not a real commit, just wanna work on my laptop

bashful.py

@@ -1,17 +1,29 @@
-import json
-import functions_framework
+import os
 import uuid
-from models.http_models.bashful_http import Txt2ImgModel
+
+import requests
+from models.http_models.bashful_http import Img2SVGModel, RemoveBGRequest, Txt2ImgModel, Txt2SVGModel
 
 from utils.http_utils import cors_decorator
 
 
-from providers import airtable_service, ai_service, logger, response_headers, gcp_service
+from providers import (
+    airtable_service,
+    ai_service,
+    logger,
+    response_headers,
+    gcp_service,
+)
 from utils.image_utils import convert_b64_to_bytes, replace_transparent_with_white
 from PIL import Image
 import io
 
-from utils.img2img_utils import create_default_img2img_payload, merge_model_config, merge_request_and_default_img2img_payload
+from utils.img2img_utils import (
+    create_default_img2img_payload,
+    merge_model_config,
+    merge_request_and_default_img2img_payload,
+)
+
 
 ##################### PROJECT: Bashful-Photoshop #####################
 
@@ -53,7 +65,7 @@ def txt2img(request: Txt2ImgModel):
         payload["upscale"] = model_config.get("upscale", "")
         payload["steps"] = model_config.get("steps", "")
         seed = payload.get("seed", None)
-        
+
         if seed:
             del payload["seed"]
 
@@ -122,7 +134,7 @@ def img2img(request):
 
         if not model_config:
             return ({"error": "No model config found"}, 400, response_headers)
-        
+
         payload = merge_model_config(payload, model_config)
 
         response = ai_service.img2img(byte_image, payload)
@@ -157,3 +169,70 @@ def img2img(request):
     except Exception as e:
         logger.error(e)
         return ({"error": str(e)}, 500, response_headers)
+
+
+def img2svg(request: Img2SVGModel):
+    image_url = request.image_url
+    if not image_url:
+        return ({"error": "Invalid image url"}, 400, response_headers)
+
+    response = requests.post(
+        "https://vectorizer.ai/api/v1/vectorize",
+        data={
+            "image.url": image_url,
+            # TODO: Add more upload options here
+        },
+        headers={
+            "Authorization": "Basic dmtjM3prbW44djM2ZmVkOjVzMXMzN2l2czRoZHNyazJjczVtZ2Uxa2ZwcjdtZmNuZzllbXM0czNpODdwZGZvczNpMHY="
+        },
+    )
+    if response.status_code == requests.codes.ok:
+        return (response.content, 200, response_headers)
+    else:
+        return ({"error": "Invalid image url"}, 400, response_headers)
+
+
+def txt2svg(request: Txt2SVGModel | Txt2ImgModel):
+    try:
+        response = txt2img(request)
+        if response[1] != 200:
+            return response
+
+        img2svg_req = Img2SVGModel(image_url=response[0].get("url"))
+        img2svg_rep = img2svg(img2svg_req)
+        if img2svg_rep[1] != 200:
+            return img2svg_rep
+
+        upload_url = gcp_service.upload_svg_to_storage(
+            img2svg_rep[0], "bashful_api", f"svg/{uuid.uuid1()}.svg"
+        )
+
+
+        return (
+            {"svg_url": upload_url, "image_url": response[0].get("url")},
+            200,
+            response_headers,
+        )
+    except Exception as e:
+        logger.error(e)
+        return ({"error": str(e)}, 500, response_headers)
+
+
+def remove_background(request: RemoveBGRequest):
+    data = request.json
+    img_response = requests.get(data.get("image_url"))
+
+    image_data = img_response.content
+
+    response = requests.post(
+        'https://sdk.photoroom.com/v1/segment',
+        headers={'x-api-key': 'eebb03f0afc9a8df9781f0c63c5c4d9edfbe9906'},
+        files={'image_file': image_data},
+    )
+
+    upload_url = gcp_service.upload_image_to_storage(
+        response.content, "bashful_api", f"remove_bg/{uuid.uuid1()}.png"
+    )
+
+
+    return ({"image_url": upload_url}, 200, response_headers)

bashful_studio.py

@@ -439,26 +439,4 @@ def embed_watermark(request):
     except Exception as e:
         logger.error(e)
         return ({"error": str(e)}, 500, response_headers)
-
-def img2svg(request):
-
-    request_data = request.json
-    image_url = request_data.get("image_url")
-    if not image_url:
-        return ({"error": "Invalid image url"}, 400 , response_headers)
-
-    response = requests.post(
-        'https://vectorizer.ai/api/v1/vectorize',
-        data={
-            'image.url': image_url,
-            # TODO: Add more upload options here
-        },
-        headers={
-            'Authorization':
-            'Basic dmtjM3prbW44djM2ZmVkOjVzMXMzN2l2czRoZHNyazJjczVtZ2Uxa2ZwcjdtZmNuZzllbXM0czNpODdwZGZvczNpMHY='
-        },
-    )
-    if response.status_code == requests.codes.ok:
-        return (response.content, 200, response_headers)
-    else:
-        return ({"error": "Invalid image url"}, 400 , response_headers)
+

chatbot/chat.py

@@ -0,0 +1,11 @@
+def chat_bot():
+    while True:
+        user_input = input("You: ")
+        if user_input.lower() == 'exit':
+            break
+        else:
+            print("Bot: " + user_input)
+
+if __name__ == "__main__":
+    print("Chat Bot is ready. Type 'exit' to end the conversation.")
+    chat_bot()

chatbot/palm_based_chat.py

@@ -0,0 +1,98 @@
+import os
+import re
+from typing import Union
+from langchain.tools import BaseTool, StructuredTool, Tool, tool
+from langchain.agents import AgentType, initialize_agent
+from langchain.chat_models import ChatVertexAI, ChatOpenAI
+from langchain import LLMMathChain
+from langchain.prompts.chat import (
+    ChatPromptTemplate,
+    SystemMessagePromptTemplate,
+    HumanMessagePromptTemplate,
+)
+from langchain.schema import (
+    HumanMessage,
+    SystemMessage
+)
+from rembg import remove
+from langchain.agents import Tool, AgentExecutor, LLMSingleActionAgent, AgentOutputParser
+from langchain.schema import AgentAction, AgentFinish, HumanMessage
+
+
+chat = ChatVertexAI(project="shepard-379102")
+# chat = ChatOpenAI()
+
+
+
+def remove_background(message: str):
+    input_path = 'with_background_2.png'
+    output_path = 'without_background_2.png'
+
+    with open(input_path, 'rb') as i:
+        with open(output_path, 'wb') as o:
+            input = i.read()
+            output = remove(input)
+            o.write(output)
+
+def get_image_location(message: str):
+    path = os.path.join(os.path.dirname(__file__), message)
+    return path
+
+def get_this_file_location(message: str):
+    # Return the location of this file
+    return os.path.dirname(__file__)
+
+tools = [
+    Tool.from_function(
+        func=remove_background,
+        name = "Background Remover",
+        description="This removes the backgrounds from images."
+        # coroutine= ... <- you can specify an async method if desired as well
+    ),
+        Tool.from_function(
+        func=get_image_location,
+        name = "Image Location Getter",
+        description="This builds the location of the image on the server."
+        # coroutine= ... <- you can specify an async method if desired as well
+    ),
+            Tool.from_function(
+        func=get_this_file_location,
+        name = "Image Location Getter",
+        description="This builds the location of the image on the server."
+        # coroutine= ... <- you can specify an async method if desired as well
+    ),
+]
+
+class CustomOutputParser(AgentOutputParser):
+
+    def parse(self, llm_output: str) -> Union[AgentAction, AgentFinish]:
+        print("llm_output:\n\n", llm_output)
+        # Check if agent should finish
+        if "Final Answer:" in llm_output:
+            return AgentFinish(
+                # Return values is generally always a dictionary with a single `output` key
+                # It is not recommended to try anything else at the moment :)
+                return_values={"output": llm_output.split("Final Answer:")[-1].strip()},
+                log=llm_output,
+            )
+        # Parse out the action and action input
+        regex = r"Action: (.*?)[\n]*Action Input:[\s]*(.*)"
+        match = re.search(regex, llm_output, re.DOTALL)
+        if not match:
+            raise ValueError(f"Could not parse LLM output: `{llm_output}`")
+        action = match.group(1).strip()
+        action_input = match.group(2)
+        # Return the action and action input
+        return AgentAction(tool=action, tool_input=action_input.strip(" ").strip('"'), log=llm_output)
+
+
+messages = [
+    SystemMessage(content="You are a helpful assistant that builds prompts for text to image generators iteratively by gathering requirements from chatting with users.  You edit the prompts and the AI generates images. You edit the images based on the edits the users asks for."),
+    HumanMessage(content="Remove the background from this image at where this script is running, the name of the file is with_background_2.png."),
+]
+agent = initialize_agent(tools, chat, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)
+result = agent.run(messages)
+print(result)
+# result = chat(messages)
+# print(result)
+

chatbot/remove_background.py

@@ -0,0 +1,10 @@
+from rembg import remove
+
+input_path = 'with_background_2.png'
+output_path = 'without_background_2.png'
+
+with open(input_path, 'rb') as i:
+    with open(output_path, 'wb') as o:
+        input = i.read()
+        output = remove(input)
+        o.write(output)

chatbot/test.py

@@ -0,0 +1,71 @@
+import re
+from langchain.agents import Tool, AgentExecutor, BaseSingleActionAgent, BaseMultiActionAgent
+from langchain.schema import AgentAction, AgentFinish
+from typing import List, Tuple, Any, Union
+
+class FileReader:
+    def read_file(self, location: str) -> str:
+        with open(location, 'r') as f:
+            return f.read()
+
+class BackgroundRemover:
+    def remove_background(self, image_path: str) -> str:
+        # code to remove background from image
+        return "background removed from " + image_path
+
+class Joker:
+    def make_joke(self, image_path: str) -> str:
+        # code to remove background from image
+        return "background removed from " + image_path
+
+file_reader = FileReader()
+background_remover = BackgroundRemover()
+joker = Joker()
+
+tools = [
+    Tool(
+        name="Read File",
+        func=file_reader.read_file,
+        description="reads a file given a location"
+    ),
+    Tool(
+        name="Remove Background",
+        func=background_remover.remove_background,
+        description="removes the background from an image"
+    ),
+        Tool(
+        name="Make Joke",
+        func=joker.make_joke,
+        description="removes the background from an image"
+    )
+]
+
+class CustomAgent(BaseMultiActionAgent):
+    @property
+    def input_keys(self):
+        return ["message"]
+
+    def plan(
+        self, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any
+    ) -> Union[AgentAction, AgentFinish]:
+        file_path = re.search(r'remove background from (.+)', kwargs["message"]).group(1)
+        return AgentAction(tool="Read File", tool_input=file_path, log="")
+
+    def aplan(
+        self, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any
+    ) -> Union[AgentAction, AgentFinish]:
+        file_path = re.search(r'remove background from (.+)', kwargs["message"]).group(1)
+        return AgentAction(tool="Read File", tool_input=file_path, log="")
+
+agent = CustomAgent()
+
+# agent = LLMSingleActionAgent(
+#     llm_chain=llm_chain, 
+#     output_parser=output_parser,
+#     stop=["\nObservation:"], 
+#     allowed_tools=tool_names
+# )
+agent_executor = AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True)
+
+result = agent_executor.run("remove background from yolo.txt")
+print(result)

chatbot/yolo.txt

@@ -0,0 +1 @@
+Sup

config.py

@@ -53,3 +53,9 @@
 VECTORIZER_AI_URL = (
     os.environ.get("VECTORIZER_AI_URL") or "https://vectorizer.ai/api/v1/vectorize"
 )
+TRAINING_DB_URL = (
+    os.environ.get("TRAINING_DB_URL") or "http://localhost:1337/"
+)
+BASHFUL_STUDIO_API_URL = (
+    os.environ.get("BASHFUL_STUDIO_API_URL") or "http://localhost:1337/"
+)

local_dev_server.py

@@ -22,4 +22,4 @@ def route_func(*args, **kwargs):
         app.add_url_rule(f'/{name}', name, route_func, methods=['POST', 'GET', 'PUT', 'DELETE', 'PATCH', 'OPTIONS', 'HEAD'])
 
 if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=8080)
+    app.run(host="0.0.0.0", debug=True, port=8080)