[AUR-385, AUR-388] Declare BaseComponent and decide LLM call interface (#2)

- Use cases related to LLM call: https://cinnamon-ai.atlassian.net/browse/AUR-388?focusedCommentId=34873
- Sample usages: `test_llms_chat_models.py` and `test_llms_completion_models.py`:

```python
from kotaemon.llms.chats.openai import AzureChatOpenAI

model = AzureChatOpenAI(
    openai_api_base="https://test.openai.azure.com/",
    openai_api_key="some-key",
    openai_api_version="2023-03-15-preview",
    deployment_name="gpt35turbo",
    temperature=0,
    request_timeout=60,
)
output = model("hello world")
```

For the LLM-call component, I decide to wrap around Langchain's LLM models and Langchain's Chat models. And set the interface as follow:

- Completion LLM component:
```python
class CompletionLLM:

    def run_raw(self, text: str) -> LLMInterface:
        # Run text completion: str in -> LLMInterface out

    def run_batch_raw(self, text: list[str]) -> list[LLMInterface]:
        # Run text completion in batch: list[str] in -> list[LLMInterface] out

# run_document and run_batch_document just reuse run_raw and run_batch_raw, due to unclear use case
```

- Chat LLM component:
```python
class ChatLLM:
    def run_raw(self, text: str) -> LLMInterface:
        # Run chat completion (no chat history): str in -> LLMInterface out

    def run_batch_raw(self, text: list[str]) -> list[LLMInterface]:
        # Run chat completion in batch mode (no chat history): list[str] in -> list[LLMInterface] out

    def run_document(self, text: list[BaseMessage]) -> LLMInterface:
        # Run chat completion (with chat history): list[langchain's BaseMessage] in -> LLMInterface out

    def run_batch_document(self, text: list[list[BaseMessage]]) -> list[LLMInterface]:
        # Run chat completion in batch mode (with chat history): list[list[langchain's BaseMessage]] in -> list[LLMInterface] out
```

- The LLMInterface is as follow:

```python
@dataclass
class LLMInterface:
    text: list[str]
    completion_tokens: int = -1
    total_tokens: int = -1
    prompt_tokens: int = -1
    logits: list[list[float]] = field(default_factory=list)
```

tests/test_telemetry.py

@@ -1,3 +1,31 @@
+import os
+import sys
+
+import pytest
+
+
+@pytest.fixture
+def clean_artifacts_for_telemetry():
+    try:
+        del sys.modules["kotaemon"]
+    except KeyError:
+        pass
+
+    try:
+        del sys.modules["haystack"]
+    except KeyError:
+        pass
+
+    try:
+        del sys.modules["haystack.telemetry"]
+    except KeyError:
+        pass
+
+    if "HAYSTACK_TELEMETRY_ENABLED" in os.environ:
+        del os.environ["HAYSTACK_TELEMETRY_ENABLED"]
+
+
+@pytest.mark.usefixtures("clean_artifacts_for_telemetry")
 def test_disable_telemetry_import_haystack_first():
     """Test that telemetry is disabled when kotaemon lib is initiated after"""
     import os
@@ -10,6 +38,7 @@ def test_disable_telemetry_import_haystack_first():
     assert os.environ.get("HAYSTACK_TELEMETRY_ENABLED", "True") == "False"
 
 
+@pytest.mark.usefixtures("clean_artifacts_for_telemetry")
 def test_disable_telemetry_import_haystack_after_kotaemon():
     """Test that telemetry is disabled when kotaemon lib is initiated before"""
     import os