This commit is contained in:
2025-10-16 00:50:12 -03:00
parent 9d4db61af9
commit 06b1c17d5d
3 changed files with 481 additions and 1 deletions

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@@ -284,7 +284,7 @@ def _norm(s: str) -> str:
@mcp.tool()
async def find_compartment(query_text: str) -> dict:
"""
Find compartment ocid by the name
Find compartment ocid by the name, the compartment ocid is the identifier field
"""
structured = f"query compartment resources where displayName =~ '.*{query_text}*.'"
code, out, err = oci_cli.run(["search","resource","structured-search","--query-text", structured])

143
files/templates/chat.html Normal file
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@@ -0,0 +1,143 @@
<!DOCTYPE html>
<html lang="pt-BR">
<head>
<meta charset="UTF-8">
<title>OCI WebChat</title>
<script src="https://unpkg.com/htmx.org@1.9.9"></script>
<style>
body {
font-family: Arial, sans-serif;
background: #f4f6f9;
display: flex;
flex-direction: column;
align-items: center;
margin: 0;
padding: 20px;
}
h2 {
font-size: 28px;
margin-bottom: 20px;
color: #333;
}
#chatbox {
border: 2px solid #ccc;
border-radius: 12px;
background: #fff;
padding: 15px;
width: 90%;
max-width: 900px;
height: 500px;
overflow-y: auto;
font-size: 20px;
line-height: 1.6;
}
.message-user {
background: #d1e7ff;
color: #003366;
padding: 12px 18px;
border-radius: 12px;
margin: 10px 0;
max-width: 80%;
align-self: flex-end;
font-size: 20px;
}
.message-bot {
background: #e8f5e9;
color: #1b5e20;
padding: 12px 18px;
border-radius: 12px;
margin: 10px 0;
max-width: 80%;
align-self: flex-start;
font-size: 20px;
}
form {
display: flex;
flex-direction: column;
margin-top: 20px;
width: 90%;
max-width: 900px;
}
textarea {
font-size: 20px;
padding: 15px;
border-radius: 10px;
border: 2px solid #bbb;
resize: none;
height: 100px;
margin-bottom: 15px;
outline: none;
transition: border 0.3s;
}
textarea:focus {
border-color: #007bff;
}
button {
font-size: 22px;
font-weight: bold;
padding: 15px;
border: none;
border-radius: 10px;
background: #007bff;
color: white;
cursor: pointer;
transition: background 0.3s, transform 0.1s;
}
button:hover {
background: #0056b3;
}
.htmx-request button {
background: #ff9800 !important;
animation: blink 1s infinite;
}
@keyframes blink {
0%, 100% { opacity: 1; }
50% { opacity: 0.5; }
}
#loading {
font-size: 20px;
color: #ff5722;
margin-top: 10px;
text-align: center;
display: none;
}
.htmx-request #loading {
display: block;
}
</style>
</head>
<body>
<h2>💻 OCI WebChat</h2>
<div id="chatbox"></div>
<script>
document.getElementById("chat-form").addEventListener("submit", function() {
const textarea = document.getElementById("userInput");
setTimeout(() => { textarea.value = ""; }, 100); // delete immediately after sending
});
</script>
<form id="chat-form"
hx-post="/send"
hx-target="#chatbox"
hx-swap="beforeend"
hx-indicator="#loading"
hx-on::after-request="this.reset()">
<textarea id="userInput" name="message" placeholder="Type your message..." required></textarea>
<button id="sendBtn" type="submit">Send</button>
<div id="loading" class="htmx-indicator">⏳ Processing...</div>
</form>
</body>
</html>

337
files/webchat.py Normal file
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@@ -0,0 +1,337 @@
# -*- coding: utf-8 -*-
import os
import sys
import json
import asyncio
from flask import Flask, render_template, request
from markupsafe import Markup
import re
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage, AIMessage
from langchain_community.chat_models.oci_generative_ai import ChatOCIGenAI
from langgraph.prebuilt import create_react_agent
from langchain_mcp_adapters.client import MultiServerMCPClient
# ----------------------------
# CONFIG
# ----------------------------
with open("./config", "r") as f:
config_data = json.load(f)
app = Flask(__name__)
# ----------------------------
# MEMORY STATE
# ----------------------------
class MemoryState:
def __init__(self):
self.messages = []
self.parameters = {
"compartment_id": None,
"subnet_id": None,
"availability_domain": None,
"image_id": None,
"shape": None,
"ocpus": None,
"memoryInGBs": None,
"display_name": None,
}
self.candidates = {} # <- novo
memory_state = MemoryState()
def safe_json_extract(text: str):
try:
match = re.search(r"\{.*\}", text, re.DOTALL)
if match:
cleaned = match.group(0).strip()
# If the JSON comes truncated (missing closing braces)
if cleaned.count("{") > cleaned.count("}"):
cleaned += "}" * (cleaned.count("{") - cleaned.count("}"))
print("⚠️ JSON truncated, added closing brace(s).")
return json.loads(cleaned)
except Exception as e:
print("⚠️ Failed to parse JSON:", e)
return None
def sanitize_json(text: str):
"""
Try to fix and parse malformed JSON from LLM responses.
"""
if not text:
return None
# Removes extra spaces/lines
cleaned = text.strip()
# If text comes outside of JSON, extract only the object
match = re.search(r'\{.*\}', cleaned, re.DOTALL)
if match:
cleaned = match.group(0)
# Remove commas before closing object/array
cleaned = re.sub(r',(\s*[}\]])', r'\1', cleaned)
# Balance brackets []
open_brackets = cleaned.count('[')
close_brackets = cleaned.count(']')
if open_brackets > close_brackets:
cleaned += "]" * (open_brackets - close_brackets)
elif close_brackets > open_brackets:
# remove extra brackets at the end
cleaned = cleaned.rstrip("]")
# Balance braces {}
open_braces = cleaned.count('{')
close_braces = cleaned.count('}')
if open_braces > close_braces:
cleaned += "}" * (open_braces - close_braces)
elif close_braces > open_braces:
# removes leftover keys at the end
cleaned = cleaned.rstrip("}")
try:
return json.loads(cleaned)
except Exception as e:
print("⚠️ Still invalid after sanitization:", e)
print("🔎 Sanitized content:", cleaned[:500])
print("🔎 Original:", text)
return None
def validate_payload(params):
"""Checks if all mandatory parameters are filled in"""
required = ["compartment_id", "subnet_id", "availability_domain",
"image_id", "shape", "ocpus", "memoryInGBs", "display_name"]
missing = [r for r in required if not params.get(r)]
return missing
def check_truncation(response: dict):
"""
VChecks if the response was truncated due to token limit.
The object returned by OCI Generative AI contains token usage.
"""
try:
usage = response.get("usage", {})
if usage:
completion_tokens = usage.get("completion_tokens", 0)
max_allowed = llm.model_kwargs.get("max_tokens", 0)
if completion_tokens >= max_allowed:
print("⚠️ Response possibly truncated by max_tokens.")
return True
except Exception:
pass
return False
# ----------------------------
# LLM
# ----------------------------
llm = ChatOCIGenAI(
model_id="cohere.command-r-08-2024",
service_endpoint=config_data["llm_endpoint"],
compartment_id=config_data["compartment_id"],
auth_profile=config_data["oci_profile"],
model_kwargs={"temperature": 0.1, "top_p": 0.75, "max_tokens": 4000}
)
# ----------------------------
# PROMPT
# ----------------------------
system_text = """
You are an **OCI Operations Agent** with access to MCP tools (server `oci-ops`).
Your job is to provision and manage OCI resources without requiring the user to know OCIDs.
No need to provide an SSH key — the `oci-ops` server already has it configured.
====================
## TOOLS
- `create_compute_instance` → Create a new Compute instance
- `resolve_image` / `list_images` → Resolve or list images
- `resolve_shape` / `list_shapes` → Resolve or list shapes
- `find_subnet` → Find subnet
- `find_compartment` → Find compartment
- `find_ad` / `list_availability_domains` → Resolve or list availability domains
- `oci_cli_passthrough` → Run raw OCI CLI (expert use only)
====================
## RULES
- Parameters: compartment_id, subnet_id, availability_domain, image_id, shape, ocpus, memoryInGBs, display_name.
- Use **snake_case** for parameters at all times.
- Only when ALL parameters are resolved → build the `create_compute_instance` payload using **camelCase**.
- If ambiguous (>1 results) → return in "candidates" with this format:
- Always use snake_case for "parameters": compartment_id, subnet_id, availability_domain, image_id, shape, ocpus, memoryInGBs, display_name.
- Only when calling `create_compute_instance`, convert to camelCase: compartmentId, subnetId, availabilityDomain, imageId, displayName, shape, shapeConfig.
- Never mix snake_case and camelCase in the same JSON object.
"candidates": {{
"image_id": [
{{ "index": 1, "name": "Oracle-Linux-9.6-2025.09.16-0", "ocid": "ocid1.image.oc1....", "version": "2025.09.16", "score": 0.99 }},
{{ "index": 2, "name": "Oracle-Linux-9.6-2025.08.31-0", "ocid": "ocid1.image.oc1....", "version": "2025.08.31", "score": 0.97 }}
]
}}
- Do not include null/None values in candidates.
- If no matches → just return "ask".
- If exactly one → assign directly in "parameters".
## OUTPUT CONTRACT
- While resolving:
{{
"parameters": {{ ... }},
"candidates": {{ ... }}, # only if ambiguous
"ask": "..." # only if needed
}}
- When all resolved:
{{
"compartmentId": "...",
"subnetId": "...",
"availabilityDomain": "...",
"imageId": "...",
"displayName": "...",
"shape": "...",
"shapeConfig": {{ "ocpus": <number>, "memoryInGBs": <number> }}
}}
Then return:
{{ "result": "✅ Creation of resource is Done." }}
⚠️ JSON must be strictly valid (RFC8259).
No markdown, no comments, no truncation, no null placeholders.
"""
prompt = ChatPromptTemplate.from_messages([
("system", system_text),
("placeholder", "{messages}")
])
# ----------------------------
# MCP TOOLS
# ----------------------------
client = MultiServerMCPClient(
{
"oci-ops": {
"command": sys.executable,
"args": ["server_mcp.py"],
"transport": "stdio",
"env": {
"PATH": os.environ.get("PATH", "") + os.pathsep + os.path.expanduser("~/.local/bin"),
"OCI_CLI_BIN": config_data["OCI_CLI_BIN"],
"OCI_CLI_PROFILE": config_data["oci_profile"],
},
},
}
)
async def load_tools():
tools = await client.get_tools()
if not tools:
print("❌ No MCP tools loaded")
else:
print("🛠️ Loaded tools:", [t.name for t in tools])
return tools
tools = asyncio.get_event_loop().run_until_complete(load_tools())
# ----------------------------
# AGENT EXECUTOR
# ----------------------------
agent_executor = create_react_agent(
model=llm,
tools=tools,
prompt=prompt,
)
# ----------------------------
# FLASK ROUTES
# ----------------------------
@app.route("/")
def index():
return render_template("chat.html")
@app.route("/send", methods=["POST"])
def send():
user_message = request.form["message"]
memory_state.messages.append(HumanMessage(content=user_message))
user_html = f"<div class='message-user'>You: {user_message}</div>"
try:
# injeta estado atual na conversa
params_json = json.dumps({"parameters": memory_state.parameters}, indent=2)
context_message = AIMessage(content=f"Current known parameters:\n{params_json}")
result = asyncio.run(agent_executor.ainvoke({
"messages": memory_state.messages + [context_message]
}))
debug_info = ""
if check_truncation(result):
debug_info += "\n\n⚠️ Warning: Response truncated by max_tokens limit."
new_messages = result.get("messages", [])
if new_messages:
memory_state.messages.extend(new_messages)
assistant_reply = new_messages[-1].content
parsed = safe_json_extract(assistant_reply)
if not parsed: # fallback se falhar
parsed = sanitize_json(assistant_reply)
if parsed and "parameters" in parsed:
# atualiza parâmetros
for k, v in parsed["parameters"].items():
if v is not None:
memory_state.parameters[k] = v
print("📌 Current status:", memory_state.parameters)
missing = validate_payload(memory_state.parameters)
if not missing:
print("✅ All parameters filled in. The agent should now create the VM..")
else:
print("⚠️ Faltando parâmetros:", missing)
if not missing:
debug_info += "\n✅ All parameters filled in. The agent should now create the VM.."
else:
debug_info += f"\n⚠️ Missing parameters: {missing}"
if missing:
auto_followup = f"Please resolve the following missing parameters: {missing}"
memory_state.messages.append(HumanMessage(content=auto_followup))
# adiciona debug_info na resposta enviada ao navegador
assistant_reply += "\n\n" + debug_info
# se vieram candidatos
if parsed and "candidates" in parsed and parsed["candidates"]:
memory_state.candidates = parsed["candidates"]
print("🔍 Candidates found:", memory_state.candidates)
# monta bloco HTML de candidatos
candidates_html = ""
for param, items in memory_state.candidates.items():
candidates_html += f"<b>Options for {param}:</b><br>"
for c in items:
line = f"{c.get('index')}. {c.get('name')}{c.get('ocid')} — v{c.get('version')} — score {c.get('score')}"
candidates_html += line + "<br>"
ask_text = parsed.get("ask", "Choose an index or provide the OCID.")
assistant_reply = f"{json.dumps({'parameters': memory_state.parameters}, ensure_ascii=False)}<br>{candidates_html}<i>{ask_text}</i>"
else:
memory_state.candidates = {}
else:
assistant_reply = "⚠️ No response from agent."
except Exception as e:
assistant_reply = f"⚠️ Erro: {e}"
bot_html = f"<div class='message-bot'>Assistant: {assistant_reply}</div>"
return Markup(user_html + bot_html)
# ----------------------------
# MAIN
# ----------------------------
if __name__ == "__main__":
app.run(host="0.0.0.0", port=8080, debug=True)