Update README

.gitignore

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+output/
+env/
+tools/__pycache__/
+tools/config.json

README.md

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 # memegraph
 I previously did meme generation via Langchain in https://github.com/runyanjake/memechain. Here is the same project but written using Langgraph instead, since that seems to have superseded Langchain in recent time.
+
+The main reason to make the switch is to explore [multi-agent](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/multi-agent-collaboration.ipynb) workflows, which hopefully we can apply to this project at some point.
+
+## Setup 
+
+### Python 
+```
+python3 -m venv env
+source env/bin/activate
+pip install -r requirements.txt
+python main.py
+...
+deactivate
+```
+
+## Usage 
+Can specify prompt when calling script or will use default prompt.
+```
+python main.py 
+python main.py --prompt "Generate an image for the 'Leonardo dicaprio cheers' meme with the text 'LANGGRAPH MEMES'."
+```

main.py

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+from langchain_ollama.llms import OllamaLLM
+from langchain_core.output_parsers import PydanticOutputParser
+from langgraph.graph import StateGraph, END
+
+from pydantic import BaseModel, Field
+
+from tools.get_memes import get_memes
+from tools.caption_image import caption_image
+from tools.download_image import download_image
+
+from typing import TypedDict, Optional
+
+import argparse
+import json
+import re 
+
+############################# State Definition ################################
+class State(TypedDict):
+    question: str
+    template_name: Optional[str]
+    text: Optional[list[str]]
+    template_id: Optional[int]
+    caption_result: Optional[dict]
+    image_path: Optional[str]
+
+############################# LLM Definition ##################################
+llm = OllamaLLM(model="llama3")
+
+class MemeInfo(BaseModel):
+    template_name: str = Field(..., description="The meme template name")
+    text: list[str] = Field(..., description="List of captions/texts for the meme")
+
+parser = PydanticOutputParser(pydantic_object=MemeInfo)
+
+def parse_input(state: State) -> State:
+    prompt = f"""
+    Extract the meme name and list of texts from the user's request. 
+    Return the output in this JSON format:
+
+    {parser.get_format_instructions()}
+
+    User input: {state["question"]}
+    """
+
+    response = llm.invoke(prompt)
+    parsed = parser.invoke(response)
+    print(parsed)
+    return {**state, **parsed.model_dump()}
+
+######################## Graph Components Definition ##########################
+def node_get_memes(state: State) -> State:
+    memes_str = get_memes()
+    memes = memes_str.strip().splitlines()
+
+    for meme in memes:
+        match = re.match(r"ID: (\d+), Name: (.+)", meme)
+        if match:
+            meme_id = int(match.group(1))
+            meme_name = match.group(2).strip()
+
+            if meme_name.lower() == state["template_name"].lower():
+                print("Found Meme: " + meme)
+                return {**state, "template_id": meme_id}
+
+    raise ValueError(f"No matching meme found for template_name: {state['template_name']}\nAvailable Memes:\n{memes}")
+
+def node_caption_image(state: State) -> State:
+    input_data = {
+        "template_id": int(state["template_id"]),
+        "text": state["text"]
+    }
+    json_input = json.dumps(input_data)
+    result = caption_image(json_input)
+    print(result)
+    return {**state, "caption_result": result}
+
+def node_download_image(state: State) -> State:
+    image_url = state["caption_result"]
+    if isinstance(image_url, str) and image_url.startswith("http"):
+        download_payload = json.dumps({"url": image_url})
+        result = download_image(download_payload)
+        return {**state, "image_path": result}
+    else:
+        print("Failed to download image. " + image_url)
+
+############################## Graph Definition ###############################
+graph = StateGraph(State)
+
+graph.add_node("parse_input", parse_input)
+graph.add_node("get_memes", node_get_memes)
+graph.add_node("caption_image", node_caption_image)
+graph.add_node("download_image", node_download_image)
+
+graph.set_entry_point("parse_input")
+graph.add_edge("parse_input", "get_memes")
+graph.add_edge("get_memes", "caption_image")
+graph.add_edge("caption_image", "download_image")
+graph.add_edge("download_image", END)
+
+app = graph.compile()
+
+#################################### Run ######################################
+def main():
+    parser = argparse.ArgumentParser(description="Meme Generation Script")
+    parser.add_argument(
+        "--prompt", 
+        type=str, 
+        help="Optional prompt for the meme generation", 
+        default="Generate an image for the 'two buttons' meme with first text 'generated meme' and second text 'langgraph error'."
+    )
+    args = parser.parse_args()
+    
+    question = args.prompt
+    final_state = app.invoke({"question": question})
+    print(final_state["image_path"])
+
+if __name__ == "__main__":
+    main()
+

requirements.txt

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+langchain_community
+langchain_core>=0.1.35
+langchain_experimental
+langchain_ollama
+langgraph
+pillow
+pydantic

tools/caption_image.py

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+import json
+import requests
+
+CAPTION_IMAGE_URL = "https://api.imgflip.com/caption_image"
+
+def load_config():
+    with open('tools/config.json') as config_file:
+        return json.load(config_file)   
+
+def caption_image(input_data):
+    # Replace single quotes with double quotes because langchain likes to use single quotes
+    input_data = input_data.replace("'", '"')
+    
+    data = json.loads(input_data)
+    template_id = data['template_id']
+    text = data['text']
+
+    config = load_config()
+    username = config['username']
+    password = config['password']
+
+    url = CAPTION_IMAGE_URL
+    payload = {
+        "template_id": template_id,
+        "username": username,
+        "password": password,
+    }
+    
+    for i in range(len(text)):
+        payload[f'text{i}'] = text[i]
+
+    response = requests.post(url, data=payload)
+    result = response.json()
+
+    if result['success']:
+        meme_url = result['data']['url']
+        print(f"Meme created! URL: {meme_url}")
+        return meme_url
+    else:
+        return None

tools/config.json.blanked

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+{
+  "username":"xxxx",
+  "password":"yyyy"
+}

tools/download_image.py

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+import os
+import requests
+import json
+
+def download_image(input_data):
+    input_data = input_data.replace("'", '"')
+    
+    data = json.loads(input_data)
+    url = data['url']
+
+    response = requests.get(url)
+    if response.status_code == 200:
+        output_dir = 'output'
+        os.makedirs(output_dir, exist_ok=True)
+        image_path = os.path.join(output_dir, url.split("/")[-1])
+        with open(image_path, 'wb') as f:
+            f.write(response.content)
+        print(f"Image saved to {image_path}")
+        return image_path
+    else:
+        print("Failed to download image.")
+        return None

tools/get_memes.py

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+import requests
+
+GET_MEMES_URL = "https://api.imgflip.com/get_memes"
+
+def get_memes():
+    return get_memes_helper()
+
+def get_memes_helper():
+    response = requests.get(GET_MEMES_URL)
+    result = response.json()
+
+    if result['success']:
+        memes = result['data']['memes']
+        memes_str = "\n".join([f"ID: {meme['id']}, Name: {meme['name']}" for meme in memes])
+        return memes_str
+    else:
+        return "No template_ids found."
+