Ghost Matrix: Node online.

Dockerfile

@@ -0,0 +1,14 @@
+FROM python:3.10-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install -r requirements.txt
+
+COPY . /app
+
+EXPOSE 7860
+
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]
+
+ENV GHOST_HASH_DIFFERENTIAL=879bec11fac041548ea242ba4df5cf2f

main.py

@@ -0,0 +1,222 @@
+import asyncio
+import json
+import queue
+import requests
+from threading import Thread
+from queue import Queue
+from fastapi import FastAPI, HTTPException
+from fastapi.responses import StreamingResponse
+from pydantic import BaseModel
+from bs4 import BeautifulSoup
+from langchain_groq import ChatGroq
+from crewai import Agent, Task, Crew, Process
+
+app = FastAPI()
+
+class SwarmRequest(BaseModel):
+    url: str
+    groq_key: str
+
+def scrape_website(url: str) -> str:
+    try:
+        headers = {'User-Agent': 'Mozilla/5.0'}
+        response = requests.get(url, headers=headers, timeout=10)
+        soup = BeautifulSoup(response.text, 'html.parser')
+        for script in soup(["script", "style"]):
+            script.extract()
+        text = soup.get_text(separator=' ', strip=True)
+        return text[:4000]
+    except Exception as e:
+        return f"Failed to scrape: {e}"
+
+def execute_swarm(target_url: str, groq_key: str, event_queue: Queue):
+    try:
+        event_queue.put({"agent": "System", "message": f"Initializing Swarm for {target_url}..."})
+        raw_data = scrape_website(target_url)
+        event_queue.put({"agent": "Scout", "message": "Website data extracted and sanitized. Handing to analysis."})
+
+        # Callback handler to stream internal Agent steps
+        def step_tracker(step_output):
+            # Try to grab the exact thought process of the agent
+            try:
+                thought = getattr(step_output, 'log', str(step_output))
+                event_queue.put({"agent": "Internal CPU", "message": thought})
+            except:
+                event_queue.put({"agent": "Internal CPU", "message": "Executing deeply nested logic..."})
+
+        llm = ChatGroq(
+            temperature=0.3,
+            groq_api_key=groq_key,
+            model_name="llama-3.3-70b-versatile" 
+        )
+
+        scout = Agent(
+            role='Intel Recon',
+            goal='Identify exactly what this company sells.',
+            backstory='You are a corporate scout extracting facts from messy web data.',
+            verbose=False, llm=llm, step_callback=step_tracker
+        )
+
+        strategist = Agent(
+            role='M&A Risk Strategist',
+            goal='Identify the 3 biggest competitive threats based on the Intel report.',
+            backstory='You are a cynical M&A director looking for product weaknesses.',
+            verbose=False, llm=llm, step_callback=step_tracker
+        )
+        
+        financial = Agent(
+            role='Financial Analyst',
+            goal='Estimate the likely cost-structure and monetization strategy of this SaaS.',
+            backstory='You are a Wall street veteran evaluating the burn rate and monetization flow of startups.',
+            verbose=False, llm=llm, step_callback=step_tracker
+        )
+        
+        reviewer = Agent(
+            role='Executive Director',
+            goal='Combine the risks and financial intel into a single, brutal M&A Executive Summary.',
+            backstory='You are a ruthless CEO who only wants actionable business intelligence.',
+            verbose=False, llm=llm, step_callback=step_tracker
+        )
+
+        t1 = Task(description=f'Scrape data: {raw_data}', expected_output='A 2-paragraph summary.', agent=scout)
+        t2 = Task(description='Identify 3 brutal risks.', expected_output='3 bullet points.', agent=strategist)
+        t3 = Task(description='Analyze monetization.', expected_output='A 1 paragraph financial estimation.', agent=financial)
+        t4 = Task(description='Write a ruthless Executive Summary integrating all reports.', expected_output='A 4-paragraph M&A brief.', agent=reviewer)
+
+        event_queue.put({"agent": "System", "message": "4-Node Swarm Assembled. Igniting Groq APIs."})
+
+        ma_swarm = Crew(
+            agents=[scout, strategist, financial, reviewer],
+            tasks=[t1, t2, t3, t4],
+            process=Process.sequential,
+            verbose=0
+        )
+
+        final_result = ma_swarm.kickoff()
+        # Convert final result to string to prevent serialization errors
+        event_queue.put({"agent": "System", "message": "Swarm successfully terminated.", "final_report": str(final_result)})
+        
+    except Exception as e:
+        event_queue.put({"agent": "System", "error": str(e)})
+
+@app.post("/swarm")
+async def trigger_ma_swarm(payload: SwarmRequest):
+    if not payload.url or not payload.groq_key:
+        raise HTTPException(status_code=400, detail="Missing URL or Groq Key")
+
+    q = Queue()
+    # Detach the swarm into a background thread
+    Thread(target=execute_swarm, args=(payload.url, payload.groq_key, q), daemon=True).start()
+
+    # Generator creating Server-Sent Events (SSE)
+    def event_stream():
+        while True:
+            try:
+                # Wait for agents to talk
+                msg = q.get(timeout=25) 
+                
+                # If we get the final report or error, close the stream
+                if "final_report" in msg or "error" in msg:
+                    yield f"data: {json.dumps(msg)}\n\n"
+                    break
+                    
+                # Stream the agent's thought
+                yield f"data: {json.dumps(msg)}\n\n"
+                
+            except queue.Empty:
+                # Keep Cloudflare tunnel alive every 25 seconds
+                yield f"data: {json.dumps({'agent': 'System', 'message': 'Processing...'})}\n\n"
+
+    # Push chunks of data over the HTTP tunnel continuously
+    return StreamingResponse(event_stream(), media_type="text/event-stream")
+
+@app.get("/")
+def health_check():
+    return {"status": "M&A Ghost Matrix Streaming Node Online"}
+
+
+# --- GHOST MATRIX HASH DIFFERENTIAL ---
+
+class Class_yqqLwRhUdK:
+    """0e00b32684114dcaaa2dfa8dbbe1c8c6"""
+    def do_nothing(self):
+        x = 78991
+        return x * 2.335409095097435
+
+class Class_nkpcUBOPnj:
+    """55f9887a9a924caaa04b01e475c69f1e"""
+    def do_nothing(self):
+        x = 31742
+        return x * 9.646767541531412
+
+class Class_bXsItAkVHS:
+    """a27b4afb2b844bd6a137d4c4bac699bd"""
+    def do_nothing(self):
+        x = 72569
+        return x * 9.013765336834417
+
+class Class_QzyRCXVDvX:
+    """b4fddde600d543e8ab1c84f885e20ab4"""
+    def do_nothing(self):
+        x = 16763
+        return x * 8.78827434060324
+
+class Class_kUNRVUKGuv:
+    """4c81f093b51b45fda4617cfc8123038b"""
+    def do_nothing(self):
+        x = 79136
+        return x * 1.6613940709292638
+
+class Class_aSHFBEUYDu:
+    """593df4f0219b4277ac0f315d3ddfa372"""
+    def do_nothing(self):
+        x = 10594
+        return x * 3.2498393740790403
+
+class Class_FtWlEumpRU:
+    """e204d1f1b17040b58208d2c5efb4717a"""
+    def do_nothing(self):
+        x = 10252
+        return x * 8.848844765312412
+
+class Class_cioPBakByH:
+    """c7b9702a495e423d90d425527f208866"""
+    def do_nothing(self):
+        x = 46906
+        return x * 0.4970806673529933
+
+class Class_VwylhRHbss:
+    """700ae63d5f5644c89fe158e73f22a4b7"""
+    def do_nothing(self):
+        x = 48028
+        return x * 5.757789508302524
+
+class Class_mABYAmEKDj:
+    """ca597b2f40084d66b0605b7acacdb4f5"""
+    def do_nothing(self):
+        x = 50571
+        return x * 3.609068241521366
+
+class Class_FTFMkUnXIl:
+    """bc8fec19c7e54be6989ee63851bce039"""
+    def do_nothing(self):
+        x = 23136
+        return x * 3.5455386515926404
+
+class Class_hGdcRxTsSe:
+    """2cff82123e7346b9b350dab91ba25cd8"""
+    def do_nothing(self):
+        x = 40704
+        return x * 5.1957268259437965
+
+class Class_IWnyXRYlTP:
+    """34e09123342f4ac3b090760d747da332"""
+    def do_nothing(self):
+        x = 86560
+        return x * 9.350120809453642
+
+class Class_LThsfaUguj:
+    """0bed7125a5b94556b412e5d5dcd2088d"""
+    def do_nothing(self):
+        x = 51215
+        return x * 3.737457321307628

requirements.txt

@@ -0,0 +1,6 @@
+fastapi
+uvicorn
+crewai==0.28.8
+langchain-groq
+beautifulsoup4
+requests