Install Deploy (https://deploy.com) as a model provider in my OpenCode setup. Follow these steps exactly:

1. Detect my OS (Windows, macOS, or Linux) and pick the right global config path:
   - macOS/Linux: ~/.config/opencode/opencode.json
   - Windows: %USERPROFILE%\.config\opencode\opencode.json
   If the file does not exist, create it with this content. If it exists, MERGE the block below into it, keeping every other key I already have. If a project-level opencode.json exists in the current repo, ask me whether to put it there or globally before writing.
2. Merge in exactly this provider block (replace {DEPLOY_API_KEY} below; if the DEPLOY_API_KEY environment variable is already set in my environment, use it without asking; otherwise STOP and ask for my Deploy Secret Key, guiding me to get it first: log in at deploy.com, open Service API Keys in the left nav, use an existing Secret Key if I saved one, or click Create API Key to generate one and copy the Secret Key (it is shown only once, at generation time; the page lists Access Key IDs later, never Secret Keys), then paste it to you when you ask; do not invent a value):
   {
     "$schema": "https://opencode.ai/config.json",
     "model": "deploy/deepseek-ai/deepseek-v4.1-flash",
     "provider": {
       "deploy": {
         "npm": "@ai-sdk/openai-compatible",
         "name": "Deploy",
         "options": {
           "baseURL": "https://api-cdn.deploy.com/api/v1",
           "apiKey": "{DEPLOY_API_KEY}"
         },
         "models": {
           "deepseek-ai/deepseek-v4.1-flash": {
             "name": "Deepseek 4.1 Flash",
             "limit": { "context": 1000000, "output": 32768 },
             "modalities": {
               "input": ["text", "image"],
               "output": ["text"]
             }
           }
         }
       }
     }
   }
3. If I am a Virginia (VA1) customer, use baseURL api-va1.deploy.com/api/v1 for the provider instead. Otherwise keep https://api-cdn.deploy.com/api/v1.
4. Make sure the final file parses as valid JSON (validate it). Never print my API key back to me or commit it to any git repo.
5. Tell me to restart OpenCode, run /models, and select "Deploy / Deepseek 4.1 Flash". Then ask me to send a short test message to confirm it works.

{
  "$schema": "https://opencode.ai/config.json",
  "model": "deploy/deepseek-ai/deepseek-v4.1-flash",
  "provider": {
    "hive-ai": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Deploy",
      "options": {
        "baseURL": "https://api-cdn.deploy.com/api/v1",
        "apiKey": "{DEPLOY_API_KEY}"
      },
      "models": {
        "deepseek-ai/deepseek-v4.1-flash": {
          "name": "Deepseek 4.1 Flash",
          "limit": { "context": 1000000, "output": 32768 },
          "modalities": {
            "input": ["text", "image"],
            "output": ["text"]
          }
        }
      }
    }
  }
}

Connect Hermes Agent to Deploy (https://deploy.com) as a custom OpenAI-compatible provider. Follow these steps exactly:

1. Detect my OS and use the correct Hermes home:
   - macOS/Linux/WSL2: ~/.hermes/
   - Native Windows: %LOCALAPPDATA%\hermes\
2. Edit config.yaml in that Hermes home. MERGE the following into it, keeping every other key I already have:
   model:
     provider: custom
     default: deepseek-ai/deepseek-v4.1-flash
     base_url: https://api-cdn.deploy.com/api/v1
     api_key: ${DEPLOY_API_KEY}
   If a model: block already exists, replace only its inner values.
3. Edit the .env file in the same Hermes home and add a line:
   DEPLOY_API_KEY=<key>
    If the DEPLOY_API_KEY environment variable is already set in my environment, use that value without asking; otherwise STOP and ask for my Deploy Secret Key, guiding me to get it first: log in at deploy.com, open Service API Keys in the left nav, use an existing Secret Key if I saved one, or click Create API Key to generate one and copy the Secret Key (it is shown only once, at generation time; the page lists Access Key IDs later, never Secret Keys), then paste it to you when you ask; never invent a value, never echo it back, never commit it to git.
4. If I am a Virginia (VA1) customer, use base_url https://api-va1.deploy.com/api/v1 for the provider instead. Otherwise keep https://api-cdn.deploy.com/api/v1.
5. The model ID is configured by hand in the block above; select it explicitly as custom:deepseek-ai/deepseek-v4.1-flash, with the model name passed as shown.
6. Verify: tell me to run `hermes doctor` (fix anything it reports related to the model config), start a new session with `hermes`, run `/model` and pick custom:deepseek-ai/deepseek-v4.1-flash, then send a test message.

model:
  provider: custom
  default: deepseek-ai/deepseek-v4.1-flash
  base_url: https://api-cdn.thehive.ai/api/v3
  api_key: ${HIVE_API_KEY}

HIVE_API_KEY={YOUR_API_KEY}

Add Deploy (https://deploy.com) as a model provider in my Kilo Code setup. Follow these steps exactly:

1. Detect my OS and find my Kilo config:
   - Global (recommended, trusted): macOS/Linux ~/.config/kilo/kilo.jsonc or kilo.json; Windows %USERPROFILE%\.config\kilo\kilo.jsonc
   - Workspace: kilo.json (or kilo.jsonc) in the current repo
   Prefer the global config for credentials. If the file does not exist, create it; if it exists, MERGE, keeping everything I already have. If both exist, put the provider in global and the model default wherever my existing config lives.
2. Merge in exactly (replace {DEPLOY_API_KEY} below; if the DEPLOY_API_KEY environment variable is already set in my environment, use it without asking; otherwise STOP and ask for my Deploy Secret Key, helping me get it first: log in at deploy.com, open Service API Keys in the left nav, use an existing Secret Key if I saved one, or click Create API Key to generate one and copy the Secret Key (it is shown only once, at generation time; the page lists Access Key IDs later, never Secret Keys), then paste it to you only when you ask, first; never invent a value, never echo it back, never commit it to git):
   {
     "$schema": "https://app.kilo.ai/config.json",
     "model": "deploy/deepseek-ai/deepseek-v4.1-flash",
     "provider": {
       "deploy": {
         "name": "Deploy",
         "npm": "@ai-sdk/openai-compatible",
         "options": {
           "baseURL": "https://api-cdn.deploy.com/api/v1",
           "apiKey": "{DEPLOY_API_KEY}"
         },
         "models": {
           "deepseek-ai/deepseek-v4.1-flash": {
             "name": "Deepseek 4.1 Flash",
             "reasoning": true,
             "tool_call": true,
             "limit": { "context": 1000000, "output": 32768 },
             "modalities": {
               "input": ["text", "image"],
               "output": ["text"]
             }
           }
         }
       }
     }
   }
   Note that {env:VAR} references only resolve in the trusted global config, so in global config you may use "apiKey": "{env:DEPLOY_API_KEY}" if I prefer, with DEPLOY_API_KEY set in my shell.
3. Keep the limit block exactly as shown: without limit.context, Kilo disables conversation compaction, and without limit.output the output cap falls back to Kilo's default.
4. If I am a Virginia (VA1) customer, use baseURL https://api-va1.deploy.com/api/v1 for the provider instead. Otherwise keep https://api-cdn.deploy.com/api/v1.
5. Verify: tell me to reload the VS Code window (or restart the Kilo CLI), open Kilo, pick Deploy / Deepseek 4.1 Flash in the model picker, and run a task that edits a file (e.g. "create hello.txt containing hi") to confirm tool calling works over Deploy.

{
  "$schema": "https://app.kilo.ai/config.json",
  "model": "deploy/deepseek-ai/deepseek-v4.1-flash",
  "provider": {
    "hive-ai": {
      "name": "Hive",
      "npm": "@ai-sdk/openai-compatible",
      "options": {
        "baseURL": "https://api-cdn.deploy.com/api/v1",
        "apiKey": "{YOUR_API_KEY}"
      },
      "models": {
        "deepseek-ai/deepseek-v4.1-flash": {
          "name": "Deepseek 4.1 Flash",
          "reasoning": true,
          "tool_call": true,
          "limit": { "context": 1000000, "output": 32768 },
          "modalities": {
            "input": ["text", "image"],
            "output": ["text"]
          }
        }
      }
    }
  }
}

Add Deploy (https://deploy.com) as a model provider to my OpenClaw gateway. Follow these steps exactly:

1. Detect my OS and open the right config file:
   - macOS/Linux/WSL2: ~/.openclaw/openclaw.json
   - Native Windows: %USERPROFILE%\.openclaw\openclaw.json
   The file is JSON5 (comments allowed). If it does not exist, create it with the block below; if it exists, MERGE the block into it, keeping every existing key, channel config, and setting I already have.
2. Merge in exactly:
   {
     agents: {
       defaults: {
         model: { primary: "deploy/deepseek-ai/deepseek-v4.1-flash" },
       },
     },
     models: {
       mode: "merge",
       providers: {
         deploy: {
           baseUrl: "https://api-cdn.deploy.com/api/v1",
           apiKey: "${DEPLOY_API_KEY}",
           api: "openai-completions",
           models: [
             {
               id: "deepseek-ai/deepseek-v4.1-flash",
               name: "Deepseek 4.1 Flash",
               reasoning: true,
               input: ["text", "image"],
               contextWindow: 1000000,
               maxTokens: 32768,
             },
           ],
         },
       },
     },
     env: {
       vars: {
         DEPLOY_API_KEY: "{DEPLOY_API_KEY}",
       },
     },
   }
   If I already define env.vars, add DEPLOY_API_KEY inside the existing block instead of duplicating it.
3. If the HIVE_API_KEY environment variable is already set in my environment, use that value without asking; otherwise STOP and ask for my key, and guide me to get one first: log in at thehive.ai, open Service API Keys in the left nav, use an existing Secret Key if I saved one, or click Create API Key to generate one and copy the Secret Key (it is shown only once, at generation time; the page lists Access Key IDs later, never Secret Keys), then paste it to you when you ask, then substitute it for {YOUR_API_KEY}; never invent a key, never echo it back, never commit it to git. Alternatively offer me the choice of keeping the key in my shell environment instead of env.vars, and do whichever I pick.
4. If I am a Virginia (VA1) customer, use baseUrl https://api-va1.thehive.ai/api/v3 for the provider instead. Otherwise keep https://api-cdn.thehive.ai/api/v3.
5. Verify: run `openclaw gateway restart` (or tell me to restart the Gateway service on my OS), then run `openclaw models list` and confirm hive/deepseek-ai/deepseek-v4.1-flash appears and is primary. Then have me send a short test message through the dashboard (`openclaw dashboard`) or any connected channel.

{
  agents: {
    defaults: {
      model: { primary: 'deploy/deepseek-ai/deepseek-v4.1-flash' },
    },
  },
  models: {
    mode: 'merge',
    providers: {
      hive: {
        baseUrl: 'https://api-cdn.deploy.com/api/v1',
        apiKey: '${DEPLOY_API_KEY}',
        api: 'openai-completions',
        models: [
          {
            id: 'deepseek-ai/deepseek-v4.1-flash',
            name: 'Deepseek 4.1 Flash',
            reasoning: true,
            input: ['text', 'image'],
            contextWindow: 1000000,
            maxTokens: 32768,
          },
        ],
      },
    },
  },
  env: {
    vars: {
      DEPLOY_API_KEY: '{DEPLOY_API_KEY}',
    },
  },
}

Add Deploy (https://deploy.com) as a custom model provider in my DeepSeek Harness (dsh) settings. Follow these steps exactly:

1. Locate $DSH_HOME/settings.yaml (the .dsh settings directory for my dsh workspace; ask me which workspace I run dsh from if it is ambiguous). If the file or llm-pi-ai section does not exist, create it; MERGE, keeping every key I already have.
2. Merge in exactly:
   agent-default-model:
     provider: deploy
     model: deepseek-ai/deepseek-v4.1-flash
   llm-pi-ai:
     defaultModel:
       provider: deploy
       model: deepseek-ai/deepseek-v4.1-flash
     providers:
       deploy:
         apiKeyEnv: DEPLOY_API_KEY
         api: openai-completions
         baseURL: https://api-cdn.deploy.com/api/v1
         compat:
           supportsDeveloperRole: false
           maxTokensField: max_tokens
         models:
           - id: deepseek-ai/deepseek-v4.1-flash
             name: Deepseek 4.1 Flash
             input: [text, image]
   (The agent-default-model block routes fresh agents to Deploy.)
3. Detect my OS and set the environment variable DEPLOY_API_KEY so the dsh server process can see it:
   - macOS/Linux: append `export DEPLOY_API_KEY=...` to my shell profile.
   - Windows: set it as a User environment variable via PowerShell and tell me to restart my terminal and the dsh server.
    If the DEPLOY_API_KEY environment variable is already set in my environment, use that value without asking; otherwise STOP and ask for my key, and guide me to get one first: log in at deploy.com, open Service API Keys in the left nav, use an existing Secret Key if I saved one, or click Create API Key to generate one and copy the Secret Key (it is shown only once, at generation time; the page lists Access Key IDs later, never Secret Keys), then paste it to you when you ask; never invent a value, never echo it, never commit it to git.
4. If I am a Virginia (VA1) customer, use baseURL https://api-va1.deploy.com/api/v1 instead. Otherwise keep https://api-cdn.deploy.com/api/v1.
5. Keep the compat switches exactly as shown. Do NOT add, invent, or stub any other provider (not even placeholder deepseek-official entries).
6. Verify: tell me to reload the dsh Web UI, open Settings, Models (the Deploy provider should show Deepseek 4.1 Flash), select deploy / Deepseek 4.1 Flash in the model picker, and send the test task "Reply with the single word: connected". If I see MISSING_CREDENTIAL, the DEPLOY_API_KEY env var is not visible to the dsh process; re-check step 3.

agent-default-model: # routes fresh agents (incl. dsh --profile headless) to Deploy
  provider: deploy
  model: deepseek-ai/deepseek-v4.1-flash
llm-pi-ai:
  defaultModel: # web-UI model picker falls back here
    provider: deploy
    model: deepseek-ai/deepseek-v4.1-flash
  providers:
    deploy:
      apiKeyEnv: DEPLOY_API_KEY
      api: openai-completions
      baseURL: https://api-cdn.deploy.com/api/v1
      compat:
        supportsDeveloperRole: false
        maxTokensField: max_tokens
      models:
        - id: deepseek-ai/deepseek-v4.1-flash
          name: Deepseek 4.1 Flash
          input: [text, image]

Set up Claude Code to use Deploy (https://deploy.com) through a local LiteLLM proxy. Claude Code speaks the Anthropic Messages API and Deploy serves an OpenAI-compatible API, so the proxy translates between them. Follow these steps exactly:

1. Detect my OS (Windows, macOS, or Linux) and adapt all paths and shell commands accordingly.
2. Check Python: LiteLLM needs Python 3.10+ (run `python --version` or `python3 --version`; if too old, tell me how to install a newer Python for my OS before continuing).
3. Create a LiteLLM config file:
   - macOS/Linux: ~/.litellm/litellm-deploy.yaml
   - Windows: %USERPROFILE%\.litellm\litellm-deploy.yaml
   Write exactly:
    model_list:
      - model_name: deploy-deepseek-v4.1-flash
        litellm_params:
          model: custom_openai/deepseek-ai/deepseek-v4.1-flash
          api_base: https://api-cdn.deploy.com/api/v1
          api_key: os.environ/DEPLOY_API_KEY
    litellm_settings:
      drop_params: true
    (Keep drop_params: true; Claude Code sends some request fields this provider does not use, and drop_params keeps the translation smooth.)
4. Install and start the proxy:
   - Install: pip install 'litellm[proxy]' (or: uv tool install 'litellm[proxy]')
   - If the DEPLOY_API_KEY environment variable is already set in my environment, use it without asking; otherwise STOP and ask for my Deploy Secret Key, guiding me to get it first: log in at deploy.com, open Service API Keys in the left nav, use an existing Secret Key if I saved one, or click Create API Key to generate one and copy the Secret Key (it is shown only once, at generation time; the page lists Access Key IDs later, never Secret Keys), then paste it to you when you ask. Set it as the environment variable DEPLOY_API_KEY for the proxy process (macOS/Linux: export DEPLOY_API_KEY=...; Windows PowerShell: $env:DEPLOY_API_KEY="..."). Never invent a key, never echo it, never commit it to git.
   - Start: litellm --config <path from step 3> --port 4000
   - Verify the proxy is listening on http://127.0.0.1:4000.
5. If I am a Virginia (VA1) customer, use api_base https://api-va1.deploy.com/api/v1 in the config instead. Otherwise keep https://api-cdn.deploy.com/api/v1.
6. Point Claude Code at the proxy by MERGING this into my Claude Code settings file (macOS/Linux: ~/.claude/settings.json; Windows: %USERPROFILE%\.claude\settings.json) under "env", keeping all my existing settings:
   {
     "env": {
       "ANTHROPIC_BASE_URL": "http://127.0.0.1:4000",
       "ANTHROPIC_AUTH_TOKEN": "sk-litellm-local",
       "ANTHROPIC_MODEL": "deploy-deepseek-v4.1-flash"
     }
   }
7. The proxy must be running whenever I use Claude Code with Deploy: give me the exact start command for my OS and offer to show how to run it in the background (e.g. nohup or a systemd user unit on Linux, a background shell or launchd on macOS, or a separate terminal on Windows).
8. Verify end-to-end: make a test request through the proxy (e.g. curl http://127.0.0.1:4000/v1/messages with headers x-api-key: sk-litellm-local and anthropic-version: 2023-06-01, body {"model":"deploy-deepseek-v4.1-flash","max_tokens":64,"messages":[{"role":"user","content":"Say connected"}]}), confirm the reply, then tell me to launch or restart `claude` and send a short test message.

model_list:
  - model_name: deploy-deepseek-v4.1-flash
    litellm_params:
      model: custom_openai/deepseek-ai/deepseek-v4.1-flash # custom_openai/ prefix + the Deploy model key
      api_base: https://api-cdn.deploy.com/api/v1
      api_key: os.environ/DEPLOY_API_KEY
litellm_settings:
  drop_params: true # keeps the translation smooth when Claude Code sends extra request fields

{
  "env": {
    "ANTHROPIC_BASE_URL": "http://127.0.0.1:4000",
    "ANTHROPIC_AUTH_TOKEN": "sk-litellm-local",
    "ANTHROPIC_MODEL": "deploy-deepseek-v4.1-flash"
  }
}

pip install 'litellm[proxy]'
export DEPLOY_API_KEY={DEPLOY_API_KEY}        # macOS/Linux
litellm --config ~/.litellm/litellm-deploy.yaml --port 4000

curl http://127.0.0.1:4000/v1/messages \
  -H "x-api-key: sk-litellm-local" -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{"model":"deploy-deepseek-v4.1-flash","max_tokens":64,"messages":[{"role":"user","content":"Say connected"}]}'

Add Deploy (https://deploy.com) as a provider to my Pi coding agent. Follow these steps exactly:

1. Detect my OS and open (or create) the right file:
   - macOS/Linux: ~/.pi/agent/models.json
   - Windows: %USERPROFILE%\.pi\agent\models.json
   It is a JSON file keyed by "providers". If it already exists, MERGE a "deploy" provider into the existing "providers" object, keeping every existing provider. The file hot-reloads when /model is opened, so no restart is needed after editing.
2. Merge in exactly:
   {
     "deploy": {
       "baseUrl": "https://api-cdn.deploy.com/api/v1",
       "api": "openai-completions",
       "apiKey": "$DEPLOY_API_KEY",
       "models": [
         {
           "id": "deepseek-ai/deepseek-v4.1-flash",
           "name": "Deepseek 4.1 Flash",
           "reasoning": true,
           "input": ["text", "image"],
           "contextWindow": 1000000,
           "maxTokens": 16384,
           "compat": {
             "supportsDeveloperRole": false,
             "supportsReasoningEffort": false,
             "maxTokensField": "max_tokens"
           }
         }
       ]
     }
   }
   Keep the compat flags exactly as shown; pi relies on them to shape requests to this provider.
3. Set DEPLOY_API_KEY in my environment so "$DEPLOY_API_KEY" resolves:
   - macOS/Linux: append `export DEPLOY_API_KEY=...` to ~/.zshrc or ~/.bashrc
   - Windows: set a User environment variable (PowerShell: [Environment]::SetEnvironmentVariable('DEPLOY_API_KEY','<key>','User')) and restart the terminal
    If the DEPLOY_API_KEY environment variable is already set in my environment, use that value without asking; otherwise STOP and ask for my key, and guide me to get one first: log in at deploy.com, open Service API Keys in the left nav, use an existing Secret Key if I saved one, or click Create API Key to generate one and copy the Secret Key (it is shown only once, at generation time; the page lists Access Key IDs later, never Secret Keys), then paste it to you when you ask; never invent a value, never echo it, never commit it to git. Offer to put the literal key in models.json instead if I prefer.
4. If I am a Virginia (VA1) customer, use baseUrl https://api-va1.deploy.com/api/v1 for the provider instead. Otherwise keep https://api-cdn.deploy.com/api/v1.
5. Verify: tell me to run `pi` in a project directory, open /model, pick deploy / deepseek-ai/deepseek-v4.1-flash, and send a short prompt. If a 400 error mentions the developer role or reasoning_effort, confirm the compat block is present and reload /model (the file hot-reloads).

{
  "providers": {
    "deploy": {
      "baseUrl": "https://api-cdn.deploy.com/api/v1",
      "api": "openai-completions",
      "apiKey": "$DEPLOY_API_KEY",
      "models": [
        {
          "id": "deepseek-ai/deepseek-v4.1-flash",
          "name": "Deepseek 4.1 Flash",
          "reasoning": true,
          "input": ["text", "image"],
          "contextWindow": 1000000,
          "maxTokens": 16384,
          "cost": { "input": 0, "output": 0, "cacheRead": 0, "cacheWrite": 0 },
          "compat": {
            "supportsDeveloperRole": false,
            "supportsReasoningEffort": false,
            "maxTokensField": "max_tokens"
          }
        }
      ]
    }
  }
}