added frontend and caddy

Author: LeooR22

create_fastapi_project/templates/__init__.py

@@ -35,8 +35,9 @@ def install_template(root: str, template: ITemplate, app_name: str):
 
     # Add pyproject.toml file and installl packages
     app_folder: str = "app"
-    if template == ITemplate.full:
-        app_folder = "backend/app"
+    if template == ITemplate.full or template == ITemplate.langchain_basic:
+        # TODO: CHECK PATHS IN MACOS AND WINDOWS | (os.path.join)
+        app_folder = "backend\\app"
 
     poetry_path = os.path.join(root, app_folder)
     has_pyproject = add_configuration_to_pyproject(poetry_path)

create_fastapi_project/templates/basic/README.md

@@ -6,6 +6,7 @@ This is a FastAPI project initialized using [`create-fastapi-project`](https://g
 
 The commands in this documentation can be customized on the **Makefile**. It can be started with and without docker.
 
+This project uses poetry, if you don't have it installed, you can the follow the instruction in [Poetry Documentation](https://python-poetry.org/docs/#installation).
 
 - Run the server (Recommended using docker):
 
@@ -20,7 +21,6 @@ make run-dev
 make run-prod
 ```
 
-
 - Run the server without docker:
 
 First, make sure you have all packages installed:
@@ -68,5 +68,4 @@ Running `pip install create-fastapi-project@latest` (with no arguments) launches
 
 By choosing `create-fastapi-project`, you streamline your initial project setup, leverage reliable patterns, and enjoy the convenience of a tool tailored for FastAPI development.
 
-
 We love ❤️ [FastAPI](https://fastapi.tiangolo.com/) and its ecosystem. You can check out the [create-fastapi-project GitHub repository](https://github.com/allient/create-fastapi-project) - your feedback and contributions are welcome!

create_fastapi_project/templates/langchain_basic/.env.example

@@ -1,4 +1,11 @@
 PROJECT_NAME=
 OPENAI_API_KEY=
 UNSPLASH_API_KEY=
-SERP_API_KEY=
+SERP_API_KEY=
+
+#############################################
+# Caddy variables
+#############################################
+EXT_ENDPOINT1=127.0.0.1
+LOCAL_1=localhost
+LOCAL_2=127.0.0.1

create_fastapi_project/templates/langchain_basic/README.md

@@ -29,6 +29,8 @@ This is a FastAPI project initialized using [`create-fastapi-project`](https://g
 
 The commands in this documentation can be customized on the **Makefile**. It can be started with and without docker.
 
+This project uses poetry, if you don't have it installed, you can the follow the instruction in [Poetry Documentation](https://python-poetry.org/docs/#installation).
+
 - Run the server (Recommended using docker):
 
 ```bash

create_fastapi_project/templates/langchain_basic/Dockerfile renamed to create_fastapi_project/templates/langchain_basic/backend/Dockerfile

@@ -2,6 +2,7 @@
     IChatResponse,
     IUserMessage,
 )
+import logging
 from app.utils.adaptive_cards.cards import create_adaptive_card
 from app.utils.callback import (
     CustomAsyncCallbackHandler,
@@ -84,55 +85,60 @@ async def websocket_endpoint(websocket: WebSocket):
 @router.websocket("/tools")
 async def websocket_endpoint(websocket: WebSocket):
     await websocket.accept()
-    while True:
-        data = await websocket.receive_json()
-        user_message = data["message"]
-        user_message_card = create_adaptive_card(user_message)
 
-        resp = IChatResponse(
-            sender="you",
-            message=user_message_card.to_dict(),
-            type="start",
-            message_id=str(uuid7()),
-            id=str(uuid7()),
-        )
-
-        await websocket.send_json(resp.dict())
-        message_id: str = str(uuid7())
-        custom_handler = CustomFinalStreamingStdOutCallbackHandler(
-            websocket, message_id=message_id
-        )
-
-        tools = [
-            GeneralKnowledgeTool(),
-            PokemonSearchTool(),
-            ImageSearchTool(),
-            YoutubeSearchTool(),
-            GeneralWeatherTool(),
-        ]
-
-        llm = ChatOpenAI(
-            streaming=True,
-            temperature=0,
-        )
-
-        agent = ZeroShotAgent.from_llm_and_tools(
-            llm=llm,
-            tools=tools,
-            prefix=zero_agent_prompt.prefix,
-            suffix=zero_agent_prompt.suffix,
-            format_instructions=zero_agent_prompt.format_instructions,
-            input_variables=zero_agent_prompt.input_variables,
-        )
-        # TODO: We should use this
-        # * max_execution_time=1,
-        # early_stopping_method="generate",
-        agent_executor = AgentExecutor.from_agent_and_tools(
-            agent=agent,
-            tools=tools,
-            verbose=False,
-            handle_parsing_errors=True,
-            memory=memory,
-        )
+    while True:
+        try:
+            data = await websocket.receive_json()
+            user_message = data["message"]
+            user_message_card = create_adaptive_card(user_message)
+
+            resp = IChatResponse(
+                sender="you",
+                message=user_message_card.to_dict(),
+                type="start",
+                message_id=str(uuid7()),
+                id=str(uuid7()),
+            )
+
+            await websocket.send_json(resp.dict())
+            message_id: str = str(uuid7())
+            custom_handler = CustomFinalStreamingStdOutCallbackHandler(
+                websocket, message_id=message_id
+            )
+
+            tools = [
+                GeneralKnowledgeTool(),
+                PokemonSearchTool(),
+                ImageSearchTool(),
+                YoutubeSearchTool(),
+                GeneralWeatherTool(),
+            ]
 
-        await agent_executor.arun(input=user_message, callbacks=[custom_handler])
+            llm = ChatOpenAI(
+                streaming=True,
+                temperature=0,
+            )
+
+            agent = ZeroShotAgent.from_llm_and_tools(
+                llm=llm,
+                tools=tools,
+                prefix=zero_agent_prompt.prefix,
+                suffix=zero_agent_prompt.suffix,
+                format_instructions=zero_agent_prompt.format_instructions,
+                input_variables=zero_agent_prompt.input_variables,
+            )
+            # TODO: We should use this
+            # * max_execution_time=1,
+            # early_stopping_method="generate",
+            agent_executor = AgentExecutor.from_agent_and_tools(
+                agent=agent,
+                tools=tools,
+                verbose=False,
+                handle_parsing_errors=True,
+                memory=memory,
+            )
+
+            await agent_executor.arun(input=user_message, callbacks=[custom_handler])
+        except WebSocketDisconnect:
+            logging.info("websocket disconnect")
+            break

create_fastapi_project/templates/langchain_basic/app/README.md renamed to create_fastapi_project/templates/langchain_basic/backend/app/README.md

@@ -23,6 +23,7 @@ def custom_media(anwser):
         if url_image.endswith(")."):
             url_image = url_image[:-2]
         media = Image(url=url_image)
+        return None
         return ICreateMediaAC(media_object=media, media_type="image", url=url_image)
 
     regex_audio = r"\b(https?|ftp):\/\/[^\s/$.?#].[^\s]*\.(mp3|wav|ogg)\b"
@@ -69,6 +70,7 @@ def custom_media(anwser):
                 media = Image(url=photo)
                 list_media_element.append(media)
         body_container_images = ImageSet(images=list_media_element)
+        return None
         return ICreateMediaAC(
             media_object=body_container_images, media_type="image", url=""
         )

create_fastapi_project/templates/langchain_basic/app/app/__init__.py renamed to create_fastapi_project/templates/langchain_basic/backend/app/app/__init__.py

@@ -9,7 +9,7 @@ class IZeroPrompt(BaseModel):
     input_variables: list[str]
 
 
-PREFIX = """Answer the following questions as best and complete you can because you are a female health and wellness coach called Alita. You have access to the following tools:"""
+PREFIX = """Answer the following questions as best and complete you can. You have access to the following tools:"""
 FORMAT_INSTRUCTIONS = """Use the following format:
 
 Question: the input question you must answer
@@ -20,7 +20,7 @@ class IZeroPrompt(BaseModel):
 ... (this Thought/Action/Action Input/Observation can repeat N times)
 Thought: I now know the final answer
 Final Answer: the final answer to the original input question"""
-SUFFIX = """When answering, if you find link the formart is the next [title](link).
+SUFFIX = """When answering, your answers should be with markdown format.
 
 Question: {input}
 Thought:{agent_scratchpad}"""

create_fastapi_project/templates/langchain_basic/app/app/api/__init__.py renamed to create_fastapi_project/templates/langchain_basic/backend/app/app/api/__init__.py

@@ -105,7 +105,7 @@ async def _arun(self, query: str, run_manager: Optional[Any] = None) -> str:
                 image_url = result["urls"]["small"]
                 images_urls.append(image_url)
             image_list_string = "\n".join(
-                [f"{i+1}. [Image {i+1}]({url})" for i, url in enumerate(images_urls)]
+                [f"{i+1}. ![Image {i+1}]({url})" for i, url in enumerate(images_urls)]
             )
             return image_list_string
 

create_fastapi_project/templates/langchain_basic/app/app/api/v1/__init__.py renamed to create_fastapi_project/templates/langchain_basic/backend/app/app/api/v1/__init__.py

@@ -0,0 +1,13 @@
+{
+  email [email protected]
+}
+
+fastapi.{$EXT_ENDPOINT1}:80, fastapi.{$LOCAL_1}:80, fastapi.{$LOCAL_2}:80, :80 {
+  reverse_proxy fastapi_server:8000
+}
+
+frontend.{$EXT_ENDPOINT1}:80, frontend.{$LOCAL_1}:80, frontend.{$LOCAL_2}:80 {
+  reverse_proxy streamlit_frontend:8501 
+}
+
+

create_fastapi_project/templates/langchain_basic/app/app/api/v1/api.py renamed to create_fastapi_project/templates/langchain_basic/backend/app/app/api/v1/api.py

@@ -1,15 +1,49 @@
-version: '3.8'
+version: "3.8"
 
 services:
   fastapi_server:
-    build: .
+    container_name: fastapi_server
+    build: ./backend
     restart: always
     command: "sh -c 'uvicorn app.main:app --reload --workers 3 --host 0.0.0.0 --port 8000'"
     volumes:
-      - ./app:/code
+      - ./backend/app:/code
     expose:
       - 8000
     ports:
-      - 8000:8000      
+      - 8000:8000
     env_file: ".env"
 
+  streamlit_frontend:
+    container_name: streamlit_frontend
+    build: ./frontend
+    restart: always
+    # command: "sh -c 'streamlit run app.py --server.port 8501'"
+    volumes:
+      - ./frontend:/code
+    expose:
+      - 8501
+    ports:
+      - 8501:8501
+    env_file: ".env"
+
+  caddy_reverse_proxy:
+    container_name: caddy_reverse_proxy
+    image: caddy:alpine
+    restart: always
+    ports:
+      - 80:80
+      - 443:443
+    environment:
+      - EXT_ENDPOINT1=${EXT_ENDPOINT1}
+      - LOCAL_1=${LOCAL_1}
+      - LOCAL_2=${LOCAL_2}
+    volumes:
+      - ./caddy/Caddyfile:/etc/caddy/Caddyfile
+      - ./static:/code/static
+      - caddy_data:/data
+      - caddy_config:/config
+
+volumes:
+  caddy_data:
+  caddy_config:

create_fastapi_project/templates/langchain_basic/app/app/api/v1/endpoints/__init__.py renamed to create_fastapi_project/templates/langchain_basic/backend/app/app/api/v1/endpoints/__init__.py

@@ -1,4 +1,4 @@
-version: '3.8'
+version: "3.8"
 
 services:
   fastapi_server:
@@ -12,4 +12,3 @@ services:
     ports:
       - 8000:8000
     env_file: ".env"
-

create_fastapi_project/templates/langchain_basic/app/app/api/v1/endpoints/chat.py renamed to create_fastapi_project/templates/langchain_basic/backend/app/app/api/v1/endpoints/chat.py

@@ -0,0 +1,24 @@
+# app/Dockerfile
+
+FROM python:3.9-slim
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    software-properties-common \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+
+# Copiar la carpeta app al directorio de trabajo del contenedor
+COPY app /app
+
+RUN pip3 install -r /app/requirements.txt
+
+EXPOSE 8501
+
+HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
+
+ENTRYPOINT ["streamlit", "run", "streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]

create_fastapi_project/templates/langchain_basic/app/app/core/__init__.py renamed to create_fastapi_project/templates/langchain_basic/backend/app/app/core/__init__.py

@@ -0,0 +1,2 @@
+streamlit
+websockets

create_fastapi_project/templates/langchain_basic/app/app/core/config.py renamed to create_fastapi_project/templates/langchain_basic/backend/app/app/core/config.py

@@ -0,0 +1,68 @@
+import streamlit as st
+import asyncio
+import websockets
+import json
+
+
+async def retrieve_bot_response(text):
+    async with websockets.connect(
+        "ws://fastapi_server:8000/api/v1/chat/tools"
+    ) as websocket:
+        message_data = {"message": text}
+        json_data = json.dumps(message_data)
+
+        await websocket.send(json_data)
+        counter = 0
+        with st.empty():
+            stream_data = ""
+            try:
+                while True:
+                    counter += 1
+                    response = await asyncio.wait_for(websocket.recv(), timeout=20)
+                    response = json.loads(response)
+
+                    if response["sender"] == "bot":
+                        stream_data = (
+                            response["message"]["body"][0]["items"][0]["text"]
+                            if counter != 2
+                            else ""
+                        )
+                        st.markdown(stream_data)
+
+                    if response["type"] == "end":
+                        break
+                st.markdown(stream_data)
+            except asyncio.TimeoutError:
+                st.warning("Connection timed out. Closing the connection.")
+
+        return stream_data
+
+
+st.title("Simple chat")
+
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# Accept user input
+if prompt := st.chat_input("What is up?"):
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    # Display user message in chat message container
+    with st.chat_message("user"):
+        st.markdown(prompt)
+
+    # Display assistant response in chat message container
+    with st.chat_message("assistant"):
+        message_placeholder = st.empty()
+        full_response = asyncio.new_event_loop().run_until_complete(
+            retrieve_bot_response(prompt)
+        )
+
+    # Add assistant response to chat history
+    st.session_state.messages.append({"role": "assistant", "content": full_response})