Merge branch 'main'

2025-07-31 12:32:34 +05:45 · 2025-07-31 12:32:34 +05:45 · 0c02eafeca
commit 0c02eafeca
parent 0a644a030f bcc3fbf099
8 changed files with 59 additions and 97 deletions
--- a/9
+++ b/9
@ -2,12 +2,15 @@ FROM python:3.11-slim-bookworm

 # Install Node.js and npm
 RUN apt-get update && apt-get install -y \
-    nodejs \  
-    npm \
    nginx \
    curl \
    redis-server

+# Install Node.js 20 using NodeSource repository
+RUN curl -fsSL https://deb.nodesource.com/setup_20.x | bash - && \
+    apt-get install -y nodejs
+
+
 # Create a working directory
 WORKDIR /app  

@ -39,7 +42,7 @@ RUN npm run build

 WORKDIR /app

-# Copy FastAPI and start script
+# Copy FastAPI
 COPY servers/fastapi/ ./servers/fastapi/
 COPY start.js LICENSE NOTICE ./

--- a/Dockerfile.dev
+++ b/Dockerfile.dev
@ -2,12 +2,16 @@ FROM python:3.11-slim-bookworm

 # Install Node.js and npm
 RUN apt-get update && apt-get install -y \
-  nodejs \  
-  npm \
  nginx \
  curl \
  redis-server

+
+# Install Node.js 20 using NodeSource repository
+RUN curl -fsSL https://deb.nodesource.com/setup_20.x | bash - && \
+  apt-get install -y nodejs
+
+
 # Change working directory
 WORKDIR /app

--- a/docker-compose.yml
+++ b/docker-compose.yml
@ -14,12 +14,15 @@ services:
      - LLM=${LLM}
      - OPENAI_API_KEY=${OPENAI_API_KEY}
      - GOOGLE_API_KEY=${GOOGLE_API_KEY}
+      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
+      - ANTHROPIC_MODEL=${ANTHROPIC_MODEL}
      - OLLAMA_URL=${OLLAMA_URL}
      - OLLAMA_MODEL=${OLLAMA_MODEL}
      - CUSTOM_LLM_URL=${CUSTOM_LLM_URL}
      - CUSTOM_LLM_API_KEY=${CUSTOM_LLM_API_KEY}
      - CUSTOM_MODEL=${CUSTOM_MODEL}
      - PEXELS_API_KEY=${PEXELS_API_KEY}
+      - EXTENDED_REASONING=${EXTENDED_REASONING}
      - DATABASE_URL=${DATABASE_URL}

  production-gpu:
@ -44,12 +47,15 @@ services:
      - LLM=${LLM}
      - OPENAI_API_KEY=${OPENAI_API_KEY}
      - GOOGLE_API_KEY=${GOOGLE_API_KEY}
+      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
+      - ANTHROPIC_MODEL=${ANTHROPIC_MODEL}
      - OLLAMA_URL=${OLLAMA_URL}
      - OLLAMA_MODEL=${OLLAMA_MODEL}
      - CUSTOM_LLM_URL=${CUSTOM_LLM_URL}
      - CUSTOM_LLM_API_KEY=${CUSTOM_LLM_API_KEY}
      - CUSTOM_MODEL=${CUSTOM_MODEL}
      - PEXELS_API_KEY=${PEXELS_API_KEY}
+      - EXTENDED_REASONING=${EXTENDED_REASONING}
      - DATABASE_URL=${DATABASE_URL}

  development:
@ -67,12 +73,15 @@ services:
      - LLM=${LLM}
      - OPENAI_API_KEY=${OPENAI_API_KEY}
      - GOOGLE_API_KEY=${GOOGLE_API_KEY}
+      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
+      - ANTHROPIC_MODEL=${ANTHROPIC_MODEL}
      - OLLAMA_URL=${OLLAMA_URL}
      - OLLAMA_MODEL=${OLLAMA_MODEL}
      - CUSTOM_LLM_URL=${CUSTOM_LLM_URL}
      - CUSTOM_LLM_API_KEY=${CUSTOM_LLM_API_KEY}
      - CUSTOM_MODEL=${CUSTOM_MODEL}
      - PEXELS_API_KEY=${PEXELS_API_KEY}
+      - EXTENDED_REASONING=${EXTENDED_REASONING}
      - DATABASE_URL=${DATABASE_URL}

  development-gpu:
@ -97,10 +106,13 @@ services:
      - LLM=${LLM}
      - OPENAI_API_KEY=${OPENAI_API_KEY}
      - GOOGLE_API_KEY=${GOOGLE_API_KEY}
+      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
+      - ANTHROPIC_MODEL=${ANTHROPIC_MODEL}
      - OLLAMA_URL=${OLLAMA_URL}
      - OLLAMA_MODEL=${OLLAMA_MODEL}
      - CUSTOM_LLM_URL=${CUSTOM_LLM_URL}
      - CUSTOM_LLM_API_KEY=${CUSTOM_LLM_API_KEY}
      - CUSTOM_MODEL=${CUSTOM_MODEL}
      - PEXELS_API_KEY=${PEXELS_API_KEY}
+      - EXTENDED_REASONING=${EXTENDED_REASONING}
      - DATABASE_URL=${DATABASE_URL}
--- a/servers/fastapi/api/v1/ppt/endpoints/presentation.py
+++ b/servers/fastapi/api/v1/ppt/endpoints/presentation.py
@ -19,7 +19,7 @@ from models.pptx_models import PptxPresentationModel
 from models.presentation_layout import PresentationLayoutModel
 from models.presentation_structure_model import PresentationStructureModel
 from models.presentation_with_slides import PresentationWithSlides
-from services.get_layout_by_name import get_layout_by_name
+from utils.get_layout_by_name import get_layout_by_name
 from services.icon_finder_service import IconFinderService
 from services.image_generation_service import ImageGenerationService
 from utils.dict_utils import deep_update
--- a/servers/fastapi/chroma/chroma.sqlite3
+++ b/servers/fastapi/chroma/chroma.sqlite3
--- a/servers/fastapi/services/llm_client.py
+++ b/servers/fastapi/services/llm_client.py
@ -26,7 +26,7 @@ from utils.llm_provider import get_llm_provider
 class LLMClient:
    def __init__(self):
        self.llm_provider = get_llm_provider()
-        self.client = self._get_client()
+        self._client = self._get_client()

    # ? Clients
    def _get_client(self):
@ -100,7 +100,7 @@ class LLMClient:

    # ? Generate Unstructured Content
    async def _generate_openai(self, model: str, messages: List[LLMMessage]):
-        client: AsyncOpenAI = self.client
+        client: AsyncOpenAI = self._client
        response = await client.chat.completions.create(
            model=model,
            messages=[message.model_dump() for message in messages],
@ -108,7 +108,7 @@ class LLMClient:
        return response.choices[0].message.content

    async def _generate_google(self, model: str, messages: List[LLMMessage]):
-        client: genai.Client = self.client
+        client: genai.Client = self._client
        response = await asyncio.to_thread(
            client.models.generate_content,
            model=model,
@ -121,7 +121,7 @@ class LLMClient:
        return response.text

    async def _generate_anthropic(self, model: str, messages: List[LLMMessage]):
-        client: AsyncAnthropic = self.client
+        client: AsyncAnthropic = self._client
        response: AnthropicMessage = await client.messages.create(
            model=model,
            messages=[message.model_dump() for message in messages],
@ -153,11 +153,6 @@ class LLMClient:
                content = await self._generate_ollama(model, messages)
            case LLMProvider.CUSTOM:
                content = await self._generate_custom(model, messages)
-            case _:
-                raise HTTPException(
-                    status_code=400,
-                    detail="LLM Provider must be either openai, google, anthropic, ollama, or custom",
-                )
        if content is None:
            raise HTTPException(
                status_code=400,
@ -169,7 +164,7 @@ class LLMClient:
    async def _generate_openai_structured(
        self, model: str, messages: List[LLMMessage], response_format: BaseModel | dict
    ):
-        client: AsyncOpenAI = self.client
+        client: AsyncOpenAI = self._client
        is_response_format_dict = isinstance(response_format, dict)
        if is_response_format_dict:
            response = await client.chat.completions.create(
@ -203,7 +198,7 @@ class LLMClient:
    async def _generate_google_structured(
        self, model: str, messages: List[LLMMessage], response_format: BaseModel | dict
    ):
-        client: genai.Client = self.client
+        client: genai.Client = self._client
        response = await asyncio.to_thread(
            client.models.generate_content,
            model=model,
@ -221,7 +216,7 @@ class LLMClient:
    async def _generate_anthropic_structured(
        self, model: str, messages: List[LLMMessage], response_format: BaseModel | dict
    ):
-        client: AsyncAnthropic = self.client
+        client: AsyncAnthropic = self._client
        is_response_format_dict = isinstance(response_format, dict)
        response: AnthropicMessage = await client.messages.create(
            model=model,
@ -279,11 +274,6 @@ class LLMClient:
                content = await self._generate_custom_structured(
                    model, messages, response_format
                )
-            case _:
-                raise HTTPException(
-                    status_code=400,
-                    detail="LLM Provider must be either openai, google, anthropic, ollama, or custom",
-                )
        if content is None:
            raise HTTPException(
                status_code=400,
@ -293,7 +283,7 @@ class LLMClient:

    # ? Stream Unstructured Content
    async def _stream_openai(self, model: str, messages: List[LLMMessage]):
-        client: AsyncOpenAI = self.client
+        client: AsyncOpenAI = self._client
        async with client.chat.completions.stream(
            model=model,
            messages=[message.model_dump() for message in messages],
@ -303,7 +293,7 @@ class LLMClient:
                    yield event.delta

    async def _stream_google(self, model: str, messages: List[LLMMessage]):
-        client: genai.Client = self.client
+        client: genai.Client = self._client
        async for event in iterator_to_async(client.models.generate_content_stream)(
            model=model,
            contents=self._get_user_prompts(messages),
@ -316,7 +306,7 @@ class LLMClient:
                yield event.text

    async def _stream_anthropic(self, model: str, messages: List[LLMMessage]):
-        client: AsyncAnthropic = self.client
+        client: AsyncAnthropic = self._client
        async with client.messages.stream(
            model=model,
            messages=[message.model_dump() for message in messages],
@ -332,7 +322,7 @@ class LLMClient:
    def _stream_custom(self, model: str, messages: List[LLMMessage]):
        return self._stream_openai(model, messages)

-    async def stream(self, model: str, messages: List[LLMMessage]):
+    def stream(self, model: str, messages: List[LLMMessage]):
        match self.llm_provider:
            case LLMProvider.OPENAI:
                return self._stream_openai(model, messages)
@ -344,17 +334,12 @@ class LLMClient:
                return self._stream_ollama(model, messages)
            case LLMProvider.CUSTOM:
                return self._stream_custom(model, messages)
-            case _:
-                raise HTTPException(
-                    status_code=400,
-                    detail="LLM Provider must be either openai, google, anthropic, ollama, or custom",
-                )

    # ? Stream Structured Content
    async def _stream_openai_structured(
        self, model: str, messages: List[LLMMessage], response_format: BaseModel | dict
    ):
-        client: AsyncOpenAI = self.client
+        client: AsyncOpenAI = self._client
        is_response_format_dict = isinstance(response_format, dict)
        async with client.chat.completions.stream(
            model=model,
@ -378,7 +363,7 @@ class LLMClient:
    async def _stream_google_structured(
        self, model: str, messages: List[LLMMessage], response_format: BaseModel | dict
    ):
-        client: genai.Client = self.client
+        client: genai.Client = self._client
        async for event in iterator_to_async(client.models.generate_content_stream)(
            model=model,
            contents=self._get_user_prompts(messages),
@ -394,7 +379,7 @@ class LLMClient:
    async def _stream_anthropic_structured(
        self, model: str, messages: List[LLMMessage], response_format: BaseModel | dict
    ):
-        client: AsyncAnthropic = self.client
+        client: AsyncAnthropic = self._client
        is_response_format_dict = isinstance(response_format, dict)
        async with client.messages.stream(
            model=model,
@ -426,7 +411,7 @@ class LLMClient:
    ):
        return self._stream_openai_structured(model, messages, response_format)

-    async def stream_structured(
+    def stream_structured(
        self, model: str, messages: List[LLMMessage], response_format: BaseModel | dict
    ):
        match self.llm_provider:
@ -442,8 +427,3 @@ class LLMClient:
                return self._stream_ollama_structured(model, messages, response_format)
            case LLMProvider.CUSTOM:
                return self._stream_custom_structured(model, messages, response_format)
-            case _:
-                raise HTTPException(
-                    status_code=400,
-                    detail="LLM Provider must be either openai, google, anthropic, ollama, or custom",
-                )
--- a/servers/fastapi/services/get_layout_by_name.py
+++ b/servers/fastapi/services/get_layout_by_name.py
--- a/servers/fastapi/utils/llm_calls/generate_presentation_outlines.py
+++ b/servers/fastapi/utils/llm_calls/generate_presentation_outlines.py
@ -1,18 +1,9 @@
 from typing import Optional
-from google.genai.types import GenerateContentConfig
-from openai.types.chat.chat_completion_chunk import ChoiceDelta

-from utils.async_iterator import iterator_to_async
+from models.llm_message import LLMMessage
+from services.llm_client import LLMClient
 from utils.get_dynamic_models import get_presentation_outline_model_with_n_slides
-from utils.llm_provider import (
-    get_anthropic_llm_client,
-    get_google_llm_client,
-    get_large_model,
-    get_llm_client,
-    is_anthropic_selected,
-    is_google_selected,
-)
-from pydantic import BaseModel
+from utils.llm_provider import get_large_model

 system_prompt = """
 You are an expert presentation creator. Generate structured presentations based on user requirements and format them according to the specified JSON schema with markdown content.
@ -64,29 +55,19 @@ def get_user_prompt(prompt: str, n_slides: int, language: str, content: str):
    """


-def get_prompt_template(prompt: str, n_slides: int, language: str, content: str):
+def get_messages(prompt: str, n_slides: int, language: str, content: str):
    return [
-        {
-            "role": "system",
-            "content": system_prompt,
-        },
-        {
-            "role": "user",
-            "content": get_user_prompt(prompt, n_slides, language, content),
-        },
+        LLMMessage(
+            role="system",
+            content=system_prompt,
+        ),
+        LLMMessage(
+            role="user",
+            content=get_user_prompt(prompt, n_slides, language, content),
+        ),
    ]


-def get_response_format(response_model: BaseModel):
-    return {
-        "type": "json_schema",
-        "json_schema": {
-            "name": "PresentationOutlineModel",
-            "schema": response_model.model_json_schema(),
-        },
-    }
-
-
 async def generate_ppt_outline(
    prompt: Optional[str],
    n_slides: int,
@ -96,29 +77,11 @@ async def generate_ppt_outline(
    model = get_large_model()
    response_model = get_presentation_outline_model_with_n_slides(n_slides)

-    if is_google_selected():
-        client = get_google_llm_client()
-        generate_stream = iterator_to_async(client.models.generate_content_stream)
-        async for event in generate_stream(
-            model=model,
-            contents=[get_user_prompt(prompt, n_slides, language, content)],
-            config=GenerateContentConfig(
-                system_instruction=system_prompt,
-                response_mime_type="application/json",
-                response_json_schema=response_model.model_json_schema(),
-            ),
-        ):
-            if event.text:
-                yield event.text
+    client = LLMClient()

-    else:
-        client = get_llm_client()
-        async for response in await client.chat.completions.create(
-            model=model,
-            messages=get_prompt_template(prompt, n_slides, language, content),
-            stream=True,
-            response_format=get_response_format(response_model),
-        ):
-            delta: ChoiceDelta = response.choices[0].delta
-            if delta.content:
-                yield delta.content
+    async for chunk in client.stream_structured(
+        model,
+        get_messages(prompt, n_slides, language, content),
+        response_model,
+    ):
+        yield chunk