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Merge remote-tracking branch 'upstream/develop' into twitter-cookies
2 parents 3622a7d + e201228 commit dbbde8a

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‎.env.example

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@@ -34,6 +34,9 @@ LARGE_HYPERBOLIC_MODEL= # Default: meta-llama/Meta-Llama-3.1-405-Instruc
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# Speech Synthesis
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ELEVENLABS_XI_API_KEY= # API key from elevenlabs
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# Direct Client Setting
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EXPRESS_MAX_PAYLOAD= # Default: 100kb
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# ElevenLabs Settings
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ELEVENLABS_MODEL_ID=eleven_multilingual_v2
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ELEVENLABS_VOICE_ID=21m00Tcm4TlvDq8ikWAM
@@ -54,6 +57,7 @@ TWITTER_2FA_SECRET=
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TWITTER_POLL_INTERVAL=120 # How often (in seconds) the bot should check for interactions
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TWITTER_SEARCH_ENABLE=FALSE # Enable timeline search, WARNING this greatly increases your chance of getting banned
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TWITTER_TARGET_USERS= # Comma separated list of Twitter user names to interact with
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TWITTER_RETRY_LIMIT= # Maximum retry attempts for Twitter login
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X_SERVER_URL=
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XAI_API_KEY=
@@ -256,6 +260,9 @@ LARGE_AKASH_CHAT_API_MODEL= # Default: Meta-Llama-3-1-405B-Instruct-FP8
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FAL_API_KEY=
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FAL_AI_LORA_PATH=
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# Web search API Configuration
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TAVILY_API_KEY=
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# WhatsApp Cloud API Configuration
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WHATSAPP_ACCESS_TOKEN= # Permanent access token from Facebook Developer Console
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WHATSAPP_PHONE_NUMBER_ID= # Phone number ID from WhatsApp Business API

‎.github/workflows/image.yaml

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@@ -9,53 +9,62 @@ on:
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# Defines two custom environment variables for the workflow. These are used for the Container registry domain, and a name for the Docker image that this workflow builds.
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env:
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REGISTRY: ghcr.io
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IMAGE_NAME: ${{ github.repository }}
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REGISTRY: ghcr.io
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IMAGE_NAME: ${{ github.repository }}
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# There is a single job in this workflow. It's configured to run on the latest available version of Ubuntu.
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jobs:
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build-and-push-image:
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runs-on: ubuntu-latest
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# Sets the permissions granted to the `GITHUB_TOKEN` for the actions in this job.
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permissions:
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contents: read
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packages: write
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attestations: write
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id-token: write
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#
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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# Uses the `docker/login-action` action to log in to the Container registry registry using the account and password that will publish the packages. Once published, the packages are scoped to the account defined here.
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- name: Log in to the Container registry
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uses: docker/login-action@65b78e6e13532edd9afa3aa52ac7964289d1a9c1
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with:
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registry: ${{ env.REGISTRY }}
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username: ${{ github.actor }}
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password: ${{ secrets.GITHUB_TOKEN }}
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# This step uses [docker/metadata-action](https://github.com/docker/metadata-action#about) to extract tags and labels that will be applied to the specified image. The `id` "meta" allows the output of this step to be referenced in a subsequent step. The `images` value provides the base name for the tags and labels.
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- name: Extract metadata (tags, labels) for Docker
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id: meta
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uses: docker/metadata-action@9ec57ed1fcdbf14dcef7dfbe97b2010124a938b7
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with:
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images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
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# This step uses the `docker/build-push-action` action to build the image, based on your repository's `Dockerfile`. If the build succeeds, it pushes the image to GitHub Packages.
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# It uses the `context` parameter to define the build's context as the set of files located in the specified path. For more information, see "[Usage](https://github.com/docker/build-push-action#usage)" in the README of the `docker/build-push-action` repository.
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# It uses the `tags` and `labels` parameters to tag and label the image with the output from the "meta" step.
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- name: Build and push Docker image
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id: push
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uses: docker/build-push-action@f2a1d5e99d037542a71f64918e516c093c6f3fc4
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with:
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context: .
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push: true
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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# This step generates an artifact attestation for the image, which is an unforgeable statement about where and how it was built. It increases supply chain security for people who consume the image. For more information, see "[AUTOTITLE](/actions/security-guides/using-artifact-attestations-to-establish-provenance-for-builds)."
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- name: Generate artifact attestation
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uses: actions/attest-build-provenance@v1
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with:
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subject-name: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME}}
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subject-digest: ${{ steps.push.outputs.digest }}
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push-to-registry: true
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build-and-push-image:
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runs-on: ubuntu-latest
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# Sets the permissions granted to the `GITHUB_TOKEN` for the actions in this job.
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permissions:
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contents: read
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packages: write
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attestations: write
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id-token: write
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#
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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# Uses the `docker/login-action` action to log in to the Container registry registry using the account and password that will publish the packages. Once published, the packages are scoped to the account defined here.
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- name: Log in to the Container registry
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uses: docker/login-action@65b78e6e13532edd9afa3aa52ac7964289d1a9c1
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with:
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registry: ${{ env.REGISTRY }}
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username: ${{ github.actor }}
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password: ${{ secrets.GITHUB_TOKEN }}
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# This step uses [docker/metadata-action](https://github.com/docker/metadata-action#about) to extract tags and labels that will be applied to the specified image. The `id` "meta" allows the output of this step to be referenced in a subsequent step. The `images` value provides the base name for the tags and labels.
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- name: Extract metadata (tags, labels) for Docker
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id: meta
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uses: docker/metadata-action@9ec57ed1fcdbf14dcef7dfbe97b2010124a938b7
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with:
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images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
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# This step uses the `docker/build-push-action` action to build the image, based on your repository's `Dockerfile`. If the build succeeds, it pushes the image to GitHub Packages.
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# It uses the `context` parameter to define the build's context as the set of files located in the specified path. For more information, see "[Usage](https://github.com/docker/build-push-action#usage)" in the README of the `docker/build-push-action` repository.
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# It uses the `tags` and `labels` parameters to tag and label the image with the output from the "meta" step.
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- name: Build and push Docker image
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id: push
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uses: docker/build-push-action@f2a1d5e99d037542a71f64918e516c093c6f3fc4
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with:
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context: .
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push: true
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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# This step generates an artifact attestation for the image, which is an unforgeable statement about where and how it was built. It increases supply chain security for people who consume the image. For more information, see "[AUTOTITLE](/actions/security-guides/using-artifact-attestations-to-establish-provenance-for-builds)."
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- name: Generate artifact attestation
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uses: actions/attest-build-provenance@v1
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with:
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subject-name: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME}}
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subject-digest: ${{ steps.push.outputs.digest }}
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push-to-registry: true
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# This step makes the Docker image public, so users can pull it without authentication.
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- name: Make Docker image public
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run: |
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curl \
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-X PATCH \
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-H "Authorization: Bearer ${{ secrets.GITHUB_TOKEN }}" \
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-H "Accept: application/vnd.github.v3+json" \
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https://api.github.com/user/packages/container/${{ env.IMAGE_NAME }}/visibility \
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-d '{"visibility":"public"}'

‎.github/workflows/integrationTests.yaml

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@@ -3,7 +3,7 @@ on:
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push:
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branches:
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- "*"
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pull_request_target:
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pull_request:
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branches:
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- "*"
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jobs:

‎.gitignore

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@@ -52,3 +52,5 @@ tsup.config.bundled_*.mjs
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coverage
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.eslintcache
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agent/content

‎.gitpod.yml

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- name: "init eliza env"
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init: |
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nvm install v23.3.0
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git fetch --tags
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git checkout $(git describe --tags --abbrev=0)
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command: pnpm install && pnpm run build

‎Dockerfile

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@@ -52,4 +52,4 @@ COPY --from=builder /app/scripts ./scripts
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COPY --from=builder /app/characters ./characters
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# Set the command to run the application
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CMD ["pnpm", "start", "--non-interactive"]
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CMD ["pnpm", "start"]

‎README.md

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```bash
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git clone https://github.com/ai16z/eliza-starter.git
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cd eliza-starter
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cp .env.example .env
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pnpm i && pnpm build && pnpm start
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```
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‎README_CN.md

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# 开始使用
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**前置要求（必须）:**
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**前置要求(必须):**
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- [Python 2.7+](https://www.python.org/downloads/)
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- [Node.js 23+](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm)
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- Nodejs安装
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- [pnpm](https://pnpm.io/installation)
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- 使用pnpm
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### 编辑.env文件
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以下是两种基础的Eliza下载方案, 请根据情况自行选择。
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- - 将 .env.example 复制为 .env 并填写适当的值
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## (A) 使用启动器(Starter): 推荐
33+
34+
```
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git clone https://github.com/ai16z/eliza-starter.git
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cd eliza-starter
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cp .env.example .env
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```
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## (B) 手动启动Eliza: 仅在您知道自己在做什么时才推荐
41+
42+
```
43+
git clone https://github.com/ai16z/eliza.git
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cd eliza
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# 切换最新发布的版本(Checkout the latest release)
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# Eliza的迭代速度非常快, 所以我们建议经常性的切换到最新的发布版本以免出现问题(This project iterates fast, so we recommend checking out the latest release)
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git checkout $(git describe --tags --abbrev=0)
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```
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在将代码下载到本地后, 我们要做两件事:
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### 1. 编辑.env文件(环境变量)
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54+
- 将 `.env.example` 复制为 `.env` 并在其中填写适当的值
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- 编辑推特环境并输入你的推特账号和密码
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36-
### 编辑角色文件
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**最简化配置方案**:
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```
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OPENAI_API_KEY=sk-xxx # 配置OpenAI 的API, sk-开头, 注意, 目前不支持AzureOpenAI!
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- 查看文件 `src/core/defaultCharacter.ts` - 您可以修改它
61+
## 如配置Twitter/X, 则需配置
62+
# Twitter/X Configuration
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TWITTER_DRY_RUN=false
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TWITTER_USERNAME=abc # Your Twitter/X account username
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TWITTER_PASSWORD=abc # Your Twitter/X account password
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TWITTER_EMAIL= xxx@gmail.com # Your Twitter/X account email
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TWITTER_COOKIES= '' # Your Twitter/X cookies, copy from broswer
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TWITTER_2FA_SECRET= # Two-factor authentication
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```
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### 2. 编辑角色文件
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- 标准的角色个性定义在文件 `characters/*.character.json`中, 您可以修改它或者直接使用它。
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- 您也可以使用 `node --loader ts-node/esm src/index.ts --characters="path/to/your/character.json"` 加载角色并同时运行多个机器人。
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- 需要说明的是, 在`characters/*.character.json`中, `clients字段对应**服务**, 默认可选`"twitter", "discord", "telegram"`等, 如果在`clients`中填入了如"twitter"等内容, 则需要在
76+
上面的`env`配置对应的环境变量。对`discord`和`telegram`同理。
77+
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```
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{
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"name": "trump",
81+
"clients": ["twitter"],
82+
"modelProvider": "openai",
83+
```
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在完成账号和角色文件的配置后，输入以下命令行启动你的bot：
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在完成环境变量和角色文件的配置后，输入以下命令行启动你的bot：
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```
88+
(A) 使用启动器(Starter)
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sh scripts/start.sh
90+
91+
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(B) 手动启动Eliza
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pnpm i
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pnpm build
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pnpm start
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```
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# 自定义Eliza
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### 添加常规行为

‎README_ES.md

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- 📚 Ingestión e interacción sencilla con documentos
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- 💾 Memoria recuperable y almacenamiento de documentos
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- 🚀 Altamente extensible - cree sus propias acciones y clientes para expandir capacidades
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- ☁️ Soporta múltiples modelos, incluyendo Llama local, OpenAI, Anthropic, Groq y más
12+
- ☁️ Soporta múltiples modelos, incluidos Llama local, OpenAI, Anthropic, Groq y más
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- 📦 Funciona perfectamente
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## Usos
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### Edite el archivo .env
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- Copie .env.example a .env y complete los valores apropiados
33-
- Edite las variables de ambiente de TWITTER para agregar nombre de usuario y contraseña del bot
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- Copie el archivo .env.example a .env y complete los valores apropiados
33+
- Edite las variables de entorno de TWITTER para agregar nombre de usuario y contraseña del bot
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### Edite el archivo de personaje
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‎README_FR.md

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- 🛠 Support des connecteurs Discord/ Twitter / Telegram
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- 🔗 Support des différents modèles d'IA (Llama, Grok, OpenAI, Anthropic, etc.)
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- 👥 Gestion de plusieurs agents et assistance
10-
- 📚 Import et intéractions avec différents types de documents simplifiés
10+
- 📚 Import et interactions avec différents types de documents simplifiés
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- 💾 Accès aux données en mémoire et aux documents stockés
1212
- 🚀 Grande personnalisation possible : création de nouveaux clients et de nouvelles actions
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- 📦 Simplicité d'utilisation
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Que pouvez-vous faire avec Eliza?
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1717
- 🤖 Chatbot
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- 🕵 ️Agents autonomes
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- 🕵 Agents autonomes
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- 📈 Processus automatisés
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- 🎮 PNJ intéractifs
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- 🎮 PNJ interactifs
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- 🧠 Trading automatisé
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# Premiers pas
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### Editer le fichier .env
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- Copier le fichier d'example et le remplir le avec les valeurs adéquates
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- Copier le fichier d'exemple .env.example et le remplir avec les valeurs adéquates
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```
3838
cp .env.example .env
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pnpm clean
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```
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#### Ressources additionelles
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#### Ressources additionnelles
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Il vous faudra peut-être installer Sharp.
65-
Si il y a une erreur lors du lancement du bot, essayez d'installer Sharp comme ceci :
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S'il y a une erreur lors du lancement du bot, essayez d'installer Sharp comme ceci :
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```
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pnpm install --include=optional sharp

‎README_IT.md

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- 🛠️ Connettori completi per Discord, Twitter e Telegram
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- 🔗 Supporto per tutti i modelli (Llama, Grok, OpenAI, Anthropic, ecc.)
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- 👥 Supporto multi-agente e per stanze
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- 📚 Acquisisci ed interagisci facilmente con i tuoi documenti
12+
- 📚 Acquisisci e interagisci facilmente con i tuoi documenti
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- 💾 Memoria recuperabile e archivio documenti
1414
- 🚀 Altamente estensibile - crea le tue azioni e clients personalizzati
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- ☁️ Supporto di numerosi modelli (Llama locale, OpenAI, Anthropic, Groq, ecc.)
1616
- 📦 Funziona e basta!
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## 🎯 Casi d'Uso
18+
## 🎯 Casi d'uso
1919

2020
- 🤖 Chatbot
2121
- 🕵️ Agenti Autonomi
22-
- 📈 Gestione Processi Aziendali
22+
- 📈 Gestione dei processi aziendali
2323
- 🎮 NPC per Videogiochi
2424
- 🧠 Trading
2525

@@ -51,7 +51,7 @@ sh scripts/start.sh
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### Modifica il file del personaggio
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54-
1. Apri `packages/agent/src/character.ts` per modificare il personaggio predefinito. Decommentare e modificare.
54+
1. Apri `packages/agent/src/character.ts` per modificare il personaggio predefinito. Decommenta e modifica.
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2. Per caricare personaggi personalizzati:
5757
- Usa `pnpm start --characters="percorso/del/tuo/personaggio.json"`
@@ -76,10 +76,10 @@ Potrebbe essere necessario installare Sharp. Se vedi un errore all'avvio, prova
7676
pnpm install --include=optional sharp
7777
```
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### Community e contatti
79+
### Comunità e contatti
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- [GitHub Issues](https://github.com/ai16z/eliza/issues). Ideale per: bug riscontrati utilizzando Eliza e proposte di funzionalità.
82-
- [Discord](https://discord.gg/ai16z). Ideale per: condividere le tue applicazioni e interagire con la community.
81+
- [GitHub Issues](https://github.com/ai16z/eliza/issues). Ideale per segnalare bug riscontrati durante l’utilizzo di Eliza e proporre nuove funzionalità.
82+
- [Discord](https://discord.gg/ai16z). Ideale per condividere le tue applicazioni e interagire con la comunità.
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## Contributori
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