Ignore images folder

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text

.gitignore

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+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+
+# Virtual environments
+.venv
+.env
+
+images/

.python-version

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+3.11

README.md

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+---
+title: Smgp
+emoji: 🌍
+colorFrom: red
+colorTo: pink
+sdk: docker
+pinned: false
+short_description: social media content generator
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

pyproject.toml

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+[project]
+name = "smpg"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "google>=3.0.0",
+    "google-genai>=1.31.0",
+    "huggingface-hub>=0.34.4",
+    "langfuse>=3.3.4",
+    "nest-asyncio>=1.6.0",
+    "openai-agents>=0.2.8",
+    "pillow>=11.3.0",
+    "pydantic>=2.11.7",
+    "pydantic-ai[logfire]>=1.0.1",
+]
+
+[tool.setuptools.packages.find]
+where = ["src"]
+
+

src/_agents.py

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+from agents import Agent, RunContextWrapper
+from model import get_model
+
+
+#----------------------- content agent ----------------------------------
+
+def content_prompt(context: RunContextWrapper, agent: Agent):
+    """You are a LinkedIn Content Writer AI.  
+Your task is to take a user's description of an idea, event, or announcement and turn it into engaging LinkedIn post text.  
+
+Guidelines:
+- Start with a strong hook or headline (1 line).
+- Write a clear and engaging body (2-5 short sentences).
+- Use a professional but approachable tone suited for LinkedIn.
+- Add 3-6 relevant hashtags.
+- End with a call-to-action (CTA), e.g., “Let's connect”, “Check out the details”, “Join the discussion”.
+- Keep sentences concise and scannable for social media.
+"""
+
+
+
+content_agent = Agent(
+    name="content_agent",
+    instructions=content_prompt,
+    model=get_model('gemini-2.0-flash'),
+)
+
+
+#----------------------- content agent ------------------------------------
+
+
+
+#----------------------- Imgae agent -------------------------------------------
+
+
+
+
+
+
+
+
+

src/main.py

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+import os
+import asyncio
+from dataclasses import dataclass
+from agents import set_tracing_disabled, Runner, SQLiteSession
+from _agents import content_agent
+from pydantic import BaseModel, Field, ConfigDict
+from typing import Optional
+import nest_asyncio
+import logfire
+from langfuse import get_client
+ 
+ 
+# set_tracing_disabled(disabled=True)
+
+# set_tracing_disabled(disabled=True)
+
+nest_asyncio.apply()
+
+
+logfire.configure(
+    service_name='smpg_agent',
+    send_to_logfire=False,
+)
+
+logfire.instrument_openai_agents()
+
+
+ 
+langfuse = get_client()
+ 
+# Verify connection
+if langfuse.auth_check():
+    print("Langfuse client is authenticated and ready!")
+else:
+    print("Authentication failed. Please check your credentials and host.")
+
+
+
+
+class AgentContext(BaseModel):
+    user_input: Optional[str] = Field(default=None,description="The input provided by the user to the agent.")
+    post_content: Optional[str] = Field(default=None,description="The generated content for the post.")
+
+    model_config= ConfigDict(extra='forbid')
+
+async def main():
+    print("Hello from smpg!")
+
+    session = SQLiteSession("conversation_123")
+
+    agent_context = AgentContext(
+        user_input="Write a LinkedIn post about the importance of AI in modern business strategies."
+        )
+
+
+    
+# orchestrator_agent = Agent(
+#     name="orchestrator_agent",
+#     instructions=(
+#         "You are a translation agent. You use the tools given to you to translate."
+#         "If asked for multiple translations, you call the relevant tools in order."
+#         "You never translate on your own, you always use the provided tools."
+#     ),
+#     tools=[
+#         spanish_agent.as_tool(
+#             tool_name="translate_to_spanish",
+#             tool_description="Translate the user's message to Spanish",
+#         ),
+#         french_agent.as_tool(
+#             tool_name="translate_to_french",
+#             tool_description="Translate the user's message to French",
+#         ),
+#         italian_agent.as_tool(
+#             tool_name="translate_to_italian",
+#             tool_description="Translate the user's message to Italian",
+#         ),
+#     ],
+#     model=model
+# )
+
+
+
+    result = await Runner.run(content_agent, context=agent_context, input=agent_context.user_input, session=session ,max_turns=5)
+    
+    agent_context.post_content = result.final_output
+    print("Generated Post Content:")
+    print(agent_context.post_content)
+
+
+
+if __name__ == "__main__":
+   asyncio.run(main())

src/model.py

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+from agents import OpenAIChatCompletionsModel, AsyncOpenAI
+from dotenv import load_dotenv, find_dotenv
+import os
+
+_: bool = load_dotenv(find_dotenv())
+
+
+# deepseek_api_key = os.getenv("DEEPSEEK_API_KEY")
+google_api_key = os.getenv("GOOGLE_API_KEY")
+# grok_api_key = os.getenv("GROK_API_KEY")
+openrouter_api_key = os.getenv("OPENROUTER_API_KEY")
+
+DEEPSEEK_BASE_URL = "https://api.deepseek.com/v1"
+GROK_BASE_URL = "https://api.x.ai/v1"
+GEMINI_BASE_URL = "https://generativelanguage.googleapis.com/v1beta/openai/"
+OPENROUTER_BASE_URL = "https://openrouter.ai/api/v1"
+
+
+
+openrouter_client = AsyncOpenAI(base_url=OPENROUTER_BASE_URL, api_key=openrouter_api_key)
+# deepseek_client = AsyncOpenAI(base_url=DEEPSEEK_BASE_URL, api_key=deepseek_api_key)
+# grok_client = AsyncOpenAI(base_url=GROK_BASE_URL, api_key=grok_api_key)
+gemini_client = AsyncOpenAI(base_url=GEMINI_BASE_URL, api_key=google_api_key)
+
+def get_model(model_name: str):
+    if "/" in model_name:
+        return OpenAIChatCompletionsModel(model=model_name, openai_client=openrouter_client)
+    # elif "deepseek" in model_name:
+    #     return OpenAIChatCompletionsModel(model=model_name, openai_client=deepseek_client)
+    # elif "grok" in model_name:
+    #     return OpenAIChatCompletionsModel(model=model_name, openai_client=grok_client)
+    elif "gemini" in model_name:
+        return OpenAIChatCompletionsModel(model=model_name, openai_client=gemini_client)
+    else:
+        return model_name

src/utils/image-generation.py

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+import os
+import re
+from google import genai
+from huggingface_hub import InferenceClient
+from dotenv import load_dotenv, find_dotenv
+
+_: bool = load_dotenv(find_dotenv())
+
+
+client = genai.Client(
+    # vertexai=True, project='1089055075981', location='us-central1'
+)
+
+
+aspect_ratios = {
+    "1:1": (1328, 1328),
+    "16:9": (1664, 928),
+    "9:16": (928, 1664),
+    "4:3": (1472, 1140),
+    "3:4": (1140, 1472),
+    "3:2": (1584, 1056),
+    "2:3": (1056, 1584),
+}
+
+hf_client = InferenceClient(
+    provider="replicate",
+    api_key=os.environ["HF_TOKEN"],
+)
+
+
+def generate_json_from_idea(idea: str, defaultValues:str) -> str:
+    """Generates a detailed JSON prompt from a simple idea using a Gemini model."""
+
+    # The prompt template includes the desired JSON schema structure.
+    schema_template = """Convert the attached user idea into a detailed JSON object for generating an image. The output should only be the raw JSON object, without any markdown formatting like ```json ... ```.
+
+Idea: "{idea}"
+
+defaultValues:{defaultValues}
+
+Schema:
+{{
+    "meta": {{
+        "styleName": "...", // A unique, descriptive name for this specific image style or preset (e.g., "Ethereal Forest Magic", "Cyberpunk Noir Alley").
+        "aspectRatio": "...", // The proportional relationship between the width and height of the image (e.g., "16:9", "1:1", "4:5", "21:9").
+        "promptPrefix": "..." // Optional text to prepend to a generated prompt, like a file name, a version number, or a specific trigger word.
+    }},
+    "camera": {{
+        "model": "...", // Describes the camera, lens, or artistic medium used (e.g., "DSLR", "iPhone 15 Pro", "8x10 view camera", "Watercolor on cold-press paper", "3D render in Blender").
+        "focalLength": "...", // The lens's focal length, which affects the field of view and perspective distortion (e.g., "16mm wide-angle", "85mm portrait", "200mm telephoto", "Isometric perspective").
+        "angle": "...", // The camera's angle relative to the main subject or scene (e.g., "eye-level", "high-angle", "dutch angle", "drone shot", "worm's-eye view").
+        "type": "..." // The genre or type of photography or art style (e.g., "macro photography", "landscape", "fantasy illustration", "architectural rendering", "abstract art").
+    }},
+    "subject": {{
+        "primary": "...", // The main focal point or subject of the image (e.g., "a majestic mountain range", "a lone wolf", "an ancient wizard", "a futuristic cityscape", "an abstract shape").
+        "emotion": "...", // The dominant emotion or mood conveyed by the subject or the overall scene (e.g., "serene and peaceful", "joyful", "melancholy", "menacing", "awe-inspiring").
+        "pose": "...", // The posture, action, or arrangement of the subject(s) (e.g., "running towards the camera", "sitting in quiet contemplation", "a winding river", "a chaotic explosion").
+        "gaze": "..." // The direction of the subject's gaze or the directional focus of the composition (e.g., "looking off-camera", "breaking the fourth wall", "facing away from the viewer", "pointing towards the horizon").
+    }},
+    "character": {{
+        "appearance": "...", // Detailed physical description of a character or key object (e.g., "weathered face with a long white beard", "sleek, chrome-plated robot", "moss-covered ancient tree").
+        "wardrobe": "...", // Clothing, armor, or any form of covering on the subject (e.g., "ornate golden armor", "tattered rags", "a vibrant kimono", "a car's glossy paint job").
+        "accessories": "..." // Additional items worn by or associated with the subject (e.g., "a magical amulet", "cybernetic implants", "a pair of glasses", "a sword and shield").
+    }},
+    "composition": {{
+        "theory": "...", // The compositional rules or theories applied (e.g., "rule of thirds", "golden ratio", "leading lines", "symmetrical balance", "negative space").
+        "visualHierarchy": "..." // Describes the order in which the viewer's eye is drawn to different elements in the scene, from most to least prominent.
+    }},
+    "setting": {{
+        "environment": "...", // The general environment or location of the scene (e.g., "a mystical forest", "a bustling cyberpunk city", "a tranquil beach at sunset", "a minimalist white room", "the surface of Mars").
+        "architecture": "...", // Describes any buildings, ruins, or significant natural structures (e.g., "gothic cathedrals", "brutalist architecture", "alien monoliths", "towering rock formations").
+        "furniture": "..." // Key objects, props, or furniture within the setting that add context or detail (e.g., "a single throne", "scattered futuristic debris", "a rustic wooden fence").
+    }},
+    "lighting": {{
+        "source": "...", // The primary source of light in the scene (e.g., "dramatic moonlight", "soft window light", "flickering candlelight", "neon signs", "magical glow").
+        "direction": "...", // The direction from which the light originates (e.g., "backlighting", "rim lighting", "top-down light", "light from below").
+        "quality": "..." // The quality and characteristics of the light and shadows (e.g., "soft and diffused", "hard and high-contrast", "dappled", "volumetric light rays", "caustic reflections").
+    }},
+    "style": {{
+        "artDirection": "...", // The overarching artistic style, movement, or influence (e.g., "impressionism", "art deco", "cyberpunk", "vaporwave", "ghibli-inspired", "cinematic").
+        "mood": "..." // The overall mood, feeling, or atmosphere of the image (e.g., "ethereal and dreamy", "dystopian and gritty", "whimsical and cheerful", "epic and dramatic").
+    }},
+    "rendering": {{
+        "engine": "...", // The rendering engine, technique, or medium used to create the final image (e.g., "Octane Render", "oil painting", "cross-hatching", "pixel art", "Unreal Engine 5").
+        "fidelitySpec": "...", // Specific details about the image's texture and fidelity (e.g., "heavy film grain", "sharp digital focus", "visible brushstrokes", "chromatic aberration", "lens flare").
+        "postProcessing": "..." // Any post-processing or finishing effects applied (e.g., "color grading with a teal and orange look", "vignette", "bloom and glare", "a vintage photo filter").
+    }},
+    "colorPalette": {{
+        "primaryColors": [ // The most dominant colors that define the overall color scheme of the image.
+            {{ "name": "...", "hex": "...", "percentage": "..." }},
+            {{ "name": "...", "hex": "...", "percentage": "..." }}
+        ],
+        "accentColors": [ // Complementary or contrasting colors used for emphasis, detail, or highlights.
+            {{ "name": "...", "hex": "...", "percentage": "..." }},
+            {{ "name": "...", "hex": "...", "percentage": "..." }}
+        ]
+    }}
+}}
+"""
+    prompt = schema_template.format(idea=idea,defaultValues=defaultValues)
+
+    response = client.models.generate_content(
+        model="gemini-2.5-pro",
+        contents=prompt,
+    )
+
+    print(response.text)
+    return response.text
+
+
+def generate_images(
+    idea: str,
+    prompt: str,
+    aspectRatio: str = "1:1",  # "1:1", "3:4", "4:3", "9:16", and "16:9".
+    output_dir: str = "images",
+    num_images: int = 1,
+):
+    """Generates images using Imagen and saves them to the output directory."""
+
+
+    try:
+        print(prompt)
+        print(f"Generating {num_images} images for {idea}")
+        # response = client.models.generate_images(
+        #     model="imagen-4.0-generate-preview-06-06",
+        #     prompt=prompt,
+        #     config=genai.types.GenerateImagesConfig(
+        #         number_of_images=num_images,
+        #         aspect_ratio=aspectRatio,
+        #     ),
+        # )
+
+        width, height = aspect_ratios[aspectRatio]
+        response = hf_client.text_to_image(
+            prompt=prompt,
+            model="Qwen/Qwen-Image",
+            width=width,
+            height=height,
+
+        )
+        print(response)
+
+        clean_idea = (re.sub(r"[^a-zA-Z0-9\s]", "", idea[:30]).lower().replace(" ", "-"))
+        image_path = os.path.join(output_dir, f"{clean_idea}-.png")
+        response.save(image_path)
+        with open(os.path.join(output_dir, f"{clean_idea}.json"), "w") as f:
+            f.write(prompt)
+        print(f"Saved image and prompt to {image_path}")
+
+        # for i, generated_image in enumerate(response):
+        #     clean_idea = (
+        #         re.sub(r"[^a-zA-Z0-9\s]", "", idea[:30]).lower().replace(" ", "-")
+        #     )
+        #     image_path = os.path.join(output_dir, f"{clean_idea}-{i+1}.png")
+        #     generated_image.image.save(image_path)
+        #     with open(os.path.join(output_dir, f"{clean_idea}.json"), "w") as f:
+        #         f.write(prompt)
+        #     print(f"Saved image and prompt to {image_path}")
+
+    except Exception as e:
+        print(f"An error occurred during image generation: {e}")
+
+
+def generate(
+    idea: str,
+    output_dir: str = "images",
+    aspectRatio: str = "1:1",
+    num_images: int = 1,
+):
+    """Orchestrates the process of generating JSON and then generating images."""
+    os.makedirs(output_dir, exist_ok=True)
+
+    ideaJson = generate_json_from_idea(idea,f"aspect_ratio:{aspectRatio}")
+
+    generate_images(
+        idea=idea,
+        prompt=f"""
+{idea}
+
+<MetaSchemaForImageGeneration>
+{ideaJson}
+</MetaSchemaForImageGeneration>
+""",
+        aspectRatio="1:1",
+        output_dir=output_dir,
+        num_images=num_images,
+    )
+
+
+if __name__ == "__main__":
+    ideas = [
+        # "A energy drink with water drops on it, ultra realistic, for a commercial.",
+        # "Graffiti with the text 'JSON Schema' on a brick wall.",
+        # "A LEGO knight fighting a huge, fire-breathing dragon on a castle wall.",
+        # "A stylish woman sipping coffee at a Parisian cafe, with the Eiffel Tower in the background. Shot in golden hour.",
+        # "An emotional, close-up portrait of an old fisherman.",
+        # "A vast, alien landscape on a distant planet with two suns, strange, towering rock formations, and bioluminescent plants. Epic sci-fi concept art.",
+        # "A whimsical illustration of a friendly fox reading a book in a cozy, cluttered library. The text 'The Midnight Reader' should be subtly integrated on a book spine.",
+        # "A magical man with sparkling pink hair and large from an anime.",
+        # "A cartoon robot waving happily, with a simple, bold outline and bright, flat colors. ",
+        # "A full-body character sheet of a realistic pirate captain, showing front, back, and side views.",
+        """An AI brain made of digital circuits seamlessly integrated into a modern office skyline, representing artificial intelligence as essential for business growth and innovation"""
+    ]
+
+    for idea in ideas:
+        generate(idea=idea,aspectRatio="1:1")