error.code === '23505') { + return NextResponse.json({ error: 'Email already registered' }, { status: 409 }); + } + throw error; + } + + return NextResponse.json({ success: true }); + } catch (error) { + console.error('Waitlist error:', error); + return NextResponse.json({ error: 'Internal server error' }, { status: 500 }); + } +} \ No newline at end of file diff --git a/bioai-platform/frontend/src/app/globals.css b/bioai-platform/frontend/src/app/globals.css new file mode 100644 index 0000000000000000000000000000000000000000..0573d5f8a63df5540800f2b5f8dec639e0d40b6e --- /dev/null +++ b/bioai-platform/frontend/src/app/globals.css @@ -0,0 +1,25 @@ +@tailwind base; +@tailwind components; +@tailwind utilities; + +:root { + --foreground-rgb: 0, 0, 0; + --background-start-rgb: 240, 253, 244; + --background-end-rgb: 255, 255, 255; +} + +body { + color: rgb(var(--foreground-rgb)); + background: linear-gradient( + to bottom, + transparent, + rgb(var(--background-end-rgb)) + ) rgb(var(--background-start-rgb)); + min-height: 100vh; +} + +@layer utilities { + .text-balance { + text-wrap: balance; + } +} \ No newline at end of file diff --git a/bioai-platform/frontend/src/app/layout.tsx b/bioai-platform/frontend/src/app/layout.tsx new file mode 100644 index 0000000000000000000000000000000000000000..86b1d5f2269aa513cac29ce3f090e28d90765a2b --- /dev/null +++ b/bioai-platform/frontend/src/app/layout.tsx @@ -0,0 +1,26 @@ +import type { Metadata } from 'next'; +import './globals.css'; +import { Toaster } from 'react-hot-toast'; +import { Providers } from './providers'; + +export const metadata: Metadata = { + title: 'Bio Nexus — One interface for every bioinformatics tool', + description: 'Protein sequence analysis, BLAST, UniProt, AlphaFold, docking — all in one place. Built for researchers who aren\'t bioinformaticians.', +}; + +export default function RootLayout({ + children, +}: { + children: React.ReactNode; +}) { + return ( + + + + {children} + + + + + ); +} \ No newline at end of file diff --git a/bioai-platform/frontend/src/app/page.tsx b/bioai-platform/frontend/src/app/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..d17e5cc94345469e143fa7bb1c618d2c3147eaa3 --- /dev/null +++ b/bioai-platform/frontend/src/app/page.tsx @@ -0,0 +1,161 @@ +'use client'; + +import { useState } from 'react'; +import toast from 'react-hot-toast'; +import { Dna, Zap, Brain, Database, ChevronRight, Check } from 'lucide-react'; + +export default function Home() { + const [email, setEmail] = useState(''); + const [loading, setLoading] = useState(false); + const [submitted, setSubmitted] = useState(false); + + const handleSubmit = async (e: React.FormEvent) => { + e.preventDefault(); + if (!email) return; + + setLoading(true); + try { + const res = await fetch('/api/backend/api/waitlist', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ email }), + }); + + if (res.status === 409) { + toast.error('You\'re already on the list!'); + setSubmitted(true); + return; + } + + if (!res.ok) throw new Error('Failed'); + + setSubmitted(true); + toast.success('You\'re on the list!'); + } catch { + toast.error('Something went wrong. Try again.'); + } finally { + setLoading(false); + } + }; + + return ( +
+ {/* Nav */} + + + {/* Hero */} +
+
+

+ One interface for every bioinformatics tool you use. +

+

+ BLAST, UniProt, AlphaFold, docking, MSA, pathway analysis — run from a single dashboard. + No command line. No juggling 12 browser tabs. Built for researchers who aren't bioinformaticians. +

+
+ + {/* Waitlist form */} +
+ {submitted ? ( +
+
+ +
+

You're on the list!

+

We'll reach out when the beta is ready.

+
+
+
+ ) : ( +
+ setEmail(e.target.value)} + required + className="flex-1 px-4 py-3 rounded-xl border border-gray-300 focus:border-green-500 focus:ring-2 focus:ring-green-200 outline-none transition text-gray-900 placeholder:text-gray-400" + /> + +
+ )} +

Free for academic researchers. No spam, ever.

+
+
+ + {/* Features */} +
+
+

+ Everything you need, nothing you don't +

+
+ {[ + { icon: Database, title: 'BLAST + UniProt', desc: 'Run searches and pull annotations in seconds. Cached for speed.' }, + { icon: Brain, title: 'AI Interpretation', desc: 'Every result explained in plain language with citations to primary sources.' }, + { icon: Zap, title: 'AlphaFold Structures', desc: 'Fetch 3D predictions for 200M+ proteins. Interactive 3D viewer built in.' }, + { icon: Dna, title: 'Drug Discovery', desc: 'ChEMBL bioactivity, PubChem compounds, molecular docking — all connected.' }, + ].map((f) => ( +
+ +

{f.title}

+

{f.desc}

+
+ ))} +
+
+
+ + {/* Who it's for */} +
+
+

+ Built for researchers at IITs, IISERs, CSIR labs, NCBS, CCMB, AIIMS +

+
+ {[ + { step: '1', text: 'Paste your protein sequence or FASTA file' }, + { step: '2', text: 'Pick a tool — BLAST, structure, docking, anything' }, + { step: '3', text: 'Get results with AI explanation you can cite' }, + ].map((s) => ( +
+
{s.step}
+

{s.text}

+
+ ))} +
+
+
+ + {/* Footer */} +
+
+
+ + Bio Nexus +
+ Made for Indian computational biology researchers +
+
+
+ ); +} \ No newline at end of file diff --git a/bioai-platform/frontend/src/app/providers.tsx b/bioai-platform/frontend/src/app/providers.tsx new file mode 100644 index 0000000000000000000000000000000000000000..b6e759f76b5281b55968d7f19518ad1c14a57e66 --- /dev/null +++ b/bioai-platform/frontend/src/app/providers.tsx @@ -0,0 +1,8 @@ +'use client'; + +import { type ReactNode } from 'react'; +import { AuthProvider } from '@/contexts/auth'; + +export function Providers({ children }: { children: ReactNode }) { + return {children}; +} diff --git a/bioai-platform/frontend/src/app/shared/[token]/page.tsx b/bioai-platform/frontend/src/app/shared/[token]/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..25fe07e9b8a7aeb3ea3600e11cf5cce80b295beb --- /dev/null +++ b/bioai-platform/frontend/src/app/shared/[token]/page.tsx @@ -0,0 +1,85 @@ +'use client'; + +import { useEffect, useState } from 'react'; +import { useParams } from 'next/navigation'; +import { Dna, Loader2 } from 'lucide-react'; +import type { JobStatus } from '@/types/pipeline'; +import { getSharedResult } from '@/lib/api'; +import AIInterpretation from '@/components/results/AIInterpretation'; +import BlastPanel from '@/components/results/BlastPanel'; +import UniprotPanel from '@/components/results/UniprotPanel'; +import StructureViewer from '@/components/results/StructureViewer'; + +export default function SharedResultPage() { + const params = useParams(); + const token = params.token as string; + const [job, setJob] = useState(null); + const [loading, setLoading] = useState(true); + const [error, setError] = useState(null); + + useEffect(() => { + getSharedResult(token) + .then(setJob) + .catch((err) => setError(err.message)) + .finally(() => setLoading(false)); + }, [token]); + + if (loading) { + return ( +
+ +
+ ); + } + + if (error || !job) { + return ( +
+
+ +

Not Found

+

This shared result does not exist or has been removed.

+
+
+ ); + } + + const context = job.context_json; + + return ( +
+
+
+ + Bio Nexus — Shared Result +
+ + {!context ? ( +
+

This result is from an older version and cannot be displayed in full.

+
+ ) : ( +
+
+

Analysis Results

+

+ Query: {context.query.sequence.slice(0, 80)}... ({context.query.length} aa) +

+
+ + + +
+ {context.blast?.hits && context.blast.hits.length > 0 && ( + + )} + {context.uniprot && } +
+ + {context.alphafold && } +
+ )} +
+
+ ); +} diff --git a/bioai-platform/frontend/src/components/pipeline/JobProgress.tsx b/bioai-platform/frontend/src/components/pipeline/JobProgress.tsx new file mode 100644 index 0000000000000000000000000000000000000000..63c59ebd75a4abf60ed8aa4f446242c714f23bb4 --- /dev/null +++ b/bioai-platform/frontend/src/components/pipeline/JobProgress.tsx @@ -0,0 +1,59 @@ +'use client'; + +import { Loader2, CheckCircle2, XCircle } from 'lucide-react'; + +interface Step { + name: string; + label: string; +} + +const STEPS: Step[] = [ + { name: 'blast', label: 'BLAST search' }, + { name: 'uniprot', label: 'UniProt annotations' }, + { name: 'alphafold', label: 'AlphaFold structure' }, +]; + +interface JobProgressProps { + stepsCompleted: string[]; + status: string; +} + +export default function JobProgress({ stepsCompleted, status }: JobProgressProps) { + const isComplete = status === 'complete'; + const isFailed = status === 'failed'; + const stepSet = new Set(stepsCompleted); + + return ( +
+

Pipeline progress

+
+ {STEPS.map((step) => { + const done = stepSet.has(step.name); + const active = status === 'running' && (step.name === stepsCompleted[stepsCompleted.length - 1] || (!done && stepsCompleted.length === 0 && step.name === STEPS[0].name)); + return ( +
+ {done ? ( + + ) : isFailed ? ( + + ) : active ? ( + + ) : ( +
+ )} + + {step.label} + +
+ ); + })} +
+ {isComplete && ( +

All steps complete

+ )} + {isFailed && ( +

Pipeline failed

+ )} +
+ ); +} diff --git a/bioai-platform/frontend/src/components/pipeline/PipelineSelector.tsx b/bioai-platform/frontend/src/components/pipeline/PipelineSelector.tsx new file mode 100644 index 0000000000000000000000000000000000000000..29d9b94a7f18f70b8474a5bb859b527e9bf454eb --- /dev/null +++ b/bioai-platform/frontend/src/components/pipeline/PipelineSelector.tsx @@ -0,0 +1,66 @@ +'use client'; + +import { useState } from 'react'; +import { Dna, ArrowRight, ChevronRight } from 'lucide-react'; + +interface PipelineOption { + id: string; + name: string; + description: string; + icon: typeof Dna; +} + +const pipelines: PipelineOption[] = [ + { + id: 'protein_analysis', + name: 'Protein Sequence Analysis', + description: 'BLAST + UniProt + AlphaFold + AI interpretation in one run', + icon: Dna, + }, +]; + +interface PipelineSelectorProps { + onSelect: (pipelineId: string) => void; +} + +export default function PipelineSelector({ onSelect }: PipelineSelectorProps) { + const [selected, setSelected] = useState(null); + + return ( +
+

Choose a pipeline

+
+ {pipelines.map((p) => { + const active = selected === p.id; + return ( + + ); + })} +
+
+ ); +} diff --git a/bioai-platform/frontend/src/components/pipeline/SequenceInput.tsx b/bioai-platform/frontend/src/components/pipeline/SequenceInput.tsx new file mode 100644 index 0000000000000000000000000000000000000000..ef50fdd8b2c681039d2b8d8c4e1833c35a8bb36f --- /dev/null +++ b/bioai-platform/frontend/src/components/pipeline/SequenceInput.tsx @@ -0,0 +1,60 @@ +'use client'; + +import { useState } from 'react'; + +const SAMPLE = `>sp|P04637|P53_HUMAN Cellular tumor antigen p53 +MEEPQSDPSVEPPLSQETFSDLWKLLPENNVLSPLPSQAMDDLMLSPDDIEQWFTEDPGP +DEAPRMPEAAPPVAPAPAAPTPAAPAPAPSWPLSSSVPSQKTYPQGLNGTVNLPGRNSFEV +RVCACPHERCTEGRAVKLFSPKELNCEMAQDIINNKFNLNLLPETIPNTIICFVESQPPQGD +SVTTCFSWRGEGNEMYLHTEKEYKALKSTLSEKYMATCLLLSPKKKSLFPEALKLCNQKYS +EEFLLLDEALLSGCFAELACALHLAPAEGRYSGGFNHELYNMMTQQQQHQHHLQMQQHHQQ +HHQQHHQQHHQQQQQQQQQQQQQQQQQH`; + +interface SequenceInputProps { + value: string; + onChange: (value: string) => void; + onSubmit: () => void; + loading: boolean; +} + +export default function SequenceInput({ value, onChange, onSubmit, loading }: SequenceInputProps) { + const aaCount = value + .split('\n') + .filter((l) => !l.startsWith('>')) + .join('').length; + + return ( +
+ +