feat(competitor-analysis): Fix 404, SDK compatibility, and update docs
Resolved multiple issues preventing the 'competitor-analysis' app from running and serving its frontend:
1. **Fixed Python SyntaxError in Prompts:** Corrected unterminated string literals and ensure proper multi-line string formatting (using .format() instead of f-strings for complex prompts) in .
2. **Addressed Python SDK Compatibility (google-generativeai==0.3.0):**
* Removed for and by adapting the orchestrator to pass JSON schemas as direct Python dictionaries, as required by the older SDK version.
* Updated with detailed guidance on handling / imports and dictionary-based schema definitions for older SDKs.
3. **Corrected Frontend Build Dependencies:** Moved critical build dependencies (like , , ) from to in .
* Updated to include this pitfall, ensuring frontend build tools are installed in Docker.
4. **Updated Documentation:**
* : Added comprehensive lessons learned regarding dependencies, Python SDK versioning (specifically and imports for ), and robust multi-line prompt handling.
* : Integrated specific details of the encountered errors and their solutions, making the migration report a more complete historical record and guide.
These changes collectively fix the 404 error by ensuring the Python backend starts correctly and serves the frontend assets after a successful build.
This commit is contained in:
@@ -12,11 +12,12 @@
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Bevor Code kopiert wird, m.ssen die Grundlagen stimmen.
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### 1.1 Package.json Check
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Generierte Apps haben oft kein `express`, da sie keinen Server erwarten.
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* **Aktion:** "."ffne `package.json` der App.
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* **Pr.fung:** Steht `express` unter `dependencies`?
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* **Fix:**
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### 1.1 Package.json Check (Frontend Build-Falle)
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Generierte Apps haben oft kein `express`, da sie keinen Server erwarten. Noch wichtiger ist, dass kritische Build-Tools oft fälschlicherweise in `devDependencies` deklariert werden.
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* **Aktion:** Öffne `package.json` der App.
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* **Prüfung 1 (Backend):** Steht `express` unter `dependencies`?
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* **Fix 1:**
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```json
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"dependencies": {
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...
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@@ -24,6 +25,8 @@ Generierte Apps haben oft kein `express`, da sie keinen Server erwarten.
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"cors": "^2.8.5"
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}
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```
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* **Prüfung 2 (Frontend Build):** Stehen Build-Tools wie `vite`, `@vitejs/plugin-react` oder `typescript` unter `devDependencies`?
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* **Fix 2 (KRITISCH):** Verschiebe **alle** `devDependencies` in die `dependencies`. Der `npm install`-Befehl im `Dockerfile` installiert `devDependencies` standardmäßig nicht, was zu einem fehlgeschlagenen `npm run build` führt.
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### 1.2 Datenbank-Datei
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Docker kann keine einzelne Datei mounten, wenn sie auf dem Host nicht existiert.
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@@ -151,16 +154,21 @@ Das System entscheidet automatisch, welches Modell genutzt wird:
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* **Szenario B: Produkt-Integration (Image-to-Image)**
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* **Modell:** `gemini-2.5-flash-image`.
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### A.6 Gemini SDK-Chaos & Modell-Verf.gbarkeit (Kritische Erkenntnis)
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### A.6 Gemini SDK-Chaos & Modell-Verfügbarkeit (Kritische Erkenntnis)
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Ein wiederkehrendes Problem bei der Migration ist der Konflikt zwischen SDK-Versionen und regionalen Modell-Beschr.nkungen.
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Ein wiederkehrendes Problem bei der Migration ist der Konflikt zwischen SDK-Versionen und regionalen Modell-Beschränkungen, sowie die schnelle Evolution der API-Schnittstellen.
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**1. Das SDK-Dilemma**
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Es existieren zwei parallele Google SDKs:
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1. **`google-generativeai` (Legacy):** Veraltet, oft instabil bei neuen Modellen, wirft Deprecation-Warnungen. Import: `import google.generativeai`.
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2. **`google-genai` (Modern):** Erforderlich f.r Imagen 4 und Gemini 2.x Features. Import: `from google import genai`.
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Es existieren zwei parallele Google SDKs, und selbst innerhalb von `google-generativeai` ändern sich die Modulstrukturen schnell:
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1. **`google-generativeai` (Legacy):** Versionen wie `0.3.0` verhalten sich anders als neuere. Oft instabil bei neuen Modellen, wirft Deprecation-Warnungen. Import: `import google.generativeai`.
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2. **`google-genai` (Modern):** Erforderlich für Imagen 4 und Gemini 2.x Features. Import: `from google import genai`.
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**L.SUNG:** Nutze den **Dual-Support-Ansatz** in `helpers.py`. Importiere beide und verwende die neue Lib f.r Bilder und die alte (da stabiler f.r bestehende Text-Prompts) f.r Flash 1.5/2.0.
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**KRITISCHES PROBLEM: `ImportError` für `Schema` und `Content` mit `google-generativeai==0.3.0`**
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* **Fehler:** `ImportError: cannot import name 'Schema' from 'google.generativeai.types'` oder `ImportError: cannot import name 'Content' from 'google.generativeai.types'`.
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* **Ursache:** In älteren Versionen des `google-generativeai`-SDK (z.B. `0.3.0`, wie in diesem Projekt verwendet) existierten diese Klassen (`Schema`, `Content`) nicht an den gleichen Importpfaden wie in neueren Versionen oder wurden gar nicht als separate Klassen verwendet.
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* **LÖSUNG (für `google-generativeai==0.3.0`):**
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* Entferne **alle** Importe für `Schema` und `Content` (z.B. `from google.generativeai.types import HarmCategory, HarmBlockThreshold`).
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* Ersetze **alle** Instanziierungen von `Schema(...)` durch einfache Python-Dictionaries, die direkt das JSON-Schema repräsentieren. Die `generation_config` akzeptiert in dieser Version direkt das Dictionary.
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**2. Der "404 Not Found" Modell-Fehler**
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Oft liefert die API einen 404 Fehler f.r ein Modell (z.B. `gemini-1.5-flash`), obwohl es laut Dokumentation existiert.
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47
MIGRATION_REPORT_COMPETITOR_ANALYSIS.md
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47
MIGRATION_REPORT_COMPETITOR_ANALYSIS.md
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@@ -0,0 +1,47 @@
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# Migration Report: Competitor Analysis Agent
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## Status: Jan 09, 2026
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The `competitor-analysis` application has been successfully migrated to the local Docker stack and integrated into the `gemini-gateway` (Nginx).
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### 1. Vorgehen (Process)
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1. **Dateistruktur:**
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* Erstellung des Verzeichnisses `competitor-analysis-app/`.
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* Kopie aller Dateien aus dem Original-Verzeichnis.
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2. **Frontend-Anpassung:**
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* `vite.config.ts`: `base: './'` gesetzt, um korrektes Routing unter dem Sub-Pfad `/ca/` zu ermöglichen.
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* `geminiService.ts`: Direkte Aufrufe an `@google/genai` entfernt. Alle Funktionen nutzen nun `fetch()` an den neuen Python-Backend-Endpunkt `/api/...`.
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3. **Backend-Orchestrator (Python/FastAPI):**
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* Erstellung von `competitor_analysis_orchestrator.py`.
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* Portierung aller Prompts und Schemata aus dem TypeScript-Code in Python (Pydantic & Google Generative AI SDK).
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* Implementierung einer robusten JSON-Parsing-Logik (`parse_json_response`), die Markdown-Blöcke entfernt und inkonsistente LLM-Antworten korrigiert.
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* Implementierung einer Modell-Kandidaten-Liste (`gemini-1.5-pro` mit Fallback), um regionale Verfügbarkeit sicherzustellen.
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* Integration von `StaticFiles`, um das fertig gebaute Frontend direkt über den Python-Server auszuliefern.
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4. **Docker-Integration:**
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* `Dockerfile`: Multi-Stage Build (Node.js zum Bauen, Python zum Ausführen).
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* `docker-compose.yml`: Neuer Service `competitor-analysis` hinzugefügt, inklusive Volume-Mounts für API-Keys und Live-Debugging des Orchestrators.
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* `nginx-proxy.conf`: Routing für `/ca/` konfiguriert.
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### 2. Next Steps
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* **Persistenz:** Aktuell werden Analysen nur im App-State (RAM) gehalten. Eine Anbindung an die SQLite-Datenbank (ähnlich wie beim `b2b-app`) wäre sinnvoll, um Analysen zu speichern und später wieder aufzurufen.
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* **Fehlermanagement:** Verfeinerung der Error-Handler im Frontend, um spezifische Backend-Fehler (z.B. API-Limits) besser anzuzeigen.
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* **Weitere Schritte im Orchestrator:** Implementierung der verbleibenden Steps (4-8), falls diese noch nicht vollständig in Python abgebildet sind (derzeit sind Step 1, 2, 3, 4, 5, 6, 7 und 8 bereits im Code vorbereitet oder implementiert).
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### 3. Lessons Learned
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* **Python SDK-Versionskonflikte (`google-generativeai==0.3.0`):** Das im Projekt verwendete Python SDK (`google-generativeai` Version `0.3.0`) ist nicht mit neueren API-Schnittstellen kompatibel.
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* `ImportError: cannot import name 'Schema' from 'google.generativeai.types'` und `ImportError: cannot import name 'Content' from 'google.generativeai.types'` treten auf, da diese Klassen in dieser SDK-Version an diesen Importpfaden nicht existieren oder anders implementiert sind.
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* **Lösung:** Schemata müssen direkt als Python-Dictionaries an die `generation_config` übergeben werden. Alle Importe für `Schema` und `Content` müssen entfernt werden.
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* **Frontend Build (`package.json` `devDependencies`):** Build-Tools wie `vite`, `@vitejs/plugin-react` und `typescript` müssen in den `dependencies` der `package.json` stehen, nicht in `devDependencies`. Andernfalls schlägt `npm install` im Docker-Build fehl, was zu einem leeren oder fehlenden `dist`-Ordner und einem 404-Fehler des Python-Servers führt.
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* **Syntaxfehler in mehrzeiligen Prompts (`f-strings`):** Besonders bei älteren Python-Versionen und komplexen mehrzeiligen Prompts mit `f-strings` können subtile Fehler (z.B. falsch platzierte Anführungszeichen oder unbeabsichtigter deutscher Text in englischen Prompts) zu `SyntaxError: unterminated string literal` führen.
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* **Lösung:** Die robusteste Methode ist, mehrzeilige Prompts als Liste von Strings zu definieren und mit `"\n".join()` zusammenzufügen.
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* **SDK-Unterschiede:** Das Python SDK (`google-generativeai`) verhält sich bei der Schema-Validierung strikter als die JS-Variante. Prompts mussten leicht angepasst werden, um sicherzustellen, dass die AI wirklich valides JSON liefert.
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* **Vite Base Path:** Ohne `base: './'` in `vite.config.ts` schlagen alle Asset-Requests fehl, wenn die App hinter einem Proxy unter `/ca/` läuft.
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* **Double JSON Trap:** LLMs neigen dazu, JSON in Markdown zu packen. Der Backend-Orchestrator muss dies proaktiv bereinigen, bevor `json.loads()` aufgerufen wird.
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* **Proxy-Routing:** Der Trailing Slash in Nginx (`proxy_pass http://.../`) ist kritisch, damit die Pfade innerhalb der App korrekt aufgelöst werden.
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---
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*Dokumentation erstellt am 09.01.2026*
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448
competitor-analysis-app/App.tsx
Normal file
448
competitor-analysis-app/App.tsx
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@@ -0,0 +1,448 @@
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import React, { useState, useCallback, useEffect, useRef } from 'react';
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import type { AppState, CompetitorCandidate, Product, TargetIndustry, Keyword, SilverBullet, Battlecard, ReferenceAnalysis } from './types';
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import { fetchStep1Data, fetchStep2Data, fetchStep3Data, fetchStep4Data, fetchStep5Data_SilverBullets, fetchStep6Data_Conclusion, fetchStep7Data_Battlecards, fetchStep8Data_ReferenceAnalysis } from './services/geminiService';
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import { generatePdfReport } from './services/pdfService';
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import InputForm from './components/InputForm';
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import StepIndicator from './components/StepIndicator';
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import Step1Extraction from './components/Step1_Extraction';
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import Step2Keywords from './components/Step2_Keywords';
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import Step3Competitors from './components/Step3_Competitors';
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import Step4Analysis from './components/Step4_Analysis';
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import Step5SilverBullets from './components/Step5_SilverBullets';
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import Step6Conclusion from './components/Step6_Conclusion';
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import Step7_Battlecards from './components/Step7_Battlecards';
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import Step8_References from './components/Step8_References';
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import LoadingSpinner from './components/LoadingSpinner';
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import { translations } from './translations';
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const SunIcon = () => (<svg xmlns="http://www.w3.org/2000/svg" className="h-6 w-6" fill="none" viewBox="0 0 24 24" stroke="currentColor"><path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 3v1m0 16v1m9-9h-1M4 12H3m15.364 6.364l-.707-.707M6.343 6.343l-.707-.707m12.728 0l-.707.707M6.343 17.657l-.707.707M16 12a4 4 0 11-8 0 4 4 0 018 0z" /></svg>);
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const MoonIcon = () => (<svg xmlns="http://www.w3.org/2000/svg" className="h-6 w-6" fill="none" viewBox="0 0 24 24" stroke="currentColor"><path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M20.354 15.354A9 9 0 018.646 3.646 9.003 9.003 0 0012 21a9.003 9.003 0 008.354-5.646z" /></svg>);
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const RestartIcon = () => (<svg xmlns="http://www.w3.org/2000/svg" className="h-6 w-6" fill="none" viewBox="0 0 24 24" stroke="currentColor" strokeWidth={2}><path strokeLinecap="round" strokeLinejoin="round" d="M4 4v5h5M4 12a9 9 0 109-9" /></svg>);
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const DownloadIcon = () => (<svg xmlns="http://www.w3.org/2000/svg" className="h-5 w-5 mr-2" fill="none" viewBox="0 0 24 24" stroke="currentColor"><path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M4 16v1a3 3 0 003 3h10a3 3 0 003-3v-1m-4-4l-4 4m0 0l-4-4m4 4V4" /></svg>);
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const ChevronDownIcon = () => (<svg className="w-5 h-5 ml-2 -mr-1" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 20 20" fill="currentColor" aria-hidden="true"><path fillRule="evenodd" d="M5.293 7.293a1 1 0 011.414 0L10 10.586l3.293-3.293a1 1 0 111.414 1.414l-4 4a1 1 0 01-1.414 0l-4-4a1 1 0 010-1.414z" clipRule="evenodd" /></svg>);
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const App: React.FC = () => {
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const [appState, setAppState] = useState<AppState | null>(null);
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const [isLoading, setIsLoading] = useState<boolean>(false);
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const [error, setError] = useState<string | null>(null);
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const [theme, setTheme] = useState<'light' | 'dark'>('dark');
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const [highestStep, setHighestStep] = useState(0);
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const [isDropdownOpen, setIsDropdownOpen] = useState(false);
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const dropdownRef = useRef<HTMLDivElement>(null);
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const t = translations[appState?.initial_params?.language || 'de'];
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useEffect(() => {
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if (theme === 'dark') {
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document.documentElement.classList.add('dark');
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} else {
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document.documentElement.classList.remove('dark');
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}
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}, [theme]);
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useEffect(() => {
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const handleClickOutside = (event: MouseEvent) => {
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if (dropdownRef.current && !dropdownRef.current.contains(event.target as Node)) {
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setIsDropdownOpen(false);
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}
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};
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document.addEventListener("mousedown", handleClickOutside);
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return () => document.removeEventListener("mousedown", handleClickOutside);
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}, []);
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const handleRestart = () => {
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setAppState(null);
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setIsLoading(false);
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setError(null);
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setHighestStep(0);
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};
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const handleStartAnalysis = useCallback(async (startUrl: string, maxCompetitors: number, marketScope: string, language: 'de' | 'en') => {
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setIsLoading(true);
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setError(null);
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setAppState(null);
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setHighestStep(0);
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const currentT = translations[language];
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try {
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const { products, target_industries } = await fetchStep1Data(startUrl, language);
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setAppState({
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step: 1,
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initial_params: { start_url: startUrl, max_competitors: maxCompetitors, market_scope: marketScope, language },
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company: { name: new URL(startUrl).hostname.replace('www.', ''), start_url: startUrl },
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products: products,
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target_industries: target_industries,
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keywords: [],
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competitor_candidates: [],
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competitors_shortlist: [],
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analyses: [],
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silver_bullets: [],
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conclusion: null,
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battlecards: [],
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reference_analysis: [],
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reference_analysis_grounding: [],
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});
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setHighestStep(1);
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} catch (e) {
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console.error("Error in Step 1:", e);
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setError(currentT.errors.step1);
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} finally {
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setIsLoading(false);
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}
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}, []);
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const handleConfirmStep = useCallback(async () => {
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if (!appState) return;
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setIsLoading(true);
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setError(null);
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const nextStep = appState.step + 1;
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const lang = appState.initial_params.language;
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try {
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let newState: Partial<AppState> = {};
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switch (appState.step) {
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case 1:
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const { keywords } = await fetchStep2Data(appState.products, appState.target_industries, lang);
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newState = { keywords, step: 2 };
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break;
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case 2:
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const { competitor_candidates } = await fetchStep3Data(appState.keywords, appState.initial_params.market_scope, lang);
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newState = { competitor_candidates, step: 3 };
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break;
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case 3:
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const shortlist = [...appState.competitor_candidates]
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.sort((a, b) => b.confidence - a.confidence)
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.slice(0, appState.initial_params.max_competitors);
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const { analyses } = await fetchStep4Data(appState.company, shortlist, lang);
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newState = { competitors_shortlist: shortlist, analyses, step: 4 };
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break;
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case 4:
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const { silver_bullets } = await fetchStep5Data_SilverBullets(appState.company, appState.analyses, lang);
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newState = { silver_bullets, step: 5 };
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break;
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case 5:
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const { conclusion } = await fetchStep6Data_Conclusion(appState.company, appState.products, appState.target_industries, appState.analyses, appState.silver_bullets, lang);
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newState = { conclusion, step: 6 };
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break;
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case 6:
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const { battlecards } = await fetchStep7Data_Battlecards(appState.company, appState.analyses, appState.silver_bullets, lang);
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newState = { battlecards, step: 7 };
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break;
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case 7:
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const { reference_analysis, groundingMetadata } = await fetchStep8Data_ReferenceAnalysis(appState.competitors_shortlist, lang);
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newState = { reference_analysis, reference_analysis_grounding: groundingMetadata, step: 8 };
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||||
break;
|
||||
}
|
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setAppState(prevState => ({ ...prevState!, ...newState }));
|
||||
if (nextStep > highestStep) {
|
||||
setHighestStep(nextStep);
|
||||
}
|
||||
} catch (e) {
|
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console.error(`Error in Step ${appState.step + 1}:`, e);
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setError(translations[lang].errors.generic(appState.step + 1));
|
||||
} finally {
|
||||
setIsLoading(false);
|
||||
}
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||||
}, [appState, highestStep]);
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|
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const handleUpdateState = useCallback((key: keyof AppState, value: any) => {
|
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setAppState(prevState => {
|
||||
if (!prevState) return null;
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||||
return { ...prevState, [key]: value };
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||||
});
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||||
}, []);
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||||
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const renderStepContent = () => {
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if (!appState) return null;
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switch (appState.step) {
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case 1: return <Step1Extraction products={appState.products} industries={appState.target_industries} onProductsChange={(p) => handleUpdateState('products', p)} onIndustriesChange={(i) => handleUpdateState('target_industries', i)} t={t.step1} lang={appState.initial_params.language} />;
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case 2: return <Step2Keywords keywords={appState.keywords} onKeywordsChange={(k) => handleUpdateState('keywords', k)} t={t.step2} />;
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case 3: return <Step3Competitors candidates={appState.competitor_candidates} onCandidatesChange={(c) => handleUpdateState('competitor_candidates', c)} maxCompetitors={appState.initial_params.max_competitors} t={t.step3} />;
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case 4: return <Step4Analysis analyses={appState.analyses} t={t.step4} />;
|
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case 5: return <Step5SilverBullets silver_bullets={appState.silver_bullets} t={t.step5} />;
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||||
case 6: return <Step6Conclusion appState={appState} t={t.step6} />;
|
||||
case 7: return <Step7_Battlecards appState={appState} t={t.step7} />;
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||||
case 8: return <Step8_References analyses={appState.reference_analysis} groundingMetadata={appState.reference_analysis_grounding} t={t.step8} />;
|
||||
default: return null;
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||||
}
|
||||
};
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||||
|
||||
// Download logic
|
||||
const handleDownloadJson = () => {
|
||||
if (!appState) return;
|
||||
const content = JSON.stringify(appState, null, 2);
|
||||
const blob = new Blob([content], { type: 'application/json' });
|
||||
const url = URL.createObjectURL(blob);
|
||||
const link = document.createElement('a');
|
||||
link.href = url;
|
||||
link.download = `analysis_${appState.company.name}.json`;
|
||||
document.body.appendChild(link);
|
||||
link.click();
|
||||
document.body.removeChild(link);
|
||||
URL.revokeObjectURL(url);
|
||||
setIsDropdownOpen(false);
|
||||
};
|
||||
|
||||
const transformMatrixData = (matrixData: any[] | undefined): { [row: string]: { [col: string]: string } } => {
|
||||
const tableData: { [row: string]: { [col: string]: string } } = {};
|
||||
if (!matrixData || !Array.isArray(matrixData) || matrixData.length === 0) {
|
||||
return tableData;
|
||||
}
|
||||
|
||||
const allCompetitors = new Set<string>();
|
||||
matrixData.forEach(row => {
|
||||
if (row && Array.isArray(row.availability)) {
|
||||
row.availability.forEach(item => {
|
||||
if (item && typeof item.competitor === 'string') {
|
||||
allCompetitors.add(item.competitor);
|
||||
}
|
||||
});
|
||||
}
|
||||
});
|
||||
const competitorList = Array.from(allCompetitors).sort();
|
||||
|
||||
matrixData.forEach(row => {
|
||||
if (!row) return;
|
||||
|
||||
const rowKey = 'product' in row ? row.product : ('industry' in row ? row.industry : undefined);
|
||||
|
||||
if (typeof rowKey !== 'string' || !rowKey) {
|
||||
return;
|
||||
}
|
||||
|
||||
const availabilityMap = new Map<string, boolean>();
|
||||
if (Array.isArray(row.availability)) {
|
||||
row.availability.forEach(item => {
|
||||
if (item && typeof item.competitor === 'string') {
|
||||
availabilityMap.set(item.competitor, item.has_offering);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
const rowObject: { [col: string]: string } = {};
|
||||
competitorList.forEach(competitor => {
|
||||
rowObject[competitor] = availabilityMap.get(competitor) ? '✓' : ' ';
|
||||
});
|
||||
tableData[rowKey] = rowObject;
|
||||
});
|
||||
|
||||
return tableData;
|
||||
};
|
||||
|
||||
|
||||
const generateMarkdownReport = (): string => {
|
||||
if (!appState) return "";
|
||||
const langT = t.step6.markdown;
|
||||
let md = `# ${langT.title}: ${appState.company.name}\n\n`;
|
||||
md += `**${langT.startUrl}:** ${appState.initial_params.start_url}\n`;
|
||||
md += `**${langT.marketScope}:** ${appState.initial_params.market_scope}\n\n`;
|
||||
|
||||
md += `## ${langT.step1_title}\n`;
|
||||
md += `### ${langT.step1_products}\n`;
|
||||
appState.products.forEach(p => md += `- **${p.name}:** ${p.purpose}\n`);
|
||||
md += `\n### ${langT.step1_industries}\n`;
|
||||
appState.target_industries.forEach(i => md += `- ${i.name}\n`);
|
||||
|
||||
md += `\n## ${langT.step4_title}\n`;
|
||||
appState.analyses.forEach(a => {
|
||||
md += `### ${a.competitor.name} (Overlap: ${a.overlap_score}%)\n`;
|
||||
md += `- **${langT.portfolio}:** ${a.portfolio.map(p => p.product).join(', ')}\n`;
|
||||
md += `- **${langT.targetIndustries}:** ${a.target_industries.join(', ')}\n`;
|
||||
md += `- **${langT.differentiators}:**\n`;
|
||||
a.differentiators.forEach(d => md += ` - ${d}\n`);
|
||||
md += `\n`;
|
||||
});
|
||||
|
||||
md += `## ${langT.step5_title}\n`;
|
||||
appState.silver_bullets.forEach(b => {
|
||||
md += `- **${langT.against} ${b.competitor_name}:** "${b.statement}"\n`;
|
||||
});
|
||||
|
||||
if (appState.battlecards && appState.battlecards.length > 0) {
|
||||
md += `\n## ${langT.step7_title}\n\n`;
|
||||
appState.battlecards.forEach(card => {
|
||||
md += `### ${langT.against} ${card.competitor_name}\n\n`;
|
||||
md += `**${langT.profile}:**\n`;
|
||||
md += `- **${langT.focus}:** ${card.competitor_profile.focus}\n`;
|
||||
md += `- **${langT.positioning}:** ${card.competitor_profile.positioning}\n\n`;
|
||||
|
||||
md += `**${langT.strengthsVsWeaknesses}:**\n`;
|
||||
(card.strengths_vs_weaknesses || []).forEach(s => md += `- ${s}\n`);
|
||||
md += `\n`;
|
||||
|
||||
md += `**${langT.landmineQuestions}:**\n`;
|
||||
(card.landmine_questions || []).forEach(q => md += `- ${q}\n`);
|
||||
md += `\n`;
|
||||
|
||||
md += `**${langT.silverBullet}:**\n`;
|
||||
md += `> "${card.silver_bullet}"\n\n`;
|
||||
});
|
||||
}
|
||||
|
||||
if (appState.reference_analysis && appState.reference_analysis.length > 0) {
|
||||
md += `\n## ${langT.step8_title}\n`;
|
||||
appState.reference_analysis.forEach(analysis => {
|
||||
md += `### ${analysis.competitor_name}\n`;
|
||||
if ((analysis.references || []).length > 0) {
|
||||
(analysis.references || []).forEach(ref => {
|
||||
md += `- **${ref.name}** (${ref.industry || 'N/A'})\n`;
|
||||
if(ref.testimonial_snippet) md += ` - *"${ref.testimonial_snippet}"*\n`;
|
||||
if(ref.case_study_url) md += ` - [${langT.caseStudyLink}](${ref.case_study_url})\n`;
|
||||
});
|
||||
} else {
|
||||
md += ` - ${langT.noReferencesFound}\n`;
|
||||
}
|
||||
md += `\n`;
|
||||
});
|
||||
if (appState.reference_analysis_grounding && appState.reference_analysis_grounding.length > 0) {
|
||||
md += `\n#### ${langT.sources}\n`;
|
||||
appState.reference_analysis_grounding
|
||||
.filter(chunk => chunk.web && chunk.web.uri)
|
||||
.forEach(chunk => {
|
||||
md += `- [${chunk.web.title || chunk.web.uri}](${chunk.web.uri})\n`;
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if(appState.conclusion) {
|
||||
md += `\n## ${langT.step6_title}\n`;
|
||||
const transformForMdTable = (data: { [key: string]: { [key: string]: string } }) => {
|
||||
if (Object.keys(data).length === 0) return { head: '', body: '' };
|
||||
const headers = Object.keys(Object.values(data)[0] || {});
|
||||
const head = `| | ${headers.join(' | ')} |\n`;
|
||||
const separator = `|---|${headers.map(() => '---').join('|')}|\n`;
|
||||
const body = Object.entries(data).map(([row, cols]) => `| **${row}** | ${headers.map(h => cols[h] || ' ').join(' | ')} |`).join('\n');
|
||||
return { head, body: separator + body };
|
||||
};
|
||||
const productMatrixForTable = transformMatrixData(appState.conclusion.product_matrix);
|
||||
const industryMatrixForTable = transformMatrixData(appState.conclusion.industry_matrix);
|
||||
|
||||
md += `### ${langT.productMatrix}\n`;
|
||||
const prodMd = transformForMdTable(productMatrixForTable);
|
||||
md += prodMd.head + prodMd.body + '\n\n';
|
||||
|
||||
md += `### ${langT.industryMatrix}\n`;
|
||||
const indMd = transformForMdTable(industryMatrixForTable);
|
||||
md += indMd.head + indMd.body + '\n\n';
|
||||
|
||||
md += `### ${langT.summary}\n${appState.conclusion.summary}\n\n`;
|
||||
md += `### ${langT.opportunities}\n${appState.conclusion.opportunities}\n\n`;
|
||||
md += `### ${langT.nextQuestions}\n`;
|
||||
(appState.conclusion.next_questions || []).forEach(q => md += `- ${q}\n`);
|
||||
}
|
||||
|
||||
return md;
|
||||
};
|
||||
|
||||
const handleDownloadMd = () => {
|
||||
const mdContent = generateMarkdownReport();
|
||||
const blob = new Blob([mdContent], { type: 'text/markdown' });
|
||||
const url = URL.createObjectURL(blob);
|
||||
const link = document.createElement('a');
|
||||
link.href = url;
|
||||
if (appState) {
|
||||
link.download = `analysis_${appState.company.name}.md`;
|
||||
}
|
||||
document.body.appendChild(link);
|
||||
link.click();
|
||||
document.body.removeChild(link);
|
||||
URL.revokeObjectURL(url);
|
||||
setIsDropdownOpen(false);
|
||||
};
|
||||
|
||||
const handleDownloadPdf = async () => {
|
||||
if (!appState) return;
|
||||
await generatePdfReport(appState, t.step6.markdown);
|
||||
setIsDropdownOpen(false);
|
||||
};
|
||||
|
||||
return (
|
||||
<div className="min-h-screen p-4 sm:p-6 lg:p-8">
|
||||
<header className="flex justify-between items-center mb-6">
|
||||
<h1 className="text-3xl font-bold">{t.appTitle}</h1>
|
||||
<div className="flex items-center space-x-4">
|
||||
{appState && highestStep >= 6 && (
|
||||
<div className="relative inline-block text-left" ref={dropdownRef}>
|
||||
<div>
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => setIsDropdownOpen(!isDropdownOpen)}
|
||||
className="inline-flex justify-center w-full rounded-lg border border-transparent shadow-sm px-4 py-2 bg-green-600 text-base font-medium text-white hover:bg-green-700 focus:outline-none focus:ring-2 focus:ring-offset-2 focus:ring-offset-light-secondary dark:focus:ring-offset-brand-secondary focus:ring-green-500"
|
||||
>
|
||||
<DownloadIcon />
|
||||
{t.step6.downloadButton}
|
||||
<ChevronDownIcon />
|
||||
</button>
|
||||
</div>
|
||||
{isDropdownOpen && (
|
||||
<div className="origin-top-right absolute right-0 mt-2 w-56 rounded-md shadow-lg bg-light-secondary dark:bg-brand-secondary ring-1 ring-black ring-opacity-5 z-20">
|
||||
<div className="py-1" role="menu" aria-orientation="vertical" aria-labelledby="options-menu">
|
||||
<a href="#" onClick={(e) => { e.preventDefault(); handleDownloadJson(); }} className="block px-4 py-2 text-sm text-light-text dark:text-brand-text hover:bg-light-accent dark:hover:bg-brand-accent" role="menuitem">{t.step6.downloadJson}</a>
|
||||
<a href="#" onClick={(e) => { e.preventDefault(); handleDownloadMd(); }} className="block px-4 py-2 text-sm text-light-text dark:text-brand-text hover:bg-light-accent dark:hover:bg-brand-accent" role="menuitem">{t.step6.downloadMd}</a>
|
||||
<a href="#" onClick={(e) => { e.preventDefault(); handleDownloadPdf(); }} className="block px-4 py-2 text-sm text-light-text dark:text-brand-text hover:bg-light-accent dark:hover:bg-brand-accent" role="menuitem">{t.step6.downloadPdf}</a>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
{appState && (
|
||||
<button onClick={handleRestart} className="p-2 rounded-full hover:bg-light-accent dark:hover:bg-brand-accent" title={t.restartAnalysis}>
|
||||
<RestartIcon />
|
||||
</button>
|
||||
)}
|
||||
<button onClick={() => setTheme(theme === 'dark' ? 'light' : 'dark')} className="p-2 rounded-full hover:bg-light-accent dark:hover:bg-brand-accent">
|
||||
{theme === 'dark' ? <SunIcon /> : <MoonIcon />}
|
||||
</button>
|
||||
</div>
|
||||
</header>
|
||||
|
||||
<main className="mx-auto">
|
||||
{!appState && !isLoading && <InputForm onStart={handleStartAnalysis} />}
|
||||
|
||||
{isLoading && !appState && <LoadingSpinner t={t.loadingSpinner} />}
|
||||
|
||||
{appState && (
|
||||
<div className="grid grid-cols-1 lg:grid-cols-4 gap-8 items-start">
|
||||
<aside className="lg:col-span-1 lg:sticky lg:top-8">
|
||||
<div className="bg-light-secondary dark:bg-brand-secondary p-4 rounded-lg shadow-md mb-6">
|
||||
<h3 className="font-bold text-lg mb-2">{t.companyCard.title}</h3>
|
||||
<p className="text-sm break-words">{appState.company.name}</p>
|
||||
</div>
|
||||
<StepIndicator
|
||||
currentStep={appState.step}
|
||||
highestStep={highestStep}
|
||||
onStepClick={(step) => setAppState(prevState => ({...prevState!, step}))}
|
||||
t={t.stepIndicator}
|
||||
/>
|
||||
</aside>
|
||||
|
||||
<div className="lg:col-span-3">
|
||||
<div className="min-h-[400px]">
|
||||
{error && (
|
||||
<div className="bg-red-100 border-l-4 border-red-500 text-red-700 p-4 rounded-lg mb-6" role="alert">
|
||||
<p className="font-bold">{t.errors.title}</p>
|
||||
<p>{error}</p>
|
||||
</div>
|
||||
)}
|
||||
{isLoading ? <LoadingSpinner t={t.loadingSpinner} /> : renderStepContent()}
|
||||
</div>
|
||||
|
||||
{appState.step < 8 && !isLoading && (
|
||||
<div className="mt-8 text-right">
|
||||
<button
|
||||
onClick={handleConfirmStep}
|
||||
className="bg-brand-highlight hover:bg-blue-600 text-white font-bold py-3 px-6 rounded-lg shadow-lg transition duration-300 transform hover:scale-105"
|
||||
>
|
||||
{t.nextStepButton}
|
||||
</button>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
</main>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default App;
|
||||
33
competitor-analysis-app/Dockerfile
Normal file
33
competitor-analysis-app/Dockerfile
Normal file
@@ -0,0 +1,33 @@
|
||||
# Stage 1: Build the React frontend
|
||||
FROM node:18-alpine AS build-stage
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# Copy package files and install dependencies
|
||||
COPY package*.json ./
|
||||
RUN npm install
|
||||
|
||||
# Copy the rest of the frontend code and build
|
||||
COPY . .
|
||||
RUN npm run build
|
||||
|
||||
# Stage 2: Python backend orchestrator
|
||||
FROM python:3.11-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# Copy requirements and install
|
||||
COPY requirements.txt .
|
||||
RUN pip install --no-cache-dir -r requirements.txt
|
||||
|
||||
# Copy the build from the first stage
|
||||
COPY --from=build-stage /app/dist ./dist
|
||||
|
||||
# Copy the orchestrator script and .env if needed (though env should be passed via docker-compose)
|
||||
COPY competitor_analysis_orchestrator.py .
|
||||
|
||||
# Expose the port the app runs on
|
||||
EXPOSE 8000
|
||||
|
||||
# Command to run the orchestrator
|
||||
CMD ["uvicorn", "competitor_analysis_orchestrator:app", "--host", "0.0.0.0", "--port", "8000"]
|
||||
20
competitor-analysis-app/README.md
Normal file
20
competitor-analysis-app/README.md
Normal file
@@ -0,0 +1,20 @@
|
||||
<div align="center">
|
||||
<img width="1200" height="475" alt="GHBanner" src="https://github.com/user-attachments/assets/0aa67016-6eaf-458a-adb2-6e31a0763ed6" />
|
||||
</div>
|
||||
|
||||
# Run and deploy your AI Studio app
|
||||
|
||||
This contains everything you need to run your app locally.
|
||||
|
||||
View your app in AI Studio: https://ai.studio/apps/drive/1vJMxbT1hW3SiMDUeEd8cXGO_PFo8GcsE
|
||||
|
||||
## Run Locally
|
||||
|
||||
**Prerequisites:** Node.js
|
||||
|
||||
|
||||
1. Install dependencies:
|
||||
`npm install`
|
||||
2. Set the `GEMINI_API_KEY` in [.env.local](.env.local) to your Gemini API key
|
||||
3. Run the app:
|
||||
`npm run dev`
|
||||
917
competitor-analysis-app/competitor_analysis_orchestrator.py
Normal file
917
competitor-analysis-app/competitor_analysis_orchestrator.py
Normal file
@@ -0,0 +1,917 @@
|
||||
import os
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
from fastapi import FastAPI, HTTPException
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from fastapi.staticfiles import StaticFiles
|
||||
from pydantic import BaseModel
|
||||
from typing import List, Dict, Any, Optional
|
||||
|
||||
import google.generativeai as genai
|
||||
from google.generativeai.types import HarmCategory, HarmBlockThreshold
|
||||
|
||||
# Load environment variables
|
||||
load_dotenv()
|
||||
API_KEY = os.getenv("GEMINI_API_KEY")
|
||||
|
||||
# Fallback: check for API Key in a file (common in this project's Docker setup)
|
||||
if not API_KEY:
|
||||
key_file_path = os.getenv("GEMINI_API_KEY_FILE", "/app/gemini_api_key.txt")
|
||||
if os.path.exists(key_file_path):
|
||||
with open(key_file_path, 'r') as f:
|
||||
API_KEY = f.read().strip()
|
||||
|
||||
if not API_KEY:
|
||||
raise ValueError("GEMINI_API_KEY environment variable or file not set")
|
||||
|
||||
genai.configure(api_key=API_KEY)
|
||||
# Use a candidate list for models as per migration guide
|
||||
MODEL_CANDIDATES = ['gemini-1.5-pro', 'gemini-1.0-pro'] # Added 1.0-pro as fallback
|
||||
model = None
|
||||
for candidate in MODEL_CANDIDATES:
|
||||
try:
|
||||
model = genai.GenerativeModel(candidate)
|
||||
print(f"DEBUG: Using Gemini model: {candidate}")
|
||||
break
|
||||
except Exception as e:
|
||||
print(f"DEBUG: Could not load model {candidate}: {e}")
|
||||
if "404" in str(e):
|
||||
continue
|
||||
raise e
|
||||
if not model:
|
||||
raise ValueError(f"No suitable Gemini model found from candidates: {MODEL_CANDIDATES}")
|
||||
|
||||
|
||||
app = FastAPI()
|
||||
|
||||
# Configure CORS
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"],
|
||||
allow_credentials=True,
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
def parse_json_response(text: str) -> Any:
|
||||
"""Parses JSON response, stripping markdown code blocks."""
|
||||
try:
|
||||
# Clean the text, removing markdown code block fences
|
||||
cleaned_text = text.replace('```json', '').replace('```', '').strip()
|
||||
# Handle cases where the model might return a list instead of a direct object
|
||||
result = json.loads(cleaned_text)
|
||||
if isinstance(result, list) and result:
|
||||
# If it's a list, assume the first element is the intended object
|
||||
return result[0]
|
||||
return result
|
||||
except json.JSONDecodeError as e:
|
||||
print(f"Failed to parse JSON: {e}\nOriginal text: {text}")
|
||||
raise ValueError("Invalid JSON response from API")
|
||||
|
||||
# --- Schemas (ported from TypeScript) ---
|
||||
evidence_schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"url": {"type": "string"},
|
||||
"snippet": {"type": "string"},
|
||||
},
|
||||
"required": ['url', 'snippet']
|
||||
}
|
||||
|
||||
product_schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"name": {"type": "string", "description": "Product name"},
|
||||
"purpose": {"type": "string", "description": "Purpose description (1-2 sentences)"},
|
||||
"evidence": {"type": "array", "items": evidence_schema},
|
||||
},
|
||||
"required": ['name', 'purpose', 'evidence']
|
||||
}
|
||||
|
||||
industry_schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"name": {"type": "string", "description": "Name of the target industry"},
|
||||
"evidence": {"type": "array", "items": evidence_schema},
|
||||
},
|
||||
"required": ['name', 'evidence']
|
||||
}
|
||||
|
||||
|
||||
# --- Request Models for FastAPI ---
|
||||
class ProductDetailsRequest(BaseModel):
|
||||
name: str
|
||||
url: str
|
||||
language: str
|
||||
|
||||
class FetchStep1DataRequest(BaseModel):
|
||||
start_url: str
|
||||
language: str
|
||||
|
||||
class ProductModel(BaseModel):
|
||||
name: str
|
||||
purpose: str
|
||||
evidence: List[Dict[str, str]]
|
||||
|
||||
class TargetIndustryModel(BaseModel):
|
||||
name: str
|
||||
evidence: List[Dict[str, str]]
|
||||
|
||||
class FetchStep2DataRequest(BaseModel):
|
||||
products: List[ProductModel]
|
||||
industries: List[TargetIndustryModel]
|
||||
language: str
|
||||
|
||||
class KeywordModel(BaseModel):
|
||||
term: str
|
||||
rationale: str
|
||||
|
||||
class FetchStep3DataRequest(BaseModel):
|
||||
keywords: List[KeywordModel]
|
||||
market_scope: str
|
||||
language: str
|
||||
|
||||
class CompanyModel(BaseModel):
|
||||
name: str
|
||||
start_url: str
|
||||
|
||||
class CompetitorCandidateModel(BaseModel):
|
||||
name: str
|
||||
url: str
|
||||
confidence: float
|
||||
why: str
|
||||
evidence: List[Dict[str, str]]
|
||||
|
||||
class FetchStep4DataRequest(BaseModel):
|
||||
company: CompanyModel
|
||||
competitors: List[CompetitorCandidateModel]
|
||||
language: str
|
||||
|
||||
class AnalysisModel(BaseModel):
|
||||
competitor: Dict[str, str]
|
||||
portfolio: List[Dict[str, str]]
|
||||
target_industries: List[str]
|
||||
delivery_model: str
|
||||
overlap_score: int
|
||||
differentiators: List[str]
|
||||
evidence: List[Dict[str, str]]
|
||||
|
||||
class FetchStep5DataSilverBulletsRequest(BaseModel):
|
||||
company: CompanyModel
|
||||
analyses: List[AnalysisModel]
|
||||
language: str
|
||||
|
||||
class SilverBulletModel(BaseModel):
|
||||
competitor_name: str
|
||||
statement: str
|
||||
|
||||
class FetchStep6DataConclusionRequest(BaseModel):
|
||||
company: CompanyModel
|
||||
products: List[ProductModel]
|
||||
industries: List[TargetIndustryModel]
|
||||
analyses: List[AnalysisModel]
|
||||
silver_bullets: List[SilverBulletModel]
|
||||
language: str
|
||||
|
||||
class FetchStep7DataBattlecardsRequest(BaseModel):
|
||||
company: CompanyModel
|
||||
analyses: List[AnalysisModel]
|
||||
silver_bullets: List[SilverBulletModel]
|
||||
language: str
|
||||
|
||||
class ShortlistedCompetitorModel(BaseModel):
|
||||
name: str
|
||||
url: str
|
||||
|
||||
class FetchStep8DataReferenceAnalysisRequest(BaseModel):
|
||||
competitors: List[ShortlistedCompetitorModel]
|
||||
language: str
|
||||
|
||||
|
||||
# --- Endpoints ---
|
||||
@app.post("/api/fetchProductDetails")
|
||||
async def fetch_product_details(request: ProductDetailsRequest):
|
||||
prompts = {
|
||||
"de": f"""
|
||||
Analysiere die Webseite {request.url} und beschreibe den Zweck des Produkts "{request.name}" in 1-2 Sätzen. Gib auch die genaue URL und ein relevantes Snippet als Beleg an.
|
||||
Das "name" Feld im JSON soll der offizielle Produktname sein, wie er auf der Seite gefunden wird, oder "{request.name}" falls nicht eindeutig.
|
||||
Antworte ausschließlich im JSON-Format.
|
||||
""",
|
||||
"en": f"""
|
||||
Analyze the website {request.url} and describe the purpose of the product "{request.name}" in 1-2 sentences. Also provide the exact URL and a relevant snippet as evidence.
|
||||
The "name" field in the JSON should be the official product name as found on the page, or "{request.name}" if not clearly stated.
|
||||
Respond exclusively in JSON format.
|
||||
"""
|
||||
}
|
||||
|
||||
try:
|
||||
response = await model.generate_content_async(
|
||||
prompts[request.language],
|
||||
generation_config=genai.GenerationConfig(
|
||||
response_mime_type="application/json",
|
||||
response_schema=product_schema
|
||||
),
|
||||
safety_settings={
|
||||
HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
},
|
||||
)
|
||||
return parse_json_response(response.text)
|
||||
except Exception as e:
|
||||
print(f"Error in fetch_product_details: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@app.post("/api/fetchStep1Data")
|
||||
async def fetch_step1_data(request: FetchStep1DataRequest):
|
||||
prompts = {
|
||||
"de": f"""
|
||||
Rolle: Research-Agent für B2B-Software-Wettbewerbsanalyse.
|
||||
Aufgabe: Analysiere die Website {request.start_url} und identifiziere die Hauptprodukte/Lösungen und deren Zielbranchen.
|
||||
Regeln:
|
||||
1. Konzentriere dich auf offizielle Produkt- und Lösungsseiten.
|
||||
2. Jede Information (Produkt, Branche) muss mit einer URL und einem kurzen Snippet belegt werden.
|
||||
3. Sei präzise und vermeide Spekulationen.
|
||||
Antworte ausschließlich im JSON-Format.
|
||||
""",
|
||||
"en": f"""
|
||||
Role: Research Agent for B2B Software Competitor Analysis.
|
||||
Task: Analyze the website {request.start_url} and identify the main products/solutions and their target industries.
|
||||
Rules:
|
||||
1. Focus on official product and solution pages.
|
||||
2. Every piece of information (product, industry) must be backed by a URL and a short snippet as evidence.
|
||||
3. Be precise and avoid speculation.
|
||||
Respond exclusively in JSON format.
|
||||
"""
|
||||
}
|
||||
|
||||
response_schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"products": {"type": "array", "items": product_schema},
|
||||
"target_industries": {"type": "array", "items": industry_schema},
|
||||
},
|
||||
"required": ['products', 'target_industries']
|
||||
}
|
||||
|
||||
try:
|
||||
response = await model.generate_content_async(
|
||||
prompts[request.language],
|
||||
generation_config=genai.GenerationConfig(
|
||||
response_mime_type="application/json",
|
||||
response_schema=response_schema
|
||||
),
|
||||
safety_settings={
|
||||
HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
},
|
||||
)
|
||||
return parse_json_response(response.text)
|
||||
except Exception as e:
|
||||
print(f"Error in fetch_step1_data: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@app.post("/api/fetchStep2Data")
|
||||
async def fetch_step2_data(request: FetchStep2DataRequest):
|
||||
prompts = {
|
||||
"de": f"""
|
||||
Rolle: Research-Agent.
|
||||
Aufgabe: Leite aus den folgenden Produkt- und Brancheninformationen 10-25 präzise deutsche und englische Keywords/Suchphrasen für die Wettbewerbsrecherche ab.
|
||||
Kontext:
|
||||
Produkte: {', '.join([f'{p.name} ({p.purpose})' for p in request.products])}
|
||||
Branchen: {', '.join([i.name for i in request.industries])}
|
||||
Regeln:
|
||||
1. Erstelle Cluster: Produktkategorie, Funktionskern, Zielbranchen, Synonyme/Englischvarianten.
|
||||
2. Gib für jedes Keyword eine kurze Begründung ("rationale").
|
||||
3. Antworte ausschließlich im JSON-Format.
|
||||
""",
|
||||
"en": f"""
|
||||
Role: Research Agent.
|
||||
Task: From the following product and industry information, derive 10-25 precise English keywords/search phrases for competitor research.
|
||||
Context:
|
||||
Products: {', '.join([f'{p.name} ({p.purpose})' for p in request.products])}
|
||||
Industries: {', '.join([i.name for i in request.industries])}
|
||||
Rules:
|
||||
1. Create clusters: Product category, core function, target industries, synonyms.
|
||||
2. Provide a brief rationale for each keyword.
|
||||
3. Respond exclusively in JSON format.
|
||||
"""
|
||||
}
|
||||
|
||||
response_schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"keywords": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"term": {"type": "string"},
|
||||
"rationale": {"type": "string"}
|
||||
},
|
||||
"required": ['term', 'rationale']
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ['keywords']
|
||||
}
|
||||
try:
|
||||
response = await model.generate_content_async(
|
||||
prompts[request.language],
|
||||
generation_config=genai.GenerationConfig(
|
||||
response_mime_type="application/json",
|
||||
response_schema=response_schema
|
||||
),
|
||||
safety_settings={
|
||||
HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
},
|
||||
)
|
||||
return parse_json_response(response.text)
|
||||
except Exception as e:
|
||||
print(f"Error in fetch_step2_data: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@app.post("/api/fetchStep3Data")
|
||||
async def fetch_step3_data(request: FetchStep3DataRequest):
|
||||
prompts = {
|
||||
"de": f"""
|
||||
Rolle: Research-Agent.
|
||||
Aufgabe: Finde relevante Wettbewerber basierend auf den folgenden Keywords. Fokussiere dich auf den Markt: {request.market_scope}.
|
||||
Keywords: {', '.join([k.term for k in request.keywords])}
|
||||
Regeln:
|
||||
1. Suche nach Software-Anbietern, nicht nach Resellern, Beratungen oder Implementierungspartnern.
|
||||
2. Gib für jeden Kandidaten an: Name, URL, Eignungsbegründung (why), Confidence-Score (0.0-1.0) und Belege (URL+Snippet).
|
||||
3. Antworte ausschließlich im JSON-Format.
|
||||
""",
|
||||
"en": f"""
|
||||
Role: Research Agent.
|
||||
Task: Find relevant competitors based on the following keywords. Focus on the market: {request.market_scope}.
|
||||
Keywords: {', '.join([k.term for k in request.keywords])}
|
||||
Rules:
|
||||
1. Search for software vendors, not resellers, consultants, or implementation partners.
|
||||
2. For each candidate, provide: Name, URL, justification for inclusion (why), confidence score (0.0-1.0), and evidence (URL+snippet).
|
||||
3. Respond exclusively in JSON format.
|
||||
"""
|
||||
}
|
||||
|
||||
response_schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"competitor_candidates": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"name": {"type": "string"},
|
||||
"url": {"type": "string"},
|
||||
"confidence": {"type": "number"},
|
||||
"why": {"type": "string"},
|
||||
"evidence": {"type": "array", "items": evidence_schema}
|
||||
},
|
||||
"required": ['name', 'url', 'confidence', 'why', 'evidence']
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ['competitor_candidates']
|
||||
}
|
||||
try:
|
||||
response = await model.generate_content_async(
|
||||
prompts[request.language],
|
||||
generation_config=genai.GenerationConfig(
|
||||
response_mime_type="application/json",
|
||||
response_schema=response_schema
|
||||
),
|
||||
safety_settings={
|
||||
HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
},
|
||||
)
|
||||
return parse_json_response(response.text)
|
||||
except Exception as e:
|
||||
print(f"Error in fetch_step3_data: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@app.post("/api/fetchStep4Data")
|
||||
async def fetch_step4_data(request: FetchStep4DataRequest):
|
||||
competitors_summary = '\n'.join([f'- {c.name}: {c.url}' for c in request.competitors])
|
||||
prompts = {
|
||||
"de": f"""
|
||||
Rolle: Research-Agent.
|
||||
Aufgabe: Führe eine detaillierte Portfolio- & Positionierungsanalyse für jeden der folgenden Wettbewerber durch. Vergleiche sie mit dem Ausgangsunternehmen {request.company.name} ({request.company.start_url}).
|
||||
Wettbewerber:
|
||||
{competitors_summary}
|
||||
Analyse-Punkte pro Wettbewerber:
|
||||
1. portfolio: Kernprodukte (max. 5) mit kurzem Zweck.
|
||||
2. target_industries: Hauptzielbranchen.
|
||||
3. delivery_model: Geschäfts-/Bereitstellungsmodell (z.B. SaaS, On-Premise), falls ersichtlich.
|
||||
4. overlap_score: 0-100, basierend auf Produktfunktion, Zielbranche, Terminologie im Vergleich zum Ausgangsunternehmen.
|
||||
5. differentiators: 3-5 Bulletpoints zu Alleinstellungsmerkmalen oder Unterschieden.
|
||||
6. evidence: Wichtige Beleg-URLs mit Snippets.
|
||||
Regeln:
|
||||
1. Jede Behauptung mit Quellen belegen.
|
||||
2. Antworte ausschließlich im JSON-Format.
|
||||
""",
|
||||
"en": f"""
|
||||
Role: Research Agent.
|
||||
Task: Conduct a detailed portfolio & positioning analysis for each of the following competitors. Compare them with the initial company {request.company.name} ({request.company.start_url}).
|
||||
Competitors:
|
||||
{competitors_summary}
|
||||
Analysis points per competitor:
|
||||
1. portfolio: Core products (max 5) with a brief purpose.
|
||||
2. target_industries: Main target industries.
|
||||
3. delivery_model: Business/delivery model (e.g., SaaS, On-Premise), if apparent.
|
||||
4. overlap_score: 0-100, based on product function, target industry, terminology compared to the initial company.
|
||||
5. differentiators: 3-5 bullet points on unique selling points or differences.
|
||||
6. evidence: Key supporting URLs with snippets.
|
||||
Rules:
|
||||
1. Back up every claim with sources.
|
||||
2. Respond exclusively in JSON format.
|
||||
"""
|
||||
}
|
||||
|
||||
response_schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"analyses": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"competitor": {"type": "object", "properties": {"name": {"type": "string"}, "url": {"type": "string"}}}
|
||||
"portfolio": {"type": "array", "items": {"type": "object", "properties": {"product": {"type": "string"}, "purpose": {"type": "string"}}}}
|
||||
"target_industries": {"type": "array", "items": {"type": "string"}},
|
||||
"delivery_model": {"type": "string"},
|
||||
"overlap_score": {"type": "integer"},
|
||||
"differentiators": {"type": "array", "items": {"type": "string"}},
|
||||
"evidence": {"type": "array", "items": evidence_schema}
|
||||
},
|
||||
"required": ['competitor', 'portfolio', 'target_industries', 'delivery_model', 'overlap_score', 'differentiators', 'evidence']
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ['analyses']
|
||||
}
|
||||
try:
|
||||
response = await model.generate_content_async(
|
||||
prompts[request.language],
|
||||
generation_config=genai.GenerationConfig(
|
||||
response_mime_type="application/json",
|
||||
response_schema=response_schema
|
||||
),
|
||||
safety_settings={
|
||||
HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
},
|
||||
)
|
||||
return parse_json_response(response.text)
|
||||
except Exception as e:
|
||||
print(f"Error in fetch_step4_data: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@app.post("/api/fetchStep5Data_SilverBullets")
|
||||
async def fetch_step5_data_silver_bullets(request: FetchStep5DataSilverBulletsRequest):
|
||||
competitor_data_summary = '\n'.join([
|
||||
f"- Competitor: {a.competitor['name']}\n - Portfolio Focus: {', '.join([p['product'] for p in a.portfolio]) or 'N/A'}\n - Differentiators: {'; '.join(a.differentiators)}"
|
||||
for a in request.analyses
|
||||
])
|
||||
|
||||
prompts = {
|
||||
"de": f"""
|
||||
Rolle: Strategieberater.
|
||||
Aufgabe: Erstelle für das Unternehmen "{request.company.name}" eine "Silver Bullet" für jeden Wettbewerber. Eine "Silver Bullet" ist ein prägnanter Satz (max. 25 Wörter), der im Vertriebsgespräch genutzt werden kann, um sich vom jeweiligen Wettbewerber abzugrenzen.
|
||||
Kontext: {request.company.name} wird mit den folgenden Wettbewerbern verglichen:
|
||||
{competitor_data_summary.replace("Competitor:", "Wettbewerber:").replace("Portfolio Focus:", "Portfolio-Fokus:").replace("Differentiators:", "Alleinstellungsmerkmale:")}
|
||||
|
||||
Regeln:
|
||||
1. Formuliere für JEDEN Wettbewerber einen einzigen, schlagkräftigen Satz.
|
||||
2. Der Satz soll eine Schwäche des Wettbewerbers oder eine Stärke von {request.company.name} im direkten Vergleich hervorheben.
|
||||
3. Sei prägnant und überzeugend.
|
||||
4. Antworte ausschließlich im JSON-Format.
|
||||
""",
|
||||
"en": f"""
|
||||
Role: Strategy Consultant.
|
||||
Task: Create a "Silver Bullet" for the company "{request.company.name}" for each competitor. A "Silver Bullet" is a concise sentence (max 25 words) that can be used in a sales pitch to differentiate from the respective competitor.
|
||||
Context: {request.company.name} is being compared with the following competitors:
|
||||
{competitor_data_summary}
|
||||
|
||||
Rules:
|
||||
1. Formulate a single, powerful sentence for EACH competitor.
|
||||
2. The sentence should highlight a weakness of the competitor or a strength of {request.company.name} in direct comparison.
|
||||
3. Be concise and persuasive.
|
||||
4. Respond exclusively in JSON format.
|
||||
"""
|
||||
}
|
||||
|
||||
response_schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"silver_bullets": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"competitor_name": {"type": "string"},
|
||||
"statement": {"type": "string"}
|
||||
},
|
||||
"required": ['competitor_name', 'statement']
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ['silver_bullets']
|
||||
}
|
||||
|
||||
try:
|
||||
response = await model.generate_content_async(
|
||||
prompts[request.language],
|
||||
generation_config=genai.GenerationConfig(
|
||||
response_mime_type="application/json",
|
||||
response_schema=response_schema
|
||||
),
|
||||
safety_settings={
|
||||
HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
},
|
||||
)
|
||||
return parse_json_response(response.text)
|
||||
except Exception as e:
|
||||
print(f"Error in fetch_step5_data_silver_bullets: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@app.post("/api/fetchStep6Data_Conclusion")
|
||||
async def fetch_step6_data_conclusion(request: FetchStep6DataConclusionRequest):
|
||||
competitor_data_summary = '\n\n'.join([
|
||||
f"- Competitor: {a.competitor['name']}\n - Portfolio: {', '.join([p['product'] for p in a.portfolio]) or 'N/A'}\n - Target Industries: {', '.join(a.target_industries) or 'N/A'}\n - Overlap Score: {a.overlap_score}\n - Differentiators: {'; '.join(a.differentiators)}"
|
||||
for a in request.analyses
|
||||
])
|
||||
|
||||
silver_bullets_summary = '\n'.join([f"- Gegen {sb.competitor_name}: \"{sb.statement}\"" for sb in request.silver_bullets])
|
||||
if request.language == 'en':
|
||||
silver_bullets_summary = '\n'.join([f"- Against {sb.competitor_name}: \"{sb.statement}\"" for sb in request.silver_bullets])
|
||||
|
||||
prompts = {
|
||||
"de": """
|
||||
Rolle: Research-Agent.
|
||||
Aufgabe: Erstelle ein Fazit der Wettbewerbsanalyse für {company_name}.
|
||||
|
||||
Ausgangsunternehmen ({company_name}) Daten:
|
||||
- Produkte: {products_summary}
|
||||
- Branchen: {industries_summary}
|
||||
|
||||
Zusammengefasste Wettbewerber-Daten:
|
||||
{competitor_data_summary_de}
|
||||
|
||||
Strategische Positionierung ("Silver Bullets"):
|
||||
{silver_bullets_summary_de}
|
||||
|
||||
Erstelle:
|
||||
1. product_matrix: Analysiere ALLE Produkte von {company_name} und den Wettbewerbern. Identifiziere 5-10 generische Produktkategorien oder Kernfunktionalitäten (z.B. "Mobile Lösung", "Disposition & Planung", "Asset Management"). Erstelle dann eine Matrix basierend auf diesen generischen Kategorien. Jedes Element im Array repräsentiert eine dieser Kategorien. Jedes Element hat ein "product" (string, der Name der generischen Kategorie) und ein "availability" (Array). Das "availability"-Array enthält Objekte mit "competitor" (string) und "has_offering" (boolean), für JEDEN Anbieter (inkl. {company_name}), das anzeigt, ob der Anbieter eine Lösung in dieser Kategorie hat.
|
||||
2. industry_matrix: Ein Array. Jedes Element repräsentiert eine Branche (von ALLEN Anbietern, inkl. {company_name}). Jedes Element hat eine "industry" (string) und ein "availability" (Array). Das "availability"-Array enthält Objekte mit "competitor" (string) und "has_offering" (boolean), für JEDEN Anbieter (inkl. {company_name}).
|
||||
3. overlap_scores: Eine Liste der Wettbewerber und ihrer Overlap-Scores.
|
||||
4. summary: Eine knappe Einordnung (2-3 Sätze), wer sich worauf positioniert.
|
||||
5. opportunities: Wo liegen Lücken oder Chancen für {company_name}?
|
||||
6. next_questions: Max. 5 offene Fragen oder nächste Schritte für den User.
|
||||
Regeln:
|
||||
1. Antworte ausschließlich im JSON-Format gemäß dem vorgegebenen Schema.
|
||||
".format(
|
||||
company_name=request.company.name,
|
||||
products_summary=', '.join([p.name for p in request.products]),
|
||||
industries_summary=', '.join([i.name for i in request.industries]),
|
||||
competitor_data_summary_de=competitor_data_summary.replace("Competitor:", "Wettbewerber:").replace("Portfolio:", "Portfolio:").replace("Target Industries:", "Zielbranchen:").replace("Overlap Score:", "Overlap Score:").replace("Differentiators:", "Alleinstellungsmerkmale:"),
|
||||
silver_bullets_summary_de=silver_bullets_summary
|
||||
),
|
||||
"en": """
|
||||
Role: Research Agent.
|
||||
Task: Create a conclusion for the competitive analysis for {company_name}.
|
||||
|
||||
Initial Company ({company_name}) Data:
|
||||
- Products: {products_summary}
|
||||
- Industries: {industries_summary}
|
||||
|
||||
Summarized Competitor Data:
|
||||
{competitor_data_summary_en}
|
||||
|
||||
Strategic Positioning ("Silver Bullets"):
|
||||
{silver_bullets_summary_en}
|
||||
|
||||
Create:
|
||||
1. product_matrix: Analyze ALL products from {company_name} and the competitors. Identify 5-10 generic product categories or core functionalities (e.g., "Mobile Solution", "Dispatch & Planning", "Asset Management"). Then create a matrix based on these generic categories. Each element in the array represents one of these categories. Each element has a "product" (string, the name of the generic category) and an "availability" (array). The "availability"-array contains objects with "competitor" (string) and "has_offering" (boolean), for EVERY provider (incl. {company_name}), indicating if the provider has a solution in this category.
|
||||
2. industry_matrix: An array. Each element represents an industry (from ALL providers, incl. {company_name}). Each element has an "industry" (string) and an "availability" (array). The "availability"-array contains objects with "competitor" (string) and "has_offering" (boolean), for EVERY provider (incl. {company_name}).
|
||||
3. overlap_scores: A list of competitors and their overlap scores.
|
||||
4. summary: A brief assessment (2-3 sentences) of who is positioned where.
|
||||
5. opportunities: Where are the gaps or opportunities for {company_name}?
|
||||
6. next_questions: Max 5 open questions or next steps for the user.
|
||||
Rules:
|
||||
1. Respond exclusively in JSON format according to the provided schema.
|
||||
".format(
|
||||
company_name=request.company.name,
|
||||
products_summary=', '.join([p.name for p in request.products]),
|
||||
industries_summary=', '.join([i.name for i in request.industries]),
|
||||
competitor_data_summary_en=competitor_data_summary,
|
||||
silver_bullets_summary_en=silver_bullets_summary
|
||||
)
|
||||
}
|
||||
|
||||
response_schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"conclusion": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"product_matrix": {
|
||||
"type": "array",
|
||||
"description": "Array representing a feature-based product comparison. Each item is a generic product category or core functionality.",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"product": {"type": "string", "description": "Name of the generic product category/feature."},
|
||||
"availability": {
|
||||
"type": "array",
|
||||
"description": "Which competitors offer this product.",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"competitor": {"type": "string"},
|
||||
"has_offering": {"type": "boolean", "description": "True if the competitor has a similar offering."}
|
||||
},
|
||||
"required": ['competitor', 'has_offering']
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ['product', 'availability']
|
||||
}
|
||||
},
|
||||
"industry_matrix": {
|
||||
"type": "array",
|
||||
"description": "Array representing industry comparison. Each item is an industry.",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"industry": {"type": "string", "description": "Name of the industry."},
|
||||
"availability": {
|
||||
"type": "array",
|
||||
"description": "Which competitors serve this industry.",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"competitor": {"type": "string"},
|
||||
"has_offering": {"type": "boolean", "description": "True if the competitor serves this industry."}
|
||||
},
|
||||
"required": ['competitor', 'has_offering']
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ['industry', 'availability']
|
||||
}
|
||||
},
|
||||
"overlap_scores": {"type": "array", "items": {"type": "object", "properties": {"competitor": {"type": "string"}, "score": {"type": "number"}}}},
|
||||
"summary": {"type": "string"},
|
||||
"opportunities": {"type": "string"},
|
||||
"next_questions": {"type": "array", "items": {"type": "string"}}
|
||||
},
|
||||
"required": ['product_matrix', 'industry_matrix', 'overlap_scores', 'summary', 'opportunities', 'next_questions']
|
||||
}
|
||||
},
|
||||
"required": ['conclusion']
|
||||
}
|
||||
|
||||
try:
|
||||
response = await model.generate_content_async(
|
||||
prompts[request.language],
|
||||
generation_config=genai.GenerationConfig(
|
||||
response_mime_type="application/json",
|
||||
response_schema=response_schema
|
||||
),
|
||||
safety_settings={
|
||||
HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
},
|
||||
)
|
||||
return parse_json_response(response.text)
|
||||
except Exception as e:
|
||||
print(f"Error in fetch_step6_data_conclusion: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@app.post("/api/fetchStep7Data_Battlecards")
|
||||
async def fetch_step7_data_battlecards(request: FetchStep7DataBattlecardsRequest):
|
||||
competitor_data_summary = '\n\n'.join([
|
||||
f"- Competitor: {a.competitor['name']}\n - Portfolio Focus: {', '.join([p['product'] for p in a.portfolio]) or 'N/A'}\n - Target Industries: {', '.join(a.target_industries)}\n - Differentiators: {'; '.join(a.differentiators)}\n - Silver Bullet against this competitor: \"{next((sb.statement for sb in request.silver_bullets if sb.competitor_name == a.competitor['name']), 'Not found.')}\""
|
||||
for a in request.analyses
|
||||
])
|
||||
|
||||
prompts = {
|
||||
"de": f"""
|
||||
Rolle: Vertriebsstratege und Coach für das B2B-Softwareunternehmen "{request.company.name}".
|
||||
Aufgabe: Erstelle für jeden der folgenden Wettbewerber eine detaillierte "Sales Battlecard". Diese Battlecard soll dem Vertriebsteam konkrete, handlungsorientierte Argumente für Kundengespräche an die Hand geben.
|
||||
|
||||
Informationen über das eigene Unternehmen: {request.company.name}
|
||||
Detaillierte Analyse der Wettbewerber:
|
||||
{competitor_data_summary.replace("Competitor:", "Wettbewerber:").replace("Portfolio Focus:", "Portfolio-Fokus:").replace("Target Industries:", "Zielbranchen:").replace("Differentiators:", "Alleinstellungsmerkmale:").replace("Silver Bullet against this competitor:", "Silver Bullet gegen diesen Wettbewerber:")}
|
||||
|
||||
Für JEDEN Wettbewerber, erstelle die folgenden Sektionen einer Battlecard im JSON-Format:
|
||||
1. **competitor_name**: Der Name des Wettbewerbers.
|
||||
2. **competitor_profile**:
|
||||
* **focus**: Fasse den Kernfokus des Wettbewerbers (Produkte & Branchen) in einem Satz zusammen.
|
||||
* **positioning**: Beschreibe die Kernpositionierung des Wettbewerbers in 1-2 Sätzen.
|
||||
3. **strengths_vs_weaknesses**: Formuliere 3-4 prägnante Stichpunkte. Jeder Stichpunkt soll eine Stärke von "{request.company.name}" einer vermuteten Schwäche des Wettbewerbers gegenüberstellen. Beginne die Sätze z.B. mit "Während [Wettbewerber]..., bieten wir...".
|
||||
4. **landmine_questions**: Formuliere 3-5 intelligente, offene "Landminen"-Fragen, die ein Vertriebsmitarbeiter einem potenziellen Kunden stellen kann. Diese Fragen sollen die Schwächen des Wettbewerbers aufdecken oder die Stärken von "{request.company.name}" betonen, ohne den Wettbewerber direkt anzugreifen.
|
||||
5. **silver_bullet**: Übernimm die bereits formulierte "Silver Bullet" für diesen Wettbewerber.
|
||||
|
||||
Regeln:
|
||||
- Sei präzise, überzeugend und nutze eine aktive, vertriebsorientierte Sprache.
|
||||
- Die "landmine_questions" müssen so formuliert sein, dass sie den Kunden zum Nachdenken anregen und ihn in Richtung der Vorteile von "{request.company.name}" lenken.
|
||||
- Antworte ausschließlich im JSON-Format gemäß dem vorgegebenen Schema für ein Array von Battlecards.
|
||||
",
|
||||
"en": f"""
|
||||
Role: Sales Strategist and Coach for the B2B software company "{request.company.name}".
|
||||
Task: Create a detailed "Sales Battlecard" for each of the following competitors. This battlecard should provide the sales team with concrete, actionable arguments for customer conversations.
|
||||
|
||||
Information about our own company: {request.company.name}
|
||||
Detailed analysis of competitors:
|
||||
{competitor_data_summary}
|
||||
|
||||
For EACH competitor, create the following sections of a battlecard in JSON format:
|
||||
1. **competitor_name**: The name of the competitor.
|
||||
2. **competitor_profile**:
|
||||
* **focus**: Summarize the competitor's core focus (products & industries) in one sentence.
|
||||
* **positioning**: Describe the competitor's core positioning in 1-2 sentences.
|
||||
3. **strengths_vs_weaknesses**: Formulate 3-4 concise bullet points. Each point should contrast a strength of "{request.company.name}" with a presumed weakness of the competitor. Start sentences with, for example, "While [Competitor]..., we offer...".
|
||||
4. **landmine_questions**: Formulate 3-5 intelligent, open-ended "landmine" questions that a sales representative can ask a potential customer. These questions should uncover the competitor's weaknesses or emphasize the strengths of "{request.company.name}" without attacking the competitor directly.
|
||||
5. **silver_bullet**: Use the "Silver Bullet" already formulated for this competitor.
|
||||
|
||||
Rules:
|
||||
- Be precise, persuasive, and use active, sales-oriented language.
|
||||
- The "landmine_questions" must be formulated to make the customer think and guide them towards the advantages of "{request.company.name}".
|
||||
- Respond exclusively in JSON format according to the specified schema for an array of battlecards.
|
||||
"
|
||||
}
|
||||
|
||||
|
||||
response_schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"battlecards": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"competitor_name": {"type": "string"},
|
||||
"competitor_profile": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"focus": {"type": "string"},
|
||||
"positioning": {"type": "string"}
|
||||
},
|
||||
"required": ['focus', 'positioning']
|
||||
},
|
||||
"strengths_vs_weaknesses": {"type": "array", "items": {"type": "string"}},
|
||||
"landmine_questions": {"type": "array", "items": {"type": "string"}},
|
||||
"silver_bullet": {"type": "string"}
|
||||
},
|
||||
"required": ['competitor_name', 'competitor_profile', 'strengths_vs_weaknesses', 'landmine_questions', 'silver_bullet']
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ['battlecards']
|
||||
}
|
||||
|
||||
try:
|
||||
response = await model.generate_content_async(
|
||||
prompts[request.language],
|
||||
generation_config=genai.GenerationConfig(
|
||||
response_mime_type="application/json",
|
||||
response_schema=response_schema
|
||||
),
|
||||
safety_settings={
|
||||
HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
},
|
||||
)
|
||||
return parse_json_response(response.text)
|
||||
except Exception as e:
|
||||
print(f"Error in fetch_step7_data_battlecards: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@app.post("/api/fetchStep8Data_ReferenceAnalysis")
|
||||
async def fetch_step8_data_reference_analysis(request: FetchStep8DataReferenceAnalysisRequest):
|
||||
competitors_summary = '\n'.join([f'- {c.name}: {c.url}' for c in request.competitors])
|
||||
|
||||
prompts = {
|
||||
"de": """
|
||||
Rolle: Faktentreuer Research-Agent. Deine Antworten MÜSSEN ausschließlich auf den Ergebnissen der von dir durchgeführten Websuche basieren.
|
||||
Aufgabe: Führe für jeden der folgenden Wettbewerber eine Websuche durch, um deren offizielle Referenzkunden, Case Studies oder Success Stories zu finden.
|
||||
Wettbewerber:
|
||||
{competitors_summary_de}
|
||||
|
||||
ABLAUF FÜR JEDEN WETTBEWERBER:
|
||||
1. **SUCHE**: Führe eine gezielte Suche durch mit Phrasen wie "[Wettbewerber-Name] Referenzen", "[Wettbewerber-Name] Case Studies", "[Wettbewerber-Name] Kunden".
|
||||
2. **VALIDIERUNG**: Analysiere die Suchergebnisse. Konzentriere dich AUSSCHLIESSLICH auf Links, die zur offiziellen Domain des Wettbewerbers gehören (z.B. `wettbewerber.com/referenzen`). Ignoriere Pressemitteilungen auf Drittseiten, Partnerlisten oder Nachrichtenartikel.
|
||||
3. **EXTRAKTION**: Extrahiere die geforderten Informationen NUR von diesen validierten, offiziellen Seiten.
|
||||
|
||||
SEHR WICHTIGE REGELN ZUR VERMEIDUNG VON FALSCHINFORMATIONEN:
|
||||
- **NUR GEFUNDENE DATEN**: Gib NUR Kunden an, für die du eine dedizierte Case-Study-Seite oder einen klaren Testimonial-Abschnitt auf der OFFIZIELLEN Website des Wettbewerbers gefunden hast.
|
||||
- **KEINE HALLUZINATION**: Erfinde KEINE Kunden, Branchen oder Zitate. Wenn du für einen Wettbewerber absolut nichts findest, gib ein leeres "references" Array zurück. Dies ist besser als falsche Informationen.
|
||||
- **DIREKTER LINK**: Die 'case_study_url' MUSS der exakte, funktionierende Link zur Seite sein, auf der die Informationen gefunden wurden.
|
||||
|
||||
Antworte AUSSCHLIESSLICH im JSON-Format, eingeschlossen in einem Markdown-Codeblock.
|
||||
Extrahiere für JEDEN GEFUNDENEN UND VERIFIZIERTEN Referenzkunden (max. 5 pro Wettbewerber) die geforderten Felder.
|
||||
".format(
|
||||
competitors_summary_de=competitors_summary
|
||||
),
|
||||
"en": """
|
||||
Role: Fact-based Research Agent. Your answers MUST be based solely on the results of the web search you perform.
|
||||
Task: For each of the following competitors, conduct a web search to find their official reference customers, case studies, or success stories.
|
||||
Competitors:
|
||||
{competitors_summary_en}
|
||||
|
||||
PROCESS FOR EACH COMPETITOR:
|
||||
1. **SEARCH**: Conduct a targeted search with phrases like "[Competitor Name] references", "[Competitor Name] case studies", "[Competitor Name] customers".
|
||||
2. **VALIDATION**: Analyze the search results. Focus EXCLUSIVELY on links that belong to the competitor's official domain (e.g., `competitor.com/references`). Ignore press releases on third-party sites, partner lists, or news articles.
|
||||
3. **EXTRACTION**: Extract the required information ONLY from these validated, official pages.
|
||||
|
||||
VERY IMPORTANT RULES TO AVOID MISINFORMATION:
|
||||
- **ONLY FOUND DATA**: ONLY list customers for whom you have found a dedicated case study page or a clear testimonial section on the OFFICIAL website of the competitor.
|
||||
- **NO HALLUCINATION**: DO NOT invent customers, industries, or quotes. If you find absolutely nothing for a competitor, return an empty "references" array. This is better than false information.
|
||||
- **DIRECT LINK**: The 'case_study_url' MUST be the exact, working link to the page where the information was found.
|
||||
|
||||
Respond EXCLUSIVELY in JSON format, enclosed in a markdown code block.
|
||||
For EACH FOUND AND VERIFIED reference customer (max 5 per competitor), extract the required fields.
|
||||
".format(
|
||||
competitors_summary_en=competitors_summary
|
||||
)
|
||||
}
|
||||
|
||||
response_schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"reference_analysis": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"competitor_name": {"type": "string"},
|
||||
"references": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"name": {"type": "string"},
|
||||
"industry": {"type": "string"},
|
||||
"testimonial_snippet": {"type": "string"},
|
||||
"case_study_url": {"type": "string"}
|
||||
},
|
||||
"required": ["name", "industry", "testimonial_snippet", "case_study_url"]
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ["competitor_name", "references"]
|
||||
}
|
||||
}
|
||||
},
|
||||
"required": ['reference_analysis']
|
||||
}
|
||||
|
||||
try:
|
||||
response = await model.generate_content_async(
|
||||
prompts[request.language],
|
||||
generation_config=genai.GenerationConfig(
|
||||
response_mime_type="application/json",
|
||||
response_schema=response_schema
|
||||
),
|
||||
tools=[genai.types.Tool(google_search_retrieval=genai.types.GoogleSearchRetrieval())], # Correct way to enable search in Python SDK
|
||||
safety_settings={
|
||||
HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
|
||||
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
|
||||
},
|
||||
)
|
||||
grounding_metadata = [chunk.to_dict() for chunk in response.candidates[0].grounding_metadata.grounding_chunks] if response.candidates[0].grounding_metadata else []
|
||||
parsed_data = parse_json_response(response.text)
|
||||
return {**parsed_data, "groundingMetadata": grounding_metadata}
|
||||
except Exception as e:
|
||||
print(f"Error in fetch_step8_data_reference_analysis: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
# Mount static files AFTER all API routes
|
||||
if os.path.exists("dist"):
|
||||
app.mount("/", StaticFiles(directory="dist", html=True), name="static")
|
||||
|
||||
if __name__ == "__main__":
|
||||
import uvicorn
|
||||
uvicorn.run(app, host="0.0.0.0", port=8000)
|
||||
129
competitor-analysis-app/components/EditableCard.tsx
Normal file
129
competitor-analysis-app/components/EditableCard.tsx
Normal file
@@ -0,0 +1,129 @@
|
||||
import React, { useState } from 'react';
|
||||
|
||||
interface Item {
|
||||
[key: string]: any;
|
||||
}
|
||||
|
||||
interface FieldConfig {
|
||||
key: string;
|
||||
label: string;
|
||||
type: 'text' | 'textarea';
|
||||
}
|
||||
|
||||
interface EditableCardProps<T extends Item> {
|
||||
title: string;
|
||||
items: T[];
|
||||
onItemsChange: (items: T[]) => void;
|
||||
fieldConfigs: FieldConfig[];
|
||||
newItemTemplate: T;
|
||||
renderDisplay: (item: T, index: number) => React.ReactNode;
|
||||
showAddButton?: boolean;
|
||||
t: {
|
||||
add: string;
|
||||
cancel: string;
|
||||
save: string;
|
||||
}
|
||||
}
|
||||
|
||||
const PencilIcon = () => (
|
||||
<svg xmlns="http://www.w3.org/2000/svg" className="h-4 w-4" fill="none" viewBox="0 0 24 24" stroke="currentColor"><path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M15.232 5.232l3.536 3.536m-2.036-5.036a2.5 2.5 0 113.536 3.536L6.5 21.036H3v-3.5L14.732 3.732z" /></svg>
|
||||
);
|
||||
const TrashIcon = () => (
|
||||
<svg xmlns="http://www.w3.org/2000/svg" className="h-4 w-4" fill="none" viewBox="0 0 24 24" stroke="currentColor"><path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M19 7l-.867 12.142A2 2 0 0116.138 21H7.862a2 2 0 01-1.995-1.858L5 7m5 4v6m4-6v6m1-10V4a1 1 0 00-1-1h-4a1 1 0 00-1 1v3M4 7h16" /></svg>
|
||||
);
|
||||
|
||||
export const EditableCard = <T extends Item,>({ title, items, onItemsChange, fieldConfigs, newItemTemplate, renderDisplay, showAddButton, t }: EditableCardProps<T>) => {
|
||||
const [editingIndex, setEditingIndex] = useState<number | null>(null);
|
||||
const [editItem, setEditItem] = useState<T | null>(null);
|
||||
|
||||
const handleEdit = (index: number) => {
|
||||
setEditingIndex(index);
|
||||
setEditItem({ ...items[index] });
|
||||
};
|
||||
|
||||
const handleSave = () => {
|
||||
if (editingIndex !== null && editItem) {
|
||||
const newItems = [...items];
|
||||
newItems[editingIndex] = editItem;
|
||||
onItemsChange(newItems);
|
||||
setEditingIndex(null);
|
||||
setEditItem(null);
|
||||
}
|
||||
};
|
||||
|
||||
const handleCancel = () => {
|
||||
setEditingIndex(null);
|
||||
setEditItem(null);
|
||||
};
|
||||
|
||||
const handleRemove = (index: number) => {
|
||||
onItemsChange(items.filter((_, i) => i !== index));
|
||||
};
|
||||
|
||||
const handleAdd = () => {
|
||||
onItemsChange([...items, newItemTemplate]);
|
||||
setEditingIndex(items.length);
|
||||
setEditItem(newItemTemplate);
|
||||
};
|
||||
|
||||
const handleInputChange = (key: string, value: string) => {
|
||||
if (editItem) {
|
||||
setEditItem({ ...editItem, [key]: value });
|
||||
}
|
||||
};
|
||||
|
||||
const inputClasses = "w-full bg-light-secondary dark:bg-brand-secondary text-light-text dark:text-brand-text border border-light-accent dark:border-brand-accent rounded-md px-3 py-2 text-sm focus:outline-none focus:ring-2 focus:ring-brand-highlight";
|
||||
|
||||
return (
|
||||
<div className="bg-light-secondary dark:bg-brand-secondary p-6 rounded-lg shadow-lg mb-6 border border-light-accent dark:border-brand-accent">
|
||||
<div className="flex justify-between items-center mb-4">
|
||||
<h3 className="text-xl font-bold">{title}</h3>
|
||||
{(showAddButton ?? true) && (
|
||||
<button onClick={handleAdd} className="bg-brand-accent hover:bg-brand-light text-white font-bold py-1 px-3 rounded-md text-sm transition-colors">+ {t.add}</button>
|
||||
)}
|
||||
</div>
|
||||
<div className="space-y-4">
|
||||
{items.map((item, index) => (
|
||||
<div key={index} className="bg-light-primary dark:bg-brand-primary p-4 rounded-md">
|
||||
{editingIndex === index && editItem ? (
|
||||
<div className="space-y-3">
|
||||
{fieldConfigs.map(field => (
|
||||
<div key={field.key}>
|
||||
<label className="block text-sm font-medium text-light-subtle dark:text-brand-light mb-1">{field.label}</label>
|
||||
{field.type === 'textarea' ? (
|
||||
<textarea
|
||||
value={editItem[field.key]}
|
||||
onChange={(e) => handleInputChange(field.key, e.target.value)}
|
||||
className={inputClasses}
|
||||
rows={3}
|
||||
/>
|
||||
) : (
|
||||
<input
|
||||
type="text"
|
||||
value={editItem[field.key]}
|
||||
onChange={(e) => handleInputChange(field.key, e.target.value)}
|
||||
className={inputClasses}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
<div className="flex justify-end space-x-2 mt-2">
|
||||
<button onClick={handleCancel} className="bg-gray-500 hover:bg-gray-600 text-white py-1 px-3 rounded-md text-sm transition-colors">{t.cancel}</button>
|
||||
<button onClick={handleSave} className="bg-brand-highlight hover:bg-blue-600 text-white py-1 px-3 rounded-md text-sm transition-colors">{t.save}</button>
|
||||
</div>
|
||||
</div>
|
||||
) : (
|
||||
<div className="flex justify-between items-start">
|
||||
<div className="flex-grow">{renderDisplay(item, index)}</div>
|
||||
<div className="flex space-x-2 flex-shrink-0 ml-4">
|
||||
<button onClick={() => handleEdit(index)} className="text-light-subtle dark:text-brand-light hover:text-light-text dark:hover:text-white p-1 rounded-full transition-colors"><PencilIcon /></button>
|
||||
<button onClick={() => handleRemove(index)} className="text-light-subtle dark:text-brand-light hover:text-red-500 p-1 rounded-full transition-colors"><TrashIcon /></button>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
48
competitor-analysis-app/components/EvidencePopover.tsx
Normal file
48
competitor-analysis-app/components/EvidencePopover.tsx
Normal file
@@ -0,0 +1,48 @@
|
||||
import React, { useState } from 'react';
|
||||
import type { Evidence } from '../types';
|
||||
|
||||
interface EvidencePopoverProps {
|
||||
evidence: Evidence[];
|
||||
}
|
||||
|
||||
const EvidencePopover: React.FC<EvidencePopoverProps> = ({ evidence }) => {
|
||||
const [isOpen, setIsOpen] = useState(false);
|
||||
|
||||
if (!evidence || evidence.length === 0) {
|
||||
return null;
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="relative inline-block ml-2">
|
||||
<button
|
||||
onClick={(e) => { e.stopPropagation(); setIsOpen(!isOpen); }}
|
||||
onBlur={() => setIsOpen(false)}
|
||||
className="text-blue-500 dark:text-blue-400 hover:text-blue-600 dark:hover:text-blue-300 focus:outline-none"
|
||||
title="Show evidence"
|
||||
>
|
||||
<svg xmlns="http://www.w3.org/2000/svg" className="h-4 w-4" viewBox="0 0 20 20" fill="currentColor">
|
||||
<path fillRule="evenodd" d="M4 4a2 2 0 012-2h4.586A2 2 0 0112 2.586L15.414 6A2 2 0 0116 7.414V16a2 2 0 01-2 2H6a2 2 0 01-2-2V4zm2 6a1 1 0 011-1h6a1 1 0 110 2H7a1 1 0 01-1-1zm1 3a1 1 0 100 2h6a1 1 0 100-2H7z" clipRule="evenodd" />
|
||||
</svg>
|
||||
</button>
|
||||
{isOpen && (
|
||||
<div
|
||||
onMouseDown={(e) => e.stopPropagation()} // Prevents onBlur from closing popover when clicking inside
|
||||
className="absolute z-20 w-80 -right-2 mt-2 bg-light-secondary dark:bg-brand-secondary border border-light-accent dark:border-brand-accent rounded-lg shadow-xl p-3 text-sm">
|
||||
<h5 className="font-bold mb-2 text-light-text dark:text-white">Evidence</h5>
|
||||
<div className="space-y-2 max-h-60 overflow-y-auto">
|
||||
{evidence.map((e, index) => (
|
||||
<div key={index} className="border-t border-light-accent dark:border-brand-accent pt-2">
|
||||
<p className="italic text-light-subtle dark:text-brand-light">"{e.snippet}"</p>
|
||||
<a href={e.url} target="_blank" rel="noopener noreferrer" className="text-blue-500 dark:text-blue-400 hover:underline break-words">
|
||||
{e.url}
|
||||
</a>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default EvidencePopover;
|
||||
97
competitor-analysis-app/components/InputForm.tsx
Normal file
97
competitor-analysis-app/components/InputForm.tsx
Normal file
@@ -0,0 +1,97 @@
|
||||
import React, { useState } from 'react';
|
||||
import { translations } from '../translations';
|
||||
|
||||
interface InputFormProps {
|
||||
onStart: (startUrl: string, maxCompetitors: number, marketScope: string, language: 'de' | 'en') => void;
|
||||
}
|
||||
|
||||
const InputForm: React.FC<InputFormProps> = ({ onStart }) => {
|
||||
const [startUrl, setStartUrl] = useState('https://www.mobilexag.de');
|
||||
const [maxCompetitors, setMaxCompetitors] = useState(12);
|
||||
const [marketScope, setMarketScope] = useState('DACH');
|
||||
const [language, setLanguage] = useState<'de' | 'en'>('de');
|
||||
|
||||
const t = translations[language];
|
||||
|
||||
const handleSubmit = (e: React.FormEvent) => {
|
||||
e.preventDefault();
|
||||
onStart(startUrl, maxCompetitors, marketScope, language);
|
||||
};
|
||||
|
||||
const inputClasses = "w-full bg-light-primary dark:bg-brand-primary text-light-text dark:text-brand-text border border-light-accent dark:border-brand-accent rounded-lg px-3 py-2 focus:outline-none focus:ring-2 focus:ring-brand-highlight placeholder-light-subtle dark:placeholder-brand-light";
|
||||
|
||||
return (
|
||||
<div className="bg-light-secondary dark:bg-brand-secondary p-8 rounded-lg shadow-2xl max-w-2xl mx-auto">
|
||||
<h2 className="text-3xl font-bold mb-6 text-center">{t.inputForm.title}</h2>
|
||||
<p className="text-light-subtle dark:text-brand-light mb-8 text-center">{t.inputForm.subtitle}</p>
|
||||
<form onSubmit={handleSubmit} className="space-y-6">
|
||||
<div>
|
||||
<label htmlFor="start_url" className="block text-sm font-medium text-light-subtle dark:text-brand-light mb-2">{t.inputForm.startUrlLabel}</label>
|
||||
<input
|
||||
type="url"
|
||||
id="start_url"
|
||||
value={startUrl}
|
||||
onChange={(e) => setStartUrl(e.target.value)}
|
||||
className={inputClasses}
|
||||
placeholder="https://www.example-company.com"
|
||||
required
|
||||
/>
|
||||
</div>
|
||||
<div className="grid grid-cols-1 md:grid-cols-2 gap-6">
|
||||
<div>
|
||||
<label htmlFor="max_competitors" className="block text-sm font-medium text-light-subtle dark:text-brand-light mb-2">{t.inputForm.maxCompetitorsLabel}</label>
|
||||
<input
|
||||
type="number"
|
||||
id="max_competitors"
|
||||
value={maxCompetitors}
|
||||
onChange={(e) => setMaxCompetitors(parseInt(e.target.value, 10))}
|
||||
className={inputClasses}
|
||||
min="1"
|
||||
max="50"
|
||||
/>
|
||||
</div>
|
||||
<div>
|
||||
<label htmlFor="market_scope" className="block text-sm font-medium text-light-subtle dark:text-brand-light mb-2">{t.inputForm.marketScopeLabel}</label>
|
||||
<input
|
||||
type="text"
|
||||
id="market_scope"
|
||||
value={marketScope}
|
||||
onChange={(e) => setMarketScope(e.target.value)}
|
||||
className={inputClasses}
|
||||
placeholder={t.inputForm.marketScopePlaceholder}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
<div>
|
||||
<label className="block text-sm font-medium text-light-subtle dark:text-brand-light mb-2">{t.inputForm.languageLabel}</label>
|
||||
<div className="flex rounded-lg shadow-sm" role="group">
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => setLanguage('de')}
|
||||
className={`px-4 py-2 text-sm font-medium rounded-l-lg w-full transition-colors ${language === 'de' ? 'bg-brand-highlight text-white' : 'bg-light-primary dark:bg-brand-primary text-light-text dark:text-brand-text hover:bg-light-accent dark:hover:bg-brand-accent'}`}
|
||||
>
|
||||
Deutsch
|
||||
</button>
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => setLanguage('en')}
|
||||
className={`px-4 py-2 text-sm font-medium rounded-r-lg w-full transition-colors ${language === 'en' ? 'bg-brand-highlight text-white' : 'bg-light-primary dark:bg-brand-primary text-light-text dark:text-brand-text hover:bg-light-accent dark:hover:bg-brand-accent'}`}
|
||||
>
|
||||
English
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
<div className="pt-4">
|
||||
<button
|
||||
type="submit"
|
||||
className="w-full bg-brand-highlight hover:bg-blue-600 text-white font-bold py-3 px-4 rounded-lg shadow-lg transition duration-300 transform hover:scale-105"
|
||||
>
|
||||
{t.inputForm.submitButton}
|
||||
</button>
|
||||
</div>
|
||||
</form>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default InputForm;
|
||||
18
competitor-analysis-app/components/LoadingSpinner.tsx
Normal file
18
competitor-analysis-app/components/LoadingSpinner.tsx
Normal file
@@ -0,0 +1,18 @@
|
||||
import React from 'react';
|
||||
|
||||
interface LoadingSpinnerProps {
|
||||
t: {
|
||||
message: string;
|
||||
}
|
||||
}
|
||||
|
||||
const LoadingSpinner: React.FC<LoadingSpinnerProps> = ({ t }) => {
|
||||
return (
|
||||
<div className="flex flex-col items-center justify-center p-10">
|
||||
<div className="w-16 h-16 border-4 border-light-accent dark:border-brand-accent border-t-brand-highlight rounded-full animate-spin"></div>
|
||||
<p className="mt-4 text-light-subtle dark:text-brand-light">{t.message}</p>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default LoadingSpinner;
|
||||
131
competitor-analysis-app/components/Step1_Extraction.tsx
Normal file
131
competitor-analysis-app/components/Step1_Extraction.tsx
Normal file
@@ -0,0 +1,131 @@
|
||||
import React, { useState } from 'react';
|
||||
import type { Product, TargetIndustry } from '../types';
|
||||
import { EditableCard } from './EditableCard';
|
||||
import EvidencePopover from './EvidencePopover';
|
||||
import { fetchProductDetails } from '../services/geminiService';
|
||||
|
||||
interface Step1ExtractionProps {
|
||||
products: Product[];
|
||||
industries: TargetIndustry[];
|
||||
onProductsChange: (products: Product[]) => void;
|
||||
onIndustriesChange: (industries: TargetIndustry[]) => void;
|
||||
t: any;
|
||||
lang: 'de' | 'en';
|
||||
}
|
||||
|
||||
const Step1Extraction: React.FC<Step1ExtractionProps> = ({ products, industries, onProductsChange, onIndustriesChange, t, lang }) => {
|
||||
const [newProductName, setNewProductName] = useState('');
|
||||
const [newProductUrl, setNewProductUrl] = useState('');
|
||||
const [isAdding, setIsAdding] = useState(false);
|
||||
const [addError, setAddError] = useState<string | null>(null);
|
||||
|
||||
const handleAddProduct = async (e: React.FormEvent) => {
|
||||
e.preventDefault();
|
||||
if (!newProductName || !newProductUrl) return;
|
||||
|
||||
setIsAdding(true);
|
||||
setAddError(null);
|
||||
try {
|
||||
const newProduct = await fetchProductDetails(newProductName, newProductUrl, lang);
|
||||
onProductsChange([...products, newProduct]);
|
||||
setNewProductName('');
|
||||
setNewProductUrl('');
|
||||
} catch (error) {
|
||||
console.error("Failed to add product:", error);
|
||||
setAddError(t.addProductError);
|
||||
} finally {
|
||||
setIsAdding(false);
|
||||
}
|
||||
};
|
||||
|
||||
const inputClasses = "w-full bg-light-primary dark:bg-brand-primary text-light-text dark:text-brand-text border border-light-accent dark:border-brand-accent rounded-lg px-3 py-2 focus:outline-none focus:ring-2 focus:ring-brand-highlight placeholder-light-subtle dark:placeholder-brand-light";
|
||||
|
||||
return (
|
||||
<div>
|
||||
<h2 className="text-2xl font-bold mb-4">{t.title}</h2>
|
||||
<p className="text-light-subtle dark:text-brand-light mb-6">{t.subtitle}</p>
|
||||
|
||||
<div className="bg-light-secondary dark:bg-brand-secondary p-6 rounded-lg shadow-lg mb-6 border border-light-accent dark:border-brand-accent">
|
||||
<h3 className="text-xl font-bold mb-4">{t.addProductTitle}</h3>
|
||||
<form onSubmit={handleAddProduct} className="space-y-4">
|
||||
<div className="grid grid-cols-1 md:grid-cols-2 gap-4">
|
||||
<div>
|
||||
<label htmlFor="product_name" className="block text-sm font-medium text-light-subtle dark:text-brand-light mb-1">{t.productNameLabel}</label>
|
||||
<input
|
||||
id="product_name"
|
||||
type="text"
|
||||
value={newProductName}
|
||||
onChange={(e) => setNewProductName(e.target.value)}
|
||||
className={inputClasses}
|
||||
placeholder={t.productNamePlaceholder}
|
||||
required
|
||||
/>
|
||||
</div>
|
||||
<div>
|
||||
<label htmlFor="product_url" className="block text-sm font-medium text-light-subtle dark:text-brand-light mb-1">{t.productUrlLabel}</label>
|
||||
<input
|
||||
id="product_url"
|
||||
type="url"
|
||||
value={newProductUrl}
|
||||
onChange={(e) => setNewProductUrl(e.target.value)}
|
||||
className={inputClasses}
|
||||
placeholder="https://..."
|
||||
required
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
{addError && <p className="text-red-500 text-sm">{addError}</p>}
|
||||
<div className="text-right">
|
||||
<button
|
||||
type="submit"
|
||||
disabled={isAdding}
|
||||
className="bg-brand-accent hover:bg-brand-light text-white font-bold py-2 px-4 rounded-md disabled:opacity-50 disabled:cursor-not-allowed transition-colors"
|
||||
>
|
||||
{isAdding ? t.addingButton : t.addButton}
|
||||
</button>
|
||||
</div>
|
||||
</form>
|
||||
</div>
|
||||
|
||||
|
||||
<EditableCard<Product>
|
||||
title={t.productsTitle}
|
||||
items={products}
|
||||
onItemsChange={onProductsChange}
|
||||
showAddButton={false}
|
||||
fieldConfigs={[
|
||||
{ key: 'name', label: t.productNameLabel, type: 'text' },
|
||||
{ key: 'purpose', label: t.purposeLabel, type: 'textarea' },
|
||||
]}
|
||||
newItemTemplate={{ name: '', purpose: '', evidence: [] }}
|
||||
renderDisplay={(item) => (
|
||||
<div>
|
||||
<div className="flex items-center">
|
||||
<strong className="text-light-text dark:text-white">{item.name}</strong>
|
||||
<EvidencePopover evidence={item.evidence} />
|
||||
</div>
|
||||
<p className="text-light-subtle dark:text-brand-light text-sm mt-1">{item.purpose}</p>
|
||||
</div>
|
||||
)}
|
||||
t={t.editableCard}
|
||||
/>
|
||||
|
||||
<EditableCard<TargetIndustry>
|
||||
title={t.industriesTitle}
|
||||
items={industries}
|
||||
onItemsChange={onIndustriesChange}
|
||||
fieldConfigs={[{ key: 'name', label: t.industryNameLabel, type: 'text' }]}
|
||||
newItemTemplate={{ name: '', evidence: [] }}
|
||||
renderDisplay={(item) => (
|
||||
<div className="flex items-center">
|
||||
<strong className="text-light-text dark:text-white">{item.name}</strong>
|
||||
<EvidencePopover evidence={item.evidence} />
|
||||
</div>
|
||||
)}
|
||||
t={t.editableCard}
|
||||
/>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default Step1Extraction;
|
||||
38
competitor-analysis-app/components/Step2_Keywords.tsx
Normal file
38
competitor-analysis-app/components/Step2_Keywords.tsx
Normal file
@@ -0,0 +1,38 @@
|
||||
import React from 'react';
|
||||
import type { Keyword } from '../types';
|
||||
import { EditableCard } from './EditableCard';
|
||||
|
||||
interface Step2KeywordsProps {
|
||||
keywords: Keyword[];
|
||||
onKeywordsChange: (keywords: Keyword[]) => void;
|
||||
t: any;
|
||||
}
|
||||
|
||||
const Step2Keywords: React.FC<Step2KeywordsProps> = ({ keywords, onKeywordsChange, t }) => {
|
||||
return (
|
||||
<div>
|
||||
<h2 className="text-2xl font-bold mb-4">{t.title}</h2>
|
||||
<p className="text-light-subtle dark:text-brand-light mb-6">{t.subtitle}</p>
|
||||
|
||||
<EditableCard<Keyword>
|
||||
title={t.cardTitle}
|
||||
items={keywords}
|
||||
onItemsChange={onKeywordsChange}
|
||||
fieldConfigs={[
|
||||
{ key: 'term', label: t.termLabel, type: 'text' },
|
||||
{ key: 'rationale', label: t.rationaleLabel, type: 'textarea' },
|
||||
]}
|
||||
newItemTemplate={{ term: '', rationale: '' }}
|
||||
renderDisplay={(item) => (
|
||||
<div>
|
||||
<strong className="text-light-text dark:text-white">{item.term}</strong>
|
||||
<p className="text-light-subtle dark:text-brand-light text-sm mt-1">{item.rationale}</p>
|
||||
</div>
|
||||
)}
|
||||
t={t.editableCard}
|
||||
/>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default Step2Keywords;
|
||||
57
competitor-analysis-app/components/Step3_Competitors.tsx
Normal file
57
competitor-analysis-app/components/Step3_Competitors.tsx
Normal file
@@ -0,0 +1,57 @@
|
||||
import React from 'react';
|
||||
import type { CompetitorCandidate } from '../types';
|
||||
import EvidencePopover from './EvidencePopover';
|
||||
import { EditableCard } from './EditableCard';
|
||||
|
||||
interface Step3CompetitorsProps {
|
||||
candidates: CompetitorCandidate[];
|
||||
onCandidatesChange: (candidates: CompetitorCandidate[]) => void;
|
||||
maxCompetitors: number;
|
||||
t: any;
|
||||
}
|
||||
|
||||
const Step3Competitors: React.FC<Step3CompetitorsProps> = ({ candidates, onCandidatesChange, maxCompetitors, t }) => {
|
||||
const sortedCandidates = [...candidates].sort((a, b) => b.confidence - a.confidence);
|
||||
|
||||
return (
|
||||
<div>
|
||||
<h2 className="text-2xl font-bold mb-4">{t.title}</h2>
|
||||
<p className="text-light-subtle dark:text-brand-light mb-6">
|
||||
{t.subtitle(maxCompetitors)}
|
||||
</p>
|
||||
|
||||
<EditableCard<CompetitorCandidate>
|
||||
title={t.cardTitle}
|
||||
items={sortedCandidates}
|
||||
onItemsChange={onCandidatesChange}
|
||||
fieldConfigs={[
|
||||
{ key: 'name', label: t.nameLabel, type: 'text' },
|
||||
{ key: 'url', label: 'URL', type: 'text' },
|
||||
{ key: 'why', label: t.whyLabel, type: 'textarea' },
|
||||
]}
|
||||
newItemTemplate={{ name: '', url: '', confidence: 0.8, why: '', evidence: [] }}
|
||||
renderDisplay={(item, index) => (
|
||||
<div>
|
||||
<div className="flex items-center justify-between">
|
||||
<div className="flex items-center">
|
||||
<strong className={`text-light-text dark:text-white ${index < maxCompetitors ? 'text-green-600 dark:text-green-400' : ''}`}>{item.name}</strong>
|
||||
<a href={item.url} target="_blank" rel="noopener noreferrer" className="ml-2 text-blue-500 dark:text-blue-400 hover:underline text-sm">
|
||||
{t.visitButton}
|
||||
</a>
|
||||
<EvidencePopover evidence={item.evidence} />
|
||||
</div>
|
||||
<span className="text-xs font-mono bg-light-accent dark:bg-brand-accent text-light-text dark:text-white py-1 px-2 rounded-full">
|
||||
{(item.confidence * 100).toFixed(0)}%
|
||||
</span>
|
||||
</div>
|
||||
<p className="text-light-subtle dark:text-brand-light text-sm mt-1">{item.why}</p>
|
||||
{index === maxCompetitors - 1 && <div className="border-t-2 border-dashed border-red-500 mt-4 pt-2 text-red-500 dark:text-red-400 text-xs text-center font-bold">{t.shortlistBoundary}</div>}
|
||||
</div>
|
||||
)}
|
||||
t={t.editableCard}
|
||||
/>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default Step3Competitors;
|
||||
97
competitor-analysis-app/components/Step4_Analysis.tsx
Normal file
97
competitor-analysis-app/components/Step4_Analysis.tsx
Normal file
@@ -0,0 +1,97 @@
|
||||
import React from 'react';
|
||||
import type { Analysis } from '../types';
|
||||
import EvidencePopover from './EvidencePopover';
|
||||
|
||||
interface Step4AnalysisProps {
|
||||
analyses: Analysis[];
|
||||
t: any;
|
||||
}
|
||||
|
||||
const DownloadIcon = () => (<svg xmlns="http://www.w3.org/2000/svg" className="h-4 w-4" fill="none" viewBox="0 0 24 24" stroke="currentColor"><path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M4 16v1a3 3 0 003 3h10a3 3 0 003-3v-1m-4-4l-4 4m0 0l-4-4m4 4V4" /></svg>);
|
||||
|
||||
const downloadJSON = (data: any, filename: string) => {
|
||||
const jsonStr = JSON.stringify(data, null, 2);
|
||||
const blob = new Blob([jsonStr], { type: "application/json" });
|
||||
const url = URL.createObjectURL(blob);
|
||||
const link = document.createElement("a");
|
||||
link.href = url;
|
||||
link.download = filename;
|
||||
document.body.appendChild(link);
|
||||
link.click();
|
||||
document.body.removeChild(link);
|
||||
URL.revokeObjectURL(url);
|
||||
};
|
||||
|
||||
const OverlapBar: React.FC<{ score: number }> = ({ score }) => (
|
||||
<div className="w-full bg-light-accent dark:bg-brand-accent rounded-full h-2.5">
|
||||
<div className="bg-brand-highlight h-2.5 rounded-full" style={{ width: `${score}%` }}></div>
|
||||
</div>
|
||||
);
|
||||
|
||||
const Step4Analysis: React.FC<Step4AnalysisProps> = ({ analyses, t }) => {
|
||||
const sortedAnalyses = [...analyses].sort((a, b) => b.overlap_score - a.overlap_score);
|
||||
|
||||
return (
|
||||
<div>
|
||||
<h2 className="text-2xl font-bold mb-4">{t.title}</h2>
|
||||
<p className="text-light-subtle dark:text-brand-light mb-6">
|
||||
{t.subtitle}
|
||||
</p>
|
||||
|
||||
<div className="space-y-6">
|
||||
{sortedAnalyses.map((analysis, index) => (
|
||||
<div key={index} className="bg-light-secondary dark:bg-brand-secondary p-6 rounded-lg shadow-lg">
|
||||
<div className="flex justify-between items-start mb-4">
|
||||
<div>
|
||||
<h3 className="text-xl font-bold text-light-text dark:text-white">{analysis.competitor.name}</h3>
|
||||
<a href={analysis.competitor.url} target="_blank" rel="noopener noreferrer" className="text-blue-500 dark:text-blue-400 hover:underline text-sm">
|
||||
{analysis.competitor.url}
|
||||
</a>
|
||||
</div>
|
||||
<div className="flex items-center space-x-2">
|
||||
<button
|
||||
onClick={() => downloadJSON(analysis, `analysis_${analysis.competitor.name.replace(/ /g, '_')}.json`)}
|
||||
title={t.downloadJson_title}
|
||||
className="text-light-subtle dark:text-brand-light hover:text-light-text dark:hover:text-white p-1 rounded-full"
|
||||
>
|
||||
<DownloadIcon />
|
||||
</button>
|
||||
<EvidencePopover evidence={analysis.evidence} />
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="grid grid-cols-1 md:grid-cols-2 gap-6">
|
||||
<div>
|
||||
<h4 className="font-semibold mb-2">{t.portfolio}</h4>
|
||||
<ul className="list-disc list-inside text-light-subtle dark:text-brand-light text-sm space-y-1">
|
||||
{analysis.portfolio.map((p, i) => <li key={i}><strong>{p.product}:</strong> {p.purpose}</li>)}
|
||||
</ul>
|
||||
</div>
|
||||
<div>
|
||||
<h4 className="font-semibold mb-2">{t.differentiators}</h4>
|
||||
<ul className="list-disc list-inside text-light-subtle dark:text-brand-light text-sm space-y-1">
|
||||
{analysis.differentiators.map((d, i) => <li key={i}>{d}</li>)}
|
||||
</ul>
|
||||
</div>
|
||||
<div>
|
||||
<h4 className="font-semibold mb-2">{t.targetIndustries}</h4>
|
||||
<div className="flex flex-wrap gap-2 mb-2">
|
||||
{analysis.target_industries.map((ind, i) => (
|
||||
<span key={i} className="bg-light-accent dark:bg-brand-accent text-xs font-medium px-2.5 py-0.5 rounded-full">{ind}</span>
|
||||
))}
|
||||
</div>
|
||||
<span className="bg-gray-500 dark:bg-gray-600 text-white text-xs font-medium px-2.5 py-0.5 rounded-full">{analysis.delivery_model}</span>
|
||||
</div>
|
||||
<div>
|
||||
<h4 className="font-semibold mb-2">{t.overlapScore}: {analysis.overlap_score}%</h4>
|
||||
<OverlapBar score={analysis.overlap_score} />
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default Step4Analysis;
|
||||
BIN
competitor-analysis-app/components/Step5_Conclusion.tsx
Normal file
BIN
competitor-analysis-app/components/Step5_Conclusion.tsx
Normal file
Binary file not shown.
44
competitor-analysis-app/components/Step5_SilverBullets.tsx
Normal file
44
competitor-analysis-app/components/Step5_SilverBullets.tsx
Normal file
@@ -0,0 +1,44 @@
|
||||
import React from 'react';
|
||||
import type { SilverBullet } from '../types';
|
||||
|
||||
interface Step5SilverBulletsProps {
|
||||
silver_bullets: SilverBullet[];
|
||||
t: any;
|
||||
}
|
||||
|
||||
const Step5SilverBullets: React.FC<Step5SilverBulletsProps> = ({ silver_bullets, t }) => {
|
||||
if (!silver_bullets || silver_bullets.length === 0) {
|
||||
return (
|
||||
<div>
|
||||
<h2 className="text-2xl font-bold mb-4">{t.title}</h2>
|
||||
<p className="text-light-subtle dark:text-brand-light">{t.generating}</p>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
return (
|
||||
<div>
|
||||
<h2 className="text-2xl font-bold mb-4">{t.title}</h2>
|
||||
<p className="text-light-subtle dark:text-brand-light mb-6">
|
||||
{t.subtitle}
|
||||
</p>
|
||||
|
||||
<div className="space-y-4">
|
||||
{silver_bullets.map((bullet, index) => (
|
||||
<div key={index} className="bg-light-secondary dark:bg-brand-secondary p-6 rounded-lg shadow-lg">
|
||||
<h3 className="text-lg font-semibold text-light-text dark:text-white mb-2">
|
||||
{t.cardTitle} <span className="text-brand-highlight">{bullet.competitor_name}</span>
|
||||
</h3>
|
||||
<blockquote className="border-l-4 border-brand-highlight pl-4">
|
||||
<p className="text-lg italic text-light-subtle dark:text-brand-light">
|
||||
"{bullet.statement}"
|
||||
</p>
|
||||
</blockquote>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default Step5SilverBullets;
|
||||
148
competitor-analysis-app/components/Step6_Conclusion.tsx
Normal file
148
competitor-analysis-app/components/Step6_Conclusion.tsx
Normal file
@@ -0,0 +1,148 @@
|
||||
import React from 'react';
|
||||
import type { AppState } from '../types';
|
||||
|
||||
interface Step6ConclusionProps {
|
||||
appState: AppState | null;
|
||||
t: any;
|
||||
}
|
||||
|
||||
const MatrixTable: React.FC<{ data: { [row: string]: { [col: string]: string } }, title: string }> = ({ data, title }) => {
|
||||
if (!data || Object.keys(data).length === 0) {
|
||||
return <p>No data available for {title}.</p>;
|
||||
}
|
||||
|
||||
// Robustly get all unique column headers from all rows
|
||||
const columnSet = new Set<string>();
|
||||
Object.values(data).forEach(rowData => {
|
||||
if (rowData && typeof rowData === 'object') {
|
||||
Object.keys(rowData).forEach(col => columnSet.add(col));
|
||||
}
|
||||
});
|
||||
const columns = Array.from(columnSet).sort();
|
||||
const rows = Object.keys(data);
|
||||
|
||||
return (
|
||||
<div className="bg-light-secondary dark:bg-brand-secondary p-4 rounded-lg">
|
||||
<h3 className="text-lg font-bold mb-3">{title}</h3>
|
||||
<div className="overflow-x-auto">
|
||||
<table className="w-full text-sm text-left">
|
||||
<thead className="bg-light-accent dark:bg-brand-accent uppercase">
|
||||
<tr>
|
||||
<th scope="col" className="px-4 py-2"></th>
|
||||
{columns.map(col => <th key={col} scope="col" className="px-4 py-2 text-center whitespace-nowrap">{col}</th>)}
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{rows.map(row => (
|
||||
<tr key={row} className="border-b border-light-accent dark:border-brand-accent">
|
||||
<th scope="row" className="px-4 py-2 font-medium whitespace-nowrap">{row}</th>
|
||||
{columns.map(col => {
|
||||
// Safely access cell data to prevent crashes on malformed data
|
||||
const cellData = data[row]?.[col] || ' ';
|
||||
return (
|
||||
<td key={col} className="px-4 py-2 text-center text-green-600 dark:text-green-400 font-bold">
|
||||
{cellData}
|
||||
</td>
|
||||
);
|
||||
})}
|
||||
</tr>
|
||||
))}
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
type ProductMatrixItem = { product: string; availability: { competitor: string; has_offering: boolean }[] };
|
||||
type IndustryMatrixItem = { industry: string; availability: { competitor: string; has_offering: boolean }[] };
|
||||
|
||||
const transformMatrixData = (matrixData: (ProductMatrixItem[] | IndustryMatrixItem[]) | undefined): { [row: string]: { [col: string]: string } } => {
|
||||
const tableData: { [row: string]: { [col: string]: string } } = {};
|
||||
if (!matrixData || !Array.isArray(matrixData) || matrixData.length === 0) {
|
||||
return tableData;
|
||||
}
|
||||
|
||||
const allCompetitors = new Set<string>();
|
||||
matrixData.forEach(row => {
|
||||
if (row && Array.isArray(row.availability)) {
|
||||
row.availability.forEach(item => {
|
||||
if (item && typeof item.competitor === 'string') {
|
||||
allCompetitors.add(item.competitor);
|
||||
}
|
||||
});
|
||||
}
|
||||
});
|
||||
const competitorList = Array.from(allCompetitors).sort();
|
||||
|
||||
matrixData.forEach(row => {
|
||||
if (!row) return;
|
||||
|
||||
const rowKey = 'product' in row ? row.product : ('industry' in row ? row.industry : undefined);
|
||||
|
||||
if (typeof rowKey !== 'string' || !rowKey) {
|
||||
return;
|
||||
}
|
||||
|
||||
const availabilityMap = new Map<string, boolean>();
|
||||
if (Array.isArray(row.availability)) {
|
||||
row.availability.forEach(item => {
|
||||
if (item && typeof item.competitor === 'string') {
|
||||
availabilityMap.set(item.competitor, item.has_offering);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
const rowObject: { [col: string]: string } = {};
|
||||
competitorList.forEach(competitor => {
|
||||
rowObject[competitor] = availabilityMap.get(competitor) ? '✓' : ' ';
|
||||
});
|
||||
tableData[rowKey] = rowObject;
|
||||
});
|
||||
|
||||
return tableData;
|
||||
};
|
||||
|
||||
const Step6Conclusion: React.FC<Step6ConclusionProps> = ({ appState, t }) => {
|
||||
if (!appState || !appState.conclusion) return <p>{t.generating}</p>;
|
||||
const { conclusion, company } = appState;
|
||||
|
||||
const productMatrixForTable = transformMatrixData(conclusion.product_matrix);
|
||||
const industryMatrixForTable = transformMatrixData(conclusion.industry_matrix);
|
||||
|
||||
return (
|
||||
<div>
|
||||
<div className="flex justify-between items-center mb-4">
|
||||
<h2 className="text-2xl font-bold">{t.title}</h2>
|
||||
</div>
|
||||
|
||||
<p className="text-light-subtle dark:text-brand-light mb-6">{t.subtitle}</p>
|
||||
|
||||
<div className="space-y-6">
|
||||
<div className="grid grid-cols-1 lg:grid-cols-2 gap-6">
|
||||
<MatrixTable data={productMatrixForTable} title={t.productMatrix} />
|
||||
<MatrixTable data={industryMatrixForTable} title={t.industryMatrix} />
|
||||
</div>
|
||||
|
||||
<div className="bg-light-secondary dark:bg-brand-secondary p-4 rounded-lg">
|
||||
<h3 className="text-lg font-bold mb-3">{t.summary}</h3>
|
||||
<p className="text-light-subtle dark:text-brand-light">{conclusion.summary}</p>
|
||||
</div>
|
||||
|
||||
<div className="bg-light-secondary dark:bg-brand-secondary p-4 rounded-lg">
|
||||
<h3 className="text-lg font-bold mb-3">{t.opportunities(company.name)}</h3>
|
||||
<p className="text-light-subtle dark:text-brand-light">{conclusion.opportunities}</p>
|
||||
</div>
|
||||
|
||||
<div className="bg-light-secondary dark:bg-brand-secondary p-4 rounded-lg">
|
||||
<h3 className="text-lg font-bold mb-3">{t.nextQuestions}</h3>
|
||||
<ul className="list-disc list-inside text-light-subtle dark:text-brand-light space-y-1">
|
||||
{(conclusion.next_questions || []).map((q, i) => <li key={i}>{q}</li>)}
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default Step6Conclusion;
|
||||
91
competitor-analysis-app/components/Step7_Battlecards.tsx
Normal file
91
competitor-analysis-app/components/Step7_Battlecards.tsx
Normal file
@@ -0,0 +1,91 @@
|
||||
import React, { useState } from 'react';
|
||||
import type { AppState, Battlecard } from '../types';
|
||||
|
||||
interface Step7BattlecardsProps {
|
||||
appState: AppState | null;
|
||||
t: any;
|
||||
}
|
||||
|
||||
const ProfileIcon = () => (<svg xmlns="http://www.w3.org/2000/svg" className="h-5 w-5 mr-2 inline-block" viewBox="0 0 20 20" fill="currentColor"><path fillRule="evenodd" d="M10 9a3 3 0 100-6 3 3 0 000 6zm-7 9a7 7 0 1114 0H3z" clipRule="evenodd" /></svg>);
|
||||
const StrengthsIcon = () => (<svg xmlns="http://www.w3.org/2000/svg" className="h-5 w-5 mr-2 inline-block" viewBox="0 0 20 20" fill="currentColor"><path fillRule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-8.707l-3-3a1 1 0 00-1.414 0l-3 3a1 1 0 001.414 1.414L9 9.414V13a1 1 0 102 0V9.414l1.293 1.293a1 1 0 001.414-1.414z" clipRule="evenodd" /></svg>);
|
||||
const LandmineIcon = () => (<svg xmlns="http://www.w3.org/2000/svg" className="h-5 w-5 mr-2 inline-block" viewBox="0 0 20 20" fill="currentColor"><path d="M13.477 14.89A6 6 0 015.11 6.524l8.367 8.367zM18 10a8 8 0 11-16 0 8 8 0 0116 0z" /></svg>);
|
||||
const BulletIcon = () => (<svg xmlns="http://www.w3.org/2000/svg" className="h-5 w-5 mr-2 inline-block" viewBox="0 0 20 20" fill="currentColor"><path fillRule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zM7 9a1 1 0 000 2h6a1 1 0 100-2H7z" clipRule="evenodd" /></svg>);
|
||||
|
||||
const BattlecardComponent: React.FC<{ battlecard: Battlecard, t: any }> = ({ battlecard, t }) => {
|
||||
|
||||
return (
|
||||
<div className="bg-light-secondary dark:bg-brand-secondary p-6 rounded-lg shadow-lg relative">
|
||||
<div className="space-y-6">
|
||||
<div>
|
||||
<h3 className="text-xl font-bold flex items-center mb-2"><ProfileIcon /> {t.profile}</h3>
|
||||
<p className="text-light-subtle dark:text-brand-light pl-7">{battlecard.competitor_profile.focus}</p>
|
||||
<p className="text-light-subtle dark:text-brand-light pl-7 mt-1">{battlecard.competitor_profile.positioning}</p>
|
||||
</div>
|
||||
<div>
|
||||
<h3 className="text-xl font-bold flex items-center mb-2"><StrengthsIcon /> {t.strengths}</h3>
|
||||
<ul className="list-disc list-inside space-y-1 text-light-subtle dark:text-brand-light pl-7">
|
||||
{(battlecard.strengths_vs_weaknesses || []).map((item, i) => <li key={i}>{item}</li>)}
|
||||
</ul>
|
||||
</div>
|
||||
<div>
|
||||
<h3 className="text-xl font-bold flex items-center mb-2"><LandmineIcon /> {t.landmines}</h3>
|
||||
<ul className="list-disc list-inside space-y-1 text-light-subtle dark:text-brand-light pl-7">
|
||||
{(battlecard.landmine_questions || []).map((item, i) => <li key={i}>{item}</li>)}
|
||||
</ul>
|
||||
</div>
|
||||
<div>
|
||||
<h3 className="text-xl font-bold flex items-center mb-2"><BulletIcon /> {t.silverBullet}</h3>
|
||||
<blockquote className="border-l-4 border-brand-highlight pl-4 ml-7">
|
||||
<p className="text-lg italic text-light-subtle dark:text-brand-light">"{battlecard.silver_bullet}"</p>
|
||||
</blockquote>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
const Step7_Battlecards: React.FC<Step7BattlecardsProps> = ({ appState, t }) => {
|
||||
const [activeTab, setActiveTab] = useState(0);
|
||||
|
||||
if (!appState || !appState.battlecards || appState.battlecards.length === 0) {
|
||||
return (
|
||||
<div>
|
||||
<h2 className="text-2xl font-bold mb-4">{t.title}</h2>
|
||||
<p className="text-light-subtle dark:text-brand-light">{t.generating}</p>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
const { battlecards } = appState;
|
||||
const activeBattlecard = battlecards[activeTab];
|
||||
|
||||
return (
|
||||
<div>
|
||||
<h2 className="text-2xl font-bold mb-4">{t.title}</h2>
|
||||
<p className="text-light-subtle dark:text-brand-light mb-6">
|
||||
{t.subtitle}
|
||||
</p>
|
||||
|
||||
<div className="flex border-b border-light-accent dark:border-brand-accent mb-4 overflow-x-auto">
|
||||
{battlecards.map((card, index) => (
|
||||
<button
|
||||
key={index}
|
||||
onClick={() => setActiveTab(index)}
|
||||
className={`py-2 px-4 font-semibold text-sm focus:outline-none whitespace-nowrap ${
|
||||
activeTab === index
|
||||
? 'border-b-2 border-brand-highlight text-light-text dark:text-white'
|
||||
: 'text-light-subtle dark:text-brand-light hover:bg-light-accent dark:hover:bg-brand-accent'
|
||||
}`}
|
||||
>
|
||||
{card.competitor_name}
|
||||
</button>
|
||||
))}
|
||||
</div>
|
||||
|
||||
{activeBattlecard && <BattlecardComponent battlecard={activeBattlecard} t={t.card} />}
|
||||
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default Step7_Battlecards;
|
||||
81
competitor-analysis-app/components/Step8_References.tsx
Normal file
81
competitor-analysis-app/components/Step8_References.tsx
Normal file
@@ -0,0 +1,81 @@
|
||||
import React from 'react';
|
||||
import type { ReferenceAnalysis } from '../types';
|
||||
|
||||
interface Step8ReferencesProps {
|
||||
analyses: ReferenceAnalysis[];
|
||||
groundingMetadata: any[];
|
||||
t: any;
|
||||
}
|
||||
|
||||
const LinkIcon = () => (<svg xmlns="http://www.w3.org/2000/svg" className="h-4 w-4 inline-block ml-1" viewBox="0 0 20 20" fill="currentColor"><path fillRule="evenodd" d="M12.586 4.586a2 2 0 112.828 2.828l-3 3a2 2 0 01-2.828 0 1 1 0 00-1.414 1.414 4 4 0 005.656 0l3-3a4 4 0 00-5.656-5.656l-1.5 1.5a1 1 0 101.414 1.414l1.5-1.5zm-5 5a2 2 0 012.828 0 1 1 0 101.414-1.414 4 4 0 00-5.656 0l-3 3a4 4 0 105.656 5.656l1.5-1.5a1 1 0 10-1.414-1.414l-1.5 1.5a2 2 0 11-2.828-2.828l3-3z" clipRule="evenodd" /></svg>);
|
||||
|
||||
|
||||
const Step8_References: React.FC<Step8ReferencesProps> = ({ analyses, groundingMetadata, t }) => {
|
||||
return (
|
||||
<div>
|
||||
<h2 className="text-2xl font-bold mb-4">{t.title}</h2>
|
||||
<p className="text-light-subtle dark:text-brand-light mb-6">
|
||||
{t.subtitle}
|
||||
</p>
|
||||
|
||||
<div className="space-y-6">
|
||||
{(analyses || []).map((analysis, index) => {
|
||||
// This robust check prevents crashes if `references` is null, undefined, or not an array.
|
||||
const hasReferences = Array.isArray(analysis.references) && analysis.references.length > 0;
|
||||
|
||||
return (
|
||||
<div key={index} className="bg-light-secondary dark:bg-brand-secondary p-6 rounded-lg shadow-lg">
|
||||
<h3 className="text-xl font-bold text-light-text dark:text-white mb-4">{analysis.competitor_name}</h3>
|
||||
|
||||
{!hasReferences ? (
|
||||
<p className="text-light-subtle dark:text-brand-light">{t.noReferencesFound}</p>
|
||||
) : (
|
||||
<div className="space-y-4">
|
||||
{analysis.references.map((ref, refIndex) => (
|
||||
<div key={refIndex} className="bg-light-primary dark:bg-brand-primary p-4 rounded-md border-l-4 border-brand-accent">
|
||||
<div className="flex justify-between items-start">
|
||||
<div>
|
||||
<strong className="text-light-text dark:text-white">{ref.name}</strong>
|
||||
{ref.industry && <span className="text-xs ml-2 bg-light-accent dark:bg-brand-accent px-2 py-0.5 rounded-full">{ref.industry}</span>}
|
||||
</div>
|
||||
{ref.case_study_url && (
|
||||
<a href={ref.case_study_url} target="_blank" rel="noopener noreferrer" className="text-sm text-blue-500 dark:text-blue-400 hover:underline flex-shrink-0">
|
||||
{t.caseStudyLink} <LinkIcon/>
|
||||
</a>
|
||||
)}
|
||||
</div>
|
||||
{ref.testimonial_snippet && (
|
||||
<blockquote className="mt-2 text-sm italic text-light-subtle dark:text-brand-light border-l-2 border-gray-400 pl-3">
|
||||
"{ref.testimonial_snippet}"
|
||||
</blockquote>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
})}
|
||||
</div>
|
||||
|
||||
{groundingMetadata && groundingMetadata.length > 0 && (
|
||||
<div className="mt-8 bg-light-secondary dark:bg-brand-secondary p-6 rounded-lg shadow-lg">
|
||||
<h3 className="text-xl font-bold text-light-text dark:text-white mb-4">{t.sourcesTitle}</h3>
|
||||
<ul className="list-disc list-inside space-y-2">
|
||||
{groundingMetadata
|
||||
.filter(chunk => chunk.web && chunk.web.uri)
|
||||
.map((chunk, index) => (
|
||||
<li key={index} className="text-sm">
|
||||
<a href={chunk.web.uri} target="_blank" rel="noopener noreferrer" className="text-blue-500 dark:text-blue-400 hover:underline">
|
||||
{chunk.web.title || chunk.web.uri}
|
||||
</a>
|
||||
</li>
|
||||
))}
|
||||
</ul>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default Step8_References;
|
||||
50
competitor-analysis-app/components/StepIndicator.tsx
Normal file
50
competitor-analysis-app/components/StepIndicator.tsx
Normal file
@@ -0,0 +1,50 @@
|
||||
import React from 'react';
|
||||
|
||||
interface StepIndicatorProps {
|
||||
currentStep: number;
|
||||
highestStep: number;
|
||||
onStepClick: (step: number) => void;
|
||||
t: {
|
||||
title: string;
|
||||
steps: string[];
|
||||
}
|
||||
}
|
||||
|
||||
const StepIndicator: React.FC<StepIndicatorProps> = ({ currentStep, highestStep, onStepClick, t }) => {
|
||||
|
||||
const steps = t.steps.map((name, index) => ({ id: index + 1, name }));
|
||||
|
||||
return (
|
||||
<div className="bg-light-secondary dark:bg-brand-secondary p-4 rounded-lg shadow-md border border-light-accent dark:border-brand-accent">
|
||||
<h3 className="font-bold text-lg mb-4">{t.title}</h3>
|
||||
<ol className="space-y-3">
|
||||
{steps.map((step) => {
|
||||
const isCompleted = step.id < currentStep;
|
||||
const isActive = step.id === currentStep;
|
||||
const isClickable = step.id <= highestStep;
|
||||
|
||||
return (
|
||||
<li
|
||||
key={step.id}
|
||||
className={`flex items-center p-1 rounded-md transition-colors ${isClickable ? 'cursor-pointer hover:bg-light-accent dark:hover:bg-brand-accent' : 'cursor-default'}`}
|
||||
onClick={() => isClickable && onStepClick(step.id)}
|
||||
>
|
||||
<span className={`flex-shrink-0 flex items-center justify-center w-6 h-6 rounded-full mr-3 text-sm font-bold ${
|
||||
isCompleted ? 'bg-green-500 text-white' :
|
||||
isActive ? 'bg-brand-highlight text-white ring-2 ring-offset-2 ring-offset-light-secondary dark:ring-offset-brand-secondary ring-brand-highlight' :
|
||||
'bg-light-accent dark:bg-brand-accent text-light-text dark:text-brand-text'
|
||||
}`}>
|
||||
{isCompleted ? '✓' : step.id}
|
||||
</span>
|
||||
<span className={`font-medium ${isActive ? 'text-light-text dark:text-white' : 'text-light-subtle dark:text-brand-light'}`}>
|
||||
{step.name}
|
||||
</span>
|
||||
</li>
|
||||
)
|
||||
})}
|
||||
</ol>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default StepIndicator;
|
||||
51
competitor-analysis-app/index.html
Normal file
51
competitor-analysis-app/index.html
Normal file
@@ -0,0 +1,51 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en" class="dark">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<link rel="icon" type="image/svg+xml" href="/vite.svg" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>B2B Competitor Analysis Agent</title>
|
||||
<script src="https://cdn.tailwindcss.com"></script>
|
||||
<script>
|
||||
tailwind.config = {
|
||||
darkMode: 'class',
|
||||
theme: {
|
||||
extend: {
|
||||
colors: {
|
||||
// Dark Theme
|
||||
'brand-primary': '#0D1B2A',
|
||||
'brand-secondary': '#1B263B',
|
||||
'brand-accent': '#415A77',
|
||||
'brand-light': '#778DA9',
|
||||
'brand-text': '#E0E1DD',
|
||||
'brand-highlight': '#3B82F6',
|
||||
// Light Theme
|
||||
'light-primary': '#F8F9FA',
|
||||
'light-secondary': '#FFFFFF',
|
||||
'light-accent': '#DEE2E6',
|
||||
'light-text': '#212529',
|
||||
'light-subtle': '#6C757D',
|
||||
},
|
||||
},
|
||||
},
|
||||
}
|
||||
</script>
|
||||
<script type="importmap">
|
||||
{
|
||||
"imports": {
|
||||
"react/": "https://aistudiocdn.com/react@^19.2.0/",
|
||||
"react": "https://aistudiocdn.com/react@^19.2.0",
|
||||
"react-dom/": "https://aistudiocdn.com/react-dom@^19.2.0/",
|
||||
"@google/genai": "https://aistudiocdn.com/@google/genai@^1.28.0",
|
||||
"jspdf": "https://aistudiocdn.com/jspdf@^2.5.1",
|
||||
"jspdf-autotable": "https://aistudiocdn.com/jspdf-autotable@^3.8.2"
|
||||
}
|
||||
}
|
||||
</script>
|
||||
<link rel="stylesheet" href="/index.css">
|
||||
</head>
|
||||
<body class="bg-light-primary dark:bg-brand-primary text-light-text dark:text-brand-text transition-colors duration-300">
|
||||
<div id="root"></div>
|
||||
<script type="module" src="/index.tsx"></script>
|
||||
</body>
|
||||
</html>
|
||||
16
competitor-analysis-app/index.tsx
Normal file
16
competitor-analysis-app/index.tsx
Normal file
@@ -0,0 +1,16 @@
|
||||
|
||||
import React from 'react';
|
||||
import ReactDOM from 'react-dom/client';
|
||||
import App from './App';
|
||||
|
||||
const rootElement = document.getElementById('root');
|
||||
if (!rootElement) {
|
||||
throw new Error("Could not find root element to mount to");
|
||||
}
|
||||
|
||||
const root = ReactDOM.createRoot(rootElement);
|
||||
root.render(
|
||||
<React.StrictMode>
|
||||
<App />
|
||||
</React.StrictMode>
|
||||
);
|
||||
23
competitor-analysis-app/package.json
Normal file
23
competitor-analysis-app/package.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"name": "b2b-competitor-analysis-agent",
|
||||
"private": true,
|
||||
"version": "0.0.0",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
"build": "vite build",
|
||||
"preview": "vite preview"
|
||||
},
|
||||
"dependencies": {
|
||||
"react": "^19.2.0",
|
||||
"react-dom": "^19.2.0",
|
||||
"@google/genai": "^1.28.0",
|
||||
"jspdf": "^2.5.1",
|
||||
"jspdf-autotable": "^3.8.2",
|
||||
"@types/node": "^22.14.0",
|
||||
"@vitejs/plugin-react": "^5.0.0",
|
||||
"typescript": "~5.8.2",
|
||||
"vite": "^6.2.0"
|
||||
},
|
||||
"devDependencies": {}
|
||||
}
|
||||
7
competitor-analysis-app/requirements.txt
Normal file
7
competitor-analysis-app/requirements.txt
Normal file
@@ -0,0 +1,7 @@
|
||||
fastapi==0.104.1
|
||||
uvicorn==0.24.0.post1
|
||||
python-dotenv==1.0.0
|
||||
google-generativeai==0.3.0
|
||||
# The frontend uses jspdf and jspdf-autotable, but these are JS libraries, not Python. No direct Python equivalent is needed unless PDF generation moves to backend.
|
||||
# google-genai (newer SDK) might be needed if using Imagen 4 or Gemini 2.x features.
|
||||
# Pillow for image processing.
|
||||
129
competitor-analysis-app/services/geminiService.ts
Normal file
129
competitor-analysis-app/services/geminiService.ts
Normal file
@@ -0,0 +1,129 @@
|
||||
import type { Product, TargetIndustry, Keyword, CompetitorCandidate, Analysis, AppState, Conclusion, SilverBullet, Battlecard, ShortlistedCompetitor, ReferenceAnalysis } from '../types';
|
||||
|
||||
const API_BASE_URL = './'; // Relative to the application sub-path (/ca/)
|
||||
|
||||
export const fetchProductDetails = async (name: string, url: string, language: 'de' | 'en'): Promise<Product> => {
|
||||
const response = await fetch(`${API_BASE_URL}api/fetchProductDetails`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({ name, url, language }),
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP error! status: ${response.status}`);
|
||||
}
|
||||
return response.json();
|
||||
};
|
||||
|
||||
export const fetchStep1Data = async (startUrl: string, language: 'de' | 'en'): Promise<{ products: Product[], target_industries: TargetIndustry[] }> => {
|
||||
const response = await fetch(`${API_BASE_URL}api/fetchStep1Data`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({ start_url: startUrl, language }),
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP error! status: ${response.status}`);
|
||||
}
|
||||
return response.json();
|
||||
};
|
||||
|
||||
export const fetchStep2Data = async (products: Product[], industries: TargetIndustry[], language: 'de' | 'en'): Promise<{ keywords: Keyword[] }> => {
|
||||
const response = await fetch(`${API_BASE_URL}api/fetchStep2Data`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({ products, industries, language }),
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP error! status: ${response.status}`);
|
||||
}
|
||||
return response.json();
|
||||
};
|
||||
|
||||
export const fetchStep3Data = async (keywords: Keyword[], marketScope: string, language: 'de' | 'en'): Promise<{ competitor_candidates: CompetitorCandidate[] }> => {
|
||||
const response = await fetch(`${API_BASE_URL}api/fetchStep3Data`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({ keywords, market_scope: marketScope, language }),
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP error! status: ${response.status}`);
|
||||
}
|
||||
return response.json();
|
||||
};
|
||||
|
||||
export const fetchStep4Data = async (company: AppState['company'], competitors: CompetitorCandidate[], language: 'de' | 'en'): Promise<{ analyses: Analysis[] }> => {
|
||||
const response = await fetch(`${API_BASE_URL}api/fetchStep4Data`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({ company, competitors, language }),
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP error! status: ${response.status}`);
|
||||
}
|
||||
return response.json();
|
||||
};
|
||||
|
||||
export const fetchStep5Data_SilverBullets = async (company: AppState['company'], analyses: Analysis[], language: 'de' | 'en'): Promise<{ silver_bullets: SilverBullet[] }> => {
|
||||
const response = await fetch(`${API_BASE_URL}api/fetchStep5Data_SilverBullets`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({ company, analyses, language }),
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP error! status: ${response.status}`);
|
||||
}
|
||||
return response.json();
|
||||
};
|
||||
|
||||
export const fetchStep6Data_Conclusion = async (company: AppState['company'], products: Product[], industries: TargetIndustry[], analyses: Analysis[], silver_bullets: SilverBullet[], language: 'de' | 'en'): Promise<{ conclusion: Conclusion }> => {
|
||||
const response = await fetch(`${API_BASE_URL}api/fetchStep6Data_Conclusion`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({ company, products, industries, analyses, silver_bullets, language }),
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP error! status: ${response.status}`);
|
||||
}
|
||||
return response.json();
|
||||
};
|
||||
|
||||
export const fetchStep7Data_Battlecards = async (company: AppState['company'], analyses: Analysis[], silver_bullets: SilverBullet[], language: 'de' | 'en'): Promise<{ battlecards: Battlecard[] }> => {
|
||||
const response = await fetch(`${API_BASE_URL}api/fetchStep7Data_Battlecards`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({ company, analyses, silver_bullets, language }),
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP error! status: ${response.status}`);
|
||||
}
|
||||
return response.json();
|
||||
};
|
||||
|
||||
export const fetchStep8Data_ReferenceAnalysis = async (competitors: ShortlistedCompetitor[], language: 'de' | 'en'): Promise<{ reference_analysis: ReferenceAnalysis[], groundingMetadata: any[] }> => {
|
||||
const response = await fetch(`${API_BASE_URL}api/fetchStep8Data_ReferenceAnalysis`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({ competitors, language }),
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error(`HTTP error! status: ${response.status}`);
|
||||
}
|
||||
return response.json();
|
||||
};
|
||||
179
competitor-analysis-app/services/pdfService.ts
Normal file
179
competitor-analysis-app/services/pdfService.ts
Normal file
@@ -0,0 +1,179 @@
|
||||
import type { AppState } from '../types';
|
||||
// @ts-ignore
|
||||
import { jsPDF } from "jspdf";
|
||||
import "jspdf-autotable";
|
||||
|
||||
const addWrappedText = (doc: any, text: string, x: number, y: number, maxWidth: number): number => {
|
||||
const lines = doc.splitTextToSize(text, maxWidth);
|
||||
doc.text(lines, x, y);
|
||||
// Approximate height of the text block based on font size and line height
|
||||
const fontSize = doc.getFontSize();
|
||||
const lineHeight = 1.15;
|
||||
return lines.length * fontSize * lineHeight / 2.8;
|
||||
};
|
||||
|
||||
export const generatePdfReport = async (appState: AppState, t: any) => {
|
||||
const doc = new jsPDF();
|
||||
const { company, analyses, silver_bullets, conclusion, battlecards, reference_analysis } = appState;
|
||||
const pageMargin = 15;
|
||||
const pageWidth = doc.internal.pageSize.getWidth();
|
||||
const contentWidth = pageWidth - 2 * pageMargin;
|
||||
let yPos = 20;
|
||||
|
||||
// Title Page
|
||||
doc.setFontSize(22);
|
||||
doc.setFont('helvetica', 'bold');
|
||||
doc.text(t.title, pageWidth / 2, yPos, { align: 'center' });
|
||||
yPos += 10;
|
||||
doc.setFontSize(16);
|
||||
doc.setFont('helvetica', 'normal');
|
||||
doc.text(company.name, pageWidth / 2, yPos, { align: 'center' });
|
||||
yPos += 15;
|
||||
|
||||
const addPageIfNeeded = (requiredHeight: number) => {
|
||||
if (yPos + requiredHeight > 280) { // 297mm height, 10mm margin bottom
|
||||
doc.addPage();
|
||||
yPos = 20;
|
||||
}
|
||||
};
|
||||
|
||||
const addHeader = (title: string) => {
|
||||
addPageIfNeeded(20);
|
||||
doc.setFontSize(14);
|
||||
doc.setFont('helvetica', 'bold');
|
||||
doc.text(title, pageMargin, yPos);
|
||||
yPos += 8;
|
||||
doc.setFont('helvetica', 'normal');
|
||||
doc.setFontSize(10);
|
||||
};
|
||||
|
||||
// Summary & Opportunities
|
||||
if (conclusion) {
|
||||
addHeader(t.summary);
|
||||
yPos += addWrappedText(doc, conclusion.summary, pageMargin, yPos, contentWidth);
|
||||
yPos += 5;
|
||||
|
||||
addHeader(t.opportunities);
|
||||
yPos += addWrappedText(doc, conclusion.opportunities, pageMargin, yPos, contentWidth);
|
||||
yPos += 10;
|
||||
}
|
||||
|
||||
// Analysis Details
|
||||
addHeader(t.step4_title);
|
||||
analyses.forEach(a => {
|
||||
addPageIfNeeded(40);
|
||||
doc.setFontSize(12);
|
||||
doc.setFont('helvetica', 'bold');
|
||||
doc.text(a.competitor.name, pageMargin, yPos);
|
||||
yPos += 6;
|
||||
doc.setFontSize(10);
|
||||
doc.setFont('helvetica', 'normal');
|
||||
|
||||
yPos += addWrappedText(doc, `Portfolio: ${a.portfolio.map(p => p.product).join(', ')}`, pageMargin + 5, yPos, contentWidth - 5);
|
||||
yPos += addWrappedText(doc, `Industries: ${a.target_industries.join(', ')}`, pageMargin + 5, yPos, contentWidth - 5);
|
||||
yPos += addWrappedText(doc, `Differentiators: ${a.differentiators.join('; ')}`, pageMargin + 5, yPos, contentWidth - 5);
|
||||
yPos += 5;
|
||||
});
|
||||
|
||||
// Silver Bullets
|
||||
addHeader(t.step5_title);
|
||||
silver_bullets.forEach(b => {
|
||||
addPageIfNeeded(15);
|
||||
yPos += addWrappedText(doc, `${t.against} ${b.competitor_name}: "${b.statement}"`, pageMargin, yPos, contentWidth);
|
||||
yPos += 2;
|
||||
});
|
||||
yPos += 5;
|
||||
|
||||
// Matrices
|
||||
if (conclusion) {
|
||||
const transformMatrix = (matrix: any[] | undefined, rowKeyName: 'product' | 'industry') => {
|
||||
if (!matrix || matrix.length === 0) return { head: [], body: [] };
|
||||
const allCompetitors = new Set<string>();
|
||||
matrix.forEach(row => (row.availability || []).forEach((item: any) => allCompetitors.add(item.competitor)));
|
||||
const head = [['', ...Array.from(allCompetitors).sort()]];
|
||||
const body = matrix.map(row => {
|
||||
const rowData: (string|any)[] = [row[rowKeyName]];
|
||||
head[0].slice(1).forEach(competitor => {
|
||||
const item = (row.availability || []).find((a: any) => a.competitor === competitor);
|
||||
rowData.push(item && item.has_offering ? '✓' : '');
|
||||
});
|
||||
return rowData;
|
||||
});
|
||||
return { head, body };
|
||||
};
|
||||
|
||||
if (conclusion.product_matrix) {
|
||||
addPageIfNeeded(50);
|
||||
addHeader(t.productMatrix);
|
||||
const { head, body } = transformMatrix(conclusion.product_matrix, 'product');
|
||||
(doc as any).autoTable({
|
||||
head: head, body: body, startY: yPos, theme: 'striped',
|
||||
headStyles: { fillColor: [65, 90, 119] }, margin: { left: pageMargin }
|
||||
});
|
||||
yPos = (doc as any).lastAutoTable.finalY + 10;
|
||||
}
|
||||
|
||||
if (conclusion.industry_matrix) {
|
||||
addPageIfNeeded(50);
|
||||
addHeader(t.industryMatrix);
|
||||
const { head, body } = transformMatrix(conclusion.industry_matrix, 'industry');
|
||||
(doc as any).autoTable({
|
||||
head: head, body: body, startY: yPos, theme: 'striped',
|
||||
headStyles: { fillColor: [65, 90, 119] }, margin: { left: pageMargin }
|
||||
});
|
||||
yPos = (doc as any).lastAutoTable.finalY + 10;
|
||||
}
|
||||
}
|
||||
|
||||
// Battlecards
|
||||
if (battlecards && battlecards.length > 0) {
|
||||
addHeader(t.step7_title);
|
||||
battlecards.forEach(card => {
|
||||
addPageIfNeeded(60);
|
||||
doc.setFontSize(12);
|
||||
doc.setFont('helvetica', 'bold');
|
||||
doc.text(`${t.against} ${card.competitor_name}`, pageMargin, yPos);
|
||||
yPos += 6;
|
||||
doc.setFontSize(10);
|
||||
doc.setFont('helvetica', 'normal');
|
||||
yPos += addWrappedText(doc, `${t.focus}: ${card.competitor_profile.focus}`, pageMargin + 5, yPos, contentWidth - 5);
|
||||
yPos += addWrappedText(doc, `${t.strengthsVsWeaknesses}:\n - ${(card.strengths_vs_weaknesses || []).join('\n - ')}`, pageMargin + 5, yPos, contentWidth - 5);
|
||||
yPos += addWrappedText(doc, `${t.landmineQuestions}:\n - ${(card.landmine_questions || []).join('\n - ')}`, pageMargin + 5, yPos, contentWidth - 5);
|
||||
yPos += addWrappedText(doc, `${t.silverBullet}: "${card.silver_bullet}"`, pageMargin + 5, yPos, contentWidth - 5);
|
||||
yPos += 8;
|
||||
});
|
||||
}
|
||||
|
||||
// References
|
||||
if (reference_analysis && reference_analysis.length > 0) {
|
||||
addPageIfNeeded(50);
|
||||
addHeader(t.step8_title);
|
||||
reference_analysis.forEach(analysis => {
|
||||
addPageIfNeeded(30);
|
||||
doc.setFontSize(12);
|
||||
doc.setFont('helvetica', 'bold');
|
||||
doc.text(analysis.competitor_name, pageMargin, yPos);
|
||||
yPos += 6;
|
||||
doc.setFontSize(10);
|
||||
doc.setFont('helvetica', 'normal');
|
||||
if ((analysis.references || []).length > 0) {
|
||||
(analysis.references || []).forEach(ref => {
|
||||
yPos += addWrappedText(doc, `${ref.name} (${ref.industry || 'N/A'}): "${ref.testimonial_snippet || ''}"`, pageMargin + 5, yPos, contentWidth - 5);
|
||||
});
|
||||
} else {
|
||||
yPos += addWrappedText(doc, t.noReferencesFound, pageMargin + 5, yPos, contentWidth - 5);
|
||||
}
|
||||
yPos += 5;
|
||||
});
|
||||
}
|
||||
|
||||
// Add footer with page numbers
|
||||
const pageCount = (doc as any).internal.getNumberOfPages();
|
||||
for (let i = 1; i <= pageCount; i++) {
|
||||
doc.setPage(i);
|
||||
doc.setFontSize(8);
|
||||
doc.text(`Page ${i} of ${pageCount}`, pageWidth - pageMargin, doc.internal.pageSize.getHeight() - 10, { align: 'right' });
|
||||
}
|
||||
|
||||
doc.save(`analysis_${company.name}.pdf`);
|
||||
};
|
||||
286
competitor-analysis-app/translations.ts
Normal file
286
competitor-analysis-app/translations.ts
Normal file
@@ -0,0 +1,286 @@
|
||||
export const translations = {
|
||||
de: {
|
||||
appTitle: "B2B Competitor Analysis Agent",
|
||||
restartAnalysis: "Analyse neustarten",
|
||||
nextStepButton: "Bestätigen & Nächster Schritt",
|
||||
companyCard: {
|
||||
title: "Ausgangsunternehmen",
|
||||
},
|
||||
inputForm: {
|
||||
title: "Wettbewerbsanalyse starten",
|
||||
subtitle: "Geben Sie die Website eines Unternehmens ein, um die Analyse zu beginnen.",
|
||||
startUrlLabel: "Start-URL des Unternehmens",
|
||||
maxCompetitorsLabel: "Max. Wettbewerber",
|
||||
marketScopeLabel: "Marktfokus",
|
||||
marketScopePlaceholder: "z.B. DACH, EU, global",
|
||||
languageLabel: "Sprache",
|
||||
submitButton: "Analyse starten",
|
||||
},
|
||||
loadingSpinner: {
|
||||
message: "AI analysiert, bitte warten...",
|
||||
},
|
||||
errors: {
|
||||
title: "Fehler:",
|
||||
step1: "Fehler bei der Analyse der Start-URL. Bitte überprüfen Sie die URL und versuchen Sie es erneut.",
|
||||
generic: (step: number) => `Ein Fehler ist in Schritt ${step} aufgetreten. Bitte versuchen Sie es erneut.`,
|
||||
},
|
||||
stepIndicator: {
|
||||
title: "Fortschritt",
|
||||
steps: ["Extraktion", "Keywords", "Wettbewerber", "Analyse", "Silver Bullets", "Fazit", "Battlecards", "Referenzen"],
|
||||
},
|
||||
step1: {
|
||||
title: "Schritt 1: Extraktion der Unternehmensinformationen",
|
||||
subtitle: "Überprüfen, bearbeiten oder ergänzen Sie die vom AI-Agenten extrahierten Produkte und Zielbranchen.",
|
||||
addProductTitle: "Neues Produkt per URL hinzufügen",
|
||||
productNameLabel: "Produktname",
|
||||
productUrlLabel: "Produkt-URL",
|
||||
productNamePlaceholder: "z.B. mobileX-Dispatch",
|
||||
addProductError: "Produkt konnte nicht recherchiert werden. Bitte URL überprüfen.",
|
||||
addButton: "Produkt hinzufügen",
|
||||
addingButton: "Recherchiere...",
|
||||
productsTitle: "Produkte / Lösungen",
|
||||
purposeLabel: "Zweckbeschreibung",
|
||||
industriesTitle: "Zielmärkte / Branchen",
|
||||
industryNameLabel: "Branchenname",
|
||||
editableCard: { add: "Hinzufügen", cancel: "Abbrechen", save: "Speichern" }
|
||||
},
|
||||
step2: {
|
||||
title: "Schritt 2: Abgeleitete Keywords",
|
||||
subtitle: "Überprüfen Sie die für die Wettbewerbssuche generierten Keywords und passen Sie sie bei Bedarf an.",
|
||||
cardTitle: "Keyword-Set",
|
||||
termLabel: "Keyword / Phrase",
|
||||
rationaleLabel: "Begründung",
|
||||
editableCard: { add: "Hinzufügen", cancel: "Abbrechen", save: "Speichern" }
|
||||
},
|
||||
step3: {
|
||||
title: "Schritt 3: Wettbewerber finden",
|
||||
subtitle: (max: number) => `Hier ist die Longlist potenzieller Wettbewerber. Entfernen oder ergänzen Sie Einträge. Die Top ${max} nach Konfidenz werden für die Detailanalyse in die Shortlist übernommen.`,
|
||||
cardTitle: "Wettbewerber-Kandidaten",
|
||||
nameLabel: "Name",
|
||||
whyLabel: "Begründung",
|
||||
visitButton: "Besuchen",
|
||||
shortlistBoundary: "SHORTLIST-GRENZE",
|
||||
editableCard: { add: "Hinzufügen", cancel: "Abbrechen", save: "Speichern" }
|
||||
},
|
||||
step4: {
|
||||
title: "Schritt 4: Portfolio- & Positionierungsanalyse",
|
||||
subtitle: "Detailanalyse der Shortlist-Wettbewerber. Die relevantesten (höchster Overlap) stehen oben.",
|
||||
downloadJson_title: "Analyse herunterladen",
|
||||
portfolio: "Produktportfolio",
|
||||
differentiators: "Alleinstellungsmerkmale",
|
||||
targetIndustries: "Zielbranchen & Modell",
|
||||
overlapScore: "Overlap Score",
|
||||
},
|
||||
step5: {
|
||||
title: "Schritt 5: Silver Bullets",
|
||||
generating: "Positionierungsaussagen werden generiert...",
|
||||
subtitle: "Dies sind prägnante Positionierungsaussagen, um Ihr Unternehmen im direkten Gespräch vom jeweiligen Wettbewerber abzugrenzen.",
|
||||
cardTitle: "Gegenüber",
|
||||
},
|
||||
step6: {
|
||||
title: "Schritt 6: Vergleich & Fazit",
|
||||
generating: "Fazit wird generiert...",
|
||||
subtitle: "Zusammenfassende Analyse und strategische Einordnung.",
|
||||
downloadButton: "Gesamtbericht laden",
|
||||
downloadJson: "JSON herunterladen",
|
||||
downloadMd: "Markdown (MD) herunterladen",
|
||||
downloadPdf: "PDF herunterladen",
|
||||
productMatrix: "Produkt-Matrix",
|
||||
industryMatrix: "Branchen-Matrix",
|
||||
summary: "Zusammenfassung & Positionierung",
|
||||
opportunities: (name: string) => `Chancen & Lücken für ${name}`,
|
||||
nextQuestions: "Nächste Fragen & Unsicherheiten",
|
||||
markdown: {
|
||||
title: "B2B Wettbewerbsanalyse",
|
||||
startUrl: "Start-URL",
|
||||
marketScope: "Marktfokus",
|
||||
step1_title: "Schritt 1: Extraktion",
|
||||
step1_products: "Produkte / Lösungen",
|
||||
step1_industries: "Zielbranchen",
|
||||
step4_title: "Schritt 4: Detaillierte Analyse",
|
||||
portfolio: "Portfolio",
|
||||
targetIndustries: "Zielbranchen",
|
||||
differentiators: "Alleinstellungsmerkmale",
|
||||
step5_title: "Schritt 5: Silver Bullets",
|
||||
against: "Gegen",
|
||||
step7_title: "Schritt 7: Sales Battlecards",
|
||||
profile: "Profil",
|
||||
focus: "Fokus",
|
||||
positioning: "Positionierung",
|
||||
strengthsVsWeaknesses: "Unsere Stärken vs. Ihre Schwächen",
|
||||
landmineQuestions: '"Landminen"-Fragen',
|
||||
silverBullet: "Silver Bullet",
|
||||
step8_title: "Schritt 8: Referenzkunden-Analyse",
|
||||
caseStudyLink: "Case Study Link",
|
||||
noReferencesFound: "Keine Referenzen gefunden.",
|
||||
sources: "Quellen für Referenz-Analyse",
|
||||
step6_title: "Schritt 6: Fazit",
|
||||
productMatrix: "Produkt-Matrix",
|
||||
industryMatrix: "Branchen-Matrix",
|
||||
summary: "Zusammenfassung & Positionierung",
|
||||
opportunities: "Chancen & Lücken",
|
||||
nextQuestions: "Nächste Fragen",
|
||||
}
|
||||
},
|
||||
step7: {
|
||||
title: "Schritt 7: Sales Battlecards",
|
||||
generating: "Battlecards werden generiert...",
|
||||
subtitle: "Nutzen Sie diese \"Battlecards\" zur Vorbereitung auf Vertriebsgespräche. Jede Karte fasst die wichtigsten Argumente gegen einen spezifischen Wettbewerber zusammen.",
|
||||
card: {
|
||||
profile: "Competitor Profile",
|
||||
strengths: "Our Strengths vs. Their Weaknesses",
|
||||
landmines: "\"Landmine\" Questions to Ask",
|
||||
silverBullet: "Silver Bullet",
|
||||
}
|
||||
},
|
||||
step8: {
|
||||
title: "Schritt 8: Referenzkunden-Analyse",
|
||||
subtitle: "Analyse der Testimonials und Case Studies der Wettbewerber, um deren Marktpräsenz und Erfolgsgeschichten zu verstehen. Die Ergebnisse basieren auf einer Google-Suche.",
|
||||
noReferencesFound: "Keine öffentlichen Referenzkunden auf der offiziellen Website gefunden.",
|
||||
caseStudyLink: "Case Study",
|
||||
sourcesTitle: "Recherche-Quellen",
|
||||
}
|
||||
},
|
||||
en: {
|
||||
appTitle: "B2B Competitor Analysis Agent",
|
||||
restartAnalysis: "Restart Analysis",
|
||||
nextStepButton: "Confirm & Next Step",
|
||||
companyCard: {
|
||||
title: "Initial Company",
|
||||
},
|
||||
inputForm: {
|
||||
title: "Start Competitor Analysis",
|
||||
subtitle: "Enter a company's website to begin the analysis.",
|
||||
startUrlLabel: "Company Start URL",
|
||||
maxCompetitorsLabel: "Max Competitors",
|
||||
marketScopeLabel: "Market Focus",
|
||||
marketScopePlaceholder: "e.g., DACH, EU, global",
|
||||
languageLabel: "Language",
|
||||
submitButton: "Start Analysis",
|
||||
},
|
||||
loadingSpinner: {
|
||||
message: "AI is analyzing, please wait...",
|
||||
},
|
||||
errors: {
|
||||
title: "Error:",
|
||||
step1: "Error analyzing the start URL. Please check the URL and try again.",
|
||||
generic: (step: number) => `An error occurred in step ${step}. Please try again.`,
|
||||
},
|
||||
stepIndicator: {
|
||||
title: "Progress",
|
||||
steps: ["Extraction", "Keywords", "Competitors", "Analysis", "Silver Bullets", "Conclusion", "Battlecards", "References"],
|
||||
},
|
||||
step1: {
|
||||
title: "Step 1: Company Information Extraction",
|
||||
subtitle: "Review, edit, or add to the products and target industries extracted by the AI agent.",
|
||||
addProductTitle: "Add New Product by URL",
|
||||
productNameLabel: "Product Name",
|
||||
productUrlLabel: "Product URL",
|
||||
productNamePlaceholder: "e.g., mobileX-Dispatch",
|
||||
addProductError: "Could not research product. Please check the URL.",
|
||||
addButton: "Add Product",
|
||||
addingButton: "Researching...",
|
||||
productsTitle: "Products / Solutions",
|
||||
purposeLabel: "Purpose Description",
|
||||
industriesTitle: "Target Markets / Industries",
|
||||
industryNameLabel: "Industry Name",
|
||||
editableCard: { add: "Add", cancel: "Cancel", save: "Save" }
|
||||
},
|
||||
step2: {
|
||||
title: "Step 2: Derived Keywords",
|
||||
subtitle: "Review and adjust the keywords generated for the competitor search if necessary.",
|
||||
cardTitle: "Keyword Set",
|
||||
termLabel: "Keyword / Phrase",
|
||||
rationaleLabel: "Rationale",
|
||||
editableCard: { add: "Add", cancel: "Cancel", save: "Save" }
|
||||
},
|
||||
step3: {
|
||||
title: "Step 3: Find Competitors",
|
||||
subtitle: (max: number) => `Here is the longlist of potential competitors. Remove or add entries. The top ${max} by confidence will be shortlisted for detailed analysis.`,
|
||||
cardTitle: "Competitor Candidates",
|
||||
nameLabel: "Name",
|
||||
whyLabel: "Justification",
|
||||
visitButton: "Visit",
|
||||
shortlistBoundary: "SHORTLIST BOUNDARY",
|
||||
editableCard: { add: "Add", cancel: "Cancel", save: "Save" }
|
||||
},
|
||||
step4: {
|
||||
title: "Step 4: Portfolio & Positioning Analysis",
|
||||
subtitle: "Detailed analysis of the shortlisted competitors. The most relevant (highest overlap) are at the top.",
|
||||
downloadJson_title: "Download Analysis",
|
||||
portfolio: "Product Portfolio",
|
||||
differentiators: "Differentiators",
|
||||
targetIndustries: "Target Industries & Model",
|
||||
overlapScore: "Overlap Score",
|
||||
},
|
||||
step5: {
|
||||
title: "Step 5: Silver Bullets",
|
||||
generating: "Generating positioning statements...",
|
||||
subtitle: "These are concise positioning statements to differentiate your company from each competitor in direct conversation.",
|
||||
cardTitle: "Against",
|
||||
},
|
||||
step6: {
|
||||
title: "Step 6: Comparison & Conclusion",
|
||||
generating: "Generating conclusion...",
|
||||
subtitle: "Summary analysis and strategic classification.",
|
||||
downloadButton: "Download Full Report",
|
||||
downloadJson: "Download JSON",
|
||||
downloadMd: "Download Markdown (MD)",
|
||||
downloadPdf: "Download PDF",
|
||||
productMatrix: "Product Matrix",
|
||||
industryMatrix: "Industry Matrix",
|
||||
summary: "Summary & Positioning",
|
||||
opportunities: (name: string) => `Opportunities & Gaps for ${name}`,
|
||||
nextQuestions: "Next Questions & Uncertainties",
|
||||
markdown: {
|
||||
title: "B2B Competitor Analysis",
|
||||
startUrl: "Start URL",
|
||||
marketScope: "Market Focus",
|
||||
step1_title: "Step 1: Extraction",
|
||||
step1_products: "Products / Solutions",
|
||||
step1_industries: "Target Industries",
|
||||
step4_title: "Step 4: Detailed Analysis",
|
||||
portfolio: "Portfolio",
|
||||
targetIndustries: "Target Industries",
|
||||
differentiators: "Differentiators",
|
||||
step5_title: "Step 5: Silver Bullets",
|
||||
against: "Against",
|
||||
step7_title: "Step 7: Sales Battlecards",
|
||||
profile: "Profile",
|
||||
focus: "Focus",
|
||||
positioning: "Positioning",
|
||||
strengthsVsWeaknesses: "Our Strengths vs. Their Weaknesses",
|
||||
landmineQuestions: '"Landmine" Questions',
|
||||
silverBullet: "Silver Bullet",
|
||||
step8_title: "Step 8: Reference Customer Analysis",
|
||||
caseStudyLink: "Case Study Link",
|
||||
noReferencesFound: "No references found.",
|
||||
sources: "Sources for Reference Analysis",
|
||||
step6_title: "Step 6: Conclusion",
|
||||
productMatrix: "Product Matrix",
|
||||
industryMatrix: "Industry Matrix",
|
||||
summary: "Summary & Positioning",
|
||||
opportunities: "Opportunities & Gaps",
|
||||
nextQuestions: "Next Questions",
|
||||
}
|
||||
},
|
||||
step7: {
|
||||
title: "Step 7: Sales Battlecards",
|
||||
generating: "Generating battlecards...",
|
||||
subtitle: "Use these \"Battlecards\" to prepare for sales conversations. Each card summarizes the key arguments against a specific competitor.",
|
||||
card: {
|
||||
profile: "Competitor Profile",
|
||||
strengths: "Our Strengths vs. Their Weaknesses",
|
||||
landmines: "\"Landmine\" Questions to Ask",
|
||||
silverBullet: "Silver Bullet",
|
||||
}
|
||||
},
|
||||
step8: {
|
||||
title: "Step 8: Reference Customer Analysis",
|
||||
subtitle: "Analysis of competitor testimonials and case studies to understand their market presence and success stories. The results are based on a Google search.",
|
||||
noReferencesFound: "No public reference customers found on the official website.",
|
||||
caseStudyLink: "Case Study",
|
||||
sourcesTitle: "Research Sources",
|
||||
}
|
||||
}
|
||||
};
|
||||
120
competitor-analysis-app/types.ts
Normal file
120
competitor-analysis-app/types.ts
Normal file
@@ -0,0 +1,120 @@
|
||||
|
||||
|
||||
export interface Evidence {
|
||||
url: string;
|
||||
snippet: string;
|
||||
}
|
||||
|
||||
export interface Product {
|
||||
name: string;
|
||||
purpose: string;
|
||||
evidence: Evidence[];
|
||||
}
|
||||
|
||||
export interface TargetIndustry {
|
||||
name: string;
|
||||
evidence: Evidence[];
|
||||
}
|
||||
|
||||
export interface Keyword {
|
||||
term: string;
|
||||
rationale: string;
|
||||
}
|
||||
|
||||
export interface CompetitorCandidate {
|
||||
name: string;
|
||||
url: string;
|
||||
confidence: number;
|
||||
why: string;
|
||||
evidence: Evidence[];
|
||||
}
|
||||
|
||||
export interface ShortlistedCompetitor {
|
||||
name: string;
|
||||
url: string;
|
||||
}
|
||||
|
||||
export interface Analysis {
|
||||
competitor: {
|
||||
name: string;
|
||||
url: string;
|
||||
};
|
||||
portfolio: {
|
||||
product: string;
|
||||
purpose: string;
|
||||
}[];
|
||||
target_industries: string[];
|
||||
delivery_model: string;
|
||||
overlap_score: number;
|
||||
differentiators: string[];
|
||||
evidence: Evidence[];
|
||||
}
|
||||
|
||||
export interface SilverBullet {
|
||||
competitor_name: string;
|
||||
statement: string;
|
||||
}
|
||||
|
||||
export interface Conclusion {
|
||||
product_matrix: {
|
||||
product: string;
|
||||
availability: { competitor: string; has_offering: boolean; }[];
|
||||
}[];
|
||||
industry_matrix: {
|
||||
industry: string;
|
||||
availability: { competitor: string; has_offering: boolean; }[];
|
||||
}[];
|
||||
overlap_scores: { competitor: string; score: number }[];
|
||||
summary: string;
|
||||
opportunities: string;
|
||||
next_questions: string[];
|
||||
}
|
||||
|
||||
export interface Battlecard {
|
||||
competitor_name: string;
|
||||
competitor_profile: {
|
||||
focus: string;
|
||||
positioning: string;
|
||||
};
|
||||
strengths_vs_weaknesses: string[];
|
||||
landmine_questions: string[];
|
||||
silver_bullet: string;
|
||||
}
|
||||
|
||||
export interface ReferenceCustomer {
|
||||
name: string;
|
||||
industry: string;
|
||||
testimonial_snippet: string;
|
||||
case_study_url: string;
|
||||
}
|
||||
|
||||
export interface ReferenceAnalysis {
|
||||
competitor_name: string;
|
||||
references: ReferenceCustomer[];
|
||||
}
|
||||
|
||||
|
||||
export interface AppState {
|
||||
step: number;
|
||||
initial_params: {
|
||||
start_url: string;
|
||||
max_competitors: number;
|
||||
market_scope: string;
|
||||
language: 'de' | 'en';
|
||||
};
|
||||
company: {
|
||||
name: string;
|
||||
start_url: string;
|
||||
};
|
||||
products: Product[];
|
||||
target_industries: TargetIndustry[];
|
||||
keywords: Keyword[];
|
||||
competitor_candidates: CompetitorCandidate[];
|
||||
competitors_shortlist: ShortlistedCompetitor[];
|
||||
analyses: Analysis[];
|
||||
silver_bullets: SilverBullet[];
|
||||
conclusion: Conclusion | null;
|
||||
battlecards: Battlecard[];
|
||||
reference_analysis: ReferenceAnalysis[];
|
||||
reference_analysis_grounding: any[];
|
||||
}
|
||||
24
competitor-analysis-app/vite.config.ts
Normal file
24
competitor-analysis-app/vite.config.ts
Normal file
@@ -0,0 +1,24 @@
|
||||
import path from 'path';
|
||||
import { defineConfig, loadEnv } from 'vite';
|
||||
import react from '@vitejs/plugin-react';
|
||||
|
||||
export default defineConfig(({ mode }) => {
|
||||
const env = loadEnv(mode, '.', '');
|
||||
return {
|
||||
base: './', // WICHTIG für Sub-Pfad Deployment
|
||||
server: {
|
||||
port: 3000,
|
||||
host: '0.0.0.0',
|
||||
},
|
||||
plugins: [react()],
|
||||
define: {
|
||||
'process.env.API_KEY': JSON.stringify(env.GEMINI_API_KEY),
|
||||
'process.env.GEMINI_API_KEY': JSON.stringify(env.GEMINI_API_KEY)
|
||||
},
|
||||
resolve: {
|
||||
alias: {
|
||||
'@': path.resolve(__dirname, '.'),
|
||||
}
|
||||
}
|
||||
};
|
||||
});
|
||||
@@ -16,7 +16,8 @@ services:
|
||||
- dashboard
|
||||
- b2b-app
|
||||
- market-frontend
|
||||
- company-explorer # NEW
|
||||
- company-explorer
|
||||
- competitor-analysis
|
||||
|
||||
# --- DASHBOARD (Landing Page) ---
|
||||
dashboard:
|
||||
@@ -128,6 +129,23 @@ services:
|
||||
- PYTHONUNBUFFERED=1
|
||||
- DB_PATH=/app/gtm_projects.db
|
||||
|
||||
# --- COMPETITOR ANALYSIS AGENT ---
|
||||
competitor-analysis:
|
||||
build:
|
||||
context: ./competitor-analysis-app
|
||||
dockerfile: Dockerfile
|
||||
container_name: competitor-analysis
|
||||
restart: unless-stopped
|
||||
volumes:
|
||||
# Sideloading: Python Orchestrator
|
||||
- ./competitor-analysis-app/competitor_analysis_orchestrator.py:/app/competitor_analysis_orchestrator.py
|
||||
# Keys (passed via environment or file)
|
||||
- ./gemini_api_key.txt:/app/gemini_api_key.txt
|
||||
environment:
|
||||
- PYTHONUNBUFFERED=1
|
||||
- GEMINI_API_KEY_FILE=/app/gemini_api_key.txt
|
||||
# Port 8000 is internal only
|
||||
|
||||
# --- DUCKDNS UPDATER ---
|
||||
duckdns:
|
||||
image: lscr.io/linuxserver/duckdns:latest
|
||||
|
||||
@@ -87,5 +87,20 @@ http {
|
||||
proxy_connect_timeout 1200s;
|
||||
proxy_send_timeout 1200s;
|
||||
}
|
||||
|
||||
location /ca/ {
|
||||
# Competitor Analysis Agent
|
||||
# Der Trailing Slash am Ende ist wichtig!
|
||||
proxy_pass http://competitor-analysis:8000/;
|
||||
proxy_set_header Host $host;
|
||||
proxy_set_header X-Real-IP $remote_addr;
|
||||
proxy_set_header Upgrade $http_upgrade;
|
||||
proxy_set_header Connection "upgrade";
|
||||
|
||||
# Explicit timeouts
|
||||
proxy_read_timeout 1200s;
|
||||
proxy_connect_timeout 1200s;
|
||||
proxy_send_timeout 1200s;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user