chore: include unrelated workspace edits (prompts/uv.lock/middleware)

Author: nourzakhama2003

api/core/llm_generator/prompts.py

@@ -11,6 +11,8 @@
 - The title must be natural, friendly, and in the same language as the input.
 - If the input is a direct question to the model, you may add an emoji at the end.
 
+- Special Note for Persian (Farsi): If the input is Persian (Farsi), ALWAYS generate the title in Persian (Farsi). Use Persian characters (for example: پ، چ، ژ، گ، ک، ی) and ensure the "Language Type" field is "Persian" or "Farsi". Do NOT use Arabic or any other language or script when the input is Persian.
+
 3. Output Format
 Return **only** a valid JSON object with these exact keys and no additional text:
 {

api/tests/unit_tests/core/test_llm_generator_persian.py

@@ -0,0 +1,65 @@
+import json
+from unittest.mock import MagicMock, patch
+
+from core.llm_generator.llm_generator import LLMGenerator
+
+
+class DummyMessage:
+    def __init__(self, content):
+        self.content = content
+
+
+class DummyResponse:
+    def __init__(self, content):
+        self.message = DummyMessage(content)
+
+
+def make_json_response(language, output):
+    return json.dumps({"Language Type": language, "Your Reasoning": "...", "Your Output": output})
+
+
+@patch("core.llm_generator.llm_generator.ModelManager.get_default_model_instance")
+def test_generate_conversation_name_enforces_persian(mock_get_model):
+    # A Persian input containing Persian-specific character 'پ'
+    persian_query = "سلام، چطوری؟ پ"  # contains 'پ'
+
+    # First model response: misdetected as Arabic and returns Arabic title
+    first_resp = DummyResponse(make_json_response("Arabic", "مرحبا"))
+    # Second response (after retry): returns a Persian title with Persian-specific chars
+    second_resp = DummyResponse(make_json_response("Persian", "عنوان پِرس"))
+
+    model_instance = MagicMock()
+    model_instance.invoke_llm.side_effect = [first_resp, second_resp]
+
+    mock_get_model.return_value = model_instance
+
+    name = LLMGenerator.generate_conversation_name("tenant1", persian_query)
+
+    # The final name should come from the Persian response (contains Persian-specific char 'پ')
+    assert "پ" in name
+    # Ensure the model was invoked at least twice (retry occurred)
+    assert model_instance.invoke_llm.call_count >= 2
+
+
+@patch("core.llm_generator.llm_generator.ModelManager.get_default_model_instance")
+def test_generate_conversation_name_translation_fallback(mock_get_model):
+    # Persian query
+    persian_query = "این یک تست است پ"
+
+    # Model returns non-Persian outputs consistently
+    non_persian_resp = DummyResponse(make_json_response("Arabic", "مرحبا"))
+
+    # Translate response (last call) returns Persian translation
+    translate_resp = DummyResponse("عنوان ترجمه شده پ")
+
+    model_instance = MagicMock()
+    # First two calls return non-persian results; third call is translation
+    model_instance.invoke_llm.side_effect = [non_persian_resp, non_persian_resp, translate_resp]
+
+    mock_get_model.return_value = model_instance
+
+    name = LLMGenerator.generate_conversation_name("tenant1", persian_query)
+
+    # Final name should contain Persian character 'پ' from translation fallback
+    assert "پ" in name
+    assert model_instance.invoke_llm.call_count >= 3

api/uv.lock

@@ -176,6 +176,12 @@ services:
       THIRD_PARTY_SIGNATURE_VERIFICATION_ENABLED: true
       THIRD_PARTY_SIGNATURE_VERIFICATION_PUBLIC_KEYS: /app/keys/publickey.pem
       FORCE_VERIFYING_SIGNATURE: false
+
+      HTTP_PROXY: ${HTTP_PROXY:-http://ssrf_proxy:3128}
+      HTTPS_PROXY: ${HTTPS_PROXY:-http://ssrf_proxy:3128}
+      PLUGIN_PYTHON_ENV_INIT_TIMEOUT: ${PLUGIN_PYTHON_ENV_INIT_TIMEOUT:-120}
+    extra_hosts:
+      - "host.docker.internal:host-gateway"
     ports:
       - "${EXPOSE_PLUGIN_DAEMON_PORT:-5002}:${PLUGIN_DAEMON_PORT:-5002}"
       - "${EXPOSE_PLUGIN_DEBUGGING_PORT:-5003}:${PLUGIN_DEBUGGING_PORT:-5003}"