enigmare/v2-crawler

1{"id":"doc-langchain_overview_docs_by_langchain-be522adf","source":"documentation","title":"LangChain overview - Docs by LangChain","url":"https://python.langchain.com/docs/","text":"Documentation IndexFetch the complete documentation index at: /llms.txtUse this file to discover all available pages before exploring further.\n\nExample:\n```text\n# pip install -qU langchain \"langchain[openai]\"\nfrom langchain.agents import create_agent\n\ndef get_weather(city: str) -> str:\n    \"\"\"Get weather for a given city.\"\"\"\n    return f\"It's always sunny in {city}!\"\n\nagent = create_agent(\n    model=\"openai:gpt-5.5\",\n    tools=[get_weather],\n    system_prompt=\"You are a helpful assistant\",\n)\n\nresult = agent.invoke(\n    {\"messages\": [{\"role\": \"user\", \"content\": \"What's the weather in San Francisco?\"}]}\n)\nprint(result[\"messages\"][-1].content_blocks)\n```\n\nExample:\n```text\n# pip install -qU langchain \"langchain[google-genai]\"\nfrom langchain.agents import create_agent\n\ndef get_weather(city: str) -> str:\n    \"\"\"Get weather for a given city.\"\"\"\n    return f\"It's always sunny in {city}!\"\n\nagent = create_agent(\n    model=\"google_genai:gemini-2.5-flash-lite\",\n    tools=[get_weather],\n    system_prompt=\"You are a helpful assistant\",\n)\n\nresult = agent.invoke(\n    {\"messages\": [{\"role\": \"user\", \"content\": \"What's the weather in San Francisco?\"}]}\n)\nprint(result[\"messages\"][-1].content_blocks)\n```\n\nExample:\n```text\n# pip install -qU langchain \"langchain[anthropic]\"\nfrom langchain.agents import create_agent\n\ndef get_weather(city: str) -> str:\n    \"\"\"Get weather for a given city.\"\"\"\n    return f\"It's always sunny in {city}!\"\n\nagent = create_agent(\n    model=\"claude-sonnet-4-6\",\n    tools=[get_weather],\n    system_prompt=\"You are a helpful assistant\",\n)\n\nresult = agent.invoke(\n    {\"messages\": [{\"role\": \"user\", \"content\": \"What's the weather in San Francisco?\"}]}\n)\nprint(result[\"messages\"][-1].content_blocks)\n```\n\nExample:\n```text\n# pip install -qU langchain langchain-openrouter\nfrom langchain.agents import create_agent\n\ndef get_weather(city: str) -> str:\n    \"\"\"Get weather for a given city.\"\"\"\n    return f\"It's always sunny in {city}!\"\n\nagent = create_agent(\n    model=\"openrouter:anthropic/claude-sonnet-4-6\",\n    tools=[get_weather],\n    system_prompt=\"You are a helpful assistant\",\n)\n\nresult = agent.invoke(\n    {\"messages\": [{\"role\": \"user\", \"content\": \"What's the weather in San Francisco?\"}]}\n)\nprint(result[\"messages\"][-1].content_blocks)\n```\n\nExample:\n```text\n# pip install -qU langchain langchain-fireworks\nfrom langchain.agents import create_agent\n\ndef get_weather(city: str) -> str:\n    \"\"\"Get weather for a given city.\"\"\"\n    return f\"It's always sunny in {city}!\"\n\nagent = create_agent(\n    model=\"fireworks:accounts/fireworks/models/qwen3p5-397b-a17b\",\n    tools=[get_weather],\n    system_prompt=\"You are a helpful assistant\",\n)\n\nresult = agent.invoke(\n    {\"messages\": [{\"role\": \"user\", \"content\": \"What's the weather in San Francisco?\"}]}\n)\nprint(result[\"messages\"][-1].content_blocks)\n```\n\nExample:\n```text\n# pip install -qU langchain langchain-baseten\nfrom langchain.agents import create_agent\n\ndef get_weather(city: str) -> str:\n    \"\"\"Get weather for a given city.\"\"\"\n    return f\"It's always sunny in {city}!\"\n\nagent = create_agent(\n    model=\"baseten:zai-org/GLM-5.2\",\n    tools=[get_weather],\n    system_prompt=\"You are a helpful assistant\",\n)\n\nresult = agent.invoke(\n    {\"messages\": [{\"role\": \"user\", \"content\": \"What's the weather in San Francisco?\"}]}\n)\nprint(result[\"messages\"][-1].content_blocks)\n```\n\nExample:\n```text\n# pip install -qU langchain langchain-ollama\nfrom langchain.agents import create_agent\n\ndef get_weather(city: str) -> str:\n    \"\"\"Get weather for a given city.\"\"\"\n    return f\"It's always sunny in {city}!\"\n\nagent = create_agent(\n    model=\"ollama:devstral-2\",\n    tools=[get_weather],\n    system_prompt=\"You are a helpful assistant\",\n)\n\nresult = agent.invoke(\n    {\"messages\": [{\"role\": \"user\", \"content\": \"What's the weather in San Francisco?\"}]}\n)\nprint(result[\"messages\"][-1].content_blocks)\n```\n\nExample:\n```text\n# pip install -qU langchain \"langchain[openai]\"\nimport os\nfrom langchain.agents import create_agent\nfrom langchain.chat_models import init_chat_model\n\ndef get_weather(city: str) -> str:\n    \"\"\"Get weather for a given city.\"\"\"\n    return f\"It's always sunny in {city}!\"\n\nmodel = init_chat_model(\n    \"azure_openai:gpt-5.5\",\n    azure_deployment=os.environ[\"AZURE_OPENAI_DEPLOYMENT_NAME\"],\n)\nagent = create_agent(\n    model=model,\n    tools=[get_weather],\n    system_prompt=\"You are a helpful assistant\",\n)\n\nresult = agent.invoke(\n    {\"messages\": [{\"role\": \"user\", \"content\": \"What's the weather in San Francisco?\"}]}\n)\nprint(result[\"messages\"][-1].content_blocks)\n```\n\nExample:\n```text\n# pip install -qU langchain langchain-aws\nfrom langchain.agents import create_agent\n\ndef get_weather(city: str) -> str:\n    \"\"\"Get weather for a given city.\"\"\"\n    return f\"It's always sunny in {city}!\"\n\n# US cross-region inference profile; use global.anthropic.claude-sonnet-4-6 for worldwide routing.\nagent = create_agent(\n    model=\"bedrock_converse:us.anthropic.claude-sonnet-4-6\",\n    tools=[get_weather],\n    system_prompt=\"You are a helpful assistant\",\n)\n\nresult = agent.invoke(\n    {\"messages\": [{\"role\": \"user\", \"content\": \"What's the weather in San Francisco?\"}]}\n)\nprint(result[\"messages\"][-1].content_blocks)\n```\n\nExample:\n```text\n# pip install -qU langchain \"langchain[huggingface]\"\nfrom langchain.agents import create_agent\n\ndef get_weather(city: str) -> str:\n    \"\"\"Get weather for a given city.\"\"\"\n    return f\"It's always sunny in {city}!\"\n\nagent = create_agent(\n    model=\"huggingface:microsoft/Phi-3-mini-4k-instruct\",\n    tools=[get_weather],\n    system_prompt=\"You are a helpful assistant\",\n)\n\nresult = agent.invoke(\n    {\"messages\": [{\"role\": \"user\", \"content\": \"What's the weather in San Francisco?\"}]}\n)\nprint(result[\"messages\"][-1].content_blocks)\n```\n\n<|endofdoc|>","metadata":{"transformedAt":"2026-08-18T15:21:32.263Z","totalSectionsIncluded":1,"totalCodeBlocksIncluded":10,"totalLines":220,"estimatedTokens":1440}}2