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CorporateChatAPI

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NujacsaintS commited on Nov 19, 2025

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76dad5b

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1 Parent(s): 31decff

Update app.py

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app.py +183 -1

app.py CHANGED Viewed

@@ -83,4 +83,186 @@ async def call_llm(message: str, context: Dict[str, str] | None = None) -> tuple
     text-generation endpoint. If LLM_URL is not set, it falls back to a local echo.
     """
-    # Fallback so the b

     text-generation endpoint. If LLM_URL is not set, it falls back to a local echo.
     """
+    # Fallback so the bridge still works even if you haven't configured the model yet
+    if not LLM_URL:
+        reply = f"[stub] Echo: {message}"
+        tokens_used = len(message)
+        return reply, tokens_used
+    # Basic prompt construction. You can get fancier later.
+    prompt = message
+    if context:
+        # Simple way to inject context: a header line then the message.
+        ctx_str = "; ".join(f"{k}={v}" for k, v in context.items())
+        prompt = f"[context: {ctx_str}]\n\n{message}"
+    headers = {}
+    if LLM_KEY:
+        # Hugging Face style: "Bearer <token>"
+        headers["Authorization"] = f"Bearer {LLM_KEY}"
+    payload = {
+        "inputs": prompt,
+        # Optional: adjust parameters to your model
+        "parameters": {
+            "max_new_tokens": 256,
+            "temperature": 0.3,
+            "do_sample": False,
+        }
+    }
+    async with httpx.AsyncClient(timeout=60.0) as client:
+        resp = await client.post(LLM_URL, headers=headers, json=payload)
+        resp.raise_for_status()
+        data = resp.json()
+    # Hugging Face text-generation outputs are usually a list of dicts with "generated_text"
+    # Adjust here if your model returns a different shape.
+    if isinstance(data, list) and data and "generated_text" in data[0]:
+        full_text = data[0]["generated_text"]
+        # Heuristic: reply is the part after the original prompt
+        reply = full_text[len(prompt) :].strip() or full_text.strip()
+    else:
+        # Fallback: just stringify whatever we got
+        reply = str(data)
+    # Approx token count: you can replace this with a real tokenizer later
+    tokens_used = len(reply.split())
+    return reply, tokens_used
+# -----------------------------
+# API endpoints
+# -----------------------------
+@app.post("/v1/chat", response_model=ChatResponse)
+async def chat_endpoint(payload: ChatRequest):
+    reply, tokens_used = await call_llm(payload.message, payload.context)
+    record_request(payload.session_id, tokens_used)
+    return ChatResponse(
+        session_id=payload.session_id,
+        reply=reply,
+        tokens_used=tokens_used,
+    )
+@app.get("/health")
+async def health():
+    return JSONResponse(
+        {
+            "status": "ok",
+            "total_requests": metrics["total_requests"],
+            "total_tokens": metrics["total_tokens"],
+            "active_sessions_5m": count_active_sessions(300),
+        }
+    )
+@app.get("/admin", response_class=HTMLResponse)
+async def admin_dashboard():
+    active_5m = count_active_sessions(300)
+    rows = []
+    for sid, s in metrics["sessions"].items():
+        last_seen = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(s["last_seen"]))
+        rows.append(
+            f"<tr>"
+            f"<td>{sid}</td>"
+            f"<td>{s['requests']}</td>"
+            f"<td>{s['tokens']}</td>"
+            f"<td>{last_seen}</td>"
+            f"</tr>"
+        )
+    rows_html = "\n".join(rows) if rows else "<tr><td colspan='4'>No sessions yet</td></tr>"
+    html = f"""
+    <!doctype html>
+    <html>
+    <head>
+        <title>Tessai LLM Admin</title>
+        <meta charset="utf-8" />
+        <style>
+            body {{
+                font-family: system-ui, sans-serif;
+                margin: 20px;
+            }}
+            h1, h2 {{
+                margin-bottom: 0.2rem;
+            }}
+            .metrics {{
+                display: flex;
+                gap: 1.5rem;
+                margin-bottom: 1.5rem;
+            }}
+            .metric-card {{
+                padding: 1rem 1.5rem;
+                border-radius: 8px;
+                border: 1px solid #ddd;
+                box-shadow: 0 1px 3px rgba(0,0,0,0.05);
+            }}
+            table {{
+                border-collapse: collapse;
+                width: 100%;
+            }}
+            th, td {{
+                border: 1px solid #ddd;
+                padding: 8px;
+                font-size: 0.9rem;
+            }}
+            th {{
+                background: #f4f4f4;
+                text-align: left;
+            }}
+        </style>
+    </head>
+    <body>
+        <h1>Tessai LLM Bridge</h1>
+        <p>Simple meter board for current traffic.</p>
+        <div class="metrics">
+            <div class="metric-card">
+                <h2>Total requests</h2>
+                <p>{metrics["total_requests"]}</p>
+            </div>
+            <div class="metric-card">
+                <h2>Total tokens (approx)</h2>
+                <p>{metrics["total_tokens"]}</p>
+            </div>
+            <div class="metric-card">
+                <h2>Active sessions (last 5 min)</h2>
+                <p>{active_5m}</p>
+            </div>
+        </div>
+        <h2>Sessions</h2>
+        <table>
+            <thead>
+                <tr>
+                    <th>Session ID</th>
+                    <th>Requests</th>
+                    <th>Tokens</th>
+                    <th>Last seen</th>
+                </tr>
+            </thead>
+            <tbody>
+                {rows_html}
+            </tbody>
+        </table>
+    </body>
+    </html>
+    """
+    return HTMLResponse(content=html)
+# -----------------------------
+# Local dev entrypoint
+# -----------------------------
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run("app:app", host="0.0.0.0", port=8000, reload=True)