Initial commit

skills/langgraph-master/06_llm_model_ids_gemini_advanced.md

@@ -0,0 +1,118 @@
+# Gemini Advanced Features
+
+Advanced configuration and multimodal features for Google Gemini models.
+
+## Context Window and Output Limits
+
+| Model | Context Window | Max Output Tokens |
+|--------|-------------------|---------------|
+| Gemini 3 Pro | - | 64K |
+| Gemini 2.5 Pro | 1M (2M planned) | - |
+| Gemini 2.5 Flash | 1M | - |
+| Gemini 2.0 Flash | 1M | - |
+
+**Tier-based Limits**:
+- Gemini Advanced / Vertex AI: 1M tokens
+- Free tier: ~32K tokens
+
+## Parameter Configuration
+
+```python
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+llm = ChatGoogleGenerativeAI(
+    model="gemini-2.5-flash",
+    temperature=0.7,          # Creativity (0.0-1.0)
+    top_p=0.9,               # Diversity
+    top_k=40,                # Sampling
+    max_tokens=8192,         # Max output
+)
+```
+
+## Multimodal Features
+
+### Image Input
+
+```python
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_core.messages import HumanMessage
+
+llm = ChatGoogleGenerativeAI(model="gemini-2.5-flash")
+
+message = HumanMessage(
+    content=[
+        {"type": "text", "text": "What is in this image?"},
+        {"type": "image_url", "image_url": "https://example.com/image.jpg"}
+    ]
+)
+
+response = llm.invoke([message])
+```
+
+### Image Generation (Gemini 3.x)
+
+```python
+llm = ChatGoogleGenerativeAI(model="google/gemini-3-pro-image-preview")
+response = llm.invoke("Generate a beautiful sunset landscape")
+```
+
+## Streaming
+
+```python
+llm = ChatGoogleGenerativeAI(
+    model="gemini-2.5-flash",
+    streaming=True
+)
+
+for chunk in llm.stream("Question"):
+    print(chunk.content, end="", flush=True)
+```
+
+## Safety Settings
+
+```python
+from langchain_google_genai import (
+    ChatGoogleGenerativeAI,
+    HarmBlockThreshold,
+    HarmCategory
+)
+
+llm = ChatGoogleGenerativeAI(
+    model="gemini-2.5-flash",
+    safety_settings={
+        HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
+        HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
+    }
+)
+```
+
+## Retrieving Model List
+
+```python
+import google.generativeai as genai
+import os
+
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+for model in genai.list_models():
+    if 'generateContent' in model.supported_generation_methods:
+        print(f"{model.name}: {model.input_token_limit} tokens")
+```
+
+## Error Handling
+
+```python
+from google.api_core import exceptions
+
+try:
+    response = llm.invoke("Question")
+except exceptions.ResourceExhausted:
+    print("Rate limit reached")
+except exceptions.InvalidArgument as e:
+    print(f"Invalid argument: {e}")
+```
+
+## Reference Links
+
+- [Gemini API Models](https://ai.google.dev/gemini-api/docs/models)
+- [Vertex AI](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models)