GaiaNet API

openapi: 3.1.0
info:
  title: GaiaNet API
  version: '2026-10-20'
  description: 'GENERATED FROM DOCUMENTATION by API Evangelist on 2026-10-20: 18 operation(s) read from 27 public documentation page(s) (each
    operation names its page in x-source). This is not the provider''s published contract; GaiaNet has published no machine-readable contract
    that the pipeline could find. Engine: local.'
  x-evidence-tiers:
    code-example: 16
    documentation: 2
    pages-with-code: 19
    pages-read: 27
  x-generated-from: documentation
  x-provenance: generated
  x-authored-by: API Evangelist
  x-generated: '2026-10-20'
  x-generator: generate-contract-from-docs.py
  x-engine: local
  x-sources:
  - https://docs.gaianet.ai/getting-started/api-reference
  - https://docs.gaianet.ai/1.0.0/user-guide/api-reference
  - https://docs.gaianet.ai/2.0.0/getting-started/api-reference
  - https://docs.gaianet.ai/templates-and-examples/templates/developer-docs-ai-agent
  - https://docs.gaianet.ai/2.0.0/templates-and-examples/templates/developer-docs-ai-agent
  - https://docs.gaianet.ai/tutorial/coinbase
  - https://docs.gaianet.ai/tutorial/llamacpp
  - https://docs.gaianet.ai/tutorial/tool-call
  - https://docs.gaianet.ai/1.0.0/tutorial/coinbase
  - https://docs.gaianet.ai/2.0.0/tutorial/coinbase
  - https://docs.gaianet.ai/2.0.0/tutorial/llamacpp
  - https://docs.gaianet.ai/getting-started/install
  - https://docs.gaianet.ai/1.0.0/tutorial/tool-call
  - https://docs.gaianet.ai/2.0.0/tutorial/tool-call
  - https://docs.gaianet.ai/tutorial/deepseek-cursor
  - https://docs.gaianet.ai/tutorial/translator-agent
  - https://docs.gaianet.ai/getting-started/quick-start
  - https://docs.gaianet.ai/1.0.0/node-guide/quick-start
  - https://docs.gaianet.ai/2.0.0/getting-started/install
  - https://docs.gaianet.ai/2.0.0/tutorial/deepseek-cursor
  - https://docs.gaianet.ai/1.0.0/tutorial/translator-agent
  - https://docs.gaianet.ai/2.0.0/tutorial/translator-agent
  - https://docs.gaianet.ai/getting-started/troubleshooting
  - https://docs.gaianet.ai/2.0.0/getting-started/quick-start
  - https://docs.gaianet.ai/2.0.0/getting-started/troubleshooting
  - https://docs.gaianet.ai/templates-and-examples/templates/stockbot
  - https://docs.gaianet.ai/templates-and-examples/templates/llamacoder
paths:
  /GaiaNet-AI/embedding-tools/raw/main/csv_embed/csv_embed.wasm:
    get:
      operationId: get_GaiaNet_AI_embedding_tools_raw_main_csv_embed_csv_embed_wasm
      tags:
      - Gaianet Ai
      summary: GET /GaiaNet-AI/embedding-tools/raw/main/csv_embed/csv_embed.wasm
      x-source: https://docs.gaianet.ai/templates-and-examples/templates/developer-docs-ai-agent
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -LO https://github.com/GaiaNet-AI/embedding-tools/raw/main/csv_embed/csv_embed.wasm \n Preparing the Documentation ​ \n\
          \ Why CSV instead of Markdown?   It's quite easier to use CSV than markdown and it’s better to paste your each chunk into different\
          \ columns and one cell per column. Fell free to use llm_info.txt file, if that’s what you prefer. \n You can use gitingest to turn the\
          \ vyper docs git "
  /GaiaNet-AI/gaianet-node/releases/download/0.1.3/install.sh:
    get:
      operationId: get_GaiaNet_AI_gaianet_node_releases_download_0_1_3_install_sh
      tags:
      - Gaianet Ai
      summary: GET /GaiaNet-AI/gaianet-node/releases/download/0.1.3/install.sh
      x-source: https://docs.gaianet.ai/getting-started/install
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -sSfL 'https://github.com/GaiaNet-AI/gaianet-node/releases/download/0.1.3/install.sh' | bash \n Check out the release log\
          \ here . \n Update the current Gaia node ​ \n Simply run the following command to upgrade your node. "
  /GaiaNet-AI/gaianet-node/releases/latest/download/install.sh:
    get:
      operationId: get_GaiaNet_AI_gaianet_node_releases_latest_download_install_sh
      tags:
      - Gaianet Ai
      summary: GET /GaiaNet-AI/gaianet-node/releases/latest/download/install.sh
      x-source: https://docs.gaianet.ai/getting-started/install
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -sSfL 'https://github.com/GaiaNet-AI/gaianet-node/releases/latest/download/install.sh' | bash \n The Gaia node will be\
          \ installed in your $HOME/gaianet folder by default. \n If you want to install gaianet in a different directory, you can use curl -sSfL\
          \ 'https://github.com/GaiaNet-AI/gaianet-node/releases/latest/download/install.sh' | bash -s -- --base <Full_Path> to specify where\
          \ you want to in"
  /GaiaNet-AI/gaianet-node/releases/latest/download/uninstall.sh:
    get:
      operationId: get_GaiaNet_AI_gaianet_node_releases_latest_download_uninstall_sh
      tags:
      - Gaianet Ai
      summary: GET /GaiaNet-AI/gaianet-node/releases/latest/download/uninstall.sh
      x-source: https://docs.gaianet.ai/getting-started/install
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -sSfL 'https://github.com/GaiaNet-AI/gaianet-node/releases/latest/download/uninstall.sh' | bash \n danger Important Reminder:\
          \ This command will remove all the Gaia-related files, including the nodeid.json . It's your responsibility to keep your nodeid.json\
          \ safe. If you want to run the same node after reinstalling, please save the nodeid.json file and frpc.toml file carefully. Edit this\
          \ page Pr"
  /WasmEdge/WasmEdge/master/utils/install_v2.sh:
    get:
      operationId: get_WasmEdge_WasmEdge_master_utils_install_v2_sh
      tags:
      - Wasmedge
      summary: GET /WasmEdge/WasmEdge/master/utils/install_v2.sh
      x-source: https://docs.gaianet.ai/templates-and-examples/templates/developer-docs-ai-agent
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/install_v2.sh | bash -s \n Why Wasm? Because you\
          \ get a build artifact (a single .wasm file) that never needs pip install. Security teams love the deterministic binary; DevOps loves\
          \ the zero-dependency story. \n Embedding Model Weights – The model that produces your 768-dimensional sentence vectors lives on Hugging\
          \ Face: "
  /collections/default:
    get:
      operationId: get_collections_default
      tags:
      - Collections
      summary: GET /collections/default
      x-source: https://docs.gaianet.ai/templates-and-examples/templates/developer-docs-ai-agent
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl - X DELETE 'http://localhost:6333/collections/default' \n And then run the following. "
    put:
      operationId: put_collections_default
      tags:
      - Collections
      summary: PUT /collections/default
      x-source: https://docs.gaianet.ai/templates-and-examples/templates/developer-docs-ai-agent
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/PutCollectionsDefaultRequest'
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -X PUT 'http://localhost:6333/collections/default' \\ -H 'Content-Type: application/json' \\ --data-raw '{ \"vectors\"\
          : { \"size\": 768, \"distance\": \"Cosine\", \"on_disk\": true } }' \n The on_disk flag is your friend when the corpus grows into the\
          \ hundreds of thousands of chunks; Qdrant memory-maps the vectors and leaves RAM for your LLM. \n Producing the Embeddings ​ \n Lets\
          \ Grab the Embedding CLI "
  /collections/default/snapshots:
    get:
      operationId: get_collections_default_snapshots
      tags:
      - Collections
      summary: List snapshots of the default collection
      x-source: https://docs.gaianet.ai/templates-and-examples/templates/developer-docs-ai-agent
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
    post:
      operationId: post_collections_default_snapshots
      tags:
      - Collections
      summary: POST /collections/default/snapshots
      x-source: https://docs.gaianet.ai/templates-and-examples/templates/developer-docs-ai-agent
      responses:
        '201':
          description: Success (status as documented)
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -X POST 'http://localhost:6333/collections/default/snapshots' \n Now it’s time to compress the snapshots, let’s head over\
          \ to qdrant_snapshots/default and then compress it by running. \n tar czvf my . snapshot . tar . gz my . snapshot \n Instead of my.snapshot\
          \ just use the file name. Upload my.snapshot.tar.gz to huggingface, you’ll need to have an account there. Now click on new dataset and\
          \ uploa"
  /gaianet/Llama-2-13B-Chat-GGUF/resolve/main/llama-2-13b-chat.Q5_K_M.gguf:
    get:
      operationId: get_gaianet_Llama_2_13B_Chat_GGUF_resolve_main_llama_2_13b_chat_Q5_K_M_gguf
      tags:
      - Gaianet
      summary: GET /gaianet/Llama-2-13B-Chat-GGUF/resolve/main/llama-2-13b-chat.Q5_K_M.gguf
      x-source: https://docs.gaianet.ai/tutorial/llamacpp
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -LO https://huggingface.co/gaianet/Llama-2-13B-Chat-GGUF/resolve/main/llama-2-13b-chat.Q5_K_M.gguf \n Create a question\
          \ and answer set for fine-tuning ​ \n Next we came up with 1700+ pairs of QAs for the chemistry subject. It is like the following in\
          \ a CSV file . \n Question Answer What is unique about hydrogen? It's the most abundant element in the universe, making up over 75%\
          \ of all matter. Wh"
  /gaianet/Nomic-embed-text-v1.5-Embedding-GGUF/resolve/main/nomic-embed-text-v1.5.f16.gguf:
    get:
      operationId: get_gaianet_Nomic_embed_text_v1_5_Embedding_GGUF_resolve_main_nomic_embed_text_v
      tags:
      - Gaianet
      summary: GET /gaianet/Nomic-embed-text-v1.5-Embedding-GGUF/resolve/main/nomic-embed-text-v1.5.f16.gguf
      x-source: https://docs.gaianet.ai/templates-and-examples/templates/developer-docs-ai-agent
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -LO https://huggingface.co/gaianet/Nomic-embed-text-v1.5-Embedding-GGUF/resolve/main/nomic-embed-text-v1.5.f16.gguf \n\
          \ These weights are in the GGUF format, the modern successor to GGML, which streams efficiently from disk and supports quantized variants\
          \ for CPU-only boxes. \n Let’s create two folders as qdrant_storage and qdrant_snapshots . We’ll find our snapshotted knowledge base\
          \ inside qdra"
  /juntaoyuan/chemistry-assistant-13b/resolve/main/chemistry-assistant-13b-q5_k_m.gguf:
    get:
      operationId: get_juntaoyuan_chemistry_assistant_13b_resolve_main_chemistry_assistant_13b_q5_k
      tags:
      - Juntaoyuan
      summary: GET /juntaoyuan/chemistry-assistant-13b/resolve/main/chemistry-assistant-13b-q5_k_m.gguf
      x-source: https://docs.gaianet.ai/tutorial/llamacpp
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -LO https://huggingface.co/juntaoyuan/chemistry-assistant-13b/resolve/main/chemistry-assistant-13b-q5_k_m.gguf \n Note\
          \ 3 If you want to use a checkpoint to generate a lora.bin file, use the following command. This is needed when you believe the final\
          \ lora.bin is an overfit. \n ../build/bin/finetune --model-base llama-2-13b-chat.Q5_K_M.gguf --checkpoint-in checkpoint-250.gguf --only-write-lora\
          \ -"
  /v1:
    get:
      operationId: get_v1
      tags:
      - Api
      summary: Working with Coinbase AgentKit
      description: The page lists the API endpoint URL https://llama8b.gaia.domains/v1 for the Gaia node used with Coinbase AgentKit.
      x-source: https://docs.gaianet.ai/1.0.0/tutorial/coinbase
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /v1/chat/completions:
    post:
      operationId: post_v1_chat_completions
      tags:
      - Chat
      summary: POST /v1/chat/completions
      x-source: https://docs.gaianet.ai/getting-started/api-reference
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/PostV1ChatCompletionsRequest'
      responses:
        '201':
          description: Success (shape read from the example response on the page)
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PostV1ChatCompletionsResponse'
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -X POST https://node_id.gaia.domains/v1/chat/completions \\ -H 'accept:application/json' \\ -H 'Content-Type: application/json'\
          \ \\ -H 'Authorization: Bearer YOUR_API_KEY_GOES_HERE' \\ -d '{\"messages\":[{\"role\":\"system\", \"content\": \"You are a helpful\
          \ assistant.\"}, {\"role\":\"user\", \"content\": \"What is the capital of France?\"}], \"model\": \"model_name\"}' \n Response: \n\
          \ {\"id\":\"chatcmpl-bcfeebe0-5372-42c0-"
  /v1/embeddings:
    post:
      operationId: post_v1_embeddings
      tags:
      - Embeddings
      summary: POST /v1/embeddings
      x-source: https://docs.gaianet.ai/getting-started/api-reference
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/PostV1EmbeddingsRequest'
      responses:
        '201':
          description: Success (shape read from the example response on the page)
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PostV1EmbeddingsResponse'
      x-evidence:
        kind: code-example
        language: curl
        snippet: 'curl -X POST https://node_id.gaia.domains/v1/embeddings \ -H ''accept:application/json'' \ -H ''Content-Type: application/json''
          \ -H ''Authorization: Bearer YOUR_API_KEY_GOES_HERE'' \ -d ''{"model": "nomic-embed-text-v1.5.f16", "input":["Paris, city and capital
          of France, ..., for Paris has retained its importance as a centre for education and intellectual pursuits.", "Paris’s site at a crossroads
          ..., '
  /v1/info:
    post:
      operationId: post_v1_info
      tags:
      - Info
      summary: POST /v1/info
      x-source: https://docs.gaianet.ai/getting-started/api-reference
      responses:
        '201':
          description: Success (shape read from the example response on the page)
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PostV1InfoResponse'
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -X POST https://node_id.gaia.domains/v1/info \n Response: \n { \"version\": \"0.5.0\", \"plugin_version\": \"b2694 (commit\
          \ 0d56246f)\", \"port\": \"8080\", \"models\": [ { \"name\": \"Llama-2-7b-chat-hf-Q5_K_M\", \"type\": \"chat\", \"prompt_template\"\
          : \"Llama2Chat\", \"n_predict\": 1024, \"n_gpu_layers\": 100, \"ctx_size\": 4096, \"batch_size\": 512, \"temperature\": 1.0, \"top_p\"\
          : 1.0, \"repeat_penalty\": 1.1, \"presence_penalty\":"
  /v1/models:
    post:
      operationId: post_v1_models
      tags:
      - Models
      summary: POST /v1/models
      x-source: https://docs.gaianet.ai/getting-started/api-reference
      responses:
        '201':
          description: Success (shape read from the example response on the page)
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PostV1ModelsResponse'
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -X POST https://node_id.gaia.domains/v1/models \n Response: \n {\"object\":\"list\",\"data\":[{\"id\":\"Llama-3-8B-Instruct-262k-Q5_K_M\"\
          ,\"created\":1716383261,\"object\":\"model\",\"owned_by\":\"Not specified\"},{\"id\":\"nomic-embed-text-v1.5.f16\",\"created\":1716383261,\"\
          object\":\"model\",\"owned_by\":\"Not specified\"}]}% \n Get the node info ​ \n The info endpoint provides detailed information about\
          \ the node. \n Request: "
  /v1/retrieve:
    post:
      operationId: post_v1_retrieve
      tags:
      - Retrieve
      summary: POST /v1/retrieve
      x-source: https://docs.gaianet.ai/getting-started/api-reference
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/PostV1RetrieveRequest'
      responses:
        '201':
          description: Success (shape read from the example response on the page)
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PostV1RetrieveResponse'
      x-evidence:
        kind: code-example
        language: curl
        snippet: "curl -X POST https://node_id.gaia.domains/v1/retrieve \\ -H 'accept:application/json' \\ -H 'Content-Type: application/json'\
          \ \\ -H 'Authorization: Bearer YOUR_API_KEY_GOES_HERE' \\ -d '{\"messages\":[{\"role\":\"system\", \"content\": \"You are a helpful\
          \ assistant.\"}, {\"role\":\"user\", \"content\": \"What is the location of Paris?\"}], \"model\":\"nomic-embed-text-v1.5.f16\"}' \n\
          \ Response: \n { \"points\": [ { \"source\": \"\\\""
components:
  schemas:
    PutCollectionsDefaultRequest:
      type: object
      properties:
        vectors:
          type: object
          properties:
            size:
              type: integer
            distance:
              type: string
            on_disk:
              type: boolean
    PostV1ChatCompletionsRequest:
      type: object
      properties:
        messages:
          type: array
          items:
            type: object
            properties:
              role:
                type: string
              content:
                type: string
        model:
          type: string
    PostV1ChatCompletionsResponse:
      type: object
      properties:
        id:
          type: string
        object:
          type: string
        created:
          type: integer
        model:
          type: string
        choices:
          type: array
          items:
            type: object
            properties:
              index:
                type: integer
              message:
                type: object
                properties:
                  role:
                    type: string
                  content:
                    type: string
              finish_reason:
                type: string
        usage:
          type: object
          properties:
            prompt_tokens:
              type: integer
            completion_tokens:
              type: integer
            total_tokens:
              type: integer
    PostV1EmbeddingsRequest:
      type: object
      properties:
        model:
          type: string
        input:
          type: array
          items:
            type: string
    PostV1EmbeddingsResponse:
      type: object
      properties:
        object:
          type: string
        data:
          type: array
          items:
            type: object
            properties:
              index:
                type: integer
              object:
                type: string
              embedding:
                type: array
                items:
                  type: number
        model:
          type: string
        usage:
          type: object
          properties:
            prompt_tokens:
              type: integer
            completion_tokens:
              type: integer
            total_tokens:
              type: integer
    PostV1InfoResponse:
      type: object
      properties:
        version:
          type: string
        plugin_version:
          type: string
        port:
          type: string
        models:
          type: array
          items:
            type: object
            properties:
              name:
                type: string
              type:
                type: string
              prompt_template:
                type: string
              n_predict:
                type: integer
              n_gpu_layers:
                type: integer
              ctx_size:
                type: integer
              batch_size:
                type: integer
              temperature:
                type: number
              top_p:
                type: number
              repeat_penalty:
                type: number
              presence_penalty:
                type: number
              frequency_penalty:
                type: number
        qdrant_config:
          type: object
          properties:
            url:
              type: string
            collection_name:
              type: string
            limit:
              type: integer
            score_threshold:
              type: number
    PostV1ModelsResponse:
      type: object
      properties:
        object:
          type: string
        data:
          type: array
          items:
            type: object
            properties:
              id:
                type: string
              created:
                type: integer
              object:
                type: string
              owned_by:
                type: string
    PostV1RetrieveRequest:
      type: object
      properties:
        messages:
          type: array
          items:
            type: object
            properties:
              role:
                type: string
              content:
                type: string
        model:
          type: string
    PostV1RetrieveResponse:
      type: object
      properties:
        points:
          type: array
          items:
            type: object
            properties:
              source:
                type: string
              score:
                type: number
        limit:
          type: integer
        score_threshold:
          type: number
  securitySchemes:
    bearer:
      type: http
      scheme: bearer
security:
- bearer: []
tags:
- name: Api
- name: Chat
- name: Collections
- name: Embeddings
- name: Gaianet
- name: Gaianet Ai
- name: Info
- name: Juntaoyuan
- name: Models
- name: Retrieve
- name: Wasmedge