perf: prompt

pnpm-lock.yaml

@@ -136,6 +136,184 @@ devDependencies:
 
 packages:
 
+  /@aws-sdk/credential-providers/3.278.0:
+    resolution: {integrity: sha512-XeCyXru9+gxePvrnPbdITZLSCC5qg3C/hgdItstDEvrQh+vMw9DJvX5ztoKh987C0puwkbB6HENC04ZTh/0Buw==}
+    engines: {node: '>=14.0.0'}
+    requiresBuild: true
+    dependencies:
+      '@aws-sdk/client-cognito-identity': registry.npmmirror.com/@aws-sdk/client-cognito-identity/3.278.0
+      '@aws-sdk/client-sso': registry.npmmirror.com/@aws-sdk/client-sso/3.278.0
+      '@aws-sdk/client-sts': registry.npmmirror.com/@aws-sdk/client-sts/3.278.0
+      '@aws-sdk/credential-provider-cognito-identity': registry.npmmirror.com/@aws-sdk/credential-provider-cognito-identity/3.278.0
+      '@aws-sdk/credential-provider-env': registry.npmmirror.com/@aws-sdk/credential-provider-env/3.272.0
+      '@aws-sdk/credential-provider-imds': registry.npmmirror.com/@aws-sdk/credential-provider-imds/3.272.0
+      '@aws-sdk/credential-provider-ini': registry.npmmirror.com/@aws-sdk/credential-provider-ini/3.278.0
+      '@aws-sdk/credential-provider-node': registry.npmmirror.com/@aws-sdk/credential-provider-node/3.278.0
+      '@aws-sdk/credential-provider-process': registry.npmmirror.com/@aws-sdk/credential-provider-process/3.272.0
+      '@aws-sdk/credential-provider-sso': registry.npmmirror.com/@aws-sdk/credential-provider-sso/3.278.0
+      '@aws-sdk/credential-provider-web-identity': registry.npmmirror.com/@aws-sdk/credential-provider-web-identity/3.272.0
+      '@aws-sdk/property-provider': registry.npmmirror.com/@aws-sdk/property-provider/3.272.0
+      '@aws-sdk/shared-ini-file-loader': registry.npmmirror.com/@aws-sdk/shared-ini-file-loader/3.272.0
+      '@aws-sdk/types': registry.npmmirror.com/@aws-sdk/types/3.272.0
+      tslib: registry.npmmirror.com/tslib/2.5.0
+    transitivePeerDependencies:
+      - aws-crt
+    dev: false
+    optional: true
+
+  /@emotion/is-prop-valid/0.8.8:
+    resolution: {integrity: sha512-u5WtneEAr5IDG2Wv65yhunPSMLIpuKsbuOktRojfrEiEvRyC85LgPMZI63cr7NUqT8ZIGdSVg8ZKGxIug4lXcA==}
+    requiresBuild: true
+    dependencies:
+      '@emotion/memoize': registry.npmmirror.com/@emotion/memoize/0.7.4
+    dev: false
+    optional: true
+
+  /@next/swc-android-arm-eabi/13.1.6:
+    resolution: {integrity: sha512-F3/6Z8LH/pGlPzR1AcjPFxx35mPqjE5xZcf+IL+KgbW9tMkp7CYi1y7qKrEWU7W4AumxX/8OINnDQWLiwLasLQ==}
+    engines: {node: '>= 10'}
+    cpu: [arm]
+    os: [android]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-android-arm64/13.1.6:
+    resolution: {integrity: sha512-cMwQjnB8vrYkWyK/H0Rf2c2pKIH4RGjpKUDvbjVAit6SbwPDpmaijLio0LWFV3/tOnY6kvzbL62lndVA0mkYpw==}
+    engines: {node: '>= 10'}
+    cpu: [arm64]
+    os: [android]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-darwin-arm64/13.1.6:
+    resolution: {integrity: sha512-KKRQH4DDE4kONXCvFMNBZGDb499Hs+xcFAwvj+rfSUssIDrZOlyfJNy55rH5t2Qxed1e4K80KEJgsxKQN1/fyw==}
+    engines: {node: '>= 10'}
+    cpu: [arm64]
+    os: [darwin]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-darwin-x64/13.1.6:
+    resolution: {integrity: sha512-/uOky5PaZDoaU99ohjtNcDTJ6ks/gZ5ykTQDvNZDjIoCxFe3+t06bxsTPY6tAO6uEAw5f6vVFX5H5KLwhrkZCA==}
+    engines: {node: '>= 10'}
+    cpu: [x64]
+    os: [darwin]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-freebsd-x64/13.1.6:
+    resolution: {integrity: sha512-qaEALZeV7to6weSXk3Br80wtFQ7cFTpos/q+m9XVRFggu+8Ib895XhMWdJBzew6aaOcMvYR6KQ6JmHA2/eMzWw==}
+    engines: {node: '>= 10'}
+    cpu: [x64]
+    os: [freebsd]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-linux-arm-gnueabihf/13.1.6:
+    resolution: {integrity: sha512-OybkbC58A1wJ+JrJSOjGDvZzrVEQA4sprJejGqMwiZyLqhr9Eo8FXF0y6HL+m1CPCpPhXEHz/2xKoYsl16kNqw==}
+    engines: {node: '>= 10'}
+    cpu: [arm]
+    os: [linux]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-linux-arm64-gnu/13.1.6:
+    resolution: {integrity: sha512-yCH+yDr7/4FDuWv6+GiYrPI9kcTAO3y48UmaIbrKy8ZJpi7RehJe3vIBRUmLrLaNDH3rY1rwoHi471NvR5J5NQ==}
+    engines: {node: '>= 10'}
+    cpu: [arm64]
+    os: [linux]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-linux-arm64-musl/13.1.6:
+    resolution: {integrity: sha512-ECagB8LGX25P9Mrmlc7Q/TQBb9rGScxHbv/kLqqIWs2fIXy6Y/EiBBiM72NTwuXUFCNrWR4sjUPSooVBJJ3ESQ==}
+    engines: {node: '>= 10'}
+    cpu: [arm64]
+    os: [linux]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-linux-x64-gnu/13.1.6:
+    resolution: {integrity: sha512-GT5w2mruk90V/I5g6ScuueE7fqj/d8Bui2qxdw6lFxmuTgMeol5rnzAv4uAoVQgClOUO/MULilzlODg9Ib3Y4Q==}
+    engines: {node: '>= 10'}
+    cpu: [x64]
+    os: [linux]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-linux-x64-musl/13.1.6:
+    resolution: {integrity: sha512-keFD6KvwOPzmat4TCnlnuxJCQepPN+8j3Nw876FtULxo8005Y9Ghcl7ACcR8GoiKoddAq8gxNBrpjoxjQRHeAQ==}
+    engines: {node: '>= 10'}
+    cpu: [x64]
+    os: [linux]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-win32-arm64-msvc/13.1.6:
+    resolution: {integrity: sha512-OwertslIiGQluFvHyRDzBCIB07qJjqabAmINlXUYt7/sY7Q7QPE8xVi5beBxX/rxTGPIbtyIe3faBE6Z2KywhQ==}
+    engines: {node: '>= 10'}
+    cpu: [arm64]
+    os: [win32]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-win32-ia32-msvc/13.1.6:
+    resolution: {integrity: sha512-g8zowiuP8FxUR9zslPmlju7qYbs2XBtTLVSxVikPtUDQedhcls39uKYLvOOd1JZg0ehyhopobRoH1q+MHlIN/w==}
+    engines: {node: '>= 10'}
+    cpu: [ia32]
+    os: [win32]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /@next/swc-win32-x64-msvc/13.1.6:
+    resolution: {integrity: sha512-Ls2OL9hi3YlJKGNdKv8k3X/lLgc3VmLG3a/DeTkAd+lAituJp8ZHmRmm9f9SL84fT3CotlzcgbdaCDfFwFA6bA==}
+    engines: {node: '>= 10'}
+    cpu: [x64]
+    os: [win32]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /fsevents/2.3.2:
+    resolution: {integrity: sha512-xiqMQR4xAeHTuB9uWm+fFRcIOgKBMiOBP+eXiyT7jsgVCq1bkVygt00oASowB7EdtpOHaaPgKt812P9ab+DDKA==}
+    engines: {node: ^8.16.0 || ^10.6.0 || >=11.0.0}
+    os: [darwin]
+    requiresBuild: true
+    dev: false
+    optional: true
+
+  /graceful-fs/4.2.10:
+    resolution: {integrity: sha512-9ByhssR2fPVsNZj478qUUbKfmL0+t5BDVyjShtyZZLiK7ZDAArFFfopyOTj0M05wE2tJPisA4iTnnXl2YoPvOA==}
+    dev: false
+    optional: true
+
+  /saslprep/1.0.3:
+    resolution: {integrity: sha512-/MY/PEMbk2SuY5sScONwhUDsV2p77Znkb/q3nSVstq/yQzYJOH/Azh29p9oJLsl3LnQwSvZDKagDGBsBwSooag==}
+    engines: {node: '>=6'}
+    requiresBuild: true
+    dependencies:
+      sparse-bitfield: registry.npmmirror.com/sparse-bitfield/3.0.3
+    dev: false
+    optional: true
+
+  /source-map/0.6.1:
+    resolution: {integrity: sha512-UjgapumWlbMhkBgzT7Ykc5YXUT46F0iKu8SGXq0bcwP5dz/h0Plj6enJqjz1Zbq2l5WaqYnrVbwWOWMyF3F47g==}
+    engines: {node: '>=0.10.0'}
+    dev: false
+    optional: true
+
   registry.npmmirror.com/@alicloud/credentials/2.2.6:
     resolution: {integrity: sha512-jG+msY77dHmAF3x+8VTy7fEgORyXLHmDci8t92HeipBdCHsPptDegA++GEwKgR7f6G4wvafYt+aqMZ1iligdrQ==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@alicloud/credentials/-/credentials-2.2.6.tgz}
     name: '@alicloud/credentials'
@@ -641,33 +819,6 @@ packages:
     dev: false
     optional: true
 
-  registry.npmmirror.com/@aws-sdk/credential-providers/3.278.0:
-    resolution: {integrity: sha512-XeCyXru9+gxePvrnPbdITZLSCC5qg3C/hgdItstDEvrQh+vMw9DJvX5ztoKh987C0puwkbB6HENC04ZTh/0Buw==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@aws-sdk/credential-providers/-/credential-providers-3.278.0.tgz}
-    name: '@aws-sdk/credential-providers'
-    version: 3.278.0
-    engines: {node: '>=14.0.0'}
-    requiresBuild: true
-    dependencies:
-      '@aws-sdk/client-cognito-identity': registry.npmmirror.com/@aws-sdk/client-cognito-identity/3.278.0
-      '@aws-sdk/client-sso': registry.npmmirror.com/@aws-sdk/client-sso/3.278.0
-      '@aws-sdk/client-sts': registry.npmmirror.com/@aws-sdk/client-sts/3.278.0
-      '@aws-sdk/credential-provider-cognito-identity': registry.npmmirror.com/@aws-sdk/credential-provider-cognito-identity/3.278.0
-      '@aws-sdk/credential-provider-env': registry.npmmirror.com/@aws-sdk/credential-provider-env/3.272.0
-      '@aws-sdk/credential-provider-imds': registry.npmmirror.com/@aws-sdk/credential-provider-imds/3.272.0
-      '@aws-sdk/credential-provider-ini': registry.npmmirror.com/@aws-sdk/credential-provider-ini/3.278.0
-      '@aws-sdk/credential-provider-node': registry.npmmirror.com/@aws-sdk/credential-provider-node/3.278.0
-      '@aws-sdk/credential-provider-process': registry.npmmirror.com/@aws-sdk/credential-provider-process/3.272.0
-      '@aws-sdk/credential-provider-sso': registry.npmmirror.com/@aws-sdk/credential-provider-sso/3.278.0
-      '@aws-sdk/credential-provider-web-identity': registry.npmmirror.com/@aws-sdk/credential-provider-web-identity/3.272.0
-      '@aws-sdk/property-provider': registry.npmmirror.com/@aws-sdk/property-provider/3.272.0
-      '@aws-sdk/shared-ini-file-loader': registry.npmmirror.com/@aws-sdk/shared-ini-file-loader/3.272.0
-      '@aws-sdk/types': registry.npmmirror.com/@aws-sdk/types/3.272.0
-      tslib: registry.npmmirror.com/tslib/2.5.0
-    transitivePeerDependencies:
-      - aws-crt
-    dev: false
-    optional: true
-
   registry.npmmirror.com/@aws-sdk/fetch-http-handler/3.272.0:
     resolution: {integrity: sha512-1Qhm9e0RbS1Xf4CZqUbQyUMkDLd7GrsRXWIvm9b86/vgeV8/WnjO3CMue9D51nYgcyQORhYXv6uVjAYCWbUExA==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@aws-sdk/fetch-http-handler/-/fetch-http-handler-3.272.0.tgz}
     name: '@aws-sdk/fetch-http-handler'
@@ -4220,16 +4371,6 @@ packages:
     version: 0.9.0
     dev: false
 
-  registry.npmmirror.com/@emotion/is-prop-valid/0.8.8:
-    resolution: {integrity: sha512-u5WtneEAr5IDG2Wv65yhunPSMLIpuKsbuOktRojfrEiEvRyC85LgPMZI63cr7NUqT8ZIGdSVg8ZKGxIug4lXcA==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@emotion/is-prop-valid/-/is-prop-valid-0.8.8.tgz}
-    name: '@emotion/is-prop-valid'
-    version: 0.8.8
-    requiresBuild: true
-    dependencies:
-      '@emotion/memoize': registry.npmmirror.com/@emotion/memoize/0.7.4
-    dev: false
-    optional: true
-
   registry.npmmirror.com/@emotion/is-prop-valid/1.2.0:
     resolution: {integrity: sha512-3aDpDprjM0AwaxGE09bOPkNxHpBd+kA6jty3RnaEXdweX1DF1U3VQpPYb0g1IStAuK7SVQ1cy+bNBBKp4W3Fjg==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@emotion/is-prop-valid/-/is-prop-valid-1.2.0.tgz}
     name: '@emotion/is-prop-valid'
@@ -4520,153 +4661,6 @@ packages:
     version: 13.1.6
     dev: false
 
-  registry.npmmirror.com/@next/swc-android-arm-eabi/13.1.6:
-    resolution: {integrity: sha512-F3/6Z8LH/pGlPzR1AcjPFxx35mPqjE5xZcf+IL+KgbW9tMkp7CYi1y7qKrEWU7W4AumxX/8OINnDQWLiwLasLQ==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-android-arm-eabi/-/swc-android-arm-eabi-13.1.6.tgz}
-    name: '@next/swc-android-arm-eabi'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [arm]
-    os: [android]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-android-arm64/13.1.6:
-    resolution: {integrity: sha512-cMwQjnB8vrYkWyK/H0Rf2c2pKIH4RGjpKUDvbjVAit6SbwPDpmaijLio0LWFV3/tOnY6kvzbL62lndVA0mkYpw==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-android-arm64/-/swc-android-arm64-13.1.6.tgz}
-    name: '@next/swc-android-arm64'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [arm64]
-    os: [android]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-darwin-arm64/13.1.6:
-    resolution: {integrity: sha512-KKRQH4DDE4kONXCvFMNBZGDb499Hs+xcFAwvj+rfSUssIDrZOlyfJNy55rH5t2Qxed1e4K80KEJgsxKQN1/fyw==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-darwin-arm64/-/swc-darwin-arm64-13.1.6.tgz}
-    name: '@next/swc-darwin-arm64'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [arm64]
-    os: [darwin]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-darwin-x64/13.1.6:
-    resolution: {integrity: sha512-/uOky5PaZDoaU99ohjtNcDTJ6ks/gZ5ykTQDvNZDjIoCxFe3+t06bxsTPY6tAO6uEAw5f6vVFX5H5KLwhrkZCA==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-darwin-x64/-/swc-darwin-x64-13.1.6.tgz}
-    name: '@next/swc-darwin-x64'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [x64]
-    os: [darwin]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-freebsd-x64/13.1.6:
-    resolution: {integrity: sha512-qaEALZeV7to6weSXk3Br80wtFQ7cFTpos/q+m9XVRFggu+8Ib895XhMWdJBzew6aaOcMvYR6KQ6JmHA2/eMzWw==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-freebsd-x64/-/swc-freebsd-x64-13.1.6.tgz}
-    name: '@next/swc-freebsd-x64'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [x64]
-    os: [freebsd]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-linux-arm-gnueabihf/13.1.6:
-    resolution: {integrity: sha512-OybkbC58A1wJ+JrJSOjGDvZzrVEQA4sprJejGqMwiZyLqhr9Eo8FXF0y6HL+m1CPCpPhXEHz/2xKoYsl16kNqw==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-linux-arm-gnueabihf/-/swc-linux-arm-gnueabihf-13.1.6.tgz}
-    name: '@next/swc-linux-arm-gnueabihf'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [arm]
-    os: [linux]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-linux-arm64-gnu/13.1.6:
-    resolution: {integrity: sha512-yCH+yDr7/4FDuWv6+GiYrPI9kcTAO3y48UmaIbrKy8ZJpi7RehJe3vIBRUmLrLaNDH3rY1rwoHi471NvR5J5NQ==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-linux-arm64-gnu/-/swc-linux-arm64-gnu-13.1.6.tgz}
-    name: '@next/swc-linux-arm64-gnu'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [arm64]
-    os: [linux]
-    libc: [glibc]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-linux-arm64-musl/13.1.6:
-    resolution: {integrity: sha512-ECagB8LGX25P9Mrmlc7Q/TQBb9rGScxHbv/kLqqIWs2fIXy6Y/EiBBiM72NTwuXUFCNrWR4sjUPSooVBJJ3ESQ==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-linux-arm64-musl/-/swc-linux-arm64-musl-13.1.6.tgz}
-    name: '@next/swc-linux-arm64-musl'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [arm64]
-    os: [linux]
-    libc: [musl]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-linux-x64-gnu/13.1.6:
-    resolution: {integrity: sha512-GT5w2mruk90V/I5g6ScuueE7fqj/d8Bui2qxdw6lFxmuTgMeol5rnzAv4uAoVQgClOUO/MULilzlODg9Ib3Y4Q==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-linux-x64-gnu/-/swc-linux-x64-gnu-13.1.6.tgz}
-    name: '@next/swc-linux-x64-gnu'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [x64]
-    os: [linux]
-    libc: [glibc]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-linux-x64-musl/13.1.6:
-    resolution: {integrity: sha512-keFD6KvwOPzmat4TCnlnuxJCQepPN+8j3Nw876FtULxo8005Y9Ghcl7ACcR8GoiKoddAq8gxNBrpjoxjQRHeAQ==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-linux-x64-musl/-/swc-linux-x64-musl-13.1.6.tgz}
-    name: '@next/swc-linux-x64-musl'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [x64]
-    os: [linux]
-    libc: [musl]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-win32-arm64-msvc/13.1.6:
-    resolution: {integrity: sha512-OwertslIiGQluFvHyRDzBCIB07qJjqabAmINlXUYt7/sY7Q7QPE8xVi5beBxX/rxTGPIbtyIe3faBE6Z2KywhQ==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-win32-arm64-msvc/-/swc-win32-arm64-msvc-13.1.6.tgz}
-    name: '@next/swc-win32-arm64-msvc'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [arm64]
-    os: [win32]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-win32-ia32-msvc/13.1.6:
-    resolution: {integrity: sha512-g8zowiuP8FxUR9zslPmlju7qYbs2XBtTLVSxVikPtUDQedhcls39uKYLvOOd1JZg0ehyhopobRoH1q+MHlIN/w==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-win32-ia32-msvc/-/swc-win32-ia32-msvc-13.1.6.tgz}
-    name: '@next/swc-win32-ia32-msvc'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [ia32]
-    os: [win32]
-    requiresBuild: true
-    dev: false
-    optional: true
-
-  registry.npmmirror.com/@next/swc-win32-x64-msvc/13.1.6:
-    resolution: {integrity: sha512-Ls2OL9hi3YlJKGNdKv8k3X/lLgc3VmLG3a/DeTkAd+lAituJp8ZHmRmm9f9SL84fT3CotlzcgbdaCDfFwFA6bA==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@next/swc-win32-x64-msvc/-/swc-win32-x64-msvc-13.1.6.tgz}
-    name: '@next/swc-win32-x64-msvc'
-    version: 13.1.6
-    engines: {node: '>= 10'}
-    cpu: [x64]
-    os: [win32]
-    requiresBuild: true
-    dev: false
-    optional: true
-
   registry.npmmirror.com/@nodelib/fs.scandir/2.1.5:
     resolution: {integrity: sha512-vq24Bq3ym5HEQm2NKCr3yXDwjc7vTsEThRDnkp2DK9p1uqLR+DHurm/NOTo0KG7HYHU7eppKZj3MyqYuMBf62g==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/@nodelib/fs.scandir/-/fs.scandir-2.1.5.tgz}
     name: '@nodelib/fs.scandir'
@@ -6018,7 +6012,7 @@ packages:
       normalize-path: registry.npmmirror.com/normalize-path/3.0.0
       readdirp: registry.npmmirror.com/readdirp/3.6.0
     optionalDependencies:
-      fsevents: registry.npmmirror.com/fsevents/2.3.2
+      fsevents: 2.3.2
     dev: false
 
   registry.npmmirror.com/chownr/1.1.4:
@@ -6812,7 +6806,7 @@ packages:
       esutils: registry.npmmirror.com/esutils/2.0.3
       optionator: registry.npmmirror.com/optionator/0.8.3
     optionalDependencies:
-      source-map: registry.npmmirror.com/source-map/0.6.1
+      source-map: 0.6.1
     dev: false
 
   registry.npmmirror.com/eslint-config-next/13.1.6_7kw3g6rralp5ps6mg3uyzz6azm:
@@ -7399,7 +7393,7 @@ packages:
       react-dom: registry.npmmirror.com/react-dom/18.2.0_react@18.2.0
       tslib: registry.npmmirror.com/tslib/2.5.0
     optionalDependencies:
-      '@emotion/is-prop-valid': registry.npmmirror.com/@emotion/is-prop-valid/0.8.8
+      '@emotion/is-prop-valid': 0.8.8
     dev: false
 
   registry.npmmirror.com/framesync/6.1.2:
@@ -7433,16 +7427,6 @@ packages:
     version: 1.0.0
     dev: true
 
-  registry.npmmirror.com/fsevents/2.3.2:
-    resolution: {integrity: sha512-xiqMQR4xAeHTuB9uWm+fFRcIOgKBMiOBP+eXiyT7jsgVCq1bkVygt00oASowB7EdtpOHaaPgKt812P9ab+DDKA==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/fsevents/-/fsevents-2.3.2.tgz}
-    name: fsevents
-    version: 2.3.2
-    engines: {node: ^8.16.0 || ^10.6.0 || >=11.0.0}
-    os: [darwin]
-    requiresBuild: true
-    dev: false
-    optional: true
-
   registry.npmmirror.com/ftp/0.3.10:
     resolution: {integrity: sha512-faFVML1aBx2UoDStmLwv2Wptt4vw5x03xxX172nhA5Y5HBshW5JweqQ2W4xL4dezQTG8inJsuYcpPHHU3X5OTQ==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/ftp/-/ftp-0.3.10.tgz}
     name: ftp
@@ -8442,7 +8426,7 @@ packages:
     name: jsonfile
     version: 4.0.0
     optionalDependencies:
-      graceful-fs: registry.npmmirror.com/graceful-fs/4.2.10
+      graceful-fs: 4.2.10
     dev: false
 
   registry.npmmirror.com/jsonwebtoken/9.0.0:
@@ -9373,8 +9357,8 @@ packages:
       mongodb-connection-string-url: registry.npmmirror.com/mongodb-connection-string-url/2.6.0
       socks: registry.npmmirror.com/socks/2.7.1
     optionalDependencies:
-      '@aws-sdk/credential-providers': registry.npmmirror.com/@aws-sdk/credential-providers/3.278.0
-      saslprep: registry.npmmirror.com/saslprep/1.0.3
+      '@aws-sdk/credential-providers': 3.278.0
+      saslprep: 1.0.3
     transitivePeerDependencies:
       - aws-crt
     dev: false
@@ -9513,19 +9497,19 @@ packages:
       sass: registry.npmmirror.com/sass/1.58.3
       styled-jsx: registry.npmmirror.com/styled-jsx/5.1.1_react@18.2.0
     optionalDependencies:
-      '@next/swc-android-arm-eabi': registry.npmmirror.com/@next/swc-android-arm-eabi/13.1.6
-      '@next/swc-android-arm64': registry.npmmirror.com/@next/swc-android-arm64/13.1.6
-      '@next/swc-darwin-arm64': registry.npmmirror.com/@next/swc-darwin-arm64/13.1.6
-      '@next/swc-darwin-x64': registry.npmmirror.com/@next/swc-darwin-x64/13.1.6
-      '@next/swc-freebsd-x64': registry.npmmirror.com/@next/swc-freebsd-x64/13.1.6
-      '@next/swc-linux-arm-gnueabihf': registry.npmmirror.com/@next/swc-linux-arm-gnueabihf/13.1.6
-      '@next/swc-linux-arm64-gnu': registry.npmmirror.com/@next/swc-linux-arm64-gnu/13.1.6
-      '@next/swc-linux-arm64-musl': registry.npmmirror.com/@next/swc-linux-arm64-musl/13.1.6
-      '@next/swc-linux-x64-gnu': registry.npmmirror.com/@next/swc-linux-x64-gnu/13.1.6
-      '@next/swc-linux-x64-musl': registry.npmmirror.com/@next/swc-linux-x64-musl/13.1.6
-      '@next/swc-win32-arm64-msvc': registry.npmmirror.com/@next/swc-win32-arm64-msvc/13.1.6
-      '@next/swc-win32-ia32-msvc': registry.npmmirror.com/@next/swc-win32-ia32-msvc/13.1.6
-      '@next/swc-win32-x64-msvc': registry.npmmirror.com/@next/swc-win32-x64-msvc/13.1.6
+      '@next/swc-android-arm-eabi': 13.1.6
+      '@next/swc-android-arm64': 13.1.6
+      '@next/swc-darwin-arm64': 13.1.6
+      '@next/swc-darwin-x64': 13.1.6
+      '@next/swc-freebsd-x64': 13.1.6
+      '@next/swc-linux-arm-gnueabihf': 13.1.6
+      '@next/swc-linux-arm64-gnu': 13.1.6
+      '@next/swc-linux-arm64-musl': 13.1.6
+      '@next/swc-linux-x64-gnu': 13.1.6
+      '@next/swc-linux-x64-musl': 13.1.6
+      '@next/swc-win32-arm64-msvc': 13.1.6
+      '@next/swc-win32-ia32-msvc': 13.1.6
+      '@next/swc-win32-x64-msvc': 13.1.6
     transitivePeerDependencies:
       - '@babel/core'
       - babel-plugin-macros
@@ -10760,17 +10744,6 @@ packages:
     version: 2.1.2
     dev: false
 
-  registry.npmmirror.com/saslprep/1.0.3:
-    resolution: {integrity: sha512-/MY/PEMbk2SuY5sScONwhUDsV2p77Znkb/q3nSVstq/yQzYJOH/Azh29p9oJLsl3LnQwSvZDKagDGBsBwSooag==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/saslprep/-/saslprep-1.0.3.tgz}
-    name: saslprep
-    version: 1.0.3
-    engines: {node: '>=6'}
-    requiresBuild: true
-    dependencies:
-      sparse-bitfield: registry.npmmirror.com/sparse-bitfield/3.0.3
-    dev: false
-    optional: true
-
   registry.npmmirror.com/sass/1.58.3:
     resolution: {integrity: sha512-Q7RaEtYf6BflYrQ+buPudKR26/lH+10EmO9bBqbmPh/KeLqv8bjpTNqxe71ocONqXq+jYiCbpPUmQMS+JJPk4A==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/sass/-/sass-1.58.3.tgz}
     name: sass
@@ -11011,6 +10984,7 @@ packages:
     name: source-map
     version: 0.6.1
     engines: {node: '>=0.10.0'}
+    dev: true
 
   registry.npmmirror.com/space-separated-tokens/1.1.5:
     resolution: {integrity: sha512-q/JSVd1Lptzhf5bkYm4ob4iWPjx0KiRe3sRFBNrVqbJkFaBm5vbbowy1mymoPNLRa52+oadOhJ+K49wsSeSjTA==, registry: https://registry.npm.taobao.org/, tarball: https://registry.npmmirror.com/space-separated-tokens/-/space-separated-tokens-1.1.5.tgz}

public/docs/intro.md

@@ -3,39 +3,41 @@
 [Git 仓库](https://github.com/c121914yu/FastGPT)
 
 ### 交流群/问题反馈
+
 扫码满了，加个小号，定时拉
-wx号: fastgpt123
+wx 号: fastgpt123
 ![](/imgs/wx300.jpg)
 
-
 ### 快速开始
-1. 使用手机号注册账号。  
-2. 进入账号页面，添加关联账号，目前只有 openai 的账号可以添加，直接去 openai 官网，把 API Key 粘贴过来。  
+
+1. 使用手机号注册账号。
+2. 进入账号页面，添加关联账号，目前只有 openai 的账号可以添加，直接去 openai 官网，把 API Key 粘贴过来。
 3. 如果填写了自己的 openai 账号，使用时会直接用你的账号。如果没有填写，需要付费使用平台的账号。
-4. 进入模型页，创建一个模型，建议直接用 ChatGPT。    
-5. 在模型列表点击【对话】，即可使用 API 进行聊天。  
+4. 进入模型页，创建一个模型，建议直接用 ChatGPT。
+5. 在模型列表点击【对话】，即可使用 API 进行聊天。
 
 ### 价格表
+
 如果使用了自己的 Api Key，不会计费。可以在账号页，看到详细账单。单纯使用 chatGPT 模型进行对话，只有一个计费项目。使用知识库时，包含**对话**和**索引**生成两个计费项。
 | 计费项 | 价格: 元/ 1K tokens（包含上下文）|
-| --- | --- | 
+| --- | --- |
+| claude - 对话 | 免费 |
 | chatgpt - 对话 | 0.03 |
 | 知识库 - 对话 | 0.03 |
 | 知识库 - 索引 | 0.004 |
 | 文件拆分 | 0.03 |
 
-
 ### 定制 prompt
 
-1. 进入模型编辑页  
-2. 调整温度和提示词  
+1. 进入模型编辑页
+2. 调整温度和提示词
 3. 使用该模型对话。每次对话时，提示词和温度都会自动注入，方便管理个人的模型。建议把自己日常经常需要使用的 5~10 个方向预设好。
 
 ### 知识库
 
-1. 创建模型时选择【知识库】  
-2. 进入模型编辑页  
-3. 导入数据，可以选择手动导入，或者选择文件导入。文件导入会自动调用 chatGPT 理解文件内容，并生成知识库。  
-4. 使用该模型对话。  
+1. 创建模型时选择【知识库】
+2. 进入模型编辑页
+3. 导入数据，可以选择手动导入，或者选择文件导入。文件导入会自动调用 chatGPT 理解文件内容，并生成知识库。
+4. 使用该模型对话。
 
-注意：使用知识库模型对话时，tokens 消耗会加快。  
+注意：使用知识库模型对话时，tokens 消耗会加快。

public/docs/versionIntro.md

@@ -1,6 +1,6 @@
-### Fast GPT V3.0
+### Fast GPT V3.1
 
+- 优化 - 知识库搜索，会将上一个问题并入搜索范围。
+- 优化 - 模型结构设计，不再区分知识库和对话模型，而是通过开关的形式，手动选择手否需要进行知识库搜索。
 - 新增 - 模型共享市场，可以使用其他用户分享的模型。
 - 新增 - 邀请好友注册功能。
-- 优化 - 选择文件，采用链式处理，避免卡死。
-- 修复 - 导入时分段问题。

src/api/chat.ts

@@ -24,6 +24,7 @@ export const delChatHistoryById = (id: string) => GET(`/chat/removeHistory?id=${
  */
 export const postSaveChat = (data: {
   modelId: string;
+  newChatId: '' | string;
   chatId: '' | string;
   prompts: ChatItemType[];
 }) => POST<string>('/chat/saveChat', data);
@@ -31,5 +32,5 @@ export const postSaveChat = (data: {
 /**
  * 删除一句对话
  */
-export const delChatRecordByIndex = (chatId: string, index: number) =>
-  DELETE(`/chat/delChatRecordByIndex?chatId=${chatId}&index=${index}`);
+export const delChatRecordByIndex = (chatId: string, contentId: string) =>
+  DELETE(`/chat/delChatRecordByContentId?chatId=${chatId}&contentId=${contentId}`);

src/api/fetch.ts

@@ -1,4 +1,6 @@
 import { getToken } from '../utils/user';
+import { SYSTEM_PROMPT_HEADER, NEW_CHATID_HEADER } from '@/constants/chat';
+
 interface StreamFetchProps {
   url: string;
   data: any;
@@ -6,50 +8,56 @@ interface StreamFetchProps {
   abortSignal: AbortController;
 }
 export const streamFetch = ({ url, data, onMessage, abortSignal }: StreamFetchProps) =>
-  new Promise<string>(async (resolve, reject) => {
-    try {
-      const res = await fetch(url, {
-        method: 'POST',
-        headers: {
-          'Content-Type': 'application/json',
-          Authorization: getToken() || ''
-        },
-        body: JSON.stringify(data),
-        signal: abortSignal.signal
-      });
-      const reader = res.body?.getReader();
-      if (!reader) return;
-      const decoder = new TextDecoder();
-      let responseText = '';
+  new Promise<{ responseText: string; systemPrompt: string; newChatId: string }>(
+    async (resolve, reject) => {
+      try {
+        const res = await fetch(url, {
+          method: 'POST',
+          headers: {
+            'Content-Type': 'application/json',
+            Authorization: getToken() || ''
+          },
+          body: JSON.stringify(data),
+          signal: abortSignal.signal
+        });
+        const reader = res.body?.getReader();
+        if (!reader) return;
 
-      const read = async () => {
-        try {
-          const { done, value } = await reader?.read();
-          if (done) {
-            if (res.status === 200) {
-              resolve(responseText);
-            } else {
-              const parseError = JSON.parse(responseText);
-              reject(parseError?.message || '请求异常');
+        const decoder = new TextDecoder();
+
+        const systemPrompt = decodeURIComponent(res.headers.get(SYSTEM_PROMPT_HEADER) || '');
+        const newChatId = decodeURIComponent(res.headers.get(NEW_CHATID_HEADER) || '');
+
+        let responseText = '';
+
+        const read = async () => {
+          try {
+            const { done, value } = await reader?.read();
+            if (done) {
+              if (res.status === 200) {
+                resolve({ responseText, systemPrompt, newChatId });
+              } else {
+                const parseError = JSON.parse(responseText);
+                reject(parseError?.message || '请求异常');
+              }
+
+              return;
             }
-
-            return;
+            const text = decoder.decode(value).replace(/<br\/>/g, '\n');
+            responseText += text;
+            onMessage(text);
+            read();
+          } catch (err: any) {
+            if (err?.message === 'The user aborted a request.') {
+              return resolve({ responseText, systemPrompt, newChatId });
+            }
+            reject(typeof err === 'string' ? err : err?.message || '请求异常');
           }
-          const text = decoder.decode(value).replace(/<br\/>/g, '\n');
-          res.status === 200 && onMessage(text);
-          responseText += text;
-          read();
-        } catch (err: any) {
-          if (err?.message === 'The user aborted a request.') {
-            return resolve(responseText);
-          }
-          reject(typeof err === 'string' ? err : err?.message || '请求异常');
-        }
-      };
-
-      read();
-    } catch (err: any) {
-      console.log(err, '====');
-      reject(typeof err === 'string' ? err : err?.message || '请求异常');
+        };
+        read();
+      } catch (err: any) {
+        console.log(err, '====');
+        reject(typeof err === 'string' ? err : err?.message || '请求异常');
+      }
     }
-  });
+  );

src/api/model.ts

@@ -12,8 +12,7 @@ export const getMyModels = () => GET<ModelSchema[]>('/model/list');
 /**
  * 创建一个模型
  */
-export const postCreateModel = (data: { name: string; serviceModelName: string }) =>
-  POST<ModelSchema>('/model/create', data);
+export const postCreateModel = (data: { name: string }) => POST<string>('/model/create', data);
 
 /**
  * 根据 ID 删除模型

src/api/response/chat.d.ts

@@ -7,7 +7,6 @@ export type InitChatResponse = {
   name: string;
   avatar: string;
   intro: string;
-  chatModel: ModelSchema.service.chatModel; // 对话模型名
-  modelName: ModelSchema.service.modelName; // 底层模型
+  chatModel: ModelSchema['chat']['chatModel']; // 对话模型名
   history: ChatItemType[];
 };

src/components/Icon/icons/export.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1682957006954" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="2644" xmlns:xlink="http://www.w3.org/1999/xlink" width="48" height="48"><path d="M942.1 593.9c-22.6 0-41 18.3-41 41v204.8c0 22.6-18.4 41-41 41H163.8c-22.6 0-41-18.4-41-41V634.9c0-22.6-18.3-41-41-41s-41 18.3-41 41v204.8c0 67.8 55.1 122.9 122.9 122.9H860c67.8 0 122.9-55.1 122.9-122.9V634.9c0.1-22.6-18.2-41-40.8-41z" p-id="2645"></path><path d="M309.3 363L471 201.3v515.5c0 22.5 18.4 41 41 41 22.5 0 41-18.4 41-41V201.3L714.7 363c15.9 15.9 42 15.9 57.9 0 15.9-15.9 15.9-42 0-57.9L541.5 73.9c-0.2-0.2-0.3-0.4-0.4-0.5-5.7-5.7-12.7-9.3-20.1-10.9-0.2-0.1-0.5-0.2-0.7-0.2-2.7-0.5-5.4-0.8-8.1-0.8-2.7 0-5.5 0.3-8.1 0.8-0.3 0.1-0.5 0.2-0.7 0.2-7.4 1.6-14.4 5.2-20.1 10.9-0.2 0.2-0.3 0.4-0.4 0.5L251.4 305.1c-15.9 15.9-15.9 42 0 57.9 15.9 15.9 42 15.9 57.9 0z" p-id="2646"></path></svg>

src/components/Icon/index.tsx

@@ -21,7 +21,8 @@ const map = {
   stop: require('./icons/stop.svg').default,
   shareMarket: require('./icons/shareMarket.svg').default,
   collectionLight: require('./icons/collectionLight.svg').default,
-  collectionSolid: require('./icons/collectionSolid.svg').default
+  collectionSolid: require('./icons/collectionSolid.svg').default,
+  export: require('./icons/export.svg').default
 };
 
 export type IconName = keyof typeof map;

src/components/Layout/navbarPhone.tsx

@@ -39,7 +39,7 @@ const NavbarPhone = ({
         px={7}
       >
         <Box onClick={onOpen}>
-          <MyIcon name="menu" width={'20px'} height={'20px'} color={'blackAlpha.600'}></MyIcon>
+          <MyIcon name="menu" width={'20px'} height={'20px'} color={'blackAlpha.700'}></MyIcon>
         </Box>
       </Flex>
       <Drawer isOpen={isOpen} placement="left" size={'xs'} onClose={onClose}>

src/components/Markdown/index.tsx

@@ -17,7 +17,7 @@ const Markdown = ({ source, isChatting = false }: { source: string; isChatting?:
 
   return (
     <ReactMarkdown
-      className={`${styles.markdown} ${
+      className={`markdown ${styles.markdown} ${
         isChatting ? (source === '' ? styles.waitingAnimation : styles.animation) : ''
       }`}
       remarkPlugins={[remarkMath]}
@@ -31,6 +31,7 @@ const Markdown = ({ source, isChatting = false }: { source: string; isChatting?:
           return !inline || match ? (
             <Box my={3} borderRadius={'md'} overflow={'hidden'} backgroundColor={'#222'}>
               <Flex
+                className="code-header"
                 py={2}
                 px={5}
                 backgroundColor={useColorModeValue('#323641', 'gray.600')}

src/constants/common.ts

@@ -4,3 +4,823 @@ export enum UserAuthTypeEnum {
 }
 
 export const PRICE_SCALE = 100000;
+
+export const htmlTemplate = `<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <meta http-equiv="X-UA-Compatible" content="IE=edge" />
+    <meta name="viewport" content="width=device-width initial-scale=1.0" />
+    <title>FastGpt</title>
+  </head>
+  <style>
+    .markdown > :first-child {
+      margin-top: 0 !important;
+    }
+    .markdown > :last-child {
+      margin-bottom: 0 !important;
+    }
+    .markdown a.absent {
+      color: #cc0000;
+    }
+    .markdown a.anchor {
+      bottom: 0;
+      cursor: pointer;
+      display: block;
+      left: 0;
+      margin-left: -30px;
+      padding-left: 30px;
+      position: absolute;
+      top: 0;
+    }
+    .markdown h1,
+    .markdown h2,
+    .markdown h3,
+    .markdown h4,
+    .markdown h5,
+    .markdown h6 {
+      cursor: text;
+      font-weight: bold;
+      margin: 10px 0;
+      padding: 0;
+      position: relative;
+    }
+    .markdown h1 .mini-icon-link,
+    .markdown h2 .mini-icon-link,
+    .markdown h3 .mini-icon-link,
+    .markdown h4 .mini-icon-link,
+    .markdown h5 .mini-icon-link,
+    .markdown h6 .mini-icon-link {
+      display: none;
+    }
+    .markdown h1:hover a.anchor,
+    .markdown h2:hover a.anchor,
+    .markdown h3:hover a.anchor,
+    .markdown h4:hover a.anchor,
+    .markdown h5:hover a.anchor,
+    .markdown h6:hover a.anchor {
+      line-height: 1;
+      margin-left: -22px;
+      padding-left: 0;
+      text-decoration: none;
+      top: 15%;
+    }
+    .markdown h1:hover a.anchor .mini-icon-link,
+    .markdown h2:hover a.anchor .mini-icon-link,
+    .markdown h3:hover a.anchor .mini-icon-link,
+    .markdown h4:hover a.anchor .mini-icon-link,
+    .markdown h5:hover a.anchor .mini-icon-link,
+    .markdown h6:hover a.anchor .mini-icon-link {
+      display: inline-block;
+    }
+    .markdown h1 tt,
+    .markdown h1 code,
+    .markdown h2 tt,
+    .markdown h2 code,
+    .markdown h3 tt,
+    .markdown h3 code,
+    .markdown h4 tt,
+    .markdown h4 code,
+    .markdown h5 tt,
+    .markdown h5 code,
+    .markdown h6 tt,
+    .markdown h6 code {
+      font-size: inherit;
+    }
+    .markdown h1 {
+      font-size: 28px;
+    }
+    .markdown h2 {
+      font-size: 24px;
+    }
+    .markdown h3 {
+      font-size: 18px;
+    }
+    .markdown h4 {
+      font-size: 16px;
+    }
+    .markdown h5 {
+      font-size: 14px;
+    }
+    .markdown h6 {
+      font-size: 12px;
+    }
+    .markdown p,
+    .markdown blockquote,
+    .markdown ul,
+    .markdown ol,
+    .markdown dl,
+    .markdown table,
+    .markdown pre {
+      margin: 10px 0;
+    }
+    .markdown > h2:first-child,
+    .markdown > h1:first-child,
+    .markdown > h1:first-child + h2,
+    .markdown > h3:first-child,
+    .markdown > h4:first-child,
+    .markdown > h5:first-child,
+    .markdown > h6:first-child {
+      margin-top: 0;
+      padding-top: 0;
+    }
+    .markdown a:first-child,
+    .markdown > h1,
+    .markdown a:first-child,
+    .markdown > h2,
+    .markdown a:first-child,
+    .markdown > h3,
+    .markdown a:first-child,
+    .markdown > h4,
+    .markdown a:first-child,
+    .markdown > h5,
+    .markdown a:first-child,
+    .markdown > h6 {
+      margin-top: 0;
+      padding-top: 0;
+    }
+    .markdown h1 + p,
+    .markdown h2 + p,
+    .markdown h3 + p,
+    .markdown h4 + p,
+    .markdown h5 + p,
+    .markdown h6 + p {
+      margin-top: 0;
+    }
+    .markdown li p.first {
+      display: inline-block;
+    }
+    .markdown ul,
+    .markdown ol {
+      padding-left: 2em;
+    }
+    .markdown ul.no-list,
+    .markdown ol.no-list {
+      list-style-type: none;
+      padding: 0;
+    }
+    .markdown ul li > :first-child,
+    .markdown ol li > :first-child {
+      margin-top: 0;
+    }
+    .markdown ul ul,
+    .markdown ul ol,
+    .markdown ol ol,
+    .markdown ol ul {
+      margin-bottom: 0;
+    }
+    .markdown dl {
+      padding: 0;
+    }
+    .markdown dl dt {
+      font-size: 14px;
+      font-style: italic;
+      font-weight: bold;
+      margin: 15px 0 5px;
+      padding: 0;
+    }
+    .markdown dl dt:first-child {
+      padding: 0;
+    }
+    .markdown dl dt > :first-child {
+      margin-top: 0;
+    }
+    .markdown dl dt > :last-child {
+      margin-bottom: 0;
+    }
+    .markdown dl dd {
+      margin: 0 0 15px;
+      padding: 0 15px;
+    }
+    .markdown dl dd > *:first-child {
+      margin-top: 0;
+    }
+    .markdown dl dd > *last-child {
+      margin-bottom: none;
+    }
+
+    .markdown blockquote {
+      border-left: solid 4px #dddddd;
+      color: #777777;
+      padding-left: 15px;
+    }
+
+    .markdown blockquote > * :first-child {
+      margin-top: 0;
+    }
+
+    .markdown blockquote > * :last-child {
+      margin-bottom: 0;
+    }
+
+    .markdown table th {
+      font-weight: bold;
+    }
+    .markdown table th,
+    .markdown table td {
+      padding: 6px 13px;
+    }
+    .markdown table tr {
+      background-color: #ffffff;
+    }
+    .markdown table tr:nth-child(2n) {
+      background-color: #f0f0f0;
+    }
+    .markdown img {
+      max-width: 100%;
+    }
+    .markdown span.frame {
+      display: block;
+      overflow: hidden;
+    }
+    .markdown span.frame > span {
+      border: 1px solid #dddddd;
+      display: block;
+      float: left;
+      margin: 13px 0 0;
+      overflow: hidden;
+      padding: 7px;
+      width: auto;
+    }
+    .markdown span.frame span img {
+      display: block;
+      float: left;
+    }
+    .markdown span.frame span span {
+      clear: both;
+      color: #333333;
+      display: block;
+      padding: 5px;
+    }
+
+    .markdown span.align-center {
+      clear: both;
+      display: block;
+      overflow: hidden;
+      text-align: center;
+    }
+
+    .markdown span.align-center > span {
+      display: block;
+      margin: 13px auto;
+      overflow: hidden;
+    }
+
+    .markdown span.align-center span img {
+      margin: 0 auto;
+      text-align: center;
+    }
+
+    .markdown span.align-right {
+      clear: both;
+      display: block;
+      overflow: hidden;
+    }
+
+    .markdown span.align-right > span {
+      display: block;
+      margin: 13px auto;
+      overflow: hidden;
+      text-align: right;
+    }
+
+    .markdown span.align-right img {
+      margin: 0;
+      text-align: right;
+    }
+
+    .markdown span.float-left {
+      display: block;
+      float: left;
+      margin-right: 13px;
+      overflow: hidden;
+    }
+
+    .markdown span.float-left > span {
+      margin: 13px auto;
+    }
+
+    .markdown span.float-right {
+      display: block;
+      float: right;
+      margin-left: 13px;
+      overflow: hidden;
+    }
+
+    .markdown span.float-right > span {
+      display: block;
+      margin: 13px auto;
+      overflow: hidden;
+      text-align: right;
+    }
+
+    .markdown code,
+    .markdown tt {
+      border: 1px solid #eaeaea;
+      border-radius: 3px;
+      margin: 0 2px;
+      padding: 0 5px;
+    }
+    .markdown pre > code {
+      background-color: transparent;
+      border: none;
+      margin: 0;
+      padding: 0;
+      white-space: pre;
+    }
+    .markdown .highlight pre,
+    .markdown pre {
+      border: 1px solid #ccc;
+      border-radius: 3px;
+      font-size: max(0.9em, 14px);
+      line-height: 19px;
+      overflow: auto;
+      padding: 6px 10px;
+    }
+
+    .markdown pre code,
+    .markdown pre tt {
+      background-color: #f8f8f8;
+      border: none;
+    }
+
+    .markdown {
+      text-align: justify;
+      overflow-y: hidden;
+      tab-size: 4;
+      word-spacing: normal;
+      word-break: break-all;
+    }
+    .markdown pre {
+      display: block;
+      width: 100%;
+      padding: 15px;
+      margin: 0;
+      border: none;
+      border-radius: none;
+      background-color: #222 !important;
+      overflow-x: auto;
+      color: #fff;
+    }
+    .markdown pre code {
+      background-color: #222 !important;
+      width: 100%;
+    }
+    .markdown a {
+      text-decoration: underline;
+      color: var(--chakra-colors-blue-600);
+    }
+    .markdown table {
+      border-collapse: separate;
+      border-spacing: 0;
+      color: #718096;
+    }
+    .markdown table thead tr:first-child th {
+      border-bottom-width: 1px;
+      border-left-width: 1px;
+      border-top-width: 1px;
+      border-color: #ccc;
+      background-color: #edf2f7;
+      overflow: hidden;
+    }
+    .markdown table thead tr:first-child th:first-child {
+      border-top-left-radius: 0.375rem;
+    }
+    .markdown table thead tr:first-child th:last-child {
+      border-right-width: 1px;
+      border-top-right-radius: 0.375rem;
+    }
+    .markdown td {
+      border-bottom-width: 1px;
+      border-left-width: 1px;
+      border-color: #ccc;
+    }
+    .markdown td:last-of-type {
+      border-right-width: 1px;
+    }
+    .markdown tbody tr:last-child {
+      overflow: hidden;
+    }
+    .markdown tbody tr:last-child td:first-child {
+      border-bottom-left-radius: 0.375rem;
+    }
+    .markdown tbody tr:last-child td:last-child {
+      border-bottom-right-radius: 0.375rem;
+    }
+    .markdown p {
+      text-align: justify;
+      white-space: pre-wrap;
+    }
+    code[class*='language-'] {
+      color: #d4d4d4;
+      text-shadow: none;
+      direction: ltr;
+      text-align: left;
+      white-space: pre;
+      word-spacing: normal;
+      word-break: normal;
+      line-height: 1.5;
+      -moz-tab-size: 4;
+      -o-tab-size: 4;
+      tab-size: 4;
+      -webkit-hyphens: none;
+      -moz-hyphens: none;
+      hyphens: none;
+    }
+
+    pre[class*='language-'] {
+      color: #d4d4d4;
+      text-shadow: none;
+      direction: ltr;
+      text-align: left;
+      white-space: pre;
+      word-spacing: normal;
+      word-break: normal;
+      line-height: 1.5;
+      -moz-tab-size: 4;
+      -o-tab-size: 4;
+      tab-size: 4;
+      -webkit-hyphens: none;
+      -moz-hyphens: none;
+      hyphens: none;
+      padding: 1em;
+      margin: 0.5em0;
+      overflow: auto;
+      background: #1e1e1e;
+    }
+
+    code[class*='language-'] ::selection,
+    code[class*='language-']::selection,
+    pre[class*='language-'] ::selection,
+    pre[class*='language-']::selection {
+      text-shadow: none;
+      background: #264f78;
+    }
+
+    :not(pre) > code[class*='language-'] {
+      padding: 0.1em 0.3em;
+      border-radius: 0.3em;
+      color: #db4c69;
+      background: #1e1e1e;
+    }
+
+    .namespace {
+      opacity: 0.7;
+    }
+
+    .doctype.doctype-tag {
+      color: #569cd6;
+    }
+
+    .doctype.name {
+      color: #9cdcfe;
+    }
+
+    comment {
+      color: #6a9955;
+    }
+
+    prolog {
+      color: #6a9955;
+    }
+
+    .language-html .language-css .token.punctuation,
+    .language-html .language-javascript .token.punctuation {
+      color: #d4d4d4;
+    }
+
+    punctuation {
+      color: #d4d4d4;
+    }
+
+    boolean {
+      color: #569cd6;
+    }
+
+    constant {
+      color: #9cdcfe;
+    }
+
+    inserted {
+      color: #b5cea8;
+    }
+
+    number {
+      color: #b5cea8;
+    }
+
+    property {
+      color: #9cdcfe;
+    }
+
+    symbol {
+      color: #b5cea8;
+    }
+
+    tag {
+      color: #569cd6;
+    }
+
+    unit {
+      color: #b5cea8;
+    }
+
+    attr-name {
+      color: #9cdcfe;
+    }
+
+    builtin {
+      color: #ce9178;
+    }
+
+    char {
+      color: #ce9178;
+    }
+
+    deleted {
+      color: #ce9178;
+    }
+
+    selector {
+      color: #d7ba7d;
+    }
+
+    string {
+      color: #ce9178;
+    }
+
+    .language-css .token.string.url {
+      text-decoration: underline;
+    }
+
+    entity {
+      color: #569cd6;
+    }
+
+    operator {
+      color: #d4d4d4;
+    }
+
+    operator.arrow {
+      color: #569cd6;
+    }
+
+    atrule {
+      color: #ce9178;
+    }
+
+    atrule.rule {
+      color: #c586c0;
+    }
+
+    atrule.url {
+      color: #9cdcfe;
+    }
+
+    atrule.url.function {
+      color: #dcdcaa;
+    }
+
+    atrule.url.punctuation {
+      color: #d4d4d4;
+    }
+    keyword {
+      color: #569cd6;
+    }
+
+    keyword.control-flow {
+      color: #c586c0;
+    }
+
+    keyword.module {
+      color: #c586c0;
+    }
+
+    function {
+      color: #dcdcaa;
+    }
+
+    function.maybe-class-name {
+      color: #dcdcaa;
+    }
+
+    regex {
+      color: #d16969;
+    }
+
+    important {
+      color: #569cd6;
+    }
+
+    italic {
+      font-style: italic;
+    }
+
+    class-name {
+      color: #4ec9b0;
+    }
+
+    maybe-class-name {
+      color: #4ec9b0;
+    }
+
+    console {
+      color: #9cdcfe;
+    }
+
+    parameter {
+      color: #9cdcfe;
+    }
+
+    interpolation {
+      color: #9cdcfe;
+    }
+    punctuation.interpolation-punctuation {
+      color: #569cd6;
+    }
+    exports.maybe-class-name {
+      color: #9cdcfe;
+    }
+    imports.maybe-class-name {
+      color: #9cdcfe;
+    }
+    variable {
+      color: #9cdcfe;
+    }
+    escape {
+      color: #d7ba7d;
+    }
+    tag.punctuation {
+      color: grey;
+    }
+    cdata {
+      color: grey;
+    }
+    attr-value {
+      color: #ce9178;
+    }
+    attr-value.punctuation {
+      color: #ce9178;
+    }
+    attr-value.punctuation.attr-equals {
+      color: #d4d4d4;
+    }
+    namespace {
+      color: #4ec9b0;
+    }
+    code[class*='language-javascript'],
+    code[class*='language-jsx'],
+    code[class*='language-tsx'],
+    code[class*='language-typescript'] {
+      color: #9cdcfe;
+    }
+
+    pre[class*='language-javascript'],
+    pre[class*='language-jsx'],
+    pre[class*='language-tsx'],
+    pre[class*='language-typescript'] {
+      color: #9cdcfe;
+    }
+
+    code[class*='language-css'] {
+      color: #ce9178;
+    }
+
+    pre[class*='language-css'] {
+      color: #ce9178;
+    }
+
+    code[class*='language-html'] {
+      color: #d4d4d4;
+    }
+
+    pre[class*='language-html'] {
+      color: #d4d4d4;
+    }
+
+    .language-regex .token.anchor {
+      color: #dcdcaa;
+    }
+
+    .language-html .token.punctuation {
+      color: grey;
+    }
+
+    pre[class*='language-'] > code[class*='language-'] {
+      position: relative;
+      z-index: 1;
+    }
+
+    .line-highlight.line-highlight {
+      background: #f7ebc6;
+      box-shadow: inset 5px 0 0 #f7d87c;
+      z-index: 0;
+    }
+    * {
+      box-sizing: border-box;
+    }
+    body,
+    h1,
+    h2,
+    h3,
+    h4,
+    hr,
+    p,
+    blockquote,
+    dl,
+    dt,
+    dd,
+    ul,
+    ol,
+    li,
+    pre,
+    form,
+    fieldset,
+    legend,
+    button,
+    input,
+    textarea,
+    th,
+    td,
+    svg  {
+      margin: 0;
+    }
+    body,
+    html {
+      font-size: 16px;
+      background-color: #fff;
+      color: rgba(0, 0, 0, 0.64);
+      font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, Arial, sans-serif,
+        'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol';
+    }
+    pre,
+    code,
+    kbd,
+    samp {
+      font-family: SFMono-Regular, Menlo, Monaco, Consolas, monospace;
+      font-size: 1em;
+    }
+    ::-webkit-scrollbar,
+    ::-webkit-scrollbar {
+      width: 10px;
+      height: 10px;
+    }
+    ::-webkit-scrollbar-track,
+    ::-webkit-scrollbar-track {
+      background: transparent;
+      border-radius: 2px;
+    }
+    ::-webkit-scrollbar-thumb,
+    ::-webkit-scrollbar-thumb {
+      background: #bfbfbf;
+      border-radius: 10px;
+    }
+    ::-webkit-scrollbar-thumb:hover,
+    ::-webkit-scrollbar-thumb:hover {
+      background: #999;
+    }
+  </style>
+  <style>
+    .chat-item {
+      display: flex;
+      align-items: flex-start;
+      padding: 20px 16px;
+      border-bottom: 1px solid rgba(0, 0, 0, 0.1);
+      justify-content: center;
+    }
+    .chat-item img {
+      width: 30px;
+      max-height: 50px;
+      object-fit: contain;
+      margin-right: 10px;
+    }
+    .chat-item:nth-child(even) {
+      background-color: #f6f6f6;
+    }
+    .chat-item:nth-child(odd) {
+      background-color: #ffffff;
+    }
+    .markdown {
+      overflow-x: hidden;
+      max-width: 800px;
+      width: 100%;
+    }
+    @media (max-width: 900px) {
+      html {
+        font-size: 14px;
+      }
+      ::-webkit-scrollbar,
+      ::-webkit-scrollbar {
+        width: 2px;
+        height: 2px;
+      }
+      .chat-item img {
+        width: 20px;
+        max-height: 40px;
+        margin-right: 4px;
+      }
+    }
+  </style>
+  <body>{{CHAT_CONTENT}}</body>
+</html>
+`;

src/constants/model.ts

@@ -1,51 +1,66 @@
 import type { ModelSchema } from '@/types/mongoSchema';
 
 export const embeddingModel = 'text-embedding-ada-002';
-export enum ChatModelEnum {
+export type EmbeddingModelType = 'text-embedding-ada-002';
+
+export enum OpenAiChatEnum {
   'GPT35' = 'gpt-3.5-turbo',
   'GPT4' = 'gpt-4',
   'GPT432k' = 'gpt-4-32k'
 }
-
-export enum ModelNameEnum {
-  GPT35 = 'gpt-3.5-turbo',
-  VECTOR_GPT = 'VECTOR_GPT'
+export enum ClaudeEnum {
+  'Claude' = 'Claude'
 }
 
-export const Model2ChatModelMap: Record<`${ModelNameEnum}`, `${ChatModelEnum}`> = {
-  [ModelNameEnum.GPT35]: 'gpt-3.5-turbo',
-  [ModelNameEnum.VECTOR_GPT]: 'gpt-3.5-turbo'
-};
+export type ChatModelType = `${OpenAiChatEnum}` | `${ClaudeEnum}`;
 
-export type ModelConstantsData = {
-  icon: 'model' | 'dbModel';
+export type ChatModelItemType = {
+  chatModel: ChatModelType;
   name: string;
-  model: `${ModelNameEnum}`;
-  trainName: string; // 空字符串代表不能训练
   contextMaxToken: number;
+  systemMaxToken: number;
   maxTemperature: number;
-  price: number; // 多少钱 / 1token，单位: 0.00001元
+  price: number;
 };
 
-export const modelList: ModelConstantsData[] = [
-  {
-    icon: 'model',
-    name: 'chatGPT',
-    model: ModelNameEnum.GPT35,
-    trainName: '',
+export const ChatModelMap = {
+  [OpenAiChatEnum.GPT35]: {
+    chatModel: OpenAiChatEnum.GPT35,
+    name: 'ChatGpt',
     contextMaxToken: 4096,
+    systemMaxToken: 3000,
     maxTemperature: 1.5,
     price: 3
   },
-  {
-    icon: 'dbModel',
-    name: '知识库',
-    model: ModelNameEnum.VECTOR_GPT,
-    trainName: 'vector',
-    contextMaxToken: 4096,
+  [OpenAiChatEnum.GPT4]: {
+    chatModel: OpenAiChatEnum.GPT4,
+    name: 'Gpt4',
+    contextMaxToken: 8000,
+    systemMaxToken: 4000,
+    maxTemperature: 1.5,
+    price: 30
+  },
+  [OpenAiChatEnum.GPT432k]: {
+    chatModel: OpenAiChatEnum.GPT432k,
+    name: 'Gpt4-32k',
+    contextMaxToken: 32000,
+    systemMaxToken: 4000,
+    maxTemperature: 1.5,
+    price: 30
+  },
+  [ClaudeEnum.Claude]: {
+    chatModel: ClaudeEnum.Claude,
+    name: 'Claude(免费体验)',
+    contextMaxToken: 9000,
+    systemMaxToken: 2500,
     maxTemperature: 1,
-    price: 3
+    price: 0
   }
+};
+
+export const chatModelList: ChatModelItemType[] = [
+  ChatModelMap[OpenAiChatEnum.GPT35],
+  ChatModelMap[ClaudeEnum.Claude]
 ];
 
 export enum ModelStatusEnum {
@@ -115,14 +130,16 @@ export const ModelVectorSearchModeMap: Record<
 export const defaultModel: ModelSchema = {
   _id: 'modelId',
   userId: 'userId',
-  name: 'modelName',
+  name: '模型名称',
   avatar: '/icon/logo.png',
   status: ModelStatusEnum.pending,
   updateTime: Date.now(),
-  systemPrompt: '',
-  temperature: 5,
-  search: {
-    mode: ModelVectorSearchModeEnum.hightSimilarity
+  chat: {
+    useKb: false,
+    searchMode: ModelVectorSearchModeEnum.hightSimilarity,
+    systemPrompt: '',
+    temperature: 0,
+    chatModel: OpenAiChatEnum.GPT35
   },
   share: {
     isShare: false,
@@ -130,10 +147,6 @@ export const defaultModel: ModelSchema = {
     intro: '',
     collection: 0
   },
-  service: {
-    chatModel: ModelNameEnum.GPT35,
-    modelName: ModelNameEnum.GPT35
-  },
   security: {
     domain: ['*'],
     contextMaxLen: 1,

src/pages/_app.tsx

@@ -51,8 +51,9 @@ export default function App({ Component, pageProps }: AppProps) {
         />
         <link rel="icon" href="/favicon.ico" />
       </Head>
-      <Script src="/js/qrcode.min.js" strategy="afterInteractive"></Script>
-      <Script src="/js/pdf.js" strategy="afterInteractive"></Script>
+      <Script src="/js/qrcode.min.js" strategy="lazyOnload"></Script>
+      <Script src="/js/pdf.js" strategy="lazyOnload"></Script>
+      <Script src="/js/html2pdf.bundle.min.js" strategy="lazyOnload"></Script>
       <QueryClientProvider client={queryClient}>
         <ChakraProvider theme={theme}>
           <ColorModeScript initialColorMode={theme.config.initialColorMode} />

src/pages/api/chat/chat.ts

@@ -0,0 +1,133 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { connectToDatabase } from '@/service/mongo';
+import { authChat } from '@/service/utils/auth';
+import { modelServiceToolMap } from '@/service/utils/chat';
+import { ChatItemSimpleType } from '@/types/chat';
+import { jsonRes } from '@/service/response';
+import { PassThrough } from 'stream';
+import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
+import { pushChatBill } from '@/service/events/pushBill';
+import { resStreamResponse } from '@/service/utils/chat';
+import { searchKb } from '@/service/plugins/searchKb';
+import { ChatRoleEnum } from '@/constants/chat';
+
+/* 发送提示词 */
+export default async function handler(req: NextApiRequest, res: NextApiResponse) {
+  let step = 0; // step=1时，表示开始了流响应
+  const stream = new PassThrough();
+  stream.on('error', () => {
+    console.log('error: ', 'stream error');
+    stream.destroy();
+  });
+  res.on('close', () => {
+    stream.destroy();
+  });
+  res.on('error', () => {
+    console.log('error: ', 'request error');
+    stream.destroy();
+  });
+
+  try {
+    const { chatId, prompt, modelId } = req.body as {
+      prompt: ChatItemSimpleType;
+      modelId: string;
+      chatId: '' | string;
+    };
+
+    const { authorization } = req.headers;
+    if (!modelId || !prompt) {
+      throw new Error('缺少参数');
+    }
+
+    await connectToDatabase();
+    let startTime = Date.now();
+
+    const { model, showModelDetail, content, userOpenAiKey, systemAuthKey, userId } =
+      await authChat({
+        modelId,
+        chatId,
+        authorization
+      });
+
+    const modelConstantsData = ChatModelMap[model.chat.chatModel];
+
+    // 读取对话内容
+    const prompts = [...content, prompt];
+
+    // 使用了知识库搜索
+    if (model.chat.useKb) {
+      const { code, searchPrompt } = await searchKb({
+        userOpenAiKey,
+        prompts,
+        similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
+        model,
+        userId
+      });
+
+      // search result is empty
+      if (code === 201) {
+        return res.send(searchPrompt?.value);
+      }
+
+      searchPrompt && prompts.unshift(searchPrompt);
+    } else {
+      // 没有用知识库搜索，仅用系统提示词
+      model.chat.systemPrompt &&
+        prompts.unshift({
+          obj: ChatRoleEnum.System,
+          value: model.chat.systemPrompt
+        });
+    }
+
+    // 计算温度
+    const temperature = (modelConstantsData.maxTemperature * (model.chat.temperature / 10)).toFixed(
+      2
+    );
+
+    // 发出请求
+    const { streamResponse } = await modelServiceToolMap[model.chat.chatModel].chatCompletion({
+      apiKey: userOpenAiKey || systemAuthKey,
+      temperature: +temperature,
+      messages: prompts,
+      stream: true,
+      res,
+      chatId
+    });
+
+    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
+
+    step = 1;
+
+    const { totalTokens, finishMessages } = await resStreamResponse({
+      model: model.chat.chatModel,
+      res,
+      stream,
+      chatResponse: streamResponse,
+      prompts,
+      systemPrompt:
+        showModelDetail && prompts[0].obj === ChatRoleEnum.System ? prompts[0].value : ''
+    });
+
+    // 只有使用平台的 key 才计费
+    pushChatBill({
+      isPay: !userOpenAiKey,
+      chatModel: model.chat.chatModel,
+      userId,
+      chatId,
+      textLen: finishMessages.map((item) => item.value).join('').length,
+      tokens: totalTokens
+    });
+  } catch (err: any) {
+    if (step === 1) {
+      // 直接结束流
+      console.log('error，结束');
+      stream.destroy();
+    } else {
+      res.status(500);
+      jsonRes(res, {
+        code: 500,
+        error: err
+      });
+    }
+  }
+}

src/pages/api/chat/chatGpt.ts

@@ -1,126 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { connectToDatabase } from '@/service/mongo';
-import { getOpenAIApi, authChat } from '@/service/utils/auth';
-import { axiosConfig, openaiChatFilter } from '@/service/utils/tools';
-import { ChatItemType } from '@/types/chat';
-import { jsonRes } from '@/service/response';
-import { PassThrough } from 'stream';
-import { modelList } from '@/constants/model';
-import { pushChatBill } from '@/service/events/pushBill';
-import { gpt35StreamResponse } from '@/service/utils/openai';
-
-/* 发送提示词 */
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  let step = 0; // step=1时，表示开始了流响应
-  const stream = new PassThrough();
-  stream.on('error', () => {
-    console.log('error: ', 'stream error');
-    stream.destroy();
-  });
-  res.on('close', () => {
-    stream.destroy();
-  });
-  res.on('error', () => {
-    console.log('error: ', 'request error');
-    stream.destroy();
-  });
-
-  try {
-    const { chatId, prompt, modelId } = req.body as {
-      prompt: ChatItemType;
-      modelId: string;
-      chatId: '' | string;
-    };
-
-    const { authorization } = req.headers;
-    if (!modelId || !prompt) {
-      throw new Error('缺少参数');
-    }
-
-    await connectToDatabase();
-    let startTime = Date.now();
-
-    const { model, content, userApiKey, systemKey, userId } = await authChat({
-      modelId,
-      chatId,
-      authorization
-    });
-
-    const modelConstantsData = modelList.find((item) => item.model === model.service.modelName);
-    if (!modelConstantsData) {
-      throw new Error('模型加载异常');
-    }
-
-    // 读取对话内容
-    const prompts = [...content, prompt];
-
-    // 如果有系统提示词，自动插入
-    if (model.systemPrompt) {
-      prompts.unshift({
-        obj: 'SYSTEM',
-        value: model.systemPrompt
-      });
-    }
-
-    // 控制在 tokens 数量，防止超出
-    const filterPrompts = openaiChatFilter({
-      model: model.service.chatModel,
-      prompts,
-      maxTokens: modelConstantsData.contextMaxToken - 500
-    });
-
-    // 计算温度
-    const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
-    // console.log(filterPrompts);
-    // 获取 chatAPI
-    const chatAPI = getOpenAIApi(userApiKey || systemKey);
-    // 发出请求
-    const chatResponse = await chatAPI.createChatCompletion(
-      {
-        model: model.service.chatModel,
-        temperature,
-        messages: filterPrompts,
-        frequency_penalty: 0.5, // 越大，重复内容越少
-        presence_penalty: -0.5, // 越大，越容易出现新内容
-        stream: true,
-        stop: ['.!?。']
-      },
-      {
-        timeout: 40000,
-        responseType: 'stream',
-        ...axiosConfig
-      }
-    );
-
-    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
-
-    step = 1;
-
-    const { responseContent } = await gpt35StreamResponse({
-      res,
-      stream,
-      chatResponse
-    });
-
-    // 只有使用平台的 key 才计费
-    pushChatBill({
-      isPay: !userApiKey,
-      modelName: model.service.modelName,
-      userId,
-      chatId,
-      messages: filterPrompts.concat({ role: 'assistant', content: responseContent })
-    });
-  } catch (err: any) {
-    if (step === 1) {
-      // 直接结束流
-      console.log('error，结束');
-      stream.destroy();
-    } else {
-      res.status(500);
-      jsonRes(res, {
-        code: 500,
-        error: err
-      });
-    }
-  }
-}

src/pages/api/chat/delChatRecordByContentId.ts

@@ -1,17 +1,17 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, Chat } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {
-    const { chatId, index } = req.query as { chatId: string; index: string };
+    const { chatId, contentId } = req.query as { chatId: string; contentId: string };
     const { authorization } = req.headers;
 
     if (!authorization) {
       throw new Error('无权操作');
     }
-    if (!chatId || !index) {
+    if (!chatId || !contentId) {
       throw new Error('缺少参数');
     }
 
@@ -26,30 +26,13 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       throw new Error('找不到对话');
     }
 
-    // 重新计算 index，跳过已经被删除的内容
-    let unDeleteIndex = +index;
-    let deletedIndex = 0;
-    for (deletedIndex = 0; deletedIndex < chatRecord.content.length; deletedIndex++) {
-      if (!chatRecord.content[deletedIndex].deleted) {
-        unDeleteIndex--;
-        if (unDeleteIndex < 0) {
-          break;
-        }
-      }
-    }
-
-    // 删除最一条数据库记录, 也就是预发送的那一条
+    // 删除一条数据库记录
     await Chat.updateOne(
       {
         _id: chatId,
         userId
       },
-      {
-        $set: {
-          [`content.${deletedIndex}.deleted`]: true,
-          updateTime: Date.now()
-        }
-      }
+      { $pull: { content: { _id: contentId } } }
     );
 
     jsonRes(res);

src/pages/api/chat/getHistory.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, Chat } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 
 /* 获取历史记录 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {

src/pages/api/chat/init.ts

@@ -2,7 +2,7 @@ import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, Chat } from '@/service/mongo';
 import type { InitChatResponse } from '@/api/response/chat';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { ChatItemType } from '@/types/chat';
 import { authModel } from '@/service/utils/auth';
 import mongoose from 'mongoose';
@@ -36,20 +36,23 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
             userId: new mongoose.Types.ObjectId(userId)
           }
         },
-        { $unwind: '$content' },
-        { $match: { 'content.deleted': false } },
-        { $sort: { 'content._id': -1 } },
-        { $limit: 50 },
         {
           $project: {
-            id: '$content._id',
+            content: {
+              $slice: ['$content', -50] // 返回 content 数组的最后50个元素
+            }
+          }
+        },
+        { $unwind: '$content' },
+        {
+          $project: {
+            _id: '$content._id',
             obj: '$content.obj',
-            value: '$content.value'
+            value: '$content.value',
+            systemPrompt: '$content.systemPrompt'
           }
         }
       ]);
-
-      history.reverse();
     }
 
     jsonRes<InitChatResponse>(res, {
@@ -59,8 +62,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
         name: model.name,
         avatar: model.avatar,
         intro: model.share.intro,
-        modelName: model.service.modelName,
-        chatModel: model.service.chatModel,
+        chatModel: model.chat.chatModel,
         history
       }
     });

src/pages/api/chat/removeHistory.ts

@@ -2,7 +2,7 @@ import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { ChatItemType } from '@/types/chat';
 import { connectToDatabase, Chat } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 
 /* 获取历史记录 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {

src/pages/api/chat/saveChat.ts

@@ -3,12 +3,14 @@ import { jsonRes } from '@/service/response';
 import { ChatItemType } from '@/types/chat';
 import { connectToDatabase, Chat } from '@/service/mongo';
 import { authModel } from '@/service/utils/auth';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
+import mongoose from 'mongoose';
 
 /* 聊天内容存存储 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {
-    const { chatId, modelId, prompts } = req.body as {
+    const { chatId, modelId, prompts, newChatId } = req.body as {
+      newChatId: '' | string;
       chatId: '' | string;
       modelId: string;
       prompts: ChatItemType[];
@@ -23,8 +25,10 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     await connectToDatabase();
 
     const content = prompts.map((item) => ({
+      _id: new mongoose.Types.ObjectId(item._id),
       obj: item.obj,
-      value: item.value
+      value: item.value,
+      systemPrompt: item.systemPrompt
     }));
 
     await authModel({ modelId, userId, authOwner: false });
@@ -32,6 +36,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     // 没有 chatId, 创建一个对话
     if (!chatId) {
       const { _id } = await Chat.create({
+        _id: newChatId ? new mongoose.Types.ObjectId(newChatId) : undefined,
         userId,
         modelId,
         content,

src/pages/api/chat/vectorGpt.ts

@@ -1,189 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { connectToDatabase } from '@/service/mongo';
-import { authChat } from '@/service/utils/auth';
-import { axiosConfig, systemPromptFilter, openaiChatFilter } from '@/service/utils/tools';
-import { ChatItemType } from '@/types/chat';
-import { jsonRes } from '@/service/response';
-import { PassThrough } from 'stream';
-import {
-  modelList,
-  ModelVectorSearchModeMap,
-  ModelVectorSearchModeEnum,
-  ModelDataStatusEnum
-} from '@/constants/model';
-import { pushChatBill } from '@/service/events/pushBill';
-import { openaiCreateEmbedding, gpt35StreamResponse } from '@/service/utils/openai';
-import dayjs from 'dayjs';
-import { PgClient } from '@/service/pg';
-
-/* 发送提示词 */
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  let step = 0; // step=1时，表示开始了流响应
-  const stream = new PassThrough();
-  stream.on('error', () => {
-    console.log('error: ', 'stream error');
-    stream.destroy();
-  });
-  res.on('close', () => {
-    stream.destroy();
-  });
-  res.on('error', () => {
-    console.log('error: ', 'request error');
-    stream.destroy();
-  });
-
-  try {
-    const { modelId, chatId, prompt } = req.body as {
-      modelId: string;
-      chatId: '' | string;
-      prompt: ChatItemType;
-    };
-
-    const { authorization } = req.headers;
-    if (!modelId || !prompt) {
-      throw new Error('缺少参数');
-    }
-
-    await connectToDatabase();
-    let startTime = Date.now();
-
-    const { model, content, userApiKey, systemKey, userId } = await authChat({
-      modelId,
-      chatId,
-      authorization
-    });
-
-    const modelConstantsData = modelList.find((item) => item.model === model.service.modelName);
-    if (!modelConstantsData) {
-      throw new Error('模型加载异常');
-    }
-
-    // 读取对话内容
-    const prompts = [...content, prompt];
-
-    // 获取提示词的向量
-    const { vector: promptVector, chatAPI } = await openaiCreateEmbedding({
-      isPay: !userApiKey,
-      apiKey: userApiKey || systemKey,
-      userId,
-      text: prompt.value
-    });
-
-    // 相似度搜素
-    const similarity = ModelVectorSearchModeMap[model.search.mode]?.similarity || 0.22;
-    const vectorSearch = await PgClient.select<{ id: string; q: string; a: string }>('modelData', {
-      fields: ['id', 'q', 'a'],
-      where: [
-        ['status', ModelDataStatusEnum.ready],
-        'AND',
-        ['model_id', model._id],
-        'AND',
-        `vector <=> '[${promptVector}]' < ${similarity}`
-      ],
-      order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
-      limit: 20
-    });
-
-    const formatRedisPrompt: string[] = vectorSearch.rows.map((item) => `${item.q}\n${item.a}`);
-
-    /* 高相似度+退出，无法匹配时直接退出 */
-    if (
-      formatRedisPrompt.length === 0 &&
-      model.search.mode === ModelVectorSearchModeEnum.hightSimilarity
-    ) {
-      return res.send('对不起，你的问题不在知识库中。');
-    }
-    /* 高相似度+无上下文，不添加额外知识 */
-    if (
-      formatRedisPrompt.length === 0 &&
-      model.search.mode === ModelVectorSearchModeEnum.noContext
-    ) {
-      prompts.unshift({
-        obj: 'SYSTEM',
-        value: model.systemPrompt
-      });
-    } else {
-      // 有匹配情况下，system 添加知识库内容。
-      // 系统提示词过滤，最多 2500 tokens
-      const systemPrompt = systemPromptFilter({
-        model: model.service.chatModel,
-        prompts: formatRedisPrompt,
-        maxTokens: 2500
-      });
-
-      prompts.unshift({
-        obj: 'SYSTEM',
-        value: `
-${model.systemPrompt}
-${
-  model.search.mode === ModelVectorSearchModeEnum.hightSimilarity
-    ? `你只能从知识库选择内容回答.不在知识库内容拒绝回复`
-    : ''
-}
-知识库内容为: 当前时间为${dayjs().format('YYYY/MM/DD HH:mm:ss')}\n${systemPrompt}'
-`
-      });
-    }
-
-    // 控制在 tokens 数量，防止超出
-    const filterPrompts = openaiChatFilter({
-      model: model.service.chatModel,
-      prompts,
-      maxTokens: modelConstantsData.contextMaxToken - 500
-    });
-
-    // console.log(filterPrompts);
-    // 计算温度
-    const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
-
-    // 发出请求
-    const chatResponse = await chatAPI.createChatCompletion(
-      {
-        model: model.service.chatModel,
-        temperature,
-        messages: filterPrompts,
-        frequency_penalty: 0.5, // 越大，重复内容越少
-        presence_penalty: -0.5, // 越大，越容易出现新内容
-        stream: true,
-        stop: ['.!?。']
-      },
-      {
-        timeout: 40000,
-        responseType: 'stream',
-        ...axiosConfig
-      }
-    );
-
-    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
-
-    step = 1;
-
-    const { responseContent } = await gpt35StreamResponse({
-      res,
-      stream,
-      chatResponse
-    });
-
-    // 只有使用平台的 key 才计费
-    pushChatBill({
-      isPay: !userApiKey,
-      modelName: model.service.modelName,
-      userId,
-      chatId,
-      messages: filterPrompts.concat({ role: 'assistant', content: responseContent })
-    });
-    // jsonRes(res);
-  } catch (err: any) {
-    if (step === 1) {
-      // 直接结束流
-      console.log('error，结束');
-      stream.destroy();
-    } else {
-      res.status(500);
-      jsonRes(res, {
-        code: 500,
-        error: err
-      });
-    }
-  }
-}

src/pages/api/model/create.ts

@@ -2,15 +2,14 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
-import { ModelStatusEnum, modelList, ModelNameEnum, Model2ChatModelMap } from '@/constants/model';
+import { authToken } from '@/service/utils/auth';
+import { ModelStatusEnum } from '@/constants/model';
 import { Model } from '@/service/models/model';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
-    const { name, serviceModelName } = req.body as {
+    const { name } = req.body as {
       name: string;
-      serviceModelName: `${ModelNameEnum}`;
     };
     const { authorization } = req.headers;
 
@@ -18,45 +17,32 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
       throw new Error('无权操作');
     }
 
-    if (!name || !serviceModelName) {
+    if (!name) {
       throw new Error('缺少参数');
     }
 
     // 凭证校验
     const userId = await authToken(authorization);
 
-    const modelItem = modelList.find((item) => item.model === serviceModelName);
-
-    if (!modelItem) {
-      throw new Error('模型不存在');
-    }
-
     await connectToDatabase();
 
     // 上限校验
     const authCount = await Model.countDocuments({
       userId
     });
-    if (authCount >= 20) {
-      throw new Error('上限 20 个模型');
+    if (authCount >= 30) {
+      throw new Error('上限 30 个模型');
     }
 
     // 创建模型
     const response = await Model.create({
       name,
       userId,
-      status: ModelStatusEnum.running,
-      service: {
-        chatModel: Model2ChatModelMap[modelItem.model], // 聊天时用的模型
-        modelName: modelItem.model // 最底层的模型，不会变，用于计费等核心操作
-      }
+      status: ModelStatusEnum.running
     });
 
-    // 根据 id 获取模型信息
-    const model = await Model.findById(response._id);
-
     jsonRes(res, {
-      data: model
+      data: response._id
     });
   } catch (err) {
     jsonRes(res, {

src/pages/api/model/data/delModelDataById.ts

@@ -1,6 +1,6 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { PgClient } from '@/service/pg';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {

src/pages/api/model/data/exportModelData.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { PgClient } from '@/service/pg';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {

src/pages/api/model/data/fetchingUrlData.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import axios from 'axios';
 import { axiosConfig } from '@/service/utils/tools';
 
@@ -22,7 +22,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
 
     const data = await axios
       .get(url, {
-        httpsAgent: axiosConfig.httpsAgent
+        httpsAgent: axiosConfig().httpsAgent
       })
       .then((res) => res.data as string);
 

src/pages/api/model/data/getModelData.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { PgClient } from '@/service/pg';
 import type { PgModelDataItemType } from '@/types/pg';
 import { authModel } from '@/service/utils/auth';

src/pages/api/model/data/getSplitData.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, SplitData, Model } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 
 /* 拆分数据成QA */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {

src/pages/api/model/data/pushModelDataCsv.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { generateVector } from '@/service/events/generateVector';
 import { ModelDataStatusEnum } from '@/constants/model';
 import { PgClient } from '@/service/pg';

src/pages/api/model/data/pushModelDataInput.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { ModelDataSchema } from '@/types/mongoSchema';
 import { generateVector } from '@/service/events/generateVector';
 import { PgClient } from '@/service/pg';

src/pages/api/model/data/putModelData.ts

@@ -1,6 +1,6 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { ModelDataStatusEnum } from '@/constants/model';
 import { generateVector } from '@/service/events/generateVector';
 import { PgClient } from '@/service/pg';

src/pages/api/model/data/splitData.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, SplitData, Model } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { generateVector } from '@/service/events/generateVector';
 import { generateQA } from '@/service/events/generateQA';
 import { PgClient } from '@/service/pg';

src/pages/api/model/del.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { Chat, Model, connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { PgClient } from '@/service/pg';
 import { authModel } from '@/service/utils/auth';
 

src/pages/api/model/detail.tsx

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { authModel } from '@/service/utils/auth';
 
 /* 获取我的模型 */

src/pages/api/model/list.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { Model } from '@/service/models/model';
 
 /* 获取模型列表 */

src/pages/api/model/share/collection.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, Collection, Model } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 
 /* 模型收藏切换 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {

src/pages/api/model/share/getCollection.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, Collection } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import type { ShareModelItem } from '@/types/model';
 
 /* 获取模型列表 */

src/pages/api/model/share/getModels.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, Collection, Model } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import type { PagingData } from '@/types';
 import type { ShareModelItem } from '@/types/model';
 

src/pages/api/model/update.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { Model } from '@/service/models/model';
 import type { ModelUpdateParams } from '@/types/model';
 import { authModel } from '@/service/utils/auth';
@@ -9,8 +9,7 @@ import { authModel } from '@/service/utils/auth';
 /* 获取我的模型 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
   try {
-    const { name, avatar, search, share, service, security, systemPrompt, temperature } =
-      req.body as ModelUpdateParams;
+    const { name, avatar, chat, share, security } = req.body as ModelUpdateParams;
     const { modelId } = req.query as { modelId: string };
     const { authorization } = req.headers;
 
@@ -18,7 +17,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
       throw new Error('无权操作');
     }
 
-    if (!name || !service || !security || !modelId) {
+    if (!name || !chat || !security || !modelId) {
       throw new Error('参数错误');
     }
 
@@ -41,12 +40,10 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse<
       {
         name,
         avatar,
-        systemPrompt,
-        temperature,
+        chat,
         'share.isShare': share.isShare,
         'share.isShareDetail': share.isShareDetail,
         'share.intro': share.intro,
-        search,
         security
       }
     );

src/pages/api/openapi/chat/chat.ts

@@ -0,0 +1,147 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { connectToDatabase } from '@/service/mongo';
+import { authOpenApiKey, authModel } from '@/service/utils/auth';
+import { modelServiceToolMap, resStreamResponse } from '@/service/utils/chat';
+import { ChatItemSimpleType } from '@/types/chat';
+import { jsonRes } from '@/service/response';
+import { PassThrough } from 'stream';
+import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
+import { pushChatBill } from '@/service/events/pushBill';
+import { searchKb } from '@/service/plugins/searchKb';
+import { ChatRoleEnum } from '@/constants/chat';
+
+/* 发送提示词 */
+export default async function handler(req: NextApiRequest, res: NextApiResponse) {
+  let step = 0; // step=1时，表示开始了流响应
+  const stream = new PassThrough();
+  stream.on('error', () => {
+    console.log('error: ', 'stream error');
+    stream.destroy();
+  });
+  res.on('close', () => {
+    stream.destroy();
+  });
+  res.on('error', () => {
+    console.log('error: ', 'request error');
+    stream.destroy();
+  });
+
+  try {
+    const {
+      prompts,
+      modelId,
+      isStream = true
+    } = req.body as {
+      prompts: ChatItemSimpleType[];
+      modelId: string;
+      isStream: boolean;
+    };
+
+    if (!prompts || !modelId) {
+      throw new Error('缺少参数');
+    }
+    if (!Array.isArray(prompts)) {
+      throw new Error('prompts is not array');
+    }
+    if (prompts.length > 30 || prompts.length === 0) {
+      throw new Error('prompts length range 1-30');
+    }
+
+    await connectToDatabase();
+    let startTime = Date.now();
+
+    /* 凭证校验 */
+    const { apiKey, userId } = await authOpenApiKey(req);
+
+    const { model } = await authModel({
+      userId,
+      modelId
+    });
+
+    const modelConstantsData = ChatModelMap[model.chat.chatModel];
+
+    // 使用了知识库搜索
+    if (model.chat.useKb) {
+      const similarity = ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22;
+
+      const { code, searchPrompt } = await searchKb({
+        prompts,
+        similarity,
+        model,
+        userId
+      });
+
+      // search result is empty
+      if (code === 201) {
+        return res.send(searchPrompt?.value);
+      }
+
+      searchPrompt && prompts.unshift(searchPrompt);
+    } else {
+      // 没有用知识库搜索，仅用系统提示词
+      if (model.chat.systemPrompt) {
+        prompts.unshift({
+          obj: ChatRoleEnum.System,
+          value: model.chat.systemPrompt
+        });
+      }
+    }
+
+    // 计算温度
+    const temperature = (modelConstantsData.maxTemperature * (model.chat.temperature / 10)).toFixed(
+      2
+    );
+
+    // 发出请求
+    const { streamResponse, responseMessages, responseText, totalTokens } =
+      await modelServiceToolMap[model.chat.chatModel].chatCompletion({
+        apiKey,
+        temperature: +temperature,
+        messages: prompts,
+        stream: isStream
+      });
+
+    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
+
+    let textLen = 0;
+    let tokens = totalTokens;
+
+    if (isStream) {
+      step = 1;
+      const { finishMessages, totalTokens } = await resStreamResponse({
+        model: model.chat.chatModel,
+        res,
+        stream,
+        chatResponse: streamResponse,
+        prompts
+      });
+      textLen = finishMessages.map((item) => item.value).join('').length;
+      tokens = totalTokens;
+    } else {
+      textLen = responseMessages.map((item) => item.value).join('').length;
+      jsonRes(res, {
+        data: responseText
+      });
+    }
+
+    pushChatBill({
+      isPay: true,
+      chatModel: model.chat.chatModel,
+      userId,
+      textLen,
+      tokens
+    });
+  } catch (err: any) {
+    if (step === 1) {
+      // 直接结束流
+      console.log('error，结束');
+      stream.destroy();
+    } else {
+      res.status(500);
+      jsonRes(res, {
+        code: 500,
+        error: err
+      });
+    }
+  }
+}

src/pages/api/openapi/chat/chatGpt.ts

@@ -1,146 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { connectToDatabase, Model } from '@/service/mongo';
-import { getOpenAIApi } from '@/service/utils/auth';
-import { axiosConfig, openaiChatFilter, authOpenApiKey } from '@/service/utils/tools';
-import { ChatItemType } from '@/types/chat';
-import { jsonRes } from '@/service/response';
-import { PassThrough } from 'stream';
-import { modelList } from '@/constants/model';
-import { pushChatBill } from '@/service/events/pushBill';
-import { gpt35StreamResponse } from '@/service/utils/openai';
-
-/* 发送提示词 */
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  let step = 0; // step=1时，表示开始了流响应
-  const stream = new PassThrough();
-  stream.on('error', () => {
-    console.log('error: ', 'stream error');
-    stream.destroy();
-  });
-  res.on('close', () => {
-    stream.destroy();
-  });
-  res.on('error', () => {
-    console.log('error: ', 'request error');
-    stream.destroy();
-  });
-
-  try {
-    const {
-      prompts,
-      modelId,
-      isStream = true
-    } = req.body as {
-      prompts: ChatItemType[];
-      modelId: string;
-      isStream: boolean;
-    };
-
-    if (!prompts || !modelId) {
-      throw new Error('缺少参数');
-    }
-    if (!Array.isArray(prompts)) {
-      throw new Error('prompts is not array');
-    }
-    if (prompts.length > 30 || prompts.length === 0) {
-      throw new Error('prompts length range 1-30');
-    }
-
-    await connectToDatabase();
-    let startTime = Date.now();
-
-    const { apiKey, userId } = await authOpenApiKey(req);
-
-    const model = await Model.findOne({
-      _id: modelId,
-      userId
-    });
-
-    if (!model) {
-      throw new Error('无权使用该模型');
-    }
-
-    const modelConstantsData = modelList.find((item) => item.model === model.service.modelName);
-    if (!modelConstantsData) {
-      throw new Error('模型加载异常');
-    }
-
-    // 如果有系统提示词，自动插入
-    if (model.systemPrompt) {
-      prompts.unshift({
-        obj: 'SYSTEM',
-        value: model.systemPrompt
-      });
-    }
-
-    // 控制在 tokens 数量，防止超出
-    const filterPrompts = openaiChatFilter({
-      model: model.service.chatModel,
-      prompts,
-      maxTokens: modelConstantsData.contextMaxToken - 500
-    });
-
-    // console.log(filterPrompts);
-    // 计算温度
-    const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
-
-    // 获取 chatAPI
-    const chatAPI = getOpenAIApi(apiKey);
-    // 发出请求
-    const chatResponse = await chatAPI.createChatCompletion(
-      {
-        model: model.service.chatModel,
-        temperature,
-        messages: filterPrompts,
-        frequency_penalty: 0.5, // 越大，重复内容越少
-        presence_penalty: -0.5, // 越大，越容易出现新内容
-        stream: isStream,
-        stop: ['.!?。']
-      },
-      {
-        timeout: 40000,
-        responseType: isStream ? 'stream' : 'json',
-        ...axiosConfig
-      }
-    );
-
-    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
-
-    let responseContent = '';
-
-    if (isStream) {
-      step = 1;
-      const streamResponse = await gpt35StreamResponse({
-        res,
-        stream,
-        chatResponse
-      });
-      responseContent = streamResponse.responseContent;
-    } else {
-      responseContent = chatResponse.data.choices?.[0]?.message?.content || '';
-      jsonRes(res, {
-        data: responseContent
-      });
-    }
-
-    // 只有使用平台的 key 才计费
-    pushChatBill({
-      isPay: true,
-      modelName: model.service.modelName,
-      userId,
-      messages: filterPrompts.concat({ role: 'assistant', content: responseContent })
-    });
-  } catch (err: any) {
-    if (step === 1) {
-      // 直接结束流
-      console.log('error，结束');
-      stream.destroy();
-    } else {
-      res.status(500);
-      jsonRes(res, {
-        code: 500,
-        error: err
-      });
-    }
-  }
-}

src/pages/api/openapi/chat/lafGpt.ts

@@ -1,20 +1,14 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { connectToDatabase, Model } from '@/service/mongo';
-import { getOpenAIApi } from '@/service/utils/auth';
-import { authOpenApiKey } from '@/service/utils/tools';
-import { axiosConfig, openaiChatFilter, systemPromptFilter } from '@/service/utils/tools';
-import { ChatItemType } from '@/types/chat';
+import { authOpenApiKey } from '@/service/utils/auth';
+import { resStreamResponse, modelServiceToolMap } from '@/service/utils/chat';
+import { ChatItemSimpleType } from '@/types/chat';
 import { jsonRes } from '@/service/response';
 import { PassThrough } from 'stream';
-import {
-  ModelNameEnum,
-  modelList,
-  ModelVectorSearchModeMap,
-  ChatModelEnum
-} from '@/constants/model';
+import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
 import { pushChatBill } from '@/service/events/pushBill';
-import { openaiCreateEmbedding, gpt35StreamResponse } from '@/service/utils/openai';
-import { PgClient } from '@/service/pg';
+import { searchKb } from '@/service/plugins/searchKb';
+import { ChatRoleEnum } from '@/constants/chat';
 
 /* 发送提示词 */
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
@@ -38,7 +32,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       modelId,
       isStream = true
     } = req.body as {
-      prompt: ChatItemType;
+      prompt: ChatItemSimpleType;
       modelId: string;
       isStream: boolean;
     };
@@ -59,26 +53,20 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       throw new Error('找不到模型');
     }
 
-    const modelConstantsData = modelList.find((item) => item.model === ModelNameEnum.VECTOR_GPT);
-    if (!modelConstantsData) {
-      throw new Error('模型已下架');
-    }
+    const modelConstantsData = ChatModelMap[model.chat.chatModel];
+
     console.log('laf gpt start');
 
-    // 获取 chatAPI
-    const chatAPI = getOpenAIApi(apiKey);
-
     // 请求一次 chatgpt 拆解需求
-    const promptResponse = await chatAPI.createChatCompletion(
-      {
-        model: ChatModelEnum.GPT35,
-        temperature: 0,
-        frequency_penalty: 0.5, // 越大，重复内容越少
-        presence_penalty: -0.5, // 越大，越容易出现新内容
-        messages: [
-          {
-            role: 'system',
-            content: `服务端逻辑生成器.根据用户输入的需求,拆解成 laf 云函数实现的步骤,只返回步骤,按格式返回步骤: 1.\n2.\n3.\n ......
+    const { responseText: resolveText, totalTokens: resolveTokens } = await modelServiceToolMap[
+      model.chat.chatModel
+    ].chatCompletion({
+      apiKey,
+      temperature: 0,
+      messages: [
+        {
+          obj: ChatRoleEnum.System,
+          value: `服务端逻辑生成器.根据用户输入的需求,拆解成 laf 云函数实现的步骤,只返回步骤,按格式返回步骤: 1.\n2.\n3.\n ......
 下面是一些例子:
 一个 hello world 例子
 1. 返回字符串: "hello world"
@@ -111,111 +99,66 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
 5. 获取当前时间,记录为 updateTime.
 6. 更新数据库数据,表为"blogs",更新符合 blogId 的记录的内容为{blogText, tags, updateTime}.
 7. 返回结果 "更新博客记录成功"`
-          },
-          {
-            role: 'user',
-            content: prompt.value
-          }
-        ]
-      },
-      {
-        timeout: 180000,
-        ...axiosConfig
-      }
-    );
-
-    const promptResolve = promptResponse.data.choices?.[0]?.message?.content || '';
-    if (!promptResolve) {
-      throw new Error('gpt 异常');
-    }
-
-    prompt.value += ` ${promptResolve}`;
-    console.log('prompt resolve success, time:', `${(Date.now() - startTime) / 1000}s`);
-
-    // 获取提示词的向量
-    const { vector: promptVector } = await openaiCreateEmbedding({
-      isPay: true,
-      apiKey,
-      userId,
-      text: prompt.value
+        },
+        {
+          obj: ChatRoleEnum.Human,
+          value: prompt.value
+        }
+      ],
+      stream: false
     });
 
+    prompt.value += ` ${resolveText}`;
+    console.log('prompt resolve success, time:', `${(Date.now() - startTime) / 1000}s`);
+
     // 读取对话内容
     const prompts = [prompt];
 
-    // 相似度搜索
-    const similarity = ModelVectorSearchModeMap[model.search.mode]?.similarity || 0.22;
-    const vectorSearch = await PgClient.select<{ id: string; q: string; a: string }>('modelData', {
-      fields: ['id', 'q', 'a'],
-      order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
-      where: [
-        ['model_id', model._id],
-        'AND',
-        ['user_id', userId],
-        'AND',
-        `vector <=> '[${promptVector}]' < ${similarity}`
-      ],
-      limit: 30
-    });
-
-    const formatRedisPrompt: string[] = vectorSearch.rows.map((item) => `${item.q}\n${item.a}`);
-
-    // system 筛选，最多 2500 tokens
-    const systemPrompt = systemPromptFilter({
-      model: model.service.chatModel,
-      prompts: formatRedisPrompt,
-      maxTokens: 2500
-    });
-
-    prompts.unshift({
-      obj: 'SYSTEM',
-      value: `${model.systemPrompt} 知识库是最新的,下面是知识库内容:${systemPrompt}`
-    });
-
-    // 控制上下文 tokens 数量，防止超出
-    const filterPrompts = openaiChatFilter({
-      model: model.service.chatModel,
+    // 获取向量匹配到的提示词
+    const { searchPrompt } = await searchKb({
+      similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
       prompts,
-      maxTokens: modelConstantsData.contextMaxToken - 500
+      model,
+      userId
     });
 
-    // console.log(filterPrompts);
-    // 计算温度
-    const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
+    searchPrompt && prompts.unshift(searchPrompt);
 
-    // 发出请求
-    const chatResponse = await chatAPI.createChatCompletion(
-      {
-        model: model.service.chatModel,
-        temperature,
-        messages: filterPrompts,
-        frequency_penalty: 0.5, // 越大，重复内容越少
-        presence_penalty: -0.5, // 越大，越容易出现新内容
-        stream: isStream
-      },
-      {
-        timeout: 180000,
-        responseType: isStream ? 'stream' : 'json',
-        ...axiosConfig
-      }
+    // 计算温度
+    const temperature = (modelConstantsData.maxTemperature * (model.chat.temperature / 10)).toFixed(
+      2
     );
 
-    console.log('code response. time:', `${(Date.now() - startTime) / 1000}s`);
+    // 发出请求
+    const { streamResponse, responseMessages, responseText, totalTokens } =
+      await modelServiceToolMap[model.chat.chatModel].chatCompletion({
+        apiKey,
+        temperature: +temperature,
+        messages: prompts,
+        stream: isStream
+      });
 
-    let responseContent = '';
+    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
+
+    let textLen = resolveText.length;
+    let tokens = resolveTokens;
 
     if (isStream) {
       step = 1;
-      const streamResponse = await gpt35StreamResponse({
+      const { finishMessages, totalTokens } = await resStreamResponse({
+        model: model.chat.chatModel,
         res,
         stream,
-        chatResponse
+        chatResponse: streamResponse,
+        prompts
       });
-      responseContent = streamResponse.responseContent;
+      textLen += finishMessages.map((item) => item.value).join('').length;
+      tokens += totalTokens;
     } else {
-      responseContent = chatResponse.data.choices?.[0]?.message?.content || '';
+      textLen += responseMessages.map((item) => item.value).join('').length;
+      tokens += totalTokens;
       jsonRes(res, {
-        data: responseContent
+        data: responseText
       });
     }
 
@@ -223,9 +166,10 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
 
     pushChatBill({
       isPay: true,
-      modelName: model.service.modelName,
+      chatModel: model.chat.chatModel,
       userId,
-      messages: filterPrompts.concat({ role: 'assistant', content: responseContent })
+      textLen,
+      tokens
     });
   } catch (err: any) {
     if (step === 1) {

src/pages/api/openapi/chat/vectorGpt.ts

@@ -1,217 +0,0 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { connectToDatabase, Model } from '@/service/mongo';
-import {
-  axiosConfig,
-  systemPromptFilter,
-  authOpenApiKey,
-  openaiChatFilter
-} from '@/service/utils/tools';
-import { ChatItemType } from '@/types/chat';
-import { jsonRes } from '@/service/response';
-import { PassThrough } from 'stream';
-import {
-  modelList,
-  ModelVectorSearchModeMap,
-  ModelVectorSearchModeEnum,
-  ModelDataStatusEnum
-} from '@/constants/model';
-import { pushChatBill } from '@/service/events/pushBill';
-import { openaiCreateEmbedding, gpt35StreamResponse } from '@/service/utils/openai';
-import dayjs from 'dayjs';
-import { PgClient } from '@/service/pg';
-
-/* 发送提示词 */
-export default async function handler(req: NextApiRequest, res: NextApiResponse) {
-  let step = 0; // step=1时，表示开始了流响应
-  const stream = new PassThrough();
-  stream.on('error', () => {
-    console.log('error: ', 'stream error');
-    stream.destroy();
-  });
-  res.on('close', () => {
-    stream.destroy();
-  });
-  res.on('error', () => {
-    console.log('error: ', 'request error');
-    stream.destroy();
-  });
-
-  try {
-    const {
-      prompts,
-      modelId,
-      isStream = true
-    } = req.body as {
-      prompts: ChatItemType[];
-      modelId: string;
-      isStream: boolean;
-    };
-
-    if (!prompts || !modelId) {
-      throw new Error('缺少参数');
-    }
-    if (!Array.isArray(prompts)) {
-      throw new Error('prompts is not array');
-    }
-    if (prompts.length > 30 || prompts.length === 0) {
-      throw new Error('prompts length range 1-30');
-    }
-
-    await connectToDatabase();
-    let startTime = Date.now();
-
-    /* 凭证校验 */
-    const { apiKey, userId } = await authOpenApiKey(req);
-
-    const model = await Model.findOne({
-      _id: modelId,
-      userId
-    });
-
-    if (!model) {
-      throw new Error('无权使用该模型');
-    }
-
-    const modelConstantsData = modelList.find((item) => item.model === model?.service?.modelName);
-    if (!modelConstantsData) {
-      throw new Error('模型初始化异常');
-    }
-
-    // 获取提示词的向量
-    const { vector: promptVector, chatAPI } = await openaiCreateEmbedding({
-      isPay: true,
-      apiKey,
-      userId,
-      text: prompts[prompts.length - 1].value // 取最后一个
-    });
-
-    // 相似度搜素
-    const similarity = ModelVectorSearchModeMap[model.search.mode]?.similarity || 0.22;
-    const vectorSearch = await PgClient.select<{ id: string; q: string; a: string }>('modelData', {
-      fields: ['id', 'q', 'a'],
-      where: [
-        ['status', ModelDataStatusEnum.ready],
-        'AND',
-        ['model_id', model._id],
-        'AND',
-        `vector <=> '[${promptVector}]' < ${similarity}`
-      ],
-      order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
-      limit: 20
-    });
-
-    const formatRedisPrompt: string[] = vectorSearch.rows.map((item) => `${item.q}\n${item.a}`);
-
-    // system 合并
-    if (prompts[0].obj === 'SYSTEM') {
-      formatRedisPrompt.unshift(prompts.shift()?.value || '');
-    }
-
-    /* 高相似度+退出，无法匹配时直接退出 */
-    if (
-      formatRedisPrompt.length === 0 &&
-      model.search.mode === ModelVectorSearchModeEnum.hightSimilarity
-    ) {
-      return res.send('对不起，你的问题不在知识库中。');
-    }
-    /* 高相似度+无上下文，不添加额外知识 */
-    if (
-      formatRedisPrompt.length === 0 &&
-      model.search.mode === ModelVectorSearchModeEnum.noContext
-    ) {
-      prompts.unshift({
-        obj: 'SYSTEM',
-        value: model.systemPrompt
-      });
-    } else {
-      // 有匹配或者低匹配度模式情况下，添加知识库内容。
-      // 系统提示词过滤，最多 2500 tokens
-      const systemPrompt = systemPromptFilter({
-        model: model.service.chatModel,
-        prompts: formatRedisPrompt,
-        maxTokens: 2500
-      });
-
-      prompts.unshift({
-        obj: 'SYSTEM',
-        value: `
-${model.systemPrompt}
-${
-  model.search.mode === ModelVectorSearchModeEnum.hightSimilarity
-    ? `你只能从知识库选择内容回答.不在知识库内容拒绝回复`
-    : ''
-}
-知识库内容为: 当前时间为${dayjs().format('YYYY/MM/DD HH:mm:ss')}\n${systemPrompt}'
-`
-      });
-    }
-
-    // 控制在 tokens 数量，防止超出
-    const filterPrompts = openaiChatFilter({
-      model: model.service.chatModel,
-      prompts,
-      maxTokens: modelConstantsData.contextMaxToken - 500
-    });
-
-    // console.log(filterPrompts);
-    // 计算温度
-    const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
-
-    // 发出请求
-    const chatResponse = await chatAPI.createChatCompletion(
-      {
-        model: model.service.chatModel,
-        temperature,
-        messages: filterPrompts,
-        frequency_penalty: 0.5, // 越大，重复内容越少
-        presence_penalty: -0.5, // 越大，越容易出现新内容
-        stream: isStream,
-        stop: ['.!?。']
-      },
-      {
-        timeout: 180000,
-        responseType: isStream ? 'stream' : 'json',
-        ...axiosConfig
-      }
-    );
-
-    console.log('api response time:', `${(Date.now() - startTime) / 1000}s`);
-
-    let responseContent = '';
-
-    if (isStream) {
-      step = 1;
-      const streamResponse = await gpt35StreamResponse({
-        res,
-        stream,
-        chatResponse
-      });
-      responseContent = streamResponse.responseContent;
-    } else {
-      responseContent = chatResponse.data.choices?.[0]?.message?.content || '';
-      jsonRes(res, {
-        data: responseContent
-      });
-    }
-
-    pushChatBill({
-      isPay: true,
-      modelName: model.service.modelName,
-      userId,
-      messages: filterPrompts.concat({ role: 'assistant', content: responseContent })
-    });
-    // jsonRes(res);
-  } catch (err: any) {
-    if (step === 1) {
-      // 直接结束流
-      console.log('error，结束');
-      stream.destroy();
-    } else {
-      res.status(500);
-      jsonRes(res, {
-        code: 500,
-        error: err
-      });
-    }
-  }
-}

src/pages/api/openapi/delKey.ts

@@ -2,7 +2,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, OpenApi } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {

src/pages/api/openapi/getKeys.ts

@@ -2,7 +2,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, OpenApi } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { UserOpenApiKey } from '@/types/openapi';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {

src/pages/api/openapi/postKey.ts

@@ -2,7 +2,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, OpenApi } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { customAlphabet } from 'nanoid';
 const nanoid = customAlphabet('abcdefghijklmnopqrstuvwxyz1234567890');
 

src/pages/api/user/checkPayResult.ts

@@ -1,7 +1,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, User, Pay } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { PaySchema, UserModelSchema } from '@/types/mongoSchema';
 import dayjs from 'dayjs';
 import { getPayResult } from '@/service/utils/wxpay';

src/pages/api/user/getBill.ts

@@ -2,7 +2,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, Bill } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import type { BillSchema } from '@/types/mongoSchema';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {

src/pages/api/user/getPayCode.ts

@@ -1,6 +1,6 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { customAlphabet } from 'nanoid';
 import { connectToDatabase, Pay } from '@/service/mongo';
 import { PRICE_SCALE } from '@/constants/common';

src/pages/api/user/getPayOrders.ts

@@ -1,6 +1,6 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { connectToDatabase, Pay } from '@/service/mongo';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {

src/pages/api/user/promotion/getPromotionData.ts

@@ -2,7 +2,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, User, promotionRecord } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import mongoose from 'mongoose';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {

src/pages/api/user/promotion/getPromotions.ts

@@ -2,7 +2,7 @@
 import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase, promotionRecord } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {

src/pages/api/user/tokenLogin.ts

@@ -3,7 +3,7 @@ import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { connectToDatabase } from '@/service/mongo';
 import { User } from '@/service/models/user';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 
 export default async function handler(req: NextApiRequest, res: NextApiResponse) {
   try {

src/pages/api/user/update.ts

@@ -3,7 +3,7 @@ import type { NextApiRequest, NextApiResponse } from 'next';
 import { jsonRes } from '@/service/response';
 import { User } from '@/service/models/user';
 import { connectToDatabase } from '@/service/mongo';
-import { authToken } from '@/service/utils/tools';
+import { authToken } from '@/service/utils/auth';
 import { UserUpdateParams } from '@/types/user';
 
 /* 更新一些基本信息 */

src/pages/chat/components/SlideBar.tsx

@@ -1,4 +1,4 @@
-import React, { useRef, useEffect, useMemo } from 'react';
+import React, { useRef, useEffect, useMemo, useCallback } from 'react';
 import { AddIcon, ChatIcon, DeleteIcon, MoonIcon, SunIcon } from '@chakra-ui/icons';
 import {
   Box,
@@ -13,7 +13,11 @@ import {
   IconButton,
   useDisclosure,
   useColorMode,
-  useColorModeValue
+  useColorModeValue,
+  Menu,
+  MenuButton,
+  MenuList,
+  MenuItem
 } from '@chakra-ui/react';
 import { useUserStore } from '@/store/user';
 import { useMutation, useQuery } from '@tanstack/react-query';
@@ -23,16 +27,20 @@ import MyIcon from '@/components/Icon';
 import WxConcat from '@/components/WxConcat';
 import { getChatHistory, delChatHistoryById } from '@/api/chat';
 import { getCollectionModels } from '@/api/model';
-import { modelList } from '@/constants/model';
+import type { ChatSiteItemType } from '../index';
+import { fileDownload } from '@/utils/file';
+import { htmlTemplate } from '@/constants/common';
 
 const SlideBar = ({
   chatId,
   modelId,
+  history,
   resetChat,
   onClose
 }: {
   chatId: string;
   modelId: string;
+  history: ChatSiteItemType[];
   resetChat: (modelId?: string, chatId?: string) => void;
   onClose: () => void;
 }) => {
@@ -42,17 +50,25 @@ const SlideBar = ({
   const { isOpen: isOpenWx, onOpen: onOpenWx, onClose: onCloseWx } = useDisclosure();
   const preChatId = useRef('chatId'); // 用于校验上一次chatId的情况,判断是否需要刷新历史记录
 
-  const { isSuccess } = useQuery(['getMyModels'], getMyModels, {
-    cacheTime: 5 * 60 * 1000
+  const { isSuccess, refetch: fetchMyModels } = useQuery(['getMyModels'], getMyModels, {
+    cacheTime: 5 * 60 * 1000,
+    enabled: false
   });
 
-  const { data: collectionModels = [] } = useQuery([getCollectionModels], getCollectionModels);
+  const { data: collectionModels = [], refetch: fetchCollectionModels } = useQuery(
+    [getCollectionModels],
+    getCollectionModels,
+    {
+      cacheTime: 5 * 60 * 1000,
+      enabled: false
+    }
+  );
 
   const models = useMemo(() => {
     const myModelList = myModels.map((item) => ({
       id: item._id,
       name: item.name,
-      icon: modelList.find((model) => model.model === item?.service?.modelName)?.icon || 'model'
+      icon: 'model' as any
     }));
     const collectionList = collectionModels
       .map((item) => ({
@@ -80,9 +96,73 @@ const SlideBar = ({
   // init history
   useEffect(() => {
     setTimeout(() => {
+      fetchMyModels();
+      fetchCollectionModels();
       loadChatHistory();
     }, 1000);
-  }, [loadChatHistory]);
+  }, [fetchCollectionModels, fetchMyModels, loadChatHistory]);
+
+  /**
+   * export md
+   */
+  const onclickExportMd = useCallback(() => {
+    fileDownload({
+      text: history.map((item) => item.value).join('\n'),
+      type: 'text/markdown',
+      filename: 'chat.md'
+    });
+  }, [history]);
+
+  const getHistoryHtml = useCallback(() => {
+    const historyDom = document.getElementById('history');
+    if (!historyDom) return;
+    const dom = Array.from(historyDom.children).map((child, i) => {
+      const avatar = `<img src="${
+        child.querySelector<HTMLImageElement>('.avatar')?.src
+      }" alt="" />`;
+
+      const chatContent = child.querySelector<HTMLDivElement>('.markdown');
+
+      if (!chatContent) {
+        return '';
+      }
+
+      const chatContentClone = chatContent.cloneNode(true) as HTMLDivElement;
+
+      const codeHeader = chatContentClone.querySelectorAll('.code-header');
+      codeHeader.forEach((childElement: any) => {
+        childElement.remove();
+      });
+
+      return `<div class="chat-item">
+        ${avatar}
+        ${chatContentClone.outerHTML}
+      </div>`;
+    });
+    const html = htmlTemplate.replace('{{CHAT_CONTENT}}', dom.join('\n'));
+    return html;
+  }, []);
+
+  const onclickExportHtml = useCallback(() => {
+    const html = getHistoryHtml();
+    html &&
+      fileDownload({
+        text: html,
+        type: 'text/html',
+        filename: '聊天记录.html'
+      });
+  }, [getHistoryHtml]);
+
+  const onclickExportPdf = useCallback(() => {
+    const html = getHistoryHtml();
+
+    html &&
+      // @ts-ignore
+      html2pdf(html, {
+        margin: 0,
+        filename: `聊天记录.pdf`
+      });
+  }, [getHistoryHtml]);
 
   const RenderHistory = () => (
     <>
@@ -145,7 +225,7 @@ const SlideBar = ({
     onClick: () => void;
     children: JSX.Element | string;
   }) => (
-    <Box px={3} mb={3}>
+    <Box px={3} mb={2}>
       <Flex
         alignItems={'center'}
         p={2}
@@ -176,7 +256,7 @@ const SlideBar = ({
           w={'90%'}
           variant={'white'}
           h={'40px'}
-          mb={4}
+          mb={2}
           mx={'auto'}
           leftIcon={<AddIcon />}
           onClick={() => resetChat()}
@@ -238,7 +318,33 @@ const SlideBar = ({
         </Accordion>
       </Box>
 
-      <Divider my={4} colorScheme={useColorModeValue('gray', 'white')} />
+      <Divider my={3} colorScheme={useColorModeValue('gray', 'white')} />
+
+      {history.length > 0 && (
+        <Menu autoSelect={false}>
+          <MenuButton
+            mx={3}
+            mb={2}
+            p={2}
+            display={'flex'}
+            alignItems={'center'}
+            cursor={'pointer'}
+            borderRadius={'md'}
+            textAlign={'left'}
+            _hover={{
+              backgroundColor: 'rgba(255,255,255,0.2)'
+            }}
+          >
+            <MyIcon name="export" fill={'white'} w={'18px'} h={'18px'} mr={4} />
+            导出聊天
+          </MenuButton>
+          <MenuList fontSize={'sm'} color={'blackAlpha.800'}>
+            <MenuItem onClick={onclickExportHtml}>HTML格式</MenuItem>
+            <MenuItem onClick={onclickExportPdf}>PDF格式</MenuItem>
+            <MenuItem onClick={onclickExportMd}>Markdown格式</MenuItem>
+          </MenuList>
+        </Menu>
+      )}
 
       <RenderButton onClick={() => router.push('/')}>
         <>

src/pages/chat/index.tsx

@@ -1,6 +1,5 @@
 import React, { useCallback, useState, useRef, useMemo, useEffect } from 'react';
 import { useRouter } from 'next/router';
-import Image from 'next/image';
 import { getInitChatSiteInfo, delChatRecordByIndex, postSaveChat } from '@/api/chat';
 import type { InitChatResponse } from '@/api/response/chat';
 import type { ChatItemType } from '@/types/chat';
@@ -16,32 +15,37 @@ import {
   Menu,
   MenuButton,
   MenuList,
-  MenuItem
+  MenuItem,
+  Image,
+  Button,
+  Modal,
+  ModalOverlay,
+  ModalContent,
+  ModalBody,
+  ModalCloseButton
 } from '@chakra-ui/react';
 import { useToast } from '@/hooks/useToast';
 import { useScreen } from '@/hooks/useScreen';
 import { useQuery } from '@tanstack/react-query';
-import { ModelNameEnum } from '@/constants/model';
+import { OpenAiChatEnum } from '@/constants/model';
 import dynamic from 'next/dynamic';
 import { useGlobalStore } from '@/store/global';
 import { useCopyData } from '@/utils/tools';
 import { streamFetch } from '@/api/fetch';
-import Icon from '@/components/Icon';
 import MyIcon from '@/components/Icon';
 import { throttle } from 'lodash';
-import { customAlphabet } from 'nanoid';
-const nanoid = customAlphabet('abcdefghijklmnopqrstuvwxyz1234567890', 5);
+import { Types } from 'mongoose';
+import Markdown from '@/components/Markdown';
+import { HUMAN_ICON, LOGO_ICON } from '@/constants/chat';
 
 const SlideBar = dynamic(() => import('./components/SlideBar'));
 const Empty = dynamic(() => import('./components/Empty'));
-const Markdown = dynamic(() => import('@/components/Markdown'));
 
 import styles from './index.module.scss';
 
 const textareaMinH = '22px';
 
 export type ChatSiteItemType = {
-  id: string;
   status: 'loading' | 'finish';
 } & ChatItemType;
 
@@ -65,12 +69,12 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
     name: '',
     avatar: '/icon/logo.png',
     intro: '',
-    chatModel: '',
-    modelName: '',
+    chatModel: OpenAiChatEnum.GPT35,
     history: []
   }); // 聊天框整体数据
 
-  const [inputVal, setInputVal] = useState(''); // 输入的内容
+  const [inputVal, setInputVal] = useState(''); // user input prompt
+  const [showSystemPrompt, setShowSystemPrompt] = useState('');
 
   const isChatting = useMemo(
     () => chatData.history[chatData.history.length - 1]?.status === 'loading',
@@ -137,17 +141,15 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
 
         setChatData({
           ...res,
-          history: res.history.map((item: any, i) => ({
-            obj: item.obj,
-            value: item.value,
-            id: item.id || `${nanoid()}-${i}`,
+          history: res.history.map((item) => ({
+            ...item,
             status: 'finish'
           }))
         });
         if (isScroll && res.history.length > 0) {
           setTimeout(() => {
             scrollToBottom('auto');
-          }, 1200);
+          }, 1000);
         }
       } catch (e: any) {
         toast({
@@ -192,27 +194,20 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
 
   // gpt 对话
   const gptChatPrompt = useCallback(
-    async (prompts: ChatSiteItemType) => {
-      const urlMap: Record<string, string> = {
-        [ModelNameEnum.GPT35]: '/api/chat/chatGpt',
-        [ModelNameEnum.VECTOR_GPT]: '/api/chat/vectorGpt'
-      };
-
-      if (!urlMap[chatData.modelName]) return Promise.reject('找不到模型');
-
+    async (prompts: ChatSiteItemType[]) => {
       // create abort obj
       const abortSignal = new AbortController();
       controller.current = abortSignal;
       isResetPage.current = false;
 
       const prompt = {
-        obj: prompts.obj,
-        value: prompts.value
+        obj: prompts[0].obj,
+        value: prompts[0].value
       };
 
       // 流请求，获取数据
-      const responseText = await streamFetch({
-        url: urlMap[chatData.modelName],
+      let { responseText, systemPrompt, newChatId } = await streamFetch({
+        url: '/api/chat/chat',
         data: {
           prompt,
           chatId,
@@ -239,17 +234,23 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
         return;
       }
 
-      let newChatId = '';
-      // 保存对话信息
+      // save chat record
       try {
         newChatId = await postSaveChat({
+          newChatId, // 如果有newChatId，会自动以这个Id创建对话框
           modelId,
           chatId,
           prompts: [
-            prompt,
             {
+              _id: prompts[0]._id,
+              obj: 'Human',
+              value: prompt.value
+            },
+            {
+              _id: prompts[1]._id,
               obj: 'AI',
-              value: responseText
+              value: responseText,
+              systemPrompt
             }
           ]
         });
@@ -273,12 +274,13 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
           if (index !== state.history.length - 1) return item;
           return {
             ...item,
-            status: 'finish'
+            status: 'finish',
+            systemPrompt
           };
         })
       }));
     },
-    [chatData.modelName, chatId, generatingMessage, modelId, router, toast]
+    [chatId, generatingMessage, modelId, router, toast]
   );
 
   /**
@@ -307,13 +309,13 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
     const newChatList: ChatSiteItemType[] = [
       ...chatData.history,
       {
-        id: nanoid(),
+        _id: String(new Types.ObjectId()),
         obj: 'Human',
         value: val,
         status: 'finish'
       },
       {
-        id: nanoid(),
+        _id: String(new Types.ObjectId()),
         obj: 'AI',
         value: '',
         status: 'loading'
@@ -333,7 +335,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
     }, 100);
 
     try {
-      await gptChatPrompt(newChatList[newChatList.length - 2]);
+      await gptChatPrompt(newChatList.slice(-2));
     } catch (err: any) {
       toast({
         title: typeof err === 'string' ? err : err?.message || '聊天出错了~',
@@ -353,11 +355,11 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
 
   // 删除一句话
   const delChatRecord = useCallback(
-    async (index: number) => {
+    async (index: number, id: string) => {
       setLoading(true);
       try {
         // 删除数据库最后一句
-        await delChatRecordByIndex(chatId, index);
+        await delChatRecordByIndex(chatId, id);
 
         setChatData((state) => ({
           ...state,
@@ -393,7 +395,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
   // 更新流中断对象
   useEffect(() => {
     return () => {
-      // eslint-disable-next-line react-hooks/exhaustive-deps
+      isResetPage.current = true;
       controller.current?.abort();
     };
   }, []);
@@ -410,6 +412,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
             resetChat={resetChat}
             chatId={chatId}
             modelId={modelId}
+            history={chatData.history}
             onClose={onCloseSlider}
           />
         </Box>
@@ -425,11 +428,11 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
             px={7}
           >
             <Box onClick={onOpenSlider}>
-              <Icon
+              <MyIcon
                 name={'menu'}
                 w={'20px'}
                 h={'20px'}
-                fill={useColorModeValue('blackAlpha.700', 'white')}
+                color={useColorModeValue('blackAlpha.700', 'white')}
               />
             </Box>
             <Box>{chatData?.name}</Box>
@@ -441,6 +444,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
                 resetChat={resetChat}
                 chatId={chatId}
                 modelId={modelId}
+                history={chatData.history}
                 onClose={onCloseSlider}
               />
             </DrawerContent>
@@ -454,10 +458,18 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
         flexDirection={'column'}
       >
         {/* 聊天内容 */}
-        <Box ref={ChatBox} pb={[4, 0]} flex={'1 0 0'} h={0} w={'100%'} overflowY={'auto'}>
+        <Box
+          id={'history'}
+          ref={ChatBox}
+          pb={[4, 0]}
+          flex={'1 0 0'}
+          h={0}
+          w={'100%'}
+          overflowY={'auto'}
+        >
           {chatData.history.map((item, index) => (
             <Box
-              key={item.id}
+              key={item._id}
               py={media(9, 6)}
               px={media(4, 2)}
               backgroundColor={
@@ -470,29 +482,43 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
                 <Menu autoSelect={false}>
                   <MenuButton as={Box} mr={media(4, 1)} cursor={'pointer'}>
                     <Image
-                      src={
-                        item.obj === 'Human'
-                          ? '/icon/human.png'
-                          : chatData.avatar || '/icon/logo.png'
-                      }
+                      className="avatar"
+                      src={item.obj === 'Human' ? HUMAN_ICON : chatData.avatar || LOGO_ICON}
                       alt="avatar"
-                      width={media(30, 20)}
-                      height={media(30, 20)}
+                      w={['20px', '30px']}
+                      maxH={'50px'}
+                      objectFit={'contain'}
                     />
                   </MenuButton>
                   <MenuList fontSize={'sm'}>
                     <MenuItem onClick={() => onclickCopy(item.value)}>复制</MenuItem>
-                    <MenuItem onClick={() => delChatRecord(index)}>删除该行</MenuItem>
+                    <MenuItem onClick={() => delChatRecord(index, item._id)}>删除该行</MenuItem>
                   </MenuList>
                 </Menu>
-                <Box flex={'1 0 0'} w={0} overflow={'hidden'} id={`chat${index}`}>
+                <Box flex={'1 0 0'} w={0} overflow={'hidden'}>
                   {item.obj === 'AI' ? (
-                    <Markdown
-                      source={item.value}
-                      isChatting={isChatting && index === chatData.history.length - 1}
-                    />
+                    <>
+                      <Markdown
+                        source={item.value}
+                        isChatting={isChatting && index === chatData.history.length - 1}
+                      />
+                      {item.systemPrompt && (
+                        <Button
+                          size={'xs'}
+                          mt={2}
+                          fontWeight={'normal'}
+                          colorScheme={'gray'}
+                          variant={'outline'}
+                          onClick={() => setShowSystemPrompt(item.systemPrompt || '')}
+                        >
+                          查看提示词
+                        </Button>
+                      )}
+                    </>
                   ) : (
-                    <Box whiteSpace={'pre-wrap'}>{item.value}</Box>
+                    <Box className="markdown" whiteSpace={'pre-wrap'}>
+                      <Box as={'p'}>{item.value}</Box>
+                    </Box>
                   )}
                 </Box>
                 {isPc && (
@@ -514,7 +540,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
                       _hover={{
                         color: 'red.600'
                       }}
-                      onClick={() => delChatRecord(index)}
+                      onClick={() => delChatRecord(index, item._id)}
                     />
                   </Flex>
                 )}
@@ -585,7 +611,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
               bottom={'15px'}
             >
               {isChatting ? (
-                <Icon
+                <MyIcon
                   className={styles.stopIcon}
                   width={['22px', '25px']}
                   height={['22px', '25px']}
@@ -597,7 +623,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
                   }}
                 />
               ) : (
-                <Icon
+                <MyIcon
                   name={'chatSend'}
                   width={['18px', '20px']}
                   height={['18px', '20px']}
@@ -610,6 +636,19 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
           </Box>
         </Box>
       </Flex>
+
+      {/* system prompt show modal */}
+      {
+        <Modal isOpen={!!showSystemPrompt} onClose={() => setShowSystemPrompt('')}>
+          <ModalOverlay />
+          <ModalContent maxW={'min(90vw, 600px)'} pr={2} maxH={'80vh'} overflowY={'auto'}>
+            <ModalCloseButton />
+            <ModalBody pt={10} fontSize={'sm'} whiteSpace={'pre-wrap'} textAlign={'justify'}>
+              {showSystemPrompt}
+            </ModalBody>
+          </ModalContent>
+        </Modal>
+      }
     </Flex>
   );
 };

src/pages/index.tsx

@@ -22,9 +22,9 @@ const Home = () => {
 
       <Card p={5} mt={4} textAlign={'center'}>
         <Box>
-          {/* <Link href="https://beian.miit.gov.cn/" target="_blank">
-            浙B2-20080101
-          </Link> */}
+          <Link href="https://beian.miit.gov.cn/" target="_blank">
+            浙ICP备2023011255号-1
+          </Link>
         </Box>
         <Box>Made by FastGpt Team.</Box>
       </Card>

src/pages/login/components/ForgetPasswordForm.tsx

@@ -78,7 +78,7 @@ const RegisterForm = ({ setPageType, loginSuccess }: Props) => {
         找回 FastGPT 账号
       </Box>
       <form onSubmit={handleSubmit(onclickFindPassword)}>
-        <FormControl mt={8} isInvalid={!!errors.username}>
+        <FormControl mt={5} isInvalid={!!errors.username}>
           <Input
             placeholder="邮箱/手机号"
             size={mediaLgMd}
@@ -95,7 +95,7 @@ const RegisterForm = ({ setPageType, loginSuccess }: Props) => {
             {!!errors.username && errors.username.message}
           </FormErrorMessage>
         </FormControl>
-        <FormControl mt={8} isInvalid={!!errors.username}>
+        <FormControl mt={5} isInvalid={!!errors.username}>
           <Flex>
             <Input
               flex={1}
@@ -121,7 +121,7 @@ const RegisterForm = ({ setPageType, loginSuccess }: Props) => {
             {!!errors.code && errors.code.message}
           </FormErrorMessage>
         </FormControl>
-        <FormControl mt={8} isInvalid={!!errors.password}>
+        <FormControl mt={5} isInvalid={!!errors.password}>
           <Input
             type={'password'}
             placeholder="新密码"
@@ -142,7 +142,7 @@ const RegisterForm = ({ setPageType, loginSuccess }: Props) => {
             {!!errors.password && errors.password.message}
           </FormErrorMessage>
         </FormControl>
-        <FormControl mt={8} isInvalid={!!errors.password2}>
+        <FormControl mt={5} isInvalid={!!errors.password2}>
           <Input
             type={'password'}
             placeholder="确认密码"
@@ -168,7 +168,7 @@ const RegisterForm = ({ setPageType, loginSuccess }: Props) => {
         </Box>
         <Button
           type="submit"
-          mt={8}
+          mt={5}
           w={'100%'}
           size={mediaLgMd}
           colorScheme="blue"

src/pages/login/components/RegisterForm.tsx

@@ -8,6 +8,7 @@ import type { ResLogin } from '@/api/response/user';
 import { useScreen } from '@/hooks/useScreen';
 import { useToast } from '@/hooks/useToast';
 import { useRouter } from 'next/router';
+import { postCreateModel } from '@/api/model';
 
 interface Props {
   loginSuccess: (e: ResLogin) => void;
@@ -64,6 +65,10 @@ const RegisterForm = ({ setPageType, loginSuccess }: Props) => {
           title: `注册成功`,
           status: 'success'
         });
+        // aut register a model
+        postCreateModel({
+          name: '模型1'
+        });
       } catch (error: any) {
         toast({
           title: error.message || '注册异常',
@@ -81,7 +86,7 @@ const RegisterForm = ({ setPageType, loginSuccess }: Props) => {
         注册 FastGPT 账号
       </Box>
       <form onSubmit={handleSubmit(onclickRegister)}>
-        <FormControl mt={8} isInvalid={!!errors.username}>
+        <FormControl mt={5} isInvalid={!!errors.username}>
           <Input
             placeholder="邮箱/手机号"
             size={mediaLgMd}
@@ -98,7 +103,7 @@ const RegisterForm = ({ setPageType, loginSuccess }: Props) => {
             {!!errors.username && errors.username.message}
           </FormErrorMessage>
         </FormControl>
-        <FormControl mt={8} isInvalid={!!errors.username}>
+        <FormControl mt={5} isInvalid={!!errors.username}>
           <Flex>
             <Input
               flex={1}
@@ -124,7 +129,7 @@ const RegisterForm = ({ setPageType, loginSuccess }: Props) => {
             {!!errors.code && errors.code.message}
           </FormErrorMessage>
         </FormControl>
-        <FormControl mt={8} isInvalid={!!errors.password}>
+        <FormControl mt={5} isInvalid={!!errors.password}>
           <Input
             type={'password'}
             placeholder="密码"
@@ -145,7 +150,7 @@ const RegisterForm = ({ setPageType, loginSuccess }: Props) => {
             {!!errors.password && errors.password.message}
           </FormErrorMessage>
         </FormControl>
-        <FormControl mt={8} isInvalid={!!errors.password2}>
+        <FormControl mt={5} isInvalid={!!errors.password2}>
           <Input
             type={'password'}
             placeholder="确认密码"
@@ -171,7 +176,7 @@ const RegisterForm = ({ setPageType, loginSuccess }: Props) => {
         </Box>
         <Button
           type="submit"
-          mt={8}
+          mt={5}
           w={'100%'}
           size={mediaLgMd}
           colorScheme="blue"

src/pages/login/index.tsx

@@ -45,12 +45,19 @@ const Login = () => {
   }, [router]);
 
   return (
-    <Box className={styles.loginPage} h={'100%'} p={isPc ? '10vh 10vw' : 0}>
+    <Flex
+      alignItems={'center'}
+      justifyContent={'center'}
+      className={styles.loginPage}
+      h={'100%'}
+      px={[0, '10vw']}
+    >
       <Flex
-        maxW={'1240px'}
-        m={'auto'}
-        backgroundColor={'#fff'}
         height="100%"
+        w={'100%'}
+        maxW={'1240px'}
+        maxH={['auto', '660px']}
+        backgroundColor={'#fff'}
         alignItems={'center'}
         justifyContent={'center'}
         p={10}
@@ -83,7 +90,7 @@ const Login = () => {
           <DynamicComponent type={pageType} />
         </Box>
       </Flex>
-    </Box>
+    </Flex>
   );
 };
 

src/pages/model/detail/components/InputDataModal.tsx

@@ -118,11 +118,11 @@ const InputDataModal = ({
           px={6}
           pb={2}
         >
-          <Box flex={2} mr={[0, 4]} mb={[4, 0]} h={['230px', '100%']}>
+          <Box flex={1} mr={[0, 4]} mb={[4, 0]} h={['230px', '100%']}>
             <Box h={'30px'}>{'匹配的知识点'}</Box>
             <Textarea
-              placeholder={'匹配的知识点。这部分内容会被搜索，请把控内容的质量。最多 1000 字。'}
-              maxLength={2000}
+              placeholder={'匹配的知识点。这部分内容会被搜索，请把控内容的质量。最多 1500 字。'}
+              maxLength={1500}
               resize={'none'}
               h={'calc(100% - 30px)'}
               {...register(`q`, {
@@ -130,13 +130,13 @@ const InputDataModal = ({
               })}
             />
           </Box>
-          <Box flex={3} h={['330px', '100%']}>
+          <Box flex={1} h={['330px', '100%']}>
             <Box h={'30px'}>补充知识</Box>
             <Textarea
               placeholder={
-                '补充知识。这部分内容不会被搜索，但会作为"匹配的知识点"的内容补充，你可以讲一些细节的内容填写在这里。最多 2000 字。'
+                '补充知识。这部分内容不会被搜索，但会作为"匹配的知识点"的内容补充，你可以讲一些细节的内容填写在这里。最多 1500 字。'
               }
-              maxLength={2000}
+              maxLength={1500}
               resize={'none'}
               h={'calc(100% - 30px)'}
               {...register('a')}

src/pages/model/detail/components/ModelDataCard.tsx

@@ -16,8 +16,10 @@ import {
   MenuButton,
   MenuList,
   MenuItem,
-  Input
+  Input,
+  Tooltip
 } from '@chakra-ui/react';
+import { QuestionOutlineIcon } from '@chakra-ui/icons';
 import type { BoxProps } from '@chakra-ui/react';
 import type { ModelDataItemType } from '@/types/model';
 import { ModelDataStatusMap } from '@/constants/model';
@@ -45,9 +47,10 @@ const ModelDataCard = ({ modelId, isOwner }: { modelId: string; isOwner: boolean
   const [searchText, setSearchText] = useState('');
   const tdStyles = useRef<BoxProps>({
     fontSize: 'xs',
+    minW: '150px',
     maxW: '500px',
-    whiteSpace: 'pre-wrap',
     maxH: '250px',
+    whiteSpace: 'pre-wrap',
     overflowY: 'auto'
   });
   const {
@@ -132,7 +135,7 @@ const ModelDataCard = ({ modelId, isOwner }: { modelId: string; isOwner: boolean
     <>
       <Flex>
         <Box fontWeight={'bold'} fontSize={'lg'} flex={1} mr={2}>
-          模型数据: {total}组
+          知识库数据: {total}组
         </Box>
         {isOwner && (
           <>
@@ -207,7 +210,16 @@ const ModelDataCard = ({ modelId, isOwner }: { modelId: string; isOwner: boolean
           <Table variant={'simple'} w={'100%'}>
             <Thead>
               <Tr>
-                <Th>{'匹配的知识点'}</Th>
+                <Th>
+                  匹配的知识点
+                  <Tooltip
+                    label={
+                      '对话时，会将用户的问题和知识库的 "匹配知识点" 进行比较，找到最相似的前 n 条记录，将这些记录的 "匹配知识点"+"补充知识点" 作为 chatgpt 的系统提示词。'
+                    }
+                  >
+                    <QuestionOutlineIcon ml={1} />
+                  </Tooltip>
+                </Th>
                 <Th>补充知识</Th>
                 <Th>状态</Th>
                 {isOwner && <Th>操作</Th>}

src/pages/model/detail/components/ModelEditForm.tsx

@@ -21,21 +21,19 @@ import {
 import { QuestionOutlineIcon } from '@chakra-ui/icons';
 import type { ModelSchema } from '@/types/mongoSchema';
 import { UseFormReturn } from 'react-hook-form';
-import { modelList, ModelVectorSearchModeMap } from '@/constants/model';
+import { ChatModelMap, ModelVectorSearchModeMap, chatModelList } from '@/constants/model';
 import { formatPrice } from '@/utils/user';
 import { useConfirm } from '@/hooks/useConfirm';
 import { useSelectFile } from '@/hooks/useSelectFile';
 import { useToast } from '@/hooks/useToast';
-import { fileToBase64 } from '@/utils/file';
+import { fileToBase64, compressImg } from '@/utils/file';
 
 const ModelEditForm = ({
   formHooks,
-  canTrain,
   isOwner,
   handleDelModel
 }: {
   formHooks: UseFormReturn<ModelSchema>;
-  canTrain: boolean;
   isOwner: boolean;
   handleDelModel: () => void;
 }) => {
@@ -54,17 +52,19 @@ const ModelEditForm = ({
     async (e: File[]) => {
       const file = e[0];
       if (!file) return;
+      try {
+        const base64 = await compressImg({
+          file
+        });
 
-      if (file.size > 100 * 1024) {
-        return toast({
-          title: '头像需小于 100kb',
+        setValue('avatar', base64);
+        setRefresh((state) => !state);
+      } catch (err: any) {
+        toast({
+          title: typeof err === 'string' ? err : '头像选择异常',
           status: 'warning'
         });
       }
-
-      const base64 = (await fileToBase64(file)) as string;
-      setValue('avatar', base64);
-      setRefresh((state) => !state);
     },
     [setValue, toast]
   );
@@ -73,6 +73,12 @@ const ModelEditForm = ({
     <>
       <Card p={4}>
         <Box fontWeight={'bold'}>基本信息</Box>
+        <Flex alignItems={'center'} mt={4}>
+          <Box flex={'0 0 80px'} w={0}>
+            modelId:
+          </Box>
+          <Box>{getValues('_id')}</Box>
+        </Flex>
         <Flex mt={4} alignItems={'center'}>
           <Box flex={'0 0 80px'} w={0}>
             头像:
@@ -101,27 +107,25 @@ const ModelEditForm = ({
             ></Input>
           </Flex>
         </FormControl>
+
         <Flex alignItems={'center'} mt={5}>
           <Box flex={'0 0 80px'} w={0}>
-            modelId:
+            对话模型:
           </Box>
-          <Box>{getValues('_id')}</Box>
-        </Flex>
-        <Flex alignItems={'center'} mt={5}>
-          <Box flex={'0 0 80px'} w={0}>
-            模型类型:
-          </Box>
-          <Box>{modelList.find((item) => item.model === getValues('service.modelName'))?.name}</Box>
+          <Select isDisabled={!isOwner} {...register('chat.chatModel')}>
+            {chatModelList.map((item) => (
+              <option key={item.chatModel} value={item.chatModel}>
+                {item.name}
+              </option>
+            ))}
+          </Select>
         </Flex>
         <Flex alignItems={'center'} mt={5}>
           <Box flex={'0 0 80px'} w={0}>
             价格:
           </Box>
           <Box>
-            {formatPrice(
-              modelList.find((item) => item.model === getValues('service.modelName'))?.price || 0,
-              1000
-            )}
+            {formatPrice(ChatModelMap[getValues('chat.chatModel')]?.price, 1000)}
             元/1K tokens(包括上下文和回答)
           </Box>
         </Flex>
@@ -163,15 +167,15 @@ const ModelEditForm = ({
               min={0}
               max={10}
               step={1}
-              value={getValues('temperature')}
+              value={getValues('chat.temperature')}
               isDisabled={!isOwner}
               onChange={(e) => {
-                setValue('temperature', e);
+                setValue('chat.temperature', e);
                 setRefresh(!refresh);
               }}
             >
               <SliderMark
-                value={getValues('temperature')}
+                value={getValues('chat.temperature')}
                 textAlign="center"
                 bg="blue.500"
                 color="white"
@@ -181,7 +185,7 @@ const ModelEditForm = ({
                 fontSize={'xs'}
                 transform={'translate(-50%, -200%)'}
               >
-                {getValues('temperature')}
+                {getValues('chat.temperature')}
               </SliderMark>
               <SliderTrack>
                 <SliderFilledTrack />
@@ -190,35 +194,43 @@ const ModelEditForm = ({
             </Slider>
           </Flex>
         </FormControl>
-        {canTrain && (
-          <FormControl mt={4}>
-            <Flex alignItems={'center'}>
-              <Box flex={'0 0 70px'}>搜索模式</Box>
-              <Select
-                isDisabled={!isOwner}
-                {...register('search.mode', { required: '搜索模式不能为空' })}
-              >
-                {Object.entries(ModelVectorSearchModeMap).map(([key, { text }]) => (
-                  <option key={key} value={key}>
-                    {text}
-                  </option>
-                ))}
-              </Select>
-            </Flex>
-          </FormControl>
+        <Flex mt={4} alignItems={'center'}>
+          <Box mr={4}>知识库搜索</Box>
+          <Switch
+            isDisabled={!isOwner}
+            isChecked={getValues('chat.useKb')}
+            onChange={() => {
+              setValue('chat.useKb', !getValues('chat.useKb'));
+              setRefresh(!refresh);
+            }}
+          />
+        </Flex>
+        {getValues('chat.useKb') && (
+          <Flex mt={4} alignItems={'center'}>
+            <Box mr={4} whiteSpace={'nowrap'}>
+              搜索模式&emsp;
+            </Box>
+            <Select
+              isDisabled={!isOwner}
+              {...register('chat.searchMode', { required: '搜索模式不能为空' })}
+            >
+              {Object.entries(ModelVectorSearchModeMap).map(([key, { text }]) => (
+                <option key={key} value={key}>
+                  {text}
+                </option>
+              ))}
+            </Select>
+          </Flex>
         )}
+
         <Box mt={4}>
           <Box mb={1}>系统提示词</Box>
           <Textarea
             rows={8}
             maxLength={-1}
             isDisabled={!isOwner}
-            placeholder={
-              canTrain
-                ? '训练的模型会根据知识库内容，生成一部分系统提示词，因此在对话时需要消耗更多的 tokens。你可以增加提示词，让效果更符合预期。例如: \n1. 请根据知识库内容回答用户问题。\n2. 知识库是电影《铃芽之旅》的内容，根据知识库内容回答。无关问题，拒绝回复！'
-                : '模型默认的 prompt 词，通过调整该内容，可以生成一个限定范围的模型。\n注意，改功能会影响对话的整体朝向！'
-            }
-            {...register('systemPrompt')}
+            placeholder={'模型默认的 prompt 词，通过调整该内容，可以引导模型聊天方向。'}
+            {...register('chat.systemPrompt')}
           />
         </Box>
       </Card>

src/pages/model/detail/components/SelectFileModal.tsx

@@ -20,8 +20,7 @@ import { useMutation } from '@tanstack/react-query';
 import { postModelDataSplitData } from '@/api/model';
 import { formatPrice } from '@/utils/user';
 import Radio from '@/components/Radio';
-import { splitText } from '@/utils/file';
-import { countChatTokens } from '@/utils/tools';
+import { splitText_token } from '@/utils/file';
 
 const fileExtension = '.txt,.doc,.docx,.pdf,.md';
 
@@ -49,7 +48,7 @@ const SelectFileModal = ({
   onSuccess: () => void;
   modelId: string;
 }) => {
-  const [selecting, setSelecting] = useState(false);
+  const [btnLoading, setBtnLoading] = useState(false);
   const { toast } = useToast();
   const [prompt, setPrompt] = useState('');
   const { File, onOpen } = useSelectFile({ fileType: fileExtension, multiple: true });
@@ -62,17 +61,21 @@ const SelectFileModal = ({
   const { openConfirm, ConfirmChild } = useConfirm({
     content: `确认导入该文件，需要一定时间进行拆解，该任务无法终止！如果余额不足，未完成的任务会被直接清除。一共 ${
       splitRes.chunks.length
-    } 组，大约 ${splitRes.tokens || '数量太多,未计算'} 个tokens, 约 ${formatPrice(
-      splitRes.tokens * modeMap[mode].price
-    )} 元`
+    } 组。${
+      splitRes.tokens
+        ? `大约 ${splitRes.tokens} 个tokens, 约 ${formatPrice(
+            splitRes.tokens * modeMap[mode].price
+          )} 元`
+        : ''
+    }`
   });
 
   const onSelectFile = useCallback(
-    async (e: File[]) => {
-      setSelecting(true);
+    async (files: File[]) => {
+      setBtnLoading(true);
       try {
         let promise = Promise.resolve();
-        e.map((file) => {
+        files.forEach((file) => {
           promise = promise.then(async () => {
             const extension = file?.name?.split('.')?.pop()?.toLowerCase();
             let text = '';
@@ -101,7 +104,7 @@ const SelectFileModal = ({
           status: 'error'
         });
       }
-      setSelecting(false);
+      setBtnLoading(false);
     },
     [toast]
   );
@@ -131,46 +134,49 @@ const SelectFileModal = ({
     }
   });
 
-  const onclickImport = useCallback(() => {
-    const chunks = fileTextArr
+  const onclickImport = useCallback(async () => {
+    setBtnLoading(true);
+    let promise = Promise.resolve();
+
+    const splitRes = fileTextArr
       .filter((item) => item)
       .map((item) =>
-        splitText({
+        splitText_token({
           text: item,
           ...modeMap[mode]
         })
-      )
-      .flat();
-
-    let tokens: number[] = [];
-
-    // just count 100 sets of tokens
-    if (chunks.length < 100) {
-      tokens = chunks.map((item) =>
-        countChatTokens({ messages: [{ role: 'system', content: item }] })
       );
-    }
 
     setSplitRes({
-      tokens: tokens.reduce((sum, item) => sum + item, 0),
-      chunks
+      tokens: splitRes.reduce((sum, item) => sum + item.tokens, 0),
+      chunks: splitRes.map((item) => item.chunks).flat()
     });
 
+    setBtnLoading(false);
+
+    await promise;
     openConfirm(mutate)();
   }, [fileTextArr, mode, mutate, openConfirm]);
 
   return (
     <Modal isOpen={true} onClose={onClose} isCentered>
       <ModalOverlay />
-      <ModalContent maxW={'min(1000px, 90vw)'} m={0} position={'relative'} h={'90vh'}>
+      <ModalContent
+        display={'flex'}
+        maxW={'min(1000px, 90vw)'}
+        m={0}
+        position={'relative'}
+        h={'90vh'}
+      >
         <ModalHeader>文件导入</ModalHeader>
         <ModalCloseButton />
 
         <ModalBody
+          flex={1}
+          h={0}
           display={'flex'}
           flexDirection={'column'}
           p={0}
-          h={'100%'}
           alignItems={'center'}
           justifyContent={'center'}
           fontSize={'sm'}
@@ -232,7 +238,7 @@ const SelectFileModal = ({
         </ModalBody>
 
         <Flex px={6} pt={2} pb={4}>
-          <Button isLoading={selecting} onClick={onOpen}>
+          <Button isLoading={btnLoading} onClick={onOpen}>
             选择文件
           </Button>
           <Box flex={1}></Box>
@@ -240,8 +246,8 @@ const SelectFileModal = ({
             取消
           </Button>
           <Button
-            isLoading={isLoading}
-            isDisabled={selecting || fileTextArr[0] === ''}
+            isLoading={isLoading || btnLoading}
+            isDisabled={isLoading || btnLoading || fileTextArr[0] === ''}
             onClick={onclickImport}
           >
             确认导入

src/pages/model/detail/index.tsx

@@ -5,7 +5,7 @@ import type { ModelSchema } from '@/types/mongoSchema';
 import { Card, Box, Flex, Button, Tag, Grid } from '@chakra-ui/react';
 import { useToast } from '@/hooks/useToast';
 import { useForm } from 'react-hook-form';
-import { formatModelStatus, modelList, defaultModel } from '@/constants/model';
+import { formatModelStatus, defaultModel } from '@/constants/model';
 import { useGlobalStore } from '@/store/global';
 import { useScreen } from '@/hooks/useScreen';
 import { useQuery } from '@tanstack/react-query';
@@ -27,11 +27,6 @@ const ModelDetail = ({ modelId }: { modelId: string }) => {
     defaultValues: model
   });
 
-  const canTrain = useMemo(() => {
-    const openai = modelList.find((item) => item.model === model?.service.modelName);
-    return !!(openai && openai.trainName);
-  }, [model]);
-
   const isOwner = useMemo(() => model.userId === userInfo?._id, [model.userId, userInfo?._id]);
 
   /* 加载模型数据 */
@@ -86,11 +81,8 @@ const ModelDetail = ({ modelId }: { modelId: string }) => {
         await putModelById(data._id, {
           name: data.name,
           avatar: data.avatar || '/icon/logo.png',
-          systemPrompt: data.systemPrompt,
-          temperature: data.temperature,
-          search: data.search,
+          chat: data.chat,
           share: data.share,
-          service: data.service,
           security: data.security
         });
         toast({
@@ -171,11 +163,15 @@ const ModelDetail = ({ modelId }: { modelId: string }) => {
               </Tag>
             </Flex>
             <Box mt={4} textAlign={'right'}>
-              <Button variant={'outline'} onClick={handlePreviewChat}>
+              <Button variant={'outline'} size={'sm'} onClick={handlePreviewChat}>
                 对话体验
               </Button>
               {isOwner && (
-                <Button ml={4} onClick={formHooks.handleSubmit(saveSubmitSuccess, saveSubmitError)}>
+                <Button
+                  ml={4}
+                  size={'sm'}
+                  onClick={formHooks.handleSubmit(saveSubmitSuccess, saveSubmitError)}
+                >
                   保存修改
                 </Button>
               )}
@@ -184,16 +180,11 @@ const ModelDetail = ({ modelId }: { modelId: string }) => {
         )}
       </Card>
       <Grid mt={5} gridTemplateColumns={['1fr', '1fr 1fr']} gridGap={5}>
-        <ModelEditForm
-          formHooks={formHooks}
-          handleDelModel={handleDelModel}
-          canTrain={canTrain}
-          isOwner={isOwner}
-        />
+        <ModelEditForm formHooks={formHooks} handleDelModel={handleDelModel} isOwner={isOwner} />
 
-        {canTrain && !!model._id && (
+        {modelId && (
           <Card p={4} gridColumnStart={[1, 1]} gridColumnEnd={[2, 3]}>
-            <ModelDataCard modelId={model._id} isOwner={isOwner} />
+            <ModelDataCard modelId={modelId} isOwner={isOwner} />
           </Card>
         )}
       </Grid>

src/pages/model/list/components/CreateModel.tsx

@@ -1,138 +0,0 @@
-import React, { Dispatch, useState, useCallback, useMemo } from 'react';
-import {
-  Modal,
-  ModalOverlay,
-  ModalContent,
-  ModalHeader,
-  ModalFooter,
-  ModalBody,
-  ModalCloseButton,
-  FormControl,
-  FormErrorMessage,
-  Button,
-  useToast,
-  Input,
-  Select,
-  Box
-} from '@chakra-ui/react';
-import { useForm } from 'react-hook-form';
-import { postCreateModel } from '@/api/model';
-import type { ModelSchema } from '@/types/mongoSchema';
-import { modelList } from '@/constants/model';
-import { formatPrice } from '@/utils/user';
-
-interface CreateFormType {
-  name: string;
-  serviceModelName: string;
-}
-
-const CreateModel = ({
-  setCreateModelOpen,
-  onSuccess
-}: {
-  setCreateModelOpen: Dispatch<boolean>;
-  onSuccess: Dispatch<ModelSchema>;
-}) => {
-  const [requesting, setRequesting] = useState(false);
-  const [refresh, setRefresh] = useState(false);
-  const toast = useToast({
-    duration: 2000,
-    position: 'top'
-  });
-  const {
-    getValues,
-    register,
-    handleSubmit,
-    formState: { errors }
-  } = useForm<CreateFormType>({
-    defaultValues: {
-      serviceModelName: modelList[0].model
-    }
-  });
-
-  const handleCreateModel = useCallback(
-    async (data: CreateFormType) => {
-      setRequesting(true);
-      try {
-        const res = await postCreateModel(data);
-        toast({
-          title: '创建成功',
-          status: 'success'
-        });
-        onSuccess(res);
-        setCreateModelOpen(false);
-      } catch (err: any) {
-        toast({
-          title: typeof err === 'string' ? err : err.message || '出现了意外',
-          status: 'error'
-        });
-      }
-      setRequesting(false);
-    },
-    [onSuccess, setCreateModelOpen, toast]
-  );
-
-  return (
-    <>
-      <Modal isOpen={true} onClose={() => setCreateModelOpen(false)}>
-        <ModalOverlay />
-        <ModalContent>
-          <ModalHeader>创建模型</ModalHeader>
-          <ModalCloseButton />
-
-          <ModalBody>
-            <FormControl mb={8} isInvalid={!!errors.name}>
-              <Input
-                placeholder="模型名称"
-                {...register('name', {
-                  required: '模型名不能为空'
-                })}
-              />
-              <FormErrorMessage position={'absolute'} fontSize="xs">
-                {!!errors.name && errors.name.message}
-              </FormErrorMessage>
-            </FormControl>
-            <FormControl isInvalid={!!errors.serviceModelName}>
-              <Select
-                placeholder="选择基础模型类型"
-                {...register('serviceModelName', {
-                  required: '底层模型不能为空',
-                  onChange() {
-                    setRefresh(!refresh);
-                  }
-                })}
-              >
-                {modelList.map((item) => (
-                  <option key={item.model} value={item.model}>
-                    {item.name}
-                  </option>
-                ))}
-              </Select>
-              <FormErrorMessage position={'absolute'} fontSize="xs">
-                {!!errors.serviceModelName && errors.serviceModelName.message}
-              </FormErrorMessage>
-            </FormControl>
-            <Box mt={3} textAlign={'center'} fontSize={'sm'} color={'blackAlpha.600'}>
-              {formatPrice(
-                modelList.find((item) => item.model === getValues('serviceModelName'))?.price || 0,
-                1000
-              )}
-              元/1K tokens(包括上下文和标点符号)
-            </Box>
-          </ModalBody>
-
-          <ModalFooter>
-            <Button mr={3} colorScheme={'gray'} onClick={() => setCreateModelOpen(false)}>
-              取消
-            </Button>
-            <Button isLoading={requesting} onClick={handleSubmit(handleCreateModel)}>
-              确认创建
-            </Button>
-          </ModalFooter>
-        </ModalContent>
-      </Modal>
-    </>
-  );
-};
-
-export default CreateModel;

src/pages/model/list/components/ModelPhoneList.tsx

@@ -2,8 +2,8 @@ import React, { useEffect } from 'react';
 import { Box, Button, Flex, Tag } from '@chakra-ui/react';
 import type { ModelSchema } from '@/types/mongoSchema';
 import { formatModelStatus } from '@/constants/model';
-import dayjs from 'dayjs';
 import { useRouter } from 'next/router';
+import { ChatModelMap } from '@/constants/model';
 
 const ModelPhoneList = ({
   models,
@@ -42,12 +42,12 @@ const ModelPhoneList = ({
             </Tag>
           </Flex>
           <Flex mt={5}>
-            <Box flex={'0 0 100px'}>最后更新时间: </Box>
-            <Box color={'blackAlpha.500'}>{dayjs(model.updateTime).format('YYYY-MM-DD HH:mm')}</Box>
+            <Box flex={'0 0 100px'}>对话模型: </Box>
+            <Box color={'blackAlpha.500'}>{ChatModelMap[model.chat.chatModel].name}</Box>
           </Flex>
           <Flex mt={5}>
-            <Box flex={'0 0 100px'}>AI模型: </Box>
-            <Box color={'blackAlpha.500'}>{model.service.modelName}</Box>
+            <Box flex={'0 0 100px'}>模型温度: </Box>
+            <Box color={'blackAlpha.500'}>{model.chat.temperature}</Box>
           </Flex>
           <Flex mt={5} justifyContent={'flex-end'}>
             <Button

src/pages/model/list/components/ModelTable.tsx

@@ -13,10 +13,9 @@ import {
   Box
 } from '@chakra-ui/react';
 import { formatModelStatus } from '@/constants/model';
-import dayjs from 'dayjs';
 import type { ModelSchema } from '@/types/mongoSchema';
 import { useRouter } from 'next/router';
-import { modelList } from '@/constants/model';
+import { ChatModelMap } from '@/constants/model';
 
 const ModelTable = ({
   models = [],
@@ -33,18 +32,18 @@ const ModelTable = ({
       dataIndex: 'name'
     },
     {
-      title: '模型类型',
+      title: '对话模型',
       key: 'service',
       render: (model: ModelSchema) => (
         <Box fontWeight={'bold'} whiteSpace={'pre-wrap'} maxW={'200px'}>
-          {modelList.find((item) => item.model === model.service.modelName)?.name}
+          {ChatModelMap[model.chat.chatModel].name}
         </Box>
       )
     },
     {
-      title: '最后更新时间',
-      key: 'updateTime',
-      render: (item: ModelSchema) => dayjs(item.updateTime).format('YYYY-MM-DD HH:mm')
+      title: '温度',
+      key: 'temperature',
+      render: (model: ModelSchema) => <>{model.chat.temperature}</>
     },
     {
       title: '状态',

src/pages/model/list/index.tsx

@@ -1,4 +1,4 @@
-import React, { useState, useCallback } from 'react';
+import React, { useCallback } from 'react';
 import { Box, Button, Flex, Card } from '@chakra-ui/react';
 import type { ModelSchema } from '@/types/mongoSchema';
 import { useRouter } from 'next/router';
@@ -7,30 +7,37 @@ import ModelPhoneList from './components/ModelPhoneList';
 import { useScreen } from '@/hooks/useScreen';
 import { useQuery } from '@tanstack/react-query';
 import { useLoading } from '@/hooks/useLoading';
-import dynamic from 'next/dynamic';
 import { useToast } from '@/hooks/useToast';
 import { useUserStore } from '@/store/user';
-
-const CreateModel = dynamic(() => import('./components/CreateModel'));
+import { postCreateModel } from '@/api/model';
 
 const modelList = () => {
   const { toast } = useToast();
   const { isPc } = useScreen();
   const router = useRouter();
-  const { myModels, setMyModels, getMyModels } = useUserStore();
-  const [openCreateModel, setOpenCreateModel] = useState(false);
+  const { myModels, getMyModels } = useUserStore();
   const { Loading, setIsLoading } = useLoading();
 
   /* 加载模型 */
   const { isLoading } = useQuery(['loadModels'], getMyModels);
 
-  /* 创建成功回调 */
-  const createModelSuccess = useCallback(
-    (data: ModelSchema) => {
-      setMyModels([data, ...myModels]);
-    },
-    [myModels, setMyModels]
-  );
+  const handleCreateModel = useCallback(async () => {
+    setIsLoading(true);
+    try {
+      const id = await postCreateModel({ name: `模型${myModels.length}` });
+      toast({
+        title: '创建成功',
+        status: 'success'
+      });
+      router.push(`/model/detail?modelId=${id}`);
+    } catch (err: any) {
+      toast({
+        title: typeof err === 'string' ? err : err.message || '出现了意外',
+        status: 'error'
+      });
+    }
+    setIsLoading(false);
+  }, [myModels.length, router, setIsLoading, toast]);
 
   /* 点前往聊天预览页 */
   const handlePreviewChat = useCallback(
@@ -61,7 +68,7 @@ const modelList = () => {
             模型列表
           </Box>
 
-          <Button flex={'0 0 145px'} variant={'outline'} onClick={() => setOpenCreateModel(true)}>
+          <Button flex={'0 0 145px'} variant={'outline'} onClick={handleCreateModel}>
             新建模型
           </Button>
         </Flex>
@@ -74,10 +81,6 @@ const modelList = () => {
           <ModelPhoneList models={myModels} handlePreviewChat={handlePreviewChat} />
         )}
       </Box>
-      {/* 创建弹窗 */}
-      {openCreateModel && (
-        <CreateModel setCreateModelOpen={setOpenCreateModel} onSuccess={createModelSuccess} />
-      )}
 
       <Loading loading={isLoading} />
     </Box>

src/pages/model/share/components/list.tsx

@@ -17,7 +17,8 @@ const ShareModelList = ({
   return (
     <>
       {models.map((model) => (
-        <Box
+        <Flex
+          flexDirection={'column'}
           key={model._id}
           p={4}
           border={'1px solid'}
@@ -36,7 +37,7 @@ const ShareModelList = ({
               {model.name}
             </Box>
           </Flex>
-          <Box className={styles.intro} my={4} fontSize={'sm'} color={'blackAlpha.600'}>
+          <Box flex={1} className={styles.intro} my={4} fontSize={'sm'} color={'blackAlpha.600'}>
             {model.share.intro || '这个模型没有介绍~'}
           </Box>
           <Flex justifyContent={'space-between'}>
@@ -74,7 +75,7 @@ const ShareModelList = ({
               )}
             </Box>
           </Flex>
-        </Box>
+        </Flex>
       ))}
     </>
   );

src/pages/model/share/index.tsx

@@ -23,7 +23,7 @@ const modelList = () => {
   });
 
   const { data: collectionModels = [], refetch: refetchCollection } = useQuery(
-    [getCollectionModels],
+    ['getCollectionModels'],
     getCollectionModels
   );
 

src/pages/number/components/PayModal.tsx

@@ -85,25 +85,6 @@ const PayModal = ({ onClose }: { onClose: () => void }) => {
           <ModalBody py={0}>
             {!payId && (
               <>
-                {/* 价格表 */}
-                {/* <TableContainer mb={4}>
-                  <Table>
-                    <Thead>
-                      <Tr>
-                        <Th>模型类型</Th>
-                        <Th>价格(元/1K tokens，包含所有上下文)</Th>
-                      </Tr>
-                    </Thead>
-                    <Tbody>
-                      {modelList.map((item, i) => (
-                        <Tr key={item.model}>
-                          <Td>{item.name}</Td>
-                          <Td>{formatPrice(item.price, 1000)}</Td>
-                        </Tr>
-                      ))}
-                    </Tbody>
-                  </Table>
-                </TableContainer> */}
                 <Grid gridTemplateColumns={'repeat(4,1fr)'} gridGap={5} mb={4}>
                   {[5, 10, 20, 50].map((item) => (
                     <Button

src/pages/openapi/index.tsx

@@ -1,5 +1,4 @@
 import React, { useState } from 'react';
-import Link from 'next/link';
 import {
   Card,
   Box,
@@ -32,7 +31,7 @@ const OpenApi = () => {
     data: apiKeys = [],
     isLoading: isGetting,
     refetch
-  } = useQuery([getOpenApiKeys], getOpenApiKeys);
+  } = useQuery(['getOpenApiKeys'], getOpenApiKeys);
   const [apiKey, setApiKey] = useState('');
   const { copyData } = useCopyData();
 

src/pages/promotion/index.tsx

@@ -47,7 +47,7 @@ const OpenApi = () => {
 
   useQuery(['init'], initUserInfo);
   const { data: { invitedAmount = 0, historyAmount = 0, residueAmount = 0 } = {} } = useQuery(
-    ['getInvitedCountAmount'],
+    ['getPromotionInitData'],
     getPromotionInitData
   );
 

src/service/constants/training.ts

@@ -1,5 +0,0 @@
-export enum OpenAiTuneStatusEnum {
-  cancelled = 'cancelled',
-  succeeded = 'succeeded',
-  pending = 'pending'
-}

src/service/errorCode.ts

@@ -23,7 +23,7 @@ export const openaiError: Record<string, string> = {
   context_length_exceeded: '内容超长了，请重置对话',
   Unauthorized: 'API-KEY 不合法',
   rate_limit_reached: 'API被限制，请稍后再试',
-  'Bad Request': 'Bad Request~ openai 异常',
+  'Bad Request': 'Bad Request~ 可能内容太多了',
   'Bad Gateway': '网关异常，请重试'
 };
 export const openaiError2: Record<string, string> = {

src/service/events/generateQA.ts

@@ -1,18 +1,21 @@
 import { SplitData } from '@/service/mongo';
-import { getOpenAIApi } from '@/service/utils/auth';
-import { axiosConfig } from '@/service/utils/tools';
-import { getOpenApiKey } from '../utils/openai';
-import type { ChatCompletionRequestMessage } from 'openai';
-import { ChatModelEnum } from '@/constants/model';
+import { getApiKey } from '../utils/auth';
+import { OpenAiChatEnum } from '@/constants/model';
 import { pushSplitDataBill } from '@/service/events/pushBill';
 import { generateVector } from './generateVector';
 import { openaiError2 } from '../errorCode';
 import { PgClient } from '@/service/pg';
 import { ModelSplitDataSchema } from '@/types/mongoSchema';
+import { modelServiceToolMap } from '../utils/chat';
+import { ChatRoleEnum } from '@/constants/chat';
 
 export async function generateQA(next = false): Promise<any> {
   if (process.env.queueTask !== '1') {
-    fetch(process.env.parentUrl || '');
+    try {
+      fetch(process.env.parentUrl || '');
+    } catch (error) {
+      console.log('parentUrl fetch error', error);
+    }
     return;
   }
   if (global.generatingQA === true && !next) return;
@@ -42,12 +45,12 @@ export async function generateQA(next = false): Promise<any> {
     const textList: string[] = dataItem.textList.slice(-5);
 
     // 获取 openapi Key
-    let userApiKey = '',
-      systemKey = '';
+    let userOpenAiKey = '',
+      systemAuthKey = '';
     try {
-      const key = await getOpenApiKey(dataItem.userId);
-      userApiKey = key.userApiKey;
-      systemKey = key.systemKey;
+      const key = await getApiKey({ model: OpenAiChatEnum.GPT35, userId: dataItem.userId });
+      userOpenAiKey = key.userOpenAiKey;
+      systemAuthKey = key.systemAuthKey;
     } catch (error: any) {
       if (error?.code === 501) {
         // 余额不够了, 清空该记录
@@ -65,55 +68,44 @@ export async function generateQA(next = false): Promise<any> {
 
     const startTime = Date.now();
 
-    // 获取 openai 请求实例
-    const chatAPI = getOpenAIApi(userApiKey || systemKey);
-    const systemPrompt: ChatCompletionRequestMessage = {
-      role: 'system',
-      content: `你是出题人
+    // 请求 chatgpt 获取回答
+    const response = await Promise.allSettled(
+      textList.map((text) =>
+        modelServiceToolMap[OpenAiChatEnum.GPT35]
+          .chatCompletion({
+            apiKey: userOpenAiKey || systemAuthKey,
+            temperature: 0.8,
+            messages: [
+              {
+                obj: ChatRoleEnum.System,
+                value: `你是出题人
 ${dataItem.prompt || '下面是"一段长文本"'}
-从中选出5至20个题目和答案,题目包含问答题,计算题,代码题等.答案要详细.按格式返回: Q1:
+从中选出5至20个题目和答案.答案详细.按格式返回: Q1:
 A1:
 Q2:
 A2:
 ...`
-    };
-
-    // 请求 chatgpt 获取回答
-    const response = await Promise.allSettled(
-      textList.map((text) =>
-        chatAPI
-          .createChatCompletion(
-            {
-              model: ChatModelEnum.GPT35,
-              temperature: 0.8,
-              n: 1,
-              messages: [
-                systemPrompt,
-                {
-                  role: 'user',
-                  content: text
-                }
-              ]
-            },
-            {
-              timeout: 180000,
-              ...axiosConfig
-            }
-          )
-          .then((res) => {
-            const rawContent = res?.data.choices[0].message?.content || ''; // chatgpt 原本的回复
-            const result = splitText(res?.data.choices[0].message?.content || ''); // 格式化后的QA对
+              },
+              {
+                obj: 'Human',
+                value: text
+              }
+            ],
+            stream: false
+          })
+          .then(({ totalTokens, responseText, responseMessages }) => {
+            const result = formatSplitText(responseText); // 格式化后的QA对
             console.log(`split result length: `, result.length);
             // 计费
             pushSplitDataBill({
-              isPay: !userApiKey && result.length > 0,
+              isPay: !userOpenAiKey && result.length > 0,
               userId: dataItem.userId,
               type: 'QA',
-              text: systemPrompt.content + text + rawContent,
-              tokenLen: res.data.usage?.total_tokens || 0
+              textLen: responseMessages.map((item) => item.value).join('').length,
+              totalTokens
             });
             return {
-              rawContent,
+              rawContent: responseText,
               result
             };
           })
@@ -186,7 +178,7 @@ A2:
 /**
  * 检查文本是否按格式返回
  */
-function splitText(text: string) {
+function formatSplitText(text: string) {
   const regex = /Q\d+:(\s*)(.*)(\s*)A\d+:(\s*)([\s\S]*?)(?=Q|$)/g; // 匹配Q和A的正则表达式
   const matches = text.matchAll(regex); // 获取所有匹配到的结果
 

src/service/events/generateVector.ts

@@ -1,10 +1,15 @@
-import { openaiCreateEmbedding, getOpenApiKey } from '../utils/openai';
+import { openaiCreateEmbedding } from '../utils/chat/openai';
+import { getApiKey } from '../utils/auth';
 import { openaiError2 } from '../errorCode';
 import { PgClient } from '@/service/pg';
 
 export async function generateVector(next = false): Promise<any> {
   if (process.env.queueTask !== '1') {
-    fetch(process.env.parentUrl || '');
+    try {
+      fetch(process.env.parentUrl || '');
+    } catch (error) {
+      console.log('parentUrl fetch error', error);
+    }
     return;
   }
 
@@ -36,11 +41,10 @@ export async function generateVector(next = false): Promise<any> {
     dataId = dataItem.id;
 
     // 获取 openapi Key
-    let userApiKey, systemKey;
+    let userOpenAiKey;
     try {
-      const res = await getOpenApiKey(dataItem.userId);
-      userApiKey = res.userApiKey;
-      systemKey = res.systemKey;
+      const res = await getApiKey({ model: 'gpt-3.5-turbo', userId: dataItem.userId });
+      userOpenAiKey = res.userOpenAiKey;
     } catch (error: any) {
       if (error?.code === 501) {
         await PgClient.delete('modelData', {
@@ -54,17 +58,16 @@ export async function generateVector(next = false): Promise<any> {
     }
 
     // 生成词向量
-    const { vector } = await openaiCreateEmbedding({
-      text: dataItem.q,
+    const { vectors } = await openaiCreateEmbedding({
+      textArr: [dataItem.q],
       userId: dataItem.userId,
-      isPay: !userApiKey,
-      apiKey: userApiKey || systemKey
+      userOpenAiKey
     });
 
     // 更新 pg 向量和状态数据
     await PgClient.update('modelData', {
       values: [
-        { key: 'vector', value: `[${vector}]` },
+        { key: 'vector', value: `[${vectors[0]}]` },
         { key: 'status', value: `ready` }
       ],
       where: [['id', dataId]]

src/service/events/pushBill.ts

@@ -1,68 +1,54 @@
 import { connectToDatabase, Bill, User } from '../mongo';
-import {
-  modelList,
-  ChatModelEnum,
-  ModelNameEnum,
-  Model2ChatModelMap,
-  embeddingModel
-} from '@/constants/model';
+import { ChatModelMap, OpenAiChatEnum, ChatModelType, embeddingModel } from '@/constants/model';
 import { BillTypeEnum } from '@/constants/user';
-import { countChatTokens } from '@/utils/tools';
 
 export const pushChatBill = async ({
   isPay,
-  modelName,
+  chatModel,
   userId,
   chatId,
-  messages
+  textLen,
+  tokens
 }: {
   isPay: boolean;
-  modelName: `${ModelNameEnum}`;
+  chatModel: ChatModelType;
   userId: string;
   chatId?: '' | string;
-  messages: { role: 'system' | 'user' | 'assistant'; content: string }[];
+  textLen: number;
+  tokens: number;
 }) => {
+  console.log(`chat generate success. text len: ${textLen}. token len: ${tokens}. pay:${isPay}`);
+  if (!isPay) return;
+
   let billId = '';
 
   try {
-    // 计算 token 数量
-    const tokens = countChatTokens({ model: Model2ChatModelMap[modelName] as any, messages });
-    const text = messages.map((item) => item.content).join('');
+    await connectToDatabase();
 
-    console.log(
-      `chat generate success. text len: ${text.length}. token len: ${tokens}. pay:${isPay}`
-    );
+    // 计算价格
+    const unitPrice = ChatModelMap[chatModel]?.price || 5;
+    const price = unitPrice * tokens;
 
-    if (isPay) {
-      await connectToDatabase();
+    try {
+      // 插入 Bill 记录
+      const res = await Bill.create({
+        userId,
+        type: 'chat',
+        modelName: chatModel,
+        chatId: chatId ? chatId : undefined,
+        textLen,
+        tokenLen: tokens,
+        price
+      });
+      billId = res._id;
 
-      // 获取模型单价格
-      const modelItem = modelList.find((item) => item.model === modelName);
-      // 计算价格
-      const unitPrice = modelItem?.price || 5;
-      const price = unitPrice * tokens;
-
-      try {
-        // 插入 Bill 记录
-        const res = await Bill.create({
-          userId,
-          type: 'chat',
-          modelName,
-          chatId: chatId ? chatId : undefined,
-          textLen: text.length,
-          tokenLen: tokens,
-          price
-        });
-        billId = res._id;
-
-        // 账号扣费
-        await User.findByIdAndUpdate(userId, {
-          $inc: { balance: -price }
-        });
-      } catch (error) {
-        console.log('创建账单失败:', error);
-        billId && Bill.findByIdAndDelete(billId);
-      }
+      // 账号扣费
+      await User.findByIdAndUpdate(userId, {
+        $inc: { balance: -price }
+      });
+    } catch (error) {
+      console.log('创建账单失败:', error);
+      billId && Bill.findByIdAndDelete(billId);
     }
   } catch (error) {
     console.log(error);
@@ -72,55 +58,49 @@ export const pushChatBill = async ({
 export const pushSplitDataBill = async ({
   isPay,
   userId,
-  tokenLen,
-  text,
+  totalTokens,
+  textLen,
   type
 }: {
   isPay: boolean;
   userId: string;
-  tokenLen: number;
-  text: string;
+  totalTokens: number;
+  textLen: number;
   type: `${BillTypeEnum}`;
 }) => {
-  await connectToDatabase();
+  console.log(
+    `splitData generate success. text len: ${textLen}. token len: ${totalTokens}. pay:${isPay}`
+  );
+  if (!isPay) return;
 
   let billId;
 
   try {
-    console.log(
-      `splitData generate success. text len: ${text.length}. token len: ${tokenLen}. pay:${isPay}`
-    );
+    await connectToDatabase();
 
-    if (isPay) {
-      try {
-        // 获取模型单价格, 都是用 gpt35 拆分
-        const modelItem = modelList.find((item) => item.model === ChatModelEnum.GPT35);
-        const unitPrice = modelItem?.price || 3;
-        // 计算价格
-        const price = unitPrice * tokenLen;
+    // 获取模型单价格, 都是用 gpt35 拆分
+    const unitPrice = ChatModelMap[OpenAiChatEnum.GPT35].price || 3;
+    // 计算价格
+    const price = unitPrice * totalTokens;
 
-        // 插入 Bill 记录
-        const res = await Bill.create({
-          userId,
-          type,
-          modelName: ChatModelEnum.GPT35,
-          textLen: text.length,
-          tokenLen,
-          price
-        });
-        billId = res._id;
+    // 插入 Bill 记录
+    const res = await Bill.create({
+      userId,
+      type,
+      modelName: OpenAiChatEnum.GPT35,
+      textLen,
+      tokenLen: totalTokens,
+      price
+    });
+    billId = res._id;
 
-        // 账号扣费
-        await User.findByIdAndUpdate(userId, {
-          $inc: { balance: -price }
-        });
-      } catch (error) {
-        console.log('创建账单失败:', error);
-        billId && Bill.findByIdAndDelete(billId);
-      }
-    }
+    // 账号扣费
+    await User.findByIdAndUpdate(userId, {
+      $inc: { balance: -price }
+    });
   } catch (error) {
-    console.log(error);
+    console.log('创建账单失败:', error);
+    billId && Bill.findByIdAndDelete(billId);
   }
 };
 
@@ -135,41 +115,40 @@ export const pushGenerateVectorBill = async ({
   text: string;
   tokenLen: number;
 }) => {
-  await connectToDatabase();
+  console.log(
+    `vector generate success. text len: ${text.length}. token len: ${tokenLen}. pay:${isPay}`
+  );
+  if (!isPay) return;
 
   let billId;
 
   try {
-    console.log(
-      `vector generate success. text len: ${text.length}. token len: ${tokenLen}. pay:${isPay}`
-    );
+    await connectToDatabase();
 
-    if (isPay) {
-      try {
-        const unitPrice = 0.4;
-        // 计算价格. 至少为1
-        let price = unitPrice * tokenLen;
-        price = price > 1 ? price : 1;
+    try {
+      const unitPrice = 0.4;
+      // 计算价格. 至少为1
+      let price = unitPrice * tokenLen;
+      price = price > 1 ? price : 1;
 
-        // 插入 Bill 记录
-        const res = await Bill.create({
-          userId,
-          type: BillTypeEnum.vector,
-          modelName: embeddingModel,
-          textLen: text.length,
-          tokenLen,
-          price
-        });
-        billId = res._id;
+      // 插入 Bill 记录
+      const res = await Bill.create({
+        userId,
+        type: BillTypeEnum.vector,
+        modelName: embeddingModel,
+        textLen: text.length,
+        tokenLen,
+        price
+      });
+      billId = res._id;
 
-        // 账号扣费
-        await User.findByIdAndUpdate(userId, {
-          $inc: { balance: -price }
-        });
-      } catch (error) {
-        console.log('创建账单失败:', error);
-        billId && Bill.findByIdAndDelete(billId);
-      }
+      // 账号扣费
+      await User.findByIdAndUpdate(userId, {
+        $inc: { balance: -price }
+      });
+    } catch (error) {
+      console.log('创建账单失败:', error);
+      billId && Bill.findByIdAndDelete(billId);
     }
   } catch (error) {
     console.log(error);

src/service/models/bill.ts

@@ -1,5 +1,5 @@
 import { Schema, model, models, Model } from 'mongoose';
-import { modelList } from '@/constants/model';
+import { ChatModelMap } from '@/constants/model';
 import { BillSchema as BillType } from '@/types/mongoSchema';
 import { BillTypeMap } from '@/constants/user';
 
@@ -16,7 +16,7 @@ const BillSchema = new Schema({
   },
   modelName: {
     type: String,
-    enum: [...modelList.map((item) => item.model), 'text-embedding-ada-002'],
+    enum: [...Object.keys(ChatModelMap), 'text-embedding-ada-002'],
     required: true
   },
   chatId: {

src/service/models/chat.ts

@@ -1,5 +1,6 @@
 import { Schema, model, models, Model } from 'mongoose';
 import { ChatSchema as ChatType } from '@/types/mongoSchema';
+import { ChatRoleMap } from '@/constants/chat';
 
 const ChatSchema = new Schema({
   userId: {
@@ -36,15 +37,15 @@ const ChatSchema = new Schema({
         obj: {
           type: String,
           required: true,
-          enum: ['Human', 'AI', 'SYSTEM']
+          enum: Object.keys(ChatRoleMap)
         },
         value: {
           type: String,
           required: true
         },
-        deleted: {
-          type: Boolean,
-          default: false
+        systemPrompt: {
+          type: String,
+          default: ''
         }
       }
     ],

src/service/models/model.ts

@@ -1,6 +1,11 @@
 import { Schema, model, models, Model as MongoModel } from 'mongoose';
 import { ModelSchema as ModelType } from '@/types/mongoSchema';
-import { ModelVectorSearchModeMap, ModelVectorSearchModeEnum } from '@/constants/model';
+import {
+  ModelVectorSearchModeMap,
+  ModelVectorSearchModeEnum,
+  ChatModelMap,
+  OpenAiChatEnum
+} from '@/constants/model';
 
 const ModelSchema = new Schema({
   userId: {
@@ -13,11 +18,6 @@ const ModelSchema = new Schema({
     required: true
   },
   avatar: {
-    type: String,
-    default: '/icon/logo.png'
-  },
-  systemPrompt: {
-    // 系统提示词
     type: String,
     default: ''
   },
@@ -30,17 +30,34 @@ const ModelSchema = new Schema({
     type: Date,
     default: () => new Date()
   },
-  temperature: {
-    type: Number,
-    min: 0,
-    max: 10,
-    default: 4
-  },
-  search: {
-    mode: {
+  chat: {
+    useKb: {
+      // use knowledge base to search
+      type: Boolean,
+      default: false
+    },
+    searchMode: {
+      // knowledge base search mode
       type: String,
       enum: Object.keys(ModelVectorSearchModeMap),
       default: ModelVectorSearchModeEnum.hightSimilarity
+    },
+    systemPrompt: {
+      // 系统提示词
+      type: String,
+      default: ''
+    },
+    temperature: {
+      type: Number,
+      min: 0,
+      max: 10,
+      default: 0
+    },
+    chatModel: {
+      // 聊天时使用的模型
+      type: String,
+      enum: Object.keys(ChatModelMap),
+      default: OpenAiChatEnum.GPT35
     }
   },
   share: {
@@ -63,18 +80,6 @@ const ModelSchema = new Schema({
       default: 0
     }
   },
-  service: {
-    chatModel: {
-      // 聊天时使用的模型
-      type: String,
-      required: true
-    },
-    modelName: {
-      // 底层模型的名称
-      type: String,
-      required: true
-    }
-  },
   security: {
     type: {
       domain: {
@@ -100,8 +105,7 @@ const ModelSchema = new Schema({
         default: -1
       }
     },
-    default: {},
-    required: true
+    default: {}
   }
 });
 

src/service/plugins/searchKb.ts

@@ -0,0 +1,134 @@
+import { PgClient } from '@/service/pg';
+import { ModelDataStatusEnum, ModelVectorSearchModeEnum, ChatModelMap } from '@/constants/model';
+import { ModelSchema } from '@/types/mongoSchema';
+import { openaiCreateEmbedding } from '../utils/chat/openai';
+import { ChatRoleEnum } from '@/constants/chat';
+import { modelToolMap } from '@/utils/chat';
+import { ChatItemSimpleType } from '@/types/chat';
+
+/**
+ *  use openai embedding search kb
+ */
+export const searchKb = async ({
+  userOpenAiKey,
+  prompts,
+  similarity = 0.2,
+  model,
+  userId
+}: {
+  userOpenAiKey?: string;
+  prompts: ChatItemSimpleType[];
+  model: ModelSchema;
+  userId: string;
+  similarity?: number;
+}): Promise<{
+  code: 200 | 201;
+  searchPrompt?: {
+    obj: `${ChatRoleEnum}`;
+    value: string;
+  };
+}> => {
+  async function search(textArr: string[] = []) {
+    // 获取提示词的向量
+    const { vectors: promptVectors } = await openaiCreateEmbedding({
+      userOpenAiKey,
+      userId,
+      textArr
+    });
+
+    const searchRes = await Promise.all(
+      promptVectors.map((promptVector) =>
+        PgClient.select<{ id: string; q: string; a: string }>('modelData', {
+          fields: ['id', 'q', 'a'],
+          where: [
+            ['status', ModelDataStatusEnum.ready],
+            'AND',
+            ['model_id', model._id],
+            'AND',
+            `vector <=> '[${promptVector}]' < ${similarity}`
+          ],
+          order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
+          limit: 20
+        }).then((res) => res.rows)
+      )
+    );
+
+    // Remove repeat record
+    const idSet = new Set<string>();
+    const filterSearch = searchRes.map((search) =>
+      search.filter((item) => {
+        if (idSet.has(item.id)) {
+          return false;
+        }
+        idSet.add(item.id);
+        return true;
+      })
+    );
+
+    return filterSearch.map((item) => item.map((item) => `${item.q}\n${item.a}`).join('\n'));
+  }
+  const modelConstantsData = ChatModelMap[model.chat.chatModel];
+
+  // search three times
+  const userPrompts = prompts.filter((item) => item.obj === 'Human');
+
+  const searchArr: string[] = [
+    userPrompts[userPrompts.length - 1].value,
+    userPrompts[userPrompts.length - 2]?.value
+  ].filter((item) => item);
+  const systemPrompts = await search(searchArr);
+
+  // filter system prompts.
+  const filterRateMap: Record<number, number[]> = {
+    1: [1],
+    2: [0.7, 0.3]
+  };
+  const filterRate = filterRateMap[systemPrompts.length] || filterRateMap[0];
+
+  const filterSystemPrompt = filterRate
+    .map((rate, i) =>
+      modelToolMap[model.chat.chatModel].sliceText({
+        text: systemPrompts[i],
+        length: Math.floor(modelConstantsData.systemMaxToken * rate)
+      })
+    )
+    .join('\n');
+
+  /* 高相似度+不回复 */
+  if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity) {
+    return {
+      code: 201,
+      searchPrompt: {
+        obj: ChatRoleEnum.AI,
+        value: '对不起，你的问题不在知识库中。'
+      }
+    };
+  }
+  /* 高相似度+无上下文，不添加额外知识,仅用系统提示词 */
+  if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.noContext) {
+    return {
+      code: 200,
+      searchPrompt: model.chat.systemPrompt
+        ? {
+            obj: ChatRoleEnum.System,
+            value: model.chat.systemPrompt
+          }
+        : undefined
+    };
+  }
+
+  /* 有匹配 */
+  return {
+    code: 200,
+    searchPrompt: {
+      obj: ChatRoleEnum.System,
+      value: `
+${model.chat.systemPrompt}
+${
+  model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity ? '不回答知识库外的内容.' : ''
+}
+知识库内容为: '${filterSystemPrompt}'
+`
+    }
+  };
+};

src/service/response.ts

@@ -39,12 +39,7 @@ export const jsonRes = <T = any>(
     } else if (openaiError[error?.response?.statusText]) {
       msg = openaiError[error.response.statusText];
     }
-    console.log(`error-> msg:${msg}`);
-    // request 时候报错
-    if (error?.response) {
-      console.log('statusText:', error?.response?.statusText);
-      console.log('openai error:', error?.response?.data?.error);
-    }
+    console.log(error);
   }
 
   res.json({

src/service/utils/auth.ts

@@ -1,18 +1,84 @@
-import { Configuration, OpenAIApi } from 'openai';
-import { Chat, Model } from '../mongo';
+import type { NextApiRequest } from 'next';
+import jwt from 'jsonwebtoken';
+import { Chat, Model, OpenApi, User } from '../mongo';
 import type { ModelSchema } from '@/types/mongoSchema';
-import { authToken } from './tools';
-import { getOpenApiKey } from './openai';
-import type { ChatItemType } from '@/types/chat';
+import type { ChatItemSimpleType } from '@/types/chat';
 import mongoose from 'mongoose';
+import { ClaudeEnum, defaultModel } from '@/constants/model';
+import { formatPrice } from '@/utils/user';
+import { ERROR_ENUM } from '../errorCode';
+import { ChatModelType, OpenAiChatEnum } from '@/constants/model';
 
-export const getOpenAIApi = (apiKey: string) => {
-  const configuration = new Configuration({
-    apiKey,
-    basePath: process.env.OPENAI_BASE_URL
+/* 校验 token */
+export const authToken = (token?: string): Promise<string> => {
+  return new Promise((resolve, reject) => {
+    if (!token) {
+      reject('缺少登录凭证');
+      return;
+    }
+    const key = process.env.TOKEN_KEY as string;
+
+    jwt.verify(token, key, function (err, decoded: any) {
+      if (err || !decoded?.userId) {
+        reject('凭证无效');
+        return;
+      }
+      resolve(decoded.userId);
+    });
   });
+};
 
-  return new OpenAIApi(configuration);
+/* 获取 api 请求的 key */
+export const getApiKey = async ({ model, userId }: { model: ChatModelType; userId: string }) => {
+  const user = await User.findById(userId);
+  if (!user) {
+    return Promise.reject({
+      code: 501,
+      message: '找不到用户'
+    });
+  }
+
+  const keyMap = {
+    [OpenAiChatEnum.GPT35]: {
+      userOpenAiKey: user.openaiKey || '',
+      systemAuthKey: process.env.OPENAIKEY as string
+    },
+    [OpenAiChatEnum.GPT4]: {
+      userOpenAiKey: user.openaiKey || '',
+      systemAuthKey: process.env.OPENAIKEY as string
+    },
+    [OpenAiChatEnum.GPT432k]: {
+      userOpenAiKey: user.openaiKey || '',
+      systemAuthKey: process.env.OPENAIKEY as string
+    },
+    [ClaudeEnum.Claude]: {
+      userOpenAiKey: '',
+      systemAuthKey: process.env.LAFKEY as string
+    }
+  };
+
+  // 有自己的key
+  if (keyMap[model].userOpenAiKey) {
+    return {
+      user,
+      userOpenAiKey: keyMap[model].userOpenAiKey,
+      systemAuthKey: ''
+    };
+  }
+
+  // 平台账号余额校验
+  if (formatPrice(user.balance) <= 0) {
+    return Promise.reject({
+      code: 501,
+      message: '账号余额不足'
+    });
+  }
+
+  return {
+    user,
+    userOpenAiKey: '',
+    systemAuthKey: keyMap[model].systemAuthKey
+  };
 };
 
 // 模型使用权校验
@@ -20,12 +86,14 @@ export const authModel = async ({
   modelId,
   userId,
   authUser = true,
-  authOwner = true
+  authOwner = true,
+  reserveDetail = false
 }: {
   modelId: string;
   userId: string;
   authUser?: boolean;
   authOwner?: boolean;
+  reserveDetail?: boolean; // focus reserve detail
 }) => {
   // 获取 model 数据
   const model = await Model.findById<ModelSchema>(modelId);
@@ -33,18 +101,24 @@ export const authModel = async ({
     return Promise.reject('模型不存在');
   }
 
-  // 使用权限校验
+  /* 
+    Access verification
+    1. authOwner=true or authUser = true ,  just owner can use
+    2. authUser = false and share, anyone can use
+  */
   if ((authOwner || (authUser && !model.share.isShare)) && userId !== String(model.userId)) {
     return Promise.reject('无权操作该模型');
   }
 
-  // detail 内容去除
-  if (!model.share.isShareDetail) {
-    model.systemPrompt = '';
-    model.temperature = 0;
+  // do not share detail info
+  if (!reserveDetail && !model.share.isShareDetail && userId !== String(model.userId)) {
+    model.chat = {
+      ...defaultModel.chat,
+      chatModel: model.chat.chatModel
+    };
   }
 
-  return { model };
+  return { model, showModelDetail: model.share.isShareDetail || userId === String(model.userId) };
 };
 
 // 获取对话校验
@@ -60,17 +134,28 @@ export const authChat = async ({
   const userId = await authToken(authorization);
 
   // 获取 model 数据
-  const { model } = await authModel({ modelId, userId, authOwner: false });
+  const { model, showModelDetail } = await authModel({
+    modelId,
+    userId,
+    authOwner: false,
+    reserveDetail: true
+  });
 
   // 聊天内容
-  let content: ChatItemType[] = [];
+  let content: ChatItemSimpleType[] = [];
 
   if (chatId) {
     // 获取 chat 数据
     content = await Chat.aggregate([
       { $match: { _id: new mongoose.Types.ObjectId(chatId) } },
+      {
+        $project: {
+          content: {
+            $slice: ['$content', -50] // 返回 content 数组的最后50个元素
+          }
+        }
+      },
       { $unwind: '$content' },
-      { $match: { 'content.deleted': false } },
       {
         $project: {
           obj: '$content.obj',
@@ -79,15 +164,53 @@ export const authChat = async ({
       }
     ]);
   }
-
   // 获取 user 的 apiKey
-  const { userApiKey, systemKey } = await getOpenApiKey(userId);
+  const { userOpenAiKey, systemAuthKey } = await getApiKey({ model: model.chat.chatModel, userId });
 
   return {
-    userApiKey,
-    systemKey,
+    userOpenAiKey,
+    systemAuthKey,
     content,
     userId,
-    model
+    model,
+    showModelDetail
   };
 };
+
+/* 校验 open api key */
+export const authOpenApiKey = async (req: NextApiRequest) => {
+  const { apikey: apiKey } = req.headers;
+
+  if (!apiKey) {
+    return Promise.reject(ERROR_ENUM.unAuthorization);
+  }
+
+  try {
+    const openApi = await OpenApi.findOne({ apiKey });
+    if (!openApi) {
+      return Promise.reject(ERROR_ENUM.unAuthorization);
+    }
+    const userId = String(openApi.userId);
+
+    // 余额校验
+    const user = await User.findById(userId);
+    if (!user) {
+      return Promise.reject(ERROR_ENUM.unAuthorization);
+    }
+    if (formatPrice(user.balance) <= 0) {
+      return Promise.reject(ERROR_ENUM.insufficientQuota);
+    }
+
+    // 更新使用的时间
+    await OpenApi.findByIdAndUpdate(openApi._id, {
+      lastUsedTime: new Date()
+    });
+
+    return {
+      apiKey: process.env.OPENAIKEY as string,
+      userId
+    };
+  } catch (error) {
+    return Promise.reject(error);
+  }
+};

src/service/utils/chat/claude.ts

@@ -0,0 +1,103 @@
+import { modelToolMap } from '@/utils/chat';
+import { ChatCompletionType, StreamResponseType } from './index';
+import { ChatRoleEnum } from '@/constants/chat';
+import axios from 'axios';
+import mongoose from 'mongoose';
+import { NEW_CHATID_HEADER } from '@/constants/chat';
+import { ClaudeEnum } from '@/constants/model';
+
+/* 模型对话 */
+export const lafClaudChat = async ({
+  apiKey,
+  messages,
+  stream,
+  chatId,
+  res
+}: ChatCompletionType) => {
+  const conversationId = chatId || String(new mongoose.Types.ObjectId());
+  // create a new chat
+  !chatId &&
+    messages.filter((item) => item.obj === 'Human').length === 1 &&
+    res?.setHeader(NEW_CHATID_HEADER, conversationId);
+
+  // get system prompt
+  const systemPrompt = messages
+    .filter((item) => item.obj === 'System')
+    .map((item) => item.value)
+    .join('\n');
+  const systemPromptText = systemPrompt ? `\n知识库内容:'${systemPrompt}'\n我的问题:` : '';
+
+  const prompt = systemPromptText + messages[messages.length - 1].value;
+
+  const lafResponse = await axios.post(
+    'https://hnvacz.laf.run/claude-gpt',
+    {
+      prompt,
+      stream,
+      conversationId
+    },
+    {
+      headers: {
+        Authorization: apiKey
+      },
+      timeout: stream ? 40000 : 240000,
+      responseType: stream ? 'stream' : 'json'
+    }
+  );
+
+  let responseText = '';
+  let totalTokens = 0;
+
+  if (!stream) {
+    responseText = lafResponse.data?.text || '';
+  }
+
+  return {
+    streamResponse: lafResponse,
+    responseMessages: messages.concat({ obj: ChatRoleEnum.AI, value: responseText }),
+    responseText,
+    totalTokens
+  };
+};
+
+/* openai stream response */
+export const lafClaudStreamResponse = async ({
+  stream,
+  chatResponse,
+  prompts
+}: StreamResponseType) => {
+  try {
+    let responseContent = '';
+
+    try {
+      const decoder = new TextDecoder();
+      for await (const chunk of chatResponse.data as any) {
+        if (stream.destroyed) {
+          // 流被中断了，直接忽略后面的内容
+          break;
+        }
+        const content = decoder.decode(chunk);
+        responseContent += content;
+        content && stream.push(content.replace(/\n/g, '<br/>'));
+      }
+    } catch (error) {
+      console.log('pipe error', error);
+    }
+    // count tokens
+    const finishMessages = prompts.concat({
+      obj: ChatRoleEnum.AI,
+      value: responseContent
+    });
+    const totalTokens = modelToolMap[ClaudeEnum.Claude].countTokens({
+      messages: finishMessages
+    });
+
+    return {
+      responseContent,
+      totalTokens,
+      finishMessages
+    };
+  } catch (error) {
+    return Promise.reject(error);
+  }
+};

src/service/utils/chat/index.ts

@@ -0,0 +1,177 @@
+import { ChatItemSimpleType } from '@/types/chat';
+import { modelToolMap } from '@/utils/chat';
+import type { ChatModelType } from '@/constants/model';
+import { ChatRoleEnum, SYSTEM_PROMPT_HEADER } from '@/constants/chat';
+import { OpenAiChatEnum, ClaudeEnum } from '@/constants/model';
+import { chatResponse, openAiStreamResponse } from './openai';
+import { lafClaudChat, lafClaudStreamResponse } from './claude';
+import type { NextApiResponse } from 'next';
+import type { PassThrough } from 'stream';
+
+export type ChatCompletionType = {
+  apiKey: string;
+  temperature: number;
+  messages: ChatItemSimpleType[];
+  stream: boolean;
+  [key: string]: any;
+};
+export type ChatCompletionResponseType = {
+  streamResponse: any;
+  responseMessages: ChatItemSimpleType[];
+  responseText: string;
+  totalTokens: number;
+};
+export type StreamResponseType = {
+  stream: PassThrough;
+  chatResponse: any;
+  prompts: ChatItemSimpleType[];
+  res: NextApiResponse;
+  systemPrompt?: string;
+  [key: string]: any;
+};
+export type StreamResponseReturnType = {
+  responseContent: string;
+  totalTokens: number;
+  finishMessages: ChatItemSimpleType[];
+};
+
+export const modelServiceToolMap: Record<
+  ChatModelType,
+  {
+    chatCompletion: (data: ChatCompletionType) => Promise<ChatCompletionResponseType>;
+    streamResponse: (data: StreamResponseType) => Promise<StreamResponseReturnType>;
+  }
+> = {
+  [OpenAiChatEnum.GPT35]: {
+    chatCompletion: (data: ChatCompletionType) =>
+      chatResponse({ model: OpenAiChatEnum.GPT35, ...data }),
+    streamResponse: (data: StreamResponseType) =>
+      openAiStreamResponse({
+        model: OpenAiChatEnum.GPT35,
+        ...data
+      })
+  },
+  [OpenAiChatEnum.GPT4]: {
+    chatCompletion: (data: ChatCompletionType) =>
+      chatResponse({ model: OpenAiChatEnum.GPT4, ...data }),
+    streamResponse: (data: StreamResponseType) =>
+      openAiStreamResponse({
+        model: OpenAiChatEnum.GPT4,
+        ...data
+      })
+  },
+  [OpenAiChatEnum.GPT432k]: {
+    chatCompletion: (data: ChatCompletionType) =>
+      chatResponse({ model: OpenAiChatEnum.GPT432k, ...data }),
+    streamResponse: (data: StreamResponseType) =>
+      openAiStreamResponse({
+        model: OpenAiChatEnum.GPT432k,
+        ...data
+      })
+  },
+  [ClaudeEnum.Claude]: {
+    chatCompletion: lafClaudChat,
+    streamResponse: lafClaudStreamResponse
+  }
+};
+
+/* delete invalid symbol */
+const simplifyStr = (str: string) =>
+  str
+    .replace(/\n+/g, '\n') // 连续空行
+    .replace(/[^\S\r\n]+/g, ' ') // 连续空白内容
+    .trim();
+
+/* 聊天上下文 tokens 截断 */
+export const ChatContextFilter = ({
+  model,
+  prompts,
+  maxTokens
+}: {
+  model: ChatModelType;
+  prompts: ChatItemSimpleType[];
+  maxTokens: number;
+}) => {
+  let rawTextLen = 0;
+  const formatPrompts = prompts.map<ChatItemSimpleType>((item) => {
+    const val = simplifyStr(item.value);
+    rawTextLen += val.length;
+    return {
+      obj: item.obj,
+      value: val
+    };
+  });
+
+  // 长度太小时，不需要进行 token 截断
+  if (formatPrompts.length <= 2 || rawTextLen < maxTokens * 0.5) {
+    return formatPrompts;
+  }
+
+  // 根据 tokens 截断内容
+  const chats: ChatItemSimpleType[] = [];
+  let systemPrompt: ChatItemSimpleType | null = null;
+
+  //  System 词保留
+  if (formatPrompts[0].obj === ChatRoleEnum.System) {
+    const prompt = formatPrompts.shift();
+    if (prompt) {
+      systemPrompt = prompt;
+    }
+  }
+
+  let messages: ChatItemSimpleType[] = [];
+
+  // 从后往前截取对话内容
+  for (let i = formatPrompts.length - 1; i >= 0; i--) {
+    chats.unshift(formatPrompts[i]);
+
+    messages = systemPrompt ? [systemPrompt, ...chats] : chats;
+
+    const tokens = modelToolMap[model].countTokens({
+      messages
+    });
+
+    /* 整体 tokens 超出范围 */
+    if (tokens >= maxTokens) {
+      return systemPrompt ? [systemPrompt, ...chats.slice(1)] : chats.slice(1);
+    }
+  }
+
+  return messages;
+};
+
+/* stream response */
+export const resStreamResponse = async ({
+  model,
+  res,
+  stream,
+  chatResponse,
+  systemPrompt,
+  prompts
+}: StreamResponseType & {
+  model: ChatModelType;
+}) => {
+  // 创建响应流
+  res.setHeader('Content-Type', 'text/event-stream;charset-utf-8');
+  res.setHeader('Access-Control-Allow-Origin', '*');
+  res.setHeader('X-Accel-Buffering', 'no');
+  res.setHeader('Cache-Control', 'no-cache, no-transform');
+  systemPrompt && res.setHeader(SYSTEM_PROMPT_HEADER, encodeURIComponent(systemPrompt));
+  stream.pipe(res);
+
+  const { responseContent, totalTokens, finishMessages } = await modelServiceToolMap[
+    model
+  ].streamResponse({
+    chatResponse,
+    stream,
+    prompts,
+    res,
+    systemPrompt
+  });
+
+  // close stream
+  !stream.destroyed && stream.push(null);
+  stream.destroy();
+
+  return { responseContent, totalTokens, finishMessages };
+};

src/service/utils/chat/openai.ts

@@ -0,0 +1,174 @@
+import { Configuration, OpenAIApi } from 'openai';
+import { createParser, ParsedEvent, ReconnectInterval } from 'eventsource-parser';
+import { axiosConfig } from '../tools';
+import { ChatModelMap, embeddingModel, OpenAiChatEnum } from '@/constants/model';
+import { pushGenerateVectorBill } from '../../events/pushBill';
+import { adaptChatItem_openAI } from '@/utils/chat/openai';
+import { modelToolMap } from '@/utils/chat';
+import { ChatCompletionType, ChatContextFilter, StreamResponseType } from './index';
+import { ChatRoleEnum } from '@/constants/chat';
+
+export const getOpenAIApi = (apiKey: string) => {
+  const configuration = new Configuration({
+    apiKey,
+    basePath: process.env.OPENAI_BASE_URL
+  });
+
+  return new OpenAIApi(configuration);
+};
+
+/* 获取向量 */
+export const openaiCreateEmbedding = async ({
+  userOpenAiKey,
+  userId,
+  textArr
+}: {
+  userOpenAiKey?: string;
+  userId: string;
+  textArr: string[];
+}) => {
+  const systemAuthKey = process.env.OPENAIKEY as string;
+
+  // 获取 chatAPI
+  const chatAPI = getOpenAIApi(userOpenAiKey || systemAuthKey);
+
+  // 把输入的内容转成向量
+  const res = await chatAPI
+    .createEmbedding(
+      {
+        model: embeddingModel,
+        input: textArr
+      },
+      {
+        timeout: 60000,
+        ...axiosConfig()
+      }
+    )
+    .then((res) => ({
+      tokenLen: res.data.usage.total_tokens || 0,
+      vectors: res.data.data.map((item) => item.embedding)
+    }));
+
+  pushGenerateVectorBill({
+    isPay: !userOpenAiKey,
+    userId,
+    text: textArr.join(''),
+    tokenLen: res.tokenLen
+  });
+
+  return {
+    vectors: res.vectors,
+    chatAPI
+  };
+};
+
+/* 模型对话 */
+export const chatResponse = async ({
+  model,
+  apiKey,
+  temperature,
+  messages,
+  stream
+}: ChatCompletionType & { model: `${OpenAiChatEnum}` }) => {
+  const filterMessages = ChatContextFilter({
+    model,
+    prompts: messages,
+    maxTokens: Math.ceil(ChatModelMap[model].contextMaxToken * 0.9)
+  });
+
+  const adaptMessages = adaptChatItem_openAI({ messages: filterMessages });
+  const chatAPI = getOpenAIApi(apiKey);
+
+  const response = await chatAPI.createChatCompletion(
+    {
+      model,
+      temperature: Number(temperature) || 0,
+      messages: adaptMessages,
+      frequency_penalty: 0.5, // 越大，重复内容越少
+      presence_penalty: -0.5, // 越大，越容易出现新内容
+      stream,
+      stop: ['.!?。']
+    },
+    {
+      timeout: stream ? 40000 : 240000,
+      responseType: stream ? 'stream' : 'json',
+      ...axiosConfig()
+    }
+  );
+
+  let responseText = '';
+  let totalTokens = 0;
+
+  // adapt data
+  if (!stream) {
+    responseText = response.data.choices[0].message?.content || '';
+    totalTokens = response.data.usage?.total_tokens || 0;
+  }
+
+  return {
+    streamResponse: response,
+    responseMessages: filterMessages.concat({ obj: 'AI', value: responseText }),
+    responseText,
+    totalTokens
+  };
+};
+
+/* openai stream response */
+export const openAiStreamResponse = async ({
+  model,
+  stream,
+  chatResponse,
+  prompts
+}: StreamResponseType & {
+  model: `${OpenAiChatEnum}`;
+}) => {
+  try {
+    let responseContent = '';
+
+    const onParse = async (event: ParsedEvent | ReconnectInterval) => {
+      if (event.type !== 'event') return;
+      const data = event.data;
+      if (data === '[DONE]') return;
+      try {
+        const json = JSON.parse(data);
+        const content: string = json?.choices?.[0].delta.content || '';
+        responseContent += content;
+
+        !stream.destroyed && content && stream.push(content.replace(/\n/g, '<br/>'));
+      } catch (error) {
+        error;
+      }
+    };
+
+    try {
+      const decoder = new TextDecoder();
+      const parser = createParser(onParse);
+      for await (const chunk of chatResponse.data as any) {
+        if (stream.destroyed) {
+          // 流被中断了，直接忽略后面的内容
+          break;
+        }
+        parser.feed(decoder.decode(chunk, { stream: true }));
+      }
+    } catch (error) {
+      console.log('pipe error', error);
+    }
+
+    // count tokens
+    const finishMessages = prompts.concat({
+      obj: ChatRoleEnum.AI,
+      value: responseContent
+    });
+    const totalTokens = modelToolMap[model].countTokens({
+      messages: finishMessages
+    });
+
+    return {
+      responseContent,
+      totalTokens,
+      finishMessages
+    };
+  } catch (error) {
+    return Promise.reject(error);
+  }
+};

src/service/utils/openai.ts

@@ -1,170 +0,0 @@
-import type { NextApiResponse } from 'next';
-import type { PassThrough } from 'stream';
-import { createParser, ParsedEvent, ReconnectInterval } from 'eventsource-parser';
-import { getOpenAIApi } from '@/service/utils/auth';
-import { axiosConfig } from './tools';
-import { User } from '../models/user';
-import { formatPrice } from '@/utils/user';
-import { embeddingModel } from '@/constants/model';
-import { pushGenerateVectorBill } from '../events/pushBill';
-
-/* 获取用户 api 的 openai 信息 */
-export const getUserApiOpenai = async (userId: string) => {
-  const user = await User.findById(userId);
-
-  const userApiKey = user?.openaiKey;
-
-  if (!userApiKey) {
-    return Promise.reject('缺少ApiKey, 无法请求');
-  }
-
-  return {
-    user,
-    openai: getOpenAIApi(userApiKey),
-    apiKey: userApiKey
-  };
-};
-
-/* 获取 open api key，如果用户没有自己的key，就用平台的，用平台记得加账单 */
-export const getOpenApiKey = async (userId: string) => {
-  const user = await User.findById(userId);
-  if (!user) {
-    return Promise.reject({
-      code: 501,
-      message: '找不到用户'
-    });
-  }
-
-  const userApiKey = user?.openaiKey;
-
-  // 有自己的key
-  if (userApiKey) {
-    return {
-      user,
-      userApiKey,
-      systemKey: ''
-    };
-  }
-
-  // 平台账号余额校验
-  if (formatPrice(user.balance) <= 0) {
-    return Promise.reject({
-      code: 501,
-      message: '账号余额不足'
-    });
-  }
-
-  return {
-    user,
-    userApiKey: '',
-    systemKey: process.env.OPENAIKEY as string
-  };
-};
-
-/* 获取向量 */
-export const openaiCreateEmbedding = async ({
-  isPay,
-  userId,
-  apiKey,
-  text
-}: {
-  isPay: boolean;
-  userId: string;
-  apiKey: string;
-  text: string;
-}) => {
-  // 获取 chatAPI
-  const chatAPI = getOpenAIApi(apiKey);
-
-  // 把输入的内容转成向量
-  const res = await chatAPI
-    .createEmbedding(
-      {
-        model: embeddingModel,
-        input: text
-      },
-      {
-        timeout: 60000,
-        ...axiosConfig
-      }
-    )
-    .then((res) => ({
-      tokenLen: res.data.usage.total_tokens || 0,
-      vector: res?.data?.data?.[0]?.embedding || []
-    }));
-
-  pushGenerateVectorBill({
-    isPay,
-    userId,
-    text,
-    tokenLen: res.tokenLen
-  });
-
-  return {
-    vector: res.vector,
-    chatAPI
-  };
-};
-
-/* gpt35 响应 */
-export const gpt35StreamResponse = ({
-  res,
-  stream,
-  chatResponse
-}: {
-  res: NextApiResponse;
-  stream: PassThrough;
-  chatResponse: any;
-}) =>
-  new Promise<{ responseContent: string }>(async (resolve, reject) => {
-    try {
-      // 创建响应流
-      res.setHeader('Content-Type', 'text/event-stream;charset-utf-8');
-      res.setHeader('Access-Control-Allow-Origin', '*');
-      res.setHeader('X-Accel-Buffering', 'no');
-      res.setHeader('Cache-Control', 'no-cache, no-transform');
-      stream.pipe(res);
-
-      let responseContent = '';
-
-      const onParse = async (event: ParsedEvent | ReconnectInterval) => {
-        if (event.type !== 'event') return;
-        const data = event.data;
-        if (data === '[DONE]') return;
-        try {
-          const json = JSON.parse(data);
-          const content: string = json?.choices?.[0].delta.content || '';
-          responseContent += content;
-
-          if (!stream.destroyed && content) {
-            stream.push(content.replace(/\n/g, '<br/>'));
-          }
-        } catch (error) {
-          error;
-        }
-      };
-
-      const decoder = new TextDecoder();
-      try {
-        const parser = createParser(onParse);
-        for await (const chunk of chatResponse.data as any) {
-          if (stream.destroyed) {
-            // 流被中断了，直接忽略后面的内容
-            break;
-          }
-          parser.feed(decoder.decode(chunk, { stream: true }));
-        }
-      } catch (error) {
-        console.log('pipe error', error);
-      }
-      // close stream
-      !stream.destroyed && stream.push(null);
-      stream.destroy();
-
-      resolve({
-        responseContent
-      });
-    } catch (error) {
-      reject(error);
-    }
-  });

src/service/utils/sendNote.ts

@@ -1,6 +1,5 @@
 import * as nodemailer from 'nodemailer';
 import { UserAuthTypeEnum } from '@/constants/common';
-import dayjs from 'dayjs';
 import Dysmsapi, * as dysmsapi from '@alicloud/dysmsapi20170525';
 // @ts-ignore
 import * as OpenApi from '@alicloud/openapi-client';
@@ -48,25 +47,6 @@ export const sendEmailCode = (email: string, code: string, type: `${UserAuthType
   });
 };
 
-export const sendTrainSucceed = (email: string, modelName: string) => {
-  return new Promise((resolve, reject) => {
-    const options = {
-      from: `"FastGPT" ${myEmail}`,
-      to: email,
-      subject: '模型训练完成通知',
-      html: `你的模型 ${modelName} 已于 ${dayjs().format('YYYY-MM-DD HH:mm')} 训练完成！`
-    };
-    mailTransport.sendMail(options, function (err, msg) {
-      if (err) {
-        console.log('send email  error->', err);
-        reject('邮箱异常');
-      } else {
-        resolve('');
-      }
-    });
-  });
-};
-
 export const sendPhoneCode = async (phone: string, code: string) => {
   const accessKeyId = process.env.aliAccessKeyId;
   const accessKeySecret = process.env.aliAccessKeySecret;

src/service/utils/tools.ts

@@ -1,13 +1,5 @@
-import type { NextApiRequest } from 'next';
 import crypto from 'crypto';
 import jwt from 'jsonwebtoken';
-import { ChatItemType } from '@/types/chat';
-import { OpenApi, User } from '../mongo';
-import { formatPrice } from '@/utils/user';
-import { ERROR_ENUM } from '../errorCode';
-import { countChatTokens } from '@/utils/tools';
-import { ChatCompletionRequestMessageRoleEnum, ChatCompletionRequestMessage } from 'openai';
-import { ChatModelEnum } from '@/constants/model';
 
 /* 密码加密 */
 export const hashPassword = (psw: string) => {
@@ -27,163 +19,10 @@ export const generateToken = (userId: string) => {
   return token;
 };
 
-/* 校验 token */
-export const authToken = (token?: string): Promise<string> => {
-  return new Promise((resolve, reject) => {
-    if (!token) {
-      reject('缺少登录凭证');
-      return;
-    }
-    const key = process.env.TOKEN_KEY as string;
-
-    jwt.verify(token, key, function (err, decoded: any) {
-      if (err || !decoded?.userId) {
-        reject('凭证无效');
-        return;
-      }
-      resolve(decoded.userId);
-    });
-  });
-};
-
-/* 校验 open api key */
-export const authOpenApiKey = async (req: NextApiRequest) => {
-  const { apikey: apiKey } = req.headers;
-
-  if (!apiKey) {
-    return Promise.reject(ERROR_ENUM.unAuthorization);
-  }
-
-  try {
-    const openApi = await OpenApi.findOne({ apiKey });
-    if (!openApi) {
-      return Promise.reject(ERROR_ENUM.unAuthorization);
-    }
-    const userId = String(openApi.userId);
-
-    // 余额校验
-    const user = await User.findById(userId);
-    if (!user) {
-      return Promise.reject(ERROR_ENUM.unAuthorization);
-    }
-    if (formatPrice(user.balance) <= 0) {
-      return Promise.reject('Insufficient account balance');
-    }
-
-    // 更新使用的时间
-    await OpenApi.findByIdAndUpdate(openApi._id, {
-      lastUsedTime: new Date()
-    });
-
-    return {
-      apiKey: process.env.OPENAIKEY as string,
-      userId
-    };
-  } catch (error) {
-    return Promise.reject(error);
-  }
-};
-
 /* openai axios config */
-export const axiosConfig = {
+export const axiosConfig = () => ({
   httpsAgent: global.httpsAgent,
   headers: {
     auth: process.env.OPENAI_BASE_URL_AUTH || ''
   }
-};
-
-/* delete invalid symbol */
-const simplifyStr = (str: string) =>
-  str
-    .replace(/\n+/g, '\n') // 连续空行
-    .replace(/[^\S\r\n]+/g, ' ') // 连续空白内容
-    .trim();
-
-/* 聊天内容 tokens 截断 */
-export const openaiChatFilter = ({
-  model,
-  prompts,
-  maxTokens
-}: {
-  model: `${ChatModelEnum}`;
-  prompts: ChatItemType[];
-  maxTokens: number;
-}) => {
-  // role map
-  const map = {
-    Human: ChatCompletionRequestMessageRoleEnum.User,
-    AI: ChatCompletionRequestMessageRoleEnum.Assistant,
-    SYSTEM: ChatCompletionRequestMessageRoleEnum.System
-  };
-
-  let rawTextLen = 0;
-  const formatPrompts = prompts.map((item) => {
-    const val = simplifyStr(item.value);
-    rawTextLen += val.length;
-    return {
-      role: map[item.obj],
-      content: val
-    };
-  });
-
-  // 长度太小时，不需要进行 token 截断
-  if (rawTextLen < maxTokens * 0.5) {
-    return formatPrompts;
-  }
-
-  // 根据 tokens 截断内容
-  const chats: ChatCompletionRequestMessage[] = [];
-  let systemPrompt: ChatCompletionRequestMessage | null = null;
-
-  //  System 词保留
-  if (formatPrompts[0]?.role === 'system') {
-    systemPrompt = formatPrompts.shift() as ChatCompletionRequestMessage;
-  }
-
-  let messages: { role: ChatCompletionRequestMessageRoleEnum; content: string }[] = [];
-
-  // 从后往前截取对话内容
-  for (let i = formatPrompts.length - 1; i >= 0; i--) {
-    chats.unshift(formatPrompts[i]);
-
-    messages = systemPrompt ? [systemPrompt, ...chats] : chats;
-
-    const tokens = countChatTokens({
-      model,
-      messages
-    });
-
-    /* 整体 tokens 超出范围 */
-    if (tokens >= maxTokens) {
-      break;
-    }
-  }
-
-  return messages;
-};
-
-/* system 内容截断. 相似度从高到低 */
-export const systemPromptFilter = ({
-  model,
-  prompts,
-  maxTokens
-}: {
-  model: 'gpt-4' | 'gpt-4-32k' | 'gpt-3.5-turbo';
-  prompts: string[];
-  maxTokens: number;
-}) => {
-  let splitText = '';
-
-  // 从前往前截取
-  for (let i = 0; i < prompts.length; i++) {
-    const prompt = simplifyStr(prompts[i]);
-
-    splitText += `${prompt}\n`;
-    const tokens = countChatTokens({ model, messages: [{ role: 'system', content: splitText }] });
-    if (tokens >= maxTokens) {
-      break;
-    }
-  }
-
-  return splitText.slice(0, splitText.length - 1);
-};
+});

src/types/chat.d.ts

@@ -1,5 +1,10 @@
-export type ChatItemType = {
-  obj: 'Human' | 'AI' | 'SYSTEM';
+import { ChatRoleEnum } from '@/constants/chat';
+
+export type ChatItemSimpleType = {
+  obj: `${ChatRoleEnum}`;
   value: string;
-  deleted?: boolean;
+  systemPrompt?: string;
 };
+export type ChatItemType = {
+  _id: string;
+} & ChatItemSimpleType;

src/types/model.d.ts

@@ -1,13 +1,11 @@
 import { ModelStatusEnum } from '@/constants/model';
 import type { ModelSchema } from './mongoSchema';
+
 export interface ModelUpdateParams {
   name: string;
   avatar: string;
-  systemPrompt: string;
-  temperature: number;
-  search: ModelSchema['search'];
+  chat: ModelSchema['chat'];
   share: ModelSchema['share'];
-  service: ModelSchema['service'];
   security: ModelSchema['security'];
 }
 

src/types/mongoSchema.d.ts

@@ -3,7 +3,7 @@ import {
   ModelStatusEnum,
   ModelNameEnum,
   ModelVectorSearchModeEnum,
-  ChatModelEnum
+  ChatModelType
 } from '@/constants/model';
 import type { DataType } from './data';
 
@@ -31,15 +31,17 @@ export interface AuthCodeSchema {
 
 export interface ModelSchema {
   _id: string;
+  userId: string;
   name: string;
   avatar: string;
-  systemPrompt: string;
-  userId: string;
   status: `${ModelStatusEnum}`;
   updateTime: number;
-  temperature: number;
-  search: {
-    mode: `${ModelVectorSearchModeEnum}`;
+  chat: {
+    useKb: boolean;
+    searchMode: `${ModelVectorSearchModeEnum}`;
+    systemPrompt: string;
+    temperature: number;
+    chatModel: ChatModelType; // 聊天时用的模型，训练后就是训练的模型
   };
   share: {
     isShare: boolean;
@@ -47,10 +49,6 @@ export interface ModelSchema {
     intro: string;
     collection: number;
   };
-  service: {
-    chatModel: `${ChatModelEnum}`; // 聊天时用的模型，训练后就是训练的模型
-    modelName: `${ModelNameEnum}`; // 底层模型名称，不会变
-  };
   security: {
     domain: string[];
     contextMaxLen: number;

src/utils/chat/claude.ts

@@ -0,0 +1,3 @@
+export const ClaudeSliceTextByToken = ({ text, length }: { text: string; length: number }) => {
+  return text.slice(0, length);
+};

src/utils/chat/index.ts

@@ -0,0 +1,30 @@
+import { ClaudeEnum, OpenAiChatEnum } from '@/constants/model';
+import type { ChatModelType } from '@/constants/model';
+import type { ChatItemSimpleType } from '@/types/chat';
+import { countOpenAIToken, openAiSliceTextByToken } from './openai';
+import { ClaudeSliceTextByToken } from './claude';
+
+export const modelToolMap: Record<
+  ChatModelType,
+  {
+    countTokens: (data: { messages: ChatItemSimpleType[] }) => number;
+    sliceText: (data: { text: string; length: number }) => string;
+  }
+> = {
+  [OpenAiChatEnum.GPT35]: {
+    countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT35, messages }),
+    sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT35, ...data })
+  },
+  [OpenAiChatEnum.GPT4]: {
+    countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT4, messages }),
+    sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT35, ...data })
+  },
+  [OpenAiChatEnum.GPT432k]: {
+    countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT432k, messages }),
+    sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT35, ...data })
+  },
+  [ClaudeEnum.Claude]: {
+    countTokens: () => 0,
+    sliceText: ClaudeSliceTextByToken
+  }
+};

src/utils/chat/openai.ts

@@ -0,0 +1,121 @@
+import { encoding_for_model, type Tiktoken } from '@dqbd/tiktoken';
+import type { ChatItemSimpleType } from '@/types/chat';
+import { ChatRoleEnum } from '@/constants/chat';
+import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
+import { OpenAiChatEnum } from '@/constants/model';
+import Graphemer from 'graphemer';
+
+const textDecoder = new TextDecoder();
+const graphemer = new Graphemer();
+
+export const adaptChatItem_openAI = ({
+  messages
+}: {
+  messages: ChatItemSimpleType[];
+}): ChatCompletionRequestMessage[] => {
+  const map = {
+    [ChatRoleEnum.AI]: ChatCompletionRequestMessageRoleEnum.Assistant,
+    [ChatRoleEnum.Human]: ChatCompletionRequestMessageRoleEnum.User,
+    [ChatRoleEnum.System]: ChatCompletionRequestMessageRoleEnum.System
+  };
+  return messages.map((item) => ({
+    role: map[item.obj] || ChatCompletionRequestMessageRoleEnum.System,
+    content: item.value || ''
+  }));
+};
+
+/* count openai chat token*/
+let OpenAiEncMap: Record<string, Tiktoken>;
+export const getOpenAiEncMap = () => {
+  if (OpenAiEncMap) return OpenAiEncMap;
+  OpenAiEncMap = {
+    'gpt-3.5-turbo': encoding_for_model('gpt-3.5-turbo', {
+      '<|im_start|>': 100264,
+      '<|im_end|>': 100265,
+      '<|im_sep|>': 100266
+    }),
+    'gpt-4': encoding_for_model('gpt-4', {
+      '<|im_start|>': 100264,
+      '<|im_end|>': 100265,
+      '<|im_sep|>': 100266
+    }),
+    'gpt-4-32k': encoding_for_model('gpt-4-32k', {
+      '<|im_start|>': 100264,
+      '<|im_end|>': 100265,
+      '<|im_sep|>': 100266
+    })
+  };
+  return OpenAiEncMap;
+};
+export function countOpenAIToken({
+  messages,
+  model
+}: {
+  messages: ChatItemSimpleType[];
+  model: `${OpenAiChatEnum}`;
+}) {
+  function getChatGPTEncodingText(
+    messages: { role: 'system' | 'user' | 'assistant'; content: string; name?: string }[],
+    model: 'gpt-3.5-turbo' | 'gpt-4' | 'gpt-4-32k'
+  ) {
+    const isGpt3 = model === 'gpt-3.5-turbo';
+
+    const msgSep = isGpt3 ? '\n' : '';
+    const roleSep = isGpt3 ? '\n' : '<|im_sep|>';
+
+    return [
+      messages
+        .map(({ name = '', role, content }) => {
+          return `<|im_start|>${name || role}${roleSep}${content}<|im_end|>`;
+        })
+        .join(msgSep),
+      `<|im_start|>assistant${roleSep}`
+    ].join(msgSep);
+  }
+  function text2TokensLen(encoder: Tiktoken, inputText: string) {
+    const encoding = encoder.encode(inputText, 'all');
+    const segments: { text: string; tokens: { id: number; idx: number }[] }[] = [];
+
+    let byteAcc: number[] = [];
+    let tokenAcc: { id: number; idx: number }[] = [];
+    let inputGraphemes = graphemer.splitGraphemes(inputText);
+
+    for (let idx = 0; idx < encoding.length; idx++) {
+      const token = encoding[idx]!;
+      byteAcc.push(...encoder.decode_single_token_bytes(token));
+      tokenAcc.push({ id: token, idx });
+
+      const segmentText = textDecoder.decode(new Uint8Array(byteAcc));
+      const graphemes = graphemer.splitGraphemes(segmentText);
+
+      if (graphemes.every((item, idx) => inputGraphemes[idx] === item)) {
+        segments.push({ text: segmentText, tokens: tokenAcc });
+
+        byteAcc = [];
+        tokenAcc = [];
+        inputGraphemes = inputGraphemes.slice(graphemes.length);
+      }
+    }
+
+    return segments.reduce((memo, i) => memo + i.tokens.length, 0) ?? 0;
+  }
+
+  const adaptMessages = adaptChatItem_openAI({ messages });
+
+  return text2TokensLen(getOpenAiEncMap()[model], getChatGPTEncodingText(adaptMessages, model));
+}
+
+export const openAiSliceTextByToken = ({
+  model = 'gpt-3.5-turbo',
+  text,
+  length
+}: {
+  model: `${OpenAiChatEnum}`;
+  text: string;
+  length: number;
+}) => {
+  const enc = getOpenAiEncMap()[model];
+  const encodeText = enc.encode(text);
+  const decoder = new TextDecoder();
+  return decoder.decode(enc.decode(encodeText.slice(0, length)));
+};

src/utils/file.ts

@@ -1,6 +1,6 @@
 import mammoth from 'mammoth';
 import Papa from 'papaparse';
-import { countChatTokens } from './tools';
+import { getOpenAiEncMap } from './chat/openai';
 
 /**
  * 读取 txt 文件内容
@@ -145,7 +145,7 @@ export const fileDownload = ({
  * slideLen - The size of the before and after Text
  * maxLen > slideLen
  */
-export const splitText = ({
+export const splitText_token = ({
   text,
   maxLen,
   slideLen
@@ -154,39 +154,32 @@ export const splitText = ({
   maxLen: number;
   slideLen: number;
 }) => {
-  const textArr =
-    text.split(/(?<=[。！？\.!\?\n])/g)?.filter((item) => {
-      const text = item.replace(/(\\n)/g, '\n').trim();
-      if (text && text !== '\n') return true;
-      return false;
-    }) || [];
+  const enc = getOpenAiEncMap()['gpt-3.5-turbo'];
+  // filter empty text. encode sentence
+  const encodeText = enc.encode(text);
 
-  const chunks: { sum: number; arr: string[] }[] = [{ sum: 0, arr: [] }];
+  const chunks: string[] = [];
+  let tokens = 0;
 
-  for (let i = 0; i < textArr.length; i++) {
-    const tokenLen = countChatTokens({ messages: [{ role: 'system', content: textArr[i] }] });
-    chunks[chunks.length - 1].sum += tokenLen;
-    chunks[chunks.length - 1].arr.push(textArr[i]);
+  let startIndex = 0;
+  let endIndex = Math.min(startIndex + maxLen, encodeText.length);
+  let chunkEncodeArr = encodeText.slice(startIndex, endIndex);
 
-    //  current length is over maxLen. create new chunk
-    if (chunks[chunks.length - 1].sum + tokenLen >= maxLen) {
-      // get slide len text as the initial value
-      const chunk: { sum: number; arr: string[] } = { sum: 0, arr: [] };
-      for (let j = chunks[chunks.length - 1].arr.length - 1; j >= 0; j--) {
-        const chunkText = chunks[chunks.length - 1].arr[j];
-        const tokenLen = countChatTokens({ messages: [{ role: 'system', content: chunkText }] });
-        chunk.sum += tokenLen;
-        chunk.arr.unshift(chunkText);
+  const decoder = new TextDecoder();
 
-        if (chunk.sum >= slideLen) {
-          break;
-        }
-      }
-      chunks.push(chunk);
-    }
+  while (startIndex < encodeText.length) {
+    tokens += chunkEncodeArr.length;
+    chunks.push(decoder.decode(enc.decode(chunkEncodeArr)));
+
+    startIndex += maxLen - slideLen;
+    endIndex = Math.min(startIndex + maxLen, encodeText.length);
+    chunkEncodeArr = encodeText.slice(Math.min(encodeText.length - slideLen, startIndex), endIndex);
   }
-  const result = chunks.map((item) => item.arr.join(''));
-  return result;
+
+  return {
+    chunks,
+    tokens
+  };
 };
 
 export const fileToBase64 = (file: File) => {
@@ -197,3 +190,67 @@ export const fileToBase64 = (file: File) => {
     reader.onerror = (error) => reject(error);
   });
 };
+
+/**
+ * compress image. response base64
+ * @param maxSize The max size of the compressed image
+ */
+export const compressImg = ({
+  file,
+  maxW = 200,
+  maxH = 200,
+  maxSize = 1024 * 100
+}: {
+  file: File;
+  maxW?: number;
+  maxH?: number;
+  maxSize?: number;
+}) =>
+  new Promise<string>((resolve, reject) => {
+    const reader = new FileReader();
+    reader.readAsDataURL(file);
+    reader.onload = () => {
+      const img = new Image();
+      // @ts-ignore
+      img.src = reader.result;
+      img.onload = () => {
+        let width = img.width;
+        let height = img.height;
+
+        if (width > height) {
+          if (width > maxW) {
+            height *= maxW / width;
+            width = maxW;
+          }
+        } else {
+          if (height > maxH) {
+            width *= maxH / height;
+            height = maxH;
+          }
+        }
+
+        const canvas = document.createElement('canvas');
+        canvas.width = width;
+        canvas.height = height;
+        const ctx = canvas.getContext('2d');
+
+        if (!ctx) {
+          return reject('压缩图片异常');
+        }
+
+        ctx.drawImage(img, 0, 0, width, height);
+        const compressedDataUrl = canvas.toDataURL(file.type, 1);
+        // 移除 canvas 元素
+        canvas.remove();
+
+        if (compressedDataUrl.length > maxSize) {
+          return reject('图片太大了');
+        }
+        resolve(compressedDataUrl);
+      };
+    };
+    reader.onerror = (err) => {
+      console.log(err);
+      reject('压缩图片异常');
+    };
+  });