feat: Add LM Studio integration with embedding and generation components

[supmo668]

No description provided.

[Copilot]

Pull Request Overview

This PR adds LM Studio integration to the system, enabling users to leverage locally hosted models through LM Studio's OpenAI-compatible API for both text generation and embedding functionality.

• Implements LMStudioGenerator for text generation using local models
• Implements LMStudioEmbedder for document and query vectorization
• Adds configuration options and environment variables for LM Studio integration

Reviewed Changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 2 comments.

File	Description
goldenverba/components/managers.py	Registers the new LM Studio components in both development and production environments
goldenverba/components/generation/LMStudioGenerator.py	Implements text generation using LM Studio's chat completions API with streaming support
goldenverba/components/embedding/LMStudioEmbedder.py	Implements embedding functionality using LM Studio's embeddings API
goldenverba/.env.example	Adds environment variable examples for LM Studio configuration

---

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[Copilot]

The conversion of JSON payload to BytesIO is unnecessary. The aiohttp library can handle JSON payloads directly using the json parameter instead of data. This would simplify the code and remove the need for manual serialization.

Suggested change

	# Convert payload to BytesIO object
	payload_bytes = json.dumps(payload).encode("utf-8")
	payload_io = io.BytesIO(payload_bytes)
	async with aiohttp.ClientSession() as session:
	try:
	async with session.post(
	f"{base_url}/embeddings",
	headers=headers,
	data=payload_io,
	# Send payload as JSON using aiohttp's json parameter
	async with aiohttp.ClientSession() as session:
	try:
	async with session.post(
	f"{base_url}/embeddings",
	headers=headers,
	json=payload,

[Copilot]

This should use json=payload instead of data=payload_io to properly send JSON data with correct Content-Type headers automatically handled by aiohttp.

Suggested change

	# Convert payload to BytesIO object
	payload_bytes = json.dumps(payload).encode("utf-8")
	payload_io = io.BytesIO(payload_bytes)
	async with aiohttp.ClientSession() as session:
	try:
	async with session.post(
	f"{base_url}/embeddings",
	headers=headers,
	data=payload_io,
	async with aiohttp.ClientSession() as session:
	try:
	async with session.post(
	f"{base_url}/embeddings",
	headers=headers,
	json=payload,

[orca-security-eu]

Orca Security Scan Summary

Status	Check	Issues by priority
Passed	Infrastructure as Code	0   0   0   0	View in Orca
Passed	SAST	0   0   0   0	View in Orca
Passed	Secrets	0   0   0   0	View in Orca
Passed	Vulnerabilities	0   0   0   0	View in Orca

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[supmo668]

I agree with the CLA set by Weaviate